检索结果-内蒙古大学图书馆

2nd International Conference on Advances in Water Treatment and Management, ICAWTM 2023

作者： Shah, Vaishvi Ramanuj, Ashwini Patel, Krisha Jethloja, Shruti Swain, Debabrata Kumar, Manish Department of Computer Science and Engineering Pandit Deendayal Energy University Knowledge Corridor Gujarat Gandhinagar382007 India Department of Electronics and Communication Engineering Pandit Deendayal Energy University Knowledge Corridor Gujarat Gandhinagar382007 India

ISBN: (纸本)9789819759545

Water, being the most vital aspect of all living creatures and the environment, its availability and quality are paramount concerns for global sustainability. Water quality is a fundamental property that determines the suitability of water for a certain application based on its intended use and the required physical, chemical, and biological characteristics. Recent activities of humans has led to the concentrations of substances in natural water resources to exceed the ideal concentration values, resulting in a modification of the natural composition. This effect has led us to find an adequate solution for water quality index (WQI) calculation as well as the prediction of water quality classification (WQC) which is suitable for usage in everyday life, from publicly available data with ML-based predictive models being a driving force in the process. A number of preprocessing techniques were performed on the dataset, which includes the relevant imputation of some missing categorical and numeric data points, along with the use of unsupervised Non-Negative Matrix Factorization (NNMF) technique and balancing of the target data using SMOTE algorithm. Different machine learning models have been applied as a part of model training for WQC forecasting. The results obtained from these models were assessed, examined, and compared on the basis of their accuracy, recall, precision, as well as F1-score. Prediction results demonstrated that the Gradient Boosting Classifier achieved the best results (96.99%) for WQC prediction. Water Management resources can benefit greatly from this kind of promising research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Non-negative matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Detecting Fake News Sources on Twitter Using Deep Neural Network 11

Detecting Fake News Sources on Twitter Using Deep Neural Net...

引用

11th International Conference on Information and Education Technology, ICIET 2023

作者： Bhatia, Thanaphan Manaskasemsak, Bundit Rungsawang, Arnon Kasetsart University Massive Information & Knowledge Engineering Laboratory Department of Computer Engineering Faculty of Engineering Bangkok10900 Thailand

ISBN: (纸本)9781665465489

Social media provides a rapid, simple, and accessible platform for people to communicate and share news through the Internet. However, the information published on this platform is not always trustworthy. As a result, malicious actors often use social media to disseminate fake news or mislead news readers, such as with personal or political attacks that could spark protests or riots. In this paper, we propose a learning technique for detecting fake news sources (i.e., fake users) on the Twitter platform. Three main types of features - tweet content, published time, and social graph - have been defined and extracted from Twitter to create a deep neural network (DNN) as a predictive model. We conducted experiments on PolitiFact, a standard FakeNewsNet dataset. The results show that the proposed approach outperforms traditional baselines with 98.7% accuracy. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Lay Summarization of Biomedical Documents with Discourse Structure-Based Prompt Tuning 28th

Lay Summarization of Biomedical Documents with Discourse S...

引用

28th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2023

作者： Wu, Yu-Hsuan Chiu, Chi-Min Kao, Hung-Yu Intelligent Knowledge Management Lab Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9789819717101

Transforming complex biomedical texts into accessible lay summaries is a critical endeavor in Natural Language Generation (NLG). This study addresses the challenges associated with this task by employing a multi-aspect approach. Firstly, we undertake a comprehensive analysis of discourse structures within a diverse range of biomedical datasets and clarify underlying patterns and structures. Secondly, we designed the power of prompting strategies to integrate training on these varied datasets, thereby reducing the noise introduced by their diversity. This twofold strategy fine-tunes the model’s training and enriches it with the ability to generate coherent and simplified lay summaries of biomedical content. Our experimental results clearly demonstrate the effectiveness of our study, underscoring its potential to make complex medical information more accessible to general readers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Classification with ensembles and case study on functional magnetic resonance imaging

引用

Digital Communications and Networks 2022年第1期8卷 80-86页

作者： Adnan OM.Abuassba Zhang Dezheng Hazrat Ali Fan Zhang Khan Ali Department of Computer Science Arab Open University-PalestineRamallahPalestine Department of Computer Science and Communication Engineering University of Science and Technology BeijingChina and Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabadPakistan

The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to design an efficient ensemble *** though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for *** paper proposes a general framework for creating ensembles in the context of ***,the ensemble framework consists of four stages:objectives,data preparing,model training,and model *** is comprehensive to design diverse *** proposed ensemble approach can be used for a wide variety of machine learning *** validate our approach on real-world *** experimental results show the efficiency of the proposed approach.

