Open Access
ISSN:1546-2218(print)
ISSN:1546-2226(online)
Publication Frequency:Monthly
Computers, Materials & Continua is a peer-reviewed Open Access journal that publishes all types of academic papers in the areas of computer networks, artificial intelligence, big data, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, and data analysis, modeling, designing and manufacturing of modern functional and multifunctional materials. This journal is published monthly by Tech Science Press.
SCI: 2021 Impact Factor 3.860; Scopus CiteScore (Impact per Publication 2021): 4.9; SNIP (Source Normalized Impact per Paper 2021): 1.277; Ei Compendex; Cambridge Scientific Abstracts; INSPEC Databases; Science Navigator; EBSCOhost; ProQuest Central; Zentralblatt für Mathematik; Portico, etc.
Refers to the articles published on the journal within the last three years that have gained the most viewing times to date (Statistics provided by TSP database)
Refers to articles published on the journal since 2020 that have received the most frequent citation to date (Statistics provided by TSP database)
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.034748
Abstract Robust watermarking requires finding invariant features under multiple attacks to ensure correct extraction. Deep learning has extremely powerful in extracting features, and watermarking algorithms based on deep learning have attracted widespread attention. Most existing methods use small kernel convolution to extract image features and embed the watermarking. However, the effective perception fields for small kernel convolution are extremely confined, so the pixels that each watermarking can affect are restricted, thus limiting the performance of the watermarking. To address these problems, we propose a watermarking network based on large kernel convolution and adaptive weight assignment for loss functions. It uses large-kernel… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 19-34, 2023, DOI:10.32604/cmc.2023.033753
Abstract There are several ethical issues that have arisen in recent years due to the ubiquity of the Internet and the popularity of social media and community platforms. Among them is cyberbullying, which is defined as any violent intentional action that is repeatedly conducted by individuals or groups using online channels against victims who are not able to react effectively. An alarmingly high percentage of people, especially teenagers, have reported being cyberbullied in recent years. A variety of approaches have been developed to detect cyberbullying, but they require time-consuming feature extraction and selection processes. Moreover, no approach to date has examined… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 35-49, 2023, DOI:10.32604/cmc.2023.036189
Abstract Public cloud computing provides a variety of services to consumers via high-speed internet. The consumer can access these services anytime and anywhere on a balanced service cost. Many traditional authentication protocols are proposed to secure public cloud computing. However, the rapid development of high-speed internet and organizations’ race to develop quantum computers is a nightmare for existing authentication schemes. These traditional authentication protocols are based on factorization or discrete logarithm problems. As a result, traditional authentication protocols are vulnerable in the quantum computing era. Therefore, in this article, we have proposed an authentication protocol based on the lattice technique for… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 51-65, 2023, DOI:10.32604/cmc.2023.035282
Abstract Observability and traceability of developed software are crucial to its success in software engineering. Observability is the ability to comprehend a system’s internal state from the outside. Monitoring is used to determine what causes system problems and why. Logs are among the most critical technology to guarantee observability and traceability. Logs are frequently used to investigate software events. In current log technologies, software events are processed independently of each other. Consequently, current logging technologies do not reveal relationships. However, system events do not occur independently of one another. With this perspective, our research has produced a new log design pattern… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 67-80, 2023, DOI:10.32604/cmc.2023.035337
Abstract Wireless network is the basis of the Internet of things and the intelligent vehicle Internet. Due to the complexity of the Internet of things and intelligent vehicle Internet environment, the nodes of the Internet of things and the intelligent vehicle Internet are more vulnerable to malicious destruction and attacks. Most of the proposed authentication and key agreement protocols for wireless networks are based on traditional cryptosystems such as large integer decomposition and elliptic curves. With the rapid development of quantum computing, these authentication protocols based on traditional cryptography will be more and more threatened, so it is necessary to design… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 81-97, 2023, DOI:10.32604/cmc.2023.033406
Abstract The outbreak of the pandemic, caused by Coronavirus Disease 2019 (COVID-19), has affected the daily activities of people across the globe. During COVID-19 outbreak and the successive lockdowns, Twitter was heavily used and the number of tweets regarding COVID-19 increased tremendously. Several studies used Sentiment Analysis (SA) to analyze the emotions expressed through tweets upon COVID-19. Therefore, in current study, a new Artificial Bee Colony (ABC) with Machine Learning-driven SA (ABCML-SA) model is developed for conducting Sentiment Analysis of COVID-19 Twitter data. The prime focus of the presented ABCML-SA model is to recognize the sentiments expressed in tweets made upon… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 99-115, 2023, DOI:10.32604/cmc.2023.034752
Abstract The Internet of Things (IoT) paradigm enables end users to access networking services amongst diverse kinds of electronic devices. IoT security mechanism is a technology that concentrates on safeguarding the devices and networks connected in the IoT environment. In recent years, False Data Injection Attacks (FDIAs) have gained considerable interest in the IoT environment. Cybercriminals compromise the devices connected to the network and inject the data. Such attacks on the IoT environment can result in a considerable loss and interrupt normal activities among the IoT network devices. The FDI attacks have been effectively overcome so far by conventional threat detection… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 117-131, 2023, DOI:10.32604/cmc.2023.033327
Abstract Fast recognition of elevator buttons is a key step for service robots to ride elevators automatically. Although there are some studies in this field, none of them can achieve real-time application due to problems such as recognition speed and algorithm complexity. Elevator button recognition is a comprehensive problem. Not only does it need to detect the position of multiple buttons at the same time, but also needs to accurately identify the characters on each button. The latest version 5 of you only look once algorithm (YOLOv5) has the fastest reasoning speed and can be used for detecting multiple objects in… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 133-148, 2023, DOI:10.32604/cmc.2023.031786
Abstract Osteosarcoma is one of the rare bone cancers that affect the individuals aged between 10 and 30 and it incurs high death rate. Early diagnosis of osteosarcoma is essential to improve the survivability rate and treatment protocols. Traditional physical examination procedure is not only a time-consuming process, but it also primarily relies upon the expert’s knowledge. In this background, the recently developed Deep Learning (DL) models can be applied to perform decision making. At the same time, hyperparameter optimization of DL models also plays an important role in influencing overall classification performance. The current study introduces a novel Symbiotic Organisms… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 149-164, 2023, DOI:10.32604/cmc.2023.033005
Abstract Melanoma is a skin disease with high mortality rate while early diagnoses of the disease can increase the survival chances of patients. It is challenging to automatically diagnose melanoma from dermoscopic skin samples. Computer-Aided Diagnostic (CAD) tool saves time and effort in diagnosing melanoma compared to existing medical approaches. In this background, there is a need exists to design an automated classification model for melanoma that can utilize deep and rich feature datasets of an image for disease classification. The current study develops an Intelligent Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification (IAOEDTT-MC) model. The proposed IAOEDTT-MC… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 165-182, 2023, DOI:10.32604/cmc.2023.034605
Abstract Human biometric analysis has gotten much attention due to its widespread use in different research areas, such as security, surveillance, health, human identification, and classification. Human gait is one of the key human traits that can identify and classify humans based on their age, gender, and ethnicity. Different approaches have been proposed for the estimation of human age based on gait so far. However, challenges are there, for which an efficient, low-cost technique or algorithm is needed. In this paper, we propose a three-dimensional real-time gait-based age detection system using a machine learning approach. The proposed system consists of training… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 183-196, 2023, DOI:10.32604/cmc.2023.034048
Abstract In recent years, Digital Twin (DT) has gained significant interest from academia and industry due to the advanced in information technology, communication systems, Artificial Intelligence (AI), Cloud Computing (CC), and Industrial Internet of Things (IIoT). The main concept of the DT is to provide a comprehensive tangible, and operational explanation of any element, asset, or system. However, it is an extremely dynamic taxonomy developing in complexity during the life cycle that produces a massive amount of engendered data and information. Likewise, with the development of AI, digital twins can be redefined and could be a crucial approach to aid the… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 197-217, 2023, DOI:10.32604/cmc.2023.036365
Abstract With the rapid development of the internet of things (IoT), electricity consumption data can be captured and recorded in the IoT cloud center. This provides a credible data source for enterprise credit scoring, which is one of the most vital elements during the financial decision-making process. Accordingly, this paper proposes to use deep learning to train an enterprise credit scoring model by inputting the electricity consumption data. Instead of predicting the credit rating, our method can generate an absolute credit score by a novel deep ranking model–ranking extreme gradient boosting net (rankXGB). To boost the performance, the rankXGB model combines… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 219-242, 2023, DOI:10.32604/cmc.2023.033331
Abstract Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection. It is also a popular biometric authentication technology in forensic and commercial transactions due to its various advantages, including noninvasiveness, user-friendliness, and social and legal acceptability. According to the literature, extensive research has been conducted on signature verification systems in a variety of languages, including English, Hindi, Bangla, and Chinese. However, the Arabic Offline Signature Verification (OSV) system is still a challenging issue that has not been investigated as much by researchers due to the Arabic script being distinguished by changing letter shapes,… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 243-258, 2023, DOI:10.32604/cmc.2023.035716
