Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Abdulaziz Yagoub Barnawi²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3213-3250, 2025, DOI:10.32604/cmes.2025.066589 - 30 September 2025

Abstract Accurate time synchronization is fundamental to the correct and efficient operation of Wireless Sensor Networks (WSNs), especially in security-critical, time-sensitive applications. However, most existing protocols degrade substantially under malicious interference. We introduce iSTSP, an Intelligent and Secure Time Synchronization Protocol that implements a four-stage defense pipeline to ensure robust, precise synchronization even in hostile environments: (1) trust preprocessing that filters node participation using behavioral trust scoring; (2) anomaly isolation employing a lightweight autoencoder to detect and excise malicious nodes in real time; (3) reliability-weighted consensus that prioritizes high-trust nodes during time aggregation; and (4) convergence-optimized synchronization… More >

Buddhini Chaturika Jayasinghe¹, Neel Chaminda Withanage¹, Prabuddh Kumar Mishra^2,*

Revue Internationale de Géomatique, Vol.34, pp. 707-729, 2025, DOI:10.32604/rig.2025.067395 - 12 September 2025

Abstract Road Traffic Accidents (RTAs) pose significant threats to public safety and urban infrastructure. While numerous studies have addressed this issue in other countries, there remains a notable gap in localized RTA research in Sri Lanka. In this context, the present study investigates the spatial and temporal patterns of RTAs in the Matara urban area in 2023, with the goal of supporting evidence-based policy interventions. A suite of GIS-based spatial analysis techniques including hotspot analysis, kernel density estimation, GiZscore mapping, and spatial autocorrelation (Moran’s I = 0.36, p < 0.01) was applied to examine the distribution and… More >

CHUCHU ZHANG^1,#, YING LIU^2,#, ZEHUI CHEN¹, YI LIU³, QIYUAN MAO⁴, GE ZHANG⁵, HONGSHENG LIN⁴, JIABIN ZHENG^6,*, HAIYAN LI^1,*

Oncology Research, Vol.33, No.6, pp. 1437-1458, 2025, DOI:10.32604/or.2025.059290 - 29 May 2025

Abstract Objectives: Decades of clinical and fundamental research advancements in oncology have led to significant breakthroughs such as early screening, targeted therapies, and immunotherapy, contributing to reduced mortality rates in cancer patients. Despite these achievements, cancer continues to be a major public health challenge. This study employs bibliometric techniques to visually analyze the English literature on cancer prevention, screening, diagnosis, treatment, and rehabilitation. Methods: We systematically reviewed publications from 01 March 2014, to 01 March 2024, indexed in the Web of Science core collection. Tools such as VOSviewer Version 1.6.20 is characterized by its core idea… More > Graphic Abstract

Rahma Gantassi, Zaki Masood, Yonghoon Choi^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 327-343, 2025, DOI:10.32604/cmc.2024.058143 - 03 January 2025

Abstract Wireless sensor network (WSN) technologies have advanced significantly in recent years. Within WSNs, machine learning algorithms are crucial in selecting cluster heads (CHs) based on various quality of service (QoS) metrics. This paper proposes a new clustering routing protocol employing the Traveling Salesman Problem (TSP) to locate the optimal path traversed by the Mobile Data Collector (MDC), in terms of energy and QoS efficiency. To be more specific, to minimize energy consumption in the CH election stage, we have developed the M-T protocol using the K-Means and the grid clustering algorithms. In addition, to improve More >

Rashid Ahmad¹, Asif Nawaz^1,*, Ghulam Mustafa¹, Tariq Ali¹, Mehdi Tlija², Mohammed A. El-Meligy^3,4, Zohair Ahmed⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4171-4194, 2024, DOI:10.32604/cmc.2024.056971 - 19 December 2024

Abstract Crime hotspot detection is essential for law enforcement agencies to allocate resources effectively, predict potential criminal activities, and ensure public safety. Traditional methods of crime analysis often rely on manual, time-consuming processes that may overlook intricate patterns and correlations within the data. While some existing machine learning models have improved the efficiency and accuracy of crime prediction, they often face limitations such as overfitting, imbalanced datasets, and inadequate handling of spatiotemporal dynamics. This research proposes an advanced machine learning framework, CHART (Crime Hotspot Analysis and Real-time Tracking), designed to overcome these challenges. The proposed methodology… More >

