Open Access
ARTICLE
Wadhah Mohammed M. Aqlan1, Ghassan Ahmed Ali2,*, Khairan Rajab2, Adel Rajab2, Asadullah Shaikh2, Fekry Olayah2, Shehab Abdulhabib Saeed Alzaeemi3,*, Kim Gaik Tay3, Mohd Adib Omar1, Ernest Mangantig4
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.039228
Abstract Thalassemia syndrome is a genetic blood disorder induced by the
reduction of normal hemoglobin production, resulting in a drop in the size of
red blood cells. In severe forms, it can lead to death. This genetic disorder
has posed a major burden on public health wherein patients with severe
thalassemia need periodic therapy of iron chelation and blood transfusion
for survival. Therefore, controlling thalassemia is extremely important and is
made by promoting screening to the general population, particularly among
thalassemia carriers. Today Twitter is one of the most influential social media
platforms for sharing opinions and discussing different topics like… More >
Open Access
ARTICLE
Pingping Li*, Jiuxin Cao
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.039076
Abstract Virtual machine (VM) consolidation is an effective way to improve
resource utilization and reduce energy consumption in cloud data centers.
Most existing studies have considered VM consolidation as a bin-packing
problem, but the current schemes commonly ignore the long-term relationship
between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in
unnecessary VM migration and increased energy consumption. To address
these limitations, a VM consolidation method based on multi-step prediction
and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed method uses an improved linear… More >
Open Access
ARTICLE
Huaxin Zhou1,2, Ziying Fang3, Yilin Wang4, Mengjun Tong1,2,*
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.037342
Abstract Plant diseases have become a challenging threat in the agricultural
field. Various learning approaches for plant disease detection and classification have been adopted to detect and diagnose these diseases early. However,
deep learning entails extensive data for training, and it may be challenging
to collect plant datasets. Even though plant datasets can be collected, they
may be uneven in quantity. As a result, the problem of classification model
overfitting arises. This study targets this issue and proposes an auxiliary
classifier GAN (small-ACGAN) model based on a small number of datasets
to extend the available data. First, after comparing various attention… More >
Open Access
ARTICLE
Sara Khalid1, Jamal Hussain Shah1,*, Muhammad Sharif1, Muhammad Rafiq2, Gyu Sang Choi3,*
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.035595
Abstract Globally traffic signs are used by all countries for healthier traffic
flow and to protect drivers and pedestrians. Consequently, traffic signs have
been of great importance for every civilized country, which makes researchers
give more focus on the automatic detection of traffic signs. Detecting these
traffic signs is challenging due to being in the dark, far away, partially
occluded, and affected by the lighting or the presence of similar objects. An
innovative traffic sign detection method for red and blue signs in color images
is proposed to resolve these issues. This technique aimed to devise an efficient,
robust and accurate… More >
Open Access
ARTICLE
Ali Haider Khan1,2,*, Hassaan Malik2, Wajeeha Khalil3, Sayyid Kamran Hussain4, Tayyaba Anees5, Muzammil Hussain2
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.039518
Abstract To prevent irreversible damage to one’s eyesight, ocular diseases
(ODs) need to be recognized and treated immediately. Color fundus imaging
(CFI) is a screening technology that is both effective and economical. According to CFIs, the early stages of the disease are characterized by a paucity of
observable symptoms, which necessitates the prompt creation of automated
and robust diagnostic algorithms. The traditional research focuses on imagelevel diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of eyes. In addition,
they usually only target one or a few different… More >
Open Access
ARTICLE
Jeongha Lee1, Hyokyung Bahn2,*
CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2023.039236
Abstract Due to the recent trend of software intelligence in the Fourth
Industrial Revolution, deep learning has become a mainstream workload for
modern computer systems. Since the data size of deep learning increasingly
grows, managing the limited memory capacity efficiently for deep learning
workloads becomes important. In this paper, we analyze memory accesses
in deep learning workloads and find out some unique characteristics differentiated from traditional workloads. First, when comparing instruction and
data accesses, data access accounts for 96%–99% of total memory accesses in
deep learning workloads, which is quite different from traditional workloads.
Second, when comparing read and write accesses,… More >
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