Abstract The exponential increase in data over the past few years, particularly in images, has led to more complex content since visual representation became the new norm. E-commerce and similar platforms maintain large image catalogues of their products. In image databases, searching and retrieving similar images is still a challenge, even though several image retrieval techniques have been proposed over the decade. Most of these techniques work well when querying general image databases. However, they often fail in domain-specific image databases, especially for datasets with low intraclass variance. This paper proposes a domain-specific image similarity search engine based on a fused… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 259-276, 2023, DOI:10.32604/cmc.2023.034622
Abstract In this paper, the axial-flux permanent magnet driver is modeled and analyzed in a simple and novel way under three-dimensional cylindrical coordinates. The inherent three-dimensional characteristics of the device are comprehensively considered, and the governing equations are solved by simplifying the boundary conditions. The axial magnetization of the sector-shaped permanent magnets is accurately described in an algebraic form by the parameters, which makes the physical meaning more explicit than the purely mathematical expression in general series forms. The parameters of the Bessel function are determined simply and the magnetic field distribution of permanent magnets and the air-gap is solved. Furthermore,… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 277-292, 2023, DOI:10.32604/cmc.2023.032840
Abstract Metamaterials (MTM) can enhance the properties of microwaves and also exceed some limitations of devices used in technical practice. Note that the antenna is the element for realizing a microwave imaging (MWI) system since it is where signal transmission and absorption occur. Ultra-Wideband (UWB) antenna superstrates with MTM elements to ensure the signal transmitted from the antenna reaches the tumor and is absorbed by the same antenna. The lack of conventional head imaging techniques, for instance, Magnetic Resonance Imaging (MRI) and Computerized Tomography (CT)-scan, has been demonstrated in the paper focusing on the point of failure of these techniques for… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 293-309, 2023, DOI:10.32604/cmc.2023.036438
Abstract Medical images are used as a diagnostic tool, so protecting their confidentiality has long been a topic of study. From this, we propose a Resnet50-DCT-based zero watermarking algorithm for use with medical images. To begin, we use Resnet50, a pre-training network, to draw out the deep features of medical images. Then the deep features are transformed by DCT transform and the perceptual hash function is used to generate the feature vector. The original watermark is chaotic scrambled to get the encrypted watermark, and the watermark information is embedded into the original medical image by XOR operation, and the logical key… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 311-329, 2023, DOI:10.32604/cmc.2023.035960
Abstract The development of the Next-Generation Wireless Network
(NGWN) is becoming a reality. To conduct specialized processes more, rapid
network deployment has become essential. Methodologies like Network
Function Virtualization (NFV), Software-Defined Networks (SDN), and
cloud computing will be crucial in addressing various challenges that 5G
networks will face, particularly adaptability, scalability, and reliability. The
motivation behind this work is to confirm the function of virtualization
and the capabilities offered by various virtualization platforms, including
hypervisors, clouds, and containers, which will serve as a guide to dealing
with the stimulating environment of 5G. This is particularly crucial when
implementing network operations at… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 331-350, 2023, DOI:10.32604/cmc.2023.035087
Abstract Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, including different translations, scales, and orientations, can be performed using these parametric curves. For this, Bézier and B-spline curves can be generated using a point set that belongs to the outer boundary of the object. The resulting object shape can be used in computer vision fields, such as searching and segmentation methods and training machine learning algorithms. The prerequisite for reconstructing the shape with parametric curves… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 351-371, 2023, DOI:10.32604/cmc.2023.035720
Abstract Federated learning is an emerging machine learning technique that enables clients to collaboratively train a deep learning model without uploading raw data to the aggregation server. Each client may be equipped with different computing resources for model training. The client equipped with a lower computing capability requires more time for model training, resulting in a prolonged training time in federated learning. Moreover, it may fail to train the entire model because of the out-of-memory issue. This study aims to tackle these problems and propose the federated feature concatenate (FedFC) method for federated learning considering heterogeneous clients. FedFC leverages the model… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 373-391, 2023, DOI:10.32604/cmc.2023.034770
Abstract In edge computing, a reasonable edge resource bidding mechanism can enable edge providers and users to obtain benefits in a relatively fair fashion. To maximize such benefits, this paper proposes a dynamic multi-attribute resource bidding mechanism (DMRBM). Most of the previous work mainly relies on a third-party agent to exchange information to gain optimal benefits. It is worth noting that when edge providers and users trade with third-party agents which are not entirely reliable and trustworthy, their sensitive information is prone to be leaked. Moreover, the privacy protection of edge providers and users must be considered in the dynamic pricing/transaction… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 393-407, 2023, DOI:10.32604/cmc.2023.033536
Abstract Watermarking of digital images is required in diversified applications ranging from medical imaging to commercial images used over the web.
Usually, the copyright information is embossed over the image in the form of
a logo at the corner or diagonal text in the background. However, this form
of visible watermarking is not suitable for a large class of applications. In all
such cases, a hidden watermark is embedded inside the original image as proof
of ownership. A large number of techniques and algorithms are proposed
by researchers for invisible watermarking. In this paper, we focus on issues
that are critical… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432
Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique. The presented AOTL-WBCC model executes… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 427-442, 2023, DOI:10.32604/cmc.2023.032885
Abstract Traffic prediction of wireless networks attracted many researchers and practitioners during the past decades. However, wireless traffic frequently exhibits strong nonlinearities and complicated patterns, which makes it challenging to be predicted accurately. Many of the existing approaches for predicting wireless network traffic are unable to produce accurate predictions because they lack the ability to describe the dynamic spatial-temporal correlations of wireless network traffic data. In this paper, we proposed a novel meta-heuristic optimization approach based on fitness grey wolf and dipper throated optimization algorithms for boosting the prediction accuracy of traffic volume. The proposed algorithm is employed to optimize the… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 443-459, 2023, DOI:10.32604/cmc.2023.035275
Abstract The Internet of Things (IoT) technology has been developed for directing and maintaining the atmosphere in smart buildings in real time. In order to optimise the power generation sector and schedule routine maintenance, it is crucial to predict future energy demand. Electricity demand forecasting is difficult because of the complexity of the available demand patterns. Establishing a perfect prediction of energy consumption at the building’s level is vital and significant to efficiently managing the consumed energy by utilising a strong predictive model. Low forecast accuracy is just one of the reasons why energy consumption and prediction models have failed to… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 461-475, 2023, DOI:10.32604/cmc.2023.035672
Abstract The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 477-491, 2023, DOI:10.32604/cmc.2023.034933
Abstract Rule-based portfolio construction strategies are rising as investment demand grows, and smart beta strategies are becoming a trend among institutional investors. Smart beta strategies have high transparency, low management costs, and better long-term performance, but are at the risk of severe short-term declines due to a lack of Risk Control tools. Although there are some methods to use historical volatility for Risk Control, it is still difficult to adapt to the rapid switch of market styles. How to strengthen the Risk Control management of the portfolio while maintaining the original advantages of smart beta has become a new issue of… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 493-512, 2023, DOI:10.32604/cmc.2023.035974
Abstract In this paper, a deep learning-based method is proposed for crowd-counting problems. Specifically, by utilizing the convolution kernel density map, the ground truth is generated dynamically to enhance the feature-extracting ability of the generator model. Meanwhile, the “cross stage partial” module is integrated into congested scene recognition network (CSRNet) to obtain a lightweight network model. In addition, to compensate for the accuracy drop owing to the lightweight model, we take advantage of “structured knowledge transfer” to train the model in an end-to-end manner. It aims to accelerate the fitting speed and enhance the learning ability of the student model. The… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 513-529, 2023, DOI:10.32604/cmc.2023.035139
Abstract Virtual Machines are the core of cloud computing and are utilized to get the benefits of cloud computing. Other essential features include portability, recovery after failure, and, most importantly, creating the core mechanism for load balancing. Several study results have been reported in enhancing load-balancing systems employing stochastic or biogenetic optimization methods. It examines the underlying issues with load balancing and the limitations of present load balance genetic optimization approaches. They are criticized for using higher-order probability distributions, more complicated solution search spaces, and adding factors to improve decision-making skills. Thus, this paper explores the possibility of summarizing load characteristics.… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 531-546, 2023, DOI:10.32604/cmc.2023.034329
Abstract The number of mobile devices accessing wireless networks is skyrocketing due to the rapid advancement of sensors and wireless communication technology. In the upcoming years, it is anticipated that mobile data traffic would rise even more. The development of a new cellular network paradigm is being driven by the Internet of Things, smart homes, and more sophisticated applications with greater data rates and latency requirements. Resources are being used up quickly due to the steady growth of smartphone devices and multimedia apps. Computation offloading to either several distant clouds or close mobile devices has consistently improved the performance of mobile… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 547-564, 2023, DOI:10.32604/cmc.2023.036025
Abstract Imbalanced data classification is one of the major problems in machine learning. This imbalanced dataset typically has significant differences in the number of data samples between its classes. In most cases, the performance of the machine learning algorithm such as Support Vector Machine (SVM) is affected when dealing with an imbalanced dataset. The classification accuracy is mostly skewed toward the majority class and poor results are exhibited in the prediction of minority-class samples. In this paper, a hybrid approach combining data pre-processing technique and SVM algorithm based on improved Simulated Annealing (SA) was proposed. Firstly, the data pre-processing technique which… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 565-586, 2023, DOI:10.32604/cmc.2023.036317
