检索结果-内蒙古大学图书馆

4th International Conference on Advancements in Computing, ICAC 2022

作者： Legrand, T.R. Bandara, K.M.R.A.I. Stefania Crishani, J.A.D. Uvindu, L.W.P. Amarasena, Nelum Kasthurirathna, Dharshana Department of Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Sri Lanka is one of the top tourist destinations in the world. However, tourists face various inconveniences due to the obsolescence of facilities. There are various tools designed to solve such problems. But they are scattered in different places and users have to use different tools. The biggest issue in the tourist sector is that travelers are unable to get the most out of their tours since there may be days when a large number of people visit the same location, causing the location to become overcrowded, and preventing tourists from enjoying their visit as anticipated. There are seasons when natural disasters occur, as well as human-centered crises. Also, there are situations when travelers feel helpless because they are unable to find the best tour guide for them. We developed a cost-effective, automatic, and efficient Machine Learning-based recommendation system as a result of this research. Based on past data on tourists and data received from the SLTDA, this research can provide the best trip plan with the tour guide and provide destination news alerts on regular basis. Furthermore, in order to achieve the best accuracy through the system, unique machine learning approaches were used in this study. © 2022 IEEE.

关键词： Obsolescence

来源：评论

学校读者我要写书评

暂无评论

Sustainable Water Futures: Enhancing Efficiency And Conservation In Madinah AL Munawara

Journal of Applied Science and Engineering

引用

Journal of Applied Science and engineering 2024年第10期28卷 2027-2042页

作者： Syed, Toqeer Ali Naqash, Muhammad Tayyab Nawaz, Waqas Namoun, Abdallah Muhammad, Munir Azam Faculty of Computer and Information System Islamic University of Madinah Saudi Arabia Civil Engineering Department Faculty of Engineering Islamic University of Madinah Madinah42351 Saudi Arabia AI Center Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351 Saudi Arabia Khwaja Fareed University of Engineering & Information Technology Faculty of Computer and Information System Punjab Rahim Yar Khan Pakistan

Water resource management worldwide faces significant challenges, including high consumption rates, scarcity, and ageing infrastructure. This paper proposes a comprehensive approach to address these issues through five key solutions. Advanced Metering Infrastructure (AMI) first facilitates real-time data collection and consumer awareness campaigns. Secondly, wastewater recycling and reuse are promoted by upgrading wastewater treatment plants and fostering public-private partnerships. Thirdly, reducing network losses is achieved through leak detection systems and regular maintenance. Fourthly, policy enhancement and regulatory frameworks are strengthened by implementing regulations for new developments and incentives for water-saving technologies. Lastly, community engagement and education initiatives are undertaken to promote sustainable water practices. This multifaceted strategy aims to improve water conservation, efficiency, and resilience of the water supply system. This paper proposes solutions that can be applied to the Madinah AL Munawara region of Saudi Arabia, an area of utmost importance, demonstrating the applicability and effectiveness of these solutions in addressing regional water management challenges. © The Author(’s).

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Large Language Models for Water Distribution Systems Modeling and Decision-Making

arXiv

引用

arXiv 2025年

作者： Goldshtein, Yinon Perelman, Gal Schuster, Assaf Ostfeld, Avi Asce, F. Faculty of Computer Science Technion – Israel Institute of Technology Haifa32000 Israel Faculty of Civil and Environmental Engineering Technion – Israel Institute of Technology Haifa32000 Israel

The design, operations, and management of water distribution systems (WDS) involve complex mathematical models. These models are continually improving due to computational advancements, leading to better decision-making and more efficient WDS management. However, the significant time and effort required for modeling, programming, and analyzing results remain substantial challenges. Another issue is the professional burden, which confines the interaction with models, databases, and other sophisticated tools to a small group of experts, thereby causing non-technical stakeholders to depend on these experts or make decisions without modeling support. Furthermore, explaining model results is challenging even for experts, as it is often unclear which conditions cause the model to reach a certain state or recommend a specific policy. The recent advancements in Large Language Models (LLM) open doors for a new stage in human–model interaction. This study proposes a framework of plain language interactions with hydraulic and water quality models based on LLM-EPANET architecture. This framework is tested with increasing levels of complexity of query to study the ability of LLMs to interact with WDS models, run complex simulations, and report simulation results. The performance of the proposed framework is evaluated across several categories of queries and hyperparameter configurations, demonstrating its potential to enhance decision-making processes in WDS management. © 2025, CC BY.

