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Mohamed A. Meselhi^*, Saber M. Elsayed, Daryl L. Essam, Ruhul A. Sarker
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.027448
Abstract Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instances can be infeasible due to various practical issues, such as a sudden change in resource requirements or a big change in the availability of resources. Decision-makers have to determine whether a particular instance is feasible or not, as infeasible instances cannot be solved as there are no solutions to implement. In this case, locating the nearest feasible solution would be valuable information for the decision-makers.… More >

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Motasem S. Alsawadi^1,*, El-Sayed M. El-kenawy^2,3, Miguel Rio¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 19-36, 2023, DOI:10.32604/cmc.2023.032499
Abstract The ever-growing available visual data (i.e., uploaded videos and pictures by internet users) has attracted the research community's attention in the computer vision field. Therefore, finding efficient solutions to extract knowledge from these sources is imperative. Recently, the BlazePose system has been released for skeleton extraction from images oriented to mobile devices. With this skeleton graph representation in place, a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action. We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of interest, it is possible to… More >

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718

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Mingsen Mo¹, Shan Ji², Xiaowan Wang^3,*, Ghulam Mohiuddin⁴, Yongjun Ren¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 37-53, 2023, DOI:10.32604/cmc.2023.028843
Abstract Due to the extensive use of various intelligent terminals and the popularity of network social tools, a large amount of data in the field of medical emerged. How to manage these massive data safely and reliably has become an important challenge for the medical network community. This paper proposes a data management framework of medical network community based on Consortium Blockchain (CB) and Federated learning (FL), which realizes the data security sharing between medical institutions and research institutions. Under this framework, the data security sharing mechanism of medical network community based on smart contract and the data privacy protection mechanism… More >

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646

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Sung Won Hwang, Dae-Ki Hong^*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 55-66, 2023, DOI:10.32604/cmc.2023.028845
Abstract The use a stabilized lithium structure as cathode material for batteries could be a fundamental alternative in the development of next-generation energy storage devices. However, the lithium structure severely limits battery life causes safety concerns due to the growth of lithium (Li) dendrites during rapid charge/discharge cycles. Solid electrolytes, which are used in high-density energy storage devices and avoid the instability of liquid electrolytes, can be a promising alternative for next-generation batteries. Nevertheless, poor lithium ion conductivity and structural defects at room temperature have been pointed out as limitations. In this study, through the application of a low-dimensional graphene quantum… More >

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Jiang Wu¹, Jianjun Zhang¹, Wenwu Tan¹, Hao Lan^1,*, Sirao Zhang¹, Ke Xiao², Li Wang², Haijun Lin¹, Guang Sun³, Peng Guo⁴
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 67-82, 2023, DOI:10.32604/cmc.2023.030703
Abstract Water resources are an indispensable and valuable resource for human survival and development. Water quality predicting plays an important role in the protection and development of water resources. It is difficult to predict water quality due to its random and trend changes. Therefore, a method of predicting water quality which combines Auto Regressive Integrated Moving Average (ARIMA) and clustering model was proposed in this paper. By taking the water quality monitoring data of a certain river basin as a sample, the water quality Total Phosphorus (TP) index was selected as the prediction object. Firstly, the sample data was cleaned, stationary… More >

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Chih-Ta Yen^1,*, Tz-Yun Chen², Un-Hung Chen³, Guo-Chang Wang³, Zong-Xian Chen³
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 83-99, 2023, DOI:10.32604/cmc.2023.032739
Abstract A system for classifying four basic table tennis strokes using wearable devices and deep learning networks is proposed in this study. The wearable device consisted of a six-axis sensor, Raspberry Pi 3, and a power bank. Multiple kernel sizes were used in convolutional neural network (CNN) to evaluate their performance for extracting features. Moreover, a multiscale CNN with two kernel sizes was used to perform feature fusion at different scales in a concatenated manner. The CNN achieved recognition of the four table tennis strokes. Experimental data were obtained from 20 research participants who wore sensors on the back of their… More >