Abstract The field of medical images has been rapidly evolving since the advent of the digital medical information era. However, medical data is susceptible to leaks and hacks during transmission. This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage, as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms. First, a pre-trained GoogLeNet network is used in this paper, based on which the parameters of several previous layers of the network are fixed and the… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 587-607, 2023, DOI:10.32604/cmc.2023.034773
Abstract Mobile ad hoc networks (MANETs) are subjected to attack detection for transmitting and creating new messages or existing message modifications. The attacker on another node evaluates the forging activity in the message directly or indirectly. Every node sends short packets in a MANET environment with its identifier, location on the map, and time through beacons. The attackers on the network broadcast the warning message using faked coordinates, providing the appearance of a network collision. Similarly, MANET degrades the channel utilization performance. Performance highly affects network performance through security algorithms. This paper developed a trust management technique called Enhanced Beacon Trust… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 609-631, 2023, DOI:10.32604/cmc.2023.035177
Abstract The traditional multi-access edge computing (MEC) capacity is overwhelmed by the increasing demand for vehicles, leading to acute degradation in task offloading performance. There is a tremendous number of resource-rich and idle mobile connected vehicles (CVs) in the traffic network, and vehicles are created as opportunistic ad-hoc edge clouds to alleviate the resource limitation of MEC by providing opportunistic computing services. On this basis, a novel scalable system framework is proposed in this paper for computation task offloading in opportunistic CV-assisted MEC. In this framework, opportunistic ad-hoc edge cloud and fixed edge cloud cooperate to form a novel hybrid cloud.… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 633-649, 2023, DOI:10.32604/cmc.2023.035414
Abstract In the smart city paradigm, the deployment of Internet of Things (IoT) services and solutions requires extensive communication and computing resources to place and process IoT applications in real time, which consumes a lot of energy and increases operational costs. Usually, IoT applications are placed in the cloud to provide high-quality services and scalable resources. However, the existing cloud-based approach should consider the above constraints to efficiently place and process IoT applications. In this paper, an efficient optimization approach for placing IoT applications in a multi-layer fog-cloud environment is proposed using a mathematical model (Mixed-Integer Linear Programming (MILP)). This approach… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 651-667, 2023, DOI:10.32604/cmc.2023.035173
Abstract Internet of Things (IoT) devices incorporate a large amount of data in several fields, including those of medicine, business, and engineering. User authentication is paramount in the IoT era to assure connected devices’ security. However, traditional authentication methods and conventional biometrics-based authentication approaches such as face recognition, fingerprints, and password are vulnerable to various attacks, including smudge attacks, heat attacks, and shoulder surfing attacks. Behavioral biometrics is introduced by the powerful sensing capabilities of IoT devices such as smart wearables and smartphones, enabling continuous authentication. Artificial Intelligence (AI)-based approaches introduce a bright future in refining large amounts of homogeneous biometric… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 669-681, 2023, DOI:10.32604/cmc.2022.033939
Abstract This paper presents a compact Multiple Input Multiple Output
(MIMO) antenna with WLAN band notch for Ultra-Wideband (UWB)
applications. The antenna is designed on 0.8 mm thick low-cost FR-4 substrate
having a compact size of 22 mm × 30 mm. The proposed antenna comprises
of two monopole patches on the top layer of substrate while having a shared
ground on its bottom layer. The mutual coupling between adjacent patches
has been reduced by using a novel stub with shared ground structure. The stub
consists of complementary rectangular slots that disturb the surface current
direction and thus result in reducing mutual… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 683-696, 2023, DOI:10.32604/cmc.2023.033370
Abstract Recently, semantic segmentation has been widely applied to image processing, scene understanding, and many others. Especially, in deep learning-based semantic segmentation, the U-Net with convolutional encoder-decoder architecture is a representative model which is proposed for image segmentation in the biomedical field. It used max pooling operation for reducing the size of image and making noise robust. However, instead of reducing the complexity of the model, max pooling has the disadvantage of omitting some information about the image in reducing it. So, this paper used two diagonal elements of down-sampling operation instead of it. We think that the down-sampling feature maps… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 697-714, 2023, DOI:10.32604/cmc.2023.035183
Abstract Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 715-740, 2023, DOI:10.32604/cmc.2023.034963
Abstract Rapid development of deepfake technology led to the spread of forged audios and videos across network platforms, presenting risks for numerous countries, societies, and individuals, and posing a serious threat to cyberspace security. To address the problem of insufficient extraction of spatial features and the fact that temporal features are not considered in the deepfake video detection, we propose a detection method based on improved CapsNet and temporal–spatial features (iCapsNet–TSF). First, the dynamic routing algorithm of CapsNet is improved using weight initialization and updating. Then, the optical flow algorithm is used to extract interframe temporal features of the videos to… More >
Open Access
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CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 741-760, 2023, DOI:10.32604/cmc.2023.036077
Abstract Electrical trees are an aging mechanism most associated with partial discharge (PD) activities in crosslinked polyethylene (XLPE) insulation of high-voltage (HV) cables. Characterization of electrical tree structures gained considerable attention from researchers since a deep understanding of the tree morphology is required to develop new insulation material. Two-dimensional (2D) optical microscopy is primarily used to examine tree structures and propagation shapes with image segmentation methods. However, since electrical trees can emerge in different shapes such as bush-type or branch-type, treeing images are complicated to segment due to manifestation of convoluted tree branches, leading to a high misclassification rate during segmentation.… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 761-784, 2023, DOI:10.32604/cmc.2023.034988
Abstract In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 785-798, 2023, DOI:10.32604/cmc.2023.034540
Abstract The Internet of Medical Things (IoMT) emerges with the vision of the Wireless Body Sensor Network (WBSN) to improve the health monitoring systems and has an enormous impact on the healthcare system for recognizing the levels of risk/severity factors (premature diagnosis, treatment, and supervision of chronic disease i.e., cancer) via wearable/electronic health sensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy plays a very significant role in the detection of gastric cancer. Convolutional Neural Network (CNN) has been widely used to diagnose gastric cancer based on various feature extraction models, consequently, limiting the identification and categorization performance in terms of cancerous… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 799-814, 2023, DOI:10.32604/cmc.2023.035729
Abstract Urban traffic volume detection is an essential part of traffic planning in terms of urban planning in China. To improve the statistics efficiency of road traffic volume, this thesis proposes a method for predicting motor vehicle traffic volume on urban roads in small and medium-sized cities during the traffic peak hour by using mobile signal technology. The method is verified through simulation experiments, and the limitations and the improvement methods are discussed. This research can be divided into three parts: Firstly, the traffic patterns of small and medium-sized cities are obtained through a questionnaire survey. A total of 19745 residents… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 815-829, 2023, DOI:10.32604/cmc.2023.034297
Abstract This study conducted in Lima, Peru, a combination of spatial decision making system and machine learning was utilized to identify potential solar power plant construction sites within the city. Sundial measurements of solar radiation, precipitation, temperature, and altitude were collected for the study. Gene Expression Programming (GEP), which is based on the evolution of intelligent models, and Artificial Neural Networks (ANN) were both utilized in this investigation, and the results obtained from each were compared. Eighty percent of the data was utilized during the training phase, while the remaining twenty percent was utilized during the testing phase. On the basis… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 831-844, 2023, DOI:10.32604/cmc.2023.033700
Abstract Image processing networks have gained great success in many fields, and thus the issue of copyright protection for image processing networks has become a focus of attention. Model watermarking techniques are widely used in model copyright protection, but there are two challenges: (1) designing universal trigger sample watermarking for different network models is still a challenge; (2) existing methods of copyright protection based on trigger s watermarking are difficult to resist forgery attacks. In this work, we propose a dual model watermarking framework for copyright protection in image processing networks. The trigger sample watermark is embedded in the training process… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 845-862, 2023, DOI:10.32604/cmc.2023.033636
Abstract Long Range Wide Area Network (LoRaWAN) in the Internet of Things (IoT) domain has been the subject of interest for researchers. There is an increasing demand to localize these IoT devices using LoRaWAN due to the quickly growing number of IoT devices. LoRaWAN is well suited to support localization applications in IoTs due to its low power consumption and long range. Multiple approaches have been proposed to solve the localization problem using LoRaWAN. The Expected Signal Power (ESP) based trilateration algorithm has the significant potential for localization because ESP can identify the signal’s energy below the noise floor with no… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 863-878, 2023, DOI:10.32604/cmc.2023.034879
Abstract In the financial sector, data are highly confidential and sensitive, and ensuring data privacy is critical. Sample fusion is the basis of horizontal federation learning, but it is suitable only for scenarios where customers have the same format but different targets, namely for scenarios with strong feature overlapping and weak user overlapping. To solve this limitation, this paper proposes a federated learning-based model with local data sharing and differential privacy. The indexing mechanism of differential privacy is used to obtain different degrees of privacy budgets, which are applied to the gradient according to the contribution degree to ensure privacy without… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 879-890, 2023, DOI:10.32604/cmc.2023.035858