关键词： Water distribution systems

来源：评论

学校读者我要写书评

暂无评论

Hybrid Segmentation Approach for Different Medical Image Modalities

引用

computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

来源：评论

学校读者我要写书评

暂无评论

A High-Performance MTJ-LUT Circuit Using 4T1M Architecture 17

A High-Performance MTJ-LUT Circuit Using 4T1M Architecture

引用

17th IEEE International Conference on Solid-State and Integrated Circuit technology, ICSICT 2024

作者： Pan, Yu Zhang, Yuejun Guo, Shuaicheng Tian, Yuanxin Hong, Bo Fang, Rui Wen, Liang Ding, Yong Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China China Coast Guard Academy Department of Electronic Technology Ningbo315211 China College of Integrated Circuits Zhejiang University Hangzhou310058 China

ISBN: (纸本)9798350361834

As fundamental components of programmable logic circuits, Lookup Table (LUT) circuits enable the implementation of arbitrary combinational logic. The volatility, standby power dissipation, and propagation delay of LUT circuits critically affect the performance of programmable logic circuits. In order to address the problems of circuit volatility, propagation delay and standby power dissipation, a high-performance Magnetic Tunnel Junction LUT (MTJ-LUT) circuit design scheme is proposed based on the 4T1M structure. According to the characteristics of MTJ principle, and comparing with the classical MTJ-LUT memory cell, MTJ-LUT memory module based on 4T1M structure is proposed;Based on the LUT circuit principle of 4T1M structure, a circuit architecture with current mirror bias circuitry is proposed to adopt the compliant reference resistor, and the steady-current-powered reading mode is used to achieve the optimal reading operation and reduce the delay;The circuit function is implemented in SMIC 40nm process using SPICE simulation tool. The experimental results show that the propagation delay and power dissipation of the MTJ-LUT circuit proposed are reduced by 72% and 15%, respectively, compared with the conventional MTJ-LUT circuit. © 2024 IEEE.

关键词： Delay circuits

来源：评论

学校读者我要写书评

暂无评论

Hybrid Multi-User Based Cloud Data Security for Medical Decision Learning Patterns 1

Hybrid Multi-User Based Cloud Data Security for Medical Deci...

引用

1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Gupta, Manish Khan, Ihtiram Raza Gomathy, B. Samal, Ansuman Department of Computer Science & Engineering Moradabad Institute of Technology Moradabad India Department of Computer Science Jamia Hamdard Delhi India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Faculty of Hospitality and Tourism Management Siksha O Anusandhan Deemed to be University Odisha Bhubaneswar India

ISBN: (纸本)9781607685395

Machine learning plays a vital role in the real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, these clouds based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers in order to store medical records or machine learning patterns for decision making. Due to high computational memory and time, these cloud systems require an efficient data security framework in order to provide strong data access control among the multiple users. In this paper, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phase's i.e data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering and security framework has better computational efficiency than the conventional approaches on large medical decision patterns. © The Electrochemical Society

关键词： Cloud Computing Hybrid Multi Model Medical Patterns

来源：评论

学校读者我要写书评

暂无评论

Unit Commitment and Load Dispatch Problems Considering Inertial Response of Dispatchable Generators

Unit Commitment and Load Dispatch Problems Considering Inert...

引用

2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Shigenobu, Ryuto Ito, Yuhi Ito, Masakazu Takano, Hirotaka Orihara, Dai Goda, Tadahiro Taoka, Hisao University of Fukui Faculty of Engineering Dept. of Electrical Electronic and Computer Engineering Fukui Japan Gifu University Faculty of Engineering Dept. of Electrical Electronic and Computer Engineering Gifu Japan Fukushima Renewable Energy Institute Aist National Institute of Advanced Industrial Science and Technology Fukushima Japan

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

The growth in penetration of renewable energy sources leads to reduction in the number of grid-tied dis-patchable synchronous generators. Since the contributions of non-dispatchable, renewable energy-based generators to both grid inertia and grid frequency controllability are significantly small, it becomes important to secure sufficient operational margins in the operation scheduling phase. This paper presents a framework that integrates constraints for the inertial response and the primary frequency control to the unit commitment and economic load dispatch (UC-ELD) problem. The authors' proposal contributes cooperative operations of dispatchable and non-dispatchable generators in the levels of inertial and primary responses although the UC-ELD is a framework for operations in longer period. Through numerical simulations and discussion on their results, the validity of the authors' proposal is verified. © 2022 IEEE.

