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检索条件"任意字段=IEEE International Conference on Developing and Managing Intelligent System Projects"

共 305 条记录，以下是61-70 订阅

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A Model for Optimizing the Portfolio of Hospital District Development projects Based on a Genetic Algorithm

A Model for Optimizing the Portfolio of Hospital District De...

引用

international Computer Sciences and Information Technologies (CSIT)

作者： Anatoliy Tryhuba Oksana Malanchuk Inna Tryhuba Roksolana Sholudko Dmytro Seleznov Department of Information Technologies Lviv National Environmental University Lviv Ukraine Department of Biophysics Danylo Halytsky Lviv National Medical University Lviv Ukraine Department of Information Technologies and Systems of Electronic Communications Lviv State University of Life Safety Lviv Ukraine Department of Industrial Engineering Lutsk National Technical University Lviv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

The article analyzes the healthcare sector's project management tools. It has been found that traditional optimization methods have limited effectiveness in solving complex multicriteria problems that are typical for managing a portfolio of projects to develop hospital districts. The expediency of developing a project portfolio optimization model based on a genetic algorithm is substantiated. The proposed model makes it possible to consider the main criteria, constraints, and goals underlying the achievement of maximum value. Based on the proposed optimization model, a decision support system (DSS) was developed. It allows us to effectively determine a rational scenario for the implementation of a portfolio of hospital district development projects. This system includes tools for analyzing, evaluating, and optimizing projects, taking into account various components of the project environment. Implementation of the SPDP can significantly improve the efficiency of management decision-making to optimize the scenario for the implementation of the hospital district development project portfolio, ensuring maximum value for stakeholders and sustainable development of the region's medical infrastructure.

关键词： Decision support systems Computer science Hospitals Optimization models Project management Stakeholders Sustainable development Information technology Portfolios Genetic algorithms

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Dynamic Learning: A system for Learning Offensive Content

Dynamic Learning: A System for Learning Offensive Content

引用

ieee international conference on Engineering Education: Innovative Practices and Future Trends (AICERA)

作者： Jeslin Rani Jiio Priyanga K. K Department Of Computer Science Christ College (Autonoumous) Irinjalakuda Kerala

In the digital era, online social networks have become an integral part of global communication. However, managing offensive language and content poses a significant challenge for these platforms. To address this issue, extensive research has focused on developing systems that can effectively detect and mitigate offensive language. This paper emphasizes two crucial aspects of offensive language detection: data preprocessing and feature selection. Data preprocessing involves removing noise, filtering out irrelevant information, and segmenting the text for analysis. Feature selection employs a fuzzy-based convolutional neural network (FCNN) to identify relevant features. Fuzzy logic handles uncertainty and ambiguity, while convolutional neural networks capture patterns and representations. By leveraging these techniques, offensive language detection systems can achieve accuracy and effectiveness, promoting a safer online environment. Continuous refinement of data preprocessing and feature selection methods contributes to the ongoing efforts to create inclusive and respectful digitalspaces.

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An IoT Based Smart Parking Lot Allocation & Monitoring system for Bidirectional Charging Station with V2G and G2V Operational Capability for Electric Vehicle in Matlab/Simulink

An IoT Based Smart Parking Lot Allocation & Monitoring Syste...

引用

international conference on Communication systems and Network Technologies (CSNT)

作者： Sarasij Adhikary Pabitra Kumar Biswas Electrical Engineering Department National Institute of Technology Mizoram Aizawl Mizoram India

ISBN: (数字)9798350305463

ISBN: (纸本)9798350305470

EV charging time is one of the significant limitations that has to be overcome by managing the charging time and utilizing the parking time of the EV. Except for commercial vehicles, most personal cars are parked 70 -80% of the time of the day. The cities have a parking lot management system to solve the parking problem by developing an intelligent IoT-based parking lot with a V2G-enabled system. The parking system is modelled to check the occurrence of the EV at the parking lot, and the V2G operation is implemented and presented in this paper. A bidirectional AC-DC converter transfers energy from the grid to the vehicle and vice versa. This MATLAB model is connected to a cloud-based platform named Things Speak to check the system occupancy with the expected completion time. This system enables the EV and the charging station to share different parameters through the cloud. This model is validated by checking the system through a web application/android application, and validation of the V2G model is implemented and analyzed.

关键词： Vehicle-to-grid Analytical models Costing Predictive models Mathematical models Resource management Internet of Things

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managing Renewable Energy In The Context Of Southeast Asia: A Case Study Of Vietnam 5

Managing Renewable Energy In The Context Of Southeast Asia: ...

