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  • Open Access

    ARTICLE

    A 3D Geometry Model of Vocal Tract Based on Smart Internet of Things

    Ming Li1, Kuntharrgyal Khysru2, Haiqiang Shi2,*, Qiang Fang3,*, Jinrong Hu4, Yun Chen5

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 783-798, 2023, DOI:10.32604/csse.2023.034687

    Abstract The Internet of Things (IoT) plays an essential role in the current and future generations of information, network, and communication development and applications. This research focuses on vocal tract visualization and modeling, which are critical issues in realizing inner vocal tract animation. That is applied in many fields, such as speech training, speech therapy, speech analysis and other speech production-related applications. This work constructed a geometric model by observation of Magnetic Resonance Imaging data, providing a new method to annotate and construct 3D vocal tract organs. The proposed method has two advantages compared with previous methods. Firstly it has a… More >

  • Open Access

    ARTICLE

    Visualization Techniques via MLBS for Personnel Management in Major Events

    Yu Su1,2,3, Lingjuan Hou2,3,*, Sinan Li1, Zhaochang Jiang1, Haoran Peng4

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 521-536, 2023, DOI:10.32604/csse.2022.028606

    Abstract Mobile location-based services (MLBS) refer to services around geographic location data. Mobile terminals use wireless communication networks (or satellite positioning systems) to obtain users’ geographic location coordinate information based on spatial databases and integrate with other information to provide users with required location-related services. The development of systems based on MLBS has significance and practical value. In this paper a visualization management information system for personnel in major events based on microservices, namely MEPMIS, is designed and implemented by using MLBS. The system consists of a server and a client app, and it has some functions including map search and… More >

  • Open Access

    ARTICLE

    A Derivative Matrix-Based Covert Communication Method in Blockchain

    Xiang Zhang1, Xiaona Zhang2,4,*, Xiaorui Zhang3,5,6, Wei Sun6,7, Ruohan Meng8, Xingming Sun1

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 225-239, 2023, DOI:10.32604/csse.2023.034915

    Abstract The data in the blockchain cannot be tampered with and the users are anonymous, which enables the blockchain to be a natural carrier for covert communication. However, the existing methods of covert communication in blockchain suffer from the predefined channel structure, the capacity of a single transaction is not high, and the fixed transaction behaviors will lower the concealment of the communication channel. Therefore, this paper proposes a derivation matrix-based covert communication method in blockchain. It uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full… More >

  • Open Access

    ARTICLE

    Lens-Oppositional Wild Geese Optimization Based Clustering Scheme for Wireless Sensor Networks Assists Real Time Disaster Management

    R. Surendran1,*, Youseef Alotaibi2, Ahmad F. Subahi3

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 835-851, 2023, DOI:10.32604/csse.2023.036757

    Abstract Recently, wireless sensor networks (WSNs) find their applicability in several real-time applications such as disaster management, military, surveillance, healthcare, etc. The utilization of WSNs in the disaster monitoring process has gained significant attention among research communities and governments. Real-time monitoring of disaster areas using WSN is a challenging process due to the energy-limited sensor nodes. Therefore, the clustering process can be utilized to improve the energy utilization of the nodes and thereby improve the overall functioning of the network. In this aspect, this study proposes a novel Lens-Oppositional Wild Goose Optimization based Energy Aware Clustering (LOWGO-EAC) scheme for WSN-assisted real-time… More >

  • Open Access

    ARTICLE

    A Cross-Plane Color Image Encryption Algorithm Based on 1D-SLM

    Xiaohong Wang, Huiqing Wu, Yuying Ma, Shuzhen Huang*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1093-1108, 2023, DOI:10.32604/csse.2023.036652

    Abstract With the rapid development of 5G technology, it has become fast and easy for people to transmit information on the Internet. Digital images can express information more intuitively, so transmitting information through images has excellent applications. This paper uses a new chaotic system called 1D-Sin-Logistic-Map (1D-SLM). 1D-SLM has two control parameters, which can provide larger parameter space, and the parameter space in the chaotic state is continuous. Through Lyapunov exponent analysis (LE), bifurcation diagrams analysis, spectral entropy analysis (SE), and 0-1 test, it is verified that 1D-SLM has complex dynamic behavior and is very suitable for cryptography. Compared with other… More >

