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Ayesha Arif¹, Yazeed Yasin Ghadi², Mohammed Alarfaj³, Ahmad Jalal¹, Shaharyar Kamal¹, Dong-Seong Kim^4,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1-18, 2022, DOI:10.32604/cmc.2022.023553 - 24 February 2022
Abstract In the new era of technology, daily human activities are becoming more challenging in terms of monitoring complex scenes and backgrounds. To understand the scenes and activities from human life logs, human-object interaction (HOI) is important in terms of visual relationship detection and human pose estimation. Activities understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been explained. Some existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures, occluded regions, and unsatisfactory detection of objects, especially small-sized objects. The existing HOI… More >

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K. Lakshmi¹, Srinivas Nagineni², E. Laxmi Lydia³, A. Francis Saviour Devaraj⁴, Sachi Nandan Mohanty⁵, Irina V. Pustokhina^6,*, Denis A. Pustokhin⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 19-35, 2022, DOI:10.32604/cmc.2022.020244 - 24 February 2022
Abstract Cooperative Intelligent Transport System (C-ITS) plays a vital role in the future road traffic management system. A vital element of C-ITS comprises vehicles, road side units, and traffic command centers, which produce a massive quantity of data comprising both mobility and service-related data. For the extraction of meaningful and related details out of the generated data, data science acts as an essential part of the upcoming C-ITS applications. At the same time, prediction of short-term traffic flow is highly essential to manage the traffic accurately. Due to the rapid increase in the amount of traffic… More >

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Saad Awadh Alanazi^*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 37-55, 2022, DOI:10.32604/cmc.2022.020118 - 24 February 2022
Abstract Melanoma, also called malignant melanoma, is a form of skin cancer triggered by an abnormal proliferation of the pigment-producing cells, which give the skin its color. Melanoma is one of the skin diseases, which is exceptionally and globally dangerous, Skin lesions are considered to be a serious disease. Dermoscopy-based early recognition and detection procedure is fundamental for melanoma treatment. Early detection of melanoma using dermoscopy images improves survival rates significantly. At the same time, well-experienced dermatologists dominate the precision of diagnosis. However, precise melanoma recognition is incredibly hard due to several factors: low contrast between… More >

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Tamer AbuKhalil¹, Bassam A. Y. Alqaralleh^2,*, Ahmad H. Al-Omari³
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 57-71, 2022, DOI:10.32604/cmc.2022.024367 - 24 February 2022
Abstract Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear images. Pap smear test analysis is laborious and tiresome work performed visually using a cytopathologist. Therefore, automated cervical cancer diagnosis using automated methods are necessary. This paper designs an optimal deep learning based Inception model for cervical cancer diagnosis (ODLIM-CCD) using pap smear images. The proposed ODLIM-CCD technique incorporates median filtering (MF) based pre-processing to discard the noise and Otsu model based segmentation process. Besides, deep convolutional neural network (DCNN) based Inception with Residual Network (ResNet) v2 model is More >

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1239

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Farman Ali¹, Sadia Khan², Arbab Waseem Abbas², Babar Shah³, Tariq Hussain², Dongho Song^4,*, Shaker EI-Sappagh^5,6, Jaiteg Singh⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 73-92, 2022, DOI:10.32604/cmc.2022.024103 - 24 February 2022
（This article belongs to the Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
Abstract Medical Image Analysis (MIA) is one of the active research areas in computer vision, where brain tumor detection is the most investigated domain among researchers due to its deadly nature. Brain tumor detection in magnetic resonance imaging (MRI) assists radiologists for better analysis about the exact size and location of the tumor. However, the existing systems may not efficiently classify the human brain tumors with significantly higher accuracies. In addition, smart and easily implementable approaches are unavailable in 2D and 3D medical images, which is the main problem in detecting the tumor. In this paper, More >

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Ayman A. Aly¹, Mohamed O. Elhabib², Bassem F. Felemban¹, B. Saleh¹, Dac-Nhuong Le^3,4,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 93-107, 2022, DOI:10.32604/cmc.2022.019681 - 24 February 2022
Abstract The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors More >

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Khalil Ibrahim Mohammad Abuzanouneh¹, Fahd N. Al-Wesabi², Amani Abdulrahman Albraikan³, Mesfer Al Duhayyim⁴, M. Al-Shabi⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza^6,*, Abu Sarwar Zamani⁶, K. Muthulakshmi⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.022648 - 24 February 2022
Abstract Agriculture 4.0, as the future of farming technology, comprises numerous key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. To achieve effective water resource usage and automated irrigation in precision agriculture, recent technologies like machine learning (ML) can be employed. With this motivation, this paper design an IoT and ML enabled smart irrigation system (IoTML-SIS) for precision agriculture. The proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for… More >

