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Anwer Mustafa Hilal¹, Imène ISSAOUI², Marwa Obayya³, Fahd N. Al-Wesabi⁴, Nadhem NEMRI⁵, Manar Ahmed Hamza^1,*, Mesfer Al Duhayyim⁶, Abu Sarwar Zamani¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3853-3867, 2022, DOI:10.32604/cmc.2022.022663
Abstract The abundant existence of both structured and unstructured data and rapid advancement of statistical models stressed the importance of introducing Explainable Artificial Intelligence (XAI), a process that explains how prediction is done in AI models. Biomedical mental disorder, i.e., Autism Spectral Disorder (ASD) needs to be identified and classified at early stage itself in order to reduce health crisis. With this background, the current paper presents XAI-based ASD diagnosis (XAI-ASD) model to detect and classify ASD precisely. The proposed XAI-ASD technique involves the design of Bacterial Foraging Optimization (BFO)-based Feature Selection (FS) technique. In addition, Whale Optimization Algorithm (WOA) with… More >

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938

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Ramon Sanchez-Iborra¹, Luis Bernal-Escobedo², Jose Santa^3,*, Antonio Skarmeta²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3869-3885, 2022, DOI:10.32604/cmc.2022.022610
（This article belongs to the Special Issue: Artificial Intelligence Enabled Intelligent Transportation Systems)
Abstract A new wave of electric vehicles for personal mobility is currently crowding public spaces. They offer a sustainable and efficient way of getting around in urban environments, however, these devices bring additional safety issues, including serious accidents for riders. Thereby, taking advantage of a connected personal mobility vehicle, we present a novel on-device Machine Learning (ML)-based fall detection system that analyzes data captured from a range of sensors integrated on an on-board unit (OBU) prototype. Given the typical processing limitations of these elements, we exploit the potential of the TinyML paradigm, which enables embedding powerful ML algorithms in constrained units.… More >

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Abdul Karim¹, Azhari Azhari^1,*, Mobeen Shahroz², Samir Brahim Belhaouri³, Khabib Mustofa¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3887-3903, 2022, DOI:10.32604/cmc.2022.021218
Abstract Leukemia is blood cancer, including bone marrow and lymphatic tissues, typically involving white blood cells. Leukemia produces an abnormal amount of white blood cells compared to normal blood. Deoxyribonucleic acid (DNA) microarrays provide reliable medical diagnostic services to help more patients find the proposed treatment for infections. DNA microarrays are also known as biochips that consist of microscopic DNA spots attached to a solid glass surface. Currently, it is difficult to classify cancers using microarray data. Nearly many data mining techniques have failed because of the small sample size, which has become more critical for organizations. However, they are not… More >

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Ismail Hossain¹, Md Samsuzzaman², Mohd Hafiz Baharuddin^3,*, Norsuzlin Binti Mohd Sahar¹, Mandeep Singh Jit Singh¹, Mohammad Tariqul Islam³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3905-3920, 2022, DOI:10.32604/cmc.2022.022027
Abstract This study presents an Epsilon Mu near-zero (EMNZ) nanostructured metamaterial absorber (NMMA) for visible regime applications. The resonator and dielectric layers are made of tungsten (W) and quartz (fused), where the working band is expanded by changing the resonator layer's design. Due to perfect impedance matching with plasmonic resonance characteristics, the proposed NMMA structure is achieved an excellent absorption of 99.99% at 571 THz, 99.50% at 488.26 THz, and 99.32% at 598 THz frequencies. The absorption mechanism is demonstrated by the theory of impedance, electric field, and power loss density distributions, respectively. The geometric parameters are explored and analyzed to… More >

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1197

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Anwer Mustafa Hil¹, Fahd N. Al-Wesabi², Hadeel Alsolai³, Ola Abdelgney Omer Ali⁴, Nadhem Nemri⁵, Manar Ahmed Hamza^1,*, Abu Sarwar Zamani¹, Mohammed Rizwanullah¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3921-3936, 2022, DOI:10.32604/cmc.2022.022301
Abstract Social media is a platform in which user can create, share and exchange the knowledge/information. Social media marketing is to identify the different consumer's demands and engages them to create marketing resources. The popular social media platforms are Microsoft, Snapchat, Amazon, Flipkart, Google, eBay, Instagram, Facebook, Pin interest, and Twitter. The main aim of social media marketing deals with various business partners and build good relationship with millions of customers by satisfying their needs. Disruptive technology is replacing old approaches in the social media marketing to new technology-based marketing. However, this disruptive technology creates some issues like fake news, insecure,… More >

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1052

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Sudan Prasad Uprety, Seung Ryul Jeong^*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3937-3952, 2022, DOI:10.32604/cmc.2022.023127
Abstract Artificial intelligent based dialog systems are getting attention from both business and academic communities. The key parts for such intelligent chatbot systems are domain classification, intent detection, and named entity recognition. Various supervised, unsupervised, and hybrid approaches are used to detect each field. Such intelligent systems, also called natural language understanding systems analyze user requests in sequential order: domain classification, intent, and entity recognition based on the semantic rules of the classified domain. This sequential approach propagates the downstream error; i.e., if the domain classification model fails to classify the domain, intent and entity recognition fail. Furthermore, training such intelligent… More >

