检索结果-内蒙古大学图书馆

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Sangjun Eom Wenyi Xu Liheng Zou Ashley Frith Ernesto Escobar Gabriel Streisfeld Anna Mall Bradi Granger Maria Gorlatova Department of Electrical and Computer Engineering Duke University Game Design Development and Innovation Duke University School of Literature Media and Communication Georgia Institute of Technology Department of Physical Therapy Duke University Duke Heart Center Duke University Hospital School of Nursing Duke University

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Patients in intensive care units (ICUs) undergoing prolonged bed rest are at high risk of physical, cognitive, and psychological impairments due to immobility. While early mobilization protocols are critical for rehabilitation, the implementation is hindered by patients’ restricted mobility and the complex ICU environment. To address these challenges, we present Legato, an immersive virtual reality (VR) game designed to enhance mobility activities for ICU patients. Legato offers a calming, customizable environment with thematic styles and music tracks, while providing real-time progress tracking and adaptive difficulty levels tailored to patients’ hand movements. To evaluate its feasibility, we deployed Legato on Meta Quest 3 and conducted a pilot study with an ICU patient at Duke University hospital, demonstrating promising potential for improving rehabilitation outcomes.

关键词： Protocols Three-dimensional displays Tracking Hospitals Psychology Games Immersive experience Real-time systems Safety Monitoring

来源：评论

学校读者我要写书评

暂无评论

Deploying Hybrid MAELM Approach for Human Emotion Detection Through Speech and Facial Expressions

Deploying Hybrid MAELM Approach for Human Emotion Detection ...

引用

International Conference on Innovative Mechanisms for Industry Applications (ICIMIA)

作者： K Senthil Kumar S. Rukmani Devi Nidhi Ranjan Gitika Rath G. Indira Neerav Nishant Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to be University Chennai India Computer Engineering Vasantdada Patil Pratishthan’s College of Engineering and Visual Arts Mumbai India Department of CSE Marri Laxman Reddy Institute of Technology and Management Hyderabad India Department of Electrical and Electronics Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department of Computer Science and Engineering School of Engineering Babu Banarasi Das University Lucknow India

Emotion recognition is one of the most fascinating emerging fields of research. It’s useful in a lot of different contexts. Some of the most exciting applications of this technology involve robots’ ability to see and communicate with one another. Human emotions can be recognized through both visual and audible cues. Facial expressions are one of the most accurate indicators of a person’s emotional state. Data preprocessing, feature extraction, and model training are the first three steps of the proposed methodology. Image resizing, a median filter, noise removal, and histogram equalization are all components of preprocessing. Gaussian mixture models and the gray level co-occurrence matrix are being used for feature extraction. After the extraction of features, models with those features are trained using MA-ELM. The proposed method outperforms PCA and ELM, two of the most popular alternatives.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep Video Representation Learning: A Survey

arXiv

引用

arXiv 2024年

作者： Ravanbakhsh, Elham Liang, Yongqing Ramanujam, J. Li, Xin Division of Electrical & Computer Engineering Center for Computation & Technology Louisiana State University Baton RougeLA70803 United States Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States Section of Visual Computing and Interactive Media Texas A&M University College StationTX77843 United States

This paper provides a review on representation learning for videos. We classify recent spatio-temporal feature learning methods for sequential visual data and compare their pros and cons for general video analysis. Building effective features for videos is a fundamental problem in computer vision tasks involving video analysis and understanding. Existing features can be generally categorized into spatial and temporal features. Their effectiveness under variations of illumination, occlusion, view and background are discussed. Finally, we discuss the remaining challenges in existing deep video representation learning studies. © 2024, CC BY-NC-ND.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Beamforming Design with Partial Channel Estimation and Feedback for FDD RIS-Assisted Systems

arXiv

引用

arXiv 2023年

作者： Ge, Xiaochun Yu, Shanping Shen, Wenqian Xing, Chengwen Shim, Byonghyo School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

Beamforming design with partial channel estimation and feedback for frequency-division duplexing (FDD) reconfigurable intelligent surface (RIS) assisted systems is considered in this paper. We leverage the observation that path angle information (PAI) varies more slowly than path gain information (PGI). Then, several dominant paths are selected among all the cascaded paths according to the known PAI for maximizing the spectral efficiency of downlink data transmission. To acquire the dominating path gain information (DPGI, also regarded as the path gains of selected dominant paths) at the base station (BS), we propose a DPGI estimation and feedback scheme by jointly beamforming design at BS and RIS. Both the required number of downlink pilot signals and the length of uplink feedback vector are reduced to the number of dominant paths, and thus we achieve a great reduction of the pilot overhead and feedback overhead. Furthermore, we optimize the active BS beamformer and passive RIS beamformer by exploiting the feedback DPGI to further improve the spectral efficiency. From numerical results, we demonstrate the superiority of our proposed algorithms over the conventional schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

来源：评论

学校读者我要写书评

暂无评论

An Interactive computer System with Gesture-Based Mouse and Keyboard

An Interactive Computer System with Gesture-Based Mouse and ...