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5th ieee international conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Ha, Van Hong Thi Nong, Nguyen Bang Nguyen, Ha Thi Van Vietnam Academy of Social Sciences Vietnam Institute of Economics Hanoi Viet Nam Vietnam Academy of Social Sciences Institute of Anthropology Hanoi Viet Nam

ISBN: (纸本)9798331542559

Since the 2021 United Nations Climate Change conference, the Asia-Pacific region has vigorously developed the renewable energy (RE) sector in Agriculture, Construction, Industry, Transport, and Power to solve climate problems. According to a report by the ADB, Vietnam has the most significant RE growth rate in Southeast Asia, with 16.5 GW in solar PV capacity compared to Thailand (3.2), Malaysia (2.6), and the Philippines (1.4). As of 2021, RE accounted for 11.8% of the country's electricity capacity. Vietnam has become a symbol of Southeast Asia in the transition of RE, serving socioeconomic development and adapting to climate change towards Net Zero. RE development in Vietnam is associated with promulgating many RE policies to turn the potential into reality. However, this overdevelopment creates unaccounted consequences, such as environmental and social impacts and the connection of the national power system. This article presents the issues of RE management in Vietnam over the past ten years. The article includes parts of policies, implementation processes, and environmental and social issues. The article consists of recommendations for further research. © 2024 ieee.

关键词： Construction industry

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intelligent parking lot control system based on Alibaba Cloud platform and machine learning 6

Intelligent parking lot control system based on Alibaba Clou...

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6th ieee international conference on intelligent Computing and Signal Processing, ICSP 2021

作者： Liao, Wendong Xie, Liang Xi, Jie Bai, Yan Zhang, Teng Wu, Yuqiong Jiangxi University of Finance and Economics College of Software and Internet of Things Engineering Nanchang China

ISBN: (纸本)9780738143705

With the development of science and technology, research into intelligent parking lot management systems has gradually emerged. However, most research projects are aimed at solving the problem of drivers looking for parking spaces, and there is less research on intelligent parking lot control and intelligent identification of surveillance videos. Science and technology are developing and changing rapidly. It is an everlasting trend to continuously solve and optimize practical social problems with technologies that closely follow the trend of the times. This article proposes a low-cost, high-efficiency, and easy-to-manage parking management system - a parking management system based on the Alibaba Cloud platform and machine learning. Through machine learning technology, the number of vehicles entering a parking lot is counted and license plate numbers are recognized, which is not only convenient for parking lot management, but also helpful for drivers to judge and find parking spaces;through data transfers on the Alibaba Cloud platform, dual control of the parking lot via app and voice control can be achieved. Internal electronic devices not only facilitate the administrators' management work, but also makes parking lots intelligent. © 2021 ieee.

关键词： Data transfer

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Omnibot: A Scalable Vision-Based Robot Swarm Platform

Omnibot: A Scalable Vision-Based Robot Swarm Platform

引用

international conference on Control and Automation (ICCA)

作者： Zhao Ma Jiachen Liang Hongyi Wang Shiliang Guo Peidong Huo Yin Zhang Shiyu Zhao Intelligent Unmanned Systems Laboratory School of Engineering at Westlake University Hangzhou China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Introducing vision sensing into swarms presents three challenges for developing robot platforms. First, the vision system requires a wide field of view to perceive surrounding robots. Second, vision algorithms demand high computational power, which poses a challenge for real-time vision-in-the-loop simulation. Third, as the swarm scale increases, managing the system becomes increasingly demanding. The main contribution of this paper is the development of a novel mobile robot swarm platform to overcome these challenges. 1) Each robot features a 360-degree omnidirectional vision system comprising four cameras, allowing each robot to detect and interact with the surrounding robots. 2) It has a novel ROS-based distributed swarm simulation system, which can effectively utilize the onboard computational resources of multiple robots to achieve parallel vision-in-the-loop simulation. 3) It features a novel swarm management system that allows real-time monitoring and debugging of multiple robots. These innovative designs provide a novel swarm platform that can facilitate the study of versatile vision-based swarm tasks.

关键词： Machine vision Robot vision systems Feature extraction Real-time systems Software Hardware Sensors

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Availability assessment for a multi-AGV system based on simulation modeling approach

Availability assessment for a multi-AGV system based on simu...

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2021 ieee international conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Jodejko-Pietruczuk, Anna Werbinska-Wojciechowska, Sylwia Wroclaw University of Science and Technology Dept. of Operation and Maintenance of Technical Systems Wroclaw Poland

ISBN: (纸本)9781665412629

One of the key issues during the autonomous robots' operational tasks performance is ensuring their operational availability. However, the reliability and maintenance issues of automated guided vehicles (AGV) still need to be investigated to provide system efficiency and stability. Therefore, the article focuses on developing a Monte Carlo simulation model for a multi-AGV system used for the system availability evaluation. The sensitivity analysis for investigating the direct relations between maintenance and operational parameters and availability ratio level is performed based on the developed model. The detailed analysis of the achievements in this area gives the possibility to identify research gaps and possible future research directions for autonomous warehouse designing processes. © 2021 ieee.

