Open Access

Qingbing Ji^1,2,*, Zhihong Rao^1,2, Lvlin Ni², Wei Zhao², Jing Fu³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.026949
Abstract MEGA is an end-to-end encrypted cloud storage platform controlled by users. Moreover, the communication between MEGA client and server is carried out under the protection of Transport Layer Security (TLS) encryption, it is difficult to intercept the key data packets in the process of MEGA registration, login, file data upload, and download. These characteristics of MEGA have brought great difficulties to its forensics. This paper presents a method to attack MEGA to provide an effective method for MEGA’s forensics. By debugging the open-source code of MEGA and analyzing the security white paper published, this paper first clarifies the encryption mechanism… More >

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Hongly Va¹, Min-Hyung Choi², Min Hong^3,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 831-848, 2022, DOI:10.32604/cmc.2022.029576
Abstract This paper presents a parallel method for simulating real-time 3D deformable objects using the volume preservation mass-spring system method on tetrahedron meshes. In general, the conventional mass-spring system is manipulated as a force-driven method because it is fast, simple to implement, and the parameters can be controlled. However, the springs in traditional mass-spring system can be excessively elongated which cause severe stability and robustness issues that lead to shape restoring, simulation blow-up, and huge volume loss of the deformable object. In addition, traditional method that uses a serial process of the central processing unit (CPU) to solve the system in… More >

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Romany F. Mansour^1,*, Sara A. Althubiti², Fayadh Alenezi³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 849-864, 2022, DOI:10.32604/cmc.2022.029265
Abstract Recently, computer vision (CV) based disease diagnosis models have been utilized in various areas of healthcare. At the same time, deep learning (DL) and machine learning (ML) models play a vital role in the healthcare sector for the effectual recognition of diseases using medical imaging tools. This study develops a novel computer vision with optimal machine learning enabled skin lesion detection and classification (CVOML-SLDC) model. The goal of the CVOML-SLDC model is to determine the appropriate class labels for the test dermoscopic images. Primarily, the CVOML-SLDC model derives a gaussian filtering (GF) approach to pre-process the input images and graph… More >

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Doaa Sami Khafaga¹, Amel Ali Alhussan^1,*, El-Sayed M. El-kenawy^2,3, Abdelhameed Ibrahim⁴, Said H. Abd Elkhalik³, Shady Y. El-Mashad⁵, Abdelaziz A. Abdelhamid^6,7
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 865-881, 2022, DOI:10.32604/cmc.2022.028550
Abstract The design of an antenna requires a careful selection of its parameters to retain the desired performance. However, this task is time-consuming when the traditional approaches are employed, which represents a significant challenge. On the other hand, machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended performance. In this paper, we propose a novel approach for accurately predicting the bandwidth of metamaterial antenna. The proposed approach is based on employing the recently emerged guided whale… More >

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Yuzhen Liu^1,2, Zhe Liu³, Xiaoliang Wang^1,2,*, Qing Yang⁴, Guocai Zuo⁵, Frank Jiang⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 883-898, 2022, DOI:10.32604/cmc.2022.029002
Abstract

A game measurement model considering the attacker's knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of service. We quantified the sensitive level of information according to the user's personalized sensitive information protection needs. Based on the probability distribution of sensitive level and attacker's knowledge background type, the strategy combination of service provider and attacker was analyzed, and a game-based sensitive information protection model was constructed. Through the combination of strategies under Bayesian equilibrium, the information entropy was used to measure the leakage of sensitive… More >

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Ashit Kumar Dutta^1,*, Yasser Albagory², Abdul Rahaman Wahab Sait³, Ismail Mohamed Keshta¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 899-915, 2022, DOI:10.32604/cmc.2022.026783
Abstract Recently, autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare, agriculture, industrial automation, etc. Among the interesting applications of autonomous systems, their applicability in agricultural sector becomes significant. Autonomous unmanned aerial vehicles (UAVs) can be used for suitable site-specific weed management (SSWM) to improve crop productivity. In spite of substantial advancements in UAV based data collection systems, automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops. The recently developed deep learning (DL) models have exhibited effective performance in several… More >

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Abdelaziz A. Abdelhamid^1,3,*, Sultan R. Alotaibi²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 917-933, 2022, DOI:10.32604/cmc.2022.027653
Abstract Employing machine learning techniques in predicting the parameters of metamaterial antennas has a significant impact on the reduction of the time needed to design an antenna with optimal parameters using simulation tools. In this paper, we propose a new approach for predicting the bandwidth of metamaterial antenna using a novel ensemble model. The proposed ensemble model is composed of two levels of regression models. The first level consists of three strong models namely, random forest, support vector regression, and light gradient boosting machine. Whereas the second level is based on the ElasticNet regression model, which receives the prediction results from… More >

