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Doaa Sami Khafaga¹, Faten Khalid Karim^1,*, Abdelaziz A. Abdelhamid^2,3, El-Sayed M. El-kenawy⁴, Hend K. Alkahtani¹, Nima Khodadadi⁵, Mohammed Hadwan⁶, Abdelhameed Ibrahim⁷
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3183-3198, 2023, DOI:10.32604/cmc.2023.033513
Abstract Managing physical objects in the network’s periphery is made possible by the Internet of Things (IoT), revolutionizing human life. Open attacks and unauthorized access are possible with these IoT devices, which exchange data to enable remote access. These attacks are often detected using intrusion detection methodologies, although these systems’ effectiveness and accuracy are subpar. This paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic optimization. The employed metaheuristic optimizer is a new version of the whale optimization algorithm (WOA), which is guided by the dipper throated optimizer (DTO) to improve… More >

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Weifeng Liu^1,2, Xin Yu^1,*, Qinyang Zhao³, Guang Cheng², Xiaobing Hou¹, Shengqi He⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3199-3219, 2023, DOI:10.32604/cmc.2023.032595
Abstract Time series forecasting and analysis are widely used in many fields and application scenarios. Time series historical data reflects the change pattern and trend, which can serve the application and decision in each application scenario to a certain extent. In this paper, we select the time series prediction problem in the atmospheric environment scenario to start the application research. In terms of data support, we obtain the data of nearly 3500 vehicles in some cities in China from Runwoda Research Institute, focusing on the major pollutant emission data of non-road mobile machinery and high emission vehicles in Beijing and Bozhou,… More >

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Memet Şahin¹, Vakkas Uluçay², S. A. Edalatpanah^3,*, Fayza Abdel Aziz Elsebaee⁴, Hamiden Abd El-Wahed Khalifa⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3221-3229, 2023, DOI:10.32604/cmc.2023.033006
Abstract Recently, fuzzy multi-sets have come to the forefront of scientists’ interest and have been used in algebraic structures such as multi-groups, multi-rings, anti-fuzzy multigroup and (α, γ)-anti-fuzzy subgroups. In this paper, we first summarize the knowledge about the algebraic structure of fuzzy multi-sets such as (α, γ)-anti-multi-fuzzy subgroups. In a way, the notion of anti-fuzzy multigroup is an application of anti-fuzzy multi sets to the theory of group. The concept of anti-fuzzy multigroup is a complement of an algebraic structure of a fuzzy multi set that generalizes both the theories of classical group and fuzzy group. The aim of this… More >

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517

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Phi-Hung Nguyen^*, Hong-Anh Pham
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3231-3248, 2023, DOI:10.32604/cmc.2023.031428
Abstract This study aims to assess and rank the service quality of the healthcare system utilizing a Fuzzy Analytical Hierarchical Process (Fuzzy AHP) and Grey Relational Analysis (Fuzzy GRA) technique. In this study, the six primary characteristics of healthcare service quality, comprising Tangibles (A), Healthcare Staff (B), Responsiveness (C), Relationships (D), Support Service (E), and Accessibility (F), are examined through a case study of 20 private and public hospitals in Hanoi, Vietnam. The weighting results of Fuzzy AHP technique indicated that Responsiveness (C) has the highest ranking, followed by Relationships (D) and Healthcare Staff (B). Meanwhile, Tangibility has finally comprised the… More >

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408

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Fahad R. Albogamy¹, M. A. Aiyashi², Fazirul Hisyam Hashim³, Imran Khan⁴, Bong Jun Choi^5,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3249-3261, 2023, DOI:10.32604/cmc.2023.031673
Abstract The non-orthogonal multiple access (NOMA) method is a novel multiple access technique that aims to increase spectral efficiency (SE) and accommodate enormous user accesses. Multi-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information, and multi-user detection algorithms, such as successive interference cancellation (SIC), are performed at the receiving end to demodulate the necessary user signals. Although its basic signal waveform, like LTE baseline, could be based on orthogonal frequency division multiple access (OFDMA) or discrete Fourier transform (DFT)-spread OFDM, NOMA superimposes numerous users in the power domain. In contrast… More >

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Sagheer Abbas¹, Syed Ali Raza^1,2, M. A. Khan³, Muhammad Adnan Khan^4,*, Atta-ur-Rahman⁵, Kiran Sultan⁶, Amir Mosavi^7,8,9
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3263-3278, 2023, DOI:10.32604/cmc.2023.032864
Abstract File labeling techniques have a long history in analyzing the anthological trends in computational linguistics. The situation becomes worse in the case of files downloaded into systems from the Internet. Currently, most users either have to change file names manually or leave a meaningless name of the files, which increases the time to search required files and results in redundancy and duplications of user files. Currently, no significant work is done on automated file labeling during the organization of heterogeneous user files. A few attempts have been made in topic modeling. However, one major drawback of current topic modeling approaches… More >

