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Local charge homogenization strategy enables ultra-high voltage tolerance of polyether electrolytes for 4.7 V lithium metal batteries

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国家科学评论（英文版） 2025年第2期12卷 213-223页

作者： Yuanlong Wu Piao Luo Kexin Su Mao Yu Xin Song Lianzhan Huang Shaocong Zhang Huiyu Song Li Du Weishu Liu Zhiming Cui Guangdong Provincial Key Laboratory of Fuel Cell Technology School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510641China Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Advanced Energy Storage Materials School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510641China School of Software Engineering South China University of TechnologyGuangzhou 510006China

In-situ fabricated polyether electrolytes have been regarded as one of the most promising solid electrolyte ***,they cannot match high-voltage cathodes over 4.3 V due to their poor oxidative ***,we propose an effective local charge homogenization strategy based on the triglycidyl isocyanurate(TGIC)crosslinker,achieving ultra-high-voltage electrochemical stability of polyether electrolytes(***)at cutoff voltages up to 4.7 *** introduction of TGIC optimizes the Li+solvation environment,thereby homogenizing the charge distribution at ether oxygen(EO)sites,resulting in significantly enhanced oxidative stability of the polyether main ***,the Li|PTIDOL|LiNi0.6Co0.2Mn0.2O2(NCM622)cell achieves long-term operation at an ultra-high cutoff voltage with a capacity retention of 81.8％after 400 cycles,one of the best results reported for polyether electrolytes to *** work provides significant insights for the development of polyether electrolytes with high-voltage tolerance and the advancement of high-energy-density batteries.

关键词： lithium metal batteries solid polymer electrolytes in-situ polymerization high voltage local charge homogenization

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A Cover-Independent Deep Image Hiding Method Based on Domain Attention Mechanism

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Computers, Materials & Continua 2024年第3期78卷 3001-3019页

作者： Nannan Wu Xianyi Chen James Msughter Adeke Junjie Zhao School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing210044China

Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information ***,these approaches have some *** example,a cover image lacks self-adaptability,information leakage,or weak *** address these issues,this study proposes a universal and adaptable image-hiding ***,a domain attention mechanism is designed by combining the Atrous convolution,which makes better use of the relationship between the secret image domain and the cover image ***,to improve perceived human similarity,perceptual loss is incorporated into the training *** experimental results are promising,with the proposed method achieving an average pixel discrepancy(APD)of 1.83 and a peak signal-to-noise ratio(PSNR)value of 40.72 dB between the cover and stego images,indicative of its high-quality ***,the structural similarity index measure(SSIM)reaches 0.985 while the learned perceptual image patch similarity(LPIPS)remarkably registers at ***,self-testing and cross-experiments demonstrate the model’s adaptability and generalization in unknown hidden spaces,making it suitable for diverse computer vision tasks.

关键词： Deep image hiding attention mechanism privacy protection data security visual quality

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Fatigue reliability assessment of turbine blade via direct probability integral method

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Chinese Journal of Aeronautics 2025年第4期38卷 305-320页

作者： Guohai CHEN Pengfei GAO Hui LI Dixiong YANG State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentSchool of Mechanics and Aerospace EngineeringDalian University of TechnologyDalian 116024China

Fatigue analysis of engine turbine blade is an essential *** to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present *** this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability ***,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random ***,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic *** probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,***,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of ***,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other *** is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue *** rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.

