Nurlan Zhangabay^1,*, Ulzhan Ibraimova², Marco Bonopera^3,*, Ulanbator Suleimenov¹, Konstantin Avramov⁴, Maryna Chernobryvko⁴, Aigerim Yessengali¹

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 1-23, 2025, DOI:10.32604/sdhm.2024.053391 - 15 November 2024

Abstract Using the software ANSYS-19.2/Explicit Dynamics, this study performed finite-element modeling of the large-diameter steel pipeline cross-section for the Beineu-Bozoy-Shymkent gas pipeline with a non-through straight crack, strengthened by steel wire wrapping. The effects of the thread tensile force of the steel winding in the form of single rings at the crack edges and the wires with different winding diameters and pitches were also studied. The results showed that the strengthening was preferably executed at a minimum value of the thread tensile force, which was 6.4% more effective than that at its maximum value. The analysis… More >

Daixuan Zhou¹, Yujin Liu¹, Xu Wang², Fuxing Wang¹, Yan Jia^2,*

Energy Engineering, Vol.121, No.12, pp. 3573-3616, 2024, DOI:10.32604/ee.2024.055853 - 22 November 2024

Abstract With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. More > Graphic Abstract

Nguyen Long Giang¹, Tran Thanh Dai², Le Hoang Son³, Tran Thi Ngan⁴, Nguyen Nhu Son¹, Cu Nguyen Giap^5,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3097-3124, 2024, DOI:10.32604/cmc.2024.057383 - 18 November 2024

Abstract Attribute reduction through the combined approach of Rough Sets (RS) and algebraic topology is an open research topic with significant potential for applications. Several research works have introduced a strong relationship between RS and topology spaces for the attribute reduction problem. However, the mentioned recent methods followed a strategy to construct a new measure for attribute selection. Meanwhile, the strategy for searching for the reduct is still to select each attribute and gradually add it to the reduct. Consequently, those methods tended to be inefficient for high-dimensional datasets. To overcome these challenges, we use the… More >

Juhwan Kim, Baehoon Son, Jihyeon Yu, Joobeom Yun^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3371-3393, 2024, DOI:10.32604/cmc.2024.057234 - 18 November 2024

Abstract Digital forensics aims to uncover evidence of cybercrimes within compromised systems. These cybercrimes are often perpetrated through the deployment of malware, which inevitably leaves discernible traces within the compromised systems. Forensic analysts are tasked with extracting and subsequently analyzing data, termed as artifacts, from these systems to gather evidence. Therefore, forensic analysts must sift through extensive datasets to isolate pertinent evidence. However, manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive. Previous studies addressed such inefficiencies by integrating artificial intelligence (AI) technologies into digital forensics. Despite the efforts in previous studies, artifacts were… More >

Jingbo Zhang¹, Qiong Wu^1,*, Pingyi Fan², Qiang Fan³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1953-1998, 2024, DOI:10.32604/cmc.2024.057006 - 18 November 2024

Abstract Federated Edge Learning (FEL), an emerging distributed Machine Learning (ML) paradigm, enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data. However, with the development of complex application scenarios such as the Internet of Things (IoT) and Smart Earth, the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands. Therefore, joint resource optimization may be the key solution to the scaling problem. This paper simultaneously addresses the multifaceted challenges of computation and communication, with the growing multiple resource demands. We… More >

Yuanyuan Ma¹, Ang Chen¹, Cunzhi Hou¹, Ruixia Jin², Jinghui Zhang¹, Ruixiang Li^3,4,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3301-3323, 2024, DOI:10.32604/cmc.2024.056854 - 18 November 2024

Abstract Currently, telecom fraud is expanding from the traditional telephone network to the Internet, and identifying fraudulent IPs is of great significance for reducing Internet telecom fraud and protecting consumer rights. However, existing telecom fraud identification methods based on blacklists, reputation, content and behavioral characteristics have good identification performance in the telephone network, but it is difficult to apply to the Internet where IP (Internet Protocol) addresses change dynamically. To address this issue, we propose a fraudulent IP identification method based on homology detection and DBSCAN(Density-Based Spatial Clustering of Applications with Noise) clustering (DC-FIPD). First, we… More >