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Mahmoud Ragab^1,2,3,*, Maged Mostafa Mahmoud^4,5,6, Amer H. Asseri^2,7, Hani Choudhry^2,7, Haitham A. Yacoub⁸
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3279-3295, 2023, DOI:10.32604/cmc.2023.031037
Abstract Colorectal carcinoma (CRC) is one such dispersed cancer globally and also prominent one in causing cancer-based death. Conventionally, pathologists execute CRC diagnosis through visible scrutinizing under the microscope the resected tissue samples, stained and fixed through Haematoxylin and Eosin (H&E). The advancement of graphical processing systems has resulted in high potentiality for deep learning (DL) techniques in interpretating visual anatomy from high resolution medical images. This study develops a slime mould algorithm with deep transfer learning enabled colorectal cancer detection and classification (SMADTL-CCDC) algorithm. The presented SMADTL-CCDC technique intends to appropriately recognize the occurrence of colorectal cancer. To accomplish this,… More >

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454

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Pooja Dhiman¹, Santosh Kumar Henge¹, Sartaj Singh¹, Avinash Kaur², Parminder Singh^2,3, Mustapha Hadabou^3,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3297-3313, 2023, DOI:10.32604/cmc.2023.030558
Abstract This research paper puts emphasis on using cloud computing with Blockchain (BC) to improve the security and privacy in a cloud. The security of data is not guaranteed as there is always a risk of leakage of users’ data. Blockchain can be used in a multi-tenant cloud environment (MTCE) to improve the security of data, as it is a decentralized approach. Data is saved in unaltered form. Also, Blockchain is not owned by a single organization. The encryption process can be done using a Homomorphic encryption (HE) algorithm along with hashing technique, hereby allowing computations on encrypted data without the… More >

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473

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Mesfer Al Duhayyim^1,*, Saud S. Alotaibi², Shaha Al-Otaibi³, Fahd N. Al-Wesabi⁴, Mahmoud Othman⁵, Ishfaq Yaseen⁶, Mohammed Rizwanullah⁶, Abdelwahed Motwakel⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3315-3332, 2023, DOI:10.32604/cmc.2023.033250
Abstract Proper waste management models using recent technologies like computer vision, machine learning (ML), and deep learning (DL) are needed to effectively handle the massive quantity of increasing waste. Therefore, waste classification becomes a crucial topic which helps to categorize waste into hazardous or non-hazardous ones and thereby assist in the decision making of the waste management process. This study concentrates on the design of hazardous waste detection and classification using ensemble learning (HWDC-EL) technique to reduce toxicity and improve human health. The goal of the HWDC-EL technique is to detect the multiple classes of wastes, particularly hazardous and non-hazardous wastes.… More >

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447

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Akram Ali Alhadad^1,2,*, Omar Tarawneh³, Reham R. Mostafa¹, Hazem M. El-Bakry¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3333-3350, 2023, DOI:10.32604/cmc.2023.033413
Abstract COVID-19 is the common name of the disease caused by the novel coronavirus (2019-nCoV) that appeared in Wuhan, China in 2019. Discovering the infected people is the most important factor in the fight against the disease. The gold-standard test to diagnose COVID-19 is polymerase chain reaction (PCR), but it takes 5–6 h and, in the early stages of infection, may produce false-negative results. Examining Computed Tomography (CT) images to diagnose patients infected with COVID-19 has become an urgent necessity. In this study, we propose a residual attention deep support vector data description SVDD (RADSVDD) approach to diagnose COVID-19. It is… More >

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Khakoo Mal^1,2,*, Tayab Din Memon^1,3, Imtiaz Hussain Kalwar⁴, Bhawani Shankar Chowdhry⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3351-3370, 2023, DOI:10.32604/cmc.2023.032940
Abstract It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad vehicle. The proper estimation of adhesion conditions and their real-time implementation is considered a challenge for scholars. In this paper, the development of simulation model of extended Kalman filter (EKF) in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of track. Due to concurrent in nature, the Xilinx^® System-on-Chip Zynq Field Programmable Gate Array (FPGA) device is chosen to check the onboard estimation of wheel-rail interaction parameters by using the National Instruments (NI) myRIO^®… More >

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Nishant Behar^*, Manish Shrivastava
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3371-3389, 2023, DOI:10.32604/cmc.2023.031949
Abstract Breast cancer is the most prevalent cancer among women, and diagnosing it early is vital for successful treatment. The examination of images captured during biopsies plays an important role in determining whether a patient has cancer or not. However, the stochastic patterns, varying intensities of colors, and the large sizes of these images make it challenging to identify and mark malignant regions in them. Against this backdrop, this study proposes an approach to the pixel categorization based on the genetic algorithm (GA) and principal component analysis (PCA). The spatial features of the images were extracted using various filters, and the… More >