关键词： Warehouses

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An Empirical Study for Common Language Features Used in Python projects 28

An Empirical Study for Common Language Features Used in Pyth...

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28th ieee international conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Peng, Yun Zhang, Yu Hu, Mingzhe Univ Sci & Technol China Lab Intelligent Networking & Knowledge Engn LINKE Hefei Peoples R China

ISBN: (纸本)9781728196305

As a dynamic programming language, Python is widely used in many fields. For developers, various language features affect programming experience. For researchers, they affect the difficulty of developing tasks such as bug finding and compilation optimization. Former research has shown that programs with Python dynamic features are more change-prone. However, we know little about the use and impact of Python language features in real-world Python projects. To resolve these issues, we systematically analyze Python language features and propose a tool named PYSCAN to automatically identify the use of 22 kinds of common Python language features in 6 categories in Python source code. We conduct an empirical study on 35 popular Python projects from eight application domains, covering over 4.3 million lines of code, to investigate the the usage of these language features in the project. We find that single inheritance, decorator, keyword argument, for loops and nested classes are top 5 used language features. Meanwhile different domains of projects may prefer some certain language features. For example, projects in DevOps use exception handling frequently. We also conduct in-depth manual analysis to dig extensive using patterns of frequently but differently used language features: exceptions, decorators and nested classes/functions. We find that developers care most about ImportError when handling exceptions. With the empirical results and in-depth analysis, we conclude with some suggestions and a discussion of implications for three groups of persons in Python community: Python designers, Python compiler designers and Python developers.

关键词： Python

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Towards an Effective Tool Wear Monitoring system with an AI Model Management Platform

Towards an Effective Tool Wear Monitoring System with an AI ...

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ieee international conference on Industrial Informatics (INDIN)

作者： Jian Wen Chen Meng Shiun Tsai Che Lun Hung Department of Computer Science National Tsing Hua University Hsinchu Taiwan Department of Mechanical Engineering National Taiwan University Taipei Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Automated monitoring of tool wear is crucial for maintaining product quality. Furthermore, implementing AI techniques for real-time tool monitoring involves not only developing models but also managing their versions, avoiding the issue of models becoming less accurate as the properties of the machinery change over time. Consequently, this study develops a tool wear prediction system integrated with an artificial intelligent (AI) model management platform. First, this system uses various machine learning models to extract diverse signal features from sensor fusion, thereby boosting the accuracy of tool wear prediction. Secondly, the AI Models Management Platform comprises the C# programming language, Neural Networks Processing Unit (NPU) board, and Docker on both user and server sides, enhancing industrial processes and enabling real-time analysis of sensor data. According to these results, the Ensemble Learning method within the machine learning model demonstrates superior performance, yielding an average root mean squared error (RMSE) of $\mathbf{0.000185}\ mm^intelligent$ . Additionally, AI model management platform efficiently handle various model versions and streamline data training processes, empowering users to select suitable models and thereby enhancing system robustness.

关键词： Training Accuracy Working environment noise Predictive models Sensor fusion Feature extraction Data models Robustness Real-time systems Monitoring

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A Blockchain based solution for managing Transplant Waiting Lists and Medical Records 16

A Blockchain based solution for Managing Transplant Waiting ...

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ieee 16th international conference on intelligent Computer Communication and Processing (ICCP)

作者： Daniel, Ioana Andreea Pop, Claudia Anghel, Ionut Antal, Marcel Cioara, Tudor Tech Univ Cluj Napoca Comp Sci Dept Cluj Napoca Romania

ISBN: (纸本)9781728190808

Nowadays, the medical domain is suffering from a lack of transparency, security, and immutability. developing a decentralized application based on blockchain technology can be helpful in achieving the requirements that will solve the identified problems. This paper proposes a blockchain-based solution for managing the waiting list for a transplant as well as a solution for sharing medical records between parties. Sharing medical records between patients and doctors represents a sensitive process since it must be secured, and it addresses a challenging requirement in terms of storage scalability which is approached by using a distributed file system. Results show that our solution allows the waiting list to be more trustful and increases the patients' chances for receiving the transplant and at the same time assures the owner of the medical records, reducing the chances of attacks for stealing medical data.

关键词： Blockchain Ethereum distributed file system medical records transplant waiting list

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