Abstract Image deraining has become a hot topic in the field of computer vision. It is the process of removing rain streaks from an image to reconstruct a high-quality background. This study aims at improving the performance of image rain streak removal and reducing the disruptive effects caused by rain. To better fit the rain removal task, an innovative image deraining method is proposed, where a kernel prediction network with Unet++ is designed and used to filter rainy images, and rainy-day images are used to estimate the pixel-level kernel for rain removal. To minimize the gap between synthetic and real data… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 891-909, 2023, DOI:10.32604/cmc.2023.035848
Abstract Pneumonia is an acute lung infection that has caused many fatalities globally. Radiologists often employ chest X-rays to identify pneumonia since they are presently the most effective imaging method for this purpose. Computer-aided diagnosis of pneumonia using deep learning techniques is widely used due to its effectiveness and performance. In the proposed method, the Synthetic Minority Oversampling Technique (SMOTE) approach is used to eliminate the class imbalance in the X-ray dataset. To compensate for the paucity of accessible data, pre-trained transfer learning is used, and an ensemble Convolutional Neural Network (CNN) model is developed. The ensemble model consists of all… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 911-925, 2023, DOI:10.32604/cmc.2023.033866
Abstract Mutual coupling reduction or isolation enhancement in antenna arrays is an important area of research as it severely affects the performance of an antenna. In this paper, a new type of compact and highly isolated Multiple-Input-Multiple-Output (MIMO) antenna for ultra-wideband (UWB) applications is presented. The design consists of four radiators that are orthogonally positioned and confined to a compact 40 × 40 × 0.8 mm3 space. The final antenna design uses an inverted L shape partial ground to produce an acceptable reflection coefficient (S11 < −10 dB) in an entire UWB band (3.1–10.6) giga hertz (GHz). Moreover, the inter-element isolation… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 927-942, 2023, DOI:10.32604/cmc.2023.035143
Abstract Diabetic Retinopathy (DR) is a serious hazard that can result in irreversible blindness if not addressed in a timely manner. Hence, numerous techniques have been proposed for the accurate and timely detection of this disease. Out of these, Deep Learning (DL) and Computer Vision (CV) methods for multiclass categorization of color fundus images diagnosed with Diabetic Retinopathy have sparked considerable attention. In this paper, we attempt to develop an extended ResNet152V2 architecture-based Deep Learning model, named ResNet2.0 to aid the timely detection of DR. The APTOS-2019 dataset was used to train the model. This consists of 3662 fundus images belonging… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 943-958, 2023, DOI:10.32604/cmc.2023.034078
Abstract Big data is usually unstructured, and many applications require the
analysis in real-time. Decision tree (DT) algorithm is widely used to analyze
big data. Selecting the optimal depth of DT is time-consuming process as it
requires many iterations. In this paper, we have designed a modified version
of a (DT). The tree aims to achieve optimal depth by self-tuning running
parameters and improving the accuracy. The efficiency of the modified (DT)
was verified using two datasets (airport and fire datasets). The airport dataset
has 500000 instances and the fire dataset has 600000 instances. A comparison
has been made between the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 959-976, 2023, DOI:10.32604/cmc.2023.035442
Abstract In the last decade, there has been remarkable progress in the areas of object detection and recognition due to high-quality color images along with their depth maps provided by RGB-D cameras. They enable artificially intelligent machines to easily detect and recognize objects and make real-time decisions according to the given scenarios. Depth cues can improve the quality of object detection and recognition. The main purpose of this research study to find an optimized way of object detection and identification we propose techniques of object detection using two RGB-D datasets. The proposed methodology extracts image normally from depth maps and then… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 977-997, 2023, DOI:10.32604/cmc.2023.036098
Abstract In the insurance sector, a massive volume of data is being generated on a daily basis due to a vast client base. Decision makers and business analysts emphasized that attaining new customers is costlier than retaining existing ones. The success of retention initiatives is determined not only by the accuracy of forecasting churners but also by the timing of the forecast. Previous works on churn forecast presented models for anticipating churn quarterly or monthly with an emphasis on customers’ static behavior. This paper’s objective is to calculate daily churn based on dynamic variations in client behavior. Training excellent models to… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 999-1015, 2023, DOI:10.32604/cmc.2023.035777
Abstract Due to small size and high occult, metacarpophalangeal fracture diagnosis displays a low accuracy in terms of fracture detection and location in X-ray images. To efficiently detect metacarpophalangeal fractures on X-ray images as the second opinion for radiologists, we proposed a novel one-stage neural network named MPFracNet based on RetinaNet. In MPFracNet, a deformable bottleneck block (DBB) was integrated into the bottleneck to better adapt to the geometric variation of the fractures. Furthermore, an integrated feature fusion module (IFFM) was employed to obtain more in-depth semantic and shallow detail features. Specifically, Focal Loss and Balanced L1 Loss were introduced to… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1017-1031, 2023, DOI:10.32604/cmc.2023.033957
Abstract Flue gas heat loss accounts for a significant component of the overall heat loss for coal-fired boilers in power plants. The flue gas absorbs more heat as the exhaust gas temperature rises, which reduces boiler efficiency and raises coal consumption. Additionally, if the exhaust gas temperature is too high, a lot of water must be used to cool the flue gas for the wet flue gas desulfurization system to function well, which has an impact on the power plant’s ability to operate profitably. It is consequently vital to take steps to lower exhaust gas temperatures in order to increase boiler… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1033-1050, 2023, DOI:10.32604/cmc.2023.034229
Abstract The demonstration of a higher data rate transmission system was a major aspect to be considered by researchers in recent years. The most relevant aspect to be studied and analyzed is the need for a reliable system to handle nonlinear impairments and reduce them. Therefore, this paper examines the influence of Four-Wave Mixing (FWM) impairment on the proposed high data rate Dual polarization–Differential Quadrature phase shift keying (DP-DQPSK) system using the Optisystem software. In the beginning, the impact of varied input power on the proposed system’s performance was evaluated in terms of QF and BER metrics. More power is used… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1051-1071, 2023, DOI:10.32604/cmc.2023.034495
Abstract This paper is to explore the problems of intelligent connected vehicles (ICVs) autonomous driving decision-making under a 5G-V2X structured road environment. Through literature review and interviews with autonomous driving practitioners, this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system. Secondly, situated on this framework, it builds a hierarchical finite state machine (HFSM) model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method (EWM) and analytic hierarchy process method (AHP) and by employing a model fusion approach between the technique for… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1073-1088, 2023, DOI:10.32604/cmc.2023.036170
Abstract Harvesting the power coming from the wind provides a green and environmentally friendly approach to producing electricity. To facilitate the ongoing advancement in wind energy applications, deep knowledge about wind regime behavior is essential. Wind speed is typically characterized by a statistical distribution, and the two-parameters Weibull distribution has shown its ability to represent wind speeds worldwide. Estimation of Weibull parameters, namely scale and shape parameters, is vital to describe the observed wind speeds data accurately. Yet, it is still a challenging task. Several numerical estimation approaches have been used by researchers to obtain c and k. However, utilizing such… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1089-1105, 2023, DOI:10.32604/cmc.2023.034563
Abstract Human action recognition (HAR) attempts to understand a subject’s behavior and assign a label to each action performed. It is more appealing because it has a wide range of applications in computer vision, such as video surveillance and smart cities. Many attempts have been made in the literature to develop an effective and robust framework for HAR. Still, the process remains difficult and may result in reduced accuracy due to several challenges, such as similarity among actions, extraction of essential features, and reduction of irrelevant features. In this work, we proposed an end-to-end framework using deep learning and an improved… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1107-1117, 2023, DOI:10.32604/cmc.2023.034917
Abstract The rapidly escalating sophistication of e-commerce fraud in recent years has led to an increasing reliance on fraud detection methods based on machine learning. However, fraud detection methods based on conventional machine learning approaches suffer from several problems, including an excessively high number of network parameters, which decreases the efficiency and increases the difficulty of training the network, while simultaneously leading to network overfitting. In addition, the sparsity of positive fraud incidents relative to the overwhelming proportion of negative incidents leads to detection failures in trained networks. The present work addresses these issues by proposing a convolutional neural network (CNN)… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1119-1137, 2023, DOI:10.32604/cmc.2023.035369
Abstract Promoting the co-constructing and sharing of organizational knowledge and improving organizational performance have always been the core research subject of knowledge management. Existing research focuses on the construction of knowledge management systems and knowledge sharing and transfer mechanisms. With the rapid development and application of cloud computing and big data technology, knowledge management is faced with many problems, such as how to combine with the new generation of information technology, how to achieve integration with organizational business processes, and so on. To solve such problems, this paper proposes a reciprocal collaborative knowledge management model (RCKM model) based on cloud computing… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1139-1156, 2023, DOI:10.32604/cmc.2023.035964
Abstract Exploiting modification direction (EMD) based data hiding techniques (DHTs) provide moderate data hiding capacity and high-quality stego images. The overflow problem and the cyclic nature of the extraction function essentially hinder their application in several fields in which reversibility is necessary. Thus far, the few EMD reversible DHTs are complex and numerically demanding. This paper presents a novel EMD-based reversible DHT using dual-image. Two novel 2 × 4 modification lookup tables are introduced, replacing the reference matrix used in similar techniques and eliminating the numerically demanding search step in similar techniques. In the embedding step, one of the modification tables modifies a… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1157-1177, 2023, DOI:10.32604/cmc.2023.035667
