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  • Open Access

    ARTICLE

    Training Multi-Layer Perceptron with Enhanced Brain Storm Optimization Metaheuristics

    Nebojsa Bacanin1, Khaled Alhazmi2,*, Miodrag Zivkovic1, K. Venkatachalam3, Timea Bezdan1, Jamel Nebhen4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4199-4215, 2022, DOI:10.32604/cmc.2022.020449

    Abstract In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing… More >

  • Open Access

    ARTICLE

    Reversible Logic Based MOS Current Mode Logic Implementation in Digital Circuits

    S. Sharmila Devi1,*, V. Bhanumathi2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3609-3624, 2022, DOI:10.32604/cmc.2022.020426

    Abstract Now a days, MOS Current Mode Logic (MCML) has emerged as a better alternative to Complementary Metal Oxide Semiconductor (CMOS) logic in digital circuits. Recent works have only traditional logic gates that have issues with information loss. Reversible logic is incorporated with MOS Current Mode Logic (MCML) in this proposed work to solve this problem, which is used for multiplier design, D Flip-Flop (DFF) and register. The minimization of power and area is the main aim of the work. In reversible logic, the count of outputs and inputs is retained as the same value for creating one-to-one mapping. A unique… More >

  • Open Access

    ARTICLE

    MNN-XSS: Modular Neural Network Based Approach for XSS Attack Detection

    Ahmed Abdullah Alqarni1, Nizar Alsharif1, Nayeem Ahmad Khan1,*, Lilia Georgieva2, Eric Pardade3, Mohammed Y. Alzahrani1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4075-4085, 2022, DOI:10.32604/cmc.2022.020389

    Abstract The rapid growth and uptake of network-based communication technologies have made cybersecurity a significant challenge as the number of cyber-attacks is also increasing. A number of detection systems are used in an attempt to detect known attacks using signatures in network traffic. In recent years, researchers have used different machine learning methods to detect network attacks without relying on those signatures. The methods generally have a high false-positive rate which is not adequate for an industry-ready intrusion detection product. In this study, we propose and implement a new method that relies on a modular deep neural network for reducing the… More >

  • Open Access

    ARTICLE

    A Study of Cellular Neural Networks with Vertex-Edge Topological Descriptors

    Sadia Husain1, Muhammad Imran2,*, Ali Ahmad1, Yasir Ahmad1, Kashif Elahi3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3433-3447, 2022, DOI:10.32604/cmc.2022.020384

    Abstract The Cellular Neural Network (CNN) has various parallel processing applications, image processing, non-linear processing, geometric maps, high-speed computations. It is an analog paradigm, consists of an array of cells that are interconnected locally. Cells can be arranged in different configurations. Each cell has an input, a state, and an output. The cellular neural network allows cells to communicate with the neighbor cells only. It can be represented graphically; cells will represent by vertices and their interconnections will represent by edges. In chemical graph theory, topological descriptors are used to study graph structure and their biological activities. It is a single… More >

  • Open Access

    ARTICLE

    Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

    Shibli Nisar1, Muhammad Asghar Khan2,*, Fahad Algarni3, Abdul Wakeel1, M. Irfan Uddin4, Insaf Ullah2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376

    Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for… More >

  • Open Access

    ARTICLE

    Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

    Mukhtar Ghaleb1,*, Yahya Almurtadha2, Fahad Algarni3, Monir Abdullah3, Emad Felemban4, Ali M. Alsharafi3, Mohamed Othman5, Khaled Ghilan6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2619-2638, 2022, DOI:10.32604/cmc.2022.020358

    Abstract People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased responses. However, chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their scope. Chatbots employ Natural Language Understanding (NLU) to infer their responses. There is a need for a chatbot that can learn from inquiries and expand its area of experience with time. This chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast retrieval. This study proposes a methodology to enhance a chatbot's brain functionality… More >

  • Open Access

    ARTICLE

    Integrating Blockchain Technology into Healthcare Through an Intelligent Computing Technique

    Asif Irshad Khan1,*, Abdullah Saad Al-Malaise ALGhamdi2, Fawaz Jaber Alsolami1, Yoosef B. Abushark1, Abdulmohsen Almalawi1, Abdullah Marish Ali1, Alka Agrawal3, Rajeev Kumar4, Raees Ahmad Khan3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2835-2860, 2022, DOI:10.32604/cmc.2022.020342

    Abstract The blockchain technology plays a significant role in the present era of information technology. In the last few years, this technology has been used effectively in several domains. It has already made significant differences in human life, as well as is intended to have noticeable impact in many other domains in the forthcoming years. The rapid growth in blockchain technology has created numerous new possibilities for use, especially for healthcare applications. The digital healthcare services require highly effective security methodologies that can integrate data security with the available management strategies. To test and understand this goal of security management in… More >

  • Open Access

    ARTICLE

    Earthquake Risk Assessment Approach Using Multiple Spatial Parameters for Shelter Demands

    Wenquan Jin1, Naeem Iqbal2, Hee-Cheal Kang3, Dohyeun Kim2,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3763-3780, 2022, DOI:10.32604/cmc.2022.020336

    Abstract The earthquake is considered one of the most devastating disasters in any area of the world due to its potentially destructive force. Based on the various earthquake-related parameters, the risk assessment is enabled in advance to prevent future earthquake disasters. In this paper, for providing the shelter space demands to reduce the damage level and prevention costs, an earthquake risk assessment approach is proposed for deriving the risk index based on multiple spatial parameters in the gridded map. The proposed assessment approach is comprised of pre-processing, methodology model, and data visualization. The risk index model derives the earthquake risk index… More >

  • Open Access

    ARTICLE

    An Optimized Algorithm for Resource Allocation for D2D in Heterogeneous Networks

    Abdul Kadir Hamid1, Fahd N. Al-Wesabi2,3,*, Nadhem Nemri4, Ammar Zahary3, Imran Khan5

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2923-2936, 2022, DOI:10.32604/cmc.2022.020309

    Abstract With the emergence of 5G mobile multimedia services, end users’ demand for high-speed, low-latency mobile communication network access is increasing. Among them, the device-to-device (D2D) communication is one of the considerable technology. In D2D communication, the data does not need to be relayed and forwarded by the base station, but under the control of the base station, a direct local link is allowed between two adjacent mobile devices. This flexible communication mode reduces the processing bottlenecks and coverage blind spots of the base station, and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless networks.… More >

  • Open Access

    ARTICLE

    Dorsal-Ventral Visual Pathways and Object Characteristics: Beamformer Source Analysis of EEG

    Akanksha Tiwari1, Ram Bilas Pachori1,2, Premjit Khanganba Sanjram1,3,4,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2347-2363, 2022, DOI:10.32604/cmc.2022.020299

    Abstract In performing a gaming task, mental rotation (MR) is one of the important aspects of visuospatial processing. MR involves dorsal-ventral pathways of the brain. Visual objects/models used in computer-games play a crucial role in gaming experience of the users. The visuospatial characteristics of the objects used in the computer-game influence the engagement of dorsal-ventral visual pathways. The current study investigates how the objects’ visuospatial characteristics (i.e., angular disparity and dimensionality) in an MR-based computer-game influence the cortical activities in dorsal-ventral visual pathways. Both the factors have two levels, angular disparity: convex angle (CA) vs. reflex angle (RA) and dimensionality: 2D… More >

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