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E-commerce Scheme Based on Proxy t-out-of-n Oblivious Signature

International Journal of Network Security 2024年第5期26卷 851-860页

作者： Chen, Jingyu Gong, Linming Ma, Xiangxiang Wang, Daoshun The Shaanxi Key Laboratory of Clothing Intelligence School of Computer Science Xi’an Polytechinic University Xi’an710048 China State and Local Joint Engineering Research Center for Advanced Networking and Intelligent Information Services School of Computer Science Xi’an Polytechnic University Shaanxi Xi’an710048 China Department of Computer Science and Technology Tsinghua University Beijing100084 China No. 58 Shan-gu Road Lintong Xi’an710600 China

With the development of the internet and the demand for online shopping, intelligent online shopping systems have received widespread attention in recent years. However, existing online shopping systems’ security and privacy issues have not been well addressed. This article proposes a shopping scheme based on proxy t-out-of-n oblivious signatures, which uses t-out-of-n oblivious signature technology to ensure that users select multiple messages from a predetermined set of messages, ensuring the legality and privacy of the selection while using proxy signature technology to provide the attribute of signature unforgeability. We have analyzed the correctness of the proposed scheme and demonstrated its security in terms of integrity, unforgeability, confidentiality of selected messages, selection restriction, non-repetitive, verifiability, distinguishability, non-repudiation, and prevention of abuse. Our scheme has lower computational and communication costs than other oblivious signature schemes. In addition, the privacy-preserving multi-choice shopping scheme we propose enables users to shop more securely and conveniently. © (2024), (International Journal of Network Security). All rights reserved.

关键词： Differential privacy

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A Dual-Core Dual-Mode Class-F VCO With Wide Frequency Tuning Range Using Wide Inductance-Switching-Range Inductor

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 460-463页

作者： Hou, Yaru Li, Runlong Chi, Pei-Ling Yang, Tao University of electronic Science and Technology of China Chengdu610036 China Sichuan Province Engineering Research Center for Broadband Microwave Circuit High Density Integration Chengdu610036 China University of Electronic Science and Technology of China School of Electronic Science and Engineering Sichuan Chengdu610054 China National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel dual-core dual-mode class-F voltage-controlled oscillator (VCO) with wide frequency tuning range (TR) is proposed in this letter. It consists of two coupled parallel "8"-shaped inductor and two crossed-coupled VCO cores. To increase the TR of the proposed VCO without adding additional footprint size, a single-turn common-mode inductor is embedded inside the "8"-shaped inductor. By controlling the mode switches, the inductor can work in different modes with large inductance difference, realizing large VCO TR consequently. Then, the two coupled inductors were engineered to form the fundamental and third harmonic resonances, respectively, thereby producing a pseudo-square wave output waveform and realizing class-F operation. With the proposed configuration, the phase noise (PN) of the proposed VCO can be significantly reduced without increasing VCO core size. To demonstrate the proposed idea, a VCO prototype is fabricated in a 65-nm CMOS process with a core size of 1.235×0.8mm. It achieves a wide frequency TR from 2.84 to 7.04 GHz. The measured PN at 1-MHz offset is from -123.9 to -113.1 dBc/Hz, demonstrating an FOMT of 196.0-201.3 dBc/Hz. © 2023 IEEE.

关键词： Variable frequency oscillators

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Applying CNN Models with Stereo Camera for Object Detection and Distance Estimation in Automatic Micro Electric Vehicle (MEVi) 1

Applying CNN Models with Stereo Camera for Object Detection ...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Harimanto, Farrell Putra Hasanah, Nurul Pradana, Muhammad Khristamto Aditya Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia National Research and Innovation Agency Kst Samaun Samadikun Research Center for Smart Mechatronics Bandung40135 Indonesia

ISBN: (纸本)9798350368918

Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%. © 2024 IEEE.

关键词： Automotive industry

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Accelerating Medical Visual Question Answering by Image Rearrangement 21

Accelerating Medical Visual Question Answering by Image Rear...

