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Research on Clustering Based on graph neural network 3

Research on Clustering Based on graph neural network

引用

2022 3rd international conference on computer Information and Big Data Applications, CIBDA 2022

作者： Xu, Dan School of computer science Wuhan Donghu University Hubei Wuhan China

ISBN: (纸本)9783800758760

In the past few years, the rise and application of neural network, it has successfully promoted the research of pattern recognition and data mining, become the focus of attention. Many machine learning tasks that used to rely heavily on manual feature extraction, today, it has been completely changed by the method of deep learning. Although the traditional deep learning method has achieved great success in extracting the features of Euclidean space data, the data in many practical application scenarios are generated from non Euclidean space, the performance of traditional deep learning methods in dealing with non European spatial data is still unsatisfactory, for Non-European spatial data, it is necessary to analyze the hidden structural information combined with the relevant knowledge of graph theory. Therefore, the concept of graph neural network is introduced to improve the traditional clustering algorithm, so that the original data structure information can be retained as much as possible while processing high-dimensional complex data, so as to achieve the goal of optimizing clustering. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Graph theory

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Comparative Analysis of Active Filters for processing of ECG signal According to AHA Recommendation

Comparative Analysis of Active Filters for Processing of ECG...

引用

2022 IEEE Delhi Section conference, DELCON 2022

作者： Pimpale, Yogita Gupta, Sachin Kanday, Rajeev School of Electronics and Electrical Engineering Lovely Professional University Phagwara India School of Computer Science and Engineering Lovely Professional University Phagwara India

ISBN: (纸本)9781665458832

In biomedical field, ECG signal and its processing is very important for design and development of smart devices. Due to rapid growth in IOT based applications, there is an indeed need to design a filter who can process the signal to remove the noise and distortion with low power consumption for such devices. Keeping in view the aim of this research study is to proposed design and analyses the comparison of active filters using American Heart Association standardization and recommendations. The Filter topologies are simulated in NI's MULTISIM 12.0 workbench. The ECG signal dataset has been taken from ***. The Sallen Key topology is used to design Butterworth and Chebyshev filters from order one to three to get optimum level of signal processing parameters such as gain, modification in signal characteristics. From the comparative results, it has been found that the band pass filter having 3rd order Inverse Chebyshev Low Pass Filter and 1st order High Pass Filter have satisfactory response. At output the, fidelity of signal was optimal as per test signal. © 2022 IEEE.

关键词： Topology

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A Design of Search and Rescue Device Based on Magnetic Compass 3

A Design of Search and Rescue Device Based on Magnetic Compa...

引用

3rd international conference on signal Image processing and Communication, ICSIPC 2023

作者： Gu, Shuming Li, Xiaomin School of Electronic and Information Engineering Zhuhai College of Science and Technology Jinwan Zhuhai519041 China

ISBN: (纸本)9781510670945

Search and rescue operations play a vital role in saving lives in emergency situations. Knowing the exact latitude, longitude coordinates and directional angles can ensure effective and efficient operations when search and rescue personnel are operating in remote or hazardous environments. This paper presents the design and implementation of a search and rescue device based on magnetic compass. The device uses ESP8266 as the primary control module, combining GPS module for positioning and magnetic compass module for angle of acquisition. The information collected is corrected and transmitted to ESP8266 to provide feedback, which is displayed on the OLED screen to search and rescue personnel. The test results showed that the device performed well in all of the selected test scenarios, with an average accuracy of 0.61°for directional angle data and 1.17 meters for latitude and longitude coordinate data. This improved search and rescue device can improve search and rescue operations and increase the chances of successful rescues. © 2023 SPIE.

关键词： Personnel

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Research on Personalized Learning Resource Recommendation Based on Knowledge Graph 3

Research on Personalized Learning Resource Recommendation Ba...