Eric Bourreau¹, Gérard Fleury², Philippe Lacomme^2,*

Journal of Quantum Computing, Vol.6, pp. 25-51, 2024, DOI:10.32604/jqc.2024.048792 - 25 October 2024

Abstract The paper presents a novel quantum method for addressing two fundamental routing problems: the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), both central to routing challenges. The proposed method, named the Indirect Quantum Approximate Optimization Algorithm (IQAOA), leverages an indirect solution representation using ranking. Our contribution focuses on two main areas: 1) the indirect representation of solutions, and 2) the integration of this representation into an extended version of QAOA, called IQAOA. This approach offers an alternative to QAOA and includes the following components: 1) a quantum parameterized circuit designed to simulate… More >

HEYI LIU^1,#, WENHAO CHENG^2,#, JINGLIANG HE², LUYAO ZHANG², KADIRYA ASAN², YULU CHEN², JIAYUN WANG², QI GAO², SENG WANG², ZIEN YU², SHAOJIE MA², LAN ZHU^3,*, JING JI^2,3,*

BIOCELL, Vol.48, No.10, pp. 1465-1473, 2024, DOI:10.32604/biocell.2024.052670 - 02 October 2024

Abstract Background: Osteosarcoma is the most common primary bone malignancy, with a strong tendency towards local invasion and metastasis. The SRY-Box Transcription Factor 1 (SOX1) gene, a member of the HMG-box family of DNA-binding transcription factors, plays a crucial role in embryogenesis and tumorigenesis. However, its role in osteosarcoma, particularly in relation to metastatic potential, is not well understood. Methods: The GSE14359 dataset containing five samples of conventional osteosarcoma and four samples of lung metastatic osteosarcoma was obtained from the Gene Expression Omnibus (GEO) database and analyzed for differential gene expression using the R language. Gene… More >

Rodrigo Vidonscky Pinto¹, Flávio Augusto Sanzovo Fiorelli^2,*

Frontiers in Heat and Mass Transfer, Vol.21, pp. 427-443, 2023, DOI:10.32604/fhmt.2023.041917 - 30 November 2023

Abstract The present work provides an experimental and numerical procedure to obtain the geometrical position of the hotspots of a microprocessor using the thermal images obtained from the transient thermal response of this processor subject to pulsating stress tests. This is performed by the solution of the steady inverse heat transfer problem using these thermal images, resulting in qualitative heat source distributions; these are analyzed using the mean heat source gradients to identify the elements that can be considered hotspots. This procedure identified that the processor INTEL Core 2 Quad Q8400S contains one hotspot located in More >

Adel A. Rezk^1,2,*, Hala A. Amin²

Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 691-705, 2023, DOI:10.32604/phyton.2022.024208 - 29 November 2022

Abstract Citrus Tristeza Virus (CTV), usually occurs in nature as a mixture of genotypes. Six naturally infected citrus (Citrus sinensis) trees grafted on sour orange rootstock were collected from three citrus growing governorates in Egypt (Sharqia, Qalyubia and Garbia). In this study, RT-PCR, Single-Strand Conformation Polymorphism (SSCP) and nucleotide sequence analysis were used for four independent CTV genomic regions (p65, p18, p20, and p23) to detect and assess the sequence and genetic variabilities among CTV Egyptian isolates. RTPCR products (650 bp) for the CTV p23 gene obtained from the selected isolates were used for the SSCP analysis… More >

Chuan Wang^1,*, Ruoyu Zhu², Yi Jiang³, Weili Liu⁴, Sang-Woon Jeon⁵, Lin Sun², Hua Wang⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1209-1228, 2023, DOI:10.32604/cmes.2022.022807 - 27 October 2022

Abstract The dynamic traveling salesman problem (DTSP) is significant in logistics distribution in real-world applications in smart cities, but it is uncertain and difficult to solve. This paper proposes a scheme library-based ant colony optimization (ACO) with a two-optimization (2-opt) strategy to solve the DTSP efficiently. The work is novel and contributes to three aspects: problem model, optimization framework, and algorithm design. Firstly, in the problem model, traditional DTSP models often consider the change of travel distance between two nodes over time, while this paper focuses on a special DTSP model in that the node locations… More >