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Research on the Coupling of College Academic Style Construction and Great Ideological Politics under the Guidance of the Concept of Three-Whole Parenting

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Applied Mathematics and Nonlinear sciences 2024年第1期9卷

作者： Li, Shanjiang Tang, Laihong Student Affairs Office Hunan University of Information Technology Hunan Changsha410151 China College of Computer Science and Engineering Hunan University of Information Technology Hunan Changsha410151 China

The construction of academic style is the central link in implementing the fundamental task of cultivating moral integrity in colleges and universities, and it is also a meaningful way and carrier for realizing the all-embracing, all-encompassing and all-encompassing cultivation of human beings. Based on the four-stage cycle theory of PDCA (Plan-Do-Check-Act), the article constructs a comprehensive evaluation system focusing on the construction of academic style and the evaluation system of the quality of the significant ideological and political cultivation with the goal of value shaping. In the study, the method of variance maximization is adopted to determine the weights of evaluation indexes, and a genetic algorithm is introduced to optimize these weights to solve the optimal linear programming problem of variance maximization. The study establishes a fuzzy comprehensive evaluation and coupled coordination model through this method. Taking University S as an example, the article conducted a comprehensive review of the quality of the academic style construction and the quality of the significant ideological and political education. It used the comprehensive development index to analyze the level of the coupled and coordinated development of the two. The results show that in the construction of academic style, the weight value of students’ learning behavior is 0.2565, while in the evaluation system of the quality of considerable ideological and political education, the weight value of teaching effect is 0.2564. These two fields’ coupling coordination levels increased 1.33 times from 2010 to 2019. This indicates that the higher the level of coupled and coordinated development of college academic style construction and more excellent ideological and political education, the more helpful it is for colleges and universities to realize the goal of cultivating moral character. The study in this paper provides a practical evaluation and optimization framework to promote

关键词： Genetic algorithms

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An Efficient IoT-based Mobile Application for Continuous Monitoring of Patients

An Efficient IoT-based Mobile Application for Continuous Mon...

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Data science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Shereen Afifi Andrew Emad Radwa Taha Mirza Baig Assistant Professor in Computer science and Engineering German University in Cairo Egypt Senior student in Computer science and Engineering German University in Cairo Egypt Master Candidate in Computer science and Engineering German University in Cairo Egypt Senior Solutions Specialist in Orion Health Auckland New Zealand

Internet of Things (IoT) is gaining much popularity nowadays, especially in the field of healthcare, where different wearables, sensors and data analysis-based systems are connected together. This research work proposes an IoT-based system/application dedicated for continuous monitoring of the patient’s health parameters and vital signs. The designed application can be used by both the patient and the doctor as the doctor can track the patient’s parameters remotely in real-time to facilitate the diagnosis and to early detect patient’s health deterioration. It also enables patients to spend more time in the comfort of their own homes and communicate with their care facilities, aiming to improve the patient’s independent living and support activities of daily life. The biosensors in the smart watch or the mobile phone are utilized to measure the health parameters of the patient, which are then used by the devloped application for further processing, analysis and efficient visualization using charts and diagrams. A notification is sent to the monitoring doctor to facilitate rapid response once any of the patient’s vital signs exceeds the normal range. The developed application could be integrated within an existing hospital system or could be made available to individuals/patients via smartphones for providing support at *** Relevance: Doctors are always in need to have exact health information for their patients to receive care and therapy in a timely manner. The task of ongoing monitoring of patients’ vital signs is carried out by nurses in the interim, but the availability of a skilled and sizable team of nurses is a major concern. Thus, we propose an efficient continuous monitoring system that automates and facilitates the process of remote and continuous monitoring of patients, targeting early detection of patient deterioration while supporting independent living.

