检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Sharma, Rajesh R. Sungeetha, Akey Chinnaiyan, R. Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India

- The oceans in the Earth's in one of the last border lines on the World, with only a fraction of their depths having been explored. Advancements in technology have led to the development of Autonomous Underwater Vehicles (AUVs) that can operate independently and perform complex tasks underwater. These vehicles have revolutionized underwater exploration, allowing us to study and understand our oceans like never before. In addition to AUVs, image processing techniques have also been developed that can help us to better understand the seabed and its features. In this comprehensive survey, we will explore the latest advancements in AUV technology and seabed image processing techniques. We'll discuss how these advancements are changing the way we explore and understand our oceans, and their potential impact on the future of marine science. Join us on this journey to discover the exciting world of underwater exploration and the technologies that are driving it forward. © 2023, CC BY.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Temperature Prediction of Permanent Magnet Synchronous Motor Using AI Techniques for Effective Traction Control

Temperature Prediction of Permanent Magnet Synchronous Motor...

引用

Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), International Conference on

作者： Judeson Antony Kovilpillai J Lalli. K Puneet Kumar Yadav Prabhakaran M Department of Computer Science Engineering Alliance College of Engineering and Design Alliance University Bangalore India

In the realm of traction drive applications, there exists a compelling need for harnessing Artificial Intelligence (AI) techniques to predict electric motor behaviour. AI-driven predictions enable proactive energy management, facilitating the implementation of optimal control strategies that minimize energy consumption and maximize overall system efficiency. In this research, various machine learning (ML), deep learning (DL), and long short-term memory (LSTM) approaches are used to analyze sensor data obtained from a Permanent Magnet Synchronous Motor (PMSM) mounted on a experimental test bench. Different regression models, including Linear Regressor, AdaBoost Regressor, Gradient Boosting Regressor, ElasticNet, K-Neighbor Regressor, and Decision Tree Regressor were utilized as a part of the research to develop efficient control strategies and enhance the efficiency and reliability of PMSMs. Performance of these techniques are evaluated using different metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the R-squared (RS) coefficients. This research also cross-evaluated different DL and LSTM architectures temperature using various parameters like convergence speed, average training time, optimal epochs for achieving peak accuracy and accuracy improvement. The knowledge gained through this in-depth exploration hold the potential to steer the formulation of advanced control strategies, thereby enhancing the efficiency and dependability of PMSMs for traction drive applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Diet and Exercise Tracking for Daily Requirements Using Artificial Intelligence Technique

Diet and Exercise Tracking for Daily Requirements Using Arti...

引用

New Frontiers in Communication, Automation, Management and Security (ICCAMS), International Conference on

作者： Vasavi Annapureddy Keerthana Mohit Hemanth Kumar Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India Department of Mechanical Engineering Alliance College of Engineering and Design Alliance University Bengaluru Karnataka India

ISBN: (数字)9798350317060

ISBN: (纸本)9798350317077

Recently, there has been a concern about our looks and fitness freaks in today’s world. The consumption of more food leads to gaining weight in the long run if it exceeds the daily requirement. The present investigation presents the control of calories consumption using the artificial intelligence (AI) model. Based on the AI model, the correct quantity of food is recommended and suggests the necessary workouts to reduce the extra calories. From this investigation, it can be concluded that people can still eat any food and do essential exercises needed for daily requirements to maintain proper health.

关键词： Costs Automation Software Security Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Bearing Error Diagnosis Using Deep Learning and Convolution Neural Network

Bearing Error Diagnosis Using Deep Learning and Convolution ...

引用

Innovation in technology (INOCON), IEEE International Conference for

作者： Richard Martin Rathnakar Achary Chetan J Shelke Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India

Fault diagnostics and prognostics are essential issues. Industrial plants will be under a huge amount of pressure that maintains unpredictable interruption, system failures, and safety issues to a minimum, that necessitates identifying and eliminating potential issues as quickly as possible. Intelligent problem diagnosis is a promising technique because of its capacity to handle gathered signals quickly and effectively while also offering reliable diagnosis findings. Numerous authors have validated deep learning and machine learning approaches for identifying bearings failures, the findings have mostly been confined to tiny train and test datasets, with the input data modified to achieve high accuracy. In this article, original data of accelerometer sensor was loaded into unique periodic sequencing prediction algorithm that develops an edge fault diagnosis technique. We utilize identical frequency patterns as inputs to an innovative deep neural Long-Short-Term-Memory, Recurrent Neural Network to diagnosis bearings insufficiency at excellent accuracy inside the least time (CRNN). Without the use of database adjustment, the technique would acquire the maximum level of competence in the industry. The fault diagnostic method’s efficacy and applicability are demonstrated by comparing the findings to those of other intelligent fault detection systems using two widely known benchmark real vibration datasets.

