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检索条件"任意字段=23rd International Conference on Computer Systems and Technologies, CompSysTech 2022"

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QuickSim: Efficient and Accurate Physical Simulation of Silicon Dangling Bond Logic

QuickSim: Efficient and Accurate Physical Simulation of Sili...

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IEEE conference on Nanotechnology

作者： Jan Drewniok Marcel Walter Samuel Sze Hang Ng Konrad Walus Robert Wille Chair for Design Automation Technical University of Munich Germany Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Software Competence Center Hagenberg GmbH Austria

Silicon Dangling Bonds have established themselves as a promising competitor in the field of beyond-CMOS technologies. Their integration density and potential for energy dissipation advantages of several orders of magnitude over conventional circuit technologies sparked the interest of academia and industry alike. While fabrication capabilities advance rapidly and first design automation methodologies have been proposed, physical simulation effectiveness has yet to keep pace. Established algorithms in this domain suffer either from exponential runtime behavior or subpar accuracy levels. In this work, we propose a novel algorithm for the physical simulation of Silicon Dangling Bond systems based on statistical methods that offers both a time-to-solution and an accuracy advantage over the state of the art by more than one order of magnitude and a factor of more than three, respectively, as demonstrated by an exhaustive experimental evaluation.

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Promising technologies and Solutions for Supporting Human Activities in Confined Spaces in Industry 23

Promising Technologies and Solutions for Supporting Human Ac...

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23rd international conference on Enterprise Information systems (ICEIS)

作者： Silva, Taynan Roger Coelho, Bruno Nazario Delabrida, Saul Emanuel Fed Univ Ouro Preto UFOP Grad Program Instrumentat Control & Automat Min P Ouro Preto Brazil Vale Inst Technol ITV Ouro Preto Brazil Fed Univ Ouro Preto UFOP Control & Automat Engn Dept DECAT Ouro Preto Brazil Fed Univ Ouro Preto UFOP Dept Comp DECOM Ouro Preto Brazil

ISBN: (纸本)9789897585098

Although there is a growing concern about accidents and illnesses at work, global statistics still reveal alarming data. It is estimated that 2.78 million people die each year worldwide due to labor factors. In this regard, information systems and automation systems applied to occupational health and safety are gaining prominence for accident prevention. One of the high risk activities that have adopted technology as an ally is working in confined spaces. Currently, non-human entry robotic systems have been widely adopted for this purpose. However, these solutions do not always cover all scenarios, still requiring humans to perform tasks in those locations. Thus, it is expected that the new era of work in confined environments will be increasingly guided by hybrid systems of human-computer interaction. Some solutions from this perspective foresee the use of wearable computing, virtual reality and augmented reality to assist at these locations. The challenges in adopting these new technologies still consist in the characteristics of the environments themselves, which are hostile places with natural blockages for traditional communication and data transmission signals.

关键词： Confined Spaces Occupational Health and Safety Human-computer Interaction

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A Step Toward Semantic Content Negotiation 23

A Step Toward Semantic Content Negotiation

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23rd international conference on Knowledge Engineering and Knowledge Management, EKAW-C 2022

作者： Taghzouti, Yousouf Vachtsevanou, Danai Mayer, Simon Ciortea, Andrei Mines Saint-Etienne Univ Clermont Auvergne INP Clermont Auvergne CNRS UMR 6158 LIMOS Saint-EtienneF - 42023 France Institute of Computer Science University of St. Gallen Rosenbergstrasse 30 St. Gallen9000 Switzerland

Content negotiation aims at enabling a server to provide a client with a representation of a resource that meets its needs. However, client and server might desire to negotiate constraints that go beyond the media type or language of the alternative representation. This is especially true in the Semantic Web, as a resource can be described with a single media type, but with different vocabularies (FOAF, ***, etc.), and may match specific patterns. In this paper, we propose an approach to increase the flexibility when negotiating a representation between client and server. Our approach follows the goals of the World Wide Web and uses a set of existing technologies: SHACL and profile-based negotiation. We define the mechanism (in terms of protocol and algorithm) for clients to announce their expectations and for servers to react and respond to them. We then explain, through a use case, how the same approach could be used in Web-based Multi-Agent systems to help autonomous agents achieve their goals on the Web. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0)