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Dibyendu Mukherjee¹, Shivnath Ghosh¹, Souvik Pal^2,*, D. Akila³, N. Z. Jhanjhi⁴, Mehedi Masud⁵, Mohammed A. AlZain⁶
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 125-140, 2022, DOI:10.32604/cmc.2022.023611 - 24 February 2022
Abstract Numerous Internet of Things (IoT) systems produce massive volumes of information that must be handled and answered in a quite short period. The growing energy usage related to the migration of data into the cloud is one of the biggest problems. Edge computation helps users unload the workload again from cloud near the source of the information that must be handled to save time, increase security, and reduce the congestion of networks. Therefore, in this paper, Optimized Energy Efficient Strategy (OEES) has been proposed for extracting, distributing, evaluating the data on the edge devices. In… More >

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1008

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R. Gopi¹, Mahantesh Mathapati², B. Prasad³, Sultan Ahmad⁴, Fahd N. Al-Wesabi⁵, Manal Abdullah Alohali^6,*, Anwer Mustafa Hilal⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 141-156, 2022, DOI:10.32604/cmc.2022.023306 - 24 February 2022
Abstract Vehicular Ad hoc Network (VANET) has become an integral part of Intelligent Transportation Systems (ITS) in today's life. VANET is a network that can be heavily scaled up with a number of vehicles and road side units that keep fluctuating in real world. VANET is susceptible to security issues, particularly DoS attacks, owing to maximum unpredictability in location. So, effective identification and the classification of attacks have become the major requirements for secure data transmission in VANET. At the same time, congestion control is also one of the key research problems in VANET which aims… More >

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Abdallah Abdallah¹, Ayman A. Aly², Bassem F. Felemban², Imran Khan³, Ki-Il Kim^4,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 157-179, 2022, DOI:10.32604/cmc.2022.023907 - 24 February 2022
Abstract The Internet of Things (IoT) has allowed for significant advancements in applications not only in the home, business, and environment, but also in factory automation. Industrial Internet of Things (IIoT) brings all of the benefits of the IoT to industrial contexts, allowing for a wide range of applications ranging from remote sensing and actuation to decentralization and autonomy. The expansion of the IoT has been set by serious security threats and obstacles, and one of the most pressing security concerns is the secure exchange of IoT data and fine-grained access control. A privacy-preserving multi-dimensional secure… More >

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Mesfer Al Duhayyim¹, Majdy M. Eltahir², Imène Issaoui³, Fahd N. Al-Wesabi^2,4, Anwer Mustafa Hilal⁵, Fuad Ali Mohammed Al-Yarimi², Manar Ahmed Hamza^5,*, Abu Sarwar Zamani⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 181-195, 2022, DOI:10.32604/cmc.2022.024206 - 24 February 2022
Abstract The grid environment is a dynamic, heterogeneous, and changeable computing system that distributes various services amongst different clients. To attain the benefits of collaborative resource sharing in Grid computing, a novel and proficient grid resource management system (RMS) is essential. Therefore, detection of an appropriate resource for the presented task is a difficult task. Several scientists have presented algorithms for mapping tasks to the resource. Few of them focus on fault tolerance, user fulfillment, and load balancing. With this motivation, this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm (DHOA), called More >

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Kiran Jot Singh¹, Divneet Singh Kapoor^1,*, Khushal Thakur¹, Anshul Sharma¹, Xiao-Zhi Gao²
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 197-213, 2022, DOI:10.32604/cmc.2022.022989 - 24 February 2022
（This article belongs to the Special Issue: Applications of Intelligent Systems in Computer Vision)
Abstract The near future has been envisioned as a collaboration of humans with mobile robots to help in the day-to-day tasks. In this paper, we present a viable approach for a real-time computer vision based object detection and recognition for efficient indoor navigation of a mobile robot. The mobile robotic systems are utilized mainly for home assistance, emergency services and surveillance, in which critical action needs to be taken within a fraction of second or real-time. The object detection and recognition is enhanced with utilization of the proposed algorithm based on the modification of You Look… More >

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Maedeh Mohammadi Azni¹, Mohammad Ali Sadrnia¹, Shahab S. Band^2,*, Zulkefli Bin Mansor³
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 215-226, 2022, DOI:10.32604/cmc.2022.023030 - 24 February 2022
Abstract Automobile power windows are mechanisms that can be opened and shut with the press of a button. Although these windows can comfort the effort of occupancy to move the window, failure to recognize the person's body part at the right time will result in damage and in some cases, loss of that part. An anti-pinch mechanism is an excellent choice to solve this problem, which detects the obstacle in the glass path immediately and moves it down. In this paper, an optimal solution is presented for fault detection of the anti-pinch window system. The anti-pinch… More >

