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Automated Quiz Generation Tool Using Artificial Intelligence Techniques 13th

Automated Quiz Generation Tool Using Artificial Intelligence...

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13th Computer Science Online Conference

作者： Fox, Richard Hayes, Peyton North Kentucky Univ Sch Comp & Analyt Highland Hts KY 41099 USA

ISBN: (