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Tsung-Yu Lu¹, Mu-En Wu², Er-Hao Chen³, Yeong-Luh Ueng^4,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 935-952, 2022, DOI:10.32604/cmc.2022.026717
Abstract This paper presents an off-line handwritten signature verification system based on the Siamese network, where a hybrid architecture is used. The Residual neural Network (ResNet) is used to realize a powerful feature extraction model such that Writer Independent (WI) features can be effectively learned. A single-layer Siamese Neural Network (NN) is used to realize a Writer Dependent (WD) classifier such that the storage space can be minimized. For the purpose of reducing the impact of the high intraclass variability of the signature and ensuring that the Siamese network can learn more effectively, we propose a method of selecting a reference… More >

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529

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Muhammad Umar Nasir¹, Muhammad Adnan Khan^1,2, Muhammad Zubair³, Taher M. Ghazal^4,5, Raed A. Said⁶, Hussam Al Hamadi^7,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 953-963, 2022, DOI:10.32604/cmc.2022.028958
Abstract One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic data. Furthermore, the complicated genetic disease has a very diverse genotype, making it challenging to find genetic markers. This is a challenging process since it must be completed effectively and efficiently. This research article focuses largely on which patients are more likely to have a genetic disorder based on numerous medical parameters. Using the patient’s medical history, we used a genetic disease prediction algorithm that predicts if the patient is likely to be diagnosed with a genetic disorder. To… More >

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Sultan Ahmad¹, Shakir Khan², Mohamed Fahad AlAjmi³, Ashit Kumar Dutta⁴, L. Minh Dang⁵, Gyanendra Prasad Joshi⁶, Hyeonjoon Moon^6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 965-979, 2022, DOI:10.32604/cmc.2022.025760
Abstract In recent times, Internet of Medical Things (IoMT) gained much attention in medical services and healthcare management domain. Since healthcare sector generates massive volumes of data like personal details, historical medical data, hospitalization records, and discharging records, IoMT devices too evolved with potentials to handle such high quantities of data. Privacy and security of the data, gathered by IoMT gadgets, are major issues while transmitting or saving it in cloud. The advancements made in Artificial Intelligence (AI) and encryption techniques find a way to handle massive quantities of medical data and achieve security. In this view, the current study presents… More >

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Thongchai Botmart¹, Wajaree Weera^1,*, Muhammad Asif Zahoor Raja², Zulqurnain Sabir³, Qusain Hiader⁴, Gilder Cieza Altamirano⁵, Plinio Junior Muro Solano⁶, Alfonso Tesen Arroyo⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 981-999, 2022, DOI:10.32604/cmc.2022.028921
Abstract In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order mathematical model will be presented… More >

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Syed Nauyan Rashid¹, Muhammad Hanif^2,*, Usman Habib², Akhtar Khalil³, Omair Inam⁴, Hafeez Ur Rehman¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1001-1017, 2022, DOI:10.32604/cmc.2022.023135
Abstract Gliomas are the most aggressive brain tumors caused by the abnormal growth of brain tissues. The life expectancy of patients diagnosed with gliomas decreases exponentially. Most gliomas are diagnosed in later stages, resulting in imminent death. On average, patients do not survive 14 months after diagnosis. The only way to minimize the impact of this inevitable disease is through early diagnosis. The Magnetic Resonance Imaging (MRI) scans, because of their better tissue contrast, are most frequently used to assess the brain tissues. The manual classification of MRI scans takes a reasonable amount of time to classify brain tumors. Besides this,… More >

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Khaled Benkouider¹, Aceng Sambas², Ibrahim Mohammed Sulaiman³, Mustafa Mamat⁴, Kottakkaran Sooppy Nisar^5,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1019-1035, 2022, DOI:10.32604/cmc.2022.025836
Abstract This study introduces a new continuous time differential system, which contains ten terms with three quadratic nonlinearities. The new system can demonstrate hyperchaotic, chaotic, quasi-periodic, and periodic behaviors for its different parameter values. All theoretical and numerical analysis are investigated to confirm the complex hyperchaotic behavior of our proposed model using many tools that include Kaplan-Yorke dimension, equilibrium points stability, bifurcation diagrams, and Lyapunov exponents. By means of Multisim software, the authors also designed an electronic circuit to confirm our proposed systems’ physical feasibility. MATLAB and Multisim simulation results excellently agree with each other, which validate the feasibility of our… More >

