检索结果-内蒙古大学图书馆

5th International Conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Al-Hgaish, Areen Atan, Rodziah Yaakob, Razali Osman, Mohd Hafeez Department of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang44330 Malaysia Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang44330 Malaysia

ISBN: (纸本)9789819761050

The utilization of Data-Driven Machine Learning (DDML) models in the healthcare sector poses unique challenges due to the crucial nature of clinical decision-making and its impact on patient outcomes. A primary concern in this domain is the data quality that forms the basis for these models, which is essential for their effectiveness. While numerous studies are dedicated to leveraging Machine Learning (ML) to enhance patient care, a substantial gap exists in understanding and evaluating the quality of training data before training ML models. This issue is exacerbated by the lack of well-defined standards to ensure that data characteristics align with the specific goals of ML in healthcare. To address this, our study introduces a conceptual three-dimensional framework focusing on data accuracy, completeness, and consistency aimed at assessing and improving the quality of training data. This framework is designed to enhance the performance, predictability, and interpretability of healthcare-specific ML models and reduce biases, thus bridging current research gaps and laying the groundwork for future developments in ML-driven healthcare systems. This paper presents the initial step for our proposed Data Quality Framework (DQF), which addresses the three dimensions mentioned above. It discusses its potential implications and applications in healthcare data, and its main goal is to provide a comprehensive overview of the proposed DQF, illustrating its significance in advancing healthcare data quality and ultimately improving patient outcomes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data accuracy

来源：评论

学校读者我要写书评

暂无评论

Liquid Neural Networks - Classification and Time Series Forecasting Use Case 8

Liquid Neural Networks - Classification and Time Series Fore...

引用

8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Kavakli, Mehmet Ucar, Ferhat Gazi Vocational and Technical Collage Computer Science Department Elazig Turkey Firat University Department of Software Engineering Elazig Turkey

ISBN: (纸本)9798331531492

This study aims to comprehensively examine the potential of Liquid Neural Networks (LNNs) in machine learning field and various application areas. LNNs offer significant advantages over traditional neural networks due to their adaptive learning capacity and dynamic structures. The study involves visual classification using the MNIST dataset and time series analysis on the Yahoo Finance dataset. The performance of the LNN model on these two different datasets has been thoroughly evaluated through the training and testing processes, with results rigorously analyzed. This comprehensive analysis aims to provide an important discussion of the potential uses and advantages of the LNN model. © 2024 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Green Computing Adoption: Understanding the Role of Individual, Social, and Organizational Factors 19

Green Computing Adoption: Understanding the Role of Individu...

引用

19th International Conference on Evaluation of Novel Approaches to software engineering, ENASE 2024

作者： Anni, Fahima Akter Islam, Muhammad Rezaul Sadia, Farzana Hasan, Mahady Rokonuzzaman, M. Department of Software Engineering Independent University Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Department Electrical and Computer Engineering North South University Dhaka Bangladesh

ISBN: (纸本)9789897586965

This study investigates the factors influencing the attitudes of software developers and IT professionals towards Green Information Technology (GIT) in Bangladeshi IT/software firms and examines their impact on engagement in green computing practices. Data was collected from 130 participants. A thorough literature review was conducted. The findings highlight key individual factors that influence employees’ attitudes, including awareness, knowledge, and perception of environmental issues. The study demonstrates the connection with GIT attitudes and behavior modification, especially through stated usage of green computing methods. Data analysis confirms 5 out of 8 hypotheses and reveals the complexity of the relationships between the constructs. The report promotes the adoption of Green IT technology by software companies in Bangladesh and highlights the significance of an organized office system integrating Green IT. Limitations include a relatively small sample size and the multidimensional nature of the relationships between the constructs. The findings can assist software companies in addressing customer concerns about the performance and functionality of green computing practices, ultimately promoting sustainable computing practices in the IT sector of Bangladesh. © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Green computing

来源：评论

学校读者我要写书评

暂无评论

Controllable chaos in the coupled waveguide-optomechanical system with phase shifter

引用

science China(Physics,Mechanics & Astronomy) 2025年第4期68卷 26-34页

作者： Deng-Wei Zhang Pei-Qi Qin Li-Li Zheng Zhi-Ming Zhan Xin-You Lü Department of Mathematics and Physics Luoyang Institute of Science and TechnologyLuoyang 471023China School of Computer and Information Engineering School of SoftwareLuoyang Institute of Science and TechnologyLuoyang 471023China School of Artificial Intelligence Jianghan UniversityWuhan 430056China School of Physics Huazhong University of Science and TechnologyWuhan 430074China

We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG)can induce chaotic *** underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP),where field localization dynamically enhances the optomechanical nonlinearity,leading to the generation of chaotic *** addition,due to the sensitivity of chaos to phase in the vicinity of the EP,we propose a theoretical scheme to measure the optical phase perturbations using *** work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.

