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OneRel: Joint Entity and Relation Extraction with One Module in One Step

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arXiv 2022年

作者： Shang, Yu-Ming Huang, Heyan Mao, Xian-Ling School of Computer Science & Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

Joint entity and relation extraction is an essential task in natural language processing and knowledge graph construction. Existing approaches usually decompose the joint extraction task into several basic modules or processing steps to make it easy to conduct. However, such a paradigm ignores the fact that the three elements of a triple are interdependent and indivisible. Therefore, previous joint methods suffer from the problems of cascading errors and redundant information. To address these issues, in this paper, we propose a novel joint entity and relation extraction model, named OneRel, which casts joint extraction as a fine-grained triple classification problem. Specifically, our model consists of a scoring-based classifier and a relation-specific horns tagging strategy. The former evaluates whether a token pair and a relation belong to a factual triple. The latter ensures a simple but effective decoding process. Extensive experimental results on two widely used datasets demonstrate that the proposed method performs better than the state-of-the-art baselines, and delivers consistent performance gain on complex scenarios of various overlapping patterns and multiple triples. © 2022, CC BY.

关键词： Extraction

An Exploration Study on Developing Blockchain Systems – the Practitioners’ Perspective

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SSRN

SSRN 2024年

作者： Aljedaani, Bakheet Ahmad, Aakash Fahmideh, Mahdi Khan, Arif Ali Shen, Jun Computer Science Department Aljumum University College Umm Alqura University Makkah Saudi Arabia School of Computing and Communications Lancaster University Leipzig Germany School of Business University of Southern Queensland QLD Australia M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland School of Computing and Information Technology University of Wollongong Wollongong Australia

Context: Blockchain-based software (BBS) exploits the concepts and technologies popularized by cryptocurrencies like Bitcoin, offering decentralized transaction ledgers with immutable content for security-critical and transaction-critical systems. Recent research has explored the strategic benefits and technical limitations of BBS in various fields, including cybersecurity, healthcare, education, and financial technologies. Despite growing interest from academia and industry, there is a lack of empirical evidence, leading to an incomplete understanding of the processes, methods, and techniques necessary for systematic BBS ***: Existing research lacks a consolidated view, particularly empirically-driven guidelines based on published evidence and development practices. This study aims to address the gap by consolidating empirical evidence and development practices to derive or leverage existing processes, patterns, and models for designing, implementing, and validating BBS ***: Tied to this knowledge gap, we conducted a two-phase research project. First, a systematic literature review of 58 studies was performed to identify a development process comprising 23 tasks for BBS systems. Second, a survey of 102 blockchain practitioners from 35 countries across six continents was conducted to validate the BBS system development ***: Our results revealed a statistically significant difference (p-value © 2024, The Authors. All rights reserved.

关键词： Blockchain

Analysis of Network Technologies and Cyber security Assessment for Enhancing Machine Learning, Grid computing and Cyber-Physical Connectivity Internetwork Effectiveness 2

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Analysis of Network Technologies and Cyber security Assessme...

2nd International Conference on Innovative Practices in technology and Management, ICIPTM 2022

作者： Dhanalakshmi, B. Singh, Chaitanya Surya, S. Hedage, Atharav Kuchhal, Shikha Tongkachok, Korakod B.S. Abdur Rahman Crescent Institute Of Science And Technology Computer Science And Engineering Tamilnadu Vandalur India Swarrnim Startup Innovation University Computer Engineering Department Gujarat Gandhinagar India School Of Computing Kalasalingam University Computer Science And Engineering Tamilnadu Sirivelliputhur India Vishwakarma Institute Of Information Technology Electronics And Telecommunications Pune Belgaum Karnataka India Spitm Dcrust Department Of Ece Murthal India Thaksin University Faculty Of Law Thailand

ISBN: (纸本)9781665466431

The fast improvement of the Internet has incredibly worked with individuals spreading information worldwide, prompting the Internet turning into a pivotal apparatus in many fields like science, trade, schooling, etc. With the Internet common in such countless parts of day to day existence, network security has become basic and requests consistent consideration. For this situation, an IDS's motivation is to recognize between real organization associations and possibly hurtful ones. The recommended method in this examination centers around an interruption identification and avoidance system that comprises of Cloudlet Controller (CC), Trust Authority (TA), and Virtual Machine Manager to recognize questionable practices in a cloud climate. Cloud clients are migrated to different regions in the climate, as indicated by our proposed approach. Whenever information bundles from different clients are gathered, network traffic happens. To resolve this issue, we assembled the Cloudlet Controller, which gets bundles from different clients through switch. CC gets parcels until they arrive at their edge level;if the cloudlet is over-burden, the bundles are shipped off inactive cloudlets. In this philosophy, network traffic is decreased, and it is significantly helpful in identifying interruptions in a straightforward way. In this review, a cross breed arrangement based interruption location and counteraction framework on the cloud is worked to distinguish gatecrasher exercises in the framework. A cross breed characterization based interruption location framework is created with a few cloudlets, a cloudlet regulator, a confided in power, and a virtual machine supervisor to distinguish interloper assaults in the framework, as well as a deterrent instrument to safeguard bundles from gatecrashers. © 2022 IEEE.