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Yazeed Yasin Ghadi¹, Mouazma Batool², Munkhjargal Gochoo³, Suliman A. Alsuhibany⁴, Tamara al Shloul⁵, Ahmad Jalal², Jeongmin Park^6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1037-1053, 2022, DOI:10.32604/cmc.2022.027422
Abstract Over the last decade, there is a surge of attention in establishing ambient assisted living (AAL) solutions to assist individuals live independently. With a social and economic perspective, the demographic shift toward an elderly population has brought new challenges to today’s society. AAL can offer a variety of solutions for increasing people’s quality of life, allowing them to live healthier and more independently for longer. In this paper, we have proposed a novel AAL solution using a hybrid bidirectional long-term and short-term memory networks (BiLSTM) and convolutional neural network (CNN) classifier. We first pre-processed the signal data, then used time-frequency… More >

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594

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Omar A. Saraereh^*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1055-1066, 2022, DOI:10.32604/cmc.2022.030193
Abstract Wireless data traffic has expanded at a rate that reminds us of Moore’s prediction for integrated circuits in recent years, necessitating ongoing attempts to supply wireless systems with ever-larger data rates in the near future, despite the under-deployment of 5G networks. Terahertz (THz) communication has been considered a viable response to communication blackout due to the rapid development of THz technology and sensors. THz communication has a high frequency, which allows for better penetration. It is a fast expanding and evolving industry, driven by an increase in wireless traffic volume and data transfer speeds. A THz modulator based on a… More >

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Tahani Alatawi^*, Ahamed Aljuhani
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1067-1086, 2022, DOI:10.32604/cmc.2022.029283
Abstract The rapid development of the Internet of Things (IoT) in the industrial domain has led to the new term the Industrial Internet of Things (IIoT). The IIoT includes several devices, applications, and services that connect the physical and virtual space in order to provide smart, cost-effective, and scalable systems. Although the IIoT has been deployed and integrated into a wide range of industrial control systems, preserving security and privacy of such a technology remains a big challenge. An anomaly-based Intrusion Detection System (IDS) can be an effective security solution for maintaining the confidentiality, integrity, and availability of data transmitted in… More >

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Ahmad Taher Azar^1,2,*, Mustafa Samy Elgendy¹, Mustafa Abdul Salam^1,3, Khaled M. Fouad^1,4
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1087-1108, 2022, DOI:10.32604/cmc.2022.028184
Abstract Big data is a vast amount of structured and unstructured data that must be dealt with on a regular basis. Dimensionality reduction is the process of converting a huge set of data into data with tiny dimensions so that equal information may be expressed easily. These tactics are frequently utilized to improve classification or regression challenges while dealing with machine learning issues. To achieve dimensionality reduction for huge data sets, this paper offers a hybrid particle swarm optimization-rough set PSO-RS and Mayfly algorithm-rough set MA-RS. A novel hybrid strategy based on the Mayfly algorithm (MA) and the rough set (RS)… More >

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558

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Mohamed W. Abo El-Soud^1,2,*, Tarek Gaber^2,3, Mohamed Tahoun², Abdullah Alourani¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1109-1123, 2022, DOI:10.32604/cmc.2022.028561
Abstract The prevalence of melanoma skin cancer has increased in recent decades. The greatest risk from melanoma is its ability to broadly spread throughout the body by means of lymphatic vessels and veins. Thus, the early diagnosis of melanoma is a key factor in improving the prognosis of the disease. Deep learning makes it possible to design and develop intelligent systems that can be used in detecting and classifying skin lesions from visible-light images. Such systems can provide early and accurate diagnoses of melanoma and other types of skin diseases. This paper proposes a new method which can be used for… More >

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Abdallah Abdallah¹, Mohamad Khairi Ishak², Nor Samsiah Sani³, Imran Khan⁴, Fahad R. Albogamy⁵, Hirofumi Amano⁶, Samih M. Mostafa^7,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1125-1140, 2022, DOI:10.32604/cmc.2022.025810
Abstract Software-defined networking (SDN) is a new paradigm that promises to change by breaking vertical integration, decoupling network control logic from the underlying routers and switches, promoting (logical) network control centralization, and introducing network programming. However, the controller is similarly vulnerable to a “single point of failure”, an attacker can execute a distributed denial of service (DDoS) attack that invalidates the controller and compromises the network security in SDN. To address the problem of DDoS traffic detection in SDN, a novel detection approach based on information entropy and deep neural network (DNN) is proposed. This approach contains a DNN-based DDoS traffic… More >

