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检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

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advances in Text Summarization Techniques: A Comprehensive Review and Future Prospects 5th

Advances in Text Summarization Techniques: A Comprehensive R...

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5th international conference on Artificial Intelligence and Speech technology, AIST 2023

作者： Vishwakarma, Harsh Kukkar, Yashika Chauhan, Aditi Maheshwari, Abhinav Saini, Dharmender Nagrath, Preeti Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India

ISBN: (纸本)9783031751660

this research work provides a concise comparative analysis of prominent content summarization models, namely Textrank, T5, Pegasus, and Bart. the models are evaluated for their specific strengths: Textrank excels in sentence extraction, T5 showcases versatility, Pegasus demonstrates superior abstractive summarization, and Bart proves robust across diverse content types. Evaluation metrics, including ROUGE scores and human assessment, offer insights into each model’s performance. Beyond performance, the paper considers computational efficiency. the study contributes to content summarization by incorporating machine learning and LSTM techniques, advancing automated text processing. this concise reference aids professionals in selecting optimal summarization models for specific use cases and resource constraints. Evaluation metrics, including ROUGE scores, highlight Pegasus as the top performer out of the implemented models. Pegasus demonstrates exceptional capability in generating summaries aligned with references. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Word processing

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Supervised Learning of Procedures from Tutorial Videos 5th

Supervised Learning of Procedures from Tutorial Videos

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5th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2022

作者： Arunima, S. Sengupta, Amlan Krishnan, Aparna Venkata Vara Prasad, D. Venkataramana, Lokeswari Y. Department of Computer Science and Engineering Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Chennai603110 India

ISBN: (纸本)9783031163630

Online educational platforms and MOOCs (Massive Open Online Courses) have made it so that learning can happen from anywhere across the globe. While this is extremely beneficial, videos are not accessible by everyone, due to time constraints and lower bandwidths. Textual step-by-step instructions will serve as a good alternative, being less time-consuming to follow than videos, and also requiring lesser bandwidth. In this work, the authors aim to create a system that extracts and presents a step-by-step tutorial from a tutorial video, which makes it much easier to follow as per the user’s convenience. this can be mainly accomplished by using Text Recognition for academic videos and Action Recognition for exercise videos. Text Recognition is accomplished using the Pytesseract package from Python which performs OCR. Action Recognition is performed with the help of a pre-trained OpenPose model. Additional information is extracted from both exercise and academic videos with the help of speech recognition. the information extracted from the videos are then segmented into procedural instructions which is easy to comprehend. For exercise videos, a frame-wise accuracy of 79.27% is obtained. Additionally, for academic videos, an accuracy of 78.47% is obtained. © 2022, IFIP international Federation for Information Processing.

关键词： Speech recognition

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Driving Fatigue Detection Combining Face Features with Physiological Information 7

Driving Fatigue Detection Combining Face Features with Physi...

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7th IEEE international conference on Network Intelligence and Digital Content, IC-NIDC 2021

作者： Zeng, Lingqiu Wang, Yang Han, Qingwen Zhou, Kun Ye, Lei Long, Yang Chongqing University School of Computer Science Chongqing400044 China Research and Development Center of Transport Industry of Self-driving Technology Chongqing400000 China School OfMicroelectronics and Communication Engineering Chongqing University Chongqing400044 China Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China

ISBN: (纸本)9781665405829

Fatigue driving is one of the main reasons that cause sever accidents. It's necessary to detect fatigue state and warn drivers to avoid life-threatening accidents. there are many related technologies to detect fatigue, some of which based on physiological information or face features. However, biological indicators are difficult to analyze in real-time and the signal sensor is invasive while image-based approaches have relatively strong subjective. Hence, in this paper, a method combined physiological information and face features is employed. We use near-infrared spectroscopy (fNIRS) on behalf of physical states and eye and mouth condition representing face states. Firstly, Multi-Task Convolutional Neural Network (MTCNN) was used to extract image features and then a lightly classifier was designed to recognize the state of face states. Finally, we use Long Short-Term Memory (LSTM) model to fuse these characters and predict fatigue. Experiment results show that the method proposed have a high accuracy about 95.8% and fast speed about 6.12ms to detect fatigue. © 2021 IEEE.