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575

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328

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Shuai Zhou¹, Dazhi Wang^1,*, Mingtian Du², Ye Li¹, Shuo Cao³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3391-3404, 2023, DOI:10.32604/cmc.2023.033397
Abstract The parameters of permanent magnet synchronous motor (PMSM) affect the performance of vector control servo system. Because of the complexity of nonlinear model of PMSM, it is very difficult to identify the parameters of PMSM. Aiming at the problems of large amount of data calculation, low identification accuracy and poor robustness in the process of multi parameter identification of permanent magnet synchronous motor, this paper proposes a weighted differential evolutionary particle swarm optimization algorithm based on double update strategy. By introducing adaptive judgment factor to control the proportion of weighted difference evolution (WDE) algorithm and particle swarm optimization (PSO) algorithm… More >

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425

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Jian Peng^1,2, Yifang Zhao^1,2, Dengyong Zhang^1,2,*, Feng Li^1,2, Arun Kumar Sangaiah³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3405-3419, 2023, DOI:10.32604/cmc.2023.027627
Abstract Recently, object detection based on convolutional neural networks (CNNs) has developed rapidly. The backbone networks for basic feature extraction are an important component of the whole detection task. Therefore, we present a new feature extraction strategy in this paper, which name is DSAFF-Net. In this strategy, we design: 1) a sandwich attention feature fusion module (SAFF module). Its purpose is to enhance the semantic information of shallow features and resolution of deep features, which is beneficial to small object detection after feature fusion. 2) to add a new stage called D-block to alleviate the disadvantages of decreasing spatial resolution when… More >

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753

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416

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Wajaree Weera¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Salem Ben Said⁴, Maria Emilia Camargo⁵, Chantapish Zamart¹, Thongchai Botmart^1,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3421-3438, 2023, DOI:10.32604/cmc.2023.030996
Abstract The current investigations provide the solutions of the nonlinear fractional order mathematical rape and its control model using the strength of artificial neural networks (ANNs) along with the Levenberg-Marquardt backpropagation approach (LMBA), i.e., artificial neural networks-Levenberg-Marquardt backpropagation approach (ANNs-LMBA). The fractional order investigations have been presented to find more realistic results of the mathematical form of the rape and its control model. The differential mathematical form of the nonlinear fractional order mathematical rape and its control model has six classes: susceptible native girls, infected immature girls, susceptible knowledgeable girls, infected knowledgeable girls, susceptible rapist population and infective rapist population. The… More >

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575

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Dengyong Zhang^1,2, Huaijian Pu^1,2, Feng Li^1,2,*, Xiangling Ding³, Victor S. Sheng⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3439-3454, 2023, DOI:10.32604/cmc.2023.027267
Abstract Now object detection based on deep learning tries different strategies. It uses fewer data training networks to achieve the effect of large dataset training. However, the existing methods usually do not achieve the balance between network parameters and training data. It makes the information provided by a small amount of picture data insufficient to optimize model parameters, resulting in unsatisfactory detection results. To improve the accuracy of few shot object detection, this paper proposes a network based on the transformer and high-resolution feature extraction (THR). High-resolution feature extraction maintains the resolution representation of the image. Channels and spatial attention are… More >

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660

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425

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Zulqurnain Sabir¹, Sánchez-Chero Manuel², Muhammad Asif Zahoor Raja³, Gilder-Cieza–Altamirano⁴, María-Verónica Seminario-Morales², Fernández Vásquez José Arquímedes⁵, Purihuamán Leonardo Celso Nazario⁶, Thongchai Botmart^7,*, Wajaree Weera⁷
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3455-3470, 2023, DOI:10.32604/cmc.2023.033352
Abstract The purpose of these investigations is to find the numerical outcomes of the fractional kind of biological system based on Leptospirosis by exploiting the strength of artificial neural networks aided by scale conjugate gradient, called ANNs-SCG. The fractional derivatives have been applied to get more reliable performances of the system. The mathematical form of the biological Leptospirosis system is divided into five categories, and the numerical performances of each model class will be provided by using the ANNs-SCG. The exactness of the ANNs-SCG is performed using the comparison of the reference and obtained results. The reference solutions have been obtained… More >