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Smart Fashion Recommendation System using Random Forest Algorithm

Smart Fashion Recommendation System using Random Forest Algo...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Shivangi Patel Arneet Kaur Theertha Sudheer Babu Nair Shamneesh Sharma Vikas Verma Nishant Agnihotri School of Computer Science and Engineering Lovely Professional University Punjab India Delivery and Student Success UpGrad Education Private Limited Bangalore Karnataka India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

The fashion sector is expanding quickly in the digital age, and this means that more sophisticated recommendation systems that improve user experiences and expedite the online purchasing process are required. This work proposes a sophisticated and all-inclusive fashion recommendation system that uses machine learning techniques, specifically Random Forest, to enhance suggestion accuracy and efficiency. Users can choose their preferred fit and style using an interactive interface, which enables the system to offer clothes based on their individual profiles. Moreover, Context-based filtering involves personalizing recommendations to users based on a variety of contextual factors which may include user preferences, current fashion trends, occasion, style, body type and others. As a result of the dynamic recommendation process, the recommendations are constantly improved and grow more specific and well-rounded over time. The outcomes showcase the system's capacity to effectively combine various machine learning algorithms to evaluate a wide range of data sources, including user preferences, item features, and contextual information, to provide individualized recommendations.

关键词： Training Measurement Accuracy Machine learning algorithms Soft sensors Clothing Market research Information age Recommender systems Random forests

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Comparative Analysis of Traditional and Machine Learning Based Face Recognition Models

Comparative Analysis of Traditional and Machine Learning Bas...

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Data, Decision and Systems (ICDDS), IEEE International Conference on

作者： Shreya R Akanksha P Mulgund Shravani Hiremath Sri Harshitha A Anjan K Koundinya Department of Computer Science PES University Bengaluru India Department of Computer Science and Engineering PES University Bengaluru India Department of Information Science and Engineering IEEE Student Branch Counsellor BMS Institute of Technology and Management Bengaluru India

Face recognition technology uses methodologies to process images, register them, and compare and verify it with a set of faces it has already registered and labelled. Recent development in visual recognition showcases the immense power of utilising machine learning techniques like deep neural networks, convolutional neural networks to achieve face recognition. Based on a comprehensive literature review it was found that some of the algorithms that provide great performance metrics in a variety of conditions are MTCNN, FaceNet model, Haar cascade, LBPH, hence it was chosen to be the subject of comparison under various conditions in the paper. A machine learning model was constructed which included MTCNN for face detection and FaceNet for face *** Performance of KNN and SVM classifiers has been studied. The second model uses a combination of Haar cascade for face detection and LBPH for face recognition, a traditional face recognition technique. The results highlight that MTCNN, FaceNet and KNN perform exceptionally well. The performance of the other models are also discussed in the results and discussion section. The research not only guides researchers and practitioners in choosing suitable face recognition techniques but also offers ground for future improvements in accuracy and reliability in the field of algorithm developments.

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Designing an AI driven intelligent Tutorial System

Designing an AI driven intelligent Tutorial System

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Recent Trends in computer science and Technology (ICRTCST), International Conference on

作者： Md Shamsher Alam Surjeet Kumar Zeeshan Khursheed Hemant Kumar Mahato Shadan Bashar Anjali Suman Computer Science and Engineering Associate Professor in R.V.S College of Engineering & Technology Jamshedpur India Computer Science and Engineering Assistant Professor in Government Engineering College Sheikhpura Bihar India DGM Jio Platform Limited Mumbai India Master of Computer Application Assistant Professor in NSHM Durgapur India Master of Computer Application Assistant Professor in R.V.S College of Engineering & Technology Jamshedpur India Computer Science & Engineering Student R.V.S College of Engineering & Technology Jamshedpur India

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

With the fast-evolving field of education, there is an increase in the demand for intelligent tutorial systems that can adapt to the diverse learning needs of individual students. This research paper explores the design and implementation of an AI-driven Intelligent Tutorial System (ITS) aimed at enhancing the personalized learning experience. The system leverages advanced machine learning algorithms to dynamically adjust instructional content, pace, and assessments based on real-time analysis of individual student performance and preferences. The paper delves into the key components of the proposed ITS, including adaptive learning models, natural language processing capabilities for interactive communication, and data-driven decision-making mechanisms. Emphasis is placed on the seamless integration of AI technologies to create an intuitive and responsive educational *** considerations in the development and deployment of the intelligent tutorial system are discussed, addressing issues related to data privacy, algorithmic bias, and the role of human oversight. The paper also highlights the collaborative potential between AI and human educators, emphasizing the system's capacity to support rather than replace teaching professionals. Through a combination of theoretical frameworks and practical examples, the research examines the potential impact of the AI-driven ITS on student engagement, learning outcomes, and the overall educational experience. Case studies and pilot implementations are presented to illustrate the system's efficacy in diverse educational *** research contributes to the ongoing discourse on AI in education by providing insights into the design principles, implementation challenges, and ethical considerations associated with developing an intelligent tutorial system. The findings aim to inform educators, policymakers, and technologists about the potential of AI to revolutionize personalized learning and contribute to the ong

