检索结果-内蒙古大学图书馆

2nd International Conference on computer, Communication and Control, IC4 2024

作者： Ravinder, Bathini Seeni, Senthil Kumar Prabhu, V.S. Asha, P. Maniraj, S.P. Srinivasan, C. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India Cognizant Technology Solutions Buffalo Grove Department of Mobile Application Development Illinois United States R.M.D. Engineering College Department of Electronics and Communication Engineering Tamilnadu Chennai India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Srm Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

Data mining on the web has developed into a simple and crucial tool for finding relevant information. When it comes to file transfers, the World Wide Web is the user's first choice. Finding useful information and trends in the ever-expanding amount of data available online is becoming ever more challenging and time-consuming. When dealing with massive amounts of textual data often seen online, there are a number of benefits to using the Naive Bayes method for web data mining. Web data mining using the Naive Bayes algorithm seeks to mine massive amounts of textual material on the web for useful patterns, insights, and knowledge. Text classification and categorization tasks are the most common uses of the Naive Bayes method in online data mining. Expert and user-requested data may be difficult to mine from the sea of unorganized and contradictory material that is the World Wide Web. Relevant data (hyperlinks, contents, web use records) is extracted from the web using a variety of mining methods. Internet-centric data mining is a subfield of data science. Structure mining, content mining, and use mining are the three main categories of online data mining. Each of these categories employs a unique set of methods, instruments, strategies, and Naïve Bayes algorithm to mine the web's vast data stores for useful insights. The results show the density and velocity of web mining using Naïve Bayes algorithm. © 2024 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Framework for classifying gait disorders and fall prevention

Framework for classifying gait disorders and fall prevention

引用

International Conference on computer, Electrical & Communication engineering (ICCECE)

作者： Rupa Saha Koushik Karmakar Suparna Biswas Department of Computer Application Narula Institute of Technology Department of Computer Science and Technology Narula Institute of Technology Department of Computer Science & Engineering MAKAUT W B

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

One of the crucial approaches that use tracking and analyzing human movement for the identification of functional disorders and illnesses of the human body is known as the gait analysis method. This method helps diagnose neurological and musculoskeletal conditions. It also tracks the effectiveness of rehabilitation. However, conventional techniques for analyzing gait frequently depend on costly items and methods like fixed lab apparatus, force plates, and motion capture devices. But new developments in wearable sensor technology and machine learning provide new methods that are cheaper, more affordable, portable, and easily accessible. It continuously tracks gait in real-world settings. In this work, the use of wearable sensors for gait analysis, which includes devices like magnetometers, gyroscopes, and accelerometers, is examined. They are integrated into gadgets like smartphones, insoles, and smartwatches and offer real-time kinematic data that machine learning algorithms can analyze. Some of the important gait parameters 1that are extracted from sensor data are stride length, cadence, and gait symmetry. Machine learning is used to process this data and use it for categorization and gait analysis. The suggested method improves patient monitoring outside of clinical settings. It supports individualized rehabilitation plans and also identifies early indicators of gait abnormalities. The use of the wearable sensor-based gait analysis may emerge as a game-changing medical tool. It offers constant, discrete monitoring and prompts intervention in gait-related disorders. This works explains it thoroughly. This report offers insights for upcoming researchers in the field by surveying the state of the art in wearable sensor-based gait analysis.

关键词： Legged locomotion Machine learning algorithms Accuracy Tracking Reviews Real-time systems Biomedical monitoring Gait recognition Wearable sensors Smart phones

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of Language Disorders in Children Using NLP and Machine Learning

Automated Detection of Language Disorders in Children Using ...

引用

2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Malathi, P. Legapriyadharshini, N. Nair, Shruthi S Sujatha, M.P. Sadaieswaran, R. Thirumalaikumari, T. Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Data Analytics Tamil Nadu Chennai India Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Application Tamil Nadu Chennai India Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Agni College of Technology Department of Computer Science and Engineering Chennai India Tagore College of Arts and Science Department of Computer Applications Chennai India Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Science Chennai India