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1001

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Murad A. A. Almekhlafi¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Abdelzahir Abdelmaboud⁵, Manar Ahmed Hamza^6,*, Abdelwahed Motwakel⁶, Ishfaq Yaseen⁶, Mohammed Rizwanullah⁶
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 227-242, 2022, DOI:10.32604/cmc.2022.024356 - 24 February 2022
Abstract Line-of-sight clarity and assurance are essential because they are considered the golden rule in wireless network planning, allowing the direct propagation path to connect the transmitter and receiver and retain the strength of the signal to be received. Despite the increasing literature on the line of sight with different scenarios, no comprehensive study focuses on the multiplicity of parameters and basic concepts that must be taken into account when studying such a topic as it affects the results and their accuracy. Therefore, this research aims to find limited values that ensure that the signal reaches… More >

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924

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S. Karthik¹, Robin Singh Bhadoria², Jeong Gon Lee^3,*, Arun Kumar Sivaraman⁴, Sovan Samanta⁵, A. Balasundaram⁶, Brijesh Kumar Chaurasia⁷, S. Ashokkumar⁸
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 243-259, 2022, DOI:10.32604/cmc.2022.023864 - 24 February 2022
（This article belongs to the Special Issue: Innovative Technology For Machine Intelligence)
Abstract Data is always a crucial issue of concern especially during its prediction and computation in digital revolution. This paper exactly helps in providing efficient learning mechanism for accurate predictability and reducing redundant data communication. It also discusses the Bayesian analysis that finds the conditional probability of at least two parametric based predictions for the data. The paper presents a method for improving the performance of Bayesian classification using the combination of Kalman Filter and K-means. The method is applied on a small dataset just for establishing the fact that the proposed algorithm can reduce the More >

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Manal Alanazi^*, Ahamed Aljuhani
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 261-279, 2022, DOI:10.32604/cmc.2022.024496 - 24 February 2022
Abstract The Internet of Things (IoT) has been deployed in diverse critical sectors with the aim of improving quality of service and facilitating human lives. The IoT revolution has redefined digital services in different domains by improving efficiency, productivity, and cost-effectiveness. Many service providers have adapted IoT systems or plan to integrate them as integral parts of their systems’ operation; however, IoT security issues remain a significant challenge. To minimize the risk of cyberattacks on IoT networks, anomaly detection based on machine learning can be an effective security solution to overcome a wide range of IoT… More >

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S. Sreedhar Kumar¹, Syed Thouheed Ahmed^2,*, Qin Xin³, S. Sandeep⁴, M. Madheswaran⁵, Syed Muzamil Basha²
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 281-299, 2022, DOI:10.32604/cmc.2022.023693 - 24 February 2022
（This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract This paper presents, a new approach of Medical Image Pixels Clustering (MIPC), aims to trace the dissimilar patterns over the Magnetic Resonance (MR) image through the process of automatically identify the appropriate number of distinct clusters based on different improved unsupervised clustering schemes for enrichment, pattern predication and deeper investigation. The proposed MIPC consists of two stages: clustering and validation. In the clustering stage, the MIPC automatically identifies the distinct number of dissimilar clusters over the gray scale MR image based on three different improved unsupervised clustering schemes likely improved Limited Agglomerative Clustering (iLIAC), Dynamic More >

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Shahid Khan^1,2, Adil Bashir³, Haider Ali⁴, Abdul Rauf⁵, Mohamed Marey^6,*, Hala Mostafa⁷, Ikram Syed⁸
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 301-314, 2022, DOI:10.32604/cmc.2022.023397 - 24 February 2022
（This article belongs to the Special Issue: Advances in 5G Antenna Designs and Systems)
Abstract This article presents a novel modified chuck wagon dinner bell shaped millimeter wave (mm-wave) antenna at 28 GHz. The proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of 2.2. The design consists of T shaped resonating elements and two open ended side stubs. The desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed structure. The maximum achieved single element gain at the desired resonance frequency is 3.45 dBi. The efficiency of the proposed design over the operating band is more than 88%. The impedance bandwidth achieved for −10 More >