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392

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Mohammed Hadwan^1,2,*, Hamzah A. Alsayadi^3,4, Salah AL-Hagree⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3471-3487, 2023, DOI:10.32604/cmc.2023.033457
Abstract The attention-based encoder-decoder technique, known as the trans-former, is used to enhance the performance of end-to-end automatic speech recognition (ASR). This research focuses on applying ASR end-to-end transformer-based models for the Arabic language, as the researchers’ community pays little attention to it. The Muslims Holy Qur’an book is written using Arabic diacritized text. In this paper, an end-to-end transformer model to building a robust Qur’an vs. recognition is proposed. The acoustic model was built using the transformer-based model as deep learning by the PyTorch framework. A multi-head attention mechanism is utilized to represent the encoder and decoder in the acoustic… More >

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946

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433

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Ibrahim Mahmoud El-Henawy¹, Mostafa Elbaz², Zainab H. Ali^3,*, Noha Sakr⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3489-3502, 2023, DOI:10.32604/cmc.2023.033356
Abstract Medical image segmentation is a crucial process for computer-aided diagnosis and surgery. Medical image segmentation refers to portioning the images into small, disjointed parts for simplifying the processes of analysis and examination. Rician and speckle noise are different types of noise in magnetic resonance imaging (MRI) that affect the accuracy of the segmentation process negatively. Therefore, image enhancement has a significant role in MRI segmentation. This paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free image. The proposed techniques consider the… More >

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Lin Lang¹, Shuang Zhou¹, Minjuan Zhong^1,*, Guang Sun¹, Bin Pan¹, Peng Guo^1,2
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3503-3513, 2023, DOI:10.32604/cmc.2023.023596
Abstract Using the RFM (Recency, Frequency, Monetary value) model can provide valuable insights about customer clusters which is the core of customer relationship management. Due to accurate customer segment coming from dynamic weighted applications, in-depth targeted marketing may also use type of dynamic weight of R, F and M as factors. In this paper, we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights. Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data… More >

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541

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Iman Almomani^1,2, Walid El-Shafai^1,3,*, Aala AlKhayer¹, Albandari Alsumayt⁴, Sumayh S. Aljameel⁵, Khalid Alissa⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3515-3537, 2023, DOI:10.32604/cmc.2023.033765
Abstract Nowadays, there is tremendous growth in biometric authentication and cybersecurity applications. Thus, the efficient way of storing and securing personal biometric patterns is mandatory in most governmental and private sectors. Therefore, designing and implementing robust security algorithms for users’ biometrics is still a hot research area to be investigated. This work presents a powerful biometric security system (BSS) to protect different biometric modalities such as faces, iris, and fingerprints. The proposed BSS model is based on hybridizing auto-encoder (AE) network and a chaos-based ciphering algorithm to cipher the details of the stored biometric patterns and ensures their secrecy. The employed… More >

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1211

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467

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Gibrael Abosamra^*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3539-3560, 2023, DOI:10.32604/cmc.2023.032976
Abstract This paper introduces the third enhanced version of a genetic algorithm-based technique to allow fast and accurate detection of vehicle plate numbers (VPLN) in challenging image datasets. Since binarization of the input image is the most important and difficult step in the detection of VPLN, a hybrid technique is introduced that fuses the outputs of three fast techniques into a pool of connected components objects (CCO) and hence enriches the solution space with more solution candidates. Due to the combination of the outputs of the three binarization techniques, many CCOs are produced into the output pool from which one or… More >

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782

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406

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Sunil Kumar¹, Manisha Jailia¹, Sudeep Varshney², Nitish Pathak³, Shabana Urooj^4,*, Nouf Abd Elmunim⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3561-3577, 2023, DOI:10.32604/cmc.2023.029999
Abstract Vehicle detection is still challenging for intelligent transportation systems (ITS) to achieve satisfactory performance. The existing methods based on one stage and two-stage have intrinsic weakness in obtaining high vehicle detection performance. Due to advancements in detection technology, deep learning-based methods for vehicle detection have become more popular because of their higher detection accuracy and speed than the existing algorithms. This paper presents a robust vehicle detection technique based on Improved You Look Only Once (RVD-YOLOv5) to enhance vehicle detection accuracy. The proposed method works in three phases; in the first phase, the K-means algorithm performs data clustering on datasets… More >

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Junhyoung Oh¹, Kyungho Lee^2,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3579-3606, 2023, DOI:10.32604/cmc.2023.031491
Abstract As technology develops, the amount of information being used has increased a lot. Every company learns big data to provide customized services with its customers. Accordingly, collecting and analyzing data of the data subject has become one of the core competencies of the companies. However, when collecting and using it, the authority of the data subject may be violated. The data often identifies its subject by itself, and even if it is not a personal information that infringes on an individual’s authority, the moment it is connected, it becomes important and sensitive personal information that we have never thought of.… More >