关键词： Long short-term memory

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A Novel Container Based Computing Environment 8th

A Novel Container Based Computing Environment

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8th international conference on advances in Computing and Data sciences, ICACDS 2024

作者： Seth, Jitendra Kumar Gupta, Ruchin Chakraborty, Chinmoy Rastogi, Tushar Chaurasia, Arpit Department of Information Technology KIET Group of Institutions Ghaziabad UP Ghaziabad India

ISBN: (纸本)9783031709050

Software development environment setup and configuration is a very tedious and time consuming task for any organization. It is challenging for those peoples who are not technically competent to configure the development environment. Delay in setting up development environment may result, loss in productivity and revenue. To overcome these problems, we proposed a Docker based computing environment which provides a quick development environment to the end users. the proposed architecture speeds up the procedure for setting up a development environment by enabling the users to start a tech stack of their choice with few clicks. the proposed system keeps their users away from the necessity for complex local system installation and provides high performance computing environment like a mainframe. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Virtual environments

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Food23:A Chinese Food Safety Dataset for Fake News Detection 23

Food23:A Chinese Food Safety Dataset for Fake News Detection

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Proceedings of the 2023 7th international conference on advances in Artificial Intelligence

作者： Ziliang Shang Li Tan Hongtao Zhang Xujie Jiang Yuzhao Liu Dongfang Li school of computer science and engineering Beijing Technology and Business University China

ISBN: (纸本)9798400708985

In the field of fake news, the topic of food safety has gradually emerged as a focal point of concern. We have exhaustively scoured the relevant scholarly literature pertaining to the detection of fake news in the domain of food safety. Unfortunately, the extant research concerning the detection of food safety fake news remains focused on analyzing their social impact, rather than providing an effective detection method. In order to facilitate research on fake news detection in the domain of food safety, this study constructed the first Chinese text fake news dataset specific to the domain of food safety. We gathered data from currently active Chinese fact-checking websites and authoritative news sources as our primary reservoir of information. this dataset contains 2,334 news across 10 distinct subdomains. these specialized domains have effectively enriched the dataset's characteristics. According to this dataset, we design an efficient model for food safety fake news detection, known as the Food Safety Fake News Detection (FSFND). By extracting text features from various perspectives and considering the characteristics inherent to each subdomain, our model makes predictions regarding the veracity of information. We chose a selection of text classification models and multi-domain fake news detection model as comparative experiments. Experimental results indicate that our approach significantly outperforms conventional methods reliant on text and domain information for detecting food safety fake news. In addition, we conducted ablation experiments to demonstrate the effectiveness of each step in our model design.

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Towards Lip Motion Based Speaking Mode Detection Using Residual Neural Networks 1

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12th international conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Afroze, Sadia Hoque, Mohammed Moshiul Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong4349 Bangladesh

ISBN: (数字)9783030736897

ISBN: (纸本)9783030736880

Speaking mode (i.e., talking or non-talking) detection is a significant research problem in the area of HCI and computer vision. Detecting the speaking mode of a speaker is quite challenging owing to the coarse-resolution images, interaction styles, and various noises. this paper proposes a vision-based technique to identify a human’s speaking mode in terms of talking and non-talking state by using the residual neural networks. Visual lip motions is a prominent cue and play a pivotal role in detecting the speaking mode of the human. thus, we consider the vision-based technique rather voice-based, which is noisy or interrupted. the evaluation result in two datasets shows better performance (of 99.56 % accuracy) in mouth state detection than previous approaches. Moreover, analysis with 36 min long video data of 15 participants reveals that the proposed technique acquired an accuracy of 98.88 % in detecting speaking mode. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Human computer interaction

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Intelligent Tutoring for Large-Scale Personalized Programming Learning Based on Knowledge Graph 53

Intelligent Tutoring for Large-Scale Personalized Programmin...

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53rd IEEE ASEE Frontiers in Education international conference, FIE 2023

作者： Li, Ying Qiu, Jincheng Yang, Runze Zhu, Tongyu Sheng, Hao Gui, ShiJie Liang, Yu School of Computer Science and Engineering Beihang University Beijing China Beijing Engineering Research Center for IoT Software and Systems Beijing University of Technology Beijing China

ISBN: (纸本)9798350336429

the development of learning analytics technology has created the necessary conditions for the implementation of large-scale personalized education. By taking advantage of the current advancements available, we can adopt a deep integration of 'artificial intelligence + education', take educational big data as the research object, aim at achieving precise teaching, and use cognitive diagnosis as a means to construct an intelligent guidance model. the model will conform to a learner's cognitive patterns and curriculum characteristics to meet his personalized learning needs under different knowledge states. Firstly, use knowledge map and abstract syntax trees to extract the characteristics of teaching objectives from questions and standard programing codes. Secondly, Use 'target characteristics - learning characteristics - learning sequence - learning effect' cognitive diagnosis model to assess student achievement in learning. Finally, according to the correlation between knowledge points, the initial learning path consisting of all relevant knowledge points is identified from a knowledge map. And the most optimal learning path is selected based on the importance of knowledge points and student's learning situation. there are three innovation points in this paper. First, the traditional method which only focuses on discovering the one-dimensional knowledge features implicated in the questions, is extended to construct a knowledge-ability multidimensional feature matrix. Secondly, it optimized static cognitive diagnosis into dynamic cognitive arbitrariness, which has a modeling capability of dynamic temporal sequence. thirdly, it regarded the correlation between knowledge points, and the importance of knowledge points as the heuristic conditions for constructing a learning path. © 2023 IEEE.