Abstract Wireless sensor networks (WSNs) operate in complex and harsh environments; thus, node faults are inevitable. Therefore, fault diagnosis of the WSNs node is essential. Affected by the harsh working environment of WSNs and wireless data transmission, the data collected by WSNs contain noisy data, leading to unreliable data among the data features extracted during fault diagnosis. To reduce the influence of unreliable data features on fault diagnosis accuracy, this paper proposes a belief rule base (BRB) with a self-adaptive quality factor (BRB-SAQF) fault diagnosis model. First, the data features required for WSN node fault diagnosis are extracted. Second, the quality… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1179-1194, 2023, DOI:10.32604/cmc.2023.035324
Abstract Manual inspection of fruit diseases is a time-consuming and costly because it is based on naked-eye observation. The authors present computer vision techniques for detecting and classifying fruit leaf diseases. Examples of computer vision techniques are preprocessing original images for visualization of infected regions, feature extraction from raw or segmented images, feature fusion, feature selection, and classification. The following are the major challenges identified by researchers in the literature: (i) low-contrast infected regions extract irrelevant and redundant information, which misleads classification accuracy; (ii) irrelevant and redundant information may increase computational time and reduce the designed model’s accuracy. This paper proposed… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1195-1212, 2023, DOI:10.32604/cmc.2023.035932
Abstract In the Ethernet lossless Data Center Networks (DCNs) deployed with Priority-based Flow Control (PFC), the head-of-line blocking problem is still difficult to prevent due to PFC triggering under burst traffic scenarios even with the existing congestion control solutions. To address the head-of-line blocking problem of PFC, we propose a new congestion control mechanism. The key point of Congestion Control Using In-Network Telemetry for Lossless Datacenters (ICC) is to use In-Network Telemetry (INT) technology to obtain comprehensive congestion information, which is then fed back to the sender to adjust the sending rate timely and accurately. It is possible to control congestion… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1213-1233, 2023, DOI:10.32604/cmc.2023.034399
Abstract The aviation industry is one of the most competitive markets. The most common approach for airline service providers is to improve passenger satisfaction. Passenger satisfaction in the aviation industry occurs when passengers’ expectations are met during flights. Airline service quality is critical in attracting new passengers and retaining existing ones. It is crucial to identify passengers’ pain points and enhance their satisfaction with the services offered. The airlines used a variety of techniques to improve service quality. They used data analysis approaches to analyze the passenger point data. These solutions have focused simply on surveys; consequently, deep-learning approaches have received… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1235-1251, 2023, DOI:10.32604/cmc.2023.036357
Abstract One of the most common types of threats to the digital world is malicious software. It is of great importance to detect and prevent existing and new malware before it damages information assets. Machine learning approaches are used effectively for this purpose. In this study, we present a model in which supervised and unsupervised learning algorithms are used together. Clustering is used to enhance the prediction performance of the supervised classifiers. The aim of the proposed model is to make predictions in the shortest possible time with high accuracy and f1 score. In the first stage of the model, the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111
Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1271-1290, 2023, DOI:10.32604/cmc.2023.036422
Abstract Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One of the online security challenges… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1291-1304, 2023, DOI:10.32604/cmc.2023.035710
Abstract Currently, the risk factors of pregnancy loss are increasing and are considered a major challenge because they vary between cases. The early prediction of miscarriage can help pregnant ladies to take the needed care and avoid any danger. Therefore, an intelligent automated solution must be developed to predict the risk factors for pregnancy loss at an early stage to assist with accurate and effective diagnosis. Machine learning (ML)-based decision support systems are increasingly used in the healthcare sector and have achieved notable performance and objectiveness in disease prediction and prognosis. Thus, we developed a model to help obstetricians predict the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1305-1316, 2023, DOI:10.32604/cmc.2023.033274
Abstract Because solar energy is among the renewable energies, it has traditionally been used to provide lighting in buildings. When solar energy is effectively utilized during the day, the environment is not only more comfortable for users, but it also utilizes energy more efficiently for both heating and cooling purposes. Because of this, increasing the building’s energy efficiency requires first controlling the amount of light that enters the space. Considering that the only parts of the building that come into direct contact with the sun are the windows, it is essential to make use of louvers in order to regulate the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1317-1330, 2023, DOI:10.32604/cmc.2023.029879
Abstract This work presents, design and specific absorption rate (SAR) analysis of a 37 GHz antenna, for 5th Generation (5G) applications. The proposed antenna comprises of 4-elements of rectangular patch and an even distribution. The radiating element is composed of copper material supported by Rogers RT5880 substrate of thickness, 0.254 mm, dielectric constant (εr), 2.2, and loss tangent, 0.0009. The 4-elements array antenna is compact in size with a dimension of 8 mm × 20 mm in length and width. The radiating patch is excited with a 50 ohms connector i.e., K-type. The antenna resonates in the frequency band of 37 GHz, that covers the 5G applications. The antenna… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1331-1351, 2023, DOI:10.32604/cmc.2023.033181
Abstract Mobile adhoc networks have grown in prominence in recent years, and they are now utilized in a broader range of applications. The main challenges are related to routing techniques that are generally employed in them. Mobile Adhoc system management, on the other hand, requires further testing and improvements in terms of security. Traditional routing protocols, such as Adhoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR), employ the hop count to calculate the distance between two nodes. The main aim of this research work is to determine the optimum method for sending packets while also extending life time of… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1353-1369, 2023, DOI:10.32604/cmc.2023.036453
Abstract The current advancement in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) transformed the traditional healthcare system into smart healthcare. Healthcare services could be enhanced by incorporating key techniques like AI and IoT. The convergence of AI and IoT provides distinct opportunities in the medical field. Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population. Therefore, earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support. Lately, the emergence of IoT, AI, smartphones, wearables, and so… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1371-1389, 2023, DOI:10.32604/cmc.2023.033509
Abstract Various feature selection algorithms are usually employed to improve classification models’ overall performance. Optimization algorithms typically accompany such algorithms to select the optimal set of features. Among the most currently attractive trends within optimization algorithms are hybrid metaheuristics. The present paper presents two Stages of Local Search models for feature selection based on WOA (Whale Optimization Algorithm) and Great Deluge (GD). GD Algorithm is integrated with the WOA algorithm to improve exploitation by identifying the most promising regions during the search. Another version is employed using the best solution found by the WOA algorithm and exploited by the GD algorithm.… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1391-1409, 2023, DOI:10.32604/cmc.2023.035894
Abstract Human verification and activity analysis (HVAA) are primarily employed to observe, track, and monitor human motion patterns using red-green-blue (RGB) images and videos. Interpreting human interaction using RGB images is one of the most complex machine learning tasks in recent times. Numerous models rely on various parameters, such as the detection rate, position, and direction of human body components in RGB images. This paper presents robust human activity analysis for event recognition via the extraction of contextual intelligence-based features. To use human interaction image sequences as input data, we first perform a few denoising steps. Then, human-to-human analyses are employed… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1411-1430, 2023, DOI:10.32604/cmc.2023.034876
Abstract In recent years, target detection of aerial images of unmanned aerial vehicle (UAV) has become one of the hottest topics. However, target detection of UAV aerial images often presents false detection and missed detection. We proposed a modified you only look once (YOLO) model to improve the problems arising in object detection in UAV aerial images: (1) A new residual structure is designed to improve the ability to extract features by enhancing the fusion of the inner features of the single layer. At the same time, triplet attention module is added to strengthen the connection between space and channel and… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1431-1446, 2023, DOI:10.32604/cmc.2023.034400
Abstract In the field of stroke imaging, deep learning (DL) has enormous untapped potential. When clinically significant symptoms of a cerebral stroke are detected, it is crucial to make an urgent diagnosis using available imaging techniques such as computed tomography (CT) scans. The purpose of this work is to classify brain CT images as normal, surviving ischemia or cerebral hemorrhage based on the convolutional neural network (CNN) model. In this study, we propose a computer-aided diagnostic system (CAD) for categorizing cerebral strokes using computed tomography images. Horizontal flip data magnification techniques were used to obtain more accurate categorization. Image Data Generator… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1447-1465, 2023, DOI:10.32604/cmc.2023.031878
Abstract Lung cancer is the leading cause of mortality in the world affecting both men and women equally. When a radiologist just focuses on the patient’s body, it increases the amount of strain on the radiologist and the likelihood of missing pathological information such as abnormalities are increased. One of the primary objectives of this research work is to develop computer-assisted diagnosis and detection of lung cancer. It also intends to make it easier for radiologists to identify and diagnose lung cancer accurately. The proposed strategy which was based on a unique image feature, took into consideration the spatial interaction of… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1467-1482, 2023, DOI:10.32604/cmc.2023.033280
Abstract This paper presents a performance analysis of novel double-damped tuned alternating current (AC) filters in high voltage direct current (HVDC) systems. The proposed double-damped tuned AC filters offer the advantages of improved performance of HVDC systems in terms of better power quality, high power factor, and lower total harmonic distortion (THD). The system under analysis consists of an 878 km long HVDC transmission line connecting converter stations at Matiari and Lahore, two major cities in Pakistan. The main focus of this research is to design a novel AC filter using the equivalent impedance method of two single-tuned and double-damped tuned… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1483-1499, 2023, DOI:10.32604/cmc.2023.036366