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521

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Ziquan Zhu¹, Muhammad Attique Khan², Shui-Hua Wang¹, Yu-Dong Zhang^1,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 101-111, 2023, DOI:10.32604/cmc.2023.030790
Abstract Brain tumor refers to the formation of abnormal cells in the brain. It can be divided into benign and malignant. The main diagnostic methods for brain tumors are plain X-ray film, Magnetic resonance imaging (MRI), and so on. However, these artificial diagnosis methods are easily affected by external factors. Scholars have made such impressive progress in brain tumors classification by using convolutional neural network (CNN). However, there are still some problems: (i) There are many parameters in CNN, which require much calculation. (ii) The brain tumor data sets are relatively small, which may lead to the overfitting problem in CNN.… More >

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549

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Ümit Işıkdağ¹, Aycan Hepsağ², Süreyya İmre Bıyıklı³, Derya Öz⁴, Gebrail Bekdaş⁵, Zong Woo Geem^6,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 113-129, 2023, DOI:10.32604/cmc.2023.032502
Abstract Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to… More >

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Xianhui Gu^1,*, Xiaokan Wang¹, Shuang Liang²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 131-139, 2023, DOI:10.32604/cmc.2023.028756
Abstract In order to solve the defect of large error in current employment quality evaluation, an employment quality evaluation model based on grey correlation degree method and fuzzy C-means (FCM) is proposed. Firstly, it analyzes the related research work of employment quality evaluation, establishes the employment quality evaluation index system, collects the index data, and normalizes the index data; Then, the weight value of employment quality evaluation index is determined by Grey relational analysis method, and some unimportant indexes are removed; Finally, the employment quality evaluation model is established by using fuzzy cluster analysis algorithm, and compared with other employment quality… More >

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491

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Nidhi Agarwal^1,2, M. Gokilavani³, S. Nagarajan⁴, S. Saranya⁵, Hadeel Alsolai⁶, Sami Dhahbi^7,*, Amira Sayed Abdelaziz⁸
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 141-152, 2023, DOI:10.32604/cmc.2023.030074
Abstract In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes in WSN are placed arbitrarily in the target field, node localization (NL) becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes. The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate. With this motivation, this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme (IAOAB-NLS) for WSN. The presented IAOAB-NLS model makes use of anchor nodes to… More >

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Hasan H. Al-Khshali^1,*, Muhammad Ilyas²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 153-178, 2023, DOI:10.32604/cmc.2023.032182
Abstract One aspect of cybersecurity, incorporates the study of Portable Executables (PE) files maleficence. Artificial Intelligence (AI) can be employed in such studies, since AI has the ability to discriminate benign from malicious files. In this study, an exclusive set of 29 features was collected from trusted implementations, this set was used as a baseline to analyze the presented work in this research. A Decision Tree (DT) and Neural Network Multi-Layer Perceptron (NN-MLPC) algorithms were utilized during this work. Both algorithms were chosen after testing a few diverse procedures. This work implements a method of subgrouping features to answer questions such… More >

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Hadi Givi¹, Marie Hubalovska^2,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 179-202, 2023, DOI:10.32604/cmc.2023.030379
Abstract Metaheuristic algorithms are widely used in solving optimization problems. In this paper, a new metaheuristic algorithm called Skill Optimization Algorithm (SOA) is proposed to solve optimization problems. The fundamental inspiration in designing SOA is human efforts to acquire and improve skills. Various stages of SOA are mathematically modeled in two phases, including: (i) exploration, skill acquisition from experts and (ii) exploitation, skill improvement based on practice and individual effort. The efficiency of SOA in optimization applications is analyzed through testing this algorithm on a set of twenty-three standard benchmark functions of a variety of unimodal, high-dimensional multimodal, and fixed-dimensional multimodal… More >

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Muhammad Imran^1,*, Hafeez Anwar², Muhammad Tufail¹, Abdullah Khan¹, Murad Khan³, Dzati Athiar Ramli⁴
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 203-216, 2023, DOI:10.32604/cmc.2023.029834
Abstract We propose to perform an image-based framework for electrical energy meter reading. Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units. Combining the readings of serial numbers and energy meter units, an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup. However, such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display, orientation and scale variations caused by camera positioning, and… More >

