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检索条件"任意字段=10th International Conference on Tools and Algorithms for the Construction and Analysis of Systems"

共 1698 条记录，以下是71-80 订阅

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10th international Workshop on Big Data Management and Service, BDMS 2024, 9th international Workshop on Big Data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in Data Science and Engineering, ERDSE 2024 and 8th international Workshop on Graph Data Management and analysis, GDMA 2024 held in conjunction with 29th international conference on Database systems for Advanced Applications, DASFAA 2024

10th International Workshop on Big Data Management and Servi...

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10th international Workshop on Big Data Management and Service, BDMS 2024, 9th international Workshop on Big Data Quality Management, BDQM 2024, DASFAA 2024 Workshop on Emerging Results in Data Science and Engineering, ERDSE 2024 and 8th international Workshop on Graph Data Management and analysis, GDMA 2024 held in conjunction with 29th international conference on Database systems for Advanced Applications, DASFAA 2024

ISBN: (纸本)9789819609130

the proceedings contain 26 papers. the special focus in this conference is on Big Data Management and Service. the topics include: FAIth: A Fast, Accurate, and Lightweight Database-Agnostic Learned Cost Model;fast Approximate Temporal Butterfly Counting on Bipartite Graphs via Edge Sampling;Financial-ICS: Identifying Peer Firms via LongBERT from 10K Reports;establishing a Decentralized Diamond Quality Management System: Advancing Towards Global Standardization;co-estimation of Data Types and their Positional Distribution;Enhancing Load Forecasting with VAE-GAN-Based Data Cleaning for Electric Vehicle Charging Loads;audio-Guided Visual Knowledge Representation;boundary Point Detection Combining Gravity and Outlier Detection Methods;A Meta-learning Approach for Category-Aware Sequential Recommendation on POIs;automatic Post-editing of Speech Recognition System Output Using Large Language Models;comparative analysis with Multiple Large-Scale Language Models for Automatic Generation of Funny Dialogues;effectiveness of the Programmed Visual Contents Comparison Method for Two Phase Collaborative Learning in Computer Programming Education: A Case Study;generating Achievement Relationship Graph Between Actions for Alternative Solution Recommendation;generating News Headline Containing Specific Person Name;Investigating Evidence in Sentence Similarity Using MASK in BERT;acceleration of Synopsis construction for Bounded Approximate Query Processing;Query Expansion in Food Review Search with Synonymous Phrase Generation by LLM;Question Answer Summary Generation from Unstructured Texts by Using LLMs;Real Estate Information Exploration in VR with LoD Control by Physical Distance;voices of Asynchronous Learning Students: Revealing Learning Characteristics through Vocabulary analysis of Notes Tagged in Videos;review Search Interface Based on Search Result Summarization Using Large Language Model;yes-No Flowchart Generation for Interactive Exploration of Personalized Health Improve

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Model Checking Linear Dynamical systems under Floating-point Rounding. 29th

Model Checking Linear Dynamical Systems under Floating-point...

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29th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： Lefaucheux, Engel Ouaknine, Joel Purser, David Sharifi, Mohammadamin Univ Lorraine LORIA Inria CNRS Nancy France Max Planck Inst Software Syst Saarland Informat Campus Saarbrucken Germany Univ Warsaw Warsaw Poland Univ Liverpool Liverpool England Sharif Univ Technol Tehran Iran

ISBN: (纸本)9783031308222;9783031308239

We consider linear dynamical systems under floating-point rounding. In these systems, a matrix is repeatedly applied to a vector, but the numbers are rounded into floating-point representation after each step (i.e., stored as a fixed-precision mantissa and an exponent). the approach more faithfully models realistic implementations of linear loops, compared to the exact arbitrary-precision setting often employed in the study of linear dynamical systems. Our results are twofold: We show that for non-negative matrices there is a special structure to the sequence of vectors generated by the system: the mantissas are periodic and the exponents grow linearly. We leverage this to show decidability of.-regular temporal model checking against semialgebraic predicates. this contrasts with the unrounded setting, where even the non-negative case encompasses the long-standing open Skolem and Positivity problems. On the other hand, when negative numbers are allowed in the matrix, we showthat the reachability problem is undecidable by encoding a two-counter machine. Again, this is in contrast with the unrounded setting where point-to-point reachability is known to be decidable in polynomial time.

关键词： Model Checking Floating-point Dynamical systems

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the Static Analyzer Infer in SV-COMP (Competition Contribution) 28th

The Static Analyzer Infer in SV-COMP (Competition Contributi...

