检索结果-内蒙古大学图书馆

45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Viskovic, Alfredo Franki, Vladimir Jevtic, Dragan Energy Platform Living Lab Zagreb Croatia Faculty of Engineering Rijeka Croatia Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9789532331035

There is a dramatic transformation occurring across the world. Efforts to decarbonize the energy sector are leading to an increasingly decentralized energy system. Power, heating, transport, building and industry sectors are progressively more interconnected. In addition, new business models and innovative technological solutions are driving change in the power industry. The new system being unfolded requires a much higher level of flexibility and coordination. The increased complexities can only be mitigated by actively managing the energy supply chain. In this context, artificial intelligence (AI) has the potential to play a key role in numerous areas such as demand forecasting, predictive maintenance, energy management and customer support. Among digital technologies, AI is the one with the highest adoption rate in the power sector. Considering the growing importance of AI, the paper analyses the current status and future prospects of the technology in the power industry. It also explores different issues and barriers to its wider adoption. The review of possible applications is conducted by analysing academic literature and by observing numerous companies around the world that are developing and implementing AI solutions on the grid's edge. © 2022 Croatian Society MIPRO.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Agent-based heuristics model for measuring customer disruption impact on production and inventory replenishment

引用

International Journal of Industrial and Systems engineering 2022年第3期40卷 370-398页

作者： Al-Bazi, Ammar Adediran, Tunde V. Faculty of Engineering Environment and Computing Coventry University West Midlands CoventryCV1-5FB United Kingdom

Agent-based simulation approach in production and inventory environment is capable of responding and adapting to disruptions caused by customers’ changing requirements. The impacts of disruptions in production and inventory systems can be measured through learning and decision-making ability of system agents. In this paper, agent-based modelling integrated with heuristic optimisation approach is presented as embedded within a scheduling and rescheduling framework. The proposed approach is implemented in a disrupted OEMs parts manufacturing system. The integration of the framework modules in connection with inventory control helped production planners to manage disruptions by tracking order processing times and quantities and for performance measurement. The proposed approach is compared with the few existing related methods like the sequential method. The proposed approach not only revealed the impact of disruptions in terms of process times and order quantities but offered ‘available times’ which were applied for production support and inventory replenishment. This demonstrates a valuable and viable resolution strategy responding and adapting to disruptions caused by customers. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Automating Galaxy Image Classification in Galaxy Zoo: A Comparative Study of Deep Learning Models 1

引用

13th National Technical Symposium on Unmanned System Technology, NUSYS 2023

作者： Chiew, Soon Piin Liau, Chung Fan Farzamnia, Ali Faculty of Engineering University Malaysia Sabah Kota Kinabalu88400 Malaysia School of Computing and Engineering University of Huddersfield West YorkshireHD1 3DH United Kingdom

ISBN: (数字)9789819720279

ISBN: (纸本)9789819720262

This study compares the effectiveness of Artificial Neural Networks (ANNs) and Logistic Regression in classifying galaxy images from Galaxy Zoo 1. We propose Convolutional Neural Network (CNN) and Autoencoder models as potential solutions to mitigate the burden of manual classification. Both models are analyzed, and results reveal that ANN surpasses Transferred Learning Logistic Regression in terms of accuracy and runtime. Further investigation highlights the impact of activation functions, neuron count, hidden layers, and algorithm ensembling on ANN's classification performance. Additionally, we explore training time complexity reduction through learning rate, optimization algorithms, and batch size. The findings provide valuable insights for galaxy image classification tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Selection of qualified reviewers and avoiding conflicts of interest within the issue of compromised peer review in paper retractions using an ontology-based decision support system

引用

International Journal of Metadata, Semantics and Ontologies 2023年第4期16卷 298-314页

作者： Al-Hidabi, Mymoona Dawood Abdulmalek Lee, Yunli Yusoff, Zaharin Teh, Phoey Lee Chia, Wai Chong Uwasomba, Chukwudi School of Engineering and Technology Sunway University Jalan Universiti Selangor No. 5 Bandar Sunway Darul Ehsan47500 Malaysia School of Engineering and Technology Sunway University Jalan Universiti Selangor No. 5 Bandar Sunway Darul Ehsan47500 Malaysia IRDI International Medical University Kuala Lumpur Malaysia Department of Cyber and Computing Faculty of Art Computing and Engineering Wrexham University Wales Wrexham United Kingdom School of Computing and Communications Open University Buckinghamshire Milton Keynes United Kingdom

Paper retractions are rising due to the absence of reliable tools to detect and identify fraudulent articles before publication. This paper proposes an ontology-based decision support system to prevent compromised peer review by carefully selecting qualified reviewers and avoiding potential conflicts of interest. There are three main contributions: (i) formulating the criteria for the selection of qualified reviewers as well as for recognising potential conflicts of interest;(ii) designing the ontology-based decision support system;(iii) designing and performing the methodology for validation. A pilot test with 30 computer science experts is conducted to determine qualified reviewers and conflict criteria, including the design of ontologies structure. Subsequently, three selected computer science experts and journal editors are requested to evaluate a set of test data as the ground truth. Overall results show that the proposed solution achieves 91% accuracy in qualified reviewer selection and 94% accuracy in conflict-of-interest detection. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Knowledge representation

来源：评论

学校读者我要写书评

暂无评论

Exploring the Potential of Interplanetary File System for Secure and Transparent Social Media 2

Exploring the Potential of Interplanetary File System for Se...