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M. M. Lotfy¹, Hazem M. El-Bakry², M. M. Elgayar³, Shaker El-Sappagh^4,5, G. Abdallah M. I¹, A. A. Soliman¹, Kyung Sup Kwak^6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1141-1158, 2022, DOI:10.32604/cmc.2022.024193
Abstract Early detection of the Covid-19 disease is essential due to its higher rate of infection affecting tens of millions of people, and its high number of deaths also by 7%. For that purpose, a proposed model of several stages was developed. The first stage is optimizing the images using dynamic adaptive histogram equalization, performing a semantic segmentation using DeepLabv3Plus, then augmenting the data by flipping it horizontally, rotating it, then flipping it vertically. The second stage builds a custom convolutional neural network model using several pre-trained ImageNet. Finally, the model compares the pre-trained data to the new output, while repeatedly… More >

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Mohammad Alamgeer¹, Saud S. Alotaibi², Shaha Al-Otaibi³, Nazik Alturki³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Ishfaq Yaseen⁴, Mohamed I. Eldesouki⁵
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1159-1175, 2022, DOI:10.32604/cmc.2022.028275
Abstract Latest developments in computing and communication technologies are enabled the design of connected healthcare system which are mainly based on IoT and Edge technologies. Blockchain, data encryption, and deep learning (DL) models can be utilized to design efficient security solutions for IoT healthcare applications. In this aspect, this article introduces a Blockchain with privacy preserving image encryption and optimal deep learning (BPPIE-ODL) technique for IoT healthcare applications. The proposed BPPIE-ODL technique intends to securely transmit the encrypted medical images captured by IoT devices and performs classification process at the cloud server. The proposed BPPIE-ODL technique encompasses the design of dragonfly… More >

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Muhammad Sajjad¹, Tariq Shah^1,*, Mohammad Mazyad Hazzazi², Adel R. Alharbi³, Iqtadar Hussain⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1177-1194, 2022, DOI:10.32604/cmc.2022.025245
Abstract The decoding algorithm for the correction of errors of arbitrary Mannheim weight has discussed for Lattice constellations and codes from quadratic number fields. Following these lines, the decoding algorithms for the correction of errors of length cyclic codes over quaternion integers of Quaternion Mannheim weight one up to two coordinates have considered. In continuation, the case of cyclic codes of lengths and has studied to improve the error correction efficiency. In this study, we present the decoding of cyclic codes of length and length 2 (where is prime integer and is Euler phi function) over Hamilton Quaternion integers of Quaternion… More >

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548

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Doaa Sami Khafaga¹, Mohammad Zubair Khan², Muhammad Awais Javed³, Amel Ali Alhussan^1,*, Wael Said⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1195-1206, 2022, DOI:10.32604/cmc.2022.028280
Abstract Vehicular communication is the backbone of future Intelligent Transportation Systems (ITS). It offers a network-based solution for vehicle safety, cooperative awareness, and traffic management applications. For safety applications, Basic Safety Messages (BSM) containing mobility information is shared by the vehicles in their neighborhood to continuously monitor other nearby vehicles and prepare a local traffic map. BSMs are shared using mode 4 of Cellular V2X (C-V2X) communications in which resources are allocated in an ad hoc manner. However, the strict packet transmission requirements of BSM and hidden node problem causes packet collisions in a vehicular network, thus reducing the reliability of… More >

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Mohammed Alarfaj¹, Manahil Waheed², Yazeed Yasin Ghadi³, Tamara al Shloul⁴, Suliman A. Alsuhibany⁵, Ahmad Jalal², Jeongmin Park^6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1207-1223, 2022, DOI:10.32604/cmc.2022.025671
Abstract Human object interaction (HOI) recognition plays an important role in the designing of surveillance and monitoring systems for healthcare, sports, education, and public areas. It involves localizing the human and object targets and then identifying the interactions between them. However, it is a challenging task that highly depends on the extraction of robust and distinctive features from the targets and the use of fast and efficient classifiers. Hence, the proposed system offers an automated body-parts-based solution for HOI recognition. This system uses RGB (red, green, blue) images as input and segments the desired parts of the images through a segmentation… More >

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Muhammad Haroon Aftab¹, Kamel Jebreen^2,*, Mohammad Issa Sowaity³, Muhammad Hussain⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1225-1236, 2022, DOI:10.32604/cmc.2022.029009
Abstract In this article, we study different molecular structures such as Polythiophene network, for and , Orthosilicate (Nesosilicate) , Pyrosilicates (Sorosilicates) , Chain silicates (Pyroxenes), and Cyclic silicates (Ring Silicates) for their cardinalities, chromatic numbers, graph variations, eigenvalues obtained from the adjacency matrices which are square matrices in order and their corresponding characteristics polynomials. We convert the general structures of these chemical networks in to mathematical graphical structures. We transform the molecular structures of these chemical networks which are mentioned above, into a simple and undirected planar graph and sketch them with various techniques of mathematics. The matrices obtained from these… More >