Abstract The diagnosis of eye disease through deep learning (DL) technology is the latest trend in the field of artificial intelligence (AI). Especially in diagnosing pathologic myopia (PM) lesions, the implementation of DL is a difficult task because of the classification complexity and definition system of PM. However, it is possible to design an AI-based technique that can identify PM automatically and help doctors make relevant decisions. To achieve this objective, it is important to have adequate resources such as a high-quality PM image dataset and an expert team. The primary aim of this research is to design and train the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1501-1526, 2023, DOI:10.32604/cmc.2023.035602
Abstract Task offloading is a key strategy in Fog Computing (FC). The definition of resource-constrained devices no longer applies to sensors and Internet of Things (IoT) embedded system devices alone. Smart and mobile units can also be viewed as resource-constrained devices if the power, cloud applications, and data cloud are included in the set of required resources. In a cloud-fog-based architecture, a task instance running on an end device may need to be offloaded to a fog node to complete its execution. However, in a busy network, a second offloading decision is required when the fog node becomes overloaded. The possibility… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1527-1545, 2023, DOI:10.32604/cmc.2023.036322
Abstract Some human diseases are recognized through of each type of White Blood Cell (WBC) count, so detecting and classifying each type is important for human healthcare. The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed, developed, and evaluated to classify WBCs into five types namely neutrophils, eosinophils, lymphocytes, monocytes, and basophils. Using a computer-artificial model reduces resource and time consumption. Various pre-trained deep learning models have been used to extract features, including AlexNet, Visual Geometry Group (VGG), Residual Network (ResNet), which belong to different taxonomy types of deep learning architectures. Also, Binary Border… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1547-1559, 2023, DOI:10.32604/cmc.2023.033300
Abstract Numerous methods are analysed in detail to improve task scheduling and data security performance in the cloud environment. The methods involve scheduling according to the factors like makespan, waiting time, cost, deadline, and popularity. However, the methods are inappropriate for achieving higher scheduling performance. Regarding data security, existing methods use various encryption schemes but introduce significant service interruption. This article sketches a practical Real-time Application Centric TRS (Throughput-Resource utilization–Success) Scheduling with Data Security (RATRSDS) model by considering all these issues in task scheduling and data security. The method identifies the required resource and their claim time by receiving the service… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1561-1576, 2023, DOI:10.32604/cmc.2023.035016
Abstract With the frequent occurrence of telecommunications and network fraud crimes in recent years, new frauds have emerged one after another which has caused huge losses to the people. However, due to the lack of an effective preventive mechanism, the police are often in a passive position. Using technologies such as web crawlers, feature engineering, deep learning, and artificial intelligence, this paper proposes a user portrait fraud warning scheme based on Weibo public data. First, we perform preliminary screening and cleaning based on the keyword “defrauded” to obtain valid fraudulent user Identity Documents (IDs). The basic information and account information of… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1577-1601, 2023, DOI:10.32604/cmc.2023.034746
Abstract The COVID-19 pandemic has spread globally, resulting in financial instability in many countries and reductions in the per capita gross domestic product. Sentiment analysis is a cost-effective method for acquiring sentiments based on household income loss, as expressed on social media. However, limited research has been conducted in this domain using the LexDeep approach. This study aimed to explore social trend analytics using LexDeep, which is a hybrid sentiment analysis technique, on Twitter to capture the risk of household income loss during the COVID-19 pandemic. First, tweet data were collected using Twint with relevant keywords before (9 March 2019 to… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1603-1619, 2023, DOI:10.32604/cmc.2023.036216
Abstract Recently, digital images have become the most used data, thanks to high internet speed and high resolution, cheap and easily accessible digital cameras. We generate, transmit and store millions of images every second. Most of these images are insignificant images containing only personal information. However, in many fields such as banking, finance, public institutions, and educational institutions, the images of many valuable objects like ID cards, photographs, credit cards, and transaction receipts are stored and transmitted to the digital environment. These images are very significant and must be secured. A valuable image can be maliciously modified by an attacker. The… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1621-1640, 2023, DOI:10.32604/cmc.2023.036177
Abstract Label assignment refers to determining positive/negative labels for each sample to supervise the training process. Existing Siamese-based trackers primarily use fixed label assignment strategies according to human prior knowledge; thus, they can be sensitive to predefined hyperparameters and fail to fit the spatial and scale variations of samples. In this study, we first develop a novel dynamic label assignment (DLA) module to handle the diverse data distributions and adaptively distinguish the foreground from the background based on the statistical characteristics of the target in visual object tracking. The core of DLA module is a two-step selection mechanism. The first step… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1641-1656, 2023, DOI:10.32604/cmc.2023.035056
Abstract Traffic flow prediction in urban areas is essential in the Intelligent Transportation System (ITS). Short Term Traffic Flow (STTF) prediction impacts traffic flow series, where an estimation of the number of vehicles will appear during the next instance of time per hour. Precise STTF is critical in Intelligent Transportation System. Various extinct systems aim for short-term traffic forecasts, ensuring a good precision outcome which was a significant task over the past few years. The main objective of this paper is to propose a new model to predict STTF for every hour of a day. In this paper, we have proposed… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1657-1669, 2023, DOI:10.32604/cmc.2023.036558
Abstract The marine environment is becoming increasingly complex due to the various marine vehicles, and the diversity of maritime objects poses a challenge to marine environmental governance. Maritime object detection technology plays an important role in this segment. In the field of computer vision, there is no sufficiently comprehensive public dataset for maritime objects in the contrast to the automotive application domain. The existing maritime datasets either have no bounding boxes (which are made for object classification) or cover limited varieties of maritime objects. To fulfil the vacancy, this paper proposed the Multi-Category Large-Scale Dataset for Maritime Object Detection (MCMOD) which… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1671-1686, 2023, DOI:10.32604/cmc.2023.035762
Abstract This paper proposes a method for detecting a helmet for the safety of workers from risk factors and a mask worn indoors and verifying a worker’s identity while wearing a helmet and mask for security. The proposed method consists of a part for detecting the worker’s helmet and mask and a part for verifying the worker’s identity. An algorithm for helmet and mask detection is generated by transfer learning of Yolov5’s s-model and m-model. Both models are trained by changing the learning rate, batch size, and epoch. The model with the best performance is selected as the model for detecting… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1687-1709, 2023, DOI:10.32604/cmc.2023.035239
Abstract Expert Recommendation (ER) aims to identify domain experts with high expertise and willingness to provide answers to questions in Community Question Answering (CQA) web services. How to model questions and users in the heterogeneous content network is critical to this task. Most traditional methods focus on modeling questions and users based on the textual content left in the community while ignoring the structural properties of heterogeneous CQA networks and always suffering from textual data sparsity issues. Recent approaches take advantage of structural proximities between nodes and attempt to fuse the textual content of nodes for modeling. However, they often fail… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1711-1733, 2023, DOI:10.32604/cmc.2023.036680
Abstract Various regions are becoming increasingly vulnerable to the increased frequency of floods due to the recent changes in climate and precipitation patterns throughout the world. As a result, specific infrastructures, notably bridges, would experience significant flooding for which they were not intended and would be submerged. The flow field and shear stress distribution around tandem bridge piers under pressurized flow conditions for various bridge deck widths are examined using a series of three-dimensional (3D) simulations. It is indicated that scenarios with a deck width to pier diameter (Ld/p) ratio of 3 experience the highest levels of turbulent disturbance. In addition,… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1735-1750, 2023, DOI:10.32604/cmc.2023.034468
Abstract Device to Device (D2D) communication is expected to be an essential part of 5G cellular networks. D2D communication enables close-proximity devices to establish a direct communication session. D2D communication offers many advantages, such as reduced latency, high data rates, range extension, and cellular offloading. The first step to establishing a D2D session is device discovery; an efficient device discovery will lead to efficient D2D communication. D2D device further needs to manage its mode of communication, perform resource allocation, manage its interference and most importantly control its power to improve the battery life of the device. This work has developed six… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1751-1764, 2023, DOI:10.32604/cmc.2023.031663
Abstract Recently, the development of the Internet of Things (IoT) has enabled continuous and personal electrocardiogram (ECG) monitoring. In the ECG monitoring system, classification plays an important role because it can select useful data (i.e., reduce the size of the dataset) and identify abnormal data that can be used to detect the clinical diagnosis and guide further treatment. Since the classification requires computing capability, the ECG data are usually delivered to the gateway or the server where the classification is performed based on its computing resource. However, real-time ECG data transmission continuously consumes battery and network resources, which are expensive and… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1765-1781, 2023, DOI:10.32604/cmc.2023.029552
Abstract Detecting double Joint Photographic Experts Group (JPEG) compression for color images is vital in the field of image forensics. In previous researches, there have been various approaches to detecting double JPEG compression with different quantization matrices. However, the detection of double JPEG color images with the same quantization matrix is still a challenging task. An effective detection approach to extract features is proposed in this paper by combining traditional analysis with Convolutional Neural Networks (CNN). On the one hand, the number of nonzero pixels and the sum of pixel values of color space conversion error are provided with 12-dimensional features… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1783-1800, 2023, DOI:10.32604/cmc.2023.035736
