检索结果-内蒙古大学图书馆

2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Roy, Pritha Singha Kukreja, Vinay Chitkara University Institute of Engineering & Technology Chitkara University Department of Computer Science & Engineering Punjab India Centre for Research Impact & Outcome Chitkara University Institute of Engineering &technology Chitkara University Punjab India

ISBN: (纸本)9798331540821

The findings of the empirical work focus mainly on establishing how much a multi-class categorization model benefits various populations. The model can appropriately describe the following events: historical, religious, artistic, architectural, gastronomic, musical, dance, literary, philosophical, or traditional. The model can also classify events that fall under any of these categories. The F1 score, precision, and recall are the metrics that are included in every class's set of metrics. The support numbers indicate the frequency with which delegates of each class are observed, whereas the support proportions ensure that this frequency corresponds across all classes. Indicating its ability to generalize and yield correct predictions throughout the entirety of the dataset, the general accuracy of the model is an essential component. Considering these findings, it is evident that the model can be useful in the real world in classifying goods into various categories. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

From Stress to Success: Leveraging Tracebility and Workability to Support Student Well-Being in Higher Education

From Stress to Success: Leveraging Tracebility and Workabili...

引用

International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Leeladhar Chourasiya Sushma Khatri Kamal K Sethi Anita Mahajan Avani Bhawsar Tanmay Verma Neeraj Sharma Computer Science and Engineering Acropolis Institute of Technology and Research Indore India Information Technology Vasantdada Patil Prasthan College of Engineering and Visual Arts Mumbai India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

The research explores the vital role of traceability in addressing student stress within the education sector. It underscores the importance of systematically tracking and analyzing stress factors and their impacts on students over time. The study aims to develop a framework for capturing, analyzing, and responding to stress-related data in educational settings. This involves understanding student behavior and engagement through machine learning and computer vision technologies. Data collection methods include Google Forms and consultations with psychologists. The document outlines model development, training, real-time monitoring, data visualization, user interaction, and intervention strategies. Furthermore, it elucidates the concepts of traceability and workability in the context of AI, addressing challenges and strategies for overcoming them. The paper also delves into stress-related issues in education and potential solutions.

关键词： Workability Data visualization Human factors Mental health Machine learning Real-time systems Data models Cultural differences Global communication Socioeconomics

来源：评论

学校读者我要写书评

暂无评论

A GPGPU-Based Algorithm Acceleration System for ECG Signal Processing 7

A GPGPU-Based Algorithm Acceleration System for ECG Signal P...

引用

7th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2024

作者： Huang, Tianyu Wang, Zhijiong Hu, Guannan Pun, Sio Hang Li, Hung Chun Vai, Mang I Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Zhuhai China Institute of Microelectronics Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China

ISBN: (纸本)9798331529314

Electrocardiogram (ECG) is an important non-invasive technique for diagnosing cardiovascular diseases (CVD). After acquiring the patients' raw ECG signal data, signal processing is essential for the diagnosis. Conventional ECG signal processing is usually performed serially, which takes a long time to process signals with large amounts of data. In this study, we have proposed a GPGPU-based algorithm acceleration system to improve the efficiency of ECG signal processing. This system utilizes OpenCL for parallel algorithm development on GPGPU. GPGPU executes certain steps in the QRS complex detection algorithm via parallel computing, thereby accelerating the algorithmic process. Experimental results showed that the system achieved a speedup of 1.279 compared to serial computing when processing 39 ECG signal sequences in parallel. In addition, our system has been equipped with a progressive transmission mechanism and a function that intelligently determines whether an algorithm can be accelerated. These features make this system practical not only in biomedical signal processing but also in engineering and research fields with large amounts of data. © 2024 IEEE.

关键词： Noninvasive medical procedures

来源：评论

学校读者我要写书评

暂无评论

A Hyperbolic Micromagnet for Multiple Spin Qubits with Fast Rabi Oscillations and High Addressability

IEEE Electron Device Letters

引用

IEEE Electron Device Letters 2024年第4期45卷 526-529页

作者： Chang, Che-Hao Li, Yu-Cheng Wu, Yu-Jui Liao, Chen-Yao Lin, Min-Jui Tsao, Hung-Yu Li, Jiun-Yun Graduate Institute of Electronics Engineering National Taiwan University Taipei10617 Taiwan Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA02139 United States National Taiwan University Department of Electrical Engineering Graduate Institute of Electronics Engineering Graduate School of Advanced Technology Taipei10617 Taiwan Taiwan Semiconductor Research Institute Hsinchu30078 Taiwan

We demonstrate a hyperbolic micromagnet to increase the manipulation speed of electron spins in silicon quantum dots using electric dipole spin resonance (EDSR). For single qubits, the hyperbolic magnet provides a large gradient of transverse magnetic fields of 4.9 mT/nm with the corresponding Rabi frequency ( 69 MHz). We then demonstrate that this hyperbolic micromagnet can drive a linear array of qubits with Rabi frequencies of 19 69 MHz and a high addressability (minimum difference of Larmor frequencies) up to 590 MHz to suppress the crosstalk between different qubits. We show that 15 qubits can be effectively addressed for high fidelity by this hyperbolic micromagnet. © 1980-2012 IEEE.