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Batyrkhan Omarov^1,2,3,4,*, Sergazy Narynov¹, Zhandos Zhumanov^1,2, Aidana Gumar^1,5, Mariyam Khassanova^1,5
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 315-331, 2022, DOI:10.32604/cmc.2022.024566 - 24 February 2022
Abstract In this paper, we propose a skeleton-based method to identify violence and aggressive behavior. The approach does not necessitate high-processing equipment and it can be quickly implemented. Our approach consists of two phases: feature extraction from image sequences to assess a human posture, followed by activity classification applying a neural network to identify whether the frames include aggressive situations and violence. A video violence dataset of 400 min comprising a single person's activities and 20 h of video data including physical violence and aggressive acts, and 13 classifications for distinguishing aggressor and victim behavior were More >

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Anwer Mustafa Hilal^1,*, Jaber S. Alzahrani², Ibrahim Abunadi³, Nadhem Nemri⁴, Fahd N. Al-Wesabi^5,6, Abdelwahed Motwakel¹, Ishfaq Yaseen¹, Abu Sarwar Zamani¹
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 333-348, 2022, DOI:10.32604/cmc.2022.024794 - 24 February 2022
Abstract In recent times, Industrial Internet of Things (IIoT) experiences a high risk of cyber attacks which needs to be resolved. Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks. Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network, the performance arrived at, in existing studies still needs improvement. In this scenario, the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT (PPBDL-IIoT) on 6G environment. The proposed PPBDL-IIoT technique aims… More >

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Sofia Nishath, P. S. Nithya Darisini^*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 349-364, 2022, DOI:10.32604/cmc.2022.023935 - 24 February 2022
（This article belongs to the Special Issue: Innovative Technology For Machine Intelligence)
Abstract Crowd Anomaly Detection has become a challenge in intelligent video surveillance system and security. Intelligent video surveillance systems make extensive use of data mining, machine learning and deep learning methods. In this paper a novel approach is proposed to identify abnormal occurrences in crowded situations using deep learning. In this approach, Adaptive GoogleNet Neural Network Classifier with Multi-Objective Whale Optimization Algorithm are applied to predict the abnormal video frames in the crowded scenes. We use multiple instance learning (MIL) to dynamically develop a deep anomalous ranking framework. This technique predicts higher anomalous values for abnormal More >

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Mahmoud Ragab^1,2,3,*, Ali Altalbe¹, Abdullah Saad Al-Malaise ALGhamdi⁴, S. Abdel-khalek^5,6, Rashid A. Saeed⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 365-380, 2022, DOI:10.32604/cmc.2022.024932 - 24 February 2022
Abstract The smart city comprises various interlinked elements which communicate data and offers urban life to citizen. Unmanned Aerial Vehicles (UAV) or drones were commonly employed in different application areas like agriculture, logistics, and surveillance. For improving the drone flying safety and quality of services, a significant solution is for designing the Internet of Drones (IoD) where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones, where the drones were utilized for collecting the data, and communicate with More >

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Pagnchakneat C. Ouk¹, Wooguil Pak^2,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 381-398, 2022, DOI:10.32604/cmc.2022.024540 - 24 February 2022
Abstract Although Android becomes a leading operating system in market, Android users suffer from security threats due to malwares. To protect users from the threats, the solutions to detect and identify the malware variant are essential. However, modern malware evades existing solutions by applying code obfuscation and native code. To resolve this problem, we introduce an ensemble-based malware classification algorithm using malware family grouping. The proposed family grouping algorithm finds the optimal combination of families belonging to the same group while the total number of families is fixed to the optimal total number. It also adopts… More >

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Fatemeh Ahmadi Zeidabadi¹, Mohammad Dehghani², Pavel Trojovský^2,*, Štěpán Hubálovský³, Victor Leiva⁴, Gaurav Dhiman⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 399-416, 2022, DOI:10.32604/cmc.2022.024736 - 24 February 2022
（This article belongs to the Special Issue: Bio-Inspired Computational Intelligence and Optimization Techniques for Real-World Engineering Applications)
Abstract Finding a suitable solution to an optimization problem designed in science is a major challenge. Therefore, these must be addressed utilizing proper approaches. Based on a random search space, optimization algorithms can find acceptable solutions to problems. Archery Algorithm (AA) is a new stochastic approach for addressing optimization problems that is discussed in this study. The fundamental idea of developing the suggested AA is to imitate the archer's shooting behavior toward the target panel. The proposed algorithm updates the location of each member of the population in each dimension of the search space by a… More >

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Shahid Hussain Danwar, Javed Ahmed Mahar^*, Aneela Kiran
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 417-440, 2022, DOI:10.32604/cmc.2022.023846 - 24 February 2022
Abstract Election allows the voter of a country to select the most suitable group of candidates to run the government. Election in Pakistan is simply paper-based method but some certain political and socio-economic issues turn that simple process in complicated and disputes once. Solutions of such problems are consisting of many methods including the e-voting system. The e-voting system facilitates the voters to cast their votes by electronic means with very easy and convenient way. This also allows maintaining the security and secrecy of the voter along with election process. Electronic voting reduces the human-involvement throughout… More >