引用

2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Pandey, Shivam Sinha, Mayank Ramya, G. SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur Chennai India SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur Chennai India

ISBN: (纸本)9798350347982

A new social media platform will be developed that utilizes blockchain technology to ensure user privacy and security. The platform will use the user's meta-mask wallet ID, which cannot be hacked, to connect to their profile on the blockchain, providing an immutable and tamper-proof ledger for their data. The platform will also allow for cryptocurrency transactions, which are secured by cryptography and do not require a centralized intermediary, adding another layer of security. Smart contracts will be used to enable decentralized and automated crowd funding and giveaways, among other features. The smart contracts will be designed using Solidity, a programming language specific to the Ethereum blockchain. When a user creates an account on the platform, their meta-mask wallet ID will be used for user identification and to verify transactions, ensuring that every transaction is validated by the blockchain. © 2023 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

NLP Techniques Cyberbullying Text Analysis on Twitter 10

NLP Techniques Cyberbullying Text Analysis on Twitter

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Rishi, R. Mohammed Irfan, M.A. Balamurugan, G. Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus Tamil Nadu Chengalpattu India Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Kattankulathur Campus Tamil Nadu Chengalpattu India

ISBN: (纸本)9798350353068

With the pervasive nature of social media, the rise of cyberbullying has become a critical concern, necessitating advanced methodologies for timely identification and analysis. This research delves into the application of Natural Language Processing (NLP) mechanisms to mention the challenges of cyberbullying within the dynamic and fast-paced environment of Twitter. The study explores the utilization of state-of-the-art NLP algorithms and methodologies for the classification and analysis of cyberbullying text. Techniques such as sentiment analysis, text categorization, and semantic understanding are employed to discern the nuanced and context-dependent nature of cyberbullying content on the Twitter platform. We present a comprehensive examination of various machine learning models, including but not limited to recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformer methods like BERT, for their effectiveness in accurately classifying cyberbullying text. Additionally, attention is given to feature engineering and pre-processing strategies tailored to the unique characteristics of Twitter data. © 2024 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Reinforcement Learning-based Optimization of EBike Charging infrastructure 11

Reinforcement Learning-based Optimization of EBike Charging ...

引用

11th IEEE/ACM International Conference on Big Data computing, Applications and Technologies, BDCAT 2024

作者： Sharif, Muddsair Seker, Huseyin Birmingham City University Faculty of Computing Engineering and the Built Environment BirminghamB5 5JU United Kingdom The University of Sharjah College of Computing and Informatics Department of Information Systems Sharjah United Arab Emirates

ISBN: (纸本)9798350367300

This paper presents a novel technique for enhancing the allocation of resources in the charging infrastructure for e-bikes by employing deep reinforcement learning (DRL) in a context-specific manner. With the evolving transportation land-scape and the increasing popularity of electric micro-mobility solutions, efficient resource management plays a vital role. The methodology involves utilizing deep Q networks (DQN) in virtual environments to dynamically allocate charging resources based on contextual parameters. Through empirical analysis, we demonstrate the efficacy of our approach in achieving optimal resource allocation while considering the needs of diverse stakeholders. Findings suggest that the DQN model, when integrated with context-awareness and stakeholder objectives, enables efficient resource allocation, maximize fleet utilization, ensures charging station availability, enhances user satisfaction, and promotes environmental sustainability. The findings of this study offer valuable insights for policymakers, urban planners, and industry stakeholders seeking to enhance the sustainability and effectiveness of micro-mobility services in urban settings. Overall, this study contributes to the advancement of sustainable urban mobility solutions and underscores the potential of DRL in addressing complex urban transportation challenges. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Robotic Automation System for Indoor Greenhouse Applications

Robotic Automation System for Indoor Greenhouse Applications

引用

IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

作者： Josiah Yang Qi Lai Chean Hung Hudyjaya Siswoyo Jo Justin Sia Wei Kiat Evon Lim Wan Ting Michelle Dunn Faculty of Engineering Computing and Science Swinburne University of Technology Kuching Malaysia Faculty of Engineering Computing and Science Swinburne University of Technology Melbourne Australia