关键词： Magnetic fields

来源：评论

学校读者我要写书评

暂无评论

Enhancing Data Security and Data Sensitivity: Leveraging the Synergy of Blockchain Artificial Intelligence

Enhancing Data Security and Data Sensitivity: Leveraging the...

引用

International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Vikas Jain Sachin Chouhan Vandana Kate Nidhi Nigam Shilpa Bhalerao Dept of Computer Science and Information Technology Acropolis Institute of Technology & Research Indore India

Data security and sensitivity have become significant challenges for organizations worldwide in the digital transformation era. Protecting sensitive user data from cyber-attacks, breaches, and information exposure is of utmost concern. This research paper explores the potential of integrating blockchain, artificial intelligence (AI), and machine learning (ML) technologies to enhance data protection and ensure confidentiality. The introduction provides an overview of data sensitivity and the growing importance of data security in the digital age. It delves into blockchain technology, emphasizing its decentralized, immutable ledger for secure authentication, access control, and tamper-proof data storage. The paper presents various use scenarios, illustrating how blockchain safeguards sensitive user data, including medical records, financial information, and personal identifiers. It further examines AI's role in data security, showcasing its capability to detect threats, analyze anomalies, and authenticate users, thereby blocking unauthorized access to confidential information. Additionally, the study explores machine learning for data sensitivity management, highlighting its prowess in formulating access control policies and data categorization. The research underscores how blockchain, AI, and machine learning synergize to create a comprehensive data security architecture, enabling businesses to leverage the immutability of blockchain and the intelligent data protection of AI/ML. Real-world examples demonstrate the effectiveness of this synergy in enhancing data security and safeguarding against modern threats.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SciMRC: Multi-perspective Scientific Machine Reading Comprehension 30

SciMRC: Multi-perspective Scientific Machine Reading Compreh...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Zhang, Xiao Zheng, Heqi Nie, Yuxiang Huang, Heyan Mao, Xian-Ling School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Southeast Academy of Information Technology Beijing Institute of Technology China State Grid Smart Grid Research Institute Co. Ltd. China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9782493814104

Scientific Machine Reading Comprehension (SMRC) aims to facilitate the understanding of scientific texts through human-machine interactions. While existing dataset has significantly contributed to this field, it predominantly focus on single-perspective question-answer pairs, thereby overlooking the inherent variation in comprehension levels among different readers. To address this limitation, we introduce a novel multi-perspective scientific machine reading comprehension dataset, SciMRC, which incorporates perspectives from beginners, students, and experts. Our dataset comprises 741 scientific papers and 6,057 question-answer pairs, with 3,306, 1,800, and 951 pairs corresponding to beginners, students, and experts respectively. Extensive experiments conducted on SciMRC using pre-trained models underscore the importance of considering diverse perspectives in SMRC and highlight the challenging nature of our scientific machine comprehension tasks. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Fundamental analysis of lead-free CsGeI3 perovskite solar cell

引用

Materials Today: Proceedings 2022年 67卷 180-186页

作者： Solanki, Sheetal Vidhya Bharathi, Kakara Bhargava, Kshitij Department of Electrical and Computer Science Engineering Institute of Infrastructure Technology Research And Management 380026 Gujarat Ahmedabad India

The perovskite solar cells have shown notable improvement in efficiency and stability among all solar cells. research on perovskite solar cells began in 2009 and has focused on understanding and improving their conversion efficiency made over the past 6 years. In 2014, they showed efficiencies of around 15.9%. Most recently, they showed an efficiency of 25%. However, there are lot of problems with lead-based perovskite solar cells. Being toxic to the environment, there should be an alternative like germanium, which has excellent optical properties but practically it has low efficiency as well as poor stability compared to lead-based perovskite solar cells. Therefore, it becomes essential to invent alternatives that offer comparable efficiency and stability like Pb-based solar cells. The completely Pb-free cesium germanium triiodide (CsGeI3) heterostructure perovskite solar cell was simulated and conversion efficiency of 12.2% was achieved with significantly improved device parameters. To optimize lead-free components, the influence of the defect density and doping concentration of absorber layer are investigated. The solar cell capacitance simulator (SCAPS) simulation results succeed in achieving the highest power conversion efficiency in an all-inorganic non-toxic CsGeI3 based solar cell. The obtained performance metric values are PCE = 12.2%, FF = 70.6%, Jsc = 20.6 mA / cm2 and Voc = 0.84 V. © 2022

关键词： Perovskite solar cells

来源：评论

学校读者我要写书评

暂无评论

Smart Home Automation with IoT Sensor Systems for Energy Conservation using Zigbee and Wifi 5