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21st International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Han, Wang Lei, Zhao Center for Future Media The School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu610000 China Sichuan Artificial Intelligence Research Institute Yibin China

ISBN: (纸本)9798331519254

Medical Visual Question Answering is designed for supporting clinical diagnosis by leveraging advanced language and visual comprehension ability. While Large Vision-Language Models offer medical visual question answering powerful generative and interpretative capabilities, they encounter significant computational challenges due to quadratic complexity that scales with sequence length, especially as image embeddings dominate the input sequence. To address this, we propose an Image Rearrangement algorithm, which reduces the number of image embeddings with minimal impact on model performance. The Image Rearrangement algorithm aggregates similar image embeddings based on their relative alignment to text embeddings. We evaluate the Image Rearrangement algorithm method across three distinct datasets using two medical visual question answering models, observing that the Image Rearrangement algorithm achieves substantial computational savings while maintaining diagnostic accuracy. © 2024 IEEE.

关键词： Visual languages

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Question Embedding on Weighted Heterogeneous Information Network for Knowledge Tracing

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ACM Transactions on Knowledge Discovery from Data 2024年第1期19卷 1-28页

作者： Sun, Jianwen Du, Shangheng Zhou, Jianpeng Yuan, Xin Shen, Xiaoxuan Liang, Ruxia National Engineering Research Center of Educational Big Data Central China Normal University Wuhan China Faculty of Artificial Intelligence in Education Central China Normal University Wuhan China Shanghai Institute of Artificial Intelligence for Education East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China

Knowledge Tracing (KT) aims to predict students' future performance on answering questions based on their historical exercise sequences. To alleviate the problem of data sparsity in KT, recent works have introduced auxiliary information to mine question similarity, resulting in the enhancement of question embeddings. Nonetheless, there remains a gap in developing an approach that effectively incorporates various forms of auxiliary information, including relational information (e.g., question-student, question-skill relation), relationship attributes (e.g., correctness indicating a student's performance on a question), and node attributes (e.g., student ability). To tackle this challenge, the Similarity-enhanced Question Embedding (SimQE) method for KT is proposed, with its central feature being the utilization of weighted and attributed meta-paths for extracting question similarity. To capture multi-dimensional question similarity semantics by integrating multiple relations, various meta-paths are constructed for learning question embeddings separately. These embeddings, each encoding different similarity semantics, are then fused to serve the task of KT. To capture finer-grained similarity by leveraging the relationship attributes and node attributes on the meta-paths, the biased random walk algorithm is designed. In addition, the auxiliary node generation method is proposed to capture high-order question similarity. Finally, extensive experiments conducted on six datasets demonstrate that SimQE performs the best among 10 representative question embedding methods. Furthermore, SimQE proves to be more effective in alleviating the problem of data sparsity. © 2024 Copyright held by the owner/author(s).

关键词： Question answering

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PUF-Based Privacy-Preserving Simultaneous Authentication Among Multiple Vehicles in VANET

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IEEE Transactions on Vehicular Technology 2024年第5期73卷 6727-6739页

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Akram, Muhammad Wahid Hussain, Shafiq Das, Ashok Kumar Park, Youngho Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Lahore Department of Software Engineering Punjab Lahore54590 Pakistan University of Sahiwal Department of Computer Science Punjab Sahiwal57000 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Telangana Hyderabad500032 India Kyungpook National University School of Electronics Engineering Daegu41566 Korea Republic of

The intellectual and immense attainment of a smart city and auto-mobile vehicles are gradually growing. This growth drives Vehicular Ad-Hoc Network (VANET), a broadly operated complex network for inter-vehicular transmission to acquire information relevant to the vehicle location, road condition, traffic congestion, and speed. Generally, this information is procured through an open-source communication, which is susceptible to various security threats. In broad terms, the privacy of data in VANET is considered an imperative task. In this regard, many authentication protocols are formerly initiated for VANET. Most of these protocols are precarious owing to eavesdropping, replay, and impersonation attacks, etc. Furthermore, most existing protocols operates on enormous communication and computation rate, which turns them inadequate for VANET. This paper exhibits a lightweight privacy-preserving authentication protocol for n number of vehicles in VANET using the physical unclonable function (PUF) technique, and offers efficient and secure communication via public channels. Moreover, we evaluate our protocol formally and informally, showing that it is scalable, lightweight, and safe compared to formerly protocols. The rate of computation and communication is less than most related protocols. We also simulate the proposed scheme using the NS-3 simulator to measure its various network performance parameters. As a result, it is apparent through the beheld statistics that the presented protocol is beyond practical, efficient, and reliable for the secure dissemination of information in VANET. © 1967-2012 IEEE.