Abstract Short-term load forecasting (STLF) is part and parcel of the efficient working of power grid stations. Accurate forecasts help to detect the fault and enhance grid reliability for organizing sufficient energy transactions. STLF ranges from an hour ahead prediction to a day ahead prediction. Various electric load forecasting methods have been used in literature for electricity generation planning to meet future load demand. A perfect balance regarding generation and utilization is still lacking to avoid extra generation and misusage of electric load. Therefore, this paper utilizes Levenberg–Marquardt (LM) based Artificial Neural Network (ANN) technique to forecast the short-term electricity load… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1801-1814, 2023, DOI:10.32604/cmc.2023.032785
Abstract License plate recognition technology use widely in intelligent traffic management and control. Researchers have been committed to improving the speed and accuracy of license plate recognition for nearly 30 years. This paper is the first to propose combining the attention mechanism with YOLO-v5 and LPRnet to construct a new license plate recognition model (LPR-CBAM-Net). Through the attention mechanism CBAM (Convolutional Block Attention Module), the importance of different feature channels in license plate recognition can be re-calibrated to obtain proper attention to features. Force information to achieve the purpose of improving recognition speed and accuracy. Experimental results show that the model… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1815-1826, 2023, DOI:10.32604/cmc.2023.032376
Abstract Considering the exponential growth of wireless devices with data-starving applications fused with artificial intelligence, the significance of wireless network scalability using distributed behavior and fairness among users is a crucial feature in guaranteeing reliable service to numerous users in the network environment. The Kuramoto model is described as nonlinear self-sustained phase oscillators spinning at varying intrinsic frequencies connected through the sine of their phase differences and displays a phase transition at a specific coupling strength, in which a mutual behavior is accomplished. In this work, we apply the Kuramoto model to achieve a weighted fair resource allocation in a wireless… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1827-1845, 2023, DOI:10.32604/cmc.2023.033934
Abstract Every application in a smart city environment like the smart grid, health monitoring, security, and surveillance generates non-stationary data streams. Due to such nature, the statistical properties of data changes over time, leading to class imbalance and concept drift issues. Both these issues cause model performance degradation. Most of the current work has been focused on developing an ensemble strategy by training a new classifier on the latest data to resolve the issue. These techniques suffer while training the new classifier if the data is imbalanced. Also, the class imbalance ratio may change greatly from one input stream to another,… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1847-1861, 2023, DOI:10.32604/cmc.2023.035698
Abstract Deep learning has been constantly improving in recent years, and a significant number of researchers have devoted themselves to the research of defect detection algorithms. Detection and recognition of small and complex targets is still a problem that needs to be solved. The authors of this research would like to present an improved defect detection model for detecting small and complex defect targets in steel surfaces. During steel strip production, mechanical forces and environmental factors cause surface defects of the steel strip. Therefore, the detection of such defects is key to the production of high-quality products. Moreover, surface defects of… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1863-1881, 2023, DOI:10.32604/cmc.2023.035287
Abstract The increasing global population at a rapid pace makes road traffic dense; managing such massive traffic is challenging. In developing countries like Pakistan, road traffic accidents (RTA) have the highest mortality percentage among other Asian countries. The main reasons for RTAs are road cracks and potholes. Understanding the need for an automated system for the detection of cracks and potholes, this study proposes a decision support system (DSS) for an autonomous road information system for smart city development with the use of deep learning. The proposed DSS works in layers where initially the image of roads is captured and coordinates… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1883-1900, 2023, DOI:10.32604/cmc.2023.031723
Abstract The rapid population growth results in a crucial problem in the early detection of diseases in medical research. Among all the cancers unveiled, breast cancer is considered the second most severe cancer. Consequently, an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical diagnoses. Utilizing recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective, reliable, and rapid responses, which could help in decreasing the death risk. In this paper, we propose a new algorithm for feature… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1901-1918, 2023, DOI:10.32604/cmc.2023.028777
Abstract IoT devices rely on authentication mechanisms to render secure message exchange. During data transmission, scalability, data integrity, and processing time have been considered challenging aspects for a system constituted by IoT devices. The application of physical unclonable functions (PUFs) ensures secure data transmission among the internet of things (IoT) devices in a simplified network with an efficient time-stamped agreement. This paper proposes a secure, lightweight, cost-efficient reinforcement machine learning framework (SLCR-MLF) to achieve decentralization and security, thus enabling scalability, data integrity, and optimized processing time in IoT devices. PUF has been integrated into SLCR-MLF to improve the security of the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1919-1939, 2023, DOI:10.32604/cmc.2023.036013
Abstract Recently, the combination of video services and 5G networks have been gaining attention in the wireless communication realm. With the brisk advancement in 5G network usage and the massive popularity of three-dimensional video streaming, the quality of experience (QoE) of video in 5G systems has been receiving overwhelming significance from both customers and service provider ends. Therefore, effectively categorizing QoE-aware video streaming is imperative for achieving greater client satisfaction. This work makes the following contribution: First, a simulation platform based on NS-3 is introduced to analyze and improve the performance of video services. The simulation is formulated to offer real-time… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1941-1961, 2023, DOI:10.32604/cmc.2023.035360
Abstract Relative positioning is one of the important techniques in collaborative robotics, autonomous vehicles, and virtual/augmented reality (VR/AR) applications. Recently, ultra-wideband (UWB) has been utilized to calculate relative position as it does not require a line of sight compared to a camera to calculate the range between two objects with centimeter-level accuracy. However, the single UWB range measurement cannot provide the relative position and attitude of any device in three dimensions (3D) because of lacking bearing information. In this paper, we have proposed a UWB-IMU fusion-based relative position system to provide accurate relative position and attitude between wearable Internet of Things… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1963-1980, 2023, DOI:10.32604/cmc.2023.033910
Abstract Since 2016, the National Institute of Standards and Technology (NIST) has been performing a competition to standardize post-quantum cryptography (PQC). Although Falcon has been selected in the competition as one of the standard PQC algorithms because of its advantages in short key and signature sizes, its performance overhead is larger than that of other lattice-based cryptosystems. This study presents multiple methodologies to accelerate the performance of Falcon using graphics processing units (GPUs) for server-side use. Direct GPU porting significantly degrades performance because the Falcon reference codes require recursive functions in its sampling process. Thus, an iterative sampling approach for efficient… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1981-1994, 2023, DOI:10.32604/cmc.2023.035245
Abstract Artificial intelligence technologies are being studied to provide scientific evidence in the medical field and developed for use as diagnostic tools. This study focused on deep learning models to classify degenerative arthritis into Kellgren–Lawrence grades. Specifically, degenerative arthritis was assessed by X-ray radiographic images and classified into five classes. Subsequently, the use of various deep learning models was investigated for automating the degenerative arthritis classification process. Although research on the classification of osteoarthritis using deep learning has been conducted in previous studies, only local models have been used, and an ensemble of deep learning models has never been applied to… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1995-2024, 2023, DOI:10.32604/cmc.2023.035888
Abstract Image segmentation is crucial for various research areas. Many computer vision applications depend on segmenting images to understand the scene, such as autonomous driving, surveillance systems, robotics, and medical imaging. With the recent advances in deep learning (DL) and its confounding results in image segmentation, more attention has been drawn to its use in medical image segmentation. This article introduces a survey of the state-of-the-art deep convolution neural network (CNN) models and mechanisms utilized in image segmentation. First, segmentation models are categorized based on their model architecture and primary working principle. Then, CNN categories are described, and various models are… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2025-2042, 2023, DOI:10.32604/cmc.2023.036051
Abstract A concurrency control mechanism for collaborative work is a key element in a mixed reality environment. However, conventional locking mechanisms restrict potential tasks or the support of non-owners, thus increasing the working time because of waiting to avoid conflicts. Herein, we propose an adaptive concurrency control approach that can reduce conflicts and work time. We classify shared object manipulation in mixed reality into detailed goals and tasks. Then, we model the relationships among goal, task, and ownership. As the collaborative work progresses, the proposed system adapts the different concurrency control mechanisms of shared object manipulation according to the modeling of… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2043-2059, 2023, DOI:10.32604/cmc.2023.033670
Abstract Internet of Medical Things (IoMT) plays an essential role in collecting and managing personal medical data. In recent years, blockchain technology has put power in traditional IoMT systems for data sharing between different medical institutions and improved the utilization of medical data. However, some problems in the information transfer process between wireless medical devices and mobile medical apps, such as information leakage and privacy disclosure. This paper first designs a cross-device key agreement model for blockchain-enabled IoMT. This model can establish a key agreement mechanism for secure medical data sharing. Meanwhile, a certificateless authenticated key agreement (KA) protocol has been… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2061-2078, 2023, DOI:10.32604/cmc.2023.034505
