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检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

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Designing an Advanced Control System for ABB IRB 140 Robotic Manipulator: Integrating machine learning and computer Vision for Enhanced Object Manipulation 5

Designing an Advanced Control System for ABB IRB 140 Robotic...

引用

5th international conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Kondratyev, Sergey Pikalov, Vladimir Belokopytov, Ruslan Muravyev, Artem Boikov, Andrey Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (纸本)9798350309126

this research paper presents an approach to developing a control system for the six-axis industrial robotic manipulator ABB IRB 140, aimed at enhancing object manipulation tasks. the focus is on the integration of computer vision and machine learning for efficient object detection and recognition. the study includes the analysis and comparison of various machine learning algorithms, including the application of convolutional neural networks and the YOLOv3 algorithm for real-time object detection using a depth camera. the work also covers the development of a robotic gripper with a robust control system capable of compensating for the saturation effect. To verify the proposed control system, the robotic complex is modeled in the Simulink environment. the research results confirm the possibility of successful implementation of the developed components into the existing robotic complex and its telecontrol system, ensuring the enhancement of efficiency and reliability in the object manipulation process. © 2023 IEEE.

关键词： Object detection

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Diagnostic Lab Locator and Health Care System using Cloud Computing and machine learning 7

Diagnostic Lab Locator and Health Care System using Cloud Co...

引用

7th international conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Chowdary, Nama Deepak Kumar, Mandepu Raj Reddy, Reddymalla Sai Kumar Maharaj, Tadikamalla Umesh Chandra Sri Reddy, Udayagiri Srinadh Sumanth, Pasumarthi Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vijayawada India Vignan Foundation of Technology and Research Department of Computer Science and Engineering Guntur India

ISBN: (纸本)9798350397253

the primary objective of this research is to demonstrate how Cloud Computing and machine learning can be used to develop a Diagnostics Lab Locator and a Smart Healthcare System. this approach allows users to have access to information about the dates and locations of the diagnostic labs that provide services and testing facilities for free. Many diagnostic labs and hospitals in India provide free testing facilities at special events in many cities like Hyderabad. the developed application provides the required information about the special events organized by hospitals. this study has used AWS Cloud Servers, services, and also the XG Boost Classification Algorithm to classify diagnostic labs and hospitals based on the availability of tests and types of tests. Further, the healthcare system is integrated into this Navigator application to store the health records of people, who utilized the services. this mechanism helps to store the test results and other important documents in the application itself. the integration of this healthcare system is also helpful to implement a booking system in future development of the application. the developed application will help the poor people in India to utilize the free services organized by the hospitals and Diagnostic labs. © 2023 IEEE.

关键词： Hospitals

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Object Sensing for Visually Impaired Using machine learning 4

Object Sensing for Visually Impaired Using Machine Learning

引用

4th international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Prabahar Godwin James, T. Pathmanaban, J. Vijayalakshmi, K. Jaitha Shree, B. Sandhyasri, B. Shalini, K.V.B. Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

Ensuring accessibility for those with visual impairments is still a major concern in the technologically modern world of today. In order to provide visual impaired with improved navigation and individualized healthcare help, this research presents a novel application that makes use of YOLOv8 (You Only Look Once version 8), a potent real-time object detection model. Utilizing the smartphone's camera, the program records live video, which YOLOv8 then processes to locate and identify objects like vehicles, pedestrians, and obstacles. It also provides the distances from the camera to all the detected objects with speed of moving objects to alert the user in case of danger. Apart from object recognition, the program incorporates extensive healthcare accessibility functionalities designed for those with visual impairments. To help users maintain the best possible health care management, this tailored healthcare feature offers reminders for medications and doctor appointments. this project aims to empower users by bridging the gap in healthcare accessibility and promoting independence, thereby improving the overall quality of life for visually impaired individuals through innovative mobile technology solutions. © 2024 IEEE.

关键词： Optical character recognition

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2023 10th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2023

2023 10th IEEE Uttar Pradesh Section International Conferenc...

引用

10th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2023

ISBN: (纸本)9798350382471

the proceedings contain 329 papers. the topics discussed include: systematic cognitive computing framework application using medical information processing;comparative analysis of epileptic seizure prediction: exploring diverse pre-processing techniques and machine learning models;analyzing textual data for mental health assessment: natural language processing for depression and anxiety;assessing water desalination in the United Arab Emirates: an overview;selection of cutting fluid for sustainable design for manufacturing;ESDPCOS: effectiveness of combined CNN and handcrafted features for ovarian cyst detection in PCOS patients using ultrasound images;analyzing the effect of edge computing on real-time data processing and latency reduction;text recognition in images and converting recognized text to speech – image processing;and comparative study of proposed linear regression algorithm to Scikit-Learn algorithm.