关键词： cavity optomechanics chaos exceptional point

来源：评论

学校读者我要写书评

暂无评论

A Blockchain Framework for Securing Examination Results in Higher Institutions of Learning

A Blockchain Framework for Securing Examination Results in H...

引用

2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Charles, Taiwo LYemi Azeta, Ambrose A. Crawford University Department of Computer and Mathematical Sciences Nigeria Namibia University of Science and Technology Department of Software Engineering Windhoek Namibia

ISBN: (纸本)9798350358155

With data security and transparency guaranteed, stakeholders' confidence and trust in certificates and degrees from our universities and colleges will improve, third party investments in education will also increase and government effort at building a strong and high quality education for all will be adequately complemented. Existing traditional approaches to execution of academic activities lacks capabilities in the area of preventing alterations to academic records after being recorded, preventing single points of failure, providing enhanced data security, encouraging the use of decentralized storage system and most importantly, ensuring distributive transparency. This study provides a blockchain framework for securing examination results in higher institutions of learning. Some of the methodology engaged includes Blockchain technology, Cryptography, schematic diagram, and Unified Modelling Language (UML). Java was used to implement the blockchain component services. Generic flat file was used to implement the database. Having adopted a measurement scale of 1-5 in this study and based on the mean ratings of the usability average rating of 4.18 findings, it can be concluded that the blockchain framework has a "Good Usability"rating. Using blockchain platform for storing students' examination results ensures transparency and provides enhance data security by locking the finalized scores to prevent any alteration. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

Automatic Anomaly Monitoring in Public Surveillance Areas

引用

Intelligent Automation & Soft Computing 2023年第3期35卷 2655-2671页

作者： Mohammed Alarfaj Mahwish Pervaiz Yazeed Yasin Ghadi Tamara al Shloul Suliman A.Alsuhibany Ahmad Jalal Jeongmin Park Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Bahria UniversityIslamabadPakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Humanities and Social Science Al Ain UniversityAl Ain15551UAE Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Engineering Korea Polytechnic University237 Sangidaehak-ro Siheung-siGyeonggi-do15073Korea

With the dramatic increase in video surveillance applications and public safety measures,the need for an accurate and effective system for abnormal/sus-picious activity classiﬁcation also *** it has multiple applications,the problem is very *** this paper,a novel approach for detecting nor-mal/abnormal activity has been *** used the Gaussian Mixture Model(GMM)and Kalmanﬁlter to detect and track the objects,*** that,we performed shadow removal to segment an object and its *** object segmentation we performed occlusion detection method to detect occlusion between multiple human silhouettes and we implemented a novel method for region shrinking to isolate occluded *** c-mean is utilized to verify human silhouettes and motion based features including velocity and opticalﬂow are extracted for each identiﬁed *** Wolf Optimizer(GWO)is used to optimize feature set followed by abnormal event classiﬁcation that is performed using the XG-Boost classiﬁ*** system is applicable in any surveillance appli-cation used for event detection or anomaly *** of proposed system is evaluated using University of Minnesota(UMN)dataset and UBI(Uni-versity of Beira Interior)-Fight dataset,each having different type of *** mean accuracy for the UMN and UBI-Fight datasets is 90.14%and 76.9%*** results are more accurate as compared to other existing methods.

关键词： Abnormal event classiﬁcation gray wolf optimizer region shrinking xg-boost classiﬁer

来源：评论

学校读者我要写书评

暂无评论

Urdu Sentiment Analysis Using Deep Learning 18

Urdu Sentiment Analysis Using Deep Learning

引用

18th International Conference on Open Source Systems and Technologies, ICOSST 2024

作者： Nasir, Imtisall Bazai, Sibghat Ullah Ghafoor, Muhammad Imran Marjan, Shah Balochistan University of Information Technology Engineering and Management Science Department of Computer Science Quetta Pakistan Balochistan University of Information Technology Engineering and Management Science Department of Computer Engineering Quetta Pakistan Pakistan Television Corporation Department of Engineering Lahore Pakistan Balochistan University of Information Technology Engineering and Management Science Department of Software Engineering Quetta Pakistan

