检索结果-内蒙古大学图书馆

2023 International Conference on computer, Electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Jayanthi, R. Christinal, A. Hepzibah Hephzibah, R. Shekinah, T. Bajaj, Chandrajit Chandy, D. Abraham Karunya University Department of Mathematics Coimbatore India Loyola - Icam College of Engineering and Technology Department of Computer Science and Engineering Chennai India University of Texas Computational Applied Mathematics Chair in Visualization Austin United States Karunya University Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350338003

Brain tumor classification is a critical task in medical imaging, where the early and accurate detection of brain tumors is crucial for patient treatment and survival. In recent years, Machine Learning techniques have emerged as a promising approach for automated brain tumor classification. In this paper, we investigate the performance of three ML classifiers - Support Vector Machine, Naïve Bayes, and an ensemble of SVM and Naïve Bayes - for the two-class classification of brain tumor data into a tumor and no tumor classes. Our experiments demonstrate that the ensemble of SVM and Naïve Bayes classifier achieved an accuracy of 97% outperforming the other classifiers. These results indicate that our ensemble classifier can be a powerful tool for the accurate and efficient classification of brain tumor data, potentially leading to improved patient outcomes. © 2023 IEEE.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Arabic Sentiment Analysis of Users’ Opinions of Governmental Mobile Applications

引用

computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： Mohammed Hadwan Mohammed A.Al-Hagery Mohammed Al-Sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent Analytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to analyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by analysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment analysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this analysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment analysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

来源：评论

学校读者我要写书评

暂无评论

Fault Tolerance in the Joint EDF-RMS Algorithm: A Comparative Simulation Study

引用

computers, Materials & Continua 2022年第9期72卷 5197-5213页

作者： Rashmi Sharma Nitin Nitin Deepak Dahiya University of Petroleum&Energy Studies(UPES) School of Computer ScienceEnergy Acres BuildingBidholiDehradun248007UttarakhandIndia Department of Electrical Engineering and Computer Science College of Engineering and Applied ScienceUniversity of Cincinnati2600 Clifton AveCincinnatiOH 45221United States College of Computer and Information Sciences(CCIS) Majmaah UniversityMajmaah11952Kingdom of Saudi Arabia

Failure is a systemic error that affects overall system performance and may eventually crash across the entire *** Real-Time Systems(RTS),deadline is the key to successful completion of the *** tasks effectively meet the deadline,it means the system is working in pristine ***,missing the deadline means a systemic fault due to which the system can crash(hard RTS)or degrade inclusive performance(soft RTS).To fine-tune the RTS,tolerance is the critical issue and must be handled with extreme *** article explains the context of fault tolerance with improvised Joint EDF-RMS algorithm in *** backup method has been derived to prevent the system from being recursively migrating the same *** any task migrates three times,this migrated task will get shifted to the backup *** backup queue assigns the task to a backup processor and is destined for final *** performance evaluation purposes,a relative graph between fault and failure rates,failure and total processor utilization along with other averages have been ***,these archived results are compared with fault-tolerant Earliest Deadline First(EDF)and Rate Monotonic Scheduling(RMS)algorithms independently in relatively similar *** comparisons show better performance against overloading conditions.

关键词： Fault tolerance joint edf-rms algorithm real-time systems(RTS) distributed systems migration

来源：评论

学校读者我要写书评

暂无评论

Reliability of Electronic Connections in Fast Chargers of Electric Vehicle 1

Reliability of Electronic Connections in Fast Chargers of El...

引用

1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Semwal, Priyanka Raturi Ekatpure, Shubham Rajendra Sharma, Merlyn Singh, Neelima Kumar, Anil Pandey, Bhumika Tula's Institute Dehradun Department of Electrical & Electronics Engineering Dehradun India Global Supply Chain in Semiconductor Manufacturing Kulicke and Soffa PA United States IIMT College of Engineering Department of ASH UP Grater Noida India Uttaranchal University Department of Computer Science and Engineering Dehradun India Physics Bharati Vidyapeeth's College of Engineering Dept. of Applied Science New Delhi India Bipin Tripathi Kumaon Institute of Technology Department of ECE Almora Dwarahat India

ISBN: (纸本)9798331518578

Global mobility is undergoing a dramatic change as cars fuelled by fossil fuels give way to those with zero or extremely low tailpipe emissions. Every one of the parts in big battery packs normally don't have similar properties and may corrupt essentially in view of assembling fluctuation and different elements. The performance and economics of the entire battery pack are impacted by the increased power waste from degraded battery modules. Additionally, the influence changes depending on the trip pattern. A variety of important factors, such as the age of the car, the internal resistance of the lithium-ion battery pack, awareness of grid energy pricing, and the distance driven, affect how much an electric vehicle (EV) costs to drive every day. It has used the grid's energy price data to optimise the cost of the typical driving cycle. Accurately forecasting battery behaviour reliability for the daily driving cycle is the aim of this project. The driver will be able to determine the best charging schedules, driving energy consumption, and excess battery energy with the aid of the reliability battery behaviour forecast. The driver can reduce the cost of travel both daily and over the battery's lifespan by having a previous understanding of the battery's behaviour, the grid's energy pricing, and the trip's duration. © 2025 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

IoT based Soil Nutrients Analysis and Monitoring System for Smart Agriculture 3

IoT based Soil Nutrients Analysis and Monitoring System for ...