关键词： Multi agent systems

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DNN and LS Based Channel Estimation in OTFS System 23

DNN and LS Based Channel Estimation in OTFS System

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23rd IEEE international conference on Communication Technology, ICCT 2023

作者： Hu, Jiacheng Bai, Zhiquan Yang, Jikai Cai, Yueying Zhou, Di Wang, Yingxun Kwak, KyungSup School of Information Science and Engineering Shandong University Shandong Provincial Key Lab. of Wireless Communication Technologies Shandong Qingdao China School of Computer and Information Engineering Qilu Institute of Technology China Graduate School of Information Technology and Telecommunications Inha University Incheon Korea Republic of

ISBN: (纸本)9798350325959

Orthogonal time frequency space (OTFS) system transmits information in the delay-Doppler domain, and it adapts well to high-speed mobile environments and can realize channel estimation with less overhead. Channel estimation in the OTFS system is necessary for subsequent channel equalization and information recovery process, aiming to eliminate the effects, such as inter-symbol interference (ISI) and noise influence. The paper proposes an effective channel estimation for the OTFS system using deep neural network (DNN) and the least square (LS) algorithm, considering the accurate and low latency channel estimation requirement in the Internet of Vehicles, where LS algorithm is first used to perform a rough time-frequency domain channel estimation, and then the DNN model is taken to optimize the rough channel estimation. Simulation results show that the proposed method achieves more accurate channel estimation performance with low complexity and better flexibility, compared with the typical LS and linear minimum mean square error (LMMSE) scheme. © 2023 IEEE.

关键词： channel estimation deep neural network (DNN) least square (LS) orthogonal time frequency space (OTFS)

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23rd international conference on Web Information systems Engineering, WISE 2021

23rd International Conference on Web Information Systems Eng...

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23rd international conference on Web Information systems Engineering, WISE 2021

ISBN: (纸本)9783031208904

The proceedings contain 47 papers. The special focus in this conference is on Web Information systems Engineering. The topics include: Explaining Unexpected Answers of SPARQL Queries;bitcoin Transaction Confirmation Time Prediction: A Classification View;offworker: An Offloading Framework for Parallel Web Applications;high-Performance Transaction Processing for Web Applications Using Column-Level Locking;sGrid++: Revising Simple Grid Based Density Estimator for Mining Outlying Aspect;LinGBM: A Performance Benchmark for Approaches to Build GraphQL Servers;a Service-Based Framework for Adaptive Data Curation in Data Lakehouses;retrofitting Industrial Machines with WebAssembly on the Edge;attention-Based Relation Prediction of Knowledge Graph by Incorporating Graph and Context Features;a Domain-Independent Method for Thematic Dataset Building from Social Media: The Case of Tourism on Twitter;rumor Detection in Social Network via Influence Based on Bi-directional Graph Convolutional Network;efficient Truss Computation for Large Hypergraphs;identifying Privacy Risks Raised by Utility Queries;an Empirical Assessment of Security and Privacy Risks of Web-Based Chatbots;an Information-Driven Genetic Algorithm for Privacy-Preserving Data Publishing;enhanced Topic Representation by Ambiguity Handling;enhancing Seq2seq Math Word Problem Solver with Entity Information and Math Knowledge;mitigating Multi-class Unintended Demographic Bias in Text Classification with Adversarial Learning;debias the Black-Box: A Fair Ranking Framework via Knowledge Distillation;incorporating News Summaries for Stock Predictions via Graphical Learning;domain Adversarial Training for Aspect-Based Sentiment Analysis;bootstrapping Joint Entity and Relation Extraction with Reinforcement Learning;EEML: Ensemble Embedded Meta-Learning;click is Not Equal to Purchase: Multi-task Reinforcement Learning for Multi-behavior Recommendation;multi-document Question Answering Powered by External Knowledge;a Learning

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23rd international conference on Information technologies and Mathematical Modelling, ITMM 2024

23rd International Conference on Information Technologies an...

