检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Hasan, Dler O. Aladdin, Aso M. Talabani, Hardi Sabah Rashid, Tarik Ahmed Mirjalili, Seyedali Department of Applied Computer College of Medical and Applied Sciences Charmo University KR Sulaymaniyah Iraq Department of Technical Information Systems Engineering Erbil Technical Engineering College Erbil Polytechnic University KR Erbil Iraq Computer Science and Engineering Department University of Kurdistan Hewler KR Erbil Iraq Centre for Artificial Intelligence Research and Optimization Torrens University Adelaide Australia Yonsei Frontier Lab Yonsei University Seoul Korea Republic of

Fifteen Puzzle problem is one of the most classical problems that have captivated mathematical enthusiasts for centuries. This is mainly because of the huge size of the state space with approximately 1013 states that have to be explored and several algorithms have been applied to solve the Fifteen Puzzle instances. In this paper, to deal with this large state space, Bidirectional A* (BA*) search algorithm with three heuristics, such as Manhattan distance (MD), linear conflict (LC), and walking distance (WD) has been used to solve the Fifteen Puzzle problems. The three mentioned heuristics will be hybridized in a way that can dramatically reduce the number of generated states by the algorithm. Moreover, all those heuristics require only 25KB of storage but help the algorithm effectively reduce the number of generated states and expand fewer nodes. Our implementation of BA* search can significantly reduce the space complexity, and guarantee either optimal or near-optimal solutions. © 2023, CC BY.

关键词： Heuristic methods

来源：评论

学校读者我要写书评

暂无评论

Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

引用

npj Flexible Electronics 2020年第1期4卷 243-254页

作者： Zixuan Zhang Tianyiyi He Minglu Zhu Zhongda Sun Qiongfeng Shi Jianxiong Zhu Bowei Dong Mehmet Rasit Yuce Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Centre for Intelligent Sensors and MEMS(CISM) National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Hybrid Integrated Flexible Electronic Systems(HIFES) 5 Engineering Drive 1Singapore 117608Singapore Smart Systems Institute National University of Singapore3 Research LinkSingapore 117602Singapore National University of Singapore Suzhou Research Institute(NUSRI) Suzhou Industrial Park215123 SuzhouChina Department of Electrical and Computer Systems Engineering Monash UniversityMelbourneVIC 3800Australia NUS Graduate School for Integrative Science and Engineering(NGS) National University of SingaporeSingapore 119077Singapore

The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable *** reveals sensory information in daily life containing personal information,regarding identification and *** wearable electronics of gait analysis are mainly limited by high fabrication cost,operation energy consumption,or inferior analysis methods,which barely involve machine learning or implement nonoptimal models that require massive datasets for ***,we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory *** sock equipped with self-powered functionality also can be used as wearable sensors to deliver information,regarding the identity,health status,and activity of the *** further address the issue of ineffective analysis methods,an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed,which produces a 93.54%identification accuracy of 13 participants and detects five different human activities with 96.67%*** practical application,we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring,healthcare,identification,and future smart home applications.

关键词： Deep smart IoT

来源：评论

学校读者我要写书评

暂无评论

An HCI Experiment to Explore Interactive Artificial Life Art 24th

An HCI Experiment to Explore Interactive Artificial Life Ar...

引用

24th International Conference on Human-computer Interaction, HCI International, HCII 2022

作者： Dumo, Glare Lind, Pedro G. Nichele, Stefano Department of Computer Science OsloMet – Oslo Metropolitan University P.O. Box 4 St. Olavs plass Oslo0130 Norway AI Lab – OsloMet Artificial Intelligence Lab Pilestredet 52 Oslo0166 Norway NordSTAR – Nordic Center for Sustainable and Trustworthy AI Research Pilestredet 52 Oslo0166 Norway Department of Holistic Systems Simula Metropolitan Center for Digital Engineering Pilestredet 52 Oslo0166 Norway Department of Computer Science and Communication Østfold University College B R A Veien 4 Halden1757 Norway