引用

3rd International Conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Pyingkodi, M. Thenmozhi, K. Karthikeyan, M. Kalpana, T. Palarimath, Suresh Kumar, G. Bala Ajith Kongu Engineering College Department of Computer Applications Erode India Kristu Jayanti College Department of Computer Science Bengaluru India University of Technology and Applied Sciences Department of It Salalah Oman

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

Soil fertility is an important factor in determining soil quality as it reflects how well the soil can support plant growth in agriculture. Soil sensor and Arduino can be used to quickly determine the nutrient content of the soil. Nitrogen, phosphorus, and potassium are all considered as important nutrient source components. These components should be measured in order to determine how much extra nutrient content should be added to the soil in order to increase the crop fertility. Soil fertility can be detected by using NPK sensors. Soil nutrient concentration data can help us to determine whether the soil used to support plant production is nutrition deficient or abundant. The nutrient content of the soil samples can be obtained in various ways by using sensing element or mass spectrogram. However, the spectral analysis method is inconvenient, where the records are only 60-70% accurate. By comparing the spectrum analysis method with classic wet chemistry methods, the accuracy of the products needs to be fully resolved due to a scarcity of data. Hence, to detect soil nitrogen, phosphorous, and potassium, a soil NPK sensor should be used. By utilizing a soil NPK sensor, which is of limited cost, fast and easy, elevated, and transportable. Its advantage over a standard detection approach is that it provides extremely fast measurements with accurate data. This paper analyzes and compares different nutrient levels in soil by using kernel density estimation algorithm and machine learning. © 2022 IEEE.

关键词： Soils

来源：评论

学校读者我要写书评

暂无评论

Fruits Quality Detection using Deep Learning Models: A Meta- Analysis 3

Fruits Quality Detection using Deep Learning Models: A Meta-...

引用

3rd International Conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Pyingkodi, M. Thenmozhi, K. Karthikeyan, M. Chitra, K. Blessing, N.R. Wilfred Kumar, Sunny Kongu Engineering College Department of Computer Applications Erode India Kristu Jayanti College Department of Computer Science Bengaluru India University of Technology and Applied Sciences Department of It Ibri Oman

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

Deep learning has progressed significantly in recent years, making it an ideal choice for image processing applications. Recognition and classification of fruits using deep learning are considered as the most promising techniques for commercial and agricultural applications. Despite this, the researchers are still having difficulty in distinguishing fruits due to their similar colour, shape, and size. This research study intends to address some of the existing challenges by developing a novel framework for fruit identification and classification. Deep learning models such as U-Net, VGG19, and ResNet are used in this work to train and test these models. Here, two sets of data were used: pre-processed and augmented dataset. ResNet performs well with 98% accuracy on the initial set of data, but it consumes more time to compute. As a result, the deep learning models could recognize and classify 122 different types of fruits in real time. However, image augmentation will have no effect on the models' performance. © 2022 IEEE.

关键词： Fruits

来源：评论

学校读者我要写书评

暂无评论

GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images

引用

mathematical Biosciences and engineering 2024年第8期21卷 6847-6869页

作者： Aggarwal, Sonam Gupta, Isha Kumar, Ashok Kautish, Sandeep Almazyad, Abdulaziz S. Mohamed, Ali Wagdy Werner, Frank Shokouhifar, Mohammad Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Model Institute of Engineering and Technology J&K Jammu India Chandigarh University Punjab Mohali140413 India Department of Computer Engineering College of Computer and Information Sciences King Saud University P.O. Box 51178 Riyadh11543 Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt Applied Science Research Center Applied Science Private University Amman11931 Jordan Faculty of Mathematics Otto-von-Guericke University Magdeburg39016 Germany Institute of Research and Development Duy Tan University Da Nang550000 Viet Nam

Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of medical specialists. This capability is particularly crucial in the realm of gastrointestinal disorders, where even experienced gastroenterologists find the automatic diagnosis of such conditions using endoscopic pictures to be a challenging endeavor. Currently, gastrointestinal findings in medical diagnosis are primarily determined by manual inspection by competent gastrointestinal endoscopists. This evaluation procedure is labor-intensive, time-consuming, and frequently results in high variability between laboratories. To address these challenges, we introduced a specialized CNN-based architecture called GastroFuse-Net, designed to recognize human gastrointestinal diseases from endoscopic images. GastroFuse-Net was developed by combining features extracted from two different CNN models with different numbers of layers, integrating shallow and deep representations to capture diverse aspects of the abnormalities. The Kvasir dataset was used to thoroughly test the proposed deep learning model. This dataset contained images that were classified according to structures (cecum, z-line, pylorus), diseases (ulcerative colitis, esophagitis, polyps), or surgical operations (dyed resection margins, dyed lifted polyps). The proposed model was evaluated using various measures, including specificity, recall, precision, F1-score, mathew’s Correlation Coefficient (MCC), and accuracy. The proposed model GastroFuse-Net exhibited exceptional performance, achieving a precision of 0.985, recall of 0.985, specificity of 0.984, F1-score of 0.997, MCC of 0.982, and an accuracy of 98.5%. ©2024 the Author(s), licensee AIMS Press.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Sensor Based Smart Agriculture with IoT Technologies: A Review 12

Sensor Based Smart Agriculture with IoT Technologies: A Revi...

