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WellBe: An intelligent Elderly Care and Well-Being Monitoring System Using Deep Learning 4

WellBe: An Intelligent Elderly Care and Well-Being Monitorin...

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4th international conference on intelligent Technologies, CONIT 2024

作者： Raotole, Atharv Shirodkar, Sailee Sanjay Shukla, Rahul Sisodia, Jignesh Devadkar, Kailas Patel Institute of Technology Dept. of Information Technology Sardar Mumbai India Patel Institute of Technology Dept. of Computer Science and Engineering Sardar Mumbai India

ISBN: (纸本)9798350349900

Deep Learning refers to a subset of Machine Learning that utilizes deep neural networks to simulate the complex decision-making process of the human brain. In recent years, DL has made remarkable progress in addressing multiple unique challenges faced by most elderly individuals. While there have been significant contributions to independent systems catered for the elderly, there is the existence of an overall integrated AI platform that unifies the use of individual modules for an optimized solution. this paper introduces 'WellBe,' an innovative AI system that encompasses an alarm-based fall detection component, a facial emotion recognition (FER) system and a built-in personalized chatbot all under a user-friendly website. the novelty of the work extends beyond the aforementioned components, owing to the implementation of an optimized FER system able to handle wrinkles and changes in skin texture, thereby tailored exclusively for the elderly demographic. the system leverages a custom feature extraction module, fusing facial and wrinkle features, in addition to extending a convolutional neural network (CNN) architecture for accurate emotion classification, achieving promising performance with precision, recall, and F1-scores of 0.87, 0.91, and 0.89 for the 'Happy' (one of the predicted emotions) class, respectively. the fall detection component, on the other hand, utilizes a pre-trained YOLOv7 Pose model for the real-time identification of falls, sitting at a performance accuracy of 95.3%. Finally, the personalized chatbot is implemented using a rule-based approach enhanced with the Jaccard similarity algorithm, to facilitate prompt assistance and a sense of companionship to the end user. Overall, the integration of these components into a cohesive website offers a comprehensive solution for enhancing the quality of life for elderly individuals living alone, addressing loneliness, safety, and overall well-being. © 2024 IEEE.

关键词： Convolutional neural networks

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Chinese Named Entity recognition Within the Electric Power Domain 1

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4th international conference on Emerging Information Security and Applications (EISA)

作者： Feng, Jun Wang, Hongkai Peng, Liangying Wang, Yidan Song, Haomin Guo, Hongju State Grid Zhejiang Elect Power Corp Informat & T Hangzhou Peoples R China Nanjing Duotuo Intelligent Technol Ltd Liabil Co Nanjing Peoples R China

ISBN: (数字)9789819996148

ISBN: (纸本)9789819996131;9789819996148

the field of electrical power encompasses a vast array of diverse information modalities, with textual data standing as a pivotal constituent of this domain. In this study, we harness an extensive corpus of textual data drawn from the electrical power systems domain, comprising regulations, reports, and other pertinent materials. Leveraging this corpus, we construct an Electrical Power systems Corpus and proceed to annotate entities within this text, thereby introducing a novel Named Entity recognition (NER) dataset tailored specifically for the electrical power domain. We employ an end-to-end deep learning model, the BERT-BiLSTM-CRF model, for named entity recognition on our custom electrical power domain dataset. this NER model integrates the BERT pre-trained model into the traditional BiLSTM-CRF model, enhancing its ability to capture contextual and semantic information within the text. Results demonstrate that the proposed model outperforms both the BiLSTM-CRF model and the BERT-softmax model in NER tasks across the electrical power domain and various other domains. this study contributes to the advancement of NER applications in the electrical power domain and holds significance for furthering the construction of knowledge graphs and databases related to electrical power systems.

关键词： Electric power domain Named entity recognition Bidirectional encoder representations from transformers Bidirectional long short-term memory Conditional random fields

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Schema of an affective cognitive learning system for piano timbre differences: application of the sequential patternmining algorithm 4

Schema of an affective cognitive learning system for piano t...

引用

4th international conference on Artificial Intelligence and Computer Engineering, ICAICE 2023

作者： Liang, Xiangdong Du, Yuqing Zhu, Fangning Dept of Graduate School Daejin University Pachon Gyeonggi Province Korea Republic of

ISBN: (纸本)9798400708831

Piano timbre difference perception is a difficult task in piano teaching, which requires the fusion of experiential analyses of the piano's physical entity, performance skills, and emotional perception of the work. this paper explores the theoretical basis and realisation path of assisted piano work performance timbre difference perception learning based on sequence pattern mining and artificial intelligence technology, and constructs a model of intelligent assisted teaching system. © 2023 ACM.

关键词： Learning systems

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Study on intelligent Image Analysis of Bitmap Vectorization Conversion in Graphic Design with pattern Fusion 4

Study on Intelligent Image Analysis of Bitmap Vectorization ...