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492

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Mohammed S. M. Gismalla^1,2,3, Asrul I. Azmi^1,2, Mohd R. Salim^1,2, Farabi Iqbal^1,2, Mohammad F. L. Abdullah⁴, Mosab Hamdan^5,6, Muzaffar Hamzah^5,*, Abu Sahmah M. Supa’at^1,2
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3607-3625, 2023, DOI:10.32604/cmc.2023.031192
Abstract Visible light communication (VLC), which is a prominent emerging solution that complements the radio frequency (RF) technology, exhibits the potential to meet the demands of fifth-generation (5G) and beyond technologies. The random movement of mobile terminals in the indoor environment is a challenge in the VLC system. The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio (SNR). As such, the optical attocells positions were optimized in this study with a developed try and error (TE) algorithm. The optimized optical attocells were examined… More >

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Fahad Alraddady¹, E. A. Zanaty², Aida H. Abu bakr³, Walaa M. Abd-Elhafiez^4,5,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3627-3646, 2023, DOI:10.32604/cmc.2023.027606
Abstract In this paper, we combine decision fusion methods with four meta-heuristic algorithms (Particle Swarm Optimization (PSO) algorithm, Cuckoo search algorithm, modification of Cuckoo Search (CS McCulloch) algorithm and Genetic algorithm) in order to improve the image segmentation. The proposed technique based on fusing the data from Particle Swarm Optimization (PSO), Cuckoo search, modification of Cuckoo Search (CS McCulloch) and Genetic algorithms are obtained for improving magnetic resonance images (MRIs) segmentation. Four algorithms are used to compute the accuracy of each method while the outputs are passed to fusion methods. In order to obtain parts of the points that determine similar… More >

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Ayesha¹, Muhammad Javed Iqbal¹, Iftikhar Ahmad^2,*, Madini O. Alassafi², Ahmed S. Alfakeeh², Ahmed Alhomoud³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3647-3661, 2023, DOI:10.32604/cmc.2023.020916
Abstract Contemporarily numerous analysts labored in the field of Vehicle detection which improves Intelligent Transport System (ITS) and reduces road accidents. The major obstacles in automatic detection of tiny vehicles are due to occlusion, environmental conditions, illumination, view angles and variation in size of objects. This research centers on tiny and partially occluded vehicle detection and identification in challenging scene specifically in crowed area. In this paper we present comprehensive methodology of tiny vehicle detection using Deep Neural Networks (DNN) namely CenterNet. Substantially DNN disregards objects that are small in size 5 pixels and more false positives likely to happen in… More >

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Muhammad Hamraz¹, Dost Muhammad Khan¹, Naz Gul¹, Amjad Ali¹, Zardad Khan¹, Shafiq Ahmad², Mejdal Alqahtani², Akber Abid Gardezi³, Muhammad Shafiq^4,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3663-3677, 2023, DOI:10.32604/cmc.2023.030064
Abstract The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio (SNR). The proposed method utilizes the robust measures of location i.e., the “Median” as well as the measures of variation i.e., “Median absolute deviation (MAD) and Interquartile range (IQR)” in the SNR. By this way, two independent robust signal-to-noise ratios have been proposed. The proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio (RSNR). The results obtained via… More >

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380

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Muhammad Raza Naqvi¹, Muhammad Waseem Iqbal^2,*, Syed Khuram Shahzad³, M. Usman Ashraf⁴, Khalid Alsubhi⁵, Hani Moaiteq Aljahdali⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3679-3695, 2023, DOI:10.32604/cmc.2023.030340
Abstract Health care has become an essential social-economic concern for all stakeholders (e.g., patients, doctors, hospitals etc.), health needs, private care and the elderly class of society. The massive increase in the usage of health care Internet of things (IoT) applications has great technological evolvement in human life. There are various smart health care services like remote patient monitoring, diagnostic, disease-specific remote treatments and telemedicine. These applications are available in a split fashion and provide solutions for variant diseases, medical resources and remote service management. The main objective of this research is to provide a management platform where all these services… More >

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926

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Nada Ali Hakami¹, Hanan Ahmed Hosni Mahmoud^2,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3697-3710, 2023, DOI:10.32604/cmc.2023.031525
Abstract A worthy text summarization should represent the fundamental content of the document. Recent studies on computerized text summarization tried to present solutions to this challenging problem. Attention models are employed extensively in text summarization process. Classical attention techniques are utilized to acquire the context data in the decoding phase. Nevertheless, without real and efficient feature extraction, the produced summary may diverge from the core topic. In this article, we present an encoder-decoder attention system employing dual attention mechanism. In the dual attention mechanism, the attention algorithm gathers main data from the encoder side. In the dual attention model, the system… More >