关键词： Classification Ensemble learning Extreme learning machine

来源：评论

学校读者我要写书评

暂无评论

Optimizing Heart Attack Prediction Through OHE2LM: A Hybrid Modelling Strategy

引用

Journal of Electrical Systems 2024年第1期20卷 66-75页

作者： Mall, Pawan Kumar Srivastava, Swapnita Patel, Mitul M. Kumar, Aniruddh Narayan, Vipul Kumar, Sanjay Singh, P.K. Singh, D.S. GL Bajaj Institute of Technology and Management India Department of Electronics and Communication Engineering Parul Institute of Engineering and Technology Parul University Vadodara India Department of Computer Science and Engineering Galgotias College of Engineering and Technology Knowledge Park-2 Greater Noida India Galgotias University Uttar Pradesh Gautam Buddha Nagar India Rajkiya Engineering College Azamgarh India Computer Science and Engineering Department Madan Mohan Malaviya University Of Technology Uttar Pradesh Gorakhpur273010 India Computer Science and Engineering Department Madan Mohan Malaviya University of Technology Uttar Pradesh Gorakhpur273010 India

Predicting heart attacks stands as a significant concern contributing to global morbidity. Within clinical data analysis, cardiovascular disease emerges as a pivotal focus for forecasting, wherein Data Science and machine learning (ML) offer invaluable tools. These methodologies aid in predicting heart attacks by considering various risk factors Just like high blood pressure, increased cholesterol levels, irregular pulse rates, and diabetes, this research aims to enhance the accuracy of predicting heart disease through machine learning *** study introduces a MLdriven approach, termed ML-ELM, dedicated to forecasting heart attacks by analysing diverse risk factors. The proposed ML-ELM model is compared with alternative Utilizing machine learning techniques like Support Vector Machines, Logistic Regression, Naïve Bayes, and XGBoost is a key aspect of this exploration into different approaches for predictive modeling., is part of the research strategy. The dataset utilized for heart disease symptoms is sourced from the UCI ML Repository. The outcomes reveal that our proposed ML-ELM model has demonstrated superior predictive performance among the ML techniques tested. ML models show notable efficiency in identifying heart attack symptoms, particularly with boosting algorithms. Accuracy assessments were employed to gauge the predictive ability, Our suggested model demonstrated an outstanding accuracy rate of 96.77%. © JES 2024 on-line: ***

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Study on Advancements in Text Mining and Natural Language Processing 2

A Comprehensive Study on Advancements in Text Mining and Nat...

引用

2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Mahire, Sarthak Balaji Saravanan, U.K. Murali, M. Prabakaran, N. Vellore Institute of Technology School of Computer Science and Engineering Vellore632014 India Knowledge Institute of Technology Department of Computer Science and Engineering Salem India Sona College of Technology Department of Information Technology Salem India

ISBN: (纸本)9798331534950

Text mining and Natural Language Processing (NLP) have witnessed significant advancements in recent years, driven by the increasing availability of unstructured data and the development of sophisticated machine learning models. This review explores the evolution of text mining and NLP, highlighting the transition from rule-based systems to modern deep learning approaches. This paper reviews various techniques and its impact across various domains. Challenges such as data bias and model interpretability still remain. The paper also discusses future directions, emphasizing the need for fair, interpretable and sustainable NLP systems. This paper aims to provide insights into the current state of text mining and NLP, the challenges faced and potential pathways for future research. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Hybrid Threshold Speech Enhancement Scheme Using TEO and Wavelet Coefficients 2

Hybrid Threshold Speech Enhancement Scheme Using TEO and Wav...

引用

2nd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2023

作者： Latha, R. Suhas, A.R. Pradeep Kumar, B.P. Ibrahim, M.Mohammed Sathiyapriya, V. HKBK College of Engineering Department of Electronics and Communication Engineering Bangalore India Sona College of Technology Department of Computer Science and Engineering Salem India Knowledge Institute of Technology Department of Computer Science and Engineering Salem India

ISBN: (纸本)9798350397635

Speech Enhancement (SE) aims to improve the quality of degraded speech while maintaining its intelligibility. The Wavelet Transform (WT) has become a powerful tool of signal analysis thereby widely used in signal detection and signal denoising. In this paper, we propose an effective means of SE by a hybrid threshold scheme using WT. The proposed methodology looks into both falling the noise and preserving edges of the speech signal unlike the conventional Hybrid Threshold (HT) and Soft Threshold (ST) in the wavelet domain. The threshold value in the wavelet domain is maintained constant for all sub-bands of the signal which reduces denoising efficiency. A novel speech augmentation technique built on the wavelet onsets and time adaption of introduced by calculating wavelet coefficients of the Teager Energy. Performance analysis of speech enhancement techniques using Wavelet coefficients and Teager Energy Operator (TEO) with hybrid threshold method is done. The experiment is carried out for speech data with various values of SNR vacillating from -10 to +10 db with Additive White Gaussian Noise (AWGN). © 2023 IEEE.