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Najla Bagais^*, Etimad Fadel, Amal Al-Mansour
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1237-1267, 2022, DOI:10.32604/cmc.2022.026070
Abstract Wireless sensor networks (WSNs) are considered the backbone of the Internet of Things (IoT), which enables sensor nodes (SNs) to achieve applications similarly to human intelligence. However, integrating a WSN with the IoT is challenging and causes issues that require careful exploration. Prolonging the lifetime of a network through appropriately utilising energy consumption is among the essential challenges due to the limited resources of SNs. Thus, recent research has examined mobile sinks (MSs), which have been introduced to improve the overall efficiency of WSNs. MSs bear the burden of data collection instead of consuming energy at the routeing by SNs.… More >

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2

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Narathip Chaobankoh¹, Tallit Jumphoo¹, Monthippa Uthansakul¹, Khomdet Phapatanaburi², Bura Sindthupakorn³, Supakit Rooppakhun⁴, Peerapong Uthansakul^1,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1269-1282, 2022, DOI:10.32604/cmc.2022.027474
Abstract Recently, the Muscle-Computer Interface (MCI) has been extensively popular for employing Electromyography (EMG) signals to help the development of various assistive devices. However, few studies have focused on ankle foot movement classification considering EMG signals at limb position. This work proposes a new framework considering two EMG signals at a lower-limb position to classify the ankle movement characteristics based on normal walking cycles. For this purpose, we introduce a human ankle-foot movement classification method using a two-dimensional-convolutional neural network (2D-CNN) with low-cost EMG sensors based on lower-limb motion. The time-domain signals of EMG obtained from two sensors belonging to Dorsiflexion,… More >

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Heba A. Elzeheiry^*, Sherief Barakat, Amira Rezk
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1283-1305, 2022, DOI:10.32604/cmc.2022.027345
Abstract Electronic Health Records (EHRs) are the digital form of patients’ medical reports or records. EHRs facilitate advanced analytics and aid in better decision-making for clinical data. Medical data are very complicated and using one classification algorithm to reach good results is difficult. For this reason, we use a combination of classification techniques to reach an efficient and accurate classification model. This model combination is called the Ensemble model. We need to predict new medical data with a high accuracy value in a small processing time. We propose a new ensemble model MDRL which is efficient with different datasets. The MDRL… More >

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Ibtisam Aldawish¹, Hamid A. Jalab^2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1307-1316, 2022, DOI:10.32604/cmc.2022.029445
Abstract The lungs CT scan is used to visualize the spread of the disease across the lungs to obtain better knowledge of the state of the COVID-19 infection. Accurately diagnosing of COVID-19 disease is a complex challenge that medical system face during the pandemic time. To address this problem, this paper proposes a COVID-19 image enhancement based on Mittag-Leffler-Chebyshev polynomial as pre-processing step for COVID-19 detection and segmentation. The proposed approach comprises the Mittag-Leffler sum convoluted with Chebyshev polynomial. The idea for using the proposed image enhancement model is that it improves images with low gray-level changes by estimating the probability… More >

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Guwei Li¹, Yun Yang¹, Zhou Li^1,*, Jingchun Fan²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1317-1327, 2022, DOI:10.32604/cmc.2022.027652
Abstract Traditional teaching and learning about industrial robots uses abstract instructions, which are difficult for students to understand. Meanwhile, there are safety issues associated with the use of practical training equipment. To address these problems, this paper developed an instructional system based on mixed-reality (MR) technology for teaching about industrial robots. The Siasun T6A-series robots were taken as a case study, and the Microsoft MR device HoloLens-2 was used as the instructional platform. First, the parameters of the robots were analyzed based on their structural drawings. Then, the robot modules were decomposed, and 1:1 three-dimensional (3D) digital reproductions were created in… More >

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Farah Tawfiq Abdul Hussien^*, Abdul Monem S. Rahma, Hala Bahjat Abdul Wahab
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1329-1346, 2022, DOI:10.32604/cmc.2022.027582
Abstract Nowadays the E-bank systems witnessed huge growth due to the huge developments in the internet and technologies. The transmitted information represents crucial information that is exposed to various kinds of attacks. This paper presents a new block cipher technique to provide security to the transmitted information between the customers and the e-bank systems. The proposed algorithm consists of 10 rounds, each round involves 5 operations. The operations involve Add round key, Sub bytes, Zigzag method, convert to vector, and Magic Square of order 11. The purpose of this algorithm is to make use of the complexity of the Magic Square… More >

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Vinay Kumar^1,*, Vineet Kansal², Manish Gaur²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1347-1364, 2022, DOI:10.32604/cmc.2022.023545
Abstract With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software, the authenticity of records is at high risk, especially in video. There is a dire need to detect such problem and do the necessary actions. In this work, we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical computations. The proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to these features to find the… More >