ISBN: (数字)9798350340204

ISBN: (纸本)9798350340211

As the world advances, the global population is projected to reach an estimated 9 billion by 2050, leading to a higher demand for food. To boost agricultural production without harming the environment, new and sustainable technologies are essential for improving efficiency and output. Precision farming has existed for years, but as its efficiency improves, scalability on large farms has emerged as a significant challenge. This project proposes using a mobile robotic system that can be deployed in existing greenhouses with minor changes and little additional infrastructure to assist current laborers in the agricultural sector. This paper would focus on the development and early onsite testing of the proposed robot in an indoor greenhouse environment. The robot successfully interacted with plants in 105 out of 135 test runs in a laboratory setting giving a success rate of 75.5%. Onsite testing where done with similar configurations to the laboratory settings to identify potential problems in a different environment.

关键词： Automation Scalability Laboratories Greenhouses Production Robots Testing IEEE Regions Farming

来源：评论

学校读者我要写书评

暂无评论

A Novel Cluster Analysis-Based Crop Dataset Recommendation Method in Precision Farming

引用

Computer Systems Science & engineering 2023年第9期46卷 3239-3260页

作者： K.R.Naveen Kumar Husam Lahza B.R.Sreenivasa Tawfeeq Shawly Ahmed A.Alsheikhy H.Arunkumar C.R.Nirmala Department of Computer Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Science&Engineering Bapuji Institute of Engineering&TechnologyDavangereKarnatakaIndia Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArarSaudi Arabia

Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making *** agriculture uses datamining to advance agricultural *** farmers aren’t getting the most out of their land because they don’t use precision *** harvest crops without a well-planned recommendation *** crop production is calculated by combining environmental conditions and management behavior,yielding numerical and categorical *** existing research still needs to address data preprocessing and crop categorization/***,statistical analysis receives less attention,despite producing more accurate and valid *** study was conducted on a dataset about Karnataka state,India,with crops of eight parameters taken into account,namely the minimum amount of fertilizers required,such as nitrogen,phosphorus,potassium,and pH *** research considers rainfall,season,soil type,and temperature parameters to provide precise cultivation recommendations for high *** presented algorithm converts discrete numerals to factors first,then reduces ***,the algorithm generates six datasets,two fromCase-1(dataset withmany numeric variables),two from Case-2(dataset with many categorical variables),and one from Case-3(dataset with reduced factor variables).Finally,the algorithm outputs a class membership allocation based on an extended version of the K-means partitioning method with lambda *** presented work produces mixed-type datasets with precisely categorized crops by organizing data based on environmental conditions,soil nutrients,and ***,the prepared dataset solves the classification problem,leading to a model evaluation that selects the best dataset for precise crop prediction.

关键词： Data mining crop prediction k-prototypes k-means cluster machine learning

来源：评论

学校读者我要写书评

暂无评论

Sociodemographic Factors Associated with Cyberbullying Experience and Practice Among Youths in Malaysia

引用

Journal of Technology in Behavioral Science 2024年 1-11页

作者： Lim, Willone Lau, Bee Theng Fu, Swee Tee Tee, Mark Kit Tsun Islam, Fakir M. Amirul Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus Sarawak Kuching 93350 Malaysia School of Health Sciences Swinburne University of Technology Hawthorn 3122 VIC Australia

Cyberbullying is a complex issue among youth, yet, while adolescent victimization is well-studied, little is known about what causes youth to perpetrate cyberbullying in Malaysia. This quantitative study examines the association of sociodemographic factors and the use of social media with cyberbullying experiences and practices among youth in Malaysia. A baseline survey, conducted from July to December 2023 as part of an intervention program, gathered data from 309 participants aged 18 to 30 via an online survey. Statistical analyses, including logistic regression, were conducted to determine the relationships between sociodemographic factors, social media use, and cyberbullying behaviors. Of the total participants, the mean age was 21 years, 201 (65%) were female, 241 (78%) were undergraduate students. Among them, 302 (97.7%) were aware of cyberbullying, 252 (81.5%) witnessed it, 179 (58%) experienced it, and 51 (17%) participated in it. Females had higher odds of experiencing cyberbullying than males (odds ratio (OR), 2.67;95% confidence interval (95% CI), 1.64–4.33), while males were more likely to engage in cyberbullying. Students and unemployed individuals had higher risks of experiencing cyberbullying. Heavy social media users (8 + hours/day) were at increased risk (OR, 16.2;95% CI, 5.31–49.4), with Facebook use linked to higher cyberbullying exposure. There is a need for targeted interventions and policies to safeguard females and students to support their well-being. Limiting social media usage may serve as a preventive measure. Further longitudinal research to deepen understanding and collaboration among researchers, educators, and policymakers is crucial to creating safer digital environments for youth. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Cyberbullying Experience Practice Risk factors Youth

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：