引用

3rd International Conference on Intelligent Computing and Optimization, ICO 2020

作者： Gupta, Dipankar Hossain, Emam Hossain, Mohammed Sazzad Hossain, Mohammad Shahadat Andersson, Karl Department of Computer Science and Engineering Port City International University Chattogram Bangladesh Department of Computer Science and Engineering University of Chittagong Chattogram Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Computer Science Electrical and Space Engineering Lulea University of Technology Skelleftea Sweden

ISBN: (纸本)9783030681531

Researchers around the world are now focused on to make our devices more interactive and trying to make the devices operational with minimal physical contact. In this research, we propose an interactive computer system which can operate without any physical keyboard and mouse. This system can be beneficial to everyone, especially to the paralyzed people who face difficulties to operate physical keyboard and mouse. We used computer vision so that user can type on virtual keyboard using a yellow-colored cap on his fingertip, and can also navigate to mouse controlling system. Once the user is in mouse controlling mode, user can perform all the mouse operations only by showing different number of fingers. We validated both module of our system by a 52 years old paralyzed person and achieved around 80% accuracy on average. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mammals

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-aided Parametric Sparse Channel Estimation for Terahertz Massive MIMO Systems

arXiv

引用

arXiv 2024年

作者： Kim, Jinhong Ahn, Yongjun Kim, Seungnyun Shim, Byonghyo Samsung Electronics Seoul06765 Korea Republic of The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Electrical and Computer Engineering The Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

Terahertz (THz) communications is considered as one of key solutions to support extremely high data demand in 6G. One main difficulty of the THz communication is the severe signal attenuation caused by the foliage loss, oxygen/atmospheric absorption, body and hand losses. To compensate for the severe path loss, multiple-input-multiple-output (MIMO) antenna array-based beamforming has been widely used. Since the beams should be aligned with the signal propagation path to achieve the maximum beamforming gain, acquisition of accurate channel knowledge, i.e., channel estimation, is of great importance. An aim of this paper is to propose a new type of deep learning (DL)-based parametric channel estimation technique. In our work, DL figures out the mapping function between the received pilot signal and the sparse channel parameters characterizing the spherical domain channel. By exploiting the long short-term memory (LSTM), we can efficiently extract the temporally correlated features of sparse channel parameters and thus make an accurate estimation with relatively small pilot overhead. From the numerical experiments, we show that the proposed scheme is effective in estimating the near-field THz MIMO channel in THz downlink environments. © 2024, CC BY-NC-ND.

关键词： Beamforming

来源：评论

学校读者我要写书评

暂无评论

An Examination of Machine Learning Techniques for Automating and Optimizing VLSI Design

An Examination of Machine Learning Techniques for Automating...

引用

Science, technology, engineering and Management (ICSTEM), International Conference on

作者： R. Jeyarohini R Sathya S. P. Sellapaandi P Kavitha D. Raja Ramesh Aparajita Mukherjee Department of Electronics and Communication Engineering PSNA College of Engineering and Technology Dindigul Tamil Nadu India Department of Computer Applications Alpha Arts and Science College Chennai Tamil Nadu India Department of Electrical and Electronics Engineering R.M.K. Engineering College Kavaraipettai Tamil Nadu India Department of Electronics and Communication Engineering MVGR College of Engineering(A) Vizianagaram Andhra Pradesh India Department of Computer Science and Engineering IEM-UEM Kolkata India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

This research examines the use of machine learning (ML) techniques to automate and optimise Very Large Scale Integration (VLSI) design procedures. Very large scale integrated circuits (VLSI) require a number of laborious and complex processes to be designed, such as placement, routing, and logic synthesis. Historically, manual involvement and specialised knowledge have been needed to complete these jobs. The goal of this research is to use machine learning approaches to increase chip performance, improve design efficiency, and streamline the workflows involved in VLSI design. Numerous machine learning (ML) techniques, including evolutionary algorithms, reinforcement learning, and supervised learning, are being investigated to determine their efficacy in automating design tasks, optimising design parameters, and cutting down on design cycle durations. This research shows that incorporating machine learning techniques into VLSI design processes is not only possible but also advantageous through extensive tests and case studies. The results of this study are highly relevant to the semiconductor industry in this era of sophisticated microelectronics. They could open the door to more scalable and effective VLSI design processes

关键词： Supervised learning Electronics industry Reinforcement learning Manuals Evolutionary computation Very large scale integration Routing

来源：评论

学校读者我要写书评

暂无评论

Text Analysis Based on Natural Language Processing (NLP)

Text Analysis Based on Natural Language Processing (NLP)