ISBN: (纸本)9783031063909

We present an interface for creating art using tools from artificial intelligence and artificial life. The interface is tested and validated, through an online experiment with the aim of investigating how AI algorithms can be used for enabling humans - able or disabled - to express their artistic creativity. The interface uses evolutionary algorithms to generate images and videos of life-like patterns of pixels, based on rules describing local updates for cellular automata. Participants were asked to select a sequence of rules, either randomly generated (control group) or assisted by an interactive evolutionary algorithm which takes into account the participant’s previous choices (test group). Our results show a significantly higher satisfaction of the test group with a significance level of 95 % and a power of 82 %. Finally, we also discuss the usefulness of such an interface for people with disabilities and limitations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cellular automata

来源：评论

学校读者我要写书评

暂无评论

Towards Situational Aware Cyber-Physical systems: A Security-Enhancing Use Case of Blockchain-based Digital Twins

arXiv

引用

arXiv 2022年

作者： Suhail, Sabah Malik, Saif Ur Rehman Jurdak, Raja Hussain, Rasheed Matulevičius, Raimundas Svetinovic, Davor Research Institute for Cryptoeconomics Information Systems and Operations Management Vienna University of Economics and Business Vienna Austria Cybernetica AS Tallinn Estonia Queensland University of Technology Brisbane Australia Smart Internet Lab University of Bristol Bristol United Kingdom University of Tartu Tartu Estonia Center for Cyber-Physical Systems Electrical Engineering and Computer Science Khalifa University of Science and Technology Abu Dhabi United Arab Emirates

The complexity of cyberattacks in Cyber-Physical systems (CPSs) calls for a mechanism that can evaluate critical infrastructures' operational behaviour and security without affecting the operation of live systems. In this regard, Digital Twins (DTs) provide actionable insights through monitoring, simulating, predicting, and optimizing the state of CPSs. Through the use cases, including system testing and training, detecting system misconfigurations, and security testing, DTs strengthen the security of CPSs throughout the product lifecycle. However, such benefits of DTs depend on an assumption about data integrity and security. Data trustworthiness becomes more critical while integrating multiple components among different DTs owned by various stakeholders to provide an aggregated view of the complex physical system. This article envisions a blockchain-based DT framework as Trusted Twins for Securing Cyber-Physical systems (TTS-CPS). With the automotive industry as a CPS use case, we demonstrate the viability of the TTS-CPS framework through a proof of concept. To utilize reliable system specification data for building the process knowledge of DTs, we ensure the trustworthiness of data-generating sources through Integrity Checking Mechanisms (ICMs). Additionally, Safety and Security (S&S) rules evaluated during simulation are stored and retrieved from the blockchain, thereby establishing more understanding and confidence in the decisions made by the underlying systems. Finally, we perform formal verification of the TTS-CPS. Copyright © 2022, The Authors. All rights reserved.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

BinaryAI: Binary Software Composition Analysis via Intelligent Binary Source Code Matching

BinaryAI: Binary Software Composition Analysis via Intellige...

引用

International Conference on Software engineering (ICSE)

作者： Ling Jiang Junwen An Huihui Huang Qiyi Tang Sen Nie Shi Wu Yuqun Zhang Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Shenzhen China Tencent Security Keen Lab Shanghai China Department of Computer Science and Engineering Southern University of Science and Technol-ogy Shenzhen China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation China

ISBN: (数字)9798400702174

ISBN: (纸本)9798350382143

While third-party libraries (TPLs) are extensively reused to enhance productivity during software development, they can also introduce potential security risks such as vulnerability propagation. Software composition analysis (SCA), proposed to identify reused TPLs for reducing such risks, has become an essential procedure within modern DevSecOps. As one of the mainstream SCA techniques, binary-to-source SCA identifies the third-party source projects contained in binary files via binary source code matching, which is a major challenge in reverse engineering since binary and source code exhibit substantial disparities after compilation. The existing binary-to-source SCA techniques leverage basic syntactic features that suffer from redundancy and lack robustness in the large-scale TPL dataset, leading to inevitable false positives and compromised recall. To mitigate these limitations, we introduce BinaryAI, a novel binary-to-source SCA technique with two-phase binary source code matching to capture both syntactic and semantic code features. First, BinaryAI trains a transformer-based model to produce function-level embeddings and obtain similar source functions for each binary function accordingly. Then by applying the link-time locality to facilitate function matching, BinaryAI detects the reused TPLs based on the ratio of matched source functions. Our experimental results demonstrate the superior performance of BinaryAI in terms of binary source code matching and the downstream SCA task. Specifically, our embedding model outperforms the state-of-the-art model CodeCMR, i.e., achieving 22.54% recall@l and 0.34 MRR compared with 10.75% and 0.17 respectively. Additionally, BinaryAI outperforms all existing binary-to-source SCA tools in TPL detection, increasing the precision from 73.36% to 85.84% and recall from 59.81% to 64.98% compared with the well-recognized commercial SCA product Black Duck. E-https://***