关键词： Ethics Data privacy Machine learning algorithms Image recognition Decision making Tutorials Market research

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Identification and Classification of Rare Medicinal Plants

Identification and Classification of Rare Medicinal Plants

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Piyush Singh Bora Shamneesh Sharma Isha Batra Arun Malik Farzeen Ashfaq School of Computer Science and Engineering Lovely Professional University Punjab India Delivery and Student Success upGrad Campus upGrad Education Private Limited Bangalore India School of Computer Science Taylor's University Subang Jaya Malaysia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

The identification and conservation of rare medicinal plants are crucial, given their invaluable role in healthcare, pharmaceuticals, and biodiversity preservation. Numerous varieties face extinction according to the International Union for Conservation of Nature (IUCN), necessitating advanced image processing and computer vision techniques for accurate identification and documentation. This paper presents a novel deep learning approach leveraging convolutional neural networks (CNNs) and transfer learning to adapt the MobileNet V2 architecture for automated identification and classification of rare medicinal plants found in different areas, utilizing a curated dataset of 6,900 images across 80 distinct classes. The robust deep learning model extracts discriminative visual features from digital images, facilitating accurate taxonomic classification, and outperforming traditional techniques and shallow models. The proposed system empowers stakeholders with reliable accessible tools and plays a pivotal role in biodiversity conservation and sustainable utilization, ensuring nature's therapeutic bounty for generations.

关键词： Medicinal plants Deep learning Adaptation models Technological innovation Accuracy Medical services Mobile applications Environmental management Biomedical imaging Pharmaceuticals

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StorySpinner: AI Based Technique to Narrate the Web Links

StorySpinner: AI Based Technique to Narrate the Web Links

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International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Prajwal Kumbar Shamneesh Sharma Isha Batra Arun Malik Farzeen Ashfaq School of Computer Science and Engineering Lovely Professional University Punjab India Delivery and Student Success upGrad Campus upGrad Education Private Limited Bangalore India School of Computer Science Taylor's University Subang Jaya Malaysia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

The rapid advancement of LLM has facilitated a variety of large language model applications in natural language processing. This report details the development of StorySpinner, an application based on large language models and retrieval-augmented generation that allows yield from articles to the format of an interesting narrative. Moreover, the model addresses processing issues related to the specifics of diverse Internet re-sources, webpages, blogs, and even YouTube videos, by combining web scraping methods, text summarization models, and semantic paragraphs with the use of the extraction of material from extracted abstracts into LLM. The present research investigated the specifics of StorySpinner architecture, the used techniques of information extraction, summarization, and narrative generation, and possible applications of this technology such as educational purposes, accessibility issues, and content development. The paper also provided a discussion of ethical aspects, including bias prevention, copyright issues, and AI technology influence on society. StorySpinner was introduced as a method to fill the gap between web content and human understanding, offering a new way to access information as a story.

