检索结果-内蒙古大学图书馆

3rd Information technology to Enhance e-Learning and Other Application, IT-ELA 2022

作者： Haji, Lailan M Zeebaree, Subhi R. M. Ageed, Zainab Salih Ahmed, Omar M. Sadeeq, Mohammed A. M. Shukur, Hanan M. University of Zakho Faculty of Science Computer Science Dep. Duhok Iraq Technical College of Engineering Duhok Polytechnic University Energy Eng. Dept. Duhok Iraq College of Science Nawroz University Computer Science Dept. Duhok Iraq Zakho Technical Institute Duhok Polytechnic University Information Technology Dept. Duhok Iraq Technical College of Administration Duhok Polytechnic University ITM Dept. Duhok Iraq Al-Kitab University Computer Engineering Dept. Kirkuk Iraq

ISBN: (纸本)9798350334968

The field of research known as 'parallel processing' examines architectural and algorithmic methods for increasing the efficiency and other desirable qualities (such as cost-effectiveness and reliability) of computers by exploiting many forms of concurrency. The development of multi-core CPUs has opened the door to novel strategies for boosting system performance via parallelism. Increasing the number of concurrent threads greatly affects the time cost. While increased parallelism might reduce calculation time, the associated synchronization costs would likely be prohibitive for most applications. In this article, we'll go through the first half of the process, which involves gathering requirements and designing a prototype;the second half, which involves monitoring and managing a program that can run on a wide range of multicore system architectures, including those with (2, 4, and 8 CPUs). A shared-memory parallel processing method was proposed and built to show off the system's full potential. The implications of multi-core systems on overall program execution time and parallel processing in shared-memory systems provide the backbone of this investigation. © 2022 IEEE.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

Comparison of Traditional ML Algorithms for Energy Consumption Prediction Models

Comparison of Traditional ML Algorithms for Energy Consumpti...

引用

2022 IEEE Future Networks World Forum (FNWF)

作者： Rebeca Estrada Víctor Asanza Danny Torres Irving Valeriano Daniel Alvarado Information Technology Center & Electrical Eng. and Computer Science Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador Electrical Eng. and Computer Science Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador Information Technology Center Escuela Superior Politécnica del Litoral Guayaquil Ecuador Mechanical and Production Sciences Eng. Dep. Escuela Superior Politécnica del Litoral Guayaquil Ecuador

Data centers consume a large amount of energy to meet the increasing demand for IT infrastructure and software due to the IT equipment and cooling infrastructure involved. Therefore, it is necessary to have energy consumption control strategies for DC computer equipment that will allow infrastructure upgrades to reduce energy consumption and to meet the requirement of Green IT. In this way, energy consumption is reduced and the use of technological resources can be optimized. In this paper, we propose to evaluate several traditional Machine Learning algorithms as prediction models using three different temporal windows (i.e. minute, hour and day) taking into account several features such as voltage, energy, frequency, current, power, power factor, and temperature. A comparison of the root square mean error (RMSE) during the validation stage is carried out in order to select the most appropriate algorithm for each time window. In addition, running times are calculated to determine the feasibility of the selected algorithms. Moreover, the suitable predictive model can be the key to the ensure a fair distribution of the workload among the different servers in a Datacenter.

关键词： Energy consumption Data centers Machine learning algorithms Temperature Computational modeling Predictive models Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Improving Obstacle Avoidance Strategies in Autonomous Navigation of a Sailboat

Improving Obstacle Avoidance Strategies in Autonomous Naviga...

引用

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Pedro Paiva Luís Gomes Dep. Electrical and Computer Engineering NOVA School of Science and Technology — FCT-NOVA NOVA University Lisbon Caparica Portugal School of Science and Technology Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI) NOVA University Lisbon Caparica Portugal

This work explores the different mechanisms involved in creating a behavioural system for route planning and collision avoidance, taking into account the constraints imposed by the navigational characteristics of the sailboat. The implementation of these mechanisms is accompanied by an introduction to fundamental concepts, including Artificial Potential Fields, Histograms of Vector Fields, Navigation in the No-Go Zone, Differentiation of the Nature of Obstacles resulting in Different Operations, and the Constitution of Different Areas of Actuation. Finally, multiple simulations are conducted in a virtual environment to verify the resilience of the proposed navigation strategy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis of Persian Language: Review of Algorithms, Approaches and Datasets

arXiv

引用

arXiv 2022年

作者： Nazarizadeh, Ali Banirostam, Touraj Sayyadpour, Minoo Computer Eng. Dep. Faculty of Technology and Engineering Islamic Azad University Central Tehran Branch Tehran Iran Kharazmi University Tehran Iran