关键词： Engine turbine blade Low-cycle fatigue High-cycle fatigue Fatigue reliability Direct probability integral method

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Data Security and Privacy Protection Scheme Based on EC-ElGamal in Federal Learning

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SN Computer Science 2025年第2期6卷 1-10页

作者： Liu, Bin Blancaflor, Eric B. School of Information Technology Mapua University Manila Philippines School of Software Engineering Xiamen University of Technology Xiamen China

Federated learning is a new distributed learning framework that can train multi-party user data without knowing the original user data, which protects user privacy to a certain extent. However, the application of federated learning in the Internet of Things still faces some problems, such as the high cost of client-server communication, frequent communication failures, and lack of high-quality data to guarantee the training process. To solve the problems of communication costs affected by different encryption schemes, dynamic user joining and exiting, and low user data quality affecting accuracy, this paper proposes a data security and privacy protection method based on EC-ElGamal in federated learning. EC-ElGamal is an additive homomorphic encryption scheme based on ElGamal elliptic curves, which has a shorter key length and less traffic than the ElGamal scheme. Firstly, the scheme uses lightweight EC-ElGamal and improved multi-key EC-ElGamal cryptosystem in the Internet of Things environment to realize cooperative training of multi-key users under federated learning and reduce communication costs. Secondly, FSOA(Federated sum optimization algorithm) is proposed to obtain high-quality data for training, which can avoid the problem of low data quality affecting accuracy. At the same time, a dynamic user joining and exiting algorithm is proposed, which can realize the dynamic user update without affecting the training accuracy. The experiment results shows that by selecting high-quality training data and a short key length encryption scheme for model training, The total encryption and decryption time of this scheme is lower than the other three encryption and decryption time of Paillier, ElGamal and LWE, the communication cost of the scheme is reduced, and the training accuracy is ensured under the condition of dynamic updating of users. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Data security Dynamic update EC-ElGamal Federated learning Internet of things Privacy protection

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Application of LSTM emotion recognition based on deep learning and attention mechanism in patient relationship mediation 4

Application of LSTM emotion recognition based on deep learni...

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4th International Conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Ma, Yuxuan School of Software Engineering Lappeenrannan University of Technology Lahti Finland

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Medical disputes are a kind of disharmonious interpersonal relationship caused by different positions, views, and ways of thinking between doctors and patients. In recent years, it has shown an upward trend and has become a major issue affecting social stability and hospital development. This paper refers to the research process and results of Henkel et al. (2020) in the service industry and uses the CREMA-D dataset to train the model to obtain the accuracy of the algorithm and design an experimental process for using AI to solve doctor-patient relationships. This paper uses the CREMA-D dataset to divide emotions into six types: anger, disgust, fear, happy, neutral, and sad. Using natural language processing and LSTM to process emotions in speech data provides help and guidance for doctors to regulate patients' emotions, and helps doctors use AI integrated tools to regulate their own emotions and improve the happiness index of both parties. © 2025 SPIE.

关键词： Emotion Recognition

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A Neural Network Slab Quality Prediction Analysis Based on a Hybrid Intelligent Optimisation Algorithm

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2025年第3期52卷 673-683页

作者： Li, Yiran Zhang, Chunna School of Applied Technology University of Science and Technology Liaoning Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Liaoning Anshan114051 China

To address the problem of inaccurate prediction of slab quality in continuous casting, an algorithm based on particle swarm optimisation and differential evolution is proposed. The algorithm combines BP neural network prediction method. Firstly, the factors affecting the quality of the slab are analysed and a sufficient number of sample sets are extracted for training;Secondly, the particle swarm optimisation algorithm is optimised, and then the BP neural network is optimised and the chaos mechanism is introduced to increase the continuity of motion of the particles. The population is partitioned hierarchically, and different types of particles are processed separately to improve the global search capability of the algorithm. The differential evolution algorithm is also integrated to optimise cross-selection and increase particle diversity. Finally, a prediction model is built to predict and analyse the sample data. In the experiment, three algorithms are tested for different benchmark functions, namely the comparison of convergence, stability and searchability. The optimisation time comparison is completed, the target curve fit test is performed and the slab quality test results are checked. The experimental results show that the PSO-EIDE algorithm has strong optimisation ability, fast convergence speed and obvious improvement in stability and accuracy. © (2025), (International Association of Engineers). All rights reserved.

关键词： Prediction models

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A Modified Dual Mode Repetitive Control for a CVCF PWM Inverter

A Modified Dual Mode Repetitive Control for a CVCF PWM Inver...