ISBN: (纸本)9798350309140

The purpose of the study is to address the essential need for a more efficient and objective technique for detecting language disorders in children, overcoming the constraints of standard manual evaluation systems. Existing systems, which utilize subjective evaluations and manual scoring, frequently result in lengthy processes and possible errors. To solve these issues, the proposed system automates the identification process by combining Natural Language Processing (NLP) and Machine Learning (ML). The system achieves a breakthrough in accuracy by normalizing text and extracting a comprehensive collection of linguistic features using advanced NLP techniques. The implementation involves difficult data preprocessing, extensive feature extraction, and the application of a cutting-edge Support Vector Machine (SVM) classifier. The proposed system achieves a 15% increase in accuracy, a 12% increase in precision, a 10% increase in recall, and an 11% increase in F1 score over existing systems. The confusion matrices show improved prediction skills, while accuracy across varied linguistic samples demonstrates the system's adaptability. Finally, the proposed system not only speeds up the detection of language disorders but also provides the groundwork for deeper insights into linguistic development, with revolutionary potential in educational and therapeutic settings. © 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

Neural Networks for Natural Language Processing

Neural Networks for Natural Language Processing

引用

2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Deshpande, Sudhindra B. Velrani, K. Sundara Bhagyalakshmi, A. Vani, M. Sowmya Ananthi, S.N. Sahu, Devika Department of Information Science and Engineering KLS Gogte Institute of Technology Udyambag Karnataka Belagavi590006 India Department of Information Technology Sathyabama Institute of Science and Technology Tamil Nadu Chennai600119 India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600062 India Department of Computer Application Mohan Babu University Andhra Pradesh Tirupati517501 India Department of Computer Science and Engineering S.A Engineering College Tamil Nadu Chennai600077 India Department of Computer Science and Engineering Government Engineering College Chhattisgarh Raipur492001 India

ISBN: (纸本)9798350374933

Artificial neural networks have made Natural Language Processing (NLP) a lot different because they can encode language data more efficiently. A lot of different natural language processing tasks, like mood analysis, translation, and text production, have been done very well with these networks are based on the neuronal structure of the human brain. This abstract delves into the fundamental principles of neural networks in natural language processing, with a particular emphasis on notable structures, including the more recent Transformer models, CNNs, and RNNs. The investigation investigates the potential future trajectories, challenges, and applications of improving language comprehension and developing assignments. © 2024 IEEE.

关键词： Natural language processing neural networks neural networks NLP recurrent neural networks RNNs

来源：评论

学校读者我要写书评

暂无评论

Finite Element Biomechanical Analysis of Pedicle Screw Redirection Insertion 24

Finite Element Biomechanical Analysis of Pedicle Screw Redir...

引用

5th International Symposium on Artificial Intelligence for Medicine Science, ISAIMS 2024

作者： Ma, Shuangshuang Gao, Dedong Shan, Zhongshu Xu, Wenxu Lu, Zhirui School of Mechanical Engineering Qinghai University Qinghai Xining China Department of Orthopedics Qinghai Provincial People?s Hospital Qinghai Xining China School of Computer Technology and Application Qinghai University Qinghai Xining China

ISBN: (纸本)9798400717826

Spinal fusion surgery is a crucial method for treating spinal diseases. Pedicle screw fixation, commonly used in spinal fusion procedures, offers excellent biomechanical properties and stability, making it a frequent choice for orthopedic surgeons. However, due to individual anatomical differences, limited intraoperative space, and variations in the surgeon’s experience and technical skills, screws may deviate from the intended path, potentially leading to complications such as nerve damage and vertebral fractures, which could result in severe consequences for the patient. To address this issue, surgeons often resort to redirected insertion, readjusting the screw path to ensure safe and effective fixation. This study employs finite element analysis combined with computer modeling based on artificial intelligence to simulate the effects of different angles and instances of screw redirection on screw pull-out strength. The study aims to explore how redirected insertion impacts screw fixation strength and to analyze the influence of various redirection strategies on fixation stability. The results indicate that redirected insertion significantly affects screw pull-out strength. The use of artificial intelligence in the analysis not only improves the precision of model simulations but also provides scientific insights for optimizing screw placement strategies, effectively reducing the risk of screw loosening. For models with initial screw insertion, pull-out strength decreases as the offset angle increases. Correcting suboptimal initial screw placements can enhance fixation strength and reduce the risk of screw loosening. However, for models with two suboptimal insertions, even after further correction, the negative impact on screw fixation remains;thus, further redirection without screw replacement is not recommended. © 2024 Copyright held by the owner/author(s).