关键词： Speech enhancement

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach for Detecting Malware Using Autoencoder

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer Science 2024年第8期51卷 1051-1059页

作者： Panchagnula, Venu Madhav Satya Keerthi, N.V.L.Ch. Surekha, S. Sujatha, R. Veeraiah, Duggineni Ramesh, Eluri Lakshmi, B. Electronics and Communication Engineering Department Prasad V Potluri Siddhartha Institute of Technology Andhra Pradesh Vijayawada India Computer Science and Engineering Department Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur India AIML Department Vignana Bharathi Institute of Technology Ghatkesar Hyderabad India Information Technology Department M. Kumarasamy College of Engineering Karur India Computer Science and Engineering Department Lakireddy Bali Reddy College of Engineering Andhra Pradesh Mylavaram India Computer Science and Engineering Department R.V.R & J. C. College of Engineering Guntur India Electronics and Communication Engineering Department Rajiv Gandhi University of Knowledge Technologies Andhra Pradesh Nuzvid India

Research in the field of malware detection is currently leaning toward methods based on artificial intelligence algorithms due to the increasing limitations of traditional detection methods and the increasing accuracy of these methods. This study therefore introduces a novel approach to malware detection. This method integrates a deep learning model's autoencoder network with a grayscale graphic depiction of malware. By looking at the autoencoder's reconstruction error, we may assess if the grey-scale picture approach is feasible to use for malware detection. Additionally, it differentiates between malicious and safe software by utilizing the autoencoder's dimensionality reduction capabilities. Using the Android dataset, our newly introduced detection model attained a 95% accuracy and maintained a consistently high F-score of approximately 95%. This outperformed more conventional methods of machine learning detection. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

Security challenges and defense approaches for blockchain-based services from a full-stack architecture perspective

引用

Blockchain(Research and Applications) 2023年第3期4卷 18-38页

作者： Hongsong Chen Xietian Luo Lei Shi Yongrui Cao Yongpeng Zhang Department of Computer Science University of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

As an advantageous technique and service,the blockchain has shown great development and application ***,its security has also met great challenges,and many security vulnerabilities and attack issues in blockchain-based services have ***,security issues of blockchain have attracted extensive ***,there is still a lack of blockchain security research from a full-stack architecture perspective,as well as representative quantitative experimental reproduction and *** aim to provide a security architecture to solve security risks in blockchain services from a full-stack architecture ***,we propose a formal definition of the full-stack security architecture for blockchain-based services,and we also propose a formal expression of security issues and defense solutions from a full-stack security *** use ConCert to conduct a smart contract formal verification experiment by property-based *** security vulnerabilities of blockchain services in the Common Vulnerabilities and Exposures(CVE)and China Nation Vulnerability Database(CNVD)are selected and ***,three real contract-layer real attack events are reproduced by an experimental *** Alibaba's blockchain services and Identity Mixer in Hyperledger Fabric as a case study,the security problems and defense techniques are analyzed and *** last,the future research directions are proposed.

关键词： Security and privacy Blockchain-based services Full stack Architecture perspective Case and experimental study Formal verification

来源：评论

学校读者我要写书评

暂无评论

Speech-to-text Transfiguration in Language Numerals for Perpetual Deaf Patients 2

Speech-to-text Transfiguration in Language Numerals for Perp...

引用

2nd International Conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2023

作者： Pradeep Kumar, B.P. Venkatesan, C. Suhas, A.R. Balamurugan, D. Sathiyapriya, V. HKBK College of Engineering Department of Electronics and Communication Engineering Bangalore India Sona College of Technology Department of Computer Science and Engineering Salem India Knowledge Institute of Technology Department of Computer Science and Engineering Salem India

ISBN: (纸本)9798350397635

This paper primarily designates the isolated words transfiguration in the Kannada language based on a few techniques like Mel Frequency Cepstral Coefficients (MFCCs), Euclidean distance measure, Wavelet Transforms and Vector Quantization (VQ) technique. The contiguous match to the test speech exclamation is found by comparing the Euclidean distance value of the MFCC coefficients with that of the utterances present in the training set. The matched sampled word is detected by the display of its text equivalent message trained during the test phase. MATLAB R2019b software is employed to build the framework. © 2023 IEEE.

关键词： Wavelet transforms

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：