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2nd International Conference on Emerging Trends in information technology and engineering, ic-ETITE 2024

作者： Modi, Pranit Asgola, Abhishek Mishra, Hiya Charanya, R. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Vellore India

ISBN: (纸本)9798350328202

Blockchain technology, born as the backbone of cryptocurrencies like Bitcoin, has rapidly expanded into a versatile platform spanning various industries. This review paper delves into the critical aspects of security and anonymity within blockchain applications. It simplifies complex technical concepts while exploring the foundation of blockchain security, including cryptography, decentralization, consensus mechanisms, and the challenges posed by smart contracts. Additionally, it examines the pseudonymous nature of blockchain addresses, privacy-enhancing cryptocurrencies, and the delicate balance between transparency and anonymity. As we navigate these intricacies, we address challenges such as scalability, regulatory concerns, and potential threats from quantum computing. This paper aims to provide a comprehensive yet easily digestible understanding of the security and anonymity dimensions in blockchain applications. © 2024 IEEE.

关键词： Blockchain

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In-doping collaboratively controlling back interface and bulk defects to achieve efficient flexible CZTSSe solar cells

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Journal of Energy Chemistry 2024年第2期89卷 10-17,I0002页

作者： Quanzhen Sun Yifan Li Caixia Zhang Shunli Du Weihao Xie Jionghua Wu Qiao Zheng Hui Deng Shuying Cheng Institute of Micro-Nano Devices and Solar Cells College of Physics and Information EngineeringFuzhou UniversityFuzhou 350108FujianChina Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108FujianChina Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering Changzhou 213164JiangsuChina

Focusing on the low open circuit voltage(V_(OC))and fill factor(FF)in flexible Cu_(2)ZnSn(S,Se)_(4)(CZTSSe)solar cells,indium(In)ions are introduced into the CZTSSe absorbers near Mo foils to modify the back interface and passivate deep level defects in CZTSSe bulk concurrently for improving the performance of flexible *** results show that In doping effectively inhibits the formation of secondary phase(Cu(S,Se)_(2))and *** studies demonstrate that the barrier height at the back interface is decreased and the deep level defects(Cu_(Sn)defects)in CZTSSe bulk are ***,the carrier concentration is increased and the V_(OC) deficit(V_(OC,def))is decreased significantly due to In ***,the flexible CZTSSe solar cell with 10.01%power conversion efficiency(PCE)has been *** synergistic strategy of interface modification and bulk defects passivation through In incorporation provides a new thought for the fabrication of efficient flexible kesterite-based solar cells.

关键词： Flexible solar cells Cu_(2)ZnSn(S,Se)_(4) Back interface Deep level defects Barrier height

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I $^{2}$ RNN: An Incremental and Interpretable Recurrent Neural Network for Encrypted Traffic Classification

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IEEE Transactions on Dependable and Secure Computing 2023年 1-14页

作者： Song, Zhuoxue Zhao, Ziming Zhang, Fan Xiong, Gang Cheng, Guang Zhao, Xinjie Guo, Shize Chen, Binbin College of Computer Science and Technology Zhejiang University Hangzhou China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Science and Engineering Southeast University Nanjing China Information Systems Technology and Design Singapore University of Technology and Design Singapore

Traffic classification occupies a significant role in cybersecurity and network management. The widespread of encryption transmission protocols such as SSL/TLS has led to the dominance of deep learning based approaches. In cybersecurity, strong adversaries often complicate their strategies by constantly developing emerging attacks. Meanwhile, security practitioners desire to grasp the reasons for inference results. However, existing deep learning approaches lack efficient adaptation for incremental traffic types and often have less interpretability. In this paper, we propose I $^{2}$ RNN, an Incremental and Interpretable Recurrent Neural Network for encrypted traffic classification. The I $^{2}$ RNN proposes a novel propagation process to extract the sequence fingerprints from sessions with local robustness. Meanwhile, this proposal provides interpretability including time-series feature attribution and inter-class similarity portrait. Moreover, we design I $^{2}$ RNN in an incremental manner to adapt to emerging traffic types. The I $^{2}$ RNN only needs to train an additional set of parameters for the newly added traffic type rather than retraining the whole model with the entire dataset. Extensive experimental results show that our I $^{2}$ RNN can achieve remarkable performance in traffic classification, incremental learning, and model interpretability. Compared with other local interpretability methods, our I $^{2}$ RNN exhibits excellent stability, robustness, and effectiveness in the interpretation of network traffic data. IEEE

关键词： Cryptography

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engineering Corynebacterium glutamicum for the efficient production of 3-hydroxypropionic acid from glucose via theβ-alanine pathway