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Elderly Health Care Data Integration Framework: Design and Implementation 4th

Elderly Health Care Data Integration Framework: Design and I...

引用

4th international conference on Data and Information in Online Environments

作者： Zhong, Zhean Liu, Chenyu Zhao, Jing Xiao, Jianmao Gao, Qinghang Gao, Chao Ouyang, Chuying Jiangxi Normal Univ Sch Software Nanchang 330022 Jiangxi Peoples R China Jiangxi Prov Engn Res Ctr Blockchain Data Secur & Nanchang 330022 Jiangxi Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin 300072 Peoples R China Jiangxi Normal Univ Dept Phys Nanchang 330022 Jiangxi Peoples R China

ISBN: (纸本)9783031807121;9783031807138

the application of Internet of things (IoT) detection devices in the field of elderly healthy generates a large amount of detection data, which faces problems such as diversified data sources and non-uniform parsing methods. the fragmentation and confusion of the process from data subscription to data analysis have become important challenges affecting the development of the healthy aging field. In this paper, we designed and proposed an elderly health care framework with a model-as-a-service orientation. the framework automates the integration of health data for the elderly, including subscription services. It handles Model Training Analysis through a workflow-based system. Users can configure workflows using a low-code method provided by the platform. First, we abstracted and formalized the integration problem and workflow and defined a workflow description language. then, we built an healthy aging unified modeling framework based on the problem model and provided a general introduction to the framework architecture. the module for analyzing is responsible for model training, persistence, and data analysis, enabling users to customize the selection of machine learning models and corresponding parametric. Ultimately, we built a model library and an external RESTful interface based on the automation option of Automated machine learning (AutoML). the experiments demonstrate this paper's proposed framework's feasibility and effectiveness.

关键词： Data curation Elderly health care Model-as-a-Service machine learning

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Prediction of Epileptic Seizures based on EEG Signal using CNN Model 8

Prediction of Epileptic Seizures based on EEG Signal using C...

引用

8th international conference on Communication and Electronics Systems, ICCES 2023

作者： Kumar, Suraj Prakash, Shiva Madan Mohan Malaviya University of Technology Department of Information Technology and Computer Application Uttar Pradesh Gorakhpur273010 India

ISBN: (纸本)9798350396638

Millions of patients suffer from epilepsy each year, a chronic nervous illness with a growing global prevalence. In a lot of situations, it might cause critical injuries or patient deaths. So, the automatic prediction of the epileptic seizure saves the patients from injury as well as from death. In this age of technological advancements, the internet of things (IoT) has started to offer a variety of solutions in the healthcare sector through the use of machine learning, deep learning, and cloud-based services. Internet of thing, Edge computing, and Cloud computing helps in the detection of such nervous disorders using deep learning and machine learning. Most of the models were developed preciously but there are many issues related to the prediction and security of the data of patients. this research study proposed an autonomous cloud-edge integrated seizure prediction model based on a convolutional neural network. the proposed model detects and classifying the epileptic seizure using an EEG dataset. the proposed model shows average training accuracy and average validation accuracy are 99.27% and 96.37%, respectively and the average losses for training and validation are 2.10 % and 14.23%, respectively. the result shows that overall accuracies and losses are better than the wellknown existing works. All implementation for seizure prediction is done in Python language. © 2023 IEEE.

关键词： Internet of things

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GCF-FedCE : An Approach to Evaluating Contributions within Federated learning based on the Growth Curve Function 4

GCF-FedCE : An Approach to Evaluating Contributions within F...

引用

4th international conference on computer Science and Management Technology, ICCSMT 2023

作者： Wang, Yingzhi Zhang, Jianfei Hao, Mengyi School of Computer Science and Technology Changchun University of Science and Technology Changchun Jilin China

ISBN: (纸本)9798400709517

Federated learning (FL), as a new machine learning paradigm, is applied in many directions. In federated learning, samples are preserved locally without transmitting or exchanging and the intermediate variables have to be exchanged under the privacy protection technology. In the real world, due to the value generated by data capitalization and the cost of communication training, data owners do not actively contribute their own data as expected, so a reasonable incentive mechanism is needed to motivate data owners to contribute high-quality models trained based on their local data. the core of the incentive mechanism for federated learning lies in two aspects: the evaluation of the contributions of each participant, and the income distribution plan. In this article, we focus on t the contribution evaluation of each participant. GCF-FedCE, a method for evaluating the contribution of participants in federated learning based on the growth curve function, is proposed. the simulations shows that GCF-FedCE can accurately and real-time evaluate he contributions in each round and the overall contributions of each participant. And it is easy to catch the malicious or free-rider participant. In addition, GCF-FedCE is of adaptability for data distributions and number of participants, which makes the evaluation fairer and more accurate. © 2023 ACM.