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23rd international conference on Information technologies and Mathematical Modelling, ITMM 2024

ISBN: (纸本)9783031883064

The proceedings contain 26 papers. The special focus in this conference is on Information technologies and Mathematical Modelling. The topics include: A Power-Law Adjustable Coefficient Dynamic Pricing Model Considering Shortages and Leftovers;inferences of Modularity for Graphs Evolved by the Clustering Attachment Model;queueing Model with Correlated Arrival Process, Simultaneous Service of a Finite Number of Customers, and Pre-processing, Post-processing and Co-processing of Customers;reliability Analysis of a k-out-of-n System with External Service and Non-preemptive Priority Under N-Policy with Multiple Server Vacations;On Recursive Marginal and MAP Inference in State Observation Models;asymptotic Analysis of Sojourn Time in Retrial Queueing System with Non-persistent Customers and Feedback;implementation of a Convolution Algorithm to the Evaluation of Stationary Characteristics of Resource Loss System with Resource-Dependent Service Times;Diffusion Approximation for the MAP/GI/1 Retrial Queue with Two-Way Communication;investigation of M/G/1//N System with Impatient Customers, Unreliable Primary and a Backup Server;g-Network with Rewards as a Cluster System Model;on Application of Karamata Slowly Varying Functions in the Theory of Noncritical Markov Branching systems;asymptotic Analysis of a Multiserver Retrial Queue with Disasters;analysis of a Batch Arrival Queue with Power Saving Mode;lumping and Numerical Analysis for Multi-Server Job Model;unloading Time Martingale Relations in a Cyclic Queueing System in Random Environment;on Estimation of Some Functional of the Distribution Function for Dependent Incomplete Observations in Queuing Theory;analysis of a Queueing System Providing Service to Regular and Ad Hoc Clients;modeling and Analysis of Cyclic Control of Periodic Conflict Flows;statistical Testing for Long-Range Dependence in the Workload of a Single-Server Queue;optimizing IoT Network Performance and Security: The Role of Queuing Theory, Stochastic Pr

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An Open-source Tool for Simplifying computer and Assistive Technology Use 21

An Open-source Tool for Simplifying Computer and Assistive T...

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23rd international ACM SIGACCESS conference on computers and Accessibility (ASSETS)

作者： Vanderheiden, Gregg C. Jordan, J. Bern Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9781450383066

computer access is increasingly critical for all aspects of life from education to employment to daily living, health and almost all types of participation. The pandemic has highlighted our dependence on technology, but the dependence existed before and is continuing after. Yet many face barriers due to disability, literacy, or digital literacy. Although the problems faced by individuals with disabilities have received focus for some time, the problems faced by people who just have difficulty in using technologies has not, but is a second large, yet less understood problem. Solutions exist but are often not installed, buried, hard to find, and difficult to understand and use. To address these problems, an open-source extension to the Windows and macOS operating systems has been under exploration and development by an international consortium of organizations, companies, and individuals. It combines auto-personalization, layering, and enhanced discovery, with the ability to Install on Demand (IoD) any assistive technologies a user needs. The software, called Morphic, is now installed on all of the computers across campus at several major universities and libraries in the US and Canada. It makes computers simpler to use, and allows whichever features or assistive technologies a person needs to appear on any computer they encounter (that has Morphic on it) and want to use at school, work, library, community center, etc. This demonstration will cover both the basic and advanced features as well as how to get free copies of the open-source software and configure it for school, work or personal use. It will also highlight lessons learned from the placements.

关键词： Auto-personalization Accessibility Inclusive Design Layering Assistive technologies

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23rd international conference on Product-Focused Software Process Improvement, PROFES 2022

23rd International Conference on Product-Focused Software Pr...

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23rd international conference on Product-Focused Software Process Improvement, PROFES 2022