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Synthetic and systems Biotechnology 2024年第4期9卷 752-758页

作者： Xiaodi Wang Junyuan Hou Jieyao Cui Zhiwen Wang Tao Chen Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering of the Ministry of Education School of Chemical Engineering and TechnologyTianjin UniversityTianjin300072China School of Chemical Engineering and Technology Tianjin UniversityTianjin300072China

3-Hydroxypropionic Acid(3-HP)is recognized as a high value-added chemical with a broad range of *** the various biosynthetic pathways for 3-HP production,theβ-alanine pathway is particularly noteworthy due to its capacity to generate 3-HP from glucose at a high theoretical *** this study,theβ-alanine biosynthesis pathway was introduced and optimized in Corynebacterium *** strategically regulating the supply of precursors,we successfully engineered a strain capable of efficiently synthesizing 3-HP through theβ-alanine pathway,utilizing glucose as the *** engineered strain CgP36 produced 47.54 g/L 3-HP at a yield of 0.295 g/g glucose during the fed-batch fermentation in a 5 L fermenter,thereby attaining the highest 3-HP titer obtained from glucose via theβ-alanine pathway.

关键词： 3-Hydroxypropionic acid β-Alanine pathway Corynebacterium glutamicum Metabolic engineering

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Tandem light-emitting technology accelerates the commercial application of perovskite LEDs

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Light(science & Applications) 2024年第12期13卷 2861-2862页

作者： Xiang Zhang Jiajun Luo Enguo Chen Abd.Rashid bin Mohd Yusoff Wuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074 HubeiChina National and Local United Engineering Laboratory of Flat Panel Display Technology College of Physics and Information EngineeringFuzhou UniversityFuzhouFujian 350108China Department of Physics Faculty of ScienceUniversiti Teknologi MalaysiaJohor BahruMalaysia

Hybrid tandem perovskite-organic LED has been developed to achieve high external quantum efficiency,narrow linewidth,and extended device lifespan,which shows great promise for future perovskite-EL-based commercial app... 详细信息

关键词： emitting perovskite narrow

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Flexible Inverse Design of Microwave Filter Customized on Demand With Wavelet Transform Deep Learning

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and systems 2025年第3期44卷 806-817页

作者： Xu, Kuiwen Wang, Jianguo Cai, Jialin Ma, Xuetiao Lv, Qinyi Chen, Shichang Liu, Jie Liu, Jun Hangzhou Dianzi University Innovation Center for Electronic Design Automation Technology The Key Laboratory of RF Circuits and Systems Ministry of Education Hangzhou310018 China Chang'an Campus Northwestern Polytechnical University School of Electronic Information Xi'an710060 China University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu610054 China Information Science Academy China Electronics Technology Group Corporation Beijing100846 China

Artificial intelligence (AI) techniques are increasingly being used for the inverse design of microwave devices. However, several challenges, including intensive computation costs for training samples, high-dimensional data, nonuniformity, and low-quality samples in the design space, can negatively impact the final modeling performance. To alleviate these issues, a high-quality sampling inverse design scheme incorporating wavelet transform deep learning (HQS-WTDL) is proposed to achieve customized, automated microwave filter design. In the forward simulation-based sampling, particle swarm optimization (PSO) is used to tentatively select rule-defined samples. Multilabel synthetic minority over-sampling technique (MLSMOTE) is then applied to enlarge the training samples and improve their uniformity in the design space. An inverse modeling approach using neural networks to map the nonlinear relationship between a given set of S-parameters and required filter structural parameters is presented. Given that the dimension of the S-parameters is much higher than that of the structure parameters, the corresponding neural network used in this approach is deep and complex, with multiple layers and neurons. To reduce the number of input variables, the S-parameters are subjected to wavelet transformation, allowing for more efficient representation by the neural network. The proposed method is validated using a band-pass microstrip hairpin filter as an example. Results demonstrate that the proposed approach achieves better modeling effectiveness and inverse design efficiency than conventional methods. In addition, the proposed method allows for fast customization of device parameters, such as center frequencies and bandwidths with good prediction accuracy. © 1982-2012 IEEE.

关键词： Inverse problems

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Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

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Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Benxue Lu Kaizhou Gao Peiyong Duan Adam Slowik School of Computer Science Liaocheng UniversityLiaocheng 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Information and Automation Engineering Qilu University of TechnologyJinan 250353China Department of Electronics and Computer Science Koszalin University of TechnologyKoszalin 75-453Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy ***,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical ***,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_***,fourteen local search operators are employed to search for better *** different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration ***,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different *** experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned *** study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.