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4th international conference on Smart systems and Inventive Technology, ICSSIT 2022

作者： Luan, Li Li, Tingting Sun, Haining Department of Art and Design Jining Polytechnic Shandong Jining272000 China

ISBN: (纸本)9781665401180

this paper takes the intelligent image analysis of the vectorized conversion of bitmaps in graphic design as the main line. Aiming at the situation that it is not easy to make three-dimensional pictures in graphic design, the intelligent image analysis algorithm is used to extract, analyze and classify the features of bitmaps. Based on the Bézier curve-based graphics boundary line extraction, graphic boundary line extraction correction and simple color graphic boundary line extraction models, use Excel for corresponding data processing, and use Photoshop, Matlab and other software to extract the graphic boundary lines. Opencv software the fitted line was tested, and the result showed that the conversion efficiency of bitmap vectorization increasedby 9.1%. © 2022 IEEE

关键词： Image analysis

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Rainy weather weak target recognition over water: an enhanced de-raining approach for QSNet networks 4

Rainy weather weak target recognition over water: an enhance...

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4th international conference on Image Processing and intelligent Control, IPIC 2024

作者： Lai, Minling Tang, Huiling Bi, Qilin Chen, Xiaowen Deng, Shuqi Huang, Chuxing Lv, Youjie Guangdong University of Technology Guangdong Guangzhou510006 China Guangzhou Maritime University Guangdong Guangzhou510725 China Guangzhou University Guangdong Guangzhou510000 China Yours Technology Co. LTD. Guangdong Jieyang522021 China

ISBN: (纸本)9781510682313

To address rainwater interference in visual imaging systems for water navigation, exploration, and rescue by proposing an improved QSMD network based on QSNet. To mitigate channel information loss, we combine guided astrous convolution with CBAM, enhancing the model's spatial representation and feature expression while optimizing computational efficiency and maintaining high accuracy. Experimental results confirm the effectiveness of this improvement. © 2024 SPIE.

关键词： Imaging systems

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Measurements and Interventions to Improve Student Engagement through Facial Expression recognition 1

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4th international conference on Adaptive Instructional systems Held as Part of the 24th international conference on Human-Computer Interaction (HCII)

作者： Lee, Will Allessio, Danielle Rebelsky, William Gattupalli, Sai Satish Yu, Hao Arroyo, Ivon Betke, Margrit Bargal, Sarah Murray, Tom Sylvia, Frank Woolf, Beverly P. Univ Massachusetts Amherst MA 01003 USA Boston Univ Boston MA 02215 USA

ISBN: (数字)9783031058875

ISBN: (纸本)9783031058875;9783031058868

A major challenge for online learning systems is supporting students' engagement. Online systems are sometimes boring, repetitive, and unappealing;external distractions often lead to off-task behavior, and a decline in learning. Student engagement and emotion are also tightly correlated with learning gains because emotion drives attention and attention drives learning. In response to this challenge, we present an exploratory study using computer vision techniques and several engagement strategies to help students re-engage once their attention wanders and their head turns away, within the context of an intelligent tutoring system for mathematics. Initial results indicate that students exposed to our re-engagement strategies were more confident and more persistent. they also responded positively to our avatar or learning companion. We discuss design implications and future work.

关键词： Facial expression recognition Engagement Emotions Gaze intelligent tutoring systems

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intelligent Music Recommendation System Based on Face Emotion recognition 4

Intelligent Music Recommendation System Based on Face Emotio...

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4th IEEE international conference on Computing, Communication, and intelligent systems, ICCCIS 2023

作者： Gupta, Nandini Agarwal, Shruti Joshi, Kireet Gupta, Vishan Kumar Shukla, Surendra Kumar Singh, Gurpreet Graphic Era Deemed to Be University Department of CSE Dehradun India Amity University Punjab Department of CSE Mohali India SVKMS NMIMS MPSTME Department of Computer Engineering India Sir Padampat Singhania University Department of CSE Udaipur India

ISBN: (纸本)9798350306118

Music has been considered a form of expression that can treat conditions such as stress, anxiety, and mood swings. the latest research in music psychology shows that music evokes palpable emotions in listeners. People's personality and mood determines what kind of music they prefer to listen to. the areas of the brain that process thoughts and emotions also control tempo, timbre, and music. Although a person's response to music depends on many external factors, we can classify music as kindness, patience, relaxation, and passion, that's why music is a high-quality connector. Industries are also part of us for a long time, backgrounds, languages, hobbies, political leanings and earning degrees, songs, and other streaming apps. those apps may be used every time and everywhere and they can be used for daily activities, travel, sports, activities, etc. It is an excessive call for as it can be combined with the rapid development of cellular networks and the digital multimedia era, the virtual track has ended up being the main content of many younger human beings. Emotion-based tunes in our device is designed to recognize emotions in actual time and suggest songs primarily based on perceived emotions. this will become an addition to the conventional tune participant apps we had on our telephones before. One of the essential blessings of being concerned in emotional intelligence is purchaser satisfaction. the main motive of this device is to research the user's image, predict the expression of the person and advise songs appropriate to the detected mood. © 2023 IEEE.