关键词： Machine learning

Federated Dropout: Convergence Analysis and Resource Allocation

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arXiv 2024年

作者： Xie, Sijing Wen, Dingzhu Liu, Xiaonan You, Changsheng Ratnarajah, Tharmalingam Huang, Kaibin The School of Information Science and Technology ShanghaiTech University Shanghai201210 China The School of Natural and Computing Science University of Aberdeen AberdeenAB24 3FX United Kingdom The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China The School of Engineering The University of Edinburgh EdinburghEH8 9YL United Kingdom The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

Federated Dropout is an efficient technique to overcome both communication and computation bottlenecks for deploying federated learning at the network edge. In each training round, an edge device only needs to update and transmit a sub-model, which is generated by the typical method of dropout in deep learning, and thus effectively reduces the per-round latency. However, the theoretical convergence analysis for Federated Dropout is still lacking in the literature, particularly regarding the quantitative influence of dropout rate on convergence. To address this issue, by using the Taylor expansion method, we mathematically show that the gradient variance increases with a scaling factor of γ/(1 − γ), with γ ∈ [0, θ) denoting the dropout rate and θ being the maximum dropout rate ensuring the loss function reduction. Based on the above approximation, we provide the convergence analysis for Federated Dropout. Specifically, it is shown that a larger dropout rate of each device leads to a slower convergence rate. This provides a theoretical foundation for reducing the convergence latency by making a tradeoff between the per-round latency and the overall rounds till convergence. Moreover, a low-complexity algorithm is proposed to jointly optimize the dropout rate and the bandwidth allocation for minimizing the loss function in all rounds under a given per-round latency and limited network resources. Finally, numerical results are provided to verify the effectiveness of the proposed algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

A Discussion of Improving Efficiency and Addressing Obstacles with the use of Data mining and IoT for crop production

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A Discussion of Improving Efficiency and Addressing Obstacle...

Advance computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： Sandeep Bisht Haider Alabdeli H. A. Alsailawi P. Kirubananthan Dharmesh Dhabalia Madi Hashem Attiwi Mohammed Y. Al-Khuzaie Ali Abdulkareem Mezaal School of Management Graphic Era Hill University Bhimtal Uttarakhand India Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq Department of Chemistry and Biochemistry College of Medicine University of Kerbala Kerbala Iraq Department of Computing Technologies School of Computing College of Engineering and Technology Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur Chennai India Vishwakarma Institute of Information Technology Pune India Dental Department Al-kunooze University College Basra Iraq College of Technical Engineering National University of Science and Technology DhiQar Iraq Business Administration Department Al kut Kut University College wasit Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

The advancement of industries such as supply chain management, smart grids, and healthcare has been made possible by the Internet of Things (IoT), which also improves people’s daily lives and interactions. However, the growing size and complexity of IoT networks pose challenges in security, authenticity, reliability, and scalability. Blockchain emerges as a solution due to its security, transparency, reliability, and traceability. This study examines the problems with Internet of Things (IoT) systems, talks about how blockchain might help solve them, assesses the state of the art, and suggests a two-layer architectural solution that combines blockchain and IoT utilizing dew and cloudlet computing. This study presents an analysis of a blockchain-based trade origination and verification system, comparing its performance to the Hyperledger Fabric framework. The system comprises three phases: Trade Origination, Verification & Authentication, and Commit. Through experiments, the system demonstrates superior performance in transaction validation, block closing times, and memory scalability as the number of trades and participating nodes increases.

关键词： Industries Supply chain management Scalability Production Medical services Blockchains Smart grids

Robustness modularity in complex networks

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Physical Review E 2022年第5期105卷 054308-054308页

作者： Filipi N. Silva Aiiad Albeshri Vijey Thayananthan Wadee Alhalabi Santo Fortunato Indiana University Network Science Institute (IUNI) Bloomington Indiana 47408 USA Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah 21589 Kingdom of Saudi Arabia Luddy School of Informatics Computing and Engineering Indiana University Bloomington Indiana 47408 USA

A basic question in network community detection is how modular a given network is. This is usually addressed by evaluating the quality of partitions detected in the network. The Girvan-Newman (GN) modularity function is the standard way to make this assessment, but it has a number of drawbacks. Most importantly, it is not clearly interpretable, given that the measure can take relatively large values on partitions of random networks without communities. Here we propose a measure based on the concept of robustness: modularity is the probability to find trivial partitions when the structure of the network is randomly perturbed. This concept can be implemented for any clustering algorithm capable of telling when a group structure is absent. Tests on artificial and real graphs reveal that robustness modularity can be used to assess and compare the strength of the community structure of different networks. We also introduce two other quality functions: modularity difference, a suitably normalized version of the GN modularity, and information modularity, a measure of distance based on information compression. Both measures are strongly correlated with robustness modularity, but have lower time complexity, so they could be used on networks whose size makes the calculation of robustness modularity too costly.