引用

3rd international conference on Electronic Information Engineering and computer Communication, EIECC 2023

作者： Zhang, Jun Jing, Shuyang Liang, Shuang Guangdong Polytechnic of Science and Technology Guangdong Zhuhai519090 China

ISBN: (纸本)9798350359961

The fast-developing online learning platforms have gathered a huge amount of learning resources, which facilitates the advancement of personalized learning recommendation methods. However, the traditional recommendation methods have problems such as sparse data and cold start, which cannot effectively recommend high-quality resources for students. This paper proposes a personalized learning resource recommendation model based on knowledge graph (KG-PLRR)to improve recommendation performance. Firstly, the student's preference set is constructed, and the fusion weight and propagation vector in the process of triple entity embedding are calculated. Then, the information of propagation nodes is aggregated to the current entity node to calculate the learning resource representation and expand the learning resource feature. By using the idea of preference propagation, the student's course resource records are used as the seed set to propagate preference outward along the relationships, and their semantics are expanded to dig out the potential connections. Finally, the personalized knowledge acquisition needs of students are more fully expressed, and the accuracy of recommendation is improved. The Experimental results show that the AUC and ACC values of this model are 0.9186 and 0.8836 in SCHOLAR dataset, and 0.7898 and 0.6541 in IMOOC dataset, respectively. The comprehensive recommendation performance of personalized learning resources is better than PLRec-KGGE, KPRN, RippleNet, KGNNLS. © 2023 IEEE.

关键词： knowledge graph Natural Language processing personalized learning Recommendation System

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Data Extraction from an Electrocardiogram signal and QRS Peak Detection Employing Wavelet-Based Approach 3

Data Extraction from an Electrocardiogram Signal and QRS Pea...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Ahmed Himu, Sheik Erfan Kalam, Safayet Das, Rana Nayem, Jannatul Sirajudeen, Safdhan Kabir, Md. Maharaj Abrar, Fahim Choity, Tasnia Fahrin International Islamic University Chittagong Dept. of Electrical and Electronic Engineering Chittagong Bangladesh South Eastern University of Sri Lanka Dept. of Information and Communication Technology Sri Lanka International Islamic University Chittagong Dept. of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9781665494991

The electrocardiogram (ECG) is a powerful diagnostic tool for attaining physiological signals. It can detect a wide range of information about a patient's pathophysiological individual state. A wavelet transform (WT) based method is introduced in this paper to analyze ECG signals. Reviewing the theory behind ECG and WT as well as identifying and summarizing the potential applications for applying WT to examine ECG are also done in this paper. Moreover, an algorithm is applied on the basis of WT to perform ECG beat segmentation and subsequently extract useful clinical parameters. ECG data from the physio-net as well as real patient data will be tested with this algorithm. The results demonstrate that even subtle changes in the ECG from synthetic data can be detected through the algorithm. Afterwards, the performed test data will be compared with previous work. So, this newly introduced system has become reliable and significant for biomedical research. © 2022 IEEE.

关键词： Electrocardiograms

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Performance Enhancement in Agriculture Sector Based on Image processing 3

Performance Enhancement in Agriculture Sector Based on Image...

引用

3rd international conference on Innovations in computer science and Software Engineering, ICONICS 2022

作者： Hassan, Ali Rehman, Faisal Ashraf, Muhammad Shahbaz Ashfaq, Ahmed Sharif, Hanan Zeeshan, Rana Akram, Salman Akram, Hira Lahore Leads University Department of Computer Science and Information Technology Lahore Pakistan

ISBN: (纸本)9781665461412

In the realm of agriculture and horticulture, machine vision and soft computing approaches have shown promise in overcoming the limitations of traditional methods for identifying plant illnesses utilizing various plant components. In all relevant studies such as fruit grading, leaf lesion area identification, and so on, image segmentation is the first and most important step. In order to diagnose the illness more effectively, a robust approach for numerous crops employing diverse plant components such as Fruit, Flower, and Leaf has been suggested in this study. Before segmentation, the acquired real-Time pictures are pre-processed for illumination normalization and color space conversion. To enhance the segmentation outcomes, the conventional ML, image processing and deep learning approaches scheme has been made adaptable, and edge detection transformations have been implemented. To separate the sick regions from photos, the aim function of the Machine Learning approach has been adjusted, and cluster centers have also been upgraded. The many classes of plant illnesses noticed by shooting various types of images of diseases in plants, including many popular plants such as grapes, apple, and tomato. In terms of both broad human observation and computing time, the results achieved are superior. © 2022 IEEE.

关键词： Image enhancement

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COVID-19 Detection from Chest X-Rays Using Deep Learning Techniques 3

COVID-19 Detection from Chest X-Rays Using Deep Learning Tec...