关键词： Codes Source coding Semantics Redundancy Syntactics Transformers Software

来源：评论

学校读者我要写书评

暂无评论

Generic Drone Simulator: Design, Development and User Testing in a Virtual Search and Rescue Mission

引用

IEEE computer Graphics and Applications 2025年 PP卷 PP页

作者： Pappas, Georgios Lappas, Dimitrios Karampelas, Panagiotis Siegel, Joshua E. Templalexis, Ioannis Stavrou, Stavros Krishnan, Sriram Open University of Cyprus Lab of Educational Material and Methodology Latsia Nicosia Cyprus University of the Aegean Learning Technology and Educational Engineering Laboratory Rhodes Greece Hellenic Air Force Academy Department of Informatics & Computers Dekelia Attiki Greece Michigan State University Department of Computer Science and Engineering East LansingMI United States Hellenic Air Force Academy Department of Thermodynamics Propulsion and Power Systems Dekelia Attiki Greece Open University of Cyprus Cybersecurity and Telecommunications Research Lab Latsia Nicosia Cyprus Indian Institute of Technology The Energy Consortium Madras India

This study addresses the need for scenario-specific drone simulators to enhance research, education, pilot training, and performance evaluation across diverse mission contexts. A gamified simulator was developed for the joint master's degree program "Security and Defence" between the Open University of Cyprus (OUC) and the Hellenic Air Force Academy (HAFA), with a focus on Search and Rescue mission training and planning. The simulator balances interface design, physics accuracy, and environmental realism to support specialized professional training and research. A survey-based evaluation involving 57 participants –pilots, engineers, and air traffic controllers –demonstrated the tool's ability to provide realistic experiences for trained pilots and meaningful learning opportunities for novices. Statistical analysis revealed significant correlations between gaming familiarity, task completion times, and participant expertise. © 1981-2012 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Early Detection of Induction Machines Fault Using Vibration-Based Analysis under COMSOL Multiphysics within a Preventive Maintenance Framework

Early Detection of Induction Machines Fault Using Vibration-...

引用

Innovative research in Applied Science, engineering and Technology (IRASET),Conference on

作者： Hamza Sabir Mohammed Ouassaid Nourdine Herbaz Nabil Ngote Mohamed El Khaili Ahmed Abid Laboratory of Engineering Sciences & Biosciences Faculty of Sciences and Techniques of Mohammedia Hassan II University Casablanca Morocco Engineering for Smart and Sustainable Systems Research Center Mohammadia School of Engineers Mohammed V University in Rabat Rabat Morocco Laboratory of Electronics Energy Automation & Information Processing (LEEA&TI). Faculty of Sciences and Techniques of Mohammedia Hassan II University Casablanca Morocco ENSMR Engineering School Rabat Morocco IESI Lab ENSET Mohammedia Hassan 2nd University of Casablanca Casablanca Morocco Electrical Engineering Department Faculty of Sciences and Techniques of Mohammedia Hassan II University Casablanca Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

In this paper, a predictive maintenance strategy is developed to enhance the fault identification of induction machines using the analysis of residual mechanical vibrations. Induction machines are the most widely adopted machines in many industrial environments, owing to their high robustness, simplicity and economic efficiency. Nevertheless, these machines are susceptible to both electrical and mechanical failures, including stator phase deficiencies, which may result in significant downtime and expensive maintenance charges. The approach developed is designed by combining FFT (Fast Fourier Transform) and vibration signal analysis to detect faults at an early stage. The methodology has been validated by simulations performed with COMSOL Multiphysics. The results reveal a significant improvement over traditional maintenance methods based solely on vibration analysis in the early detection of failures, resulting in reduced downtime and lower maintenance costs.