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Arwa A. Mashat, Niayesh Gharaei^*, Aliaa M. Alabdali
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 441-459, 2022, DOI:10.32604/cmc.2022.024131 - 24 February 2022
Abstract Compared with the traditional techniques of forest fires detection, wireless sensor network (WSN) is a very promising green technology in detecting efficiently the wildfires. However, the power constraint of sensor nodes is one of the main design limitations of WSNs, which leads to limited operation time of nodes and late fire detection. In the past years, wireless power transfer (WPT) technology has been known as a proper solution to prolong the operation time of sensor nodes. In WPT-based mechanisms, wireless mobile chargers (WMC) are utilized to recharge the batteries of sensor nodes wirelessly. Likewise, the… More >

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Abdulbasit A. Darem^*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 461-479, 2022, DOI:10.32604/cmc.2022.023566 - 24 February 2022
Abstract Malicious software (malware) is one of the main cyber threats that organizations and Internet users are currently facing. Malware is a software code developed by cybercriminals for damage purposes, such as corrupting the system and data as well as stealing sensitive data. The damage caused by malware is substantially increasing every day. There is a need to detect malware efficiently and automatically and remove threats quickly from the systems. Although there are various approaches to tackle malware problems, their prevalence and stealthiness necessitate an effective method for the detection and prevention of malware attacks. The More >

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Rajkumar Sarma¹, Cherry Bhargava², Ketan Kotecha^3,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 481-495, 2022, DOI:10.32604/cmc.2022.024516 - 24 February 2022
（This article belongs to the Special Issue: Soft Computing and Machine Learning for Predictive Data Analytics)
Abstract In the era of digital signal processing, like graphics and computation systems, multiplication-accumulation is one of the prime operations. A MAC unit is a vital component of a digital system, like different Fast Fourier Transform (FFT) algorithms, convolution, image processing algorithms, etcetera. In the domain of digital signal processing, the use of normalization architecture is very vast. The main objective of using normalization is to perform comparison and shift operations. In this research paper, an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer, Adder etc. The… More >

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Hameed AlQaheri^1,*, Manash Sarkar², Saptarshi Gupta³, Bhavya Gaur⁴
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 497-517, 2022, DOI:10.32604/cmc.2022.022735 - 24 February 2022
Abstract The most common alarming and dangerous disease in the world today is the coronavirus disease 2019 (COVID-19). The coronavirus is perceived as a group of coronaviruses which causes mild to severe respiratory diseases among human beings. The infection is spread by aerosols emitted from infected individuals during talking, sneezing, and coughing. Furthermore, infection can occur by touching a contaminated surface followed by transfer of the viral load to the face. Transmission may occur through aerosols that stay suspended in the air for extended periods of time in enclosed spaces. To stop the spread of the… More >

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J. Stanly Jayaprakash¹, Kishore Balasubramanian², Rossilawati Sulaiman³, Mohammad Kamrul Hasan^3,*, B. D. Parameshachari⁴, Celestine Iwendi⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 519-534, 2022, DOI:10.32604/cmc.2022.021269 - 24 February 2022
（This article belongs to the Special Issue: Next - Generation Secure Solutions for Wireless Communications, IoT and SDNs)
Abstract Many organizations apply cloud computing to store and effectively process data for various applications. The user uploads the data in the cloud has less security due to the unreliable verification process of data integrity. In this research, an enhanced Merkle hash tree method of effective authentication model is proposed in the multi-owner cloud to increase the security of the cloud data. Merkle Hash tree applies the leaf nodes with a hash tag and the non-leaf node contains the table of hash information of child to encrypt the large data. Merkle Hash tree provides the efficient… More >

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Fawaz Alassery^*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 535-559, 2022, DOI:10.32604/cmc.2022.023558 - 24 February 2022
（This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract Today, Internet of Things (IoT) is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities. Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio, energy efficiency, end-to-end delays etc. However, traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics. In big data smart cities applications which need fast packets transmission ratio such… More >

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Aymen Saad¹, Israa S. Kamil², Ahmed Alsayat³, Ahmed Elaraby^4,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 561-576, 2022, DOI:10.32604/cmc.2022.023878 - 24 February 2022
（This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world widespread. This spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment. X-ray images are one of the most classifiable images that are used widely in diagnosing patients’ data depending on radiographs due to their structures and tissues that could be classified. Convolutional Neural Networks (CNN) is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number… More >