关键词： Emotion recognition

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A two-stage intelligent condition monitoring method for electromagnets in high-voltage circuit breakers 4

A two-stage intelligent condition monitoring method for elec...

引用

4th international conference on Sensors and Information Technology, ICSI 2024

作者： Han, Miaomiao Fu, Yu Li, Chuangchuang Zhang, Xianglei College of Mechanical and Electrical Engineering Wenzhou University Wenzhou China

ISBN: (数字)9781510678699

ISBN: (纸本)9781510678682

intelligent condition monitoring of electromagnets in high-voltage circuit breakers is crucial for the safe operation of power systems. In this study, a hybrid two-phase approach is proposed, aiming at intelligently identifying key feature points in electromagnet current signals by a modified one-dimensional U-Net model, as well as determining the operating state of electromagnets based on the location and magnitude of these key feature points. In the first data-driven phase, an improved U-Net model applicable to time series is introduced for the intelligent identification of key features in the electromagnet current signal. In the second knowledge-based phase, the operating state of the electromagnet is accurately identified based on the position and size of the key feature points by exploring the motion mechanism of the electromagnet. the experimental results show that the proposed method can effectively identify the key points, and the recognition success rate is close to 100%. the proposed method can realize the adaptive identification of various electromagnet faults with only a few fault samples. therefore, the proposed method paves the way for robust state identification of electromagnets and enjoys the merit of strong anti-interference. © 2024 SPIE.

关键词： Electric circuit breakers

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Spatio-Temporal Motion pattern Analysis for Anomaly recognition in Crowded Sections using Kernel SVM 4

Spatio-Temporal Motion Pattern Analysis for Anomaly Recognit...

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4th IEEE international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Rathika, S. Minhas, Deepak Spoorthi, B. Kumar, Santosh Vigenesh, M. Garg, Prateek Prince Shri Venkateshwara Padmavathy Engineering College Department of Mba Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Engineering and Technology Karnataka Bangalore India Vishwakarma Institute of Technology Aids Pune India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798331518981

the advancement of information technology, the proliferation of monitoring networks, and the automated detection of anomalous behavior in surveillance video are all becoming more crucial for the purpose of public safety and smart city development. Context modeling is the foundation upon which the new methods for recognizing moving objects are built. Consequently, these systems are vulnerable to noise and background movement. It is a challenging endeavor to keep track of individuals in crowded scenarios because of the variations in movement and appearance that are brought about by the vast number of people present in the picture. An efficient Kernel Support Vector Machine is constructed for the purpose of anomaly identification in congested settings by making use of spatio-temporal movement pattern models. this is done to find solutions to these challenges. At the outset, the movie is divided into frames by making use of the threshold value. Protracted Kalman Filters are used to segment the motions of the objects to enhance the accuracy of the categorization. the textural characteristics are used to determine which item is in the front and which is in the background. To track objects in an effective manner, enhanced vector quantization is used. To categorize the abnormalities, the Kernel Support Vector Machine is used. © 2024 IEEE.

关键词： Smart city

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intelligent Video Surveillance: Artificial Intelligence and its Applications on Security systems 4

Intelligent Video Surveillance: Artificial Intelligence and ...

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4th international conference on Smart Electronics and Communication, ICOSEC 2023

作者： Morales Cauti, Guisseppi Paul Vargas-Murillo, Alfonso Renato De Jesus Guevara-Soto, Francisco Ypanaque-Pereira, Isai Luis Universidad Privada Del Norte Facultad de Derecho y Ciencias Políticas Lima Peru Universidad Privada de Tacna Escuela Profesional de Ciencias de la Comunicación Lima Peru Escuela de Postgrado Universidad Nacional Jorge Basadre Grohmann Tacna Peru

ISBN: (纸本)9798350300888

Artificial Intelligence has found its way through applications within diverse fields such as education, engineering, academics, among others. And even though constant improvement is made upon this technology in areas like data processing and text generation based on machine learning, other areas like the security field might need a different approach to be improved upon by this technology. Smart home security could come into mind as a primary example of how people could monitor their day-to-day life and prevent different occurrences by having an AI based system that focuses on intelligent video surveillance, but there is a need to answer the questions regarding how well does AI adapt to this field, what are its different applications and what are the challenges presented within said applications. For this matter, a systematic Literature Review was conducted in order to analyze the current and previous knowledge regarding this subject, in order to determine the different appliances that AI can have on video surveillance and security. the results of this study show the versatility of AI assisted security, in areas such as video surveillance, monitoring systems and even facial recognition. this study also concludes that, even though there are some impressive advancements regarding these applications, further development could be recommended to explore a greater number of possibilities for AI assisted security. © 2023 IEEE.

关键词： Face recognition

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