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476

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Mazen Mushabab Alqahtani¹, Ashit Kumar Dutta², Sultan Almotairi³, M. Ilayaraja⁴, Amani Abdulrahman Albraikan⁵, Fahd N. Al-Wesabi^6,7,*, Mesfer Al Duhayyim⁸
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 217-233, 2023, DOI:10.32604/cmc.2023.025280
Abstract Recent developments in digital cameras and electronic gadgets coupled with Machine Learning (ML) and Deep Learning (DL)-based automated apple leaf disease detection models are commonly employed as reasonable alternatives to traditional visual inspection models. In this background, the current paper devises an Effective Sailfish Optimizer with EfficientNet-based Apple Leaf disease detection (ESFO-EALD) model. The goal of the proposed ESFO-EALD technique is to identify the occurrence of plant leaf diseases automatically. In this scenario, Median Filtering (MF) approach is utilized to boost the quality of apple plant leaf images. Moreover, SFO with Kapur's entropy-based segmentation technique is also utilized for the… More >

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467

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Binhui Tang^1,3, Junfeng Wang^2,*, Huanran Qiu³, Jian Yu², Zhongkun Yu², Shijia Liu^2,4
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 235-252, 2023, DOI:10.32604/cmc.2023.029135
Abstract The continuous improvement of the cyber threat intelligence sharing mechanism provides new ideas to deal with Advanced Persistent Threats (APT). Extracting attack behaviors, i.e., Tactics, Techniques, Procedures (TTP) from Cyber Threat Intelligence (CTI) can facilitate APT actors’ profiling for an immediate response. However, it is difficult for traditional manual methods to analyze attack behaviors from cyber threat intelligence due to its heterogeneous nature. Based on the Adversarial Tactics, Techniques and Common Knowledge (ATT&CK) of threat behavior description, this paper proposes a threat behavioral knowledge extraction framework that integrates Heterogeneous Text Network (HTN) and Graph Convolutional Network (GCN) to solve this… More >

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Salaheddine Kably^1,2,*, Tajeddine Benbarrad¹, Nabih Alaoui², Mounir Arioua¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 253-278, 2023, DOI:10.32604/cmc.2023.032220
Abstract Blockchain merges technology with the Internet of Things (IoT) for addressing security and privacy-related issues. However, conventional blockchain suffers from scalability issues due to its linear structure, which increases the storage overhead, and Intrusion detection performed was limited with attack severity, leading to performance degradation. To overcome these issues, we proposed MZWB (Multi-Zone-Wise Blockchain) model. Initially, all the authenticated IoT nodes in the network ensure their legitimacy by using the Enhanced Blowfish Algorithm (EBA), considering several metrics. Then, the legitimately considered nodes for network construction for managing the network using Bayesian-Direct Acyclic Graph (B-DAG), which considers several metrics. The intrusion… More >

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9

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Iftikhar Ahmad^1,*, Ambreen Shahnaz², Muhammad Asfand-e-Yar³, Wajeeha Khalil¹, Yasmin Bano¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 279-291, 2023, DOI:10.32604/cmc.2023.031344
Abstract The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be… More >

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Jiangyuan Yao¹, Zheng Jiang², Kaiwen Zou², Shuhua Weng¹, Yaxin Li³, Deshun Li¹, Yahui Li^4,*, Xingcan Cao⁵
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 293-311, 2023, DOI:10.32604/cmc.2023.031282
Abstract With the expansion of network services, large-scale networks have progressively become common. The network status changes rapidly in response to customer needs and configuration changes, so network configuration changes are also very frequent. However, no matter what changes, the network must ensure the correct conditions, such as isolating tenants from each other or guaranteeing essential services. Once changes occur, it is necessary to verify the after-changed network. Whereas, for the verification of large-scale network configuration changes, many current verifiers show poor efficiency. In order to solve the problem of multiple global verifications caused by frequent updates of local configurations in… More >