Smart Home Automation with IoT Sensor Systems for Energy Con...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Jagannathan, Srinivasan Deepa, V. Sakthi Karthi Durai, B. Rajan, M. Sundar Celin, J. Jeya A. Dhamodaran, Sasikala Madanapalle Institute of Technology & Science Department of Computer Applications Madanapalle India Tiruppur Kumaran College for Women Pg and Research Department of Computer Science Tamil Nadu Tiruppur India Kalasalingam Academy of Research and Education Computer Science and Engineering India Arbaminch Institute of Technology Arbaminch University Faculty of Electrical and Computer Engineering Ethiopia Kalasalingam Academy of Research and Education Department of Information Technology Viruthunagar Krishnankoil626126 India Rajasthan Jaipur India

ISBN: (纸本)9798350379945

This study presents a comprehensive study on smart home automation systems utilizing Internet of Things (IoT) sensor technology to achieve efficient energy conservation. The proposed system integrates ZigBee and WiFi communication protocols for effective and reliable connectivity across various smart devices within a home. Through the deployment of interconnected sensors and intelligent controllers, the system allows real-time monitoring and management of household energy usage, optimizing energy consumption and reducing waste. The combination of ZigBee for low-power, long-range sensor networks and WiFi for high-speed data transmission enables seamless interaction between smart appliances, lighting, heating, and cooling systems. Proposesd approach offers a scalable, cost-effective solution for enhancing home automation with an emphasis on energy conservation and sustainability. Also discussed the implementation, challenges, and future potential of IoT-based smart home systems for improved energy efficiency. © 2024 IEEE.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

Intelligent Personality Assessment and Verification from Handwriting using Machine Learning

引用

International Journal of Information technology (Singapore) 2024年第7期16卷 4541-4546页

作者： Mishra, Pradeep Kumar Mishra, Gouri Sankar Abidi, Ali Imam Kumar, Rajiv Sahoo, Ashok Kumar Maini, Tarun Department of Computer Science and Application SSET Sharda University Department of Computer Science and Engineering SSET Sharda University NVIDIA AI Learning & amp Research Center Department of Applied Computational Science and Engineering G L Bajaj Institute of Technology and Management Greater Noida Graphic Era Hill University School of Computer Science and Engineering Galgotias University

It is possible to tell a lot about a person just by looking at their handwriting. The way someone writes might tell you a lot about who, they are as a person. There has been a lot of study on the possibility of deducing aspects of a person’s character from their handwriting. In this piece, we’ll look at the different personality qualities and how they might be utilized to make an evaluation. The report includes a dataset showing a correlation between several traits of personality. The Big Five Personality Traits are mapped using handwritten personality data. It was suggested that a comparison table should be used to spot distinctive character quirks. The article includes a review of previous studies and an assessment of the current status of the topic. Handwriting embodies have both creativity and expressiveness. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Agreeableness Conscientiousness Extraversion Neuroticism Openness

来源：评论

学校读者我要写书评

暂无评论

XcepCovidNet: deep neural networks-based COVID-19 diagnosis

引用

Multimedia Tools and Applications 2024年第37期83卷 85195-85225页

作者： Juneja, Akshay Kumar, Vijay Kaur, Manjit Singh, Dilbag Lee, Heung-No Department of Electrical & amp Instrumentation Thapar University Punjab 147001 India Department of Information Technology Dr. B. R. Ambedkar National Institute of Technology Punjab 147001 India School of Computer Science and Artificial Intelligence SR University Telangana Warangal506371 India Research and Development Cell Lovely Professional University Punjab Phagwara144411 India Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of

Coronavirus (also known as COVID-19) is an extremely contagious disease spreading around the globe. An efficient and fast diagnostic method must be designed to identify COVID-19 patients. There are several methods for identification and monitoring of the disease, namely radiological imaging of the patient's chest and polymerase chain reaction (RT-PCR) test. Recent investigations have shown that radiological images are used to observe the effect of COVID on the lungs. Deep Learning is proven effective for image detection and classification in many applications. The majority of existing COVID-19 architectures detect irrelevant features for decision-making. In this paper, a novel network called XcepCovidNet is proposed for feature detection of chest X-rays. It employs transfer learning using hyperparameter-tuning to account for the inadequacies of the training dataset. The proposed model is found superior to pre-trained models such as VGG-19, ResNet-50, DenseNet-201, Xception, and DarkNet-19, in terms of different performance metrics. It is an automated, fast, reliable, and precise COVID-19 detection system for initial screening and diagnosing infected individuals. The obtained results indicate that XcepCovidNet yielded an accuracy of 98.67% and 93.66% for binary and four-class classification, respectively. A two-step verification is performed to validate the proposed model using different models of explainable artificial intelligence, i.e., LIME and occlusion sensitivity. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： COVID-19

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：