关键词： Vibrations Deep learning Time-frequency analysis Technological innovation Tensors Databases Fault detection

来源：评论

学校读者我要写书评

暂无评论

IoT-Enabled Smart Irrigation System with ABiLSTM for Optimized Water Management and Crop Yields 3

IoT-Enabled Smart Irrigation System with ABiLSTM for Optimiz...

引用

3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Chaturvedi, Abhay Rao, Praveena Venkata Maruti Prasad, S. Malini, T. Prabagar, S. Bharathi, K. Gla University Department of Electronics and Communication Engineering Mathura India Institute of Aeronautical Engineering Department of Civil Engineering Hyderabad India Aditya Institute of Technology & Management Department of Bs & H Tekkali India Sri Krishna College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India School of Advanced Computing Alliance University Department of Computer Science and Engineering Bangalore India Erode Sengunthar Engineering College Department of Agricultural Engineering Perundurai India

ISBN: (纸本)9798331508456

An efficient management of water resources in agriculture is now crucial in light of the growing global population and increased demand for water. Innovative solutions are needed to improve water efficiency since conventional irrigation methods are not sustainable anymore. Through the use of precision agriculture and the Internet of Things (IoT), smart irrigation has revolutionised water management, leading to increased crop yields. In order to improve the efficiency of decision-making, this research presents an Internet of Things (IoT) smart irrigation system that uses SA-BiLSTM (Self-Attention Bidirectional Long Short-Term Memory). Using Min-Max and Z-score normalisation approaches for feature scaling, the methodology includes data preparation, feature selection, and model training. Methods based on ranking, such as the Chi-Square Test, Pearson Correlation Coefficient (PCC), and Mutual Information (MI), were used to prioritise feature selection. Classification and prediction testing showed that the proposed SA-BiLSTM model outperformed state-of-the-art models like HGAT and Linear SVM, with an astounding 95.63% accuracy. Improved resource allocation and irrigation effectiveness, leading to increased agricultural output, are highlighted by the results, which highlight the effectiveness of advanced machine learning approaches in precision agriculture. © 2025 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Optimized Deep Learning Models for AUV Seabed Image Analysis

arXiv

引用

arXiv 2023年

作者： Sharma, Rajesh R. Sungheetha, Akey Chinnaiyan, R. Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India

Using autonomous underwater vehicles, or AUVs, has completely changed how we gather data from the ocean floor. AUV innovation has advanced significantly, especially in the analysis of images, due to the increasing need for accurate and efficient seafloor mapping. This blog post provides a detailed summary and comparison of the most current advancements in AUV seafloor image processing. We will go into the realm of undersea technology, covering everything through computer and algorithmic advancements to advances in sensors and cameras. After reading this page through to the end, you will have a solid understanding of the most up-to-date techniques and tools for using AUVs to process seabed photos and how they could further our comprehension of the ocean floor. © 2023, CC BY.

关键词： Autonomous underwater vehicles

来源：评论

学校读者我要写书评

暂无评论

Attention Based CNN to Improve Identification of Ischaemia and Infection in DFU

Attention Based CNN to Improve Identification of Ischaemia a...

引用

New Frontiers in Communication, Automation, Management and Security (ICCAMS), International Conference on

作者： Priya Bhowmick K Revanth Parlapalli Lakshmi Sujit Kumar Das Tina Babu Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru India

ISBN: (数字)9798350317060

ISBN: (纸本)9798350317077

Diabetic foot ulcers (DFUs) frequently occur as complications of diabetes. Identifying infection and ischaemia in DFUs is crucial for wound assessment and treatment planning. Recent advancements in deep learning have shown promise in classifying infection and ischaemia in DFUs using computerized methods. Many modern systems for classifying DFU images rely on deep neural networks, particularly convolutional neural networks. These networks analyze distinctive features and predict class probabilities based on these features. During testing, predictions are made using individual input images and trained parameters. To harness the information in training data more effectively, this study introduces the concept of an attention layer. This layer aids neural networks in memorizing long sequences of data, mitigates issues like exploding gradients, and enhances model accuracy. Experimental results demonstrate that this proposed approach significantly improves the accuracy of DFU infection and ischaemia detection.