Sentiment analysis aims to extract people's emotions and opinion from their comments on the web. It widely used in businesses to detect sentiment in social data, gauge brand reputation, and understand customers. Most of articles in this area have concentrated on the English language whereas there are limited resources for Persian language. In this review paper, recent published articles between 2018 and 2022 in sentiment analysis in Persian Language have been collected and their methods, approach and dataset will be explained and analyzed. Almost all the methods used to solve sentiment analysis are machine learning and deep learning. The purpose of this paper is to examine 40 different approach sentiment analysis in the Persian Language, analysis datasets along with the accuracy of the algorithms applied to them and also review strengths and weaknesses of each. Among all the methods, transformers such as BERT and RNN Neural Networks such as LSTM and Bi-LSTM have achieved higher accuracy in the sentiment analysis. In addition to the methods and approaches, the datasets reviewed are listed between 2018 and 2022 and information about each dataset and its details are provided. Copyright © 2022, The Authors. All rights reserved.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Intelligent Recognition of Immune Cells: Analysis and Research

Intelligent Recognition of Immune Cells: Analysis and Resear...

引用

IEEE International Conference on e-Business Engineering (ICEBE)

作者： Chih-En Li Wei-Lun Liu Kun-Yi Lai Yu-Hsiang Chiang Xiaowei Yan Hao-Xiang Chen Hsu-Ching Li Wan-Shu Cheng Department of Electrical Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Institute for Systems Biology Seattle Washington U.S.A Dep. of Computer Science and Information Management Providence University Taichung Taiwan

Immunotherapy utilizes the potential of the patient's immune system to fight disease. T-lymphocytes have become the central focus of the immune system in the fight against cancer. One of the fundamental studies in immunotherapy is how to accurately identify various types of immune cells. Therefore, the study of immune-related cells will be an important reference for the treatment of COVID19 or other related diseases. In this paper, a series of experiments were conducted with COVID-19 patients as the starting point to design a strategy to identify the important subtypes of CD$4^{+}$T cells. In this paper, an intelligent machine learning algorithm is proposed according to the results of different experiments of linear and nonlinear dimension reduction algorithms, integrating the important characteristics of these two algorithms and improving the performance. Our experimental results show that the algorithm designed based on the front-end experiments can effectively distinguish the important lymphocytes. The proposed algorithm not only improves the performance, but also the dimension reduction procedure keeps the important features of both global and regional data. The experimental results of this paper will be beneficial for the subsequent analysis of the clustering in identifying important subtypes of CD$4^{+}$T cells. Most importantly, this wm significantly improve the procedure of manually integrating and labeling the recorded data after several tedious and monotonous analyses with external software.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Navigating Change: Enhancing Transportation Resilience in the Face of Climate Change - A Moroccan Case Study

Navigating Change: Enhancing Transportation Resilience in th...

引用

Public Safety technology (WFPST), IEEE World Forum on

作者： Soukaina El Maachi Rachid Saadane Abdellah Chehri Abdeslam Jakimi SIRC/LAGES-EHTP Department Hassania School of Public Works Casablanca Morocco Dep. Maths. and Computer Science Royal Military College Kingston Ontario Canada GL-ISI Team Faculty of Science and Technology Errachidia Moulay Ismail University Morocco Morocco

ISBN: (数字)9798350329148

ISBN: (纸本)9798350329155

Climate change manifested through extreme weather events such as hurricanes, floods, wildfires, and rising sea levels, poses significant threats to transportation infrastructure, disrupts services, and raises safety concerns with dangerous repercussions on the broader economic sector. Drawing insights from the Moroccan Ministry of Equipment and Water on climate change and resilience, we delve into the unique challenges and vulnerabilities faced by the transportation sector in Morocco amidst a changing climate. The study explores advanced technologies, particularly artificial intelligence (AI) and computer vision, to mitigate the impacts of climate change on transportation safety. Emphasizing the need for foresighted measures, we explore applications such as computer vision for weather pattern recognition by analyzing satellite imagery and real-time monitoring via video feeds. This approach enables accurate and timely predictions of extreme weather events, facilitating improved preparedness and response strategies. The findings contribute to the broader discourse on climate change adaptation and sustainable development, offering a nuanced perspective based on the specific realities of the Moroccan transportation scene.

关键词： Climate change Artificial intelligence Traffic control computer vision Sustainable development Resilience Weather forecasting Transportation Safety

来源：评论

学校读者我要写书评

暂无评论

Intelligent disease detection system for greenhouse with a robotic monitoring system 2

Intelligent disease detection system for greenhouse with a r...