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28th international conference on tools and algorithms for the construction and analysis of systems (TACAS) Held as Part of the 25th European Joint conferences on theory and Practice of Software (ETAPS)

作者： Kettl, Matthias Lemberger, thomas Ludwig Maximilians Univ Munchen Munich Germany

ISBN: (纸本)9783030995270;9783030995263

We present INFER-SV, a wrapper that adapts INFER for SV-COMP. INFER is a static-analysis tool for C and other languages, developed by Facebook and used by multiple large companies. It is strongly aimed at industry and the internal use at Facebook. Despite its popularity, there are no reported numbers on its precision and efficiency. With INFER-SV, we take a first step towards an objective comparison of INFER with other SV-COMP participants from academia and industry.

关键词： Static analysis

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USING EYE-GAZE TO EVALUATE E-HEALth DECISION SUPPORT systems 9

USING EYE-GAZE TO EVALUATE E-HEALTH DECISION SUPPORT SYSTEMS

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9th international conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2024, the 10th international conference on Connected Smart Cities, CSC 2024 and the 16th international conference on e-Health, EH 2024, Part of the 18th Multi conference on Computer Science and Information systems 2024, MCCSIS 2024

作者： Krupinski, Elizabeth A. Department of Radiology Imaging Sciences Emory University 1364 Clifton Rd NE AtlantaGA30032 United States

ISBN: (纸本)9789898704597

Eye-tracking technologies have been used for decades to assess the impact of technologies on clinical decision making in medical imaging. eHealth and telemedicine present new opportunities to integrate images and other visual data into routine clinical care. Artificial intelligence (AI) tools can work synergistically with these data to improve the efficacy and efficiency of data analysis and interpretation by the human decision maker. However, we know little about the optimal ways to present AI output to providers. this study used radiology image interpretation with AI-based decision support to explore the impact of different types of AI output on reader performance. Four different outputs (plus no AI feedback) were evaluated with experienced radiologists and radiology residents. Results reveal that the rates of decision changes prior to and after receiving the AI output differ as a function of the output format and reader experience. More complex output formats tend to increase reading time. © 2024 Big Data Analytics, Data Mining and Computational Intelligence. All Rights Reserved.

关键词： Electronic health record

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Revolutionizing Consumer Power Management: Unveiling Power Grid Feasibility analysis Using Machine Learning 10

Revolutionizing Consumer Power Management: Unveiling Power G...

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10th IEEE international conference on Power systems, ICPS 2023

作者： Rahman, Minhazur Himu, Sheik Erfan Ahmed Al Shahid Chowdhury, Abdullah Ikram, Arafat Ibne Kashfi, Samiul Hoque Uddin, Md Imtiaz Faisal, M.D. International Islamic University Chittagong Department of Electrical and Electronic Engineering Chittagong Bangladesh Nagoya Institute of Technology Department of Electrical and Mechanical Engineering Nagoya Japan

ISBN: (纸本)9798350318739

As distributed energy sources become more prevalent, maintaining power grid stability is increasingly challenging. By integrating machine intelligence and communication technologies, traditional power networks could transform into smart grids. through machine learning and artificial intelligence, these smart grids can adeptly respond to unexpected changes in consumer demand, power interruptions, surges in renewable energy production, and other crucial situations. Variations in power generation and loads, along with changes in the power system's structure, lead to varying shifts in the entire network's active power. Detecting these fluctuations through manual analysis is laborious, but machine learning can be highly impactful in this regard. this study aims to collect comprehensive data for analyzing grid stability, utilizing machine learning tools to thoroughly examine the data, and adopting a multimodal approach to compare model outcomes for an improved solution strategy. Our analysis reveals an accuracy exceeding 0.97, indicating strong potential for practical application and implications. © 2023 IEEE.

关键词： Decision trees

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A Prototype for Data Race Detection in CSeq 3 (Competition Contribution) 28th

A Prototype for Data Race Detection in CSeq 3 (Competition C...

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作者： Coto, Alex Inverso, Omar Sales, Emerson Tuosto, Emilio Gran Sasso Sci Inst Laquila Italy

We sketch a sequentialization-based technique for bounded detection of data races under sequential consistency, and summarise the major improvements to our verification framework over the last years.

ISBN: (纸本)9783030995270;9783030995263

We sketch a sequentialization-based technique for bounded detection of data races under sequential consistency, and summarise the major improvements to our verification framework over the last years.

关键词： Bounded model checking Context-bounded analysis Sequentialization Data races Reachability Concurrency threads

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Software Verification: 10th Comparative Evaluation (SV-COMP 2021) 27th

Software Verification: 10th Comparative Evaluation (SV-COMP ...