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1034

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Mesfer Al Duhayyim¹, Amani Abdulrahman Albraikan², Fahd N. Al-Wesabi^3,4, Hiba M. Burbur⁵, Mohammad Alamgeer⁶, Anwer Mustafa Hilal⁷, Manar Ahmed Hamza^7,*, Mohammed Rizwanullah⁷
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3953-3968, 2022, DOI:10.32604/cmc.2022.022692
Abstract Short-term traffic flow prediction (TFP) is an important area in intelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodic features are susceptible to weather conditions, making TFP a challenging issue. TFP process are significantly influenced by several factors like accident and weather. Particularly, the inclement weather conditions may have an extreme impact on travel time and traffic flow. Since most of the existing TFP techniques do not consider the impact of weather conditions on the TF, it is needed to develop effective TFP with the consideration… More >

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1136

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CSS Anupama¹, T. J. Benedict Jose², Heba F. Eid³, Nojood O Aljehane⁴, Fahd N. Al-Wesabi^5,*, Marwa Obayya⁶, Anwer Mustafa Hilal⁷
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3969-3983, 2022, DOI:10.32604/cmc.2022.022701
Abstract Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or tissues. Biomedical image processing concepts are identical to biomedical signal processing, which includes the investigation, improvement, and exhibition of images gathered using x-ray, ultrasound, MRI, etc. At the same time, cervical cancer becomes a major reason for increased women's mortality rate. But cervical cancer is an identified at an earlier stage using regular pap smear images. In this aspect, this paper devises a new biomedical pap smear image classification using cascaded deep forest (BPSIC-CDF) model on Internet of Things (IoT)… More >

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988

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Muhammad Asif¹, Ishfaq Ali¹, Shahbaz Ahmad¹, Azeem Irshad², Akber Abid Gardezi³, Fawaz Alassery⁴, Habib Hamam⁵, Muhammad Shafiq^6,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3985-3999, 2022, DOI:10.32604/cmc.2022.023010
Abstract Industrial automation or assembly automation is a strictly monitored environment, in which changes occur at a good speed. There are many types of entities in the focusing environment, and the data generated by these devices is huge. In addition, because the robustness is achieved by sensing redundant data, the data becomes larger. The data generating device, whether it is a sensing device or a physical device, streams the data to a higher-level deception device for calculation, so that it can be driven and configured according to the updated conditions. With the emergence of the Industry 4.0 concept that includes a… More >

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952

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Ibrahim M. Mehedi^1,2,*, Ubaid M. Al-Saggaf^1,2, Mahendiran T. Vellingiri¹, Ahmad H. Milyani¹, Nordin Bin Saad³, Nor Zaihar Bin Yahaya³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4001-4017, 2022, DOI:10.32604/cmc.2022.021981
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract In recent times, wind energy receives maximum attention and has become a significant green energy source globally. The wind turbine (WT) entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid. The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction. The pitch control angle is employed to effectively operate the WT at the above nominal wind speed. Besides, the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep… More >

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1051

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Ahmed Elaraby^1,*, Walid Hamdy², Madallah Alruwaili³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4019-4031, 2022, DOI:10.32604/cmc.2022.022161
（This article belongs to the Special Issue: Recent Advances in Deep Learning and Saliency Methods for Agriculture)
Abstract Plant diseases are a major impendence to food security, and due to a lack of key infrastructure in many regions of the world, quick identification is still challenging. Harvest losses owing to illnesses are a severe problem for both large farming structures and rural communities, motivating our mission. Because of the large range of diseases, identifying and classifying diseases with human eyes is not only time-consuming and labor intensive, but also prone to being mistaken with a high error rate. Deep learning-enabled breakthroughs in computer vision have cleared the road for smartphone-assisted plant disease and diagnosis. The proposed work describes… More >

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Walid Aydi^1,3,*, Fuad S. Alduais^2,4
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4033-4050, 2022, DOI:10.32604/cmc.2022.023119
（This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract The Weibull distribution is regarded as among the finest in the family of failure distributions. One of the most commonly used parameters of the Weibull distribution (WD) is the ordinary least squares (OLS) technique, which is useful in reliability and lifetime modeling. In this study, we propose an approach based on the ordinary least squares and the multilayer perceptron (MLP) neural network called the OLSMLP that is based on the resilience of the OLS method. The MLP solves the problem of heteroscedasticity that distorts the estimation of the parameters of the WD due to the presence of outliers, and eases… More >

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Omaima Bamasaq¹, Daniyal Alghazzawi², Surbhi Bhatia³, Pankaj Dadheech^4,*, Farrukh Arslan⁵, Sudhakar Sengan⁶, Syed Hamid Hassan²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4051-4068, 2022, DOI:10.32604/cmc.2022.023634
Abstract Applications based on Wireless Sensor Networks (WSN) have shown to be quite useful in monitoring a particular geographic area of interest. Relevant geometries of the surrounding environment are essential to establish a successful WSN topology. But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes (SN) in a WSN is always a challenging task. In this research paper, Distance Matrix and Markov Chain (DM-MC) model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node. The method further employs a… More >

