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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wei, Xiaobo Li, Peng Huang, Weiyi Liu, Zhiyuan Liu, Qin Wuhan University of Science and Technology School of Computer Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China Wuhan University School of Cyber Science and Engineering China

ISBN: (纸本)9798350331684

Ridesharing benefits the economy and the environment. In multi-hop ridesharing, passengers are permitted to switch vehicles within a single trip, extending the flexibility of conventional ridesharing. Nonetheless, vehicle dispatch is a difficult issue in multi-hop ridesharing. We subdivide the vehicle dispatching problem into the vehicle pairing problem and the request selection problem within a vehicle pair. To address these subproblems, we propose a two-stage framework for vehicle pair dispatching. In the initial stage, we model the vehicle pairing problem as a maximum vehicle-vehicle matching problem in a general graph, which differs from the conventional vehicle-request matching problem in a bipartite graph. The vehicle pairing algorithm is proposed to efficiently solve the vehicle pairing problem. In the second stage, we model the request selection problem as a multidimensional knapsack problem (d-KP) and propose an LP-relaxation request selection algorithm with an approximation ratio 1/5. Experiments conducted on a real-world dataset demonstrate the economic benefit of our proposed two-stage framework. © 2023 IEEE.

关键词： Vehicles

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A Dense Retrieval system and Evaluation Dataset for Scientific Computational Notebooks 19

A Dense Retrieval System and Evaluation Dataset for Scientif...

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19th IEEE International Conference on e-science, e-science 2023

作者： Li, Na Zhang, Yangjun Zhao, Zhiming Multiscale Networked System Informatics Institute University of Amsterdam Netherlands School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Amsterdam Netherlands

ISBN: (纸本)9798350322231

The discovery and reutilization of scientific codes are crucial in many research activities. Computational notebooks have emerged as a particularly effective medium for sharing and reusing scientific codes. Nevertheless, effectively locating relevant computational notebooks is a significant challenge. First, computational notebooks encompass multi-modal data comprising unstructured text, source code, and other media, posing complexities in representing such data for retrieval purposes. Second, the absence of evaluation datasets for the computational notebook search task hampers fair performance assessments within the research community. Prior studies have either treated computational notebook search as a code-snippet search problem or focused solely on content-based approaches for searching computational notebooks. To address the aforementioned difficulties, we present DeCNR, tackling the information needs of researchers in seeking computational notebooks. Our approach leverages a fused sparse-dense retrieval model to represent computational notebooks effectively. Additionally, we construct an evaluation dataset including actual scientific queries, computational notebooks, and relevance judgments for fair and objective performance assessment. Experimental results demonstrate that the proposed method surpasses baseline approaches in terms of F1@5 and NDCG@5. The proposed system has been implemented as a web service shipped with REST APIs, allowing seamless integration with other applications and web services. © 2023 IEEE.

关键词： Web services

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Mapping Quantum Circuits to 2-Dimensional Quantum Architectures

Mapping Quantum Circuits to 2-Dimensional Quantum Architectu...

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2022 Informatik in den Naturwissenschaften, INFORMATIK 2022 - 2022 computer science in the Natural sciences, INFORMATIK 2022

作者： Datta, Kamalika Kole, Abhoy Sengupta, Indranil Drechsler, Rolf Cyber Physical System Bremen Germany JIS University Department of Computer Science and Engineering Kolkata India Indian Institute of Technology Kharagpur Department of Computer Science and Engineering India University of Bremen Group of Computer Architecture Bremen Germany

ISBN: (纸本)9783885797203

We have been witnessing a rapid growth in quantum computing research over the years, with the emergence of demonstrable quantum computers of moderate size. The major issues that are faced to run a quantum algorithm reliably on these systems are: (i) lower qubit coherence period, (ii) noisy primitive gate operations, (iii) limited number of available physical qubits, and (iv) support of restricted set of 2-qubit operations. Overcoming these issues mandates physical resources that exceeds the capabilities of these noisy intermediate scale quantum (NISQ) systems. On the other hand, computation using bare qubits get further disturbed due to the inclusion of additional gates to mitigate the nearest neighbor constraints. In the present work, the 2-dimensional square, heavy-hex and fully hexagonal qubit coupling lattices are considered for mapping quantum circuits. The benefits are assessed in terms of minimal additional gates needed to satisfy the nearest neighbor (NN) constraint and the compilation complexity of mapping circuits on these architectures. From the experiments by mapping benchmark circuits on 16-qubit square and 65-qubit heavy-hex architectures from IBM as well as on a 64-qubit fully hexagonal architecture, it is observed that none of the square or heavy-hex lattice architecture provides uniform compilation advantage compared to the fully hexagonal architecture. It is expected that beyond the NISQ era, strongly connected lattices like hexagonal will become practically feasible. © 2022 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Qubits

