Min Liu¹, Qiliang Wu¹, Zhixin Li², Bo Zhao¹, Leiqi Zhang¹, Junhui Li², Xingxu Zhu^2,*

Energy Engineering, Vol.122, No.4, pp. 1403-1424, 2025, DOI:10.32604/ee.2025.060256 - 31 March 2025

Abstract To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms, an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed. First, considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage, an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system. Next, an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with… More >

Haoyuan Li, Lingling Li^*

Energy Engineering, Vol.122, No.4, pp. 1337-1358, 2025, DOI:10.32604/ee.2025.060105 - 31 March 2025

Abstract Rational distribution network planning optimizes power flow distribution, reduces grid stress, enhances voltage quality, promotes renewable energy utilization, and reduces costs. This study establishes a distribution network planning model incorporating distributed wind turbines (DWT), distributed photovoltaics (DPV), and energy storage systems (ESS). K-means++ is employed to partition the distribution network based on electrical distance. Considering the spatiotemporal correlation of distributed generation (DG) outputs in the same region, a joint output model of DWT and DPV is developed using the Frank-Copula. Due to the model’s high dimensionality, multiple constraints, and mixed-integer characteristics, bilevel programming theory is… More >

Yuxin Zheng, Ke Xu, Baicheng Zhang, Shengxin Guan, Lin Xia, Zhaoge Huang^*

Journal of Polymer Materials, Vol.42, No.1, pp. 237-253, 2025, DOI:10.32604/jpm.2025.059622 - 27 March 2025

Abstract In this manuscript, we conveniently prepared a series of polyester-polycarbonate copolymer (PPC-P)/polybutylene adipate terephthalate (PBAT) blends that exhibit both flame-retardant properties and toughness. Piperazine pyrophosphate (PAPP), melamine phosphate (MPP) and ZnO were used as synergistic flame retardants for PPC-P/PBAT blends. The effects of synergistic flame retardants on thermal stability, combustion behavior and flame retardancy of PPC-P/PBAT blends were investigated. The results showed that when the ratio of PAPP/MPP/ZnO was 18.4:9.2:2.4, the LOI of PPC-P/PBAT composite was 42.8%, and UL-94 reached V-0 level. The results of cone calorimetry showed that the mass loss rate (MLR), the… More >

Yi-Ze Wu, Yi-Cheng Huang^*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 97-114, 2025, DOI:10.32604/cmc.2025.063441 - 26 March 2025

Abstract Precision steel balls are critical components in precision bearings. Surface defects on the steel balls will significantly reduce their useful life and cause linear or rotational transmission errors. Human visual inspection of precision steel balls demands significant labor work. Besides, human inspection cannot maintain consistent quality assurance. To address these limitations and reduce inspection time, a convolutional neural network (CNN) based optical inspection system has been developed that automatically detects steel ball defects using a novel designated vertical mechanism. During image detection processing, two key challenges were addressed and resolved. They are the reflection caused… More >

Zaid Derea^1,2,*, Beiji Zou¹, Xiaoyan Kui^1,*, Monir Abdullah³, Alaa Thobhani¹, Amr Abdussalam⁴

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 115-136, 2025, DOI:10.32604/cmc.2025.062729 - 26 March 2025

Abstract Improving website security to prevent malicious online activities is crucial, and CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) has emerged as a key strategy for distinguishing human users from automated bots. Text-based CAPTCHAs, designed to be easily decipherable by humans yet challenging for machines, are a common form of this verification. However, advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising efficiency. In our comprehensive investigation into CAPTCHA recognition, we have tailored the renowned UpDown image captioning model specifically for this… More >

Long Cai, Ke Gu^*, Jiaqi Lei

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 239-258, 2025, DOI:10.32604/cmc.2025.061377 - 26 March 2025

Abstract Large-scale neural networks-based federated learning (FL) has gained public recognition for its effective capabilities in distributed training. Nonetheless, the open system architecture inherent to federated learning systems raises concerns regarding their vulnerability to potential attacks. Poisoning attacks turn into a major menace to federated learning on account of their concealed property and potent destructive force. By altering the local model during routine machine learning training, attackers can easily contaminate the global model. Traditional detection and aggregation solutions mitigate certain threats, but they are still insufficient to completely eliminate the influence generated by attackers. Therefore, federated… More >

Tajinder Kumar¹, Purushottam Sharma^2,*, Xiaochun Cheng^3,*, Sachin Lalar⁴, Shubham Kumar⁵, Sandhya Bansal⁶

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 719-738, 2025, DOI:10.32604/cmc.2025.060836 - 26 March 2025

Abstract With cloud computing, large chunks of data can be handled at a small cost. However, there are some reservations regarding the security and privacy of cloud data stored. For solving these issues and enhancing cloud computing security, this research provides a Three-Layered Security Access model (TLSA) aligned to an intrusion detection mechanism, access control mechanism, and data encryption system. The TLSA underlines the need for the protection of sensitive data. This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard (AES). For data transfer and storage, this encryption guarantees the data’s… More >

Chexiaole Zhang, Haiyan Fu^*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1291-1306, 2025, DOI:10.32604/cmc.2025.060740 - 26 March 2025

Abstract As computer data grows exponentially, detecting anomalies within system logs has become increasingly important. Current research on log anomaly detection largely depends on log templates derived from log parsing. Word embedding is utilized to extract information from these templates. However, this method neglects a portion of the content within the logs and confronts the challenge of data imbalance among various log template types after parsing. Currently, specialized research on data imbalance across log template categories remains scarce. A dual-attention-based log anomaly detection model (LogDA), which leveraged data imbalance, was proposed to address these issues in More >

Jialiang Dong^1,2, Xuemao Dong^3,4, Zhongxue Feng^3,4,*, Caiju Li^3,4, Jianhong Yi^3,4, Jun Tan^5,*

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 65-77, 2025, DOI:10.32604/cmc.2025.059727 - 26 March 2025

Abstract To explore atomic-level phenomena in the Cu-Ni-Sn alloy, a second nearest-neighbor modified embedded-atom method (2NN MEAM) potential has been developed for the Cu-Ni-Sn system, building upon the work of other researchers. This potential demonstrates remarkable accuracy in predicting the lattice constant, with a relative error of less than 0.5% when compared to density functional theory (DFT) results, and it achieves a 10% relative error in the enthalpy of formation compared to experimental data, marking substantial advancements over prior models. The bulk modulus is predicted with a relative error of 8% compared to DFT. Notably, the More >

Zeric Tabekoueng Njitacke¹, Louai A. Maghrabi², Musheer Ahmad^3,*, Turki Althaqafi⁴

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 917-933, 2025, DOI:10.32604/cmc.2025.059640 - 26 March 2025

Abstract This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine map. The map demonstrates remarkable chaotic dynamics over a wide range of parameters. We employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map, which allows us to select optimal parameter configurations for the encryption process. Our findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors, an essential characteristic for effective encryption. The encryption technique is based on bit-plane decomposition, wherein a plain image is divided into distinct… More >