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Al-Batool Al-Ghamdi^1,*, Souad Kamel², Mashael Khayyat³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1365-1383, 2022, DOI:10.32604/cmc.2022.026246
Abstract Water is a vital resource. It supports a multitude of industries, civilizations, and agriculture. However, climatic conditions impact water availability, particularly in desert areas where the temperature is high, and rain is scarce. Therefore, it is crucial to forecast water demand to provide it to sectors either on regular or emergency days. The study aims to develop an accurate model to forecast daily water demand under the impact of climatic conditions. This forecasting is known as a multivariate time series because it uses both the historical data of water demand and climatic conditions to forecast the future. Focusing on the… More >

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Jieren Cheng^1,3, Yuan Zhang^2,3,*, Yuming Yuan⁴, Hui Li⁴, Xiangyan Tang^1,3, Victor S. Sheng⁵, Guangjing Hu^1,3
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1385-1402, 2022, DOI:10.32604/cmc.2022.026437
Abstract The research on the governing blockchain by blockchain supervision system is an important development trend of blockchain technology. In this system there is a supervisory blockchain managing and governing the supervised blockchain based on blockchain technology, results in a uniquely cross-blockchain demand to consensus mechanism for solving the trust problem between supervisory blockchain and supervised blockchain. To solve this problem, this paper proposes a cross-blockchain consensus mechanism based on smart contract and a set of smart contracts endorse the cross-blockchain consensus. New consensus mechanism called Proof-of-Endorse-Contracts (PoEC) consensus, which firstly transfers the consensus reached in supervisory blockchain to supervised blockchain… More >

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Mohammad Adnan Aladaileh, Mohammed Anbar^*, Iznan H. Hasbullah, Abdullah Ahmed Bahashwan, Shadi Al-Sarawn
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1403-1416, 2022, DOI:10.32604/cmc.2022.029369
Abstract The emergence of a new network architecture, known as Software Defined Networking (SDN), in the last two decades has overcome some drawbacks of traditional networks in terms of performance, scalability, reliability, security, and network management. However, the SDN is vulnerable to security threats that target its controller, such as low-rate Distributed Denial of Service (DDoS) attacks, The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component. Therefore, there is an urgent need to propose a detection approach for this type of attack… More >

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623

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Naglaa F. El Abady^1,*, Mohamed Taha¹, Hala H. Zayed^1,2
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1417-1436, 2022, DOI:10.32604/cmc.2022.028044
Abstract Because of the widespread availability of low-cost printers and scanners, document forgery has become extremely popular. Watermarks or signatures are used to protect important papers such as certificates, passports, and identification cards. Identifying the origins of printed documents is helpful for criminal investigations and also for authenticating digital versions of a document in today’s world. Source printer identification (SPI) has become increasingly popular for identifying frauds in printed documents. This paper provides a proposed algorithm for identifying the source printer and categorizing the questioned document into one of the printer classes. A dataset of 1200 papers from 20 distinct (13)… More >

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578

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Mohammad Alamgeer¹, Hanan Abdullah Mengash², Radwa Marzouk², Mohamed K Nour³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Abu Sarwar Zamani⁴, Mohammed Rizwanullah⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1437-1448, 2022, DOI:10.32604/cmc.2022.027896
Abstract Early detection of lung cancer can help for improving the survival rate of the patients. Biomedical imaging tools such as computed tomography (CT) image was utilized to the proper identification and positioning of lung cancer. The recently developed deep learning (DL) models can be employed for the effectual identification and classification of diseases. This article introduces novel deep learning enabled CAD technique for lung cancer using biomedical CT image, named DLCADLC-BCT technique. The proposed DLCADLC-BCT technique intends for detecting and classifying lung cancer using CT images. The proposed DLCADLC-BCT technique initially uses gray level co-occurrence matrix (GLCM) model for feature… More >

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624

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Wei Song^1,2,3, Haolin Wang¹, Xinping Zhang¹, Jianxin Xia^4,*, Tongmu Liu⁵, Yuxi Shi⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1449-1462, 2022, DOI:10.32604/cmc.2022.027213
Abstract Deep-sea mineral image segmentation plays an important role in deep-sea mining and underwater mineral resource monitoring and evaluation. The application of artificial intelligence technology to deep-sea mining projects can effectively improve the quality and efficiency of mining. The existing deep learning-based underwater image segmentation algorithms have problems such as the accuracy rate is not high enough and the running time is slightly longer. In order to improve the segmentation performance of underwater mineral images, this paper uses the Pix2PixHD (Pixel to Pixel High Definition) algorithm based on Conditional Generative Adversarial Network (CGAN) to segment deep-sea mineral images. The model uses… More >