引用

Advances in engineering Science and technology (AEST), International Conference on

作者： Azhar Kassem Flayeh Yaser Issam Hamodi Nashwan Dheyaa Zaki Department of Computer Engineering & Information Technology Ministry of Higher Education & Scientific Research Baghdad Iraq Computer Engineering - College of Electrical And Electronic Techniques Ministry of Higher Education & Scientific Research Baghdad Iraq Media Technology Engineering 3University of Information Technology and Communications/College of Engineering Baghdad Iraq

In the modern era of information explosion, where there is enormous information including thousands and millions of texts loaded on the Internet of over 1.2 million terabytes, there are no accurate statistics on the size of texts within this huge amount of data. Given the multiplicity of websites on the Internet and the spread of social networking services like Twitter, for example, it is stated that about 6000 tweets are posted per second in the year 2019. This work aims to analyze these texts through resorting to artificial intelligence to help solve this problem. In this article, a review is presented on the latest concepts in the field of word processing, information extraction, and implementing an interface for text analysis using the C ++ programming language and Visual Studio 2015 edition. A comparison is made between two articles in terms of the number of verbs, prepositions, article strength, number of letters, with the possibility of sorting the text into verbs, nouns, object, and adjectives, as will be displayed in the program interface.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The intentions of the designers of digital educational tools in early childhood education

引用

International Journal of Child-computer Interaction 2024年 40卷

作者： Ploog, Maria Wiktorski, Tomasz Department of Early Childhood Education Faculty of Arts and Education University of Stavanger Postboks 8600 Forus Stavanger 4036 Norway Department of Electrical Engineering and Computer Science Faculty of Science and Technology University of Stavanger Stavanger Norway

The popularity of programmable robots in early childhood education is growing. Such robots are discussed in the literature from the points of view of teachers, parents and children. We add the role of robot designers to this list. Focusing on designers and specifically their intentions is beneficial in two settings: in teacher training and whenever using the robots in playing activities in ECE. We present a qualitative study on robot designer intentions, conducted by group interviews with designers of two common but significantly different programmable robots, the Kubo robot and the Rugged robot. Using Activity Theory as the underlying framework for the thematic analysis of the interviews, our data reveal a large overlap of the intentions of both groups. They express the common goal of preparing children for the future although through slightly different competencies: enhancing computational thinking and 21st century skills, respectively. Both groups highlight the relevance of subjects outside computer science, specifically beyond coding. Our data also show a design process difference the Rugged robot was developed with a teacher-oriented approach whereas the Kubo robot with an object-oriented approach. © 2024 The Authors

关键词： Coding and computational thinking Designers' intention Early childhood education Educational robots Future competencies

来源：评论

学校读者我要写书评

暂无评论

Crop Yield Forecasting Using Bidirectional Gated Recurrent Unit (Bi-GRU) Networks

Crop Yield Forecasting Using Bidirectional Gated Recurrent U...

引用

Automation and Computation (AUTOCOM), International Conference on

作者： Layth Hussein Prashant Johri A.Anusha Priya R. Ramya J. Karpagam A. Devendran Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq School of Computing Science and Engineering Galgotias University Greater Noida India Department of Computer Science Muthayammal College of Arts and Science Rasipuram Tamilnadu India Department of Information Technology PSNA college of Engineering and Technology. Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore India School of Business Woxsen University Hyderabad India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Crop yield forecasting is an important aspect of the sustainable agriculture to help farmers and policy makers anticipate both production quantities and qualities, thus providing a technical tool for decision making. In this paper, a new technique of using Bidirectional Gated Recurrent Unit (Bi-GRU) to forecast the growth rate of one or several crops with improved precision and credibility is introduced. The model used here utilizes sequence data of meteorological parameters, soil, satellite index, and yield data also to incorporate temporal dependency and non-linear trends. Imputation of missing values; normalization; feature scaling all helps to remove inconsistencies in data and improve model performance. Folically, the employment of the Bi-GRU model provided a significan improvement over traditional machine learning models and unidirectional models with RMSE of 460.3 kg/ha and $\mathrm{R}^{2}$ of 0.89. Moreover, hyperparameters tuning enhanced the model revealing the importance of bidirectional architecture in managing and capturing the past and future temporal contexts. Similar trends of increased TVB-accuracy arias were observed in sub-Regional analysis considering different crop types and environmental conditions and the accuracy prediction of the yield increased up to 14.1%. This work suggests that Bi-GRU networks can be beneficial to predict crop yields with predictive power, reliability, and fine-grained architectures to handle problems such as climate fluctuations and dataset heterogeneity. The study provides a solution of how to incorporate deep learning algorithms into smart agriculture systems for development, posterity.

关键词： Deep learning Accuracy Computational modeling Predictive models Market research Data models Forecasting Crop yield Tuning Context modeling

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：