Zhe Li, Yun Liang, Jinyu Wang, Yang Gao^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1171-1192, 2025, DOI:10.32604/cmc.2024.057225 - 03 January 2025

Abstract Iced transmission line galloping poses a significant threat to the safety and reliability of power systems, leading directly to line tripping, disconnections, and power outages. Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source, neglect of irregular time series, and lack of attention-based closed-loop feedback, resulting in high rates of missed and false alarms. To address these challenges, we propose an Internet of Things (IoT) empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather… More >

Peng Li, Yanrui Wei, Lili Yin^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 609-625, 2025, DOI:10.32604/cmc.2024.056651 - 03 January 2025

Abstract Stock price prediction is a typical complex time series prediction problem characterized by dynamics, nonlinearity, and complexity. This paper introduces a generative adversarial network model that incorporates an attention mechanism (GAN-LSTM-Attention) to improve the accuracy of stock price prediction. Firstly, the generator of this model combines the Long and Short-Term Memory Network (LSTM), the Attention Mechanism and, the Fully-Connected Layer, focusing on generating the predicted stock price. The discriminator combines the Convolutional Neural Network (CNN) and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices. Secondly, to evaluate the practical application… More >

Tianzhi Zhang¹, Gang Zhou^1,*, Shuang Zhang², Shunhang Li¹, Yepeng Sun¹, Qiankun Pi¹, Shuo Liu³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 279-305, 2025, DOI:10.32604/cmc.2024.055943 - 03 January 2025

Abstract Joint Multimodal Aspect-based Sentiment Analysis (JMASA) is a significant task in the research of multimodal fine-grained sentiment analysis, which combines two subtasks: Multimodal Aspect Term Extraction (MATE) and Multimodal Aspect-oriented Sentiment Classification (MASC). Currently, most existing models for JMASA only perform text and image feature encoding from a basic level, but often neglect the in-depth analysis of unimodal intrinsic features, which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features. Given this problem, we propose a Text-Image Feature Fine-grained… More >

Adnan Ahmad, Zhao Li^*, Irfan Tariq, Zhengran He

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 729-749, 2025, DOI:10.32604/cmc.2024.055768 - 03 January 2025

Abstract Micro-expressions (ME) recognition is a complex task that requires advanced techniques to extract informative features from facial expressions. Numerous deep neural networks (DNNs) with convolutional structures have been proposed. However, unlike DNNs, shallow convolutional neural networks often outperform deeper models in mitigating overfitting, particularly with small datasets. Still, many of these methods rely on a single feature for recognition, resulting in an insufficient ability to extract highly effective features. To address this limitation, in this paper, an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm (IDSSCNN-XgBoost) is introduced for ME… More >

Jiajia Liu^*, Mingxing Tian, Xusheng Mao

Energy Engineering, Vol.122, No.1, pp. 379-404, 2025, DOI:10.32604/ee.2024.058137 - 27 December 2024

Abstract After a century of relative stability in the electricity sector, the widespread adoption of distributed energy resources, along with recent advancements in computing and communication technologies, has fundamentally altered how energy is consumed, traded, and utilized. This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach. At the heart of this transformation are innovative energy distribution models, like peer-to-peer (P2P) sharing, which enable communities to collaboratively manage their energy resources. The effectiveness of P2P sharing not only improves the economic prospects for prosumers, who… More >

Hongliang Hao¹, Caifeng Wen^2,3, Feifei Xue^2,*, Hao Qiu¹, Ning Yang², Yuwen Zhang¹, Chaoyu Wang¹, Edwin E. Nyakilla¹

Energy Engineering, Vol.122, No.1, pp. 285-306, 2025, DOI:10.32604/ee.2024.057720 - 27 December 2024

Abstract Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources. This paper proposes a wind-solar hybrid energy storage system (HESS) to ensure a stable supply grid for a longer period. A multi-objective genetic algorithm (MOGA) and state of charge (SOC) region division for the batteries are introduced to solve the objective function and configuration of the system capacity, respectively. MATLAB/Simulink was used for simulation test. The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system, with a combination of a 300 More >

Xin Zhang^*, Mingming Yao, Daiwen He, Jihong Zhang, Peihong Yang, Xiaoming Zhang

Energy Engineering, Vol.122, No.1, pp. 349-378, 2025, DOI:10.32604/ee.2024.057676 - 27 December 2024

Abstract In this paper, a bilevel optimization model of an integrated energy operator (IEO)–load aggregator (LA) is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system (IIES). The upper level represents the integrated energy operator, and the lower level is the electricity-heat-gas load aggregator. Owing to the benefit conflict between the upper and lower levels of the IIES, a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed, combined with factors such as the carbon emissions of the IIES, as well as the lower load… More > Graphic Abstract

Jie Lin^*, Hongchi Shen, Tingting Pei, Yan Wu

Energy Engineering, Vol.122, No.1, pp. 331-347, 2025, DOI:10.32604/ee.2024.055611 - 27 December 2024

Abstract Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unit power generation costs. The service life of these modules directly affects these costs. Over time, the performance of PV modules gradually declines due to internal degradation and external environmental factors. This cumulative degradation impacts the overall reliability of photovoltaic power generation. This study addresses the complex degradation process of PV modules by developing a two-stage Wiener process model. This approach accounts for the distinct phases of degradation resulting from module aging and environmental influences. A power degradation model based on the More > Graphic Abstract

MERYEM A. ABDESSALEM, SIRIN A. ADHAM^*

Oncology Research, Vol.33, No.1, pp. 27-44, 2025, DOI:10.32604/or.2024.056955 - 20 December 2024

Abstract Nanotechnology in cancer therapy has significantly advanced treatment precision, effectiveness, and safety, improving patient outcomes and personalized care. Engineered smart nanoparticles and cell-based therapies are designed to target tumor cells, precisely sensing the tumor microenvironment (TME) and sparing normal cells. These nanoparticles enhance drug accumulation in tumors by solubilizing insoluble compounds or preventing their degradation, and they can also overcome therapy resistance and deliver multiple drugs simultaneously. Despite these benefits, challenges remain in patient-specific responses and regulatory approvals for cell-based or nanoparticle therapies. Cell-based drug delivery systems (DDSs) that primarily utilize the immune-recognition principle between… More > Graphic Abstract

RYUL KIM^1,#, JOO KYUNG PARK^2,#, MINSUK KWON³, MINAE AN⁴, JUNG YONG HONG¹, JOON OH PARK¹, SUNG HEE LIM^1,*, SEUNG TAE KIM^1,*

Oncology Research, Vol.33, No.1, pp. 57-65, 2025, DOI:10.32604/or.2024.049054 - 20 December 2024

Abstract Background: Immune checkpoint inhibitors (ICIs) are effective in a subset of patients with metastatic solid tumors. However, the patients who would benefit most from ICIs in biliary tract cancer (BTC) are still controversial. Materials and methods: We molecularly characterized tissues and blood from 32 patients with metastatic BTC treated with the ICI pembrolizumab as second-line therapy. Results: All patients had microsatellite stable (MSS) type tumors. Three of the 32 patients achieved partial response (PR), with an objective response rate (ORR) of 9.4% (95% confidence interval [CI], 2.0–25.2) and nine showed stable disease (SD), exhibiting a disease… More >