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Abdulaziz Alhumam^*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1463-1482, 2022, DOI:10.32604/cmc.2022.029473
Abstract The most resource-intensive and laborious part of debugging is finding the exact location of the fault from the more significant number of code snippets. Plenty of machine intelligence models has offered the effective localization of defects. Some models can precisely locate the faulty with more than 95% accuracy, resulting in demand for trustworthy models in fault localization. Confidence and trustworthiness within machine intelligence-based software models can only be achieved via explainable artificial intelligence in Fault Localization (XFL). The current study presents a model for generating counterfactual interpretations for the fault localization model's decisions. Neural system approximations and disseminated presentation of… More >

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507

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Samar Elbedwehy^1,*, T. Medhat², Taher Hamza³, Mohammed F. Alrahmawy³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1483-1500, 2022, DOI:10.32604/cmc.2022.029313
Abstract Image captioning is an emerging field in machine learning. It refers to the ability to automatically generate a syntactically and semantically meaningful sentence that describes the content of an image. Image captioning requires a complex machine learning process as it involves two sub models: a vision sub-model for extracting object features and a language sub-model that use the extracted features to generate meaningful captions. Attention-based vision transformers models have a great impact in vision field recently. In this paper, we studied the effect of using the vision transformers on the image captioning process by evaluating the use of four different… More >

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Syed Irtaza Haider¹, Khursheed Aurangzeb^2,*, Musaed Alhussein²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1501-1526, 2022, DOI:10.32604/cmc.2022.025479
Abstract The accurate segmentation of retinal vessels is a challenging task due to the presence of various pathologies as well as the low-contrast of thin vessels and non-uniform illumination. In recent years, encoder-decoder networks have achieved outstanding performance in retinal vessel segmentation at the cost of high computational complexity. To address the aforementioned challenges and to reduce the computational complexity, we propose a lightweight convolutional neural network (CNN)-based encoder-decoder deep learning model for accurate retinal vessels segmentation. The proposed deep learning model consists of encoder-decoder architecture along with bottleneck layers that consist of depth-wise squeezing, followed by full-convolution, and finally depth-wise… More >

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776

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Zhilin Zhang¹, Ting Zhang¹, Zhaoying Liu^1,*, Peijie Zhang¹, Shanshan Tu¹, Yujian Li², Muhammad Waqas³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1527-1539, 2022, DOI:10.32604/cmc.2022.029297
Abstract The fine-grained ship image recognition task aims to identify various classes of ships. However, small inter-class, large intra-class differences between ships, and lacking of training samples are the reasons that make the task difficult. Therefore, to enhance the accuracy of the fine-grained ship image recognition, we design a fine-grained ship image recognition network based on bilinear convolutional neural network (BCNN) with Inception and additive margin Softmax (AM-Softmax). This network improves the BCNN in two aspects. Firstly, by introducing Inception branches to the BCNN network, it is helpful to enhance the ability of extracting comprehensive features from ships. Secondly, by adding… More >

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550

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K. Pradeep Mohan Kumar¹, S. Dhanasekaran², I. S. Hephzi Punithavathi³, P. Duraipandy⁴, Ashit Kumar Dutta⁵, Irina V. Pustokhina^6,*, Denis A. Pustokhin⁷
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1541-1555, 2022, DOI:10.32604/cmc.2022.028338
Abstract Financial crisis prediction (FCP) models are used for predicting or forecasting the financial status of a company or financial firm. It is considered a challenging issue in the financial sector. Statistical and machine learning (ML) models can be employed for the design of accurate FCP models. Though numerous works have existed in the literature, it is needed to design effective FCP models adaptable to different datasets. This study designs a new bird swarm algorithm (BSA) with fuzzy min-max neural network (FMM-NN) model, named BSA-FMMNN for FCP. The major intention of the BSA-FMMNN model is to determine the financial status of… More >

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544

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Haya Mesfer Alshahrani¹, Faisal S. Alsubaei², Taiseer Abdalla Elfadil Eisa³, Mohamed K. Nour⁴, Manar Ahmed Hamza^5,*, Abdelwahed Motwakel⁵, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1557-1570, 2022, DOI:10.32604/cmc.2022.027135
Abstract The increasing quantity of sensitive and personal data being gathered by data controllers has raised the security needs in the cloud environment. Cloud computing (CC) is used for storing as well as processing data. Therefore, security becomes important as the CC handles massive quantity of outsourced, and unprotected sensitive data for public access. This study introduces a novel chaotic chimp optimization with machine learning enabled information security (CCOML-IS) technique on cloud environment. The proposed CCOML-IS technique aims to accomplish maximum security in the CC environment by the identification of intrusions or anomalies in the network. The proposed CCOML-IS technique primarily… More >