关键词： Cognitive Diagnosis Intelligent Guidance Model Knowledge Graph Personalized Learning Path

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A Machine Learning Classification Application to Identify Inefficient Novice Programmers

A Machine Learning Classification Application to Identify In...

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7th international conference on advances in Visual Informatics, IVIC 2021

作者： Khan, Ijaz Al-Mamari, Aysha Al-Abdulsalam, Bashayer Al-Abdulsalam, Fatma Al-Khansuri, Maryam Iqbal Malik, Sohail Ahmad, Abdul Rahim Information Technology Department Buraimi University College Al-Buraimi Oman College of Graduate Studies Universiti Tenaga Nasional Kajang Malaysia

ISBN: (纸本)9783030902346

To preserve their reputation and prestige, the educational institutes are required to provide evidences of their students’ academic performance to the governmental bureaus and accreditation agencies. As a consequence, the monitoring individual student academic performance is emerging as a vital task for the educational institutes. the indispensability of this prediction amplifies when it comes to programming language course;which emerges as backbone for computer science students. Machine Learning classifiers are considered as productive tools to develop models which can identify the students with inefficient academic performance. the early identification of inefficient students will provide an opportunity to instructor to take appropriate precautionary measures. this paper proposes a prediction model with an added application layer with graphical user interface. the experimental part of paper compares the performance of several machine learning algorithms and comes up with k-NN as appropriate classifier in the addressed context. Further, the application layer of the proposed architecture facilitates instructor with a Graphical User Interface to execute a wide range of operations. © 2021, Springer Nature Switzerland AG.

关键词： Students

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Virtualization technology to Support Green Computing Among IT Personnel in the Public Sector

Virtualization Technology to Support Green Computing Among I...

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7th international conference on advances in Visual Informatics, IVIC 2021

作者： Jusoh, Mohd Yusri Haron, Haryani Kaur, Jasber Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor Malaysia

ISBN: (纸本)9783030902346

this paper presents virtualization technology that supports green computing among IT personnel in the public sector. the selection of effective technology in virtualization is crucial to reduce the negative impact of IT usage in the public sector by leveraging resources and maximizing the use of IT devices. Virtualization can provide important processes related to green computing implementation in the organization. However, the organization still faces problems in identifying suitable technology used by IT personnel in the organization. thus, there is a need to understand the process to select the suitable technology based on the role of people, process, technology, and IT organization structure. the methodology comprises that the work process exploration, end-user segmentation, and technology evaluation process, which is validated by interviewing targeting IT personnel in government-based institutions in Malaysia that have in-house green data centers. the qualitative approach was adopted to understand the work activities of IT personnel and IT devices used to perform the task. A case study approach was used where the data was collected from open-ended interviews, observation, and report documents. the data was analyzed using a thematic analysis approach. then, technology evaluation was conducted to select appropriate virtualization technologies to be used to support green computing in the IT work process by integrating four dimensions that consist of the people, process, technology, and IT organization structure. the results show a list of virtualization technology to support green computing based on the technology evaluation process. © 2021, Springer Nature Switzerland AG.

关键词： Virtualization

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A Brief Systematic Review of the Latest advances in IOT Platforms in Agriculture 7th

A Brief Systematic Review of the Latest Advances in IOT Plat...

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7th international conference on Technologies and Innovation, CITI 2021

作者： Yerovi, Elke Delgado-Vera, Carlota Molina-Oleas, Wilson Ortega-Ponce, Laura School of Engineering in Computing and Informatics Faculty of Agrarian Sciences Agrarian University of Ecuador Av. 25 de Julio y Pio Jaramillo P.O. BOX 09-04-100 Guayaquil Ecuador

ISBN: (纸本)9783030882617

IoT or Internet of things is an innovative advance in technology that helps interconnectivity between smart devices and machines helping to reduce human intervention. the use of IOT platforms, their architectures, network technologies and devices allow to improve the efficiency and productivity of any type of industry or mass production, this research is focused on one of the most important fields which is agriculture. the Internet of things (IoT) is related to millions of applications and various devices throughout the world that communicate with each other and can exchange data and perform cooperative tasks without the intervention of human beings. Considering the aforementioned facts, relevant information is provided for farmers and researchers with a clear perspective of the technologies, devices, architecture, network and sensors used in IoT, in addition to the solutions that IoT provides in the agriculture field. © 2021, Springer Nature Switzerland AG.

关键词： Agriculture

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