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386

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Sugandhi Midha¹, Sahil Verma^1,*, Kavita¹, Mohit Mittal², Nz Jhanjhi^3,4, Mehedi Masud⁵, Mohammed A. AlZain⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3711-3726, 2023, DOI:10.32604/cmc.2023.027992
Abstract Cloud-based SDN (Software Defined Network) integration offers new kinds of agility, flexibility, automation, and speed in the network. Enterprises and Cloud providers both leverage the benefits as networks can be configured and optimized based on the application requirement. The integration of cloud and SDN paradigms has played an indispensable role in improving ubiquitous health care services. It has improved the real-time monitoring of patients by medical practitioners. Patients’ data get stored at the central server on the cloud from where it is available to medical practitioners in no time. The centralisation of data on the server makes it more vulnerable… More >

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362

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Md Zahid Hasan Ontor¹, Md Mamun Ali¹, Kawsar Ahmed^2,3,*, Francis M. Bui³, Fahad Ahmed Al-Zahrani⁴, S. M. Hasan Mahmud⁵, Sami Azam⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3727-3741, 2023, DOI:10.32604/cmc.2023.032794
Abstract Cervical Cancer (CC) is a rapidly growing disease among women throughout the world, especially in developed and developing countries. For this many women have died. Fortunately, it is curable if it can be diagnosed and detected at an early stage and taken proper treatment. But the high cost, awareness, highly equipped diagnosis environment, and availability of screening tests is a major barrier to participating in screening or clinical test diagnoses to detect CC at an early stage. To solve this issue, the study focuses on building a deep learning-based automated system to diagnose CC in the early stage using cervix… More >

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Arfat Ahmad Khan¹, Malik Muhammad Ali Shahid², Rab Nawaz Bashir², Salman Iqbal², Arshad Shehzad Ahmad Shahid³, Javeria Maqbool⁴, Chitapong Wechtaisong^5,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3743-3761, 2023, DOI:10.32604/cmc.2023.033924
Abstract COVID-19 disease caused by the SARS-CoV-2 virus has created social and economic disruption across the world. The ability of the COVID-19 virus to quickly mutate and transfer has created serious concerns across the world. It is essential to detect COVID-19 infection caused by different variants to take preventive measures accordingly. The existing method of detection of infections caused by COVID-19 and its variants is costly and time-consuming. The impacts of the COVID-19 pandemic in developing countries are very drastic due to the unavailability of medical facilities and infrastructure to handle the pandemic. Pneumonia is the major symptom of COVID-19 infection.… More >

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Mrim M. Alnfiai^*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3763-3780, 2023, DOI:10.32604/cmc.2023.033448
Abstract Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems. Both structural and non-structural data of industrial systems are collected, which covers data formats of time-series, text, images, sound, etc. Several researchers discussed above were mostly qualitative, and ceratin techniques need expert guidance to conclude on the condition of gearboxes. But, in this study, an improved symbiotic organism search with deep learning enabled fault diagnosis (ISOSDL-FD) model for gearbox fault detection in industrial systems. The proposed ISOSDL-FD technique majorly concentrates on the identification and classification of faults in the gearbox… More >

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359

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Said Benkirane¹, Azidine Guezzaz¹, Mourade Azrour¹, Akber Abid Gardezi², Shafiq Ahmad³, Abdelaty Edrees Sayed³, Salman Naseer⁴, Muhammad Shafiq^5,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3781-3794, 2023, DOI:10.32604/cmc.2023.033119
Abstract Today, road safety remains a serious concern for governments around the world. In fact, approximately 1.35 million people die and 2–50 million are injured on public roads worldwide each year. Straight bends in road traffic are the main cause of many road accidents, and excessive and inappropriate speed in this very critical area can cause drivers to lose their vehicle stability. For these reasons, new solutions must be considered to stop this disaster and save lives. Therefore, it is necessary to study this topic very carefully and use new technologies such as Vehicle Ad Hoc Networks (VANET), Internet of Things… More >

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416

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Ahmed M. Alghamdi^1,*, Khalid Hamid², Muhammad Waseem Iqbal³, M. Usman Ashraf⁴, Abdullah Alshahrani⁵, Adel Alshamrani⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3795-3810, 2023, DOI:10.32604/cmc.2023.033976
Abstract In various fields, different networks are used, most of the time not of a single kind; but rather a mix of at least two networks. These kinds of networks are called bridge networks which are utilized in interconnection networks of PC, portable networks, spine of internet, networks engaged with advanced mechanics, power generation interconnection, bio-informatics and substance intensify structures. Any number that can be entirely calculated by a graph is called graph invariants. Countless mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty years. Nevertheless, no trustworthy evaluation has been embraced to pick, how… More >