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Discriminative feature encoding for intrinsic image decomposition

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Computational Visual Media 2023年第3期9卷 597-618页

作者： Zongji Wang Yunfei Liu Feng Lu Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100190China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peng Cheng Laboratory Shenzhen 518000China

Intrinsic image decomposition is an important and long-standing computer vision *** an input image,recovering the physical scene properties is *** physically motivated priors have been used to restrict the solution space of the optimization problem for intrinsic image *** work takes advantage of deep learning,and shows that it can solve this challenging computer vision problem with high *** focus lies in the feature encoding phase to extract discriminative features for different intrinsic layers from an input *** achieve this goal,we explore the distinctive characteristics of different intrinsic components in the high-dimensional feature embedding *** define feature distribution divergence to efficiently separate the feature vectors of different intrinsic *** feature distributions are also constrained to fit the real ones through a feature distribution *** addition,a data refinement approach is provided to remove data inconsistency from the Sintel dataset,making it more suitable for intrinsic image *** method is also extended to intrinsic video decomposition based on pixel-wise correspondences between adjacent *** results indicate that our proposed network structure can outperform the existing state-of-the-art.

关键词： intrinsic image decomposition deep learning feature distribution data refinement

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Energy Aware Secure Cyber-Physical systems with Clustered Wireless Sensor Networks

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computers, Materials & Continua 2022年第9期72卷 5499-5513页

作者： Masoud Alajmi Mohamed K.Nour Siwar Ben Haj Hassine Mimouna Abdullah Alkhonaini Manar Ahmed Hamza Ishfaq Yaseen Abu Sarwar Zamani Mohammed Rizwanullah Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Recently,cyber physical system(CPS)has gained significant attention which mainly depends upon an effective collaboration with computation and physical *** greatly interrelated and united characteristics of CPS resulting in the development of cyber physical energy systems(CPES).At the same time,the rising ubiquity of wireless sensor networks(WSN)in several application areas makes it a vital part of the design of *** security and energy efficiency are the major challenging issues in CPES,this study offers an energy aware secure cyber physical systems with clustered wireless sensor networks using metaheuristic algorithms(EASCPSMA).The presented EASCPS-MA technique intends to attain lower energy utilization via clustering and security using intrusion *** EASCPSMA technique encompasses two main stages namely improved fruit fly optimization algorithm(IFFOA)based clustering and optimal deep stacked autoencoder(OSAE)based intrusion ***,the optimal selection of stacked autoencoder(SAE)parameters takes place using root mean square propagation(RMSProp)*** extensive performance validation of the EASCPS-MA technique takes place and the results are inspected under varying *** simulation results reported the improved effectiveness of the EASCPS-MA technique over other recent approaches interms of several measures.

关键词： Intrusion detection system metaheuristics stacked autoencoder deep learning cyber physical energy systems clustering wsn

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A Coarse to Fine Detection Method for Prohibited Object in X-ray Images Based on Progressive Transformer Decoder 24

A Coarse to Fine Detection Method for Prohibited Object in X...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Ma, Chunjie Du, Lina Gao, Zan Zhuo, Li Wang, Meng Shandong Jinan China School of Computer Science and Technology Shandong Jianzhu University Shandong Jinan China Faculty of Information Technology Beijing University Of Technology Beijing China School of Computer Science and Information Engineering Hefei University of Technology Anhui Hefei China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798400706868

Currently, Transformer-based prohibited object detection methods in X-ray images appear constantly, but there are still some shortcomings such as poor performance and high computational complexity for prohibited object detection with heavily occlusion. Therefore, a coarse to fine detection method for prohibited object in X-ray images based on progressive Transformer decoder is proposed in this paper. Firstly, a coarse to fine framework is proposed, which includes two stages: coarse detection and fine detection. Through adaptive inference in stages, the computational efficiency of the model is effectively improved. Then, a position and class object queries method is proposed, which improves the convergence speed and detection accuracy of the model by fusing the position and class information of prohibited object with object queries. Finally, a progressive Transformer decoder is proposed, which distinguishes high and low score queries by decreasing confidence thresholds, so that high-score queries are not affected by low-score queries in the decoding stage, and the model can focus more on decoding low-score queries, which usually correspond to prohibited object with severe occlusion. The experimental results on three public benchmark datasets (SIXray, OPIXray, HiXray) demonstrate that compared with the baseline DETR, the proposed method achieves the state-of-the-art detection accuracy with a 21.6% reduction in model computational complexity. Especially for prohibited objects with heavily occlusion, accurate detection can be carried out. © 2024 ACM.