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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Dapeng, Li School of Software Engineering Jingling Institute of Technology Nanjing China

ISBN: (纸本)9789819620418

Repetitive control (RC) is a commonly employed approach for accurately tracking periodic signals and mitigating periodic disturbances. However, the inherent delay in repetitive controllers can adversely impact both transient and steady-state system performances. To address this challenge and enhance the overall performance of repetitive control systems, a digital dual mode repetitive control (DMRC) strategy has been introduced. DMRC has high tracking precision and swift transient response, representing a significant and noteworthy improvement. Based on DMRC, a modified dual mode repetitive control (MDRC) is introduced in the paper. The superiority of this method is analyzed. The experimental results show that MDRC can improve the steady state control accuracy of the system when the control system remains stable. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Low pass filters

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A Reduced Infinite-Order Repetitive Controller for PWM Inverters

A Reduced Infinite-Order Repetitive Controller for PWM Inver...

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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Li, Dapeng School of Software Engineering Jingling Institute of Technology Nanjing China

ISBN: (纸本)9789819620456

High order repetitive control (HORC) has been reported to improve the robustness of the control system that incorporate the non-periodic disturbance. In fact, the higher the order is, the more memory cells are needed, and the more total delay time of the control system is needed. Notably, in practical applications, the reported order of HORC rarely exceeds three, and an application with infinite-order HORC has never been reported. To address this issue, a reduced infinite-order repetitive controller (RIORC), using geometric principles, is introduced in this paper. The RIORC is equivalent to a second order repetitive controller. Compared to the traditional infinite-order repetitive control, the memory cells are largely reduced, and the total delay time of the control system is less needed. The effectiveness of the proposed RIORC scheme is verified through its application in a PWM inverter. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Delay control systems

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Integrating Information Security and Hardware Defense in Medical Printers: Addressing RowHammer Vulnerabilities 24

Integrating Information Security and Hardware Defense in Med...

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4th International Conference on Signal Processing and Communication technology, SPCT 2024

作者： Han, Zongshuo School of Software Engineering Lappeenranta University of Technology Lahti Finland

ISBN: (纸本)9798400710636

With the rapid development of modern medical equipment technology, more and more diagnosis and treatment processes rely on the support of printing devices. When the doctor transfers data to the printer, the printer first stores the data in RAM to ensure the smooth progress of the printing process. However, the data in RAM faces potential security threats, especially the design defects of dynamic random access memory (DRAM) are vulnerable to RowHammer attacks. RowHammer attacks use charge interference to affect the charge state of adjacent rows by quickly and repeatedly reading a row of memory data, thereby destroying data integrity and even obtaining access to key data in the system memory, causing the risk of data leakage and tampering. In response to this security risk, this paper proposes to use RockHammer to enhance the security performance of printers. RockHammer strengthens the protection mechanism of embedded system memory, can effectively resist the interference operation of attackers, and ensure the integrity and confidentiality of data. The application of this technology can not only ensure the security of medical printing equipment data, but also provide important technical contributions to the fields of medical data security and embedded system security. © 2024 Copyright held by the owner/author(s).

关键词： Information leakage

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Competition for gradient-free tuning of large language models:approaches, results, current challenges and future directions

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National Science Review 2023年第6期10卷 16-19页

作者： Tingfeng Cao Liang Chen Dixiang Zhang Tianxiang Sun Zhengfu He Xipeng Qiu Xing Xu Hai Zhang School of Software Engineering South China University of Technology School of Computer Science Fudan University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

PROBLEM Recent years have witnessed the rapid progress of self-supervised language models (LMs)[1],especially large language models (LLMs)[2].LLMs not only achieved state-of-the-art performance on many natural language processing tasks,but also captured widespread attention from the public due to their great potential in a variety of real-world applications (***,search engines,writing assistants,etc.)through providing general-purpose intelligent services.A few of the LLMs are becoming foundation models,an analogy to infrastructure,that empower hundreds of downstream applications.

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