Urfa Gul^#, M. Junaid Gul^#, Gyu Sang Choi, Chang-Hyeon Park^*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3811-3834, 2025, DOI:10.32604/cmc.2025.063789 - 03 July 2025

Abstract Spiking Neural Network (SNN) inspired by the biological triggering mechanism of neurons to provide a novel solution for plant disease detection, offering enhanced performance and efficiency in contrast to Artificial Neural Networks (ANN). Unlike conventional ANNs, which process static images without fully capturing the inherent temporal dynamics, our approach represents the first implementation of SNNs tailored explicitly for agricultural disease classification, integrating an encoding method to convert static RGB plant images into temporally encoded spike trains. Additionally, while Bernoulli trials and standard deep learning architectures like Convolutional Neural Networks (CNNs) and Fully Connected Neural Networks… More >

Mourad Benmalek^1,*,#,*, Abdessamed Seddiki^2,#, Kamel-Dine Haouam¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1157-1184, 2025, DOI:10.32604/cmes.2025.062841 - 11 April 2025

Abstract The Internet of Medical Things (IoMT) connects healthcare devices and sensors to the Internet, driving transformative advancements in healthcare delivery. However, expanding IoMT infrastructures face growing security threats, necessitating robust Intrusion Detection Systems (IDS). Maintaining the confidentiality of patient data is critical in AI-driven healthcare systems, especially when securing interconnected medical devices. This paper introduces SNN-IoMT (Stacked Neural Network Ensemble for IoMT Security), an AI-driven IDS framework designed to secure dynamic IoMT environments. Leveraging a stacked deep learning architecture combining Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM), the model optimizes data management More >

Deepak Kumar¹, Ramandeep Singh², Sukhvinder Singh Bamber^3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2981-2996, 2022, DOI:10.32604/cmc.2022.024221 - 29 March 2022

Abstract Individuals and PCs (personal computers) can be recognized using CAPTCHAs (Completely Automated Public Turing test to distinguish Computers and Humans) which are mechanized for distinguishing them. Further, CAPTCHAs are intended to be solved by the people, but are unsolvable by the machines. As a result, using Convolutional Neural Networks (CNNs) these tests can similarly be unraveled. Moreover, the CNNs quality depends majorly on: the size of preparation set and the information that the classifier is found out on. Next, it is almost unmanageable to handle issue with CNNs. A new method of detecting CAPTCHA has More >

Kriti¹, Mohd Anul Haq², Urvashi Garg¹, Mohd Abdul Rahim Khan^2,*, V. Rajinikanth³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 939-957, 2022, DOI:10.32604/cmc.2022.023169 - 24 February 2022

Abstract A crucial task in hyperspectral image (HSI) taxonomy is exploring effective methodologies to effusively practice the 3-D and spectral data delivered by the statistics cube. For classification of images, 3-D data is adjudged in the phases of pre-cataloging, an assortment of a sample, classifiers, post-cataloging, and accurateness estimation. Lastly, a viewpoint on imminent examination directions for proceeding 3-D and spectral approaches is untaken. In topical years, sparse representation is acknowledged as a dominant classification tool to effectually labels deviating difficulties and extensively exploited in several imagery dispensation errands. Encouraged by those efficacious solicitations, sparse representation… More >

Ankush Aggarwal¹, Jiun-Shyan Chen², William S. Klug³

CMES-Computer Modeling in Engineering & Sciences, Vol.98, No.1, pp. 69-99, 2014, DOI:10.3970/cmes.2014.098.069

Abstract Mechanical properties of proteins play an important role in their biological function. For example, microtubules carry large loads to transport organelles inside the cell, and virus shells undergo changes in shape and mechanical properties during maturation which affect their infectivity. Various theoretical models including continuum elasticity have been applied to study these structural properties, and a significant success has been achieved. But, the previous frameworks lack a connection between the atomic and continuum descriptions. Here this is accomplished through the development of a meshfree framework based on reproducing kernel shape functions for the large deformation… More >