Xin Zhang^1,2, Xitao Zheng^1,2, Tiantian Yang³, Mingyu Song^1,2, Yuanyuan Tian⁴, Leilei Yan^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011277

Abstract Composite joints are widely used in machinery industries such as aviation, aerospace, and marine, where they transfer main loads as lightweight connectors. Recently, 3D printing with continuous fibers has relieved the required molds in composite manufacturing process and given flexibility to the design of robust composite joints. However, how the curved paths and variable hatch spaces affect the mechanical properties and failure modes of 3D-printed single-bolt composite joints with continuous fibers remains undisclosed. In this study, 3D printing has been introduced to fabricate three types of continuous fiber-reinforced single-bolt composite joints with different paths, including… More >

Mohammed A. Alhartomi^1,*, Mohammad F. L. Abdullah², Wafi A. B. Mabrouk², Mohammed S. M. Gismalla³, Ahmed Alzahmi¹, Saeed Alzahrani¹, Mohammad R. Altimania¹, Mohammed S. Alsawat⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2087-2105, 2024, DOI:10.32604/cmes.2024.055679 - 31 October 2024

Abstract The demand for broadband data services on high-speed trains is rapidly growing as more people commute between their homes and workplaces. However, current radio frequency (RF) technology cannot adequately meet this demand. In order to address the bandwidth constraint, a technique known as free space optics (FSO) has been proposed. This paper presents a mathematical derivation and formulation of curve track G2T-FSO (Ground-to-train Free Space Optical) model, where the track radius characteristics is 2667 m, divergence angle track is 1.5° for train velocity at V = 250 km/h. Multiple transmitter configurations are proposed to maximize More >

Zongbao Jiang, Minqing Zhang^*, Weina Dong, Chao Jiang, Fuqiang Di

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1123-1155, 2024, DOI:10.32604/cmc.2024.055120 - 15 October 2024

Abstract With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction… More >

Giada Faraco, Andrea Vincenzo De Nunzio, Nicola Ivan Giannoccaro^*, Arcangelo Messina

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 739-762, 2024, DOI:10.32604/sdhm.2024.052663 - 20 September 2024

Abstract The possibility of determining the integrity of a real structure subjected to non-invasive and non-destructive monitoring, such as that carried out by a series of accelerometers placed on the structure, is certainly a goal of extreme and current interest. In the present work, the results obtained from the processing of experimental data of a real structure are shown. The analyzed structure is a lattice structure approximately 9 m high, monitored with 18 uniaxial accelerometers positioned in pairs on 9 different levels. The data used refer to continuous monitoring that lasted for a total of 1… 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 >

Cyril Enault^*

Revue Internationale de Géomatique, Vol.33, pp. 273-293, 2024, DOI:10.32604/rig.2024.053490 - 26 August 2024

Abstract La question environnementale est devenue un enjeu majeur de société dans les pays occidentaux et principalement en France. L’Ile de France est aujourd’hui au cœur de cette nouvelle politique de maitrise de l’expansion des agglomérations. Aussi l’étalement urbain et plus particulièrement sa mesure et son évaluation actuelle et future présente un véritable enjeu de société. L’exploration de l’étalement urbain est donc au cœur de la géographie et de l’Economie Géographique depuis le début des années 1980, période où s’amorcent les grands développements du périurbain. Fort de ces enjeux, cet article s’intéresse à la question de… More > Graphic Abstract

He Wang, Xingyu Tong, Huanan Yu^*, Xiao Hu, Jing Bian

Energy Engineering, Vol.121, No.9, pp. 2525-2542, 2024, DOI:10.32604/ee.2024.050594 - 19 August 2024

Abstract Cyber-physical power system (CPPS) has significantly improved the operational efficiency of power systems. However, cross-space cascading failures may occur due to the coupling characteristics, which poses a great threat to the safety and reliability of CPPS, and there is an acute need to reduce the probability of these failures. Towards this end, this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services. On this basis, a joint improved risk-balanced service function chain routing strategy (SFC-RS) is proposed, which is modeled as More >

Guochen Xu^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1915-1924, 2024, DOI:10.32604/fdmp.2024.048337 - 06 August 2024

Abstract Microscopic pore structure in continental shale oil reservoirs is characterized by small pore throats and complex micro-structures. The adsorption behavior of hydrocarbons on the pore walls exhibits unique physical and chemical properties. Therefore, studying the adsorption morphology of hydrocarbon components in nanometer-sized pores and clarifying the exploitation limits of shale oil at the microscopic level are of great practical significance for the efficient development of continental shale oil. In this study, molecular dynamics simulations were employed to investigate the adsorption characteristics of various single-component shale oils in inorganic quartz fissures, and the influence of pore… More >

Lei Feng¹, Miao Liu¹, Yexun Yuan¹, Chi Zhang², Peng Geng^1,*

Journal on Internet of Things, Vol.6, pp. 1-16, 2024, DOI:10.32604/jiot.2024.053584 - 24 July 2024

Abstract With the rapid development of electric vehicles, the requirements for charging stations are getting higher and higher. In this study, we constructed a charging station topology network in Nanjing through the Space-L method, mapping charging stations as network nodes and constructing edges through road relationships. The experiment introduced five EV charging recommendation strategies (based on distance, number of fast charging piles, user preference, price, and overall rating) used to simulate disordered charging caused by different user preferences, and the impact of the network dynamic robustness in case of node failure is explored by simulating the… More >

Yu Yan¹, Yu Yang^1,*, Shen Fang¹, Minna Gao², Yiding Chen¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 875-896, 2024, DOI:10.32604/cmc.2024.051685 - 18 July 2024

Abstract In the face of the effective popularity of the Internet of Things (IoT), but the frequent occurrence of cybersecurity incidents, various cybersecurity protection means have been proposed and applied. Among them, Intrusion Detection System (IDS) has been proven to be stable and efficient. However, traditional intrusion detection methods have shortcomings such as low detection accuracy and inability to effectively identify malicious attacks. To address the above problems, this paper fully considers the superiority of deep learning models in processing high-dimensional data, and reasonable data type conversion methods can extract deep features and detect classification using… More >