  • Open Access

    ARTICLE

    Enhanced Best Fit Algorithm for Merging Small Files

    Adnan Ali1, Nada Masood Mirza1,2, Mohamad Khairi Ishak1,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 913-928, 2023, DOI:10.32604/csse.2023.036400

    Abstract In the Big Data era, numerous sources and environments generate massive amounts of data. This enormous amount of data necessitates specialized advanced tools and procedures that effectively evaluate the information and anticipate decisions for future changes. Hadoop is used to process this kind of data. It is known to handle vast volumes of data more efficiently than tiny amounts, which results in inefficiency in the framework. This study proposes a novel solution to the problem by applying the Enhanced Best Fit Merging algorithm (EBFM) that merges files depending on predefined parameters (type and size). Implementing this algorithm will ensure that… More >

  • Open Access

    ARTICLE

    A Lightweight Electronic Water Pump Shell Defect Detection Method Based on Improved YOLOv5s

    Qunbiao Wu1, Zhen Wang1,*, Haifeng Fang1, Junji Chen1, Xinfeng Wan2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 961-979, 2023, DOI:10.32604/csse.2023.036239

    Abstract For surface defects in electronic water pump shells, the manual detection efficiency is low, prone to misdetection and leak detection, and encounters problems, such as uncertainty. To improve the speed and accuracy of surface defect detection, a lightweight detection method based on an improved YOLOv5s method is proposed to replace the traditional manual detection methods. In this method, the MobileNetV3 module replaces the backbone network of YOLOv5s, depth-separable convolution is introduced, the parameters and calculations are reduced, and CIoU_Loss is used as the loss function of the boundary box regression to improve its detection accuracy. A dataset of electronic pump… More >

  • Open Access

    ARTICLE

    An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

    Ahmed Ben Atitallah1,*, Mohamed Amin Ben Atitallah2,3, Yahia Said4,5, Mohammed Albekairi1, Anis Boudabous6, Turki M. Alanazi1, Khaled Kaaniche1, Mohamed Atri7

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 701-717, 2023, DOI:10.32604/csse.2023.035871

    Abstract The challenge faced by the visually impaired persons in their day-to-day lives is to interpret text from documents. In this context, to help these people, the objective of this work is to develop an efficient text recognition system that allows the isolation, the extraction, and the recognition of text in the case of documents having a textured background, a degraded aspect of colors, and of poor quality, and to synthesize it into speech. This system basically consists of three algorithms: a text localization and detection algorithm based on mathematical morphology method (MMM); a text extraction algorithm based on the gamma… More >

  • Open Access

    ARTICLE

    Innovative Hetero-Associative Memory Encoder (HAMTE) for Palmprint Template Protection

    Eslam Hamouda1, Mohamed Ezz1,*, Ayman Mohamed Mostafa1, Murtada K. Elbashir1, Meshrif Alruily1, Mayada Tarek2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 619-636, 2023, DOI:10.32604/csse.2023.035830

    Abstract Many types of research focus on utilizing Palmprint recognition in user identification and authentication. The Palmprint is one of biometric authentication (something you are) invariable during a person’s life and needs careful protection during enrollment into different biometric authentication systems. Accuracy and irreversibility are critical requirements for securing the Palmprint template during enrollment and verification. This paper proposes an innovative HAMTE neural network model that contains Hetero-Associative Memory for Palmprint template translation and projection using matrix multiplication and dot product multiplication. A HAMTE-Siamese network is constructed, which accepts two Palmprint templates and predicts whether these two templates belong to the… More >

  • Open Access

    ARTICLE

    Discharge Summaries Based Sentiment Detection Using Multi-Head Attention and CNN-BiGRU

    Samer Abdulateef Waheeb*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 981-998, 2023, DOI:10.32604/csse.2023.035753

    Abstract Automatic extraction of the patient’s health information from the unstructured data concerning the discharge summary remains challenging. Discharge summary related documents contain various aspects of the patient health condition to examine the quality of treatment and thereby help improve decision-making in the medical field. Using a sentiment dictionary and feature engineering, the researchers primarily mine semantic text features. However, choosing and designing features requires a lot of manpower. The proposed approach is an unsupervised deep learning model that learns a set of clusters embedded in the latent space. A composite model including Active Learning (AL), Convolutional Neural Network (CNN), BiGRU,… More >

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