关键词： Community structure Complex systems Robustness

ChatGPT as a Software Development Bot: A Project-based Study

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arXiv 2023年

作者： Waseem, Muhammad Das, Teerath Ahmad, Aakash Liang, Peng Fahmideh, Mahdi Mikkonen, Tommi Faculty of Information Technology University of Jyväskylä Jyväskylä Finland School of Computing and Communications Lancaster University Leipzig Leipzig Germany School of Computer Science Wuhan University Wuhan China School of Business University of Southern Queensland QLD Australia

Artificial Intelligence has demonstrated its significance in software engineering through notable improvements in productivity, accuracy, collaboration, and learning outcomes. This study examines the impact of generative AI tools, specifically ChatGPT, on the software development experiences of undergraduate students. Over a three-month project with seven students, ChatGPT was used as a support tool. The research focused on assessing ChatGPT's effectiveness, benefits, limitations, and its influence on learning. Results showed that ChatGPT significantly addresses skill gaps in software development education, enhancing efficiency, accuracy, and collaboration. It also improved participants' fundamental understanding and soft skills. The study highlights the importance of incorporating AI tools like ChatGPT in education to bridge skill gaps and increase productivity, but stresses the need for a balanced approach to technology use. Future research should focus on optimizing ChatGPT's application in various development contexts to maximize learning and address specific challenges. © 2023, CC BY.

关键词： Software design

Optimizing Patrolling Route with a Risk-Aware Reinforcement Learning Model

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SSRN

SSRN 2024年

作者： Chen, Haowen Wu, Yifan Wang, Weikun Zheng, Zengwei Ma, Jianhua Zhou, Binbin School of Computer and Computing Science Hangzhou City University No. 48 Huzhou Street Zhejiang Hangzhou310015 China College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou310015 China Faculty of Computer and Information Sciences Hosei University Chiyoda-ku 1028160 Japan

In recent years, the burgeoning urban population, coupled with expanding urban dimensions and various sociodemographic factors, has led to an alarming escalation in criminal activities within urban centers. This escalation has further exacerbated the existing strain on police resources, rendering them increasingly inadequate for effective law enforcement. Concurrently, police patrol operations have emerged as a pivotal instrument in the ongoing battle against violent criminal activities. The judicious planning of patrol routes has the potential to markedly enhance the efficiency of police patrolling endeavors, thereby bolstering the overall security infrastructure within the jurisdiction while simultaneously conserving invaluable police resources. The formulation of an efficient patrol strategy within the intricate and ever-evolving landscape of urban regions replete with crime hotspots represents an intellectually taxing challenge. To address this exigent problem, this paper proffers a novel real-time patrol route planning algorithm tailored to dynamic environments, employing the principles of deep reinforcement learning, specifically the Integrated Double Q-Network (IDQN) method. Subsequently, the efficacy of the proposed method is empirically substantiated through experimentation, attesting to its practical viability and utility in the field of computer science and urban security management. All the codes are available at https://***/ZJUDataIntelligence/PatrollingOptimization. © 2024, The Authors. All rights reserved.

关键词： Motion planning

Spatial computing: Concept, Applications, Challenges and Future Directions

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arXiv 2024年

作者： Yenduri, Gokul Ramalingam, M. Maddikunta, Praveen Kumar Reddy Gadekallu, Thippa Reddy Jhaveri, Rutvij H. Bandi, Ajay Chen, Junxin Wang, Wei Shirawalmath, Adarsh Arunkumar Ravishankar, Raghav Wang, Weizheng School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology TamilNadu 632014 India Zhongda Group Haiyan County Zhejiang Province Jiaxing City314312 China College of Information Science and Engineering Jiaxing University Jiaxing314001 China Division of Research and Development Lovely Professional University Phagwara India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gandhinagar India School of Computer Science and Information Systems Northwest Missouri State University 800 University Dr MaryvilleMO64468 United States School of Software Dalian University of Technology Dalian116621 China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Medical Technology Beijing Institute of Technology Beijing100081 China School of Computer Science and Engineering Vellore Institute of Technology TamilNadu 632014 India Department of Computer Science City University of Hong Kong Hong Kong

Spatial computing is a technological advancement that facilitates the seamless integration of devices into the physical environment, resulting in a more natural and intuitive digital world user experience. Spatial computing has the potential to become a significant advancement in the field of computing. From GPS and location-based services to healthcare, spatial computing technologies have influenced and improved our interactions with the digital world. The use of spatial computing in creating interactive digital environments has become increasingly popular and effective. This is explained by its increasing significance among researchers and industrial organisations, which motivated us to conduct this review. This review provides a detailed overview of spatial computing, including its enabling technologies and its impact on various applications. Projects related to spatial computing are also discussed. In this review, we also explored the potential challenges and limitations of spatial computing. Furthermore, we discuss potential solutions and future directions. Overall, this paper aims to provide a comprehensive understanding of spatial computing, its enabling technologies, their impact on various applications, emerging challenges, and potential solutions. © 2024, CC BY.

关键词： Augmented reality