关键词： hybrid flow shop scheduling Q-learning lot streaming local search

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Residual diverse ensemble for long-tailed multi-label text classification

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science China(information sciences) 2024年第11期67卷 92-105页

作者： Jiangxin SHI Tong WEI Yufeng LI National Key Laboratory for Novel Software Technology Nanjing University School of Artificial Intelligence Nanjing University School of Computer Science and Engineering Southeast University Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of Education

Long-tailed multi-label text classification aims to identify a subset of relevant labels from a large candidate label set, where the training datasets usually follow long-tailed label distributions. Many of the previous studies have treated head and tail labels equally, resulting in unsatisfactory performance for identifying tail labels. To address this issue, this paper proposes a novel learning method that combines arbitrary models with two steps. The first step is the “diverse ensemble” that encourages diverse predictions among multiple shallow classifiers, particularly on tail labels, and can improve the generalization of tail *** second is the “error correction” that takes advantage of accurate predictions on head labels by the base model and approximates its residual errors for tail labels. Thus, it enables the “diverse ensemble” to focus on optimizing the tail label performance. This overall procedure is called residual diverse ensemble(RDE). RDE is implemented via a single-hidden-layer perceptron and can be used for scaling up to hundreds of thousands of labels. We empirically show that RDE consistently improves many existing models with considerable performance gains on benchmark datasets, especially with respect to the propensity-scored evaluation ***, RDE converges in less than 30 training epochs without increasing the computational overhead.

关键词： multi-label learning extreme multi-label learning long-tailed distribution multi-label text classification ensemble learning

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Adaptive Dead Zone Compensation Control Method for Electro-Hydrostatic Actuators Under Low-Speed Conditions

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Chinese Journal of Mechanical engineering 2024年第6期37卷 199-211页

作者： Haoyi Jiang Zhenfei Ling Fengqi Zhou Maowen Sun Hao Liu Lilin Xu Yeming Yao Xiaoping Ouyang Huayong Yang State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing Engineering Institute of Aircraft SystemNanjing 210000China

This study proposes an accurate dead zone compensation control method for electro-hydrostatic actuators(EHAs)under low-speed ***,the nonlinear dead zone characteristics under low-speed conditions are summarized based on numerous EHA *** adaptive compensation function(ACF)is then constructed for the dead ***,this study proposes an adaptive dead zone compensation control method for EHAs by integrating the ACF with a virtual decomposition controller(VDC)based on the established EHA *** stability of the proposed control method is also ***,the proposed control method is verified using an EHA *** test results show that the dead zone trajectory tracking errors of EHAs are significantly reduced when combined with the ***,since most EHAs are controlled by adjusting the motor speed,the method presented in this study is simpler and easier to use than methods that employ flow compensation.

关键词： Electro-hydrostatic actuator Dead zone Compensation Control Low-speed

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Sensitivity-Enhanced Hot-Wire Anemometer by Using Cladding-Etched Fiber Bragg Grating

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Photonic Sensors 2023年第3期13卷 1-7页

作者： Yuhan TANG Xuke CHEN Jiarui ZHANG Dajuan LV Liangming XIONG Xinyong DONG School of Physics and Optoelectronic Engineering Guangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangzhou 510006China Institute of Optoelectronic Technology China Jiliang UniversityHangzhou 310018China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Wuhan 430073China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai 519000China

A sensitivity-enhanced hot-wire anemometer based on a cladding-etched optical fiber Bragg grating(FBG)coated with a layer of silver film and optically heated by using a 1480nm laser diode is *** silver film absorbs the laser power to heat the FBG to a certain high temperature and the airflow cools down the FBG hot-wire with the cooling effect and hence the Bragg wavelength of the FBG is determined by the airflow *** measurement results show that the heating efficiency of the FBG hot wire is improved by 3.8times in magnitude by etching the fiber cladding from 125μm down to 73.4μm,and the achieved airflow velocity sensitivities,under a laser power of 200mW,are–3180pm/(m/s),–889pm/(m/s),–268pm/(m/s),and–8.7pm/(m/s)at different airflow velocities of 0.1m/s,0.5m/s,1.5m/s,and 17m/s,*** comparison,the sensitivities are only–2193 pm/(m/s),–567 pm/(m/s),–161 pm/(m/s),and–4.9pm/(m/s)for the reference anemometer without cladding etching even at a much higher heating laser power of *** results prove that the method by using a cladding-etched FBG to improve sensitivity of FBG-based hot-wire anemometers works and the sensitivity is improved significantly.

关键词： Fiber Bragg grating hot-wire anemometer optical fiber sensors

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