引用

2nd International Conference on Advancements in Computing, ICAC 2020

作者： Fernando, Sandunika Nethmi, Ranusha Silva, Ashen Perera, Ayesh De Silva, Rajitha Abeygunawardhana, Pradeep K.W. Dep. of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe10115 Sri Lanka

ISBN: (纸本)9781728184128

Greenhouse farming plays a significant role in the agricultural industry because of its controlled climatic features. Recent examinations have stated that the mean creation of the yields under greenhouses is lessening due to disease events in the plants. These foods have become an imposing undertaking because these plants are being assaulted by different bacterial diseases, micro-organisms, and pests. The chemicals are applied to the plants intermittently without thinking about the necessity of each plant. Several problems have occurred in the greenhouse environment due to these causes. Therefore, there is a huge necessity for a system to detect diseases at an early stage. This research focused on designing a system to detect disease, which causes yellowish in greenhouse plants. Plant yellowing can be considered a significant problem of plants that grow under greenhouse-controlled environments. Through this research is focused on the most important and one of the most attention-grabbing crop tomato. There are specific diseases that cause yellowish the tomato plant, and they have been identified. The techniques utilized for early recognition of infection are image processing, machine learning, and deep learning. Index Terms-Greenhouses, Disease diagnosis, Image processing, Machine Learning, Deep Learning, Tomato Farming. © 2020 IEEE.

关键词： Greenhouses

来源：评论

学校读者我要写书评

暂无评论

AI based greenhouse farming support system with robotic monitoring

AI based greenhouse farming support system with robotic moni...

引用

2020 IEEE Region 10 Conference, TENCON 2020

作者： Fernando, Sandunika Nethmi, Ranusha Silva, Ashen Perera, Ayesh Silva, Rajitha De Abeygunawardhana, Pradeep W. K. Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Malabe10115 Sri Lanka

ISBN: (纸本)9781728184555

Greenhouses plays a major role in today's agriculture since farmers can grow plants under controlled climatic conditions and can optimize production. The greenhouses are usually built in areas where the climatic conditions for the growth of plants are not optimal so requires some artificial setups to bring about productivity. Automating process of a greenhouse requires monitoring and controlling of the climatic parameters. This paper is an attempt to minimize the cost of maintaining greenhouse environments using new technologies. The end goal of this research an automated system to optimally monitor and control the environmental factors inside greenhouse by monitoring temperature, soil moisture, humidity and pH through a cloud connected mobile robot which can detect unhealthy plants using image processing and machine learning. The mobile robot navigates through a predefined map of greenhouse. Database server has created to store gathered real-time data. And the necessary accurate data represent by using proper application for analyzing. © 2020 IEEE.

关键词： Greenhouses

来源：评论

学校读者我要写书评

暂无评论

Drones as Pedagogical technology in STEAM Subjects: Analysis of Student Perceptions

Drones as Pedagogical Technology in STEAM Subjects: Analysis...

引用

EAEEIE Annual Conference,

作者： Igor Yepes Dante Augusto Couto Barone Computer Science Dep. Federal Institute of Education Science and Technology Farroupilha Frederico Westphalen/RS Brazil Interdisciplinary Center for New Technologies in Education Federal University of Rio Grande do Sul Porto Alegre/RS Brazil

This research investigates the use of drones as a pedagogical technology in STEAM (Science, technology, Engineering, Arts, and Mathematics) subjects at a federal school in Frederico Westphalen, Brazil. Through a methodology involving pre and post-tests, workshops, and interviews with students, the study revealed a positive impact on engagement and meaningful learning for the students. The findings suggest that drones have the potential to improve teaching in STEAM areas and call for further research in the field.

关键词：

来源：评论

学校读者我要写书评

暂无评论

FVMM: Fast VM Migration for Virtualization-based Fault Tolerance Using Templates

FVMM: Fast VM Migration for Virtualization-based Fault Toler...

引用

IEEE International Conference on Cloud Computing technology and Science (CloudCom)

作者： Wen-Hsiu Tsai Po-Jui Tsao Che-Rung Lee Dep. of Computer Science National Tsing Hua University Hsinchu Taiwan Information and Communications Research Lab. Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (纸本)9781665463683

In the era of cloud computing, virtualization based fault tolerance that utilizes the continuous virtual machine (VM) migration to synchronize a VM and its remote replica is a common technique to achieve high availability. However, traditional live VM migration, whose goal is to minimize the system downtime, has a long duration owing to the expense of the pre-copy for machine status and memory content, which increases the period of failover when failures occur. In this paper, we proposed a new VM migration method, called Fast VM Migration (FVMM), which utilizes the templating technique to accelerate the VM migration by reducing the cost of pre-copy. The templating technique that creates VMs from a master copy, called a template, is a usually used to dep.oy many similar VMs in a large virtual environment. FVMM employs VM templating to mitigate the cost of pre-copy. Its implementation is optimized with six new techniques: SFVMM and LFVMM, COW templating, continuous templating, asynchronous transmission buffering, VM recovery from continuous templating, and templating regularly. We also applied FVMM for virtualization based fault tolerance to accelerate the failover process. Experimental results show that FVMM is more than 56 times faster than pre-copy live migration for a VM with 16GB, and can reduce upto 32% of the system downtime and the fault tolerance resynchronization time comparing to the methods using pre-copy live migration.

关键词： computers Fault tolerance Cloud computing Costs Fault tolerant systems Cows Virtual machining

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：