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Amal Abdullah Mohammed Alteaimi^1,*, Mohamed Tahar Ben Othman^1,2
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 577-595, 2022, DOI:10.32604/cmc.2022.023591 - 24 February 2022
（This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract The Hand Gestures Recognition (HGR) System can be employed to facilitate communication between humans and computers instead of using special input and output devices. These devices may complicate communication with computers especially for people with disabilities. Hand gestures can be defined as a natural human-to-human communication method, which also can be used in human-computer interaction. Many researchers developed various techniques and methods that aimed to understand and recognize specific hand gestures by employing one or two machine learning algorithms with a reasonable accuracy. This work aims to develop a powerful hand gesture recognition model with… More >

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S. Sudha^*, A. Srinivasan, T. Gayathri Devi
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 597-609, 2022, DOI:10.32604/cmc.2022.024065 - 24 February 2022
Abstract Diabetes is associated with many complications that could lead to death. Diabetic retinopathy, a complication of diabetes, is difficult to diagnose and may lead to vision loss. Visual identification of micro features in fundus images for the diagnosis of DR is a complex and challenging task for clinicians. Because clinical testing involves complex procedures and is time-consuming, an automated system would help ophthalmologists to detect DR and administer treatment in a timely manner so that blindness can be avoided. Previous research works have focused on image processing algorithms, or neural networks, or signal processing techniques… More >

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Muhammad Hameed Siddiqi^1,*, Helal Alshammari¹, Amjad Ali², Madallah Alruwaili¹, Yousef Alhwaiti¹, Saad Alanazi¹, M. M. Kamruzzaman¹
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 611-634, 2022, DOI:10.32604/cmc.2022.024760 - 24 February 2022
（This article belongs to the Special Issue: Face Image Analysis Using Deep Learning)
Abstract Human activity recognition (HAR) can play a vital role in the monitoring of human activities, particularly for healthcare conscious individuals. The accuracy of HAR systems is completely reliant on the extraction of prominent features. Existing methods find it very challenging to extract optimal features due to the dynamic nature of activities, thereby reducing recognition performance. In this paper, we propose a robust feature extraction method for HAR systems based on template matching. Essentially, in this method, we want to associate a template of an activity frame or sub-frame comprising the corresponding silhouette. In this regard,… More >

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Israr Ghani^*, Wan M. N. Wan-Kadir, Adila Firdaus Arbain, Noraini Ibrahim
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 635-650, 2022, DOI:10.32604/cmc.2022.025027 - 24 February 2022
Abstract Regression testing (RT) is an essential but an expensive activity in software development. RT confirms that new faults/errors will not have occurred in the modified program. RT efficiency can be improved through an effective technique of selected only modified test cases that appropriate to the modifications within the given time frame. Earlier, several test case selection approaches have been introduced, but either these techniques were not sufficient according to the requirements of software tester experts or they are ineffective and cannot be used for available test suite specifications and architecture. To address these limitations, we… More >

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Ibrahim M. Mehedi^1,2,*, Maher H. AL-Sereihy², Asmaa Ubaid Al-Saggaf², Ubaid M. Al-Saggaf^1,2
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 651-662, 2022, DOI:10.32604/cmc.2022.022013 - 24 February 2022
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Tracking load changes in a pressurized water reactor (PWR) with the help of an efficient core power control scheme in a nuclear power station is very important. The reason is that it is challenging to maintain a stable core power according to the reference value within an acceptable tolerance for the safety of PWR. To overcome the uncertainties, a non-integer-based fractional order control method is demonstrated to control the core power of PWR. The available dynamic model of the reactor core is used in this analysis. Core power is controlled using a modified state feedback More >

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Faheem Khan¹, Muhammad Zahid², Hüseyin Gürüler³, Ilhan Tarimer³, Taegkeun Whangbo^1,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 663-678, 2022, DOI:10.32604/cmc.2022.022934 - 24 February 2022
（This article belongs to the Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract The Internet of thing (IoT) is a growing concept for smart cities, and it is compulsory to communicate data between different networks and devices. In the IoT, communication should be rapid with less delay and overhead. For this purpose, flooding is used for reliable data communication in a smart cities concept but at the cost of higher overhead, energy consumption and packet drop etc. This paper aims to increase the efficiency in term of overhead and reliability in term of delay by using multicasting and unicasting instead of flooding during packet forwarding in a smart… More >