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Azuwa Ali¹, Mohd Najib Mohd Yasin^2,*, Ismahayati Adam², Ali H. Rambe³, Mohd Haizal Jamaludin⁴, Hasliza A Rahim², Corhan Cengiz⁵, Mohd Ibrahim Shapiai Abd. Razak⁶
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 313-325, 2023, DOI:10.32604/cmc.2023.031706
Abstract This paper proposes a new dielectric resonator antenna (DRA) design that can generate circularly polarized (CP) triple-band signals. A triple-band CP DRA antenna fed by a probe feed system is achieved with metal strips structure on side of DRA structure. The design start with conventional rectangular DRA with F shaped metal strips on DRA structure alongside the feed. Then, the F metal strip is enhanced by extending the length of the metal strip to obtain wider impedance bandwidth. Further improvement on the antenna performance is observed by improvised the conventional DRA structure. The method of removing part of DRA bottom… More >

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Saif Saad Hameed, Ismail Taha Ahmed^*, Omar Munthir Al Okashi
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 327-340, 2023, DOI:10.32604/cmc.2023.031622
Abstract Biometric recognition refers to the identification of individuals through their unique behavioral features (e.g., fingerprint, face, and iris). We need distinguishing characteristics to identify people, such as fingerprints, which are world-renowned as the most reliable method to identify people. The recognition of fingerprints has become a standard procedure in forensics, and different techniques are available for this purpose. Most current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification models. Therefore, we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints… More >

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Ankush Kapoor¹, Pradeep Kumar^2,*, Ranjan Mishra³
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 341-361, 2023, DOI:10.32604/cmc.2023.028874
Abstract Frequency selective surfaces (FSSs) play an important role in wireless systems as these can be used as filters, in isolating the unwanted radiation, in microstrip patch antennas for improving the performance of these antennas and in other 5G applications. The analysis and design of the double concentric ring frequency selective surface (DCRFSS) is presented in this research. In the sub-6 GHz 5G FR1 spectrum, a computational synthesis technique for creating DCRFSS based spatial filters is proposed. The analytical tools presented in this study can be used to gain a better understanding of filtering processes and for constructing the spatial filters.… More >

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508

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Khalid Hamid¹, Muhammad Waseem Iqbal^2,*, Muhammad Usman Ashraf³, Ahmed Mohammed Alghamdi⁴, Adel A. Bahaddad⁵, Khalid Ali Almarhabi⁶
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 363-378, 2023, DOI:10.32604/cmc.2023.032271
Abstract Due to a tremendous increase in mobile traffic, mobile operators have started to restructure their networks to offload their traffic. New research directions will lead to fundamental changes in the design of future Fifth-generation (5G) cellular networks. For the formal reason, the study solves the physical network of the mobile base station for the prediction of the best characteristics to develop an enhanced network with the help of graph theory. Any number that can be uniquely calculated by a graph is known as a graph invariant. During the last two decades, innumerable numerical graph invariants have been portrayed and used… More >

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Edgar Scavino^1,*, Mohd Amiruddin Abd Rahman¹, Zahid Farid²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 379-397, 2023, DOI:10.32604/cmc.2023.023824
Abstract Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received… More >

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Nora Abdullah Alkhaldi^1,*, Hanan T. Halawani²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 399-414, 2023, DOI:10.32604/cmc.2023.030872
Abstract Automated segmentation of blood vessels in retinal fundus images is essential for medical image analysis. The segmentation of retinal vessels is assumed to be essential to the progress of the decision support system for initial analysis and treatment of retinal disease. This article develops a new Grasshopper Optimization with Fuzzy Edge Detection based Retinal Blood Vessel Segmentation and Classification (GOFED-RBVSC) model. The proposed GOFED-RBVSC model initially employs contrast enhancement process. Besides, GOAFED approach is employed to detect the edges in the retinal fundus images in which the use of GOA adjusts the membership functions. The ORB (Oriented FAST and Rotated… More >

