检索结果-内蒙古大学图书馆

Advancements in Computing (ICAC), International Conference on

作者： O.V.D.E Roshani H.M.K.J.J Ayuwardhana P.H.M.S Rodrigo R.U Hewageegana Harinda Fernando Dilshan I. de Silva Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

Frequently, individuals undergo specific episodes of mental health challenges throughout their lifetime. But the COVID pandemic has triggered a surge in mental health disorders arising from isolation, monotonous routines, demanding workloads, financial disparities, and disruptions to daily schedules. Furthermore, the global pandemic has induced constant anxiety and stress. Beyond the pandemic, the competition and intense pressure of the modern world impact mental health. Access to advanced mental health solutions and the necessary familiarity remain limited for most of the population. Given the integration of technology into daily life, diverse remedies, including mobile and web applications, have emerged to tackle the escalating challenge of mental health disorders. This study proposes an accessible and cost-effective approach that employs machine learning to detect stress levels and discern user emotions from journal entries and facial expressions while integrating self-journaling, video recommendations, and visual content generation to stimulate positive emotions and relieve stress.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effective Intrusion Detection and Classification using Fuzzy Rule based Classifier in Cloud Environment 1

Effective Intrusion Detection and Classification using Fuzzy...

引用

1st IEEE International Conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Veena, C. Ramalakshmi, S. Bhoopathy, V. Bhosale, Minakshi Dattatraya Magadum, C.G. Abirami, S.K. Ghatkesar Telangana Hyderabad India Puducherry Karaikal India Department of Computer Science and Engineering Malla Reddy College of Engineering Telangana Secunderabad India Faculty of MCA Yashoda Technical Campus Maharashtra Satara India Smt. Kasturbai Walchand College Maharashtra Sangli India Department of Computer Science and Business Systems Sri Eshwar College of Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9781665460842

Cloud computing (CC) is the demonstration of the technology that makes use of the substructure for computing in a proficient fashion. This sort of computing offers great quantity of consequences in augmenting the productivity that verifies the risk handling management and decreases the cost. Intrusion detection system (IDS) is widely applied for detecting malicious actions in its host and the communication network. IDS is a procedure of discovering activities that take place in a network and attempts to fulfill the confidentiality, network, or security accessibility to smear the trust procedure. This article introduces an Effective Intrusion Detection and Classification using Fuzzy Rule based Classifier (EIDC-FRC) model in Cloud Environment. The goal of the presented EIDC-FRC model is to determine the occurrence of intrusions and normal data traffic in the cloud environment. In order to achieve this, the presented EIDC-FRC model applies FRC for data classification process. The parameter tuning of the FRC model is performed using enhanced bird swarm algorithm (EBSA). The FRC is an effective model in pattern recognition that offers effective outcomes by the use of linguistic labels in the antecedents of the rules. The simulation analysis of the EIDC-FRC model ensured the enhancements of the presented approach compared to recent state of art approaches. © 2022 IEEE

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based pixel interpolation in spatial-domain phase shifting digital holography

Deep learning-based pixel interpolation in spatial-domain ph...

引用

2022 International Symposium on Imaging, Sensing, and Optical Memory, ODS 2022

作者： Kajitani, Shu Takabayashi, Masanori School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2-4 Hibikino Wakamatsu-ku Fukuoka Kitakyushu808-0196 Japan

We propose to apply deep learning to interpolate missing pixels in interferograms acquired by the spatial-domain phase-shifting interferometry (PSI), and numerically evaluate the quality of object light reconstructed ... 详细信息

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Digital Learning Ecosystem: Online Concept for engineering Education

Digital Learning Ecosystem: Online Concept for Engineering E...