关键词： Renewable energy resources

来源：评论

学校读者我要写书评

暂无评论

AI Bot to Increase the Accuracy and Efficiency of Hiring Process of Business Organizations

AI Bot to Increase the Accuracy and Efficiency of Hiring Pro...

引用

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Dilusha, N.H.A.S. Weerasinghe, E.J.K.D. Chamuditha, S.M.A. Wijekoon, K.W.M. Thelijjagoda, Samantha Giguruwa, Nishantha Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Computer System Engineering Malabe Sri Lanka College of Sustainability and Tourism Ritsumeikan Asia Pacific University Oita Prefecture Beppu Japan

ISBN: (纸本)9798331543617

Recruitment in most organizations is normally a rather inefficient process where it takes quite a long time to match the right candidate to a given job. In this research, AI-based hiring system is recommended to improve the efficiency and accuracy of the hiring process with the help of NLP and machine learning algorithms. Employment enabling processes such as CV filtering, skill evaluation and personality profiling as well as job matching are achieved by the system. An NLP-based tool is used for short listing of CVs, assessment quizzes are used to evaluate different skills and qualifications of the candidates and chatbot enables communication between candidates and HRs, while an AI bot is used to complete different document verifications' processes. Recruitment operation is made easier and efficient, and matching of candidates to the available jobs is done better since it is less time-consuming and energy-demanding, giving a solution that may be implemented on a large scale. Further improvements are to be made in the fine tuning of algorithms, enlargement of comprehensiveness of systems and the implementation of actual sample cases before the introduction into the marketplace. © 2024 IEEE.

关键词： Bot (Internet)

来源：评论

学校读者我要写书评

暂无评论

Improving Lithium-Ion Battery Life Prediction using CEEMDAN Decomposition and Machine Learning 5

Improving Lithium-Ion Battery Life Prediction using CEEMDAN ...

引用

5th International Symposium on computer engineering and Intelligent Communications, ISCEIC 2024

作者： Li, Xinxin Xie, Kun An, Ziliang Zuo, Yiwen School of Rail Transportation Shanghai Institute of Technology Shanghai China Shanghai Urban Construction Vocational College Faculty of Urban Operations and Management Shanghai China School of computer and Information Engineering Shanghai Polytechnic University Shanghai China

ISBN: (纸本)9798331518677

The remaining useful life (RUL) of lithium-ion batteries is a key indicator for the optimal design of battery management systems and ensuring equipment safety. Most existing RUL prediction methods retain only the trend term of the capacity curve, neglecting the potential information in high-frequency fluctuations. Therefore, this paper presents a combined model based on adaptive white noise complete integrated empirical mode decomposition (CEEMDAN), gradient boosted decision tree (GBDT), and long-short-term memory neural network (LSTM). CEEMDAN is employed to reduce noise and extract fluctuation components at different frequencies. GBDT assigns weights to each component to assess its contribution to the interpretation of the original data. The final prediction is obtained by weighted reconstruction of the LSTM prediction results for each component. The experimental results show that using the NASA lithium battery dataset, the CEEMDAN-GBDT-LSTM model significantly improves RUL prediction accuracy and outperforms single models in predictive performance. © 2024 IEEE.

关键词： NASA

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Continuity-Aware Refinement Network for Weakly Supervised Video Anomaly Detection

Multi-Scale Continuity-Aware Refinement Network for Weakly S...

引用

2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Gong, Yiling Wang, Chong Dai, Xinmiao Yu, Shenghao Xiang, Lehong Wu, Jiafei Ningbo University Faculty of Electrical Engineering and Computer Science China Loctek Ergonomic Technology Corporation China SenseTime Research China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

In many previous work, weakly supervised video anomaly detection is formulated as a multiple instance learning (MIL) problem, which represents the video as a bag of multiple instances. However, most MIL-based frameworks only focused on identifying anomalous events from the given instances, without considering the event continuity. Motivated by the fact that abnormal events tend to be more continuous in real-world videos, a Multi-scale Continuity-aware Refinement Network (MCR) is proposed in this paper. It utilizes the property of multi-scale continuity to refine anomaly scores by introducing differential contextual information of instances. At the same time, multi-scale attention is designed to produce a video-level weights in order to select the proper scale and fuse all scores at different scales. Experimental results of MCR show noticeable improvement on two public datasets, specifically obtaining a frame-level AUC 94.92% on ShanghaiTech dataset. © 2022 IEEE.

关键词： Anomaly detection

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：