关键词： Screws

来源：评论

学校读者我要写书评

暂无评论

A Study on the Design of Eye and Eyeball Method Based on MTCNN 1

引用

13th International Conference on Frontier Computing, FC 2023

作者： Hsueh, Cheng-Yu Hung, Jason C. Tzeng, Jian-Wei Huang, Hui-Chun Huang, Chun-Hong Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404348 Taiwan Department of Information Management National Taichung University of Science and Technology Taichung404348 Taiwan Department of Innovation Application and Management Chang Jung Christian University Tainan71101 Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan33306 Taiwan

ISBN: (数字)9789819993420

ISBN: (纸本)9789819993413

Studies on eye tracking have relied on wearable eye trackers and chin-resting eye trackers, but the high cost of equipment and the need to wear devices during experiments can lead to less natural facial movement. This study collected eye-tracking data by using a raw-video camera without adjusting any parameters. Python was used as the primary programming language. Eye tracking was adjusted through calculations of facial distance, and multitask cascaded convolutional networks were used to collect eye-tracking data. The corrected results were visualized, and linear regression was used to determine correction error. The root mean square error was 221.66, and the mean squared error was 260.48. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Eye tracking

来源：评论

学校读者我要写书评

暂无评论

FMICS: A Robust Learning Methodology to Predict Skin Cancer Disease Using Fused Melanoma Image Classification Scheme

FMICS: A Robust Learning Methodology to Predict Skin Cancer ...

引用

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Bhavani, G. Rama, M. Padma, S. Kumar, P. Praveen Kumar, K. Suresh Rajeshwari, R. R.M.K. Engineering College Department of Electronics and Communication Engineering Chennai India Qis College of Engineering and Technology Department of It AndhraPradesh Ongole India Sona College of Technology Department of Eee Salem636005 India Qis College of Engineering and Technology Department of Ece AndhraPradesh Ongole India Panimalar Engineering College Department of Mba Chennai India S.A Engineering College Department of Master of Computer Application Chennai India

ISBN: (纸本)9798331543617

Skin cancer (SC), particularly melanoma, is a significant health issue due to its high mortality rate when not detected early. This study introduces a novel approach, FMICS: A Robust Learning Methodology (Hybrid ANN + XGBoost) for predicting SC through fused melanoma image classification. The methodology integrates Artificial Neural Networks (ANN) for feature extraction and XGBoost for classification, leveraging the strengths of both models. Preprocessing techniques such as image filtering, contrast enhancement, and hair removal were applied to improve image quality. The study utilized dermoscopic images from the PH2 and HAM10000 datasets, containing both benign and malignant lesions. The hybrid model achieved superior performance compared to individual models, with an accuracy of 94.80%, sensitivity of 94.90%, and specificity of 94.70%. Data augmentation techniques, including rotation, scaling, and flipping, were applied to enhance the model's robustness. Evaluation metrics such as the F1-score and ROC-AUC were used to assess the performance. The hybrid approach significantly reduced false negatives, making it highly reliable for melanoma detection. These results suggest that the FMICS methodology offers a promising solution for accurate and efficient SC diagnosis, with potential applications in clinical and mobile environments. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning-based Transfer Learning Approach Fine-Tuned for Detecting Diabetic Retinopathy

引用

Procedia computer Science 2024年 233卷 444-453页

作者： Devendra Singh Dinesh C. Dobhal Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun 248002 India Department of Computer Application Graphic Era Deemed to be University Dehradun 248002 India

Diabetics have blood sugar levels that are abnormal. Because of this, their eyesight can be affected. Untreated diabetes has the potential to result in permanent blindness, a grave complication. Among the severe consequences, early detection stands out as a critical hurdle for ensuring effective treatment. Regrettably, accurately assessing fundus images relies on human expertise to determine the stage of diabetic retinopathy. A simplified detection process could greatly benefit a vast population. Leveraging convolutional neural networks (CNN), which have demonstrated efficacy across various domains, diabetic retinopathy identification has seen advancements. The possibility of preventing complete, irreversible blindness lies in timely identification, underscoring the need for a dependable screening mechanism. To enhance the efficiency of screening and reduce errors that plague current models, a novel system has been introduced, capable of categorizing distinct diabetic retinopathy stages. This study focuses on examining datasets of Indian diabetic retinopathy images, encompassing four classes: Microaneurysms (MA), Soft Exudates (SE), Hard Exudates (EX), and Hemorrhages (HE). By employing the proposed VGG16 architecture for feature extraction and the Logistic Regression classifier for classification, an impressive accuracy of 90.4% was achieved.