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M. Bharathidasan¹, V. Indragandhi¹, Ramya Kuppusamy², Yuvaraja Teekaraman³, Shabana Urooj^4,*, Norah Alwadi⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4069-4084, 2022, DOI:10.32604/cmc.2022.021846
Abstract Renewable electricity options, such as fuel cells, solar photovoltaic, and batteries, are being integrated, which has made DC micro-grids famous. For DC micro-grid systems, a multi input interleaved non-isolated dc-dc converter is suggested by the use of coupled inductor techniques. Since it compensates for mismatches in photovoltaic devices and allows for separate and continuous power flow from these sources. The proposed converter has the benefits of high gain, a low ripple in the output voltage, minimal stress voltage across the power semiconductor devices, a low ripple in inductor current, high power density, and high efficiency. Soft-switching techniques are used to… More >

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846

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Arpit Jain¹, Rakesh Kumar Dwivedi¹, Hammam Alshazly^2,*, Adesh Kumar³, Sami Bourouis⁴, Manjit Kaur⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4085-4100, 2022, DOI:10.32604/cmc.2022.023017
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract The network-on-chip (NoC) technology is frequently referred to as a front-end solution to a back-end problem. The physical substructure that transfers data on the chip and ensures the quality of service begins to collapse when the size of semiconductor transistor dimensions shrinks and growing numbers of intellectual property (IP) blocks working together are integrated into a chip. The system on chip (SoC) architecture of today is so complex that not utilizing the crossbar and traditional hierarchical bus architecture. NoC connectivity reduces the amount of hardware required for routing and functions, allowing SoCs with NoC interconnect fabrics to operate at higher… More >

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ARTICLE

R. Joshua Samuel Raj¹, V. Ilango², Prince Thomas³, V. R. Uma⁴, Fahd N. Al-Wesabi^5,6,*, Radwa Marzouk⁷, Anwer Mustafa Hilal⁸
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4101-4114, 2022, DOI:10.32604/cmc.2022.022063
Abstract Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of… More >

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885

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Jorge Gallego-Madrid¹, Ramon Sanchez-Iborra^2,*, Antonio Skarmeta¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4115-4134, 2022, DOI:10.32604/cmc.2022.021754
（This article belongs to the Special Issue: Security and Privacy Issues in Systems and Networks Beyond 5G)
Abstract As the 5G ecosystem continues its consolidation, the testing and validation of the innovations achieved by integrators and verticals service providers is of preponderant importance. In this line, 5GASP is a European H2020-funded project that aims at easing the idea-to-market process through the creation of an European testbed that is fully automated and self-service, in order to foster rapid development and testing of new and innovative 5G Network Applications (NetApps). The main objective of this paper is to present the 5GASP's unified methodology to design, develop and onboard NetApps within the scope of different vertical services, letting them use specific… More >

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Mesfer AI Duhayyim¹, Fahd N. Al-Wesabi², Radwa Marzouk³, Abdalla Ibrahim Abdalla Musa⁴, Noha Negm⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza^6,*, Mohammed Rizwanullah⁶
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4135-4149, 2022, DOI:10.32604/cmc.2022.022336
Abstract Internet of Medical Things (IoMT) is a breakthrough technology in the transfer of medical data via a communication system. Wearable sensor devices collect patient data and transfer them through mobile internet, that is, the IoMT. Recently, the shift in paradigm from manual data storage to electronic health recording on fog, edge, and cloud computing has been noted. These advanced computing technologies have facilitated medical services with minimum cost and available conditions. However, the IoMT raises a high concern on network security and patient data privacy in the health care system. The main issue is the transmission of health data with… More >

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Maha Farouk S. Sabir¹, Irfan Mehmood^2,*, Wafaa Adnan Alsaggaf³, Enas Fawai Khairullah³, Samar Alhuraiji⁴, Ahmed S. Alghamdi⁵, Ahmed A. Abd El-Latif⁶
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4151-4166, 2022, DOI:10.32604/cmc.2022.017865
（This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis. According to the World Health Organization (WHO), people in public places should wear a face mask to control the rapid transmission of COVID-19. The governmental bodies of different countries imposed that wearing a face mask is compulsory in public places. Therefore, it is very difficult to manually monitor people in overcrowded areas. This research focuses on providing a solution to enforce one of the important preventative measures of COVID-19 in public places, by presenting an automated system that automatically localizes masked and unmasked human… More >

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Sunwoo Hwang¹, Jaemin Park¹, Jongun Won², Yongjang Kwon³, Youngmin Kim^1,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4167-4181, 2022, DOI:10.32604/cmc.2022.023295
（This article belongs to the Special Issue: Analysis, Processing, and Applications of Fuzzy System and Deep Learning)
Abstract With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field, but so far, algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development. In this study, the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study, and a cargo object recognition algorithm applicable to the automatic loading device is… More >

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