Punam Gulande^*, R. N. Awale

Computer Systems Science and Engineering, Vol.48, No.4, pp. 937-952, 2024, DOI:10.32604/csse.2024.046123 - 17 July 2024

Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

B. Jegajothi^1,*, Sundaram Arumugam², Neeraj Kumar Shukla³, I. Kathir⁴, P. Yamunaa⁵, Monia Digra⁶

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2417-2437, 2023, DOI:10.32604/csse.2023.038074 - 28 July 2023

Abstract Renewable energy sources like solar, wind, and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment. Because, Since the production of renewable energy sources is still in the process of being created, photovoltaic (PV) systems are commonly utilized for installation situations that are acceptable, clean, and simple. This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking (MPPT) in solar systems with the help of an embedded controller. The adaptive method incorporates both the Whale Optimization Algorithm (WOA) and the Artificial… More >

Anjani Kumar Singha¹, Swaleha Zubair¹, Areej Malibari², Nitish Pathak³, Shabana Urooj^4,*, Neelam Sharma⁵

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3491-3508, 2023, DOI:10.32604/csse.2023.029165 - 03 April 2023

Abstract Suspicious mass traffic constantly evolves, making network behaviour tracing and structure more complex. Neural networks yield promising results by considering a sufficient number of processing elements with strong interconnections between them. They offer efficient computational Hopfield neural networks models and optimization constraints used by undergoing a good amount of parallelism to yield optimal results. Artificial neural network (ANN) offers optimal solutions in classifying and clustering the various reels of data, and the results obtained purely depend on identifying a problem. In this research work, the design of optimized applications is presented in an organized manner.… More >

Yichiet Aun^1,*, Ming-Lee Gan¹, Nur Haliza Binti Abdul Wahab², Goh Hock Guan¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4917-4931, 2023, DOI:10.32604/cmc.2023.032373 - 28 December 2022

Abstract In defense-in-depth, humans have always been the weakest link in cybersecurity. However, unlike common threats, social engineering poses vulnerabilities not directly quantifiable in penetration testing. Most skilled social engineers trick users into giving up information voluntarily through attacks like phishing and adware. Social Engineering (SE) in social media is structurally similar to regular posts but contains malicious intrinsic meaning within the sentence semantic. In this paper, a novel SE model is trained using a Recurrent Neural Network Long Short Term Memory (RNN-LSTM) to identify well-disguised SE threats in social media posts. We use a custom… More >

Sneha Basak¹, Himanshi Agrawal¹, Shreya Jena¹, Shilpa Gite^2,*, Mrinal Bachute², Biswajeet Pradhan^3,4,5,*, Mazen Assiri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2022.021755 - 27 October 2022

Abstract Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various More >

Anil Kumar Yadav¹, R. K. Pateriya², Nirmal Kumar Gupta³, Punit Gupta^4,*, Dinesh Kumar Saini⁴, Mohammad Alahmadi⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052 - 29 March 2022

Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems More >

Mario Bonagura, Lucio Nobile^*

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 125-137, 2021, DOI:10.32604/sdhm.2021.015644 - 03 June 2021

Abstract The compressive strength of concrete is one of most important mechanical parameters in the performance assessment of existing reinforced concrete structures. According to various international codes, core samples are drilled and tested to obtain the concrete compressive strengths. Non-destructive testing is an important alternative when destructive testing is not feasible without damaging the structure. The commonly used non-destructive testing (NDT) methods to estimate the in-situ values include the Rebound hammer test and the Ultrasonic Pulse Velocity test. The poor reliability of these tests due to different aspects could be partially contrasted by using both methods together,… More >

Jianping Sun¹, Jan Niederwestberg^2,*, Fangchao Cheng¹, Yinghei Chui²

Journal of Renewable Materials, Vol.8, No.3, pp. 319-328, 2020, DOI:10.32604/jrm.2020.08696 - 01 March 2020

Abstract Cross laminated timber (CLT) panels, which are used as load bearing plates and shear panels in timber structures, can serve as roofs, walls and floors. Since timber is construction material with relatively less stiffness, the design of such structures is often driven by serviceability criteria, such as deflection and vibration. Therefore, accurate vibration and elastic properties are vital for engineered CLT products. The objective of this research is to explore a method to determine the natural frequencies of orthotropic wood plates efficiently and fast. The method was developed based on vibration signal processing by wavelet More >

D. S. Liu¹, C.Y. Tsai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.39, No.1, pp. 29-48, 2009, DOI:10.3970/cmes.2009.039.029

Abstract Utilizing a thin copper substrate for illustration purposes, this study presents a novel numerical method for extracting the thermo-mechanical properties of a thin-film. In the proposed approach, molecular dynamics (MD) simulations are performed to establish the load-displacement response of a thin copper substrate nanoindented at temperatures ranging from 300~1400 K. The load data are then input to an artificial neural network (ANN), trained using a finite element model (FEM), in order to extract the material constants of the copper substrate. The material constants are then used to construct the corresponding stress-strain curve, from which the… More >