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434

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M. A. Fazlina, Rohaya Latip^*, Hamidah Ibrahim, Azizol Abdullah
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 415-433, 2023, DOI:10.32604/cmc.2023.020764
Abstract As the amount of data continues to grow rapidly, the variety of data produced by applications is becoming more affluent than ever. Cloud computing is the best technology evolving today to provide multi-services for the mass and variety of data. The cloud computing features are capable of processing, managing, and storing all sorts of data. Although data is stored in many high-end nodes, either in the same data centers or across many data centers in cloud, performance issues are still inevitable. The cloud replication strategy is one of best solutions to address risk of performance degradation in the cloud environment.… More >

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Ahyoung Lee¹, Jui Mhatre¹, Rupak Kumar Das², Min Hong^3,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 435-452, 2023, DOI:10.32604/cmc.2023.029340
Abstract Healthcare is a fundamental part of every individual’s life. The healthcare industry is developing very rapidly with the help of advanced technologies. Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises, as well as by patients from their mobile devices through communication interfaces. These systems promote reliable and remote interactions between patients and healthcare professionals. However, there are several limitations to these innovative cloud computing-based systems, namely network availability, latency, battery life and resource availability. We propose a hybrid mobile cloud computing (HMCC) architecture to address these challenges. Furthermore, we… More >

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Mohamed Amine Ouamri^1,2, Reem Alkanhel^3,*, Cedric Gueguen¹, Manal Abdullah Alohali⁴, Sherif S. M. Ghoneim⁵
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 453-467, 2023, DOI:10.32604/cmc.2023.031450
Abstract With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed… More >

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Xiaoting Liang¹, Fang Liu^1,*, Linqi Wang¹, Baoying Zheng¹, Yiyuan Sun²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 469-488, 2023, DOI:10.32604/cmc.2023.029641
Abstract Driven by the visions of the Internet of Things (IoT), Artificial Intelligence (AI), and 5G communications, the Internet of Cultural Things (IoCT) realize the comprehensive interconnection among cultural products, cultural services, cultural resources, and cultural platforms, bringing individuals with richer humanistic experience, increasing economic benefits for the cultural sector, and promoting the development of cultural heritage protection and education. At present, IoCT has received widespread attention in both industry and academia. To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications, this survey provides a comprehensive overview of the IoCT components and key technologies.… More >

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Farhan Amin¹, Omar M. Barukab², Gyu Sang Choi^1,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 489-502, 2023, DOI:10.32604/cmc.2023.030615
Abstract The networks are fundamental to our modern world and they appear throughout science and society. Access to a massive amount of data presents a unique opportunity to the researcher’s community. As networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep pace. Therefore, this paper initiates a discussion on graph signal processing for large-scale data analysis. We first provide a comprehensive overview of core ideas in Graph signal processing (GSP) and their connection to conventional digital signal processing (DSP). We then summarize… More >

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Komsan Kanjanasit¹, Pracha Osklang^2,*, Terapass Jariyanorawiss³, Akkarat Boonpoonga⁴, Chuwong Phongcharoenpanich⁵
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 503-522, 2023, DOI:10.32604/cmc.2023.032427
Abstract A 5G wireless system requests a high-performance compact antenna device. This research work aims to report the characterization and verification of the artificial magnetic conductor (AMC) metamaterial for a high-gain planar antenna. The configuration is formed by a double-side structure on an intrinsic dielectric slab. The 2-D periodic pattern as an impedance surface is mounted on the top surface, whereas at the bottom surface the ground plane with an inductive narrow aperture source is embedded. The characteristic of the resonant transmission is illustrated based on the electromagnetic virtual object of the AMC resonant structure to reveal the unique property of… More >

