检索结果-内蒙古大学图书馆

A Voice Assistive Mobile Application Tool to Detect Cardiovascular Disease Using Machine Learning Approach

Biomedical Materials and Devices 2024年第2期2卷 1246-1257页

作者： Uddin, Khandaker Mohammad Mohi Dey, Samrat Kumar Babu, Hafiz Md. Hasan Department of Computer Science and Engineering Southeast University School of Science and Technology Bangladesh Open University Department of Computer Science and Engineering University of Dhaka

Many people all around the world suffer from heart disease, which is regarded as a severe illness. In healthcare, especially cardiology, it is crucial to accurately and quickly diagnose cardiac problems. In this research, we proposed an accurate and efficient mobile application-based system for diagnosing cardiac disease based on machine learning approaches. The developed mobile application is voice assistive, which makes the proposed application more user-friendly. Numerous machine learning methods have been examined in this study to predict and diagnose cardiovascular disease (CVD). A detailed comparative study was also drawn using eighteen (18) classification algorithms such as Support Vector Machines, Logistic Regression, Linear SVC, K-Nearest Neighbors, Naive Bayes, Stochastic Gradient Descent, Gradient Boosting, Ridge, Bagging, Random Forest, Decision Tree, XGB, LGBM, Extra Trees Perceptron, and Voting Classifier (hard or soft voting). Sixty-eight thousand nine hundred seventy-five (68,975) samples from various patients were used to test the performance of each approach. According to the study, Random Forest and Decision Trees have the best accuracy levels at 99.9%. However, the Support Vector Machine classifier had the lowest performance, barely achieving 60% accuracy. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC 2024.

关键词： Cardiovascular heart disease Detection Healthcare informatics Machine learning Mobile application

来源：评论

学校读者我要写书评

暂无评论

Study on the Analysis and Prediction of Drug Addiction Among University Students of Bangladesh Using Machine Learning 2nd

Study on the Analysis and Prediction of Drug Addiction Among...

引用

2nd International Conference on Big Data, IoT and Machine Learning, BIM 2023

作者： Ismail, Md. Afzal Islam, Ashraful Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh Department of Computer Science and Engineering Sylhet Engineering College Sylhet Bangladesh

ISBN: (纸本)9789819989362

Abuse of illicit substances among students at educational institutions is rapidly reaching crisis proportions in terms of the number of addicts. Substance abuse of all kinds is becoming an increasingly widespread problem. The goal of this research is to determine whether or not it is possible to make a prediction regarding the abuse of intoxicating substances that is frequent among university students in Bangladesh. The visualization of the data from this study indicated parameters or factors connected to the propensity to take drugs. In this particular study, machine learning is used to derive projections and predictions regarding the use of illicit drugs. In this study, Questionnaires were used to gather the data. For the purpose of carrying out this study, the sample consisted of a total of 468 different pupils. The use of Google Forms allowed for the collection of information as a questionnaire. The majority of those who participated were young adults (between the ages of 24 and 29), and the majority of those young adults were male students. At least 30% of the sample for this study admitted to experimenting with drugs for recreational purposes. According to their responses, the most significant factors that lead to student drug use include spending the night at the home of an addicted friend, being subjected to the destructive influence of peers, and smoking cigarettes. The neural network (Multilayer perceptron) algorithm gives an accuracy of 93% which is the highest, furthermore, the random forest algorithm gives the second-best accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Revealing inputs causing web API performance latency using response-time-guided genetic algorithm fuzzing

引用

Artificial Life and Robotics 2024年第4期29卷 459-472页

作者： Huang, Ying-Tzu Lee, Shin-Jie Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

Web APIs are integral to modern web development, enabling service integration and automation. Ensuring their performance and functionality is critical, yet performance testing is less explored due to the difficulty in detecting performance bugs. This paper presents a response time-guided genetic algorithm (GA) fuzzing approach to uncover web API performance latency in a black-box setting. Unlike traditional random input generation, our method uses GA to refine inputs through crossover and mutation, guided by response time-based fitness. We propose two seed generation methods: pairwise combinatorial testing using Mircosoft’s Pairwise Independent Combinatorial Testing (PICT) and randomly paired combinations. We compared our method with classic random fuzzing. Experiments on five real-world web APIs show that our approach significantly outperforms classic random fuzzing, identifying inputs with response times 1.5 to 26.3 times longer. Additionally, PICT-generated seeds demonstrated superior performance compared to randomly-paired combinations in 2 out of 5 APIs. Our findings highlight the potential of GA-based fuzzing to reveal web API performance latency, advocating for further research in this area. © International Society of Artificial Life and Robotics (ISAROB) 2024.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