引用

International Scientific Conference on Power and Electrical engineering of Riga Technical University (RTUCON)

作者： Anatolijs Zabasta Volodymyr Kazymyr Nadezhda Kunicina Oleksandr Velihorskyi Faculty of Computer Science Information Technology and Energy Riga Technical University Riga Latvia Information and Computer Systems Department Chernihiv Polytechnic National University Chernihiv Ukraine Radio Engineering and Embedded Systems Department Chernihiv Polytechnic National University Chernihiv Ukraine

ISBN: (数字)9798350365771

ISBN: (纸本)9798350365788

This article examines the development of a Digital Learning Ecosystem (DLE) for engineering education, supported by online learning, within the framework of Erasmus+ international educational projects. We hypothesize that a DLE can address the challenges posed by rapid technological changes associated with Industry 4.0 and digital transformation, thus transforming engineering education to meet modern industry needs. Building on the earlier Erasmus+ CybPhys project, which established a Sharing Modelling and Simulation Environment (SMSE) for digitalizing online technical courses, the DIGITRANS project aims to enhance this architecture to include remote laboratories through the Sharing Remote Experiment Environment (SREE) platform. The project involves acquiring hardware and open-source software for SREE and establishing two physical remote laboratories. A study conducted in spring 2023, using the Technology Acceptance Model framework, indicated positive student perceptions of SMSE, with students believing it would enhance learning outcomes and expressing intentions to use the platform frequently. The efficacy of the DLE in addressing technological advancement challenges will be further evaluated through post-ante assessments and feedback from prospective employers and stakeholders, focusing on the implementation of industry recommendations and the correlation between pre- and post-implementation survey responses from industry and academic experts.

关键词： Training Surveys Remote laboratories Biological system modeling Ecosystems Hardware Stakeholders engineering education Kernel Programming profession

来源：评论

学校读者我要写书评

暂无评论

Tcn-Inception: Temporal Convolutional Network and Inception Modules for Sensor-Based Human Activity Recognition

SSRN

引用

SSRN 2024年

作者： Helmi, Ahmed M. Al-Qaness, Mohammed A.A. Dahou, Abdelghani Trouba, Nafissa Toureche Elaziz, Mohamed Abd College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China School of Computer Science and Technology Zhejiang Normal University Jinhua321004 China Mathematics and Computer Science department University of Ahmed DRAIA Adrar01000 Algeria Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt Computer Engineering Dept. Engineering and Information Technology College Buraydah Private Colleges Buraydah51418 Saudi Arabia Computer and Systems Engineering Dept. Faculty of Engineering Zagazig University Zagazig44519 Egypt

HighlightsTCN-InceptionTemporal Convolutional Network and Inception modules for Sensor-based Human Activity RecognitionMohammed A. A. Al-qaness,Abdelghani Dahou,Nafissa Toureche Trouba,Mohamed Abd Elaziz,Ahmed M. Helmi• Employing the Inception modules with Temporal Convolutional Network and using residual connections for capturing complex temporal patterns in HAR signals.• Extraction of multi-scale features and capturing of extended temporal dependencies using the novel model• Consideration of training efficiency and model depth through the strategic use of residual connections and batch normalization.• Studying four different complex datasets, with variant set of activities, and carrying out an ablation study for more detailed analysis of the model. © 2024, The Authors. All rights reserved.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Remote Patient Monitoring systems Network Adaptation Scenarios

Remote Patient Monitoring Systems Network Adaptation Scenari...

引用

2022 IEEE International Conference on Current Development in engineering and Technology, CCET 2022

作者： Khujamatov, Halimjon Akhmedov, Nurshod Lazarev, Amir Arsheen, Sobiya Tashkent University of Information Technologies Dean of the Faculty of Computer Engineering Tashkent Uzbekistan Tashkent University of Information Technologies Data Transmission Networks and Systems Department Tashkent Uzbekistan Maulana Azad National Urdu University Department of Computer Science and Information Technology India

ISBN: (纸本)9781665454155

This article is devoted to the actual topic of studying scenarios for adapting a network infrastructure to a network of remote patient monitoring systems (PCMS). The paper presents an overview and analysis of scenarios for adapting the network infrastructure of monitoring systems. The stages of scenario execution have been studied and simulation models of the RPMS network infrastructure have been developed that implement various adaptation scenarios. A comparative analysis of adaptation scenarios was carried out according to several criteria, such as the speed of request delivery, delivery time, and network load. Simulation models built in the Anylogic environment, a powerful simulator of mass service system, showed the effectiveness of the mesh topology in relation to the ad-hoc topology according to several criteria. The theoretical significance of the work lies in carrying out analytical work on scenarios for adapting the network infrastructure of the RPMS, as well as in studying the network architecture. The practical significance of the work lies in the development of a simulation model that allows you to explore scenarios for adapting the network architecture. © 2022 IEEE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Single and shift-multiplexing recording properties in self-referential holographic data storage with designed additional pattern

Single and shift-multiplexing recording properties in self-r...