关键词： Decoding

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Predictive Modeling of Child Identity Risk using Machine and Deep Learning: A systematic Literature Review

Predictive Modeling of Child Identity Risk using Machine and...

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Advances in Computation, Communication and Information Technology (ICAICCIT), International Conference on

作者： Akshada Dighe Bindu Garg Department of Computer Engineering BVDUCOE Pune India Department of Computer Science and Business System BVDUCOE Pune India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

Intellectual disability (ID), a developmental condition often stemming from prenatal or postnatal factors, exerts a profound influence on individuals’ lives and necessitates timely intervention. Conventional screening methods are resource-intensive and demand specialized medical expertise. This study introduces a novel, non-invasive approach to ID screening by meticulously analyzing facial features and vocal characteristics extracted from interview *** the extraction of facial measurements and speech patterns, we devised a Craniofacial Variability Index (CVI) to assess the likelihood of ID. Furthermore, advanced machine learning techniques were strategically employed to augment the predictive accuracy of this index. Our empirical findings unequivocally demonstrate promising results, with an accuracy rate reaching up to 80% when synergizing CVI scores and phonetic features. This research underscores the potential of a non-invasive, AI-powered screening instrument for ID, offering a more accessible and efficient alternative to prevailing practices. Future investigations will concentrate on refining the model and validating its efficacy across diverse populations.

关键词： Accuracy Refining Predictive models Phonetics Feature extraction Recording Indexes Reliability Facial features systematic literature review

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Comprehensive Analysis of Electronic Health Records: Introducing SWASTHA - A Novel Model

Comprehensive Analysis of Electronic Health Records: Introdu...

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Sustainable Computing and Smart systems (ICSCSS), International Conference on

作者： Kavita Moholkar Ayan Sayyad Shrinivas Mogle Satish Prasad Prashant Raut Sneha Jayabhaye Computer Science and Business System JSPM's Rajarshi Shahu College of Engineering Pune

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

This research study presents a comprehensive evaluation of the healthcare landscape in India and proposes a unique Electronic Health Record (EHR) model customized to the current state of healthcare delivery, technology infrastructure, and government initiatives in the country. The proposed EHR model aims to enhance access to healthcare services, improve care coordination among providers, promote patient engagement, and support decision-making through clinical text summarization and data visualization. Additionally, the model provides a robust framework for the efficient and secure management of health information. The study highlights the potential of the EHR system to transform health care delivery in India by streamlining processes and improving overall patient outcomes.

关键词： Electric potential Government Decision making Text summarization Data visualization Medical services Transforms

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, engineering, science, and Technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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Integrating GPS and GSM Technologies for Enhanced Women's Safety: A Fingerprint-Activated Device Approach

Integrating GPS and GSM Technologies for Enhanced Women's Sa...

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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Singh, Kamred Udham Chaudhary, Varun Sharma, Pradeep Kumar Kumar, Pushpendra Varshney, Neeraj Singh, Teekam Graphic Era Hill University School of Computing Dehradun India Ims Engineering College Ghaziabad India Hcl Technologies UP Noida India Scanno System Greater Noida India Gla University Department of Computer Engineering & Applications UP Mathura India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350382723

The creation of a safety system that is based on GPS and is developed exclusively for the health and safety of women via the incorporation of novel elements in order to meet the rising concerns about crimes committed against women. The gadget is capable of contacting authorities, conveying the user's position via SMS, and generating a loud noise to attract attention. It may be triggered in anticipation of potential danger and can be activated in the event that danger is imminent. In order to guarantee that only authorized users are able to activate the device, the system makes use of fingerprint recognition in a very unique way. Using technologies such as global positioning system (GPS), global system for mobile communications (GSM), and microcontrollers, this study makes a contribution to the continuing efforts to improve the safety of women via technological innovation. It provides a proactive approach to prevent violence against women and save lives. The research emphasizes the significance of combining hardware and software in order to provide a complete safety tool. It also illustrates the vital role that quick support plays and the potential of such gadgets to promote confidence among women in public places. © 2024 IEEE.

关键词： Microcontrollers

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