Abstract Fileless webshell attacks against Java web applications have become more frequent in recent years as Java has gained market share. Webshell is a malicious script that can remotely execute commands and invade servers. It is widely used in attacks against web applications. In contrast to traditional file-based webshells, fileless webshells leave no traces on the hard drive, which means they are invisible to most antivirus software. To make matters worse, although there are some studies on fileless webshells, almost all of them are aimed at web applications developed in the PHP language. The complex mechanism of Java makes researchers face… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2079-2099, 2023, DOI:10.32604/cmc.2023.034118
Abstract This paper constructs a non-cooperative/cooperative stochastic differential game model to prove that the optimal strategies trajectory of agents in a system with a topological configuration of a Multi-Local-World graph would converge into a certain attractor if the system’s configuration is fixed. Due to the economics and management property, almost all systems are divided into several independent Local-Worlds, and the interaction between agents in the system is more complex. The interaction between agents in the same Local-World is defined as a stochastic differential cooperative game; conversely, the interaction between agents in different Local-Worlds is defined as a stochastic differential non-cooperative game.… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2101-2117, 2023, DOI:10.32604/cmc.2023.035530
Abstract Deploying task caching at edge servers has become an effective way to handle compute-intensive and latency-sensitive tasks on the industrial internet. However, how to select the task scheduling location to reduce task delay and cost while ensuring the data security and reliable communication of edge computing remains a challenge. To solve this problem, this paper establishes a task scheduling model with joint blockchain and task caching in the industrial internet and designs a novel blockchain-assisted caching mechanism to enhance system security. In this paper, the task scheduling problem, which couples the task scheduling decision, task caching decision, and blockchain reward,… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2119-2135, 2023, DOI:10.32604/cmc.2023.035077
Abstract In recent years, the Internet of Things (IoT) technology has developed by leaps and bounds. However, the large and heterogeneous network structure of IoT brings high management costs. In particular, the low cost of IoT devices exposes them to more serious security concerns. First, a convolutional neural network intrusion detection system for IoT devices is proposed. After cleaning and preprocessing the NSL-KDD dataset, this paper uses feature engineering methods to select appropriate features. Then, based on the combination of DCNN and machine learning, this paper designs a cloud-based loss function, which adopts a regularization method to prevent overfitting. The model… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2137-2153, 2023, DOI:10.32604/cmc.2023.036861
Abstract Encryption algorithms are one of the methods to protect data during its transmission through an unsafe transmission medium. But encryption methods need a lot of time during encryption and decryption, so it is necessary to find encryption algorithms that consume little time while preserving the security of the data. In this paper, more than one algorithm was combined to obtain high security with a short implementation time. A chaotic system, DNA computing, and Salsa20 were combined. A proposed 5D chaos system was used to generate more robust keys in a Salsa algorithm and DNA computing. Also, the confusion is performed… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2155-2170, 2023, DOI:10.32604/cmc.2023.034699
Abstract The purpose of this study is to present the numerical performances and interpretations of the SEIR nonlinear system based on the Zika virus spreading by using the stochastic neural networks based intelligent computing solver. The epidemic form of the nonlinear system represents the four dynamics of the patients, susceptible patients S(y), exposed patients hospitalized in hospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIR model. The computing numerical outcomes and performances of the system are examined by using the artificial neural networks (ANNs) and the scaled conjugate gradient (SCG) for the training of the networks, i.e., ANNs-SCG. The… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2171-2190, 2023, DOI:10.32604/cmc.2023.035559
Abstract Online Social Networks (OSN) sites allow end-users to share a great deal of information, which may also contain sensitive information, that may be subject to commercial or non-commercial privacy attacks. As a result, guaranteeing various levels of privacy is critical while publishing data by OSNs. The clustering-based solutions proved an effective mechanism to achieve the privacy notions in OSNs. But fixed clustering limits the performance and scalability. Data utility degrades with increased privacy, so balancing the privacy utility trade-off is an open research issue. The research has proposed a novel privacy preservation model using the enhanced clustering mechanism to overcome… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2191-2208, 2023, DOI:10.32604/cmc.2023.036205
Abstract Video analytics is an integral part of surveillance cameras. Compared to video analytics, audio analytics offers several benefits, including less expensive equipment and upkeep expenses. Additionally, the volume of the audio datastream is substantially lower than the video camera datastream, especially concerning real-time operating systems, which makes it less demanding of the data channel’s bandwidth needs. For instance, automatic live video streaming from the site of an explosion and gunshot to the police console using audio analytics technologies would be exceedingly helpful for urban surveillance. Technologies for audio analytics may also be used to analyze video recordings and identify occurrences.… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2209-2226, 2023, DOI:10.32604/cmc.2023.027102
Abstract The automatically defect detection method using vision inspection is a promising direction. In this paper, an efficient defect detection method for detecting surface damage to cables on a cable-stayed bridge automatically is developed. A mechanism design method for the protective layer of cables of a bridge based on vision inspection and diameter measurement is proposed by combining computer vision and diameter measurement techniques. A detection system for the surface damages of cables is de-signed. Images of cable surfaces are then enhanced and subjected to threshold segmentation by utilizing the improved local grey contrast enhancement method and the improved maximum correlation… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2227-2245, 2023, DOI:10.32604/cmc.2023.031890
Abstract Gastrointestinal diseases like ulcers, polyps’, and bleeding are increasing rapidly in the world over the last decade. On average 0.7 million cases are reported worldwide every year. The main cause of gastrointestinal diseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in more than 50% of people around the globe. Many researchers have proposed different methods for gastrointestinal disease using computer vision techniques. Few of them focused on the detection process and the rest of them performed classification. The major challenges that they faced are the similarity of infected and healthy regions that misleads the correct classification accuracy. In… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2247-2263, 2023, DOI:10.32604/cmc.2023.027882
Abstract Food processing companies pursue the distribution of ingredients that were packaged according to a certain weight. Particularly, foods like fish are highly demanded and supplied. However, despite the high quantity of fish to be supplied, most seafood processing companies have yet to install automation equipment. Such absence of automation equipment for seafood processing incurs a considerable cost regarding labor force, economy, and time. Moreover, workers responsible for fish processing are exposed to risks because fish processing tasks require the use of dangerous tools, such as power saws or knives. To solve these problems observed in the fish processing field, this… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2265-2281, 2023, DOI:10.32604/cmc.2023.032429
Abstract Biomedical image processing is finding useful in healthcare sector for the investigation, enhancement, and display of images gathered by distinct imaging technologies. Diabetic retinopathy (DR) is an illness caused by diabetes complications and leads to irreversible injury to the retina blood vessels. Retinal vessel segmentation techniques are a basic element of automated retinal disease screening system. In this view, this study presents a novel blood vessel segmentation with deep learning based classification (BVS-DLC) model for DR diagnosis using retinal fundus images. The proposed BVS-DLC model involves different stages of operations such as preprocessing, segmentation, feature extraction, and classification. Primarily, the… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2283-2299, 2023, DOI:10.32604/cmc.2023.030706
Abstract Brain hemorrhage is a serious and life-threatening condition. It can cause permanent and lifelong disability even when it is not fatal. The word hemorrhage denotes leakage of blood within the brain and this leakage of blood from capillaries causes stroke and adequate supply of oxygen to the brain is hindered. Modern imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI) are employed to get an idea regarding the extent of the damage. An early diagnosis and treatment can save lives and limit the adverse effects of a brain hemorrhage. In this case, a deep neural network (DNN)… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2301-2312, 2023, DOI:10.32604/cmc.2023.028333
Abstract Personality distinguishes individuals’ patterns of feeling, thinking, and behaving. Predicting personality from small video series is an exciting research area in computer vision. The majority of the existing research concludes preliminary results to get immense knowledge from visual and Audio (sound) modality. To overcome the deficiency, we proposed the Deep Bimodal Fusion (DBF) approach to predict five traits of personality-agreeableness, extraversion, openness, conscientiousness and neuroticism. In the proposed framework, regarding visual modality, the modified convolution neural networks (CNN), more specifically Descriptor Aggregator Model (DAN) are used to attain significant visual modality. The proposed model extracts audio representations for greater efficiency… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2313-2329, 2023, DOI:10.32604/cmc.2023.031133
Abstract In the context of both the Virtual Power Plant (VPP) and microgrid (MG), the Energy Management System (EMS) is a key decision-maker for integrating Distributed renewable Energy Resources (DERs) efficiently. The EMS is regarded as a strong enabler of providing the optimized scheduling control in operation and management of usage of disperse DERs and Renewable Energy reSources (RES) such as a small-size wind-turbine (WT) and photovoltaic (PV) energies. The main objective to be pursued by the EMS is the minimization of the overall operating cost of the MG integrated VPP network. However, the minimization of the power peaks is a… More >
Open Access
ARTICLE
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2331-2346, 2023, DOI:10.32604/cmc.2023.028712
Abstract Hand gesture recognition (HGR) is used in a numerous applications, including medical health-care, industrial purpose and sports detection. We have developed a real-time hand gesture recognition system using inertial sensors for the smart home application. Developing such a model facilitates the medical health field (elders or disabled ones). Home automation has also been proven to be a tremendous benefit for the elderly and disabled. Residents are admitted to smart homes for comfort, luxury, improved quality of life, and protection against intrusion and burglars. This paper proposes a novel system that uses principal component analysis, linear discrimination analysis feature extraction, and… More >
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