Abdulrahman M. Abdulghani^*

Journal on Artificial Intelligence, Vol.6, pp. 241-259, 2024, DOI:10.32604/jai.2024.056259 - 16 October 2024

Abstract Cloud computing has rapidly evolved into a critical technology, seamlessly integrating into various aspects of daily life. As user demand for cloud services continues to surge, the need for efficient virtualization and resource management becomes paramount. At the core of this efficiency lies task scheduling, a complex process that determines how tasks are allocated and executed across cloud resources. While extensive research has been conducted in the area of task scheduling, optimizing multiple objectives simultaneously remains a significant challenge due to the NP (Non-deterministic Polynomial) Complete nature of the problem. This study aims to address… More >

Ibtissam El Aouni, Hicham Labrim, Elhoussaine Ouabida, Ahmed Ait Errouhi, Rachid El Bouayadi, Driss Zejli, Aouatif Saad^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2323-2335, 2024, DOI:10.32604/fdmp.2024.050611 - 23 September 2024

Abstract The perfect combination of renewable energy and desalination technologies is the key to meeting water demands in a cost-effective, efficient and environmentally friendly way. The desalination technique by humidification-dehumidification is non-conventional approach suitable for areas with low infrastructure (such as rural and decentralized regions) since it does not require permanent maintenance. In this study, this technology is implemented by using solar energy as a source of thermal power. A seawater desalination unit is considered, which consists of a chamber with two evaporators (humidifiers), a wetted porous material made of a corrugated cellulose cardboard and a… More >

Kaveh Heidary^1,*, Venkata Atluri¹, John Bland²

Journal of Cyber Security, Vol.6, pp. 69-87, 2024, DOI:10.32604/jcs.2024.051196 - 28 August 2024

Abstract This paper investigates the impact of reducing feature-vector dimensionality on the performance of machine learning (ML) models. Dimensionality reduction and feature selection techniques can improve computational efficiency, accuracy, robustness, transparency, and interpretability of ML models. In high-dimensional data, where features outnumber training instances, redundant or irrelevant features introduce noise, hindering model generalization and accuracy. This study explores the effects of dimensionality reduction methods on binary classifier performance using network traffic data for cybersecurity applications. The paper examines how dimensionality reduction techniques influence classifier operation and performance across diverse performance metrics for seven ML models. Four… More >

Yaqiong He, Jinlin Fan^*, Huaiguang Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 995-1032, 2024, DOI:10.32604/cmc.2024.052887 - 18 July 2024

Abstract With the rise of blockchain technology, the security issues of smart contracts have become increasingly critical. Despite the availability of numerous smart contract vulnerability detection tools, many face challenges such as slow updates, usability issues, and limited installation methods. These challenges hinder the adoption and practicality of these tools. This paper examines smart contract vulnerability detection tools from 2016 to 2023, sourced from the Web of Science (WOS) and Google Scholar. By systematically collecting, screening, and synthesizing relevant research, 38 open-source tools that provide installation methods were selected for further investigation. From a developer’s perspective,… More >

Ali Shokor Golam^*

Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 633-653, 2024, DOI:10.32604/fhmt.2024.050218 - 20 May 2024

Abstract The thermal-hydraulic performance of plain tubes with and without wire coils in turbulent regimes is investigated experimentally and numerically. The effects of wire coil distribution (circular cross section) within the tube were explored experimentally, and water was employed as the working fluid. The numerical simulation was carried out using software programmer ANSYS Fluent 2019 R3 using the finite-volume approach. In the turbulent regime, six cross-sectioned wire coils were analyzed, including: circular, rectangular, hexagonal, square, star shape, and triangle. The utilization of a tube with a wire coil has been shown to increase heat transfer rate More >

Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 337-352, 2024, DOI:10.32604/iasc.2024.047017 - 21 May 2024

Abstract Multi-Agent Reinforcement Learning (MARL) has proven to be successful in cooperative assignments. MARL is used to investigate how autonomous agents with the same interests can connect and act in one team. MARL cooperation scenarios are explored in recreational cooperative augmented reality environments, as well as real-world scenarios in robotics. In this paper, we explore the realm of MARL and its potential applications in cooperative assignments. Our focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory with minimal damage. To accomplish this, we utilize the StarCraft… More >

Xiaofang Kang^1,*, Jian Wu¹, Xinqi Wang¹, Shancheng Lei²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 551-593, 2024, DOI:10.32604/cmes.2023.029044 - 22 September 2023

Abstract In order to improve the seismic performance of adjacent buildings, two types of tuned inerter damper (TID) damping systems for adjacent buildings are proposed, which are composed of springs, inerter devices and dampers in serial or in parallel. The dynamic equations of TID adjacent building damping systems were derived, and the H₂ norm criterion was used to optimize and adjust them, so that the system had the optimum damping performance under white noise random excitation. Taking TID frequency ratio and damping ratio as optimization parameters, the optimum analytical solutions of the displacement frequency response of the… More > Graphic Abstract

Hang Yang^1,2,3,*, Xunbo Li¹, Witold Pedrycz²

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3039-3058, 2023, DOI:10.32604/iasc.2023.040412 - 11 September 2023

Abstract Fire rescue challenges and solutions have evolved from straightforward plane rescue to encompass 3D space due to the rise of high-rise city buildings. Hence, this study facilitates a system with quick and simplified on-site launching and generates real-time location data, enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue. Auto-positioning with step-by-step instructions is proposed when launching the locating system, while no extra measuring instrument like Total Station (TS) is needed. Real-time location tracking is provided via a 3D space real-time locating system (RTLS) constructed using Ultra-wide… More >

Niharika Gupta¹, Baijnath Kaushik¹, Mohammad Khalid Imam Rahmani^2,*, Saima Anwar Lashari^2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 347-366, 2023, DOI:10.32604/cmc.2023.038864 - 08 June 2023

Abstract Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision… More >

Jiangyuan Yao¹, Weiping Yang¹, Shuhua Weng¹, Minrui Wang¹, Zheng Jiang², Deshun Li^1,*, Yahui Li³, Xingcan Cao⁴

Computer Systems Science and Engineering, Vol.47, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.031531 - 26 May 2023

Abstract Software-defined networking (SDN) is widely used in multiple types of data center networks, and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers. However, the network topology of each control domain of SDN will affect the performance of the multi-domain network, so performance evaluation is required before the deployment of the multi-domain SDN. Besides, there is a high cost to build real multi-domain SDN networks with different topologies, so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network. As… More >