Yanxue Ma¹, Xiaoling Liu^1,*, Bing Wang², Ying Liu¹

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 871-889, 2024, DOI:10.32604/sdhm.2024.052683 - 20 September 2024

Abstract In the bridge technical condition assessment standards, the evaluation of bridge conditions primarily relies on the defects identified through manual inspections, which are determined using the comprehensive hierarchical analysis method. However, the relationship between the defects and the technical condition of the bridges warrants further exploration. To address this situation, this paper proposes a machine learning-based intelligent diagnosis model for the technical condition of highway bridges. Firstly, collect the inspection records of highway bridges in a certain region of China, then standardize the severity of diverse defects in accordance with relevant specifications. Secondly, in order… More >

Wenwen Li¹, Yutian Ma¹

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.40, No.2, pp. 1-6, 2024, DOI:10.23967/j.rimni.2024.06.003 - 21 June 2024

Abstract In the contemporary epoch, bolstered by information technology, the quintessence of networks is ubiquitously manifested, with a plethora of network types—ranging from the Internet, vehicular traffic frameworks, electrical distribution systems, cellular communication matrices, to social interconnection webs—being intricately woven into the fabric of societal functionality and quotidian existence. The domain of complex networks has burgeoned into a fervently pursued research vector, magnetizing an eclectic cohort of investigators from disciplines as variegated as mathematics, biosciences, and engineering. Notably, fractional calculus has eclipsed its integer-order counterpart by offering enhanced precision in the depiction of real-world systems and… More >

Jothi Prabha Appadurai¹, Dr. Rajesh T², R. Yugha³, Rashel Sarkar⁴, Arunadevi Thirumalraj⁵, Balasubramanian Prabhu kavin⁶, Dr. Gan Hong Seng⁷

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.40, No.2, pp. 1-9, 2024, DOI:10.23967/j.rimni.2024.02.002 - 03 May 2024

Abstract In smart city applications, electric vehicles (EVs) are rapidly gaining popularity due to their ability to help cut down on carbon emissions. Numerous environmental conditions, including terrain, traffic, driving style, temperature, and so on, affect the amount of energy an EV needs to operate. However, the burden on power grid infrastructure from widespread EV deployment is one of the biggest obstacles. Smart scheduling algorithms can be used to handle the rising public charging demand. Scheduling algorithms can be improved using data-driven tools and procedures to study EV charging behaviour. Predictions of behaviour, including temperature, departure… More >

Sheng Xu¹, Shixiong Xiang², Feiyu Meng¹, Qiang Wu^1,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4197-4218, 2024, DOI:10.32604/cmc.2024.055157 - 12 September 2024

Abstract In Unsupervised Domain Adaptation (UDA) for person re-identification (re-ID), the primary challenge is reducing the distribution discrepancy between the source and target domains. This can be achieved by implicitly or explicitly constructing an appropriate intermediate domain to enhance recognition capability on the target domain. Implicit construction is difficult due to the absence of intermediate state supervision, making smooth knowledge transfer from the source to the target domain a challenge. To explicitly construct the most suitable intermediate domain for the model to gradually adapt to the feature distribution changes from the source to the target domain,… More >

Xu Sun, Yinhui Yu^*, Qing Cheng

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4149-4171, 2024, DOI:10.32604/cmc.2024.052725 - 12 September 2024

Abstract Object detection in unmanned aerial vehicle (UAV) aerial images has become increasingly important in military and civil applications. General object detection models are not robust enough against interclass similarity and intraclass variability of small objects, and UAV-specific nuisances such as uncontrolled weather conditions. Unlike previous approaches focusing on high-level semantic information, we report the importance of underlying features to improve detection accuracy and robustness from the information-theoretic perspective. Specifically, we propose a robust and discriminative feature learning approach through mutual information maximization (RD-MIM), which can be integrated into numerous object detection methods for aerial images.… More >

R. Mahaveerakannan¹, Thanarajan Tamilvizhi^2,*, Sonia Jenifer Rayen³, Osamah Ibrahim Khalaf⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3945-3966, 2024, DOI:10.32604/cmc.2024.051611 - 12 September 2024

Abstract The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content. In light of the data-centric aspect of contemporary communication, the information-centric network (ICN) paradigm offers hope for a solution by emphasizing content retrieval by name instead of location. If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things (IoT) devices, then effective caching solutions will be required to maximize network throughput and minimize the use of resources. Hence, an ICN-based Cooperative Caching (ICN-CoC) technique has been used to select… More >

Benxin Li^*, Xuanming Chang

Energy Engineering, Vol.121, No.10, pp. 3001-3018, 2024, DOI:10.32604/ee.2024.051332 - 11 September 2024

Abstract The increasingly large number of electric vehicles (EVs) has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks. To address this issue, an EV charging station load prediction method is proposed in coupled urban transportation and distribution networks. Firstly, a finer dynamic urban transportation network model is formulated considering both nodal and path resistance. Then, a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature. Thirdly, the Monte Carlo method… More > Graphic Abstract

Humberto Esqueda¹, Salvador Botello², S.Ivvan Valdez³

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.40, No.3, pp. 1-24, 2024, DOI:10.23967/j.rimni.2024.08.002 - 27 August 2024

Abstract Floods produce enormous human and material losses every year. Evaluating their extent and severity, and especially simulating possible future scenarios can improve the response, mitigation and prevention oftheeffectsofthisphenomenon.Thispaper presentsa methodology toreproduce theextentoffloods producedbychannel overflows and recorded by satellite images, identifying the maximum discharge that produced it by means of the numerical solution of the 2D shallow water equations and Differential Evolution. The objective is to minimize the difference between the extent of the flooded area recorded in the satellite images, and that obtained in the simulation by adjusting the maximum value of the flow curve More >

Lirong Yin¹, Lei Wang¹, Zhuohang Cai², Siyu Lu^2,*, Ruiyang Wang², Ahmed AlSanad³, Salman A. AlQahtani³, Xiaobing Chen⁴, Zhengtong Yin⁵, Xiaolu Li⁶, Wenfeng Zheng^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 771-786, 2024, DOI:10.32604/cmes.2024.052622 - 20 August 2024

Abstract Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset More >

Ebtesam Ahmad Alomari^*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 43-85, 2024, DOI:10.32604/cmes.2024.052256 - 20 August 2024

Abstract As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been a notable growth in research activity. This rapid uptake reflects increasing interest in the field and induces critical inquiries into ChatGPT’s applicability in the NLP domain. This review paper systematically investigates the role of ChatGPT in diverse NLP tasks, including information extraction, Name Entity Recognition (NER), event extraction, relation extraction, Part of Speech (PoS) tagging, text classification, sentiment analysis, emotion recognition and text annotation. The novelty of this work lies in its… More >