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27th international conference on tools and algorithms for construction and analysis of systems (TACAS)

作者： Beyer, Dirk Ludwig Maximilians Univ Munchen Munich Germany

ISBN: (纸本)9783030720124;9783030720131

SV-COMP 2021 is the 10th edition of the Competition on Software Verification (SV-COMP), which is an annual comparative evaluation of fully automatic software verifiers for C and Java programs. the competition provides a snapshot of the current state of the art in the area, and has a strong focus on reproducibility of its results. the competition was based on 15 201 verification tasks for C programs and 473 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). SV-COMP 2021 had 30 participating verification systems from 27 teams from 11 countries.

关键词： Formal Verification Program analysis Competition Software Verification Verification Tasks Benchmark C Language Java Language SV-Benchmarks

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construction and Optimization of Regular Expressions in Genetic Sequence analysis 5

Construction and Optimization of Regular Expressions in Gene...

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5th international conference on Emerging systems and Intelligent Computing, ESIC 2025

作者： Kunkri, Rajdeep Ray, Sanchita Saha St. Thomas' College of Engineering & Technology Dept. of Information Technology Kolkata India

ISBN: (纸本)9798331522100

In this paper a novel approach for generating and optimizing regular expressions for genetic sequences is presented. the proposed technique introduces a systematic process to create initial regular expressions, compress and optimize them, and validate their accuracy for sequence matching. the method ensures a precise and reliable match with the given sequences while reducing complexity through an efficient optimization process. the proposed approach is versatile, being applicable to DNA, RNA, protein sequences, or any formal language processing. the method has been tested using a set of sequences with lengths ranging from 64 to 512 characters, with 50-100 pseudo-random generated sequence pairs and 5-10 % mutations for each case. Although the regular expression optimization process consumes slightly more time compared to conventional methods, it significantly reduces the overall matching time. Additionally, the optimized regular expressions show a reduction in memory usage. the results demonstrate that the proposed approach is highly effective for Motif Discovery and Representation, Pattern Matching algorithms, Comparative Genomics and Phylogenetic and Gene Regulation, and Promoter analysis, making it suitable for applications in bioinformatics and computational linguistics. © 2025 IEEE.

关键词： Gene expression regulation

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Comparative analysis of Multiclass Classification Machine Learning Models for Cybersecurity Intrusion Detection 4th

Comparative Analysis of Multiclass Classification Machine Le...

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4th international conference on Digital Technologies and Applications (ICDTA)

作者： Loughmari, Mohamed El Affar, Anass Sidi Mohamed Ben Abdellah Univ Polydisciplinary Fac Taza Engn Sci Lab LSI BP 1223 Taza Morocco

ISBN: (纸本)9783031686528;9783031686535

Recently, the use of the Internet and computer networks in general, has increased exponentially, leading to a high demand for cybersecurity to protect against all kinds of network attacks that are constantly evolving. Nowadays, Machine Learning (ML) is implemented in various cybersecurity tools, Intrusion Detection System-based ML brings more capabilities to improve the detection of cyber attacks. this study aims to perform a comparative analysis of a multiclass classification problem for cybersecurity attack detection. the comparative analysis is performed using six different machine learning algorithms: Naive Bayes, Decision Tree, Random Forest, Support Vector Machine, eXtreme Gradient Boosting, and Multi-Layer Perceptron, which are applied to the full NSL-KDD dataset, and three other subsets of datasets to confirm and verify the findings in terms of precision, accuracy, training time, and testing time. In all dataset subsets we worked on in addition to the NSL-KDD dataset, eXtreme Gradient Boosting significantly beat the other algorithms. From all the experimental results, it is concluded that XGBoost is a plausible choice for an intrusion detection system in terms of all the metrics compared to the other ML algorithms discussed.

关键词： Cybersecurity Machine Learning Network Intrusion detection system NSL_KDD KDDcup UNSW-NB15

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GDart: An Ensemble of tools for Dynamic Symbolic Execution on the Java Virtual Machine (Competition Contribution) 28th

GDart: An Ensemble of Tools for Dynamic Symbolic Execution o...

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作者： Mues, Malte Howar, Falk TU Dortmund Univ Dortmund Germany Fraunhofer ISST Dortmund Germany

ISBN: (纸本)9783030995270;9783030995263

GDART is an ensemble of tools allowing dynamic symbolic execution of JVM programs. the dynamic symbolic execution engine is decomposed into three different components: a symbolic decision engine (DSE), a concolic executor (SPouT), and a SMT solver backend allowing meta-strategy solving of SMT problems (JConstraints). the symbolic decision component is loosely coupled with the executor by a newly introduced communication protocol. At SV-COMP 2022, GDART solved 471 of 586 tasks finding more correct false results (302) than correct true results (169). It scored fourth place.

关键词： Dynamic Symbolic Execution Software Verification

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