ISBN: (纸本)9783031213878

The proceedings contain 55 papers. The special focus in this conference is on Product-Focused Software Process Improvement. The topics include: Data-Driven Improvement of Static Application Security Testing Service: An Experience Report in Visma;near Failure Analysis Using Dynamic Behavioural Data;a Process Model of Product Strategy Development: A Case of a B2B SaaS Product;communication Skills Requirements of Junior Software Engineers − Analysis of Job Ads;benefit Considerations in Project Decisions;towards Situational Process Management for Professional Education Programmes;change Management in Cloud-Based Offshore Software Development: A Researchers Perspective;half-Empty Offices in Flexible Work Arrangements: Why Are Employees Not Returning?;technical Debt in Service-Oriented Software systems;Managing the Root Causes of "Internal API Hell": An Experience Report;an Investigation of Entropy and Refactoring in Software Evolution;"To Clean Code or Not to Clean Code" A Survey Among Practitioners;counter the Uncertainties in a Dynamic World: An Approach to Creating Outcome-Driven Product Roadmaps;designing Platforms for Crowd-Based Software Prototype Validation: A Design Science Study;rapid Delivery of Software: The Effect of Alignment on Time to Market;exploring the "Why", "How", and "What" of Continuous Digital Service Innovation;why Traditional Product Roadmaps Fail in Dynamic Markets: Global Insights;understanding Low-Code or No-Code Adoption in Software Startups: Preliminary Results from a Comparative Case Study;Test Case Selection with Incremental ML;inferring Metamorphic Relations from JavaDocs: A Deep Dive into the MeMo Approach;requirements for Anomaly Detection Techniques for Microservices;an Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect Prediction;a/B Testing in the Small: An Empirical Exploration of Controlled Experimentation on Internal Tools;TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Grap

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23rd international conference on Engineering Applications of Neural Networks, EANN 2022

23rd International Conference on Engineering Applications of...

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23rd international conference on Engineering Applications of Neural Networks, EANN 2022

ISBN: (纸本)9783031082221

The proceedings contain 42 papers. The special focus in this conference is on Engineering Applications of Neural Networks. The topics include: Learning Image Captioning as a Structured Transduction Task;Reconstructing Electricity Profiles in Submetering systems Using a GRU-AE Network;trend and Seasonality Elimination from Relational Data;Using a Deep Neural Network in a Relative Risk Model to Estimate Vaccination Protection for COVID-19;A Gene Ontology-Driven Wide and Deep Learning Architecture for Cell-Type Classification from Single-Cell RNA-seq Data;Brain Tumour Segmentation on 3D MRI Using Attention V-Net;route Scheduling System for Multiple Self-driving Cars Using K-means and Bio-inspired Algorithms;Semantic Segmentation of Diabetic Retinopathy Lesions, Using a UNET with Pretrained Encoder;efficient Approaches for Data Augmentation by Using Generative Adversarial Networks;a Robust, Quantization-Aware Training Method for Photonic Neural Networks;towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles;an Exploration of Semi-supervised Text Classification;SNNs Model Analyzing and Visualizing Experimentation Using RAVSim;A Custom State LSTM Cell for Text Classification Tasks;Text Analysis of COVID-19 Tweets;Automatic Accent and Gender Recognition of Regional UK Speakers;novel Decision Forest Building Techniques by Utilising Correlation Coefficient Methods;on Forecasting Project Activity Durations with Neural Networks;human Activity Recognition Under Partial Occlusion;preface;an Accurate Convolutional Neural Networks Approach to Wound Detection for Farmed Salmon;ITSC Fault Diagnosis in Permanent Magnet Synchronous Motor Drives Using Shallow CNNs;synopsis of Video Files Using Neural Networks;trojanDroid: Android Malware Detection for Trojan Discovery Using Convolutional Neural Networks;generation of Orthogonality for Feature Spaces in the Bio-inspired Neural Networks;echo State Networks in Data Marketplaces for Digital Content Creatio

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Application of Machine Learning Methods for Cross-Matching Astronomical Catalogues 23rd

Application of Machine Learning Methods for Cross-Matching A...

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23rd international conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2021

作者： Kulishova, Aleksandra Briukhov, Dmitry Lomonosov Moscow State University Moscow Russia Federal Research Center "Computer Science and Control" of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031122842

The paper presents an approach for the application of machine learning methods for cross-matching astronomical catalogues. Related works on the cross-matching are analyzed and machine learning methods applied are briefly discussed. The approach is applied for cross-matching of three catalogues: Gaia, SDSS and ALLWISE. Experimental results of application of several machine learning methods for cross-matching these catalogues are presented. Recommendations for the application of the approach in astronomical information systems are proposed. © 2022, Springer Nature Switzerland AG.

关键词： Machine learning

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