ChatOps for microservice systems: A low-code approach using service composition and large language models

引用

Future Generation computer Systems 2024年 161卷 518-530页

作者： Wang, Sheng-Kai Ma, Shang-Pin Lai, Guan-Hong Chao, Chen-Hao Department of Computer Science and Engineering National Taiwan Ocean University Keelung202 Taiwan

The Microservice Architecture (MSA) plays a pivotal role in contemporary e-business, promoting service independence, autonomy, and continual evolution in line with the principles of DevOps. However, the distributed nature of the MSA introduces additional complexity, which requires familiarity with multiple DevOps (Development and Operations) tools, thereby increasing the learning curve. This paper presents a specialized ChatOps (Chat Operations) approach that allows MSA developers to compose new ChatOps capabilities in a low-code way (i.e., with minimal coding). The proposed ChatOps4Msa approach leverages established ChatOps functionalities to facilitate the real-time monitoring of service status, conduct service testing, track issues, and receive alerts using natural language or the proposed ChatOps Query Language (CQL). The use of large language models (LLMs) for functional intents also enhances the usability of the DevOps toolchain in microservices systems to streamline implementation. © 2024 Elsevier B.V.

关键词： Query languages

来源：评论

学校读者我要写书评

暂无评论

Investigating the Use of Automation in Cryptocurrency Trading 2

Investigating the Use of Automation in Cryptocurrency Tradin...

引用

2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Kaur, Inderpreet Chauhan, Yashica Gupta, Utsav Malik, Sagar Department of Computer Science and Engineering Uttar Pradesh India Department of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350371055

CryptoBot is a groundbreaking automated cryptocurrency trading system that answers the issues faced by traders in an environment where market dynamics change swiftly. Hence, CryptoBot employs a holistic approach of data gathering, preprocessing, predictive modelling, and real-time decision-making, thus it keeps analyzing real-time market data. The system then uses state of the art machine learning algorithms to make accurate predictions about price movements and determine when to enter and exit trades. This program also shows very promising results indicating a significant improvement in trading performance compared to traditional human-based strategies. CryptoBot therefore becomes an instrument of innovation for both experienced and non-experienced cryptocurrency investors. Thus, with its flexibility, precision, and smart automation users become more competitive reshaping how the investor interacts with the volatile but lucrative world of cryptocurrencies. As digital assets continue to reshape finance, CryptoBot stands at the forefront, exemplifying the future of intelligent trading. © 2024 IEEE.

关键词： Artificial Intelligence Automated Trading Cryptocurrency Machine Learning Market Analysis Price Prediction Risk Mitigation

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Model for Human Detection-Enhanced YOLO Comparative Analysis 4

Deep Learning Model for Human Detection-Enhanced YOLO Compar...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Suresh, P. Aswathy, R.H. Soms, Nisha Niranjani, V. Saveetha School of Engineering Simats Department of Computer Science and Engineering Thandalam Chennai India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Sri eshwar college of engineering Department of Computer science and engineering Coimbatore India

ISBN: (纸本)9798331540364

Video surveillance systems employing closed-circuit television (CCTV) are crucial for public safety. Accurately detecting humans within video frames is a core component of this technology. This knowledge is crucial for numerous uses, including detecting possible dangers, observing crowd dynamics, and examining patterns of human behavior. This research introduces a new method called YOLOv8, designed to enhance human detection capabilities within CCTV footage. The proposed algorithm, YOLOv8, is built upon the popular object recognition framework, YOLO, but with significant enhancements to improve its accuracy and efficiency in detecting humans. YOLOv8 utilizes deep convolutional neural networks (CNNs) and advanced object recognition techniques to achieve high accuracy in human detection, even in challenging environments such as low light conditions, occlusions, and varying scales of human poses. To assess the effectiveness of YOLOv8, various tests were performed using standard datasets and real-world CCTV surveillance footage. The results demonstrate that YOLOv8 outperforms existing human detection algorithms regarding accuracy, robustness, and real-time processing capability. YOLOv8 achieved an average precision of over 95% in human detection, making it highly suitable for everyday CCTV surveillance. The proposed YOLOv8 algorithm has the potential to significantly improve human detection in security camera footage and enhance public safety. This research contributes to advancing human detection technology and can benefit various domains, including law enforcement, public safety, and video analytics. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Quantum Circuits for Stabilizer Error Correcting Codes: A Tutorial