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Wei Wu¹, Weigong Zhang^1,*, Dong Wang¹, Lydia Zhu², Xiang Song³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3811-3828, 2023, DOI:10.32604/cmc.2023.029787
Abstract An increase in car ownership brings convenience to people’s life. However, it also leads to frequent traffic accidents. Precisely forecasting surrounding agents’ future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian collisions. Long-short-term memory (LSTM) network is often used for vehicle trajectory prediction, but it has some shortages such as gradient explosion and low efficiency. A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’ future trajectories in a complex traffic environment. It realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on attention mechanism. To perform trajectory prediction more… More >

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378

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Qamar Hafeez¹, Waqar Aslam¹, M. Ikramullah Lali², Shafiq Ahmad³, Mejdal Alqahtani³, Muhammad Shafiq^4,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3829-3847, 2023, DOI:10.32604/cmc.2023.026422
Abstract Optical Mark Recognition (OMR) systems have been studied since 1970. It is widely accepted as a data entry technique. OMR technology is used for surveys and multiple-choice questionnaires. Due to its ease of use, OMR technology has grown in popularity over the past two decades and is widely used in universities and colleges to automatically grade and grade student responses to questionnaires. The accuracy of OMR systems is very important due to the environment in which they are used. The OMR algorithm relies on pixel projection or Hough transform to determine the exact answer in the document. These techniques rely… More >

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610

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Musawwer Khan¹, Islam Ali¹, Shahzada Khurram², Salman Naseer³, Shafiq Ahmad⁴, Ahmed T. Soliman⁴, Akber Abid Gardezi⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3849-3863, 2023, DOI:10.32604/cmc.2023.027387
Abstract The effectiveness of the Business Intelligence (BI) system mainly depends on the quality of knowledge it produces. The decision-making process is hindered, and the user’s trust is lost, if the knowledge offered is undesired or of poor quality. A Data Warehouse (DW) is a huge collection of data gathered from many sources and an important part of any BI solution to assist management in making better decisions. The Extract, Transform, and Load (ETL) process is the backbone of a DW system, and it is responsible for moving data from source systems into the DW system. The more mature the ETL… More >

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392

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Souvik Pal^1,2,*, Hannah VijayKumar³, D. Akila⁴, N. Z. Jhanjhi^5,6, Omar A. Darwish⁷, Fathi Amsaad⁸
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3865-3880, 2023, DOI:10.32604/cmc.2023.029038
Abstract Smart farming has become a strategic approach of sustainable agriculture management and monitoring with the infrastructure to exploit modern technologies, including big data, the cloud, and the Internet of Things (IoT). Many researchers try to integrate IoT-based smart farming on cloud platforms effectively. They define various frameworks on smart farming and monitoring system and still lacks to define effective data management schemes. Since IoT-cloud systems involve massive structured and unstructured data, data optimization comes into the picture. Hence, this research designs an Information-Centric IoT-based Smart Farming with Dynamic Data Optimization (ICISF-DDO), which enhances the performance of the smart farming infrastructure… More >

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375

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Asma Sajjad¹, Humaira Ashraf¹, NZ Jhanjhi^2,3,*, Mamoona Humayun⁴, Mehedi Masud⁵, Mohammed A. AlZain⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3881-3898, 2023, DOI:10.32604/cmc.2023.030197
Abstract The most valuable resource on the planet is no longer oil, but data. The transmission of this data securely over the internet is another challenge that comes with its ever-increasing value. In order to transmit sensitive information securely, researchers are combining robust cryptography and steganographic approaches. The objective of this research is to introduce a more secure method of video steganography by using Deoxyribonucleic acid (DNA) for embedding encrypted data and an intelligent frame selection algorithm to improve video imperceptibility. In the previous approach, DNA was used only for frame selection. If this DNA is compromised, then our frames with… More >

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869

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Sajadul Hassan Kumhar¹, Syed Immamul Ansarullah², Akber Abid Gardezi³, Shafiq Ahmad⁴, Abdelaty Edrees Sayed⁴, Muhammad Shafiq^5,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3899-3912, 2023, DOI:10.32604/cmc.2023.032290
Abstract English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu translation. In order to make knowledge available to the masses, there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated fashion. Machine translation has achieved this goal with encouraging results. When decoding the source text into the target language, the translator checks all the characteristics of the text. To achieve machine translation, rule-based, computational, hybrid and neural machine translation approaches have been proposed to… More >

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673

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Muhammad Islam Satti¹, Jawad Ahmed², Hafiz Syed Muhammad Muslim¹, Akber Abid Gardezi³, Shafiq Ahmad⁴, Abdelaty Edrees Sayed⁴, Salman Naseer⁵, Muhammad Shafiq^6,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3913-3929, 2023, DOI:10.32604/cmc.2023.033001
Abstract Daily newspapers publish a tremendous amount of information disseminated through the Internet. Freely available and easily accessible large online repositories are not indexed and are in an un-processable format. The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed. There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora, especially for South Asian languages. The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu language.… More >