关键词： Vehicular ad hoc networks

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Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves

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Journal of Rock Mechanics and Geotechnical engineering 2024年第3期16卷 1018-1032页

作者： Xiao Ye Hong-Hu Zhu Gang Cheng Hua-Fu Pei Bin Shi Luca Schenato Alessandro Pasuto School of Earth Sciences and Engineering Nanjing UniversityNanjing210023China School of Computer Science North China Institute of Science and Technology(National Safety Training Center of Coal Mines)Beijing101601China State Key Lab of Coastal and Offshore Engineering Department of Geotechnical EngineeringDalian University of TechnologyDalian116024China National Research Council-Research Institute for Geo-Hydrological Protection(CNR-IRPI) Padova35127Italy Department of Information Engineering University of PadovaPadova35131Italy

Thermo-poro-mechanical responses along sliding zone/surface have been extensively ***,it has not been recognized that the potential contribution of other crucial engineering geological interfaces beyond the slip surface to progressive ***,we aim to investigate the subsurface multiphysics of reservoir landslides under two extreme hydrologic conditions(*** and dry),particularly within sliding *** on ultra-weak fiber Bragg grating(UWFBG)technology,we employ specialpurpose fiber optic sensing cables that can be implanted into boreholes as“nerves of the Earth”to collect data on soil temperature,water content,pore water pressure,and *** Xinpu landslide in the middle reach of the Three Gorges Reservoir Area in China was selected as a case study to establish a paradigm for in situ thermo-hydro-poro-mechanical *** UWFBG-based sensing cables were vertically buried in a 31 m-deep borehole at the foot of the landslide,with a resolution of 1 m except for the pressure *** reported field measurements covering the period 2021 and 2022 and produced the spatiotemporal profiles throughout the *** show that wet years are more likely to motivate landslide motions than dry *** annual thermally active layer of the landslide has a critical depth of roughly 9 m and might move downward in warmer *** dynamic groundwater table is located at depths of 9e15 m,where the peaked strain undergoes a periodical response of leap and withdrawal to annual hydrometeorological *** interface behaviors may support the interpretation of the contribution of reservoir regulation to slope stability,allowing us to correlate them to local damage events and potential global *** paper also offers a natural framework for interpreting thermo-hydro-poro-mechanical signatures from creeping reservoir bank slopes,which may form the basis for a landslide monitoring and early warning system.

关键词： Reservoir landslide Thermo-hydro-poro-mechanical response Ultra-weak fiber bragg grating(UWFBG) subsurface evolution engineering geological interface Geotechnical monitoring

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A Modified Feature Selection Algorithm for Intrusion Detection System Based on Student Psychology-Based Optimization with Explainable AI

A Modified Feature Selection Algorithm for Intrusion Detecti...

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2023 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2023

作者： Evan, Md. Raisul Islam Motiur Rahman, Mohammad Tanzir Mehedi, Sk. Nazib, Abdullah Islam, Rafiqul Rahman, Ziaur Mawlana Bhashani Science and Technology University Computer Science and Engineering Tangail1902 Bangladesh Mawlana Bhashani Science and Technology University Information and Communication Technology Tangail1902 Bangladesh School of Electrical Engineering and Robotics Queensland University of Technology BrisbaneQLD Australia School of Computing Mathematics and Engineering Charles Sturt University Bathurst Australia School of Computer Science Queensland University of Technology BrisbaneQLD Australia