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3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Suresh, T Anju Rajendran V, Viji Nss College of Engineering Department of Computer Science Palakkad India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

The CoronaVirus Disease (COVID-19) is a global pandemic, according to theWorld Health Organization (WHO), which was declared in March 2020. Medical image analysis is a well-known method that could be useful in detecting COVID-19. This is because the cardiovascular system is the organ in the body that is most affected by the virus, so the chest X-rays may be a more suitable technique than thermal screening. Deep learning (DL) algorithms can play a crucial role in diagnosing COVID-19 patients' Chest X-Ray (CXR) pictures when properly studying them. The first stage involved in covid detection is pre-processing where cropping and resizing of image for fast processing. The next stage is feature extraction and classification by using deep convolution network. Various methods involved in these stages are studied and model was build using Pre-trained models. © 2022 IEEE.

关键词： Coronavirus

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Design of Regenerative Chatter Stability Detection System in Machine Tool Cutting based on computer Vision and SAR Image 3

Design of Regenerative Chatter Stability Detection System in...

引用

3rd international conference on Electronics and Sustainable Communication Systems, ICESC 2022

作者： Li, Liyao Yancheng Institute of Educational Science Yancheng224000 China

ISBN: (数字)9781665479714

ISBN: (纸本)9781665479714

The thesis starts with the analysis of the stability of the regenerative cutting chatter system. Based on the SAR image algorithm, the machine is processed in the processing steps of image denoising, image segmentation, target detection and recognition, focusing on the limit cutting width and random bed spindle speed W. The main factors affecting the stability of the machine tool cutting system are systematically analyzed, including the dynamic parameters of the main vibration system, and a SAR image segmentation method based on the global Maxflow neighborhood growth algorithm is proposed, which combines the texture and boundary information In combination, using C# as the development tool, designed a turning chatter stability limit prediction software, and systematically introduced the function realization and use method of the software. © 2022 IEEE.

关键词： Synthetic aperture radar

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Findings of the Second Shared Task on Offensive Span Identification from Code-Mixed Tamil-English Comments 3

Findings of the Second Shared Task on Offensive Span Identif...

引用

3rd Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2023

作者： Ravikiran, Manikandan Ganesh, Ananth Madasamy, Anand Kumar Rajalakshmi, Ratnavel Chakravarthi, Bharathi Raja Georgia Institute of Technology AtlantaGA United States National Institute of Technology Karnataka Surathkal India Vellore Institute of Technology Chennai India School of Computer Science Univeristy of Galway Ireland

ISBN: (纸本)9789544520854

Maintaining effective control over offensive content is essential on social media platforms to foster constructive online discussions. Yet, when it comes to code-mixed Dravidian languages, the current prevalence of offensive content moderation is restricted to categorizing entire comments, failing to identify specific portions that contribute to the offensiveness. Such limitation is primarily due to the lack of annotated data and open source systems for offensive spans. To alleviate this issue, in this shared task, we offer a collection of Tamil-English code-mixed social comments that include offensive comments. This paper provides an overview of the released dataset, the algorithms employed, and the outcomes achieved by the systems submitted for this task. © DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th international conference on Recent Advances in Natural Language processing, RANLP 2023 - Proceedings.

关键词： Social networking (online)

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A Coarse-to-Fine Ensembling Framework for Head and Neck Tumor and Lymph Segmentation in CT and PET Images 1

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3rd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, held in Conjunction with the 25th international conference on Medical Image Computing and computer Assisted Intervention, MICCAI 2022

作者： Sun, Xiao An, Chengyang Wang, Lisheng Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9783031274206

ISBN: (纸本)9783031274190

Head and neck (H &N) cancer is one of the most prevalent cancers [1]. In its treatment and prognosis analysis, tumors and metastatic lymph nodes may play an important role but their manual segmentations are time-consuming and laborious. In this paper, we propose a coarse-to-fine ensembling framework to segment the H &N tumor and metastatic lymph nodes automatically from Positron Emission Tomography (PET) and Computed Tomography (CT) images. The framework consists of three steps. The first step is to locate the head region in CT images. The second step is a coarse segmentation, to locate the tumor and lymph region of interest (ROI) from the head region. The last step is a fine segmentation, to get the final precise predictions of tumors and metastatic lymph nodes, where we proposed a ensembling refinement model. This framework is evaluated quantitatively with aggregated Dice Similarity Coefficient (DSC) of 0.77782 in the task 1 of the HECKTOR 2022 challenge[2, 3] as team SJTU426. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Tumors

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