关键词： Deep Convolutional Networks Confusion Matrix Machine Learning (ML) Algorithms Transfer Learning Diabetic Retinopathy (DR) Visual Geometry Group16

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Techniques for IoT Data Sharing 9

Privacy-Preserving Techniques for IoT Data Sharing

引用

9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Karthikeyan, P. Teotia, Shashiraj Pawan, Toralkar Reena, B. Ardly Melba Vibhakar, Chirag Kalai Priya, V. Velammal College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Madurai625009 India Swami Vivekanand Subharti University Department of Computer Application Meerut250005 India Madanapalle Institute of Technology & Science Department of Artificial Intelligence Andhra Pradesh Madanapalle517325 India Saveetha University Department of Computer Science And Engineering Tamil Nadu Chennai600124 India Gujarat Power Engineering &. Research Institute Mevad Mehsana Gujarat Technological University Department of Electrical Engineering Gujarat Ahmedabad382710 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Tamil Nadu Puduvoyal601206 India

ISBN: (纸本)9798350365092

In aperiod dominated by the Internet of Effects (IoT), the sharing of data has become an integral aspect of technological advancements. still, the ubiquitous nature of IoT raises significant enterprises regarding stonerse questration. Thisexploration paper delves into innovatives equestration conservingwaysacclimatized for securing the sharing of IoT-generated data. The explores cryptographic protocols, anonymisation strategies, and decentralized fabrics toguard sensitive information while easing meaningful data exchange. Addressing the contradiction between datamileage and individuals equestration, the paper proposes new methodologies that intricately balance the need for dataparticipation with the imperative tocoverstoner confidentiality. By introducing a comprehensive analysis of sequestration-conserving mechanisms with in the IoT eco system, this exploration contribute sprecious perceptivity to the ongoingconverse on securing the digitalgeography. The findings offer a foundation for developing robustfabrics that harmonize the imperatives of dataparticipating with the consummatesignificance of securing stoner sequestration in the expanding realm of Io'Toperations. © 2024 IEEE.

关键词： Privacy-preserving techniques

来源：评论

学校读者我要写书评

暂无评论

Particle Swarm Optimization Technique for Current Equalization of PV Systems to Achieve Higher GMPP Under PSCs

Particle Swarm Optimization Technique for Current Equalizati...

引用

International Conference on Smart Energy and Advancement in Power Technologies, ICSEAPT 2021

作者： Pachauri, Rupendra Kumar Prasad, Hanuman Gupta, Pankaj Kumar Sharma, Manish Electrical and Electronics Engineering Department School of Engineering University of Petroleum and Energy Dehradun248007 India Electrical Engineering Department Model Institute of Technology Jammu181123 India School of Computer Science and Application IIMT University Meerut250001 India

ISBN: (纸本)9789811949708

The sun irradiations levels are always vary at different times, which affect the performance of solar photovoltaic (PV) systems in terms of power losses (PL). But many natural and un-natural causes exist and behave an obstruction to extract best performance from PV systems. The popular unacceptable causes are partial shading conditions (PSCs), which affects the PV performance highly. To diminish the effect of PSCs, relevant PV module rearrangement method is another good solution. In this paper, particle swarm optimization (PSO) technique demonstrates the current equalization of PV array systems under PSCs. In that method, a particle reaches the optimum value depending on its present velocity, past experience, and the experience of its nearby group members. Also, traditional arrangement techniques such as the series–parallel (SP) and total cross-tied (TCT) configurations have been used. As a result, performance parameters such as power and voltage at global maximum power point (GMPP), PL, and fill factor (FF) have been assessed. This paper displays the methods of implementation of the techniques to avert the effect of PSCs and to improve the energy output of the PV array under non-uniform irradiation circumstances. MATLAB/Simulink modelling is carried out to compare the results of various reconfiguration techniques and to find out which one is the best one under considered PSCs. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Solar energy

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：