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Runze Li¹, Jiaohua Qin^1,*, Yun Tan¹, Neal N. Xiong²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1571-1583, 2022, DOI:10.32604/cmc.2022.029378
Abstract Most existing coverless video steganography algorithms use a particular video frame for information hiding. These methods do not reflect the unique sequential features of video carriers that are different from image and have poor robustness. We propose a coverless video steganography method based on frame sequence perceptual distance mapping. In this method, we introduce Learned Perceptual Image Patch Similarity (LPIPS) to quantify the similarity between consecutive video frames to obtain the sequential features of the video. Then we establish the relationship map between features and the hash sequence for information hiding. In addition, the MongoDB database is used to store… More >

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508

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Aytha Ramesh Kumar^1,*, K. Lal Kishore²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1585-1600, 2022, DOI:10.32604/cmc.2022.021573
Abstract The 5G communication systems are widely established for high-speed data processing to meet users demands. The 5G New Radio (NR) communications comprise a network of ultra-low latency, high processing speeds, high throughput and rapid synchronization with a time frame of 10 ms. Synchronization between User Equipment (UE) and 5G base station known as gNB is a fundamental procedure in a cellular system and it is performed by a synchronization signal. In 5G NR system, Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS) are used to detect the best serving base station with the help of a cell search procedure.… More >

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1296

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Pranav Pushkar¹, Christo Ananth², Preeti Nagrath¹, Jehad F. Al-Amri⁵, Vividha¹, Anand Nayyar^3,4,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1601-1619, 2022, DOI:10.32604/cmc.2022.026205
Abstract The study of viruses and their genetics has been an opportunity as well as a challenge for the scientific community. The recent ongoing SARS-Cov2 (Severe Acute Respiratory Syndrome) pandemic proved the unpreparedness for these situations. Not only the countermeasures for the effect caused by virus need to be tackled but the mutation taking place in the very genome of the virus is needed to be kept in check frequently. One major way to find out more information about such pathogens is by extracting the genetic data of such viruses. Though genetic data of viruses have been cultured and stored as… More >

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582

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Juan Fang^1,*, Kuan Zhou¹, Mengyuan Zhang¹, Wei Xiang^2,3
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1621-1635, 2022, DOI:10.32604/cmc.2022.027147
Abstract In recent years, with the development of processor architecture, heterogeneous processors including Center processing unit (CPU) and Graphics processing unit (GPU) have become the mainstream. However, due to the differences of heterogeneous core, the heterogeneous system is now facing many problems that need to be solved. In order to solve these problems, this paper try to focus on the utilization and efficiency of heterogeneous core and design some reasonable resource scheduling strategies. To improve the performance of the system, this paper proposes a combination strategy for a single task and a multi-task scheduling strategy for multiple tasks. The combination strategy… More >

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695

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Rajneesh Pareek¹, Karthikeyan Rajagopal², Himanshu Sharma¹, Nidhi Gour¹, Arun Kumar³, Sami Althahabi⁴, Haya Mesfer Alshahrani⁵, Mohamed Mousa⁶, Manar Ahmed Hamza^7,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1637-1648, 2022, DOI:10.32604/cmc.2022.029563
Abstract Multi and single carrier waveforms are utilized in cellular systems for high-speed data transmission. In The Fifth Generation (5G) system, several waveform techniques based on multi carrier waveforms are proposed. However, the Peak to Average Power Ratio (PAPR) is seen as one of the significant concerns in advanced waveforms as it degrades the efficiency of the framework. The proposed article documents the study, progress, and implementation of PAPR reduction algorithms for the 5G radio framework. We compare the PAPR algorithm performance for advanced and conventional waveforms. The simulation results reveal that the advanced Partial Transmission Sequence (PTS) and Selective Mapping… More >

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Wei Song^1,2,3, Lihui Dong¹, Xiaobing Zhao^1,3, Jianxin Xia^4,*, Tongmu Liu⁵, Yuxi Shi⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1649-1669, 2022, DOI:10.32604/cmc.2022.027214
Abstract A large number of nodule minerals exist in the deep sea. Based on the factors of difficulty in shooting, high economic cost and high accuracy of resource assessment, large-scale planned commercial mining has not yet been conducted. Only experimental mining has been carried out in areas with high mineral density and obvious benefits after mineral resource assessment. As an efficient method for deep-sea mineral resource assessment, the deep towing system is equipped with a visual system for mineral resource analysis using collected images and videos, which has become a key component of resource assessment. Therefore, high accuracy in deep-sea mineral… More >

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