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Abdelzahir Abdelmaboud¹, Fahd N. Al-Wesabi^1,2,3, Mesfer Al Duhayyim⁴, Taiseer Abdalla Elfadil Eisa⁵, Manar Ahmed Hamza^6,*, Mohammed Rizwanullah⁶, Abu Serwar Zamani⁶, Radwa Marzouk⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 679-693, 2022, DOI:10.32604/cmc.2022.024240 - 24 February 2022
Abstract Internet of Things (IoT) with e-learning is widely employed to collect data from various smart devices and share it with other ones for efficient e-learning applications. At the same time, machine learning (ML) and data mining approaches are presented for accomplishing prediction and classification processes. With this motivation, this study focuses on the design of intelligent machine learning enabled e-learner non-verbal behaviour detection (IML-ELNVBD) in IoT environment. The proposed IML-ELNVBD technique allows the IoT devices such as audio sensors, cameras, etc. which are then connected to the cloud server for further processing. In addition, the More >

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Wenzheng Yu¹, Xin Yao¹, Li Shao², Jing Liu¹, Yanbo Shen^3,4,*, Hanxiaoya Zhang⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 695-711, 2022, DOI:10.32604/cmc.2022.023191 - 24 February 2022
Abstract In this paper, RS, GIS and GPS technologies are used to interpret the remote sensing images of the north shore of Qinghai Lake from 1987 to 2014 according to the inversion results of vegetation coverage (FVC), albedo, land surface temperature (LST), soil moisture (WET) and other major parameters after image preprocessing, such as radiometric correction, geometric correction and atmospheric correction. On this basis, the decision tree classification method based on landsat8 remote sensing image is used to classify the desertification land in this area, and the development and change of desertification in this period are More >

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Anwer Mustafa Hilal^1,*, Siwar Ben Haj Hassine², Souad Larabi-Marie-Sainte³, Nadhem Nemri², Mohamed K. Nour⁴, Abdelwahed Motwakel¹, Abu Sarwar Zamani¹, Mesfer Al Duhayyim⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 713-726, 2022, DOI:10.32604/cmc.2022.024501 - 24 February 2022
Abstract The development in Information and Communication Technology has led to the evolution of new computing and communication environment. Technological revolution with Internet of Things (IoTs) has developed various applications in almost all domains from health care, education to entertainment with sensors and smart devices. One of the subsets of IoT is Internet of Medical things (IoMT) which connects medical devices, hardware and software applications through internet. IoMT enables secure wireless communication over the Internet to allow efficient analysis of medical data. With these smart advancements and exploitation of smart IoT devices in health care technology… More >

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Changsung Lee^1,3, Junsung Kim^2,3, Jaewook Jung³, Jungsuk Baik³, Jong-Moon Chung^3,*
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 727-738, 2022, DOI:10.32604/cmc.2022.024824 - 24 February 2022
Abstract Packet duplication (PD) with dual connectivity (DC) was newly introduced in the 5G New Radio (NR) specifications to meet the stringent ultra reliable low latency communication (URLLC) requirements. PD technology uses duplicated packets in the packet data convergence protocol (PDCP) layer that are transmitted via two different access nodes (ANs) to the user equipment (UE) in order to enhance the reliability performance. However, PD can result in unnecessary retransmissions in the lower layers since the hybrid automatic retransmission request (HARQ) operation is unaware of the transmission success achieved through the alternate DC link to the… More >

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Khalid A. AlAfandy¹, Hicham Omara², Hala S. El-Sayed³, Mohammed Baz^4,*, Mohamed Lazaar⁵, Osama S. Faragallah⁶, Mohammed Al Achhab¹
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 739-753, 2022, DOI:10.32604/cmc.2022.022457 - 24 February 2022
Abstract Remote sensing image processing engaged researchers’ attentiveness in recent years, especially classification. The main problem in classification is the ratio of the correct predictions after training. Feature extraction is the foremost important step to build high-performance image classifiers. The convolution neural networks can extract images’ features that significantly improve the image classifiers’ accuracy. This paper proposes two efficient approaches for remote sensing images classification that utilizes the concatenation of two convolution channels’ outputs as a features extraction using two classic convolution models; these convolution models are the ResNet 50 and the DenseNet 169. These elicited… More >

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Dah-Jing Jwo^1,*, Wei-Yeh Chang²
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 755-773, 2022, DOI:10.32604/cmc.2022.025040 - 24 February 2022
Abstract This paper investigates the navigational performance of Global Positioning System (GPS) using the variational Bayesian (VB) based robust filter with interacting multiple model (IMM) adaptation as the navigation processor. The performance of the state estimation for GPS navigation processing using the family of Kalman filter (KF) may be degraded due to the fact that in practical situations the statistics of measurement noise might change. In the proposed algorithm, the adaptivity is achieved by estimating the time-varying noise covariance matrices based on VB learning using the probabilistic approach, where in each update step, both the system… More >