ISBN: (纸本)9798331508692

Sentiment Analysis is a deep text analysis to determine the expressions from the written text, The Urdu language holds significant importance due to the usage of these social media platforms and content generated at these platform in Urdu. Effective sentiment analysis in Urdu can provide valuable information about social trends, customer feedback, and public opinion on different sets of topics in the Urdu context. This study uses an deep learning (ANN) Artificial Neural Network to predict and classify the sentiments in the Urdu language, labeling them into positive, negative, and neutral sentiments. To achieve the research goals, advanced preprocessing techniques were utilized such as removing stop words, emojis, emails, and characters, removing symbols, performing lemmatization to expand the meaning of text, tokenized each word by using Lexicon-based approach and ngram. The dataset are tweets dependent and have 1,140,021 tweets. These steps ensure that data is standardized and cleaned to be split into training and testing. The datasets were converted into sequence and categorized to be input into the ANN model. The ANN model was trained and achieved an accuracy of 90%, precision of 98%, and f1-score of 97%. These high values indicate that the model accurately predicted the sentiments in the Urdu text. However, during experimentation limitations were discovered due to the complexities of Urdu text, difficult script patterns, and linguistic problems that were not solved by the preprocessing technique. During analysis, the limitation was discovered due to the limited number of preprocessing techniques and tools for Urdu text. However, the study highlights the potential of neural networks, especially ANN in Urdu sentiment analysis. This study contributed significantly to Urdu natural language processing by providing robust techniques and identifying limitations to work on it as a research problem. © 2024 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

An improved pulse coupled neural networks model for semantic IoT

引用

Digital Communications and Networks 2024年第3期10卷 557-567页

作者： Rong Ma Zhen Zhang Yide Ma Xiping Hu Edith C.H.Ngai Victor C.M.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of Medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and Computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PCNN are determined by trial and error,which limits its *** overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this *** IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation *** IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Adventures in data analysis: a systematic review of Deep Learning techniques for pattern recognition in cyber-physical-social systems

引用

Multimedia Tools and Applications 2024年第8期83卷 22909-22973页

作者： Amiri, Zahra Heidari, Arash Navimipour, Nima Jafari Unal, Mehmet Mousavi, Ali Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Department of Software Engineering Haliç University Istanbul34060 Turkey Department of Computer Engineering Kadir Has Universitesi Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou64002 Taiwan Department of Computer Engineering Nisantasi Universitesi Istanbul Turkey Islamic Azad University Sanandaj Branch Sanandaj Iran

Machine Learning (ML) and Deep Learning (DL) have achieved high success in many textual, auditory, medical imaging, and visual recognition patterns. Concerning the importance of ML/DL in recognizing patterns due to its high accuracy, many researchers argued for many solutions for improving pattern recognition performance using ML/DL methods. Due to the importance of the required intelligent pattern recognition of machines needed in image processing and the outstanding role of big data in generating state-of-the-art modern and classical approaches to pattern recognition, we conducted a thorough Systematic Literature Review (SLR) about DL approaches for big data pattern recognition. Therefore, we have discussed different research issues and possible paths in which the abovementioned techniques might help materialize the pattern recognition notion. Similarly, we have classified 60 of the most cutting-edge articles put forward pattern recognition issues into ten categories based on the DL/ML method used: Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Generative Adversarial Network (GAN), Autoencoder (AE), Ensemble Learning (EL), Reinforcement Learning (RL), Random Forest (RF), Multilayer Perception (MLP), Long-Short Term Memory (LSTM), and hybrid methods. SLR method has been used to investigate each one in terms of influential properties such as the main idea, advantages, disadvantages, strategies, simulation environment, datasets, and security issues. The results indicate most of the articles were published in 2021. Moreover, some important parameters such as accuracy, adaptability, fault tolerance, security, scalability, and flexibility were involved in these investigations. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Extended Reality and Digital Twin in the Oil and Gas Pipeline Industry: A Systematic Review on Applications, Trends, and Future Directions 23

Extended Reality and Digital Twin in the Oil and Gas Pipelin...

引用

23rd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024

作者： Sarvesh, Muskan Kang, Ryan Nam, Hyeongil Park, Simon Hugo, Ron Maurer, Frank Kim, Kangsoo University of Calgary Department of Electrical and Software Engineering Canada University of Calgary Department of Mechanical and Manufacturing Engineering Canada University of Calgary Department of Computer Science Canada

ISBN: (纸本)9798331516475

Immersive and simulation technologies, such as Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Digital Twins (DTs), have proven effective in enhancing decision-making, streamlining operations, and improving safety through intuitive visualizations. Unsurprisingly, the oil and gas (O&G) pipeline industry is increasingly turning to these technologies to tackle complex construction and resource management challenges. This paper reviews the applications, benefits, and future trends of these technologies, focusing on integration and emerging trends in monitoring, training, maintenance, and testing. It identifies potential gaps, offers guidance for future research, and emphasizes adapting to technological evolution, providing insights to improve system reliability and sustainability in O&G pipeline operations using immersion and simulation methods. © 2024 IEEE.

关键词： Gas pipelines

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：