ISBN: (纸本)9798350341072

Intrusion Detection Systems (IDS) play a vital role in safeguarding network security by monitoring and identifying both normal and intrusive activities. However, constructing an effective IDS from extensive datasets poses a significant challenge. The process of feature selection from these datasets is crucial, as it not only enhances accuracy but also reduces the time required to build the model. In this paper, we employ a modified version of the Student Psychology-Based Optimization (SPBO) algorithm to identify the most relevant features set for IDS. Following feature selection, various machine learning algorithms are employed for multi-level classification. To evaluate our approach, we utilize the NLS-KDD dataset. Our proposed algorithm surpasses several state-of-the-art feature selection methods in terms of accuracy, precision, recall, Fl-score, and finally faster convergence. Specif-ically, our proposed bio-inspired SPBO algorithm combined with the Random Forest (RF) algorithm achieves a comparable accuracy rate of 99.81 %. To ensure better comprehensibility, we employ two widely used Explainable Artificial Intelligence (XAI) techniques: SHapley Additive exPlanations (SHAP) and Local In-terpretable Model-Agnostic Explanations (LIME). These methods provide insightful explanations for our model's decisions, further enhancing its interpretability. © 2023 IEEE.

关键词： Feature Selection

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A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Robot System and Its Applications

A Novel Quadruple Dispensing Heads Sticking Adhesive Tape Ro...

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Suwanratchatamanee, Kitti Sawada, Hideyuki Hashimoto, Shuji Robotics Research and Development Center GOLDEN ROBOT Co. Ltd. Rayong Thailand Grad. School of Advanced Science and Engineering WASEDA University Tokyo Japan WASEDA University Tokyo Japan

ISBN: (纸本)9798331533892

Industrial robots are increasingly being used to assist and replace workers in factories to address the global labor shortage in various applications. The use of robots can provide many benefits to the effective production and manufacturing. Taping is one of the robots' applications. However, current tape robots can only tape one strip at a time, which can be time-consuming in practice if multiple strips of tape are required at the same time for special workpieces. This paper presents a novel sticking adhesive tape robot system. As the object to be taped are four-line hot pipes to be attached on the outer shell of refrigerator, thus four strips of tape are required at the same time before assembly process. The proposed robot system contains the novel tooling called 'Quadruple Dispensing Heads'. This tooling was developed to tape four strips of tape to be applied simultaneously. This tooling can adjust the gap of tape strips from 80mm to 110mm. Moreover, the research objective is to produce a robot system that can apply tape with higher quality and faster than human workers, so that human workers can move on to more complicated tasks instead of performing repetitive, routine tasks that do not require such special skills and knowledge. As the result, our proposed system can achieve the four lines of *** length, through IS7N pushing force (when operate the air working pressure at ***) sticking taping task perfectly with 100% success rate of experiments in just 3 seconds and faster than human worker significantly. Since, human worker needs about 3 seconds per each I.5m taping line. Therefore, human needs approximately 12 seconds in total for four lines. Accordingly, our proposed robot system is faster than human worker in four times. © 2025 IEEE.

关键词： Industrial robots

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Quantum Algorithms and Lower Bounds for Finite-Sum Optimization 41

Quantum Algorithms and Lower Bounds for Finite-Sum Optimizat...

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41st International Conference on Machine Learning, ICML 2024

作者： Zhang, Yexin Zhang, Chenyi Fang, Cong Wang, Liwei Li, Tongyang School of Electronics Engineering and Computer Science Peking University China Computer Science Department Stanford University United States National Key Lab of General Artificial Intelligence School of Intelligence Science and Technology Peking University China Institute for Artificial Intelligence Peking University China Center on Frontiers of Computing Studies Peking University China School of Computer Science Peking University China

Finite-sum optimization has wide applications in machine learning, covering important problems such as support vector machines, regression, *** this paper, we initiate the study of solving finite-sum optimization problems by quantum ***, let f1, ..., fn : d → be -smooth convex functions and ψ: d → be a µ-strongly convex proximal *** goal is to find an ϵ-optimal point for F(x) = n1 Pni=1 fi(x) + ψ(x).We give a quantum algorithm with complexity Õ(Equation presented) 1 improving the classical tight bound (Equation presented).We also prove a quantum lower bound Ω˜(n + n3/4(/µ)1/4) when d is large *** our quantum upper and lower bounds can extend to the cases where ψ is not necessarily strongly convex, or each fi is Lipschitz but not necessarily *** addition, when F is nonconvex, our quantum algorithm can find_an ϵ-critial point using (Equation presented) queries. Copyright 2024 by the author(s)

关键词： Quantum computers

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