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Zeyad Ghaleb Al-Mekhlafi¹, Ebrahim Mohammed Senan², Taha H. Rassem³, Badiea Abdulkarem Mohammed^4,5,*, Nasrin M. Makbol⁵, Adwan Alownie Alanazi¹, Tariq S. Almurayziq¹, Fuad A. Ghaleb⁶
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 775-796, 2022, DOI:10.32604/cmc.2022.024492 - 24 February 2022
（This article belongs to the Special Issue: Social Networks Analysis and Knowledge Management)
Abstract Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart disease. In this work, a dataset containing medical, physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning, deep learning and a hybrid technique between deep learning and machine learning on the Magnetic Resonance Imaging (MRI) dataset for cerebral haemorrhage. In the first dataset (medical records), two features, namely, diabetes and obesity, were created on the basis of the values of the corresponding features. The t-Distributed Stochastic Neighbour Embedding algorithm was applied to… More >

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Ayman M. Abdalla^1,*, Mohammad Abu Awad², Omar AlZoubi², La'aly A. Al-Samrraie³
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 797-814, 2022, DOI:10.32604/cmc.2022.024913 - 24 February 2022
Abstract The enlarged veins in the pampiniform venous plexus, known as varicocele disease, are typically identified using ultrasound scans. The medical diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male patient. The proposed system is designed to determine whether a patient is affected. Varicocele is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other positions. Therefore, the experimental results of this study focused on images taken in the supine… More >

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Manar Elshahawy¹, Ahmed O. Aseeri^2,*, Shaker El-Sappagh^3,4, Hassan Soliman¹, Mohammed Elmogy¹, Mervat Abu-Elkheir⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 815-832, 2022, DOI:10.32604/cmc.2022.023852 - 24 February 2022
Abstract The identification and classification of collective people's activities are gaining momentum as significant themes in machine learning, with many potential applications emerging. The need for representation of collective human behavior is especially crucial in applications such as assessing security conditions and preventing crowd congestion. This paper investigates the capability of deep neural network (DNN) algorithms to achieve our carefully engineered pipeline for crowd analysis. It includes three principal stages that cover crowd analysis challenges. First, individual's detection is represented using the You Only Look Once (YOLO) model for human detection and Kalman filter for multiple… More >

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Saleh Albahli^1,*, Farman Hassan², Ali Javed^2,3, Aun Irtaza^2,4
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 833-849, 2022, DOI:10.32604/cmc.2022.024267 - 24 February 2022
（This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract COVID-19 has become a pandemic, with cases all over the world, with widespread disruption in some countries, such as Italy, US, India, South Korea, and Japan. Early and reliable detection of COVID-19 is mandatory to control the spread of infection. Moreover, prediction of COVID-19 spread in near future is also crucial to better plan for the disease control. For this purpose, we proposed a robust framework for the analysis, prediction, and detection of COVID-19. We make reliable estimates on key pandemic parameters and make predictions on the point of inflection and possible washout time for… More >

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Soobia Saeed^1,*, Afnizanfaizal Abdullah¹, N. Z. Jhanjhi², Mehmood Naqvi³, Mehedi Masud⁴, Mohammed A. AlZain⁵
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 851-869, 2022, DOI:10.32604/cmc.2022.024085 - 24 February 2022
Abstract Diagnosing data or object detection in medical images is one of the important parts of image segmentation especially those data which is less effective to identify in MRI such as low-grade tumors or cerebral spinal fluid (CSF) leaks in the brain. The aim of the study is to address the problems associated with detecting the low-grade tumor and CSF in brain is difficult in magnetic resonance imaging (MRI) images and another problem also relates to efficiency and less execution time for segmentation of medical images. For tumor and CSF segmentation using trained light field database… More >

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Ahmed S. Almasoud¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Abubakar Elsafi⁵, Mesfer Al Duhayyim⁶, Ishfaq Yaseen⁷, Manar Ahmed Hamza^7,*, Abdelwahed Motwakel⁷
CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 871-886, 2022, DOI:10.32604/cmc.2022.024596 - 24 February 2022
Abstract Early detection of Parkinson's Disease (PD) using the PD patients’ voice changes would avoid the intervention before the identification of physical symptoms. Various machine learning algorithms were developed to detect PD detection. Nevertheless, these ML methods are lack in generalization and reduced classification performance due to subject overlap. To overcome these issues, this proposed work apply graph long short term memory (GLSTM) model to classify the dynamic features of the PD patient speech signal. The proposed classification model has been further improved by implementing the recurrent neural network (RNN) in batch normalization layer of GLSTM… More >

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