Nataliya Shakhovska^1,2,*, Mykola Medykovskyi¹, Oleksandr Gurbych^1,3, Mykhailo Mamchur^1,3, Mykhailo Melnyk¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3147-3163, 2024, DOI:10.32604/cmc.2024.056542 - 18 November 2024

Abstract The increasing adoption of solar photovoltaic systems necessitates accurate forecasting of solar energy production to enhance grid stability, reliability, and economic benefits. This study explores advanced machine learning (ML) and deep learning (DL) techniques for predicting solar energy generation, emphasizing the significant impact of meteorological data. A comprehensive dataset, encompassing detailed weather conditions and solar energy metrics, was collected and preprocessed to improve model accuracy. Various models were developed and trained with different preprocessing stages. Finally, three datasets were prepared. A novel hour-based prediction wrapper was introduced, utilizing external sunrise and sunset data to restrict… More >

Rongwei Yu, Xiya Guo^*, Peihao Zhang, Kaijuan Zhang

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2643-2664, 2024, DOI:10.32604/cmc.2024.056165 - 18 November 2024

Abstract Encrypted traffic plays a crucial role in safeguarding network security and user privacy. However, encrypting malicious traffic can lead to numerous security issues, making the effective classification of encrypted traffic essential. Existing methods for detecting encrypted traffic face two significant challenges. First, relying solely on the original byte information for classification fails to leverage the rich temporal relationships within network traffic. Second, machine learning and convolutional neural network methods lack sufficient network expression capabilities, hindering the full exploration of traffic’s potential characteristics. To address these limitations, this study introduces a traffic classification method that utilizes… More >

Kusum Yadav¹, Yasser Alharbi¹, Eissa Jaber Alreshidi¹, Abdulrahman Alreshidi¹, Anuj Kumar Jain², Anurag Jain³, Kamal Kumar⁴, Sachin Sharma⁵, Brij B. Gupta^6,7,8,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2665-2683, 2024, DOI:10.32604/cmc.2024.053565 - 18 November 2024

Abstract In today’s world, image processing techniques play a crucial role in the prognosis and diagnosis of various diseases due to the development of several precise and accurate methods for medical images. Automated analysis of medical images is essential for doctors, as manual investigation often leads to inter-observer variability. This research aims to enhance healthcare by enabling the early detection of diabetic retinopathy through an efficient image processing framework. The proposed hybridized method combines Modified Inertia Weight Particle Swarm Optimization (MIWPSO) and Fuzzy C-Means clustering (FCM) algorithms. Traditional FCM does not incorporate spatial neighborhood features, making More >

HUI ZHOU^#, ZHENGYU YU^#, JING XU, ZHONGWANG WANG, YALI TAO, JINJIN WANG, PEIPEI YANG, JINRONG YANG^*, TING NIU^*

Oncology Research, Vol.32, No.12, pp. 1903-1919, 2024, DOI:10.32604/or.2024.048138 - 13 November 2024

Abstract Background: Dihydrolipoamide S-acetyltransferase (DLAT) is a subunit of the pyruvate dehydrogenase complex (PDC), a rate-limiting enzyme complex, that can participate in either glycolysis or the tricarboxylic acid cycle (TCA). However, the pathogenesis is not fully understood. We aimed to perform a more systematic and comprehensive analysis of DLAT in the occurrence and progression of tumors, and to investigate its function in patients’ prognosis and immunotherapy. Methods: The differential expression, diagnosis, prognosis, genetic and epigenetic alterations, tumor microenvironment, stemness, immune infiltration cells, function enrichment, single-cell analysis, and drug response across cancers were conducted based on multiple computational… More > Graphic Abstract