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Sameena Javaid^*, Safdar Rizvi
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 523-537, 2023, DOI:10.32604/cmc.2023.031924
Abstract Sign language fills the communication gap for people with hearing and speaking ailments. It includes both visual modalities, manual gestures consisting of movements of hands, and non-manual gestures incorporating body movements including head, facial expressions, eyes, shoulder shrugging, etc. Previously both gestures have been detected; identifying separately may have better accuracy, but much communicational information is lost. A proper sign language mechanism is needed to detect manual and non-manual gestures to convey the appropriate detailed message to others. Our novel proposed system contributes as Sign Language Action Transformer Network (SLATN), localizing hand, body, and facial gestures in video sequences. Here… More >

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Dur-e-Jabeen^1,*, Tahmina Khan², Rumaisa Iftikhar¹, Ali Akbar Siddique¹, Samiya Asghar¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 539-557, 2023, DOI:10.32604/cmc.2023.032393
Abstract In recent years, it has been evident that internet is the most effective means of transmitting information in the form of documents, photographs, or videos around the world. The purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual quality. During transmission, this massive data necessitates a lot of channel space. In order to overcome this problem, an effective visual compression approach is required to resize this large amount of data. This work is based on lossy image compression and is offered for static color images. The quantization procedure determines… More >

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Thongchai Botmart¹, Qusain Hiader², Zulqurnain Sabir³, Muhammad Asif Zahoor Raja⁴, Wajaree Weera^1,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 559-573, 2023, DOI:10.32604/cmc.2023.031871
Abstract The goal of this research is to introduce the simulation studies of the vector-host disease nonlinear system (VHDNS) along with the numerical treatment of artificial neural networks (ANNs) techniques supported by Levenberg-Marquardt backpropagation (LMQBP), known as ANNs-LMQBP. This mechanism is physically appropriate, where the number of infected people is increasing along with the limited health services. Furthermore, the biological effects have fading memories and exhibit transition behavior. Initially, the model is developed by considering the two and three categories for the humans and the vector species. The VHDNS is constructed with five classes, susceptible humans , infected humans , recovered… More >

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Jasurbek Gulomov^1,*, Oussama Accouche², Rayimjon Aliev¹, Marc AZAB², Irodakhon Gulomova¹
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 575-590, 2023, DOI:10.32604/cmc.2023.031289
Abstract Today, it has become an important task to modify existing traditional silicon-based solar cell factory to produce high-efficiency silicon-based heterojunction solar cells, at a lower cost. Therefore, the aim of this paper is to analyze CH₃NH₃PbI₃ and ZnO materials as an emitter layer for p-type silicon wafer-based heterojunction solar cells. CH₃NH₃PbI₃ and ZnO can be synthesized using the cheap Sol-Gel method and can form n-type semiconductor. We propose to combine these two materials since CH₃NH₃PbI₃ is a great light absorber and ZnO has an optimal complex refractive index which can be used as antireflection material. The photoelectric parameters of n-CH₃NH₃PbI₃/p-Si,… More >

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Mushtaq Niazi¹, Sagheer Abbas¹, Abdel-Hamid Soliman², Tahir Alyas³, Shazia Asif⁴, Tauqeer Faiz^5,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 591-606, 2023, DOI:10.32604/cmc.2023.032474
Abstract Kubernetes is an open-source container management tool which automates container deployment, container load balancing and container(de)scaling, including Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA). HPA enables flawless operation, interactively scaling the number of resource units, or pods, without downtime. Default Resource Metrics, such as CPU and memory use of host machines and pods, are monitored by Kubernetes. Cloud Computing has emerged as a platform for individuals beside the corporate sector. It provides cost-effective infrastructure, platform and software services in a shared environment. On the other hand, the emergence of industry 4.0 brought new challenges for the adaptability and infusion… More >

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Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Mohamed K. Nour⁴, Mashael M. Asiri⁵, Ali M. Al-Sharafi⁶, Mahmoud Othman⁷, Abdelwahed Motwakel²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 607-621, 2023, DOI:10.32604/cmc.2023.031371
Abstract Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation,… More >

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Farah Mohammad^*, Saad Al-Ahmadi
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 623-639, 2023, DOI:10.32604/cmc.2023.032552
Abstract