引用

IEEE Circuits and Systems Magazine 2024年第1期24卷 33-51页

作者： Mondal, Arijit Parhi, Keshab K. University of Minnesota Department of Electrical and Computer Engineering MinneapolisMN55455 United States

Quantum computers have the potential to provide exponential speedups over their classical counterparts. Quantum principles are being applied to fields such as communications, information processing, and artificial intelligence to achieve quantum advantage. However, quantum bits are extremely noisy and prone to decoherence. Thus, keeping the qubits error free is extremely important toward reliable quantum computing. Quantum error correcting codes have been studied for several decades and methods have been proposed to import classical error correcting codes to the quantum domain. Along with the exploration into novel and more efficient quantum error correction codes, it is also essential to design circuits for practical realization of these codes. This article serves as a tutorial on designing and simulating quantum encoder and decoder circuits for stabilizer codes. We first describe Shor's 9-qubit code which was the first quantum error correcting code. We discuss the stabilizer formalism along with the design of encoding and decoding circuits for stabilizer codes such as the five-qubit code and Steane code. We also design nearest neighbor compliant circuits for the above codes. The circuits were simulated and verified using IBM Qiskit. © 2001-2012 IEEE.

关键词： Timing circuits

来源：评论

学校读者我要写书评

暂无评论

Characterizing Sub-Terahertz Reflection and Its Impact on Next-Generation Wireless Networking

引用

IEEE Transactions on Communications 2024年第6期73卷 3778-3791页

作者： Shen, Ruiyi Ghasempour, Yasaman Princeton University Department Of Electrical And Computer Engineering PrincetonNJ08544 United States

Owing to the substantial bandwidth they offer, the exploration of 100+ GHz frequencies for wireless communications has surged in recent years. These sub-Terahertz channels are susceptible to blockage, which makes reflected paths crucial for seamless connectivity. However, at such high frequencies, reflections deviate from the known mirror-like specular behavior as the signal wavelength becomes comparable to the height perturbation at the surface of the reflectors. Such reflectors are considered electromagnetically 'rough' which results in random non-specular reflection components that are not well understood. In this paper, we delve into the fundamentals of rough scattering to analyze its implications for sub-THz wireless networks, including the existence and strength of non-specular links, mobility resilience, and beam reciprocity. Further, we present a novel framework that re-purposes IEEE 802.11ay-like beam sweeps for estimating the surface roughness of a reflector in the vicinity of the communication nodes. Through extensive modeling, simulation, and experiments with everyday reflector samples, we demonstrate the impact of rough scattering on over-the-air data links and evaluate the accuracy of our roughness inference framework. © 1972-2012 IEEE.

关键词： Terahertz waves

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis on Sentiment Using Deep Learning and Transformers 6

A Comprehensive Analysis on Sentiment Using Deep Learning an...

引用

6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Mohsin, Md. Wankhede, Jaishri Fatima, Afshan Solanki, Vijender Kumar Department of Computer Science and Engineering Hyderabad India Stanley College of Engineering & Technology for women Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331505790

Emotions describe the social attachment between the human that are ascendancy by cultural norms, social interactions, and Interpersonal bonds. So in this paper we are represent the application of deep learning models and transformers for emotion analysis on text based data. We are using different Word2Vec approaches for analyze the emotion from the textual data. As we know, Distributed Bag of Words (DBOW), Distributed Memory Concatenation (DMC), Distributed Memory Mean (DMM), and hybrid models DBOW+DMC and DBOW+DMM that's all are the part of Word2Vec model and all are based on deep learning techniques. In this paper we also explore the NLP transformer such as BERT, BART, DistilBERT, RoBERTa, and GPT to analyze the emotion of data and compare the performance of deep learning based technique with transformers based techniques. The aim of the exploration is compare the effectiveness of these models using standard sentiment analysis datasets, assessing performance through accuracy metrics. © 2024 IEEE.

关键词： Distribution transformers

来源：评论

学校读者我要写书评

暂无评论

HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism

引用

computers, Materials & Continua 2024年第8期80卷 3351-3377页

作者： TugbaÇelikten Aytug Onan Department of Software Engineering Faculty of TechnologyManisa Celal Bayar UniversityManisa45140Turkey Department of Computer Engineering Faculty of Engineering and ArchitectureIzmir KatipÇelebi UniversityIzmir35620Turkey

Class Title:Radiological imaging method a comprehensive overview *** GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the *** and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed *** recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis ***:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical ***:Radiological imaging is an extremely important tool in modern medicine to assist in medical *** work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.

关键词： Generative artificial intelligence AI-generated text detection attention mechanism hybrid model for text classification

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：