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435

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Naixin Kang¹, Zhenhu Ning^1,*, Shiqiang Zhang¹, Sadaqat ur Rehman², Muhammad Waqas^1,3
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3931-3943, 2023, DOI:10.32604/cmc.2023.029711
Abstract With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based… More >

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Walaa N. Ismail^1,2,*, Hessah A. Alsalamah^3,4, Ebtesam Mohamed²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3945-3976, 2023, DOI:10.32604/cmc.2023.031194
Abstract As a result of the increased number of COVID-19 cases, Ensemble Machine Learning (EML) would be an effective tool for combatting this pandemic outbreak. An ensemble of classifiers can improve the performance of single machine learning (ML) classifiers, especially stacking-based ensemble learning. Stacking utilizes heterogeneous-base learners trained in parallel and combines their predictions using a meta-model to determine the final prediction results. However, building an ensemble often causes the model performance to decrease due to the increasing number of learners that are not being properly selected. Therefore, the goal of this paper is to develop and evaluate a generic, data-independent… More >

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514

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Billel Meghni¹, Afaf Benamor², Oussama Hachana³, Ahmad Taher Azar^4,5,*, Amira Boulmaiz⁶, Salah Saad¹, El-Sayed M. El-kenawy^7,8, Nashwa Ahmad Kamal⁹, Suliman Mohamed Fati⁵, Naglaa K. Bahgaat¹⁰
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3977-3996, 2023, DOI:10.32604/cmc.2023.029838
Abstract The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, to improve the rendition of… More >

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623

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Lojain Nahhas¹, Marwan Albahar^1,*, Abdullah Alammari², Anca Jurcut³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3997-4014, 2023, DOI:10.32604/cmc.2023.028316
Abstract There has been an increase in attacks on mobile devices, such as smartphones and tablets, due to their growing popularity. Mobile malware is one of the most dangerous threats, causing both security breaches and financial losses. Mobile malware is likely to continue to evolve and proliferate to carry out a variety of cybercrimes on mobile devices. Mobile malware specifically targets Android operating system as it has grown in popularity. The rapid proliferation of Android malware apps poses a significant security risk to users, making static and manual analysis of malicious files difficult. Therefore, efficient identification and classification of Android malicious… More >

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485

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Dae-Young Kim¹, SoYeon Lee², Seokhoon Kim^1,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4015-4025, 2023, DOI:10.32604/cmc.2023.027078
Abstract Networks based on backscatter communication provide wireless data transmission in the absence of a power source. A backscatter device receives a radio frequency (RF) source and creates a backscattered signal that delivers data; this enables new services in battery-less domains with massive Internet-of-Things (IoT) devices. Connectivity is highly energy-efficient in the context of massive IoT applications. Outdoors, long-range (LoRa) backscattering facilitates large IoT services. A backscatter network guarantees timeslot-and contention-based transmission. Timeslot-based transmission ensures data transmission, but is not scalable to different numbers of transmission devices. If contention-based transmission is used, collisions are unavoidable. To reduce collisions and increase transmission… More >

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639

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514

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Doaa Sami Khafaga¹, El-Sayed M. El-kenawy², Fadwa Alrowais^1,*, Sunil Kumar³, Abdelhameed Ibrahim⁴, Abdelaziz A. Abdelhamid^5,6
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4027-4041, 2023, DOI:10.32604/cmc.2023.033039
Abstract In data mining and machine learning, feature selection is a critical part of the process of selecting the optimal subset of features based on the target data. There are 2ⁿ potential feature subsets for every n features in a dataset, making it difficult to pick the best set of features using standard approaches. Consequently, in this research, a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm (ASSOA) has been proposed. When using metaheuristics to pick features, it is common for the selection of features to vary across runs, which can lead to instability. Because of… More >

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367

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Yinggang Sun¹, Hongguo Zhang¹, Chao Ma^1,*, Hai Huang¹, Dongyang Zhan^2,3, Jiaxing Qu⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4043-4058, 2023, DOI:10.32604/cmc.2023.031684
Abstract The problem of data island hinders the application of big data in artificial intelligence model training, so researchers propose a federated learning framework. It enables model training without having to centralize all data in a central storage point. In the current horizontal federated learning scheme, each participant gets the final jointly trained model. No solution is proposed for scenarios where participants only provide training data in exchange for benefits, but do not care about the final jointly trained model. Therefore, this paper proposes a new boosted tree algorithm, called RPBT (the originator Rights Protected federated Boosted Tree algorithm). Compared with… More >

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