There exists various neurological disorder based diseases like tumor, sleep disorder, headache, dementia and Epilepsy. Among these, epilepsy is the most common neurological illness in humans, comparable to stroke. Epilepsy is a severe chronic neurological illness that can be discovered through analysis of the signals generated by brain neurons and brain Magnetic resonance imaging (MRI). Neurons are intricately coupled in order to communicate and generate signals from human organs. Due to the complex nature of electroencephalogram (EEG) signals and MRI’s the epileptic seizures detection and brain related problems diagnosis becomes a challenging task. Computer based techniques and machine learning models… More >

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Kun Ding¹, Lu Xu², Ming Liu¹, Xiaoxiong Zhang¹, Liu Liu¹, Daojian Zeng^2,*, Yuting Liu^1,3, Chen Jin⁴
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 641-654, 2023, DOI:10.32604/cmc.2023.031052
Abstract Event detection (ED) is aimed at detecting event occurrences and categorizing them. This task has been previously solved via recognition and classification of event triggers (ETs), which are defined as the phrase or word most clearly expressing event occurrence. Thus, current approaches require both annotated triggers as well as event types in training data. Nevertheless, triggers are non-essential in ED, and it is time-wasting for annotators to identify the “most clearly” word from a sentence, particularly in longer sentences. To decrease manual effort, we evaluate event detection without triggers. We propose a novel framework that combines Type-aware Attention and Graph… More >

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Divya Sharma^1,*, Sanjay Jain², Vivek Maik³
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 655-669, 2023, DOI:10.32604/cmc.2023.032207
Abstract Security is the one of the major challenges for routing the data between the source and destination in an Internet of Things (IoT) network. To overcome this challenge, a secure Lightweight On-demand Ad hoc Distance-vector—Next Generation (LOADng) Routing Protocol is proposed in this paper. As the LOADng protocol is the second version of Ad Hoc On-Demand Distance Vector (AODV) protocol, it retains most of the basic functionality and characteristics of AODV. During the route discovery process, the cyclic shift transposition algorithm (CSTA) is used to encrypt the control packets of the LOADng protocol to improve its security. CSTA approach only… More >

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413

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ARTICLE

Ahmed Abdulhakim Al-Absi¹, Dae-Ki Kang^2,*, Mohammed Abdulhakim Al-Absi³
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 671-691, 2023, DOI:10.32604/cmc.2023.030262
Abstract Sentiment analysis (AS) is one of the basic research directions in natural language processing (NLP), it is widely adopted for news, product review, and politics. Aspect-based sentiment analysis (ABSA) aims at identifying the sentiment polarity of a given target context, previous existing model of sentiment analysis possesses the issue of the insufficient exaction of features which results in low accuracy. Hence this research work develops a deep-semantic and contextual knowledge networks (DSCNet). DSCNet tends to exploit the semantic and contextual knowledge to understand the context and enhance the accuracy based on given aspects. At first temporal relationships are established then… More >

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Khlood Shinan^1,2, Khalid Alsubhi², M. Usman Ashraf^3,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 693-714, 2023, DOI:10.32604/cmc.2023.031641
Abstract The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet. Bot detection using machine learning (ML) with flow-based features has been extensively studied in the literature. Existing flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features of malicious hosts. Recently, Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations, as graphs provide a real representation of network communications. The purpose of this study is to build a botnet… More >

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440

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Zahraa Tarek¹, Mahmoud Y. Shams^2,*, Ahmed M. Elshewey³, El-Sayed M. El-kenawy^4,5, Abdelhameed Ibrahim⁶, Abdelaziz A. Abdelhamid^7,8, Mohamed A. El-dosuky^1,9
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 715-732, 2023, DOI:10.32604/cmc.2023.032533
Abstract Wind power is one of the sustainable ways to generate renewable energy. In recent years, some countries have set renewables to meet future energy needs, with the primary goal of reducing emissions and promoting sustainable growth, primarily the use of wind and solar power. To achieve the prediction of wind power generation, several deep and machine learning models are constructed in this article as base models. These regression models are Deep neural network (DNN), k-nearest neighbor (KNN) regressor, long short-term memory (LSTM), averaging model, random forest (RF) regressor, bagging regressor, and gradient boosting (GB) regressor. In addition, data cleaning and… More >