引用

2022 International Symposium on Imaging, Sensing, and Optical Memory, ODS 2022

作者： Chijiwa, Kazuki Takabayashi, Masanori School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Fukuoka Iizuka820-8502 Japan Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology 2-4 Hibikino Wakamatsu-ku Fukuoka Kitakyushu808-0196 Japan

The reconstruction quality and shift multiplexing properties of self-referential holographic data storage (SR-HDS) with additional patterns which are designed with a target intensity of nonuniform distributions such a... 详细信息

关键词： Holography

来源：评论

学校读者我要写书评

暂无评论

Exploring the Influence of Digital Media on Secondary School Students' Daily Lives

Exploring the Influence of Digital Media on Secondary School...

引用

International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Előd Gőgh Attila Kovari Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Institute of Computer Science University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The focus of this study is to investigate how digital media use affects the daily activities, emotional well-being, and general lifestyle of high school students in relation to education amidst concerns about a “new terrain or venue” for learning in an era moving full swing towards digitization. The study, conducted with students from grades 9–11, seeks to identify overall trends and associations involving digital media interactions: considering both byproducts of using new technology as an educational tool- in addition discursive aspects allowing for different forms of distraction. In summary, the results showed that digital media use is common and often regarded as educationally beneficial or a positive form of relaxation; however, daily activities are it affected by substantial adverse impacts on everyday life and time management. Suggestions focus on supporting healthy digital media habits, including content-wise engagement and time management tools.

关键词： Surveys Power engineering Mood Education Media Market research

来源：评论

学校读者我要写书评

暂无评论

Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets 6

Creating Own AI Datasets from Different Language Sources Eff...

引用

6th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2023

作者： Molnar, Gyorgy Cserko, Jazsef Nagy, Eniko Balogh, Zoltan Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary Győr Hungary Institute of Cyberphysical Systems Óbuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Constantine the Philosopher University in Nitra Faculty of Natural Sciences and Informatics Department of Informatics Nitra94901 Slovakia

ISBN: (纸本)9798350328752

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation. © 2023 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence's Contribution To Mental Health Education 2

Artificial Intelligence's Contribution To Mental Health Educ...

引用

2nd International Conference on Sustainable Computing and Data Communication systems, ICSCDS 2023

作者： Anand, Neha Pant, Lalit Mohan Alam, Tanweer Pundir, Sumit Thomas, Lims Rakshith, U.R. Teerthaanker Mahaveer University Moradabad India Uttarakhand Open University Department of Psychology Haldwani India Islamic University of Madinah Faculty of Computer and Information Systems Department of Computer Science Madinah Saudi Arabia Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Department of Social Work Thrissur India Jss College of Pharmacy Jss Academy of Higher Education and Research Department of Pharmacy Practice Karnataka Mysuru570015 India

ISBN: (纸本)9781665491990

As AI offers a suitable response to various challenges associated with this disease, it plays a crucial role in mental health. A fundamental concept of the AI-based mental health remedy and its impact on directly affecting social-emotional learning has also been examined in this study with the appropriate material and references. The many types of AI that may unquestionably aid in general mental health education have already been specifically outlined in this research using all the data from existing books and publications. In addition to this, an AI-based chatbot platform has been built within the software system to identify various health factors that seem to be directly linked to mental health. The main challenges in this regard remained consistent with other AI-related healthcare systems including concerns for privacy and confidentiality apart from data integrity. © 2023 IEEE.

关键词： Artificial intelligence

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：