关键词： learning systems

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Predicting Mumbai's Air Quality Index by machine learning 4

Predicting Mumbai's Air Quality Index by Machine Learning

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4th international conference for Emerging Technology, INCET 2023

作者： Chaudhari, Kalpana Joshi, Dhruvi Harugade, Pratik Jambusariya, Kritik Tiwari, Vaibhav Shah and Anchor Kutchhi Engineering College Department of Electronics and Telecommunication Engineering Mumbai India Shah and Anchor Kutchhi Engineering College Department of Computer Science Mumbai India Shah and Anchor Kutchhi Engineering College Department of Electronics and Computer Science Mumbai India

ISBN: (纸本)9798350335750

the purity of air plays a major role on mortal health of people. Poor quality of air leads to many forms of diseases, most probably in the kids. Looking at the vulnerability of air quality standards the government further decides to take important acts for prevention of such diseases. Ancient ways of tackling diseases have a short range of success due to no access to huge sets of data. For this project , we have considered using machine's algorithm to augur Air quality pointer for megacity Mumbai. Our created model can analyze closer to 93percent of aqi(air quality index), it further also predicts many oxides of carbon,nitrogen,sulfur and oxygen. therefore,we as a country feel the need to have a machine to read the pollution levels for us to maintain the environment and to start taking respective precautions needed. In numerous artificial and civic regions at the moment,balancing the air index for human health is the biggest task right now. the burning of fossil energies, business patterns, and artificial variables all have a big impact on air pollution. We need to apply models that will record information regarding the attention of air pollutants because of the rising pollutant situations. the quality of people's lives is being impacted by the buildup of these dangerous chemicals in the air, particularly in metropolitan areas. Several lab tests have lately started using the Big Data Analytics fashion as per rise of pollutants in air. © 2023 IEEE.

关键词： Air quality

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Integrating machine learning and Social Sensing in Smart City Digital Twin for Citizen Feedback 25

Integrating Machine Learning and Social Sensing in Smart Cit...

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25th IEEE international conferences on High Performance Computing and Communications, 9th international conference on Data Science and Systems, 21st IEEE international conference on Smart City and 9th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Kumi, Sandra Lomotey, Richard K. Deters, Ralph University of Saskatchewan Department of Computer Science SK Canada The Pennsylvania State University Information Sciences and Technology PA United States

ISBN: (纸本)9798350330014

Smart City Digital Twin (SCDT), a virtual representation of a physical city, is an emerging technology for optimizing urban services and enhancing urban planning and decision-making. the integration of machine learning (ML) and social sensing provides valuable insights into public feedback to policymakers and for informed decision-making and responsive urban governance. this study aims to explore the use of social media data and topic modeling algorithms in the context of SCDT to highlight the concerns of citizens in Saskatoon, Canada. In this work, we use the Uniform Manifold Approximation and Projection (UMAP) and K-means clustering algorithm in the BERTopic architecture to extract 30 topics from comments collected through the Saskatoon subreddit posts. the topics were then merged into 15 themes to discover the concerns. A pretrained transformer model, SiEBERT was used to determine the sentiments of the Reddit comments. the research findings highlighted concerns such as - unreliable public transit, high cost of living, long wait times in emergency rooms, shortage of family doctors, drug addiction, and lack of mental awareness. © 2023 IEEE.

关键词： Sentiment analysis

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Network Security Evaluation Method of College Freshmen Career Counseling Service Based on machine learning 4th

Network Security Evaluation Method of College Freshmen Caree...

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4th international conference on machine learning for Cyber Security, ML4CS 2022

作者： Song, Shuilan Liang, Xinjiu Nanning University Nanning530200 China

ISBN: (纸本)9783031200953

Because the career guidance service network for college freshmen is vulnerable to malicious attacks, network security is difficult to be guaranteed, therefore, a network security evaluation method based on machine learning is proposed for college freshmen career counseling services. According to the principle of index system, 3 primary indexes and 15 secondary evaluation indexes are selected. three collectors are used to collect index data and implement pretreatment. Using the entropy weight method to calculate the index weights, taking this as input, the evaluation method based on BP neural network is used to obtain the network security trend. the experimental results show that, the average relative error, mean square error and root mean square error of the proposed method are low, which proves that the network security evaluation effect of the proposed method is better. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： machine learning

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