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Salwa M. Serag Eldin^1,*, Ahmed Sedik², Sultan S. Alshamrani³, Ahmed M. Ayoup⁴
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 733-749, 2023, DOI:10.32604/cmc.2023.030789
Abstract In this paper, a novel cancellable biometrics technique called Multi-Biometric-Feature-Hashing (MBFH) is proposed. The MBFH strategy is utilized to actualize a single direction (non-invertibility) biometric shape. MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies (retina, palm print, Hand Dorsum, fingerprint). A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources. This may raise worries about their utilization and security when these spread out designs are subverted as… More >

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Fatemeh Sadeghi¹, Omid Rostami², Myung-Kyu Yi³, Seong Oun Hwang^3,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 751-768, 2023, DOI:10.32604/cmc.2023.031519
Abstract Real-time detection of Covid-19 has definitely been the most widely-used world-wide classification problem since the start of the pandemic from 2020 until now. In the meantime, airspace opacities spreads related to lung have been of the most challenging problems in this area. A common approach to do on that score has been using chest X-ray images to better diagnose positive Covid-19 cases. Similar to most other classification problems, machine learning-based approaches have been the first/most-used candidates in this application. Many schemes based on machine/deep learning have been proposed in recent years though increasing the performance and accuracy of the system… More >

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449

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ARTICLE

Hasnain Kashif^1,*, Muhammad Nasir Khan¹, Zubair Nawaz²
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 769-781, 2023, DOI:10.32604/cmc.2023.032565
Abstract Free-space optical (FSO) communication is of supreme importance for designing next-generation networks. Over the past decades, the radio frequency (RF) spectrum has been the main topic of interest for wireless technology. The RF spectrum is becoming denser and more employed, making its availability tough for additional channels. Optical communication, exploited for messages or indications in historical times, is now becoming famous and useful in combination with error-correcting codes (ECC) to mitigate the effects of fading caused by atmospheric turbulence. A free-space communication system (FSCS) in which the hybrid technology is based on FSO and RF. FSCS is a capable solution… More >

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Muhammad Hasnain¹, Imran Ghani², Seung Ryul Jeong^3,*, Muhammad Fermi Pasha⁴, Sardar Usman⁵, Anjum Abbas⁶
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 783-799, 2023, DOI:10.32604/cmc.2023.030162
Abstract Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to conduct this empirical analysis a… More >

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Yongjie Yang¹, Shanshan Tu¹, Raja Hashim Ali², Hisham Alasmary^3,4, Muhammad Waqas^5,6,*, Muhammad Nouman Amjad⁷
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 801-815, 2023, DOI:10.32604/cmc.2023.031907
Abstract With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed.… More >

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Kamal A. ElDahshan, AbdAllah A. AlHabshy, Luay Thamer Mohammed^*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 817-839, 2023, DOI:10.32604/cmc.2023.032287
Abstract This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods. To reduce the volume of big data and minimize model training time (Tt) while maintaining data quality. We contributed to meeting the challenges of big data visualization using the embedded method based “Select from model (SFM)” method by using “Random forest Importance algorithm (RFI)” and comparing it with the filter method by using “Select percentile (SP)” method based chi square “Chi2” tool for selecting the most important features, which are then fed into a classification process using the… More >

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547

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Mahwish Pervaiz¹, Mohammad Shorfuzzaman², Abdulmajeed Alsufyani², Ahmad Jalal³, Suliman A. Alsuhibany⁴, Jeongmin Park^5,*
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 841-853, 2023, DOI:10.32604/cmc.2023.029629
Abstract Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded… More >

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445

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ARTICLE

Borja Bordel^1,*, Ramón Alcarria¹, Joaquin Chung², Rajkumar Kettimuthu², Tomás Robles¹, Iván Armuelles³
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 855-880, 2023, DOI:10.32604/cmc.2023.026787
Abstract Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those… More >

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