关键词： Video on demand Large language models Prevention and mitigation Semantics Text summarization Market research Natural language processing Internet Web sites Videos

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Image Security Utilizing Hybrid Model of Steganography and Asymmetric Cryptography Methods

Image Security Utilizing Hybrid Model of Steganography and A...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Arora, Himanshu Agarwal, Radhika Sharma, Priyanka Shankar, Gori Arora, Deepti Arya Institute of Engineering and Technology Department of Computer Science and Engineering Rajasthan Jaipur India Maharaja Sawai Man Singh Vidyalaya Student of 12th Class Rajasthan Jaipur India Jaipur Engineering College Department of Mathematics Rajasthan Jaipur India Jaipur Engineering College Department of Electronics and Communication Rajasthan Jaipur India Arya Institute of Engineering and Technology Department of Mathematics Rajasthan Jaipur India

ISBN: (纸本)9781665474511

With the recent technologies, digital data is mostly used in every communication and data transferring process. Moreover, digital images are highly preferred by people nowadays. In order to establish a secure transferring or exchange of data, the digital data needs to be secured. There are different techniques and algorithms that can used to provide security to the digital data. In this research work, a hybrid digital image security technique is proposed by combining two different types of methods and algorithms, which are used to protect the digital image. The proposed combination of steganography and asymmetric cryptography techniques are utilized to secure the digital images. © 2023 IEEE.

关键词： Cryptography

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A Hybrid Harmony Search Algorithm based on Firefly Algorithm and Boltzmann Machine

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 241-251页

作者： Yang, J. Zhang, Xiaoxia Fu, S. Hu, Y.Y. Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Professor of School of computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China

Harmony Search Algorithm (HS) is a new meta-heuristic algorithm based on music creation process. The algorithm has been widely used in many fields because of its simple and flexible structure and fewer controlled parameters. However, HS is easy to be affected by the initial harmony memory and falls into local optimization. In addition, there are also problems, such as low searching accuracy and slow convergence speed of the optimal solution. Therefore, this paper proposes a hybrid harmony search algorithm based on firefly algorithm and boltzmann machine (HSFA-BM). First, in order to avoid the possibility of harmony search algorithm falling into local optimum, boltzmann machine (BM) mechanism is used to update the harmony memory in this paper. Second, in order to enhance the ability of the algorithm to exploit optimal solutions, this paper uses the movement mode of fireflies to generate new solutions. The improved algorithm enhances the ability of global optimization and search precision, and speeds up the convergence speed. In this paper, six classical test functions are used to test the effectiveness of the algorithm, and a very obvious optimization result is obtained. © 2022. All Rights Reserved.

关键词： Flexible structures

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Accurate Classroom Person Detection Based on Multi-Frame Feature Fusion with Attention 8

Accurate Classroom Person Detection Based on Multi-Frame Fea...

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8th International Conference on Image, Vision and Computing, ICIVC 2023

作者： Cheng, Guoan Ren, Jiandong Li, Yuping Wang, Shengke Ding, Yougang Wang, Hao School of Information & Electrical Engineering Qingdao Harbour Vocational & Technical College Qingdao China Qingdao Harbour Vocational & Technical College Student Work Department Qingdao China College of Computer Science and Engineering Ocean University of China Qingdao China Experimental School Affiliated to Shandong University Mathematics Teaching and Research Group Heze China

ISBN: (纸本)9798350335231

In recent years, object detection technology has developed rapidly and is widely used in the field of intelligent video monitoring, especially in the classroom scenes, where incorporating the intelligent object detection technique into the video monitoring systems for intelligent monitoring purpose has important practical significance. However, surveillance videos may encounter issues such as object occlusion, motion blur, posture changes, and video defocus, which poses great challenges to object detection in the surveillance video scenarios. Therefore, in this paper, we conduct in-depth research on human detection in classroom multi camera surveillance video scenes and propose a multi frame feature fusion network based on the attention mechanism. The algorithm first adds the dilated convolution layers to the ResNet50 backbone network to expand the receptive field and retain more feature information;Secondly, a multi frame feature fusion strategy based on the attention mechanism was proposed to enhance the feature representation ability of the deep detector by fusing the feature information of adjacent frames, thereby improving the accuracy of human detection in the classroom monitoring video. To verify the effectiveness of the proposed method, we have compiled and produced a large-scale classroom monitoring video dataset, named OUC-ClassVideo. The proposed object detection network, which is developed based on the attention mechanism and multi frame feature fusion strategy, has achieved satisfactory performance on both the public dataset ImageNet VID and the OUC-ClassVideo dataset collected by ourselves. © 2023 IEEE.

关键词： Object detection

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