关键词： Vibrations Fault diagnosis Machine learning algorithms Fast Fourier transforms Windings Stator windings Maintenance Wind turbines Induction machines Preventive maintenance

来源：评论

学校读者我要写书评

暂无评论

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments (vol 18, e1010241, 2022)

引用

PLOS COMPUTATIONAL BIOLOGY 2022年第9期18卷 e1010241页

作者： Alinejad-Rokny, Hamid Modegh, Rassa Ghavami Rabiee, Hamid R. Sarbandi, Ehsan Ramezani Rezaie, Narges Tam, Kin Tung Forrest, Alistair R. R. Harry Perkins Institute of Medical Research QEII Medical Centre and Centre for Medical Research The University of Western Australia Perth Australia. Bioinformatics and Computational Biology Lab Department of Computer Engineering Sharif University of Technology Tehran Iran. Center for Complex Biological Systems University of California Irvine Irvine California United States of America.

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.

关键词： Genomics Chromatin Genome-wide association studies Single nucleotide polymorphisms Histones Gene regulation Deoxyribonucleases Insulators

来源：评论

学校读者我要写书评

暂无评论

Efficient multi-task learning with instance selection for biomedical NLP

引用

computers in Biology and Medicine 2025年 190卷 110050-110050页

作者： Bonfigli, Agnese Bacco, Luca Pecchia, Leandro Merone, Mario Dell'Orletta, Felice ItaliaNLP Lab Institute of Computational Linguistics "Antonio Zampolli" National Research Council Via Giuseppe Moruzzi 1 Pisa56124 Italy Research Unit of Intelligent Technology for Health and Wellbeing Department of Engineering Università Campus Bio-Medico di Roma Via Alvaro del Portillo 21 Rome00128 Italy Research Unit of Computer Systems and Bioinformatics Department of Engineering Università Campus Bio-Medico di Roma Via Alvaro del Portillo 21 Rome00128 Italy Fondazione Policlinico Universitario Campus Bio-Medico di Roma Via Alvaro del Portillo 200 Rome00128 Italy

Background: Biomedical natural language processing (NLP) increasingly relies on large language models and extensive datasets, presenting significant computational challenges. Methods: We propose Blue5, a multi-task model based on SciFive that incorporates instance selection (IS) to enable efficient, multi-task learning (MTL) on biomedical data. We adapt the E2SC-IS framework for the biomedical domain, integrating a calibrated SVM classifier to reduce computational costs. Results: Our approach achieves an average data reduction of 26.6% across the several tasks of the BLUE (Biomedical Language Understanding Evaluation) Benchmark, while maintaining performance comparable with state-of-the-art models. The multi-task SVM configuration emerges as the most effective, demonstrating the power of combining IS with MTL for biomedical NLP. As a result of the unified framework, Blue5 effectively selects the most informative instances across tasks, ensuring model generalization while efficiently handling multiple NLP tasks. Conclusion: Our work offers a practical solution to address growing computational demands, enabling more scalable and accessible applications of advanced NLP techniques in biomedical research and healthcare. © 2025 The Authors

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

A Diversity-Enhanced Knowledge Distillation Model for Practical Math Word Problem Solving

arXiv

引用

arXiv 2025年

作者： Zhang, Yi Zhou, Guangyou Xie, Zhiwen Ma, Jinjin Huang, Jimmy Xiangji Faculty of Artificial Intelligence in Education Central China Normal University Hubei Wuhan430079 China School of Information and Safety Engineering Zhongnan University of Economics and Law Hubei Wuhan430073 China Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning School of Computer Central China Normal University Hubei Wuhan430079 China Information Retrieval and Knowledge Management Research Lab York University Toronto Canada

Math Word Problem (MWP) solving is a critical task in natural language processing, has garnered significant research interest in recent years. Various recent studies heavily rely on Seq2Seq models and their extensions (e.g., Seq2Tree and Graph2Tree) to generate mathematical equations. While effective, these models struggle to generate diverse but counterpart solution equations, limiting their generalization across various math problem scenarios. In this paper, we introduce a novel Diversity-enhanced Knowledge Distillation (DivKD) model for practical MWP solving. Our approach proposes an adaptive diversity distillation method, in which a student model learns diverse equations by selectively transferring high-quality knowledge from a teacher model. Additionally, we design a diversity prior-enhanced student model to better capture the diversity distribution of equations by incorporating a conditional variational auto-encoder. Extensive experiments on four MWP benchmark datasets demonstrate that our approach achieves higher answer accuracy than strong baselines while maintaining high efficiency for practical applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：