关键词： Visualization Training data Wounds Prediction algorithms Skin Diabetes Planning

来源：评论

学校读者我要写书评

暂无评论

Emotion Based Prediction in the Context of Optimized Trajectory Planning for Immersive Learning

arXiv

引用

arXiv 2023年

作者： Sungheetha, Akey Rajesh, Sharma R. Chinnaiyan, R. Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bangalore India

The use of Google Expedition and touch screen-based emotion in the virtual components of immersive learning is investigated. The objective is to investigate possible ways to combine these technologies to enhance virtual learning environments and learners’ emotional engagement. Pedagogical application, affordances, and cognitive load are the corresponding measures that are involved. Students will gain insight into the reason behind their significantly higher post-assessment Prediction Systems scores compared to preassessment scores through this work that leverages technology. This suggests that it is effective to include emotional elements in immersive learning scenarios. The results of this study may help develop new strategies by leveraging the features of immersive learning technology (ILT) in educational technologies to improve virtual reality (VR) and augmented reality (AR) experiences. Furthermore, the effectiveness of immersive learning environments can be raised by utilizing magnetic, optical, or hybrid trackers that considerably improve object tracking. © 2023, CC BY.

关键词： Touch screens

来源：评论

学校读者我要写书评

暂无评论

Track-Rex:A universal toolbox for tracking recrystallization nucleation and grain growth behaviors in polycrystalline materials

引用

Journal of Materials Science & technology 2024年第30期197卷 149-159页

作者： Xun Zeng Haoran Yi Zhuoran Zeng Liang Yuan Sangbong Yi Junheng Gao Mark Rainforth Dikai Guan Department of Mechanical Engineering University of SouthamptonSouthamptonSO171BJUK College of Engineering and Computer Science Australian National UniversityACT 2601Australia College of Bioresources Chemical and Materials Engineering Shaanxi University of Science and TechnologyXi’an710021China Institute of Materials and Process Design Helmholtz-Zentrum HereonGeesthacht21502Germany Department of Materials Science and Engineering University of SheffieldSheffieldS13JDUK Institute for Carbon Neutrality University of Science and Technology BeijingNo.30 Xueyuan RoadHaidian DistrictBeijing100083China

Recrystallization annealing is widely used to tailor the microstructure and enhance the performance of cold-deformed metallic ***,the underlying recrystallization mechanisms are debated,even with the use of cutting-edge characterization ***,we develop a Track-Rex toolbox to analyze quasi-in-situ electron backscatter diffraction(EBSD)datasets of two magnesium(Mg)alloys dur-ing static recrystallization via grain *** results show that the recrystallized grains do not always grow;instead,they can shrink or even be *** is attributed to the presence of newly formed recrystallized grains that possess a growth advantage over the old recrystallized *** rare earth containing Mg-2.4Zn-0.2Ce wt.%(ZE20)alloy exhibits a higher nucleation activity in the shear bands compared to the commercial Mg-3Al-1 Zn(AZ31)*** of the nucleation timing and sites,re-crystallized grains in the ZE20 alloy show consistent off-basal orientations,serving as the origin of the rare earth ***,the off-basal texture of these recrystallized grains is further strengthened through preferential growth during subsequent *** the contrary,the recrystallized grains in the AZ31 exhibit scattered basal orientations that grow uniformly,resulting in a weak basal texture.

关键词： Grain correlation Grain tracking Recrystallization Texture Mg alloys

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor:Hybrid Feature Extraction Based on UNet and 3DCNN

引用

computer Systems Science & engineering 2023年第5期45卷 2093-2109页

作者： Sureshkumar Rajagopal Tamilvizhi Thanarajan Youseef Alotaibi Saleh Alghamdi Center for System Design Chennai Institute of TechnologyChennai600069India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Automated segmentation of brain tumors using Magnetic Resonance Imaging(MRI)data is critical in the analysis and monitoring of disease *** a result,gliomas are aggressive and diverse tumors that may be split into intra-tumoral groups by using effective and accurate segmentation *** is intended to extract characteristics from an image using the Gray Level Co-occurrence(GLC)matrix feature extraction method described in the proposed *** Convolutional Neural Networks(CNNs),which are commonly used in biomedical image segmentation,CNNs have significantly improved the precision of the state-of-the-art segmentation of a brain *** two segmentation networks,a U-Net and a 3D CNN,we present a major yet easy combinative technique that results in improved and more precise *** U-Net and 3D CNN are used together in this study to get better and more accurate estimates of what is going *** the dataset,two models were developed and assessed to provide segmentation maps that differed fundamentally in terms of the segmented tumour ***,the estimates was made by two separate models that were put together to produce the final *** comparison to current state-of-the-art designs,the precision(percentage)was 98.35,98.5,and 99.4 on the validation set for tumor core,enhanced tumor,and whole tumor,respectively.

关键词： Medical imaging segmentation U-net 3D CNN brain tumor

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：