引用

12th International Conference on computer Communication and Informatics, ICCCI 2022

作者： Pyingkodi, M. Thenmozhi, K. Nanthini, K. Karthikeyan, M. Palarimath, Suresh Erajavignesh, V. Kumar, G. Bala Ajith Kongu Engineering College Department of Computer Applications Erode India Kristu Jayanthi College Department of Computer Science Bengaluru India University of Technology and Applied Sciences Department of It Salalah Oman

ISBN: (纸本)9781665480352

The IoT is a new technology trend used in almost every area thing, when connected to the internet and to each other, when you connect to the internet or interconnect, your entire system will be smarter. We have used IoT in all areas of our lives, including smart cities, smart homes, and smart retail. Much more. From 9.6 billion by 2050, agriculture needs to deliver even faster to meet this type of demand. This is possible with the latest technology, especially the IoT. The IoT enables labour free farms. Not only can it be used for large-scale agriculture, but it can also be used for livestock, greenhouse management, and agricultural land management. The most significant tool for the IoT is the sensor. A sensor is a device that collects important data that is interpreted to obtain the required analysis. The important objective of sensors are used to determine the soil's physical qualities and the environment. The main applications of sensors are control and supervise, safety, alarm, diagnostics, and analytics. Sensors make innovative agriculture more effective and trouble-free. In agriculture, the sensor is mainly used for measuring, measuring NPK (Nitrogen, Phosphorus, Potassium) levels, and detecting disease and soil moisture content. The main solution to this problem is smart farming, which modernizes traditional farming practices. This paper narrates the role of IoT application in smart agriculture. Smart farming is also known as precision farming hence it uses accurate information to draw outcomes. It demonstrates the different sensors, applications, challenges, strengths and weaknesses that support the IoT and agriculture. © 2022 IEEE.

关键词： Precision agriculture

来源：评论

学校读者我要写书评

暂无评论

Updating Top-k Dominate Individuals with Incomplete Data Addition

Updating Top-k Dominate Individuals with Incomplete Data Add...

引用

2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Wu, Jimmy Ming-Tai Wang, Ke Yan, Huizhen Chen, Chao-Chun Chen, Pei-Wei Lin, Jerry Chun-Wei Shandong University of Science and Technology College of Computer Science and Engineering Qingdao China National Cheng Kung University Institute of Manufacturing Information and Systems Tainan70101 Taiwan Western Norway University of Applied Sciences Department of Computer Science Electrical Engineering and Mathematical Sciences Bergen Norway

ISBN: (纸本)9781665475549

Top-k dominance (TKD) query is an extended query method of skyline query and top-k query, which reveals the top-k dominant individuals in an incomplete dataset by analyzing the dominance relationships between individuals and is a common decision tool in intelligent recommendation applications. This research proposes two parallel query algorithms based on Spark computing engine to address the shortcomings of the parallel top-k-dominated query algorithms for dynamic incomplete datasets. The designed model achieves good performance in terms of runtime performance compared to previous studies. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IoT Technologies for Precision Agriculture: A Survey 6

IoT Technologies for Precision Agriculture: A Survey

引用

6th International Conference on Computing Methodologies and Communication, ICCMC 2022

作者： Pyingkodi, M. Thenmozhi, K. Karthikeyan, M. Nanthini, K. Wilfried Blessing, N.R. Ajay Martin, A. Deepak, P.V. Jegan, K. Kongu Engineering College Department of Computer Applications Erode India Kristu Jayanthi College Department of Computer Science Bengaluru India University of Technology and Applied Sciences Department of IT Salalah Oman

ISBN: (纸本)9781665410281

Precision agriculture is gaining popularity in both commercial and research and development applications recent days. Plant management systems are constantly evolving, taking into account real-time or offline data collecting and processing in order to fully account for the geographical and temporal fluctuations of plant and soil components. This step can be achieved by lowering energy use, reducing the use of chemicals, fertilizers, and greenhouse gases (GHG), while simultaneously increasing output. To address the food and fibre needs of a rapidly rising population, sustainability is critical. With this in mind, the goal of this study is to not only present a complete picture, but also to elucidate the context by highlighting major scientific research and applications related to optoelectronics proximate sensors. Is to attempt to create a 360-degree vision. Agriculture. The reviews are divided into categories based on the most common sensor types and applications (grayscale / RGB imaging, Visible Near Infrared (VisNIR) and NIR, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Vegetation Index (NDRE) sensors, stereo). That's precisely the Point that the Vision, thermography, composite sensors, phenotypic sensors, and other technologies are being developed. Two distinct chapters on the use and development of specialised analytical methodologies, as well as term map analysis to visually identify major clusters based on certain subject areas are studied. © 2022 IEEE.

关键词： Remote sensing

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：