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arXiv 2024年

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2024, CC BY.

关键词： Bamboo

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Neural Signal Compression System with Spike Detection Using Compressed Sensing

Neural Signal Compression System with Spike Detection Using ...

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2023 Cross Strait Radio science and Wireless Technology Conference, CSRSWTC 2023

作者： Zheng, Ruihan Xia, Yu Li, Dongming Wang, Liyang Li, Hung Chun Mak, Peng Un Vai, Mang I. Pun, Sio Hang State Key Laboratory of Analog and Mixed-Signal VLSL University of Macau Macau China Institution of Microelectronics University of Macau Macau China Jt. Lab. of Zhuhai UM Sci. and Technol. Research Institution - Lingyange Semiconductor Incorporated Zhuhai China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering Macau China

ISBN: (纸本)9798350358971

This article aims to demonstrate a signal compression method for the wireless invasive neural recording system. A compression system with spike detection for neural signals is proposed. The input signal is firstly detected in the spike detection part and then the intercepted spike segments are sent to the compression part. A compressed sensing technique is applied in the compression part, and the Minimum Euclidean or Manhattan Distance Cluster-based (MDC) matrix is adopted for compressing neural spike segments. During simulation, the compression rate can surpass 99% and the signal-to-noise distortion ratio is around 37 dB. Moreover, the proposed method is also contrasted with the direct compression of input neural signals. When the input neural signal is directly compressed, the compression ratio is 98%, and the signal-to-noise ratio distortion rate is about 28 dB. By employing spike detection and utilizing this MDC matrix, it becomes possible to compress non-sparse spike segments in the time domain, resulting in a higher compression rate and improved reconstruction performance. © 2023 IEEE.

关键词： compressed sensing neural signal compression spike detection

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BENCHMARKING COMMUNITY DRUG RESPONSE PREDICTION MODELS: DATASETS, MODELS, TOOLS, AND METRICS FOR CROSS-DATASET GENERALIZATION ANALYSIS

arXiv

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arXiv 2025年

作者： Partin, Alexander Vasanthakumari, Priyanka Narykov, Oleksandr Wilke, Andreas Koussa, Natasha Jones, Sara E. Zhu, Yitan Overbeek, Jamie C. Jain, Rajeev Fernando, Gayara Demini Sanchez-Villalobos, Cesar Garcia-Cardona, Cristina Mohd-Yusof, Jamaludin Chia, Nicholas Wozniak, Justin M. Ghosh, Souparno Pal, Ranadip Brettin, Thomas S. Weil, M. Ryan Stevens, Rick L. Division of Data Science and Learning Argonne National Laboratory LemontIL United States Frederick National Laboratory for Cancer Research Cancer Data Science Initiatives Cancer Research Technology Program FrederickMD United States Department of Statistics University of Nebraska–Lincoln LincolnNE United States Department of Electrical & Computer Engineering Texas Tech University LubbockTX United States Division of Computer Computational and Statistical Sciences Los Alamos National Laboratory Los AlamosNM United States Department of Computer Science The University of Chicago ChicagoIL United States

Deep learning (DL) and machine learning (ML) models have shown promise in drug response prediction (DRP), yet their ability to generalize across datasets remains an open question, raising concerns about their real-world applicability. Due to the lack of standardized benchmarking approaches, model evaluations and comparisons often rely on inconsistent datasets and evaluation criteria, making it difficult to assess true predictive capabilities. In this work, we introduce a benchmarking framework for evaluating cross-dataset prediction generalization in DRP models. Our framework incorporates five publicly available drug screening datasets, six standardized DRP models, and a scalable workflow for systematic evaluation. To assess model generalization, we introduce a set of evaluation metrics that quantify both absolute performance (e.g., predictive accuracy across datasets) and relative performance (e.g., performance drop compared to within-dataset results), enabling a more comprehensive assessment of model transferability. Our results reveal substantial performance drops when models are tested on unseen datasets, underscoring the importance of rigorous generalization assessments. While several models demonstrate relatively strong cross-dataset generalization, no single model consistently outperforms across all datasets. Furthermore, we identify CTRPv2 as the most effective source dataset for training, yielding higher generalization scores across target datasets. By sharing this standardized evaluation framework with the community, our study aims to establish a rigorous foundation for model comparison, and accelerate the development of robust DRP models for real-world applications. © 2025, CC BY.

关键词： Prediction models

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Deep-sea Nodule Mineral Image Segmentation Algorithm Based on Pix2PixHD

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computers, Materials & Continua 2022年第10期73卷 1449-1462页

作者： Wei Song Haolin Wang Xinping Zhang Jianxin Xia Tongmu Liu Yuxi Shi School of Information and Engineering Minzu University of ChinaBeijing100081China Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural ResourceGuangzhou510300China National Language Resource Monitoring&Research Center of Minority Languages Beijing100081China School of Ocean Science China University of GeosciencesBeijing100191China Department of Buoy Engineering South China Sea Marine Survey and Technology CenterGuangzhou510300China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNew Jersey07102USA

Deep-sea mineral image segmentation plays an important role in deep-sea mining and underwater mineral resource monitoring and *** application of artificial intelligence technology to deep-sea mining projects can effectively improve the quality and efficiency of *** existing deep learning-based underwater image segmentation algorithms have problems such as the accuracy rate is not high enough and the running time is slightly *** order to improve the segmentation performance of underwater mineral images,this paper uses the Pix2PixHD(Pixel to Pixel High Definition)algorithm based on Conditional Generative Adversarial Network(CGAN)to segment deep-sea mineral *** model uses a coarse-to-fine generator composed of a global generation network and two local enhancement networks,and multiple multi-scale discriminators with same network structures but different input pictures to generate highquality *** test results on the deep-sea mineral datasets show that the Pix2PixHD algorithm can identify more target minerals under certain other *** evaluation index shows that the Pix2PixHD algorithm effectively improves the accuracy rate and the recall rate of deep-sea mineral image segmentation compared with the CGAN algorithm and the U-Net *** is important for expanding the application of deep learning techniques in the field of deep-sea exploration and mining.

关键词： Deep-sea mineral image segmentation generative adversarial network

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Distributed time-varying formation control with uncertainties based on an event-triggered mechanism

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science China(Information sciences) 2021年第3期64卷 167-176页

作者： Xiaoduo LI Yumeng BAI Xiwang DONG Qingdong LI Zhang REN Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical EngineeringBeihang University Department of Electrical and Computer Engineering University of Wisconsin-Madison Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

This paper investigates the distributed time-varying formation(TVF) problems for general linear multi-agent systems(MASs) subject to matched bounded uncertainties based on an adaptive event-triggered mechanism. A TVF protocol was designed with an event-triggered mechanism by introducing adaptive weights into the formation control protocol and triggering condition, and the large chattering phenomenon was avoided by the σ-modification adaptive law. According to the Lyapunov stability theory, proof has been established that the MASs in the presence of uncertainties can realize the expected formation that satisfies the given feasible condition. Finally, an example is provided to verify the effectiveness of the proposed algorithm.

关键词： formation control multi-agent systems event-triggered adaptive control

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Sitting Posture Recognition Using a Spiking Neural Network

arXiv

引用

arXiv 2022年

作者： Wang, Jianquan Hafidh, Basim Dong, Haiwei Saddik, Abdulmotaleb El The Multimedia Computing Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada

To increase the quality of citizens’ lives, we designed a personalized smart chair system to recognize sitting behaviors. The system can receive surface pressure data from the designed sensor and provide feedback for guiding the user towards proper sitting postures. We used a liquid state machine and a logistic regression classifier to construct a spiking neural network for classifying 15 sitting postures. To allow this system to read our pressure data into the spiking neurons, we designed an algorithm to encode map-like data into cosine-rank sparsity data. The experimental results consisting of 15 sitting postures from 19 participants show that the prediction precision of our SNN is 88.52%. Copyright © 2022, The Authors. All rights reserved.

关键词： Neural networks

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Deception in Differential Games: Information Limiting Strategy to Induce Dilemma

arXiv

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arXiv 2024年

作者： Shishika, Daigo Moll, Alexander Von Maity, Dipankar Dorothy, Michael Department of Mechanical Engineering George Mason University FairfaxVA22030 United States Control Science Center Air Force Research Laboratory WPAFB OH45433 United States Department of Electrical and Computer Engineering University of North Carolina CharlotteNC28223 United States Army Research Directorate DEVCOM Army Research Laboratory APG MD20783 United States

Can deception exist in differential games? We provide a case study for a Turret-Attacker differential game, where two Attackers seek to score points by reaching a target region while a Turret tries to minimize the score by aligning itself with the Attackers before they reach the target. In contrast to the original problem solved with complete information, we assume that the Turret only has partial information about the maximum speed of the Attackers. We investigate whether there is any incentive for the Attackers to move slower than their maximum speed in order to "deceive" the Turret into taking suboptimal actions. We first describe the existence of a dilemma that the Turret may face. Then we derive a set of initial conditions from which the Attackers can force the Turret into a situation where it must take a guess. © 2024, CC BY.

关键词： Game theory

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Interactive Learning Through the Metaverse and its Impact on Primary Education

Interactive Learning Through the Metaverse and its Impact on...

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Cheilsi Sharma Basant Agarwal Lunchakorn Wuttisittikulkij Daksh Joshi Akshat Bhatnagar Sushank Chaudhary Pruk Sasithong Dept. of Computer Science Rajasthan University Jaipur India Department of Computer Science and Engineering Central University of Rajasthan Kishangarh India Telecommunication System Research Laboratory Chulalongkorn University Bangkok Thailand Bangkok Thailand Department of CSE Indian Institute of Information Technology Kota (IIIT Kota) Kota India Department of Electrical Engineering Chulalongkorn University Bangkok Thailand Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The rise of the Metaverse, an immersive, three-dimensional digital environment, has been gradually transforming human-computer interaction. This paper focuses on exploring the potential of the Metaverse to improve learning through interactive games. The Metaverse serves as a dynamic platform for students to collaborate, explore and engage with. It enables educators to create interactive learning environments that amalgamate both physical and virtual spaces through technologies such as virtual reality, augmented reality, and artificial intelligence. These interactive games within the Metaverse foster critical thinking and problem-solving on top of making learning enjoyable. This paper discusses the development of educational environments within the metaverse, the integration of interactive games as well as their impact on learning outcomes and student engagement. The Metaverse poses a novel route towards effective education with this gamified approach. This study highlights the potential for the Metaverse to prepare students for the challenges inherent in this digital age by transforming traditional educational methods.

关键词： Metaverse Space technology Education Mixed reality Games Learning (artificial intelligence) Telecommunications

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Learning to Estimate 3D Human Pose from Point Cloud

arXiv

引用

arXiv 2022年

作者： Zhou, Yufan Dong, Haiwei El Saddik, Abdulmotaleb The Multimedia Computing Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada

3D pose estimation is a challenging problem in computer vision. Most of the existing neural-network-based approaches address color or depth images through convolution networks (CNNs). In this paper, we study the task of 3D human pose estimation from depth images. Different from the existing CNN-based human pose estimation method, we propose a deep human pose network for 3D pose estimation by taking the point cloud data as input data to model the surface of complex human structures. We first cast the 3D human pose estimation from 2D depth images to 3D point clouds and directly predict the 3D joint position. Our experiments on two public datasets show that our approach achieves higher accuracy than previous state-of-art methods. The reported results on both ITOP and EVAL datasets demonstrate the effectiveness of our method on the targeted tasks. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

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Human Machine Interface with Wearable Electronics Using Biodegradable Triboelectric Films for Calligraphy Practice and Correction

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Nano-Micro Letters 2022年第12期14卷 630-644页

作者： Shen Shen Jia Yi Zhongda Sun Zihao Guo Tianyiyi He Liyun Ma Huimin Li Jiajia Fu Chengkuo Lee Zhong Lin Wang Jiangsu Engineering Technology Research Center for Functional Textiles Jiangnan UniversityNo.1800 Lihu AvenueWuxiP.R.China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-Nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 100083P.R.China China National Textile and Apparel Council Key Laboratory of Natural Dyes Soochow UniversitySuzhou 215123People’s Republic of China School of Material Science and Engineering Georgia Institute of TechnologyAtlantaGA 30332-0245USA

Letter handwriting,especially stroke correction,is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the *** this study,a biodegradable and conductive carboxymethyl chitosan-silk fibroin(CSF)film is prepared to design wearable triboelectric nanogenerator(denoted as CSF-TENG),which outputs of V_(oc)≈165 V,I_(sc)≈1.4μA,and Q_(sc)≈72 mW cm^(−2).Further,in vitro biodegradation of CSF film is performed through trypsin and *** results show that trypsin and lysozyme have stable and favorable biodegradation properties,removing 63.1%of CSF film after degrading for 11 ***,the CSF-TENG-based human-machine interface(HMI)is designed to promptly track writing steps and access the accuracy of letters,resulting in a straightforward communication media of human and *** CSF-TENG-based HMI can automatically recognize and correct three representative letters(F,H,and K),which is benefited by HMI system for data processing and *** CSF-TENG-based HMI can make decisions for the next stroke,highlighting the stroke in advance by replacing it with red,which can be a candidate for calligraphy practice and ***,various demonstrations are done in real-time to achieve virtual and real-world controls including writing,vehicle movements,and healthcare.

关键词： Letter handwriting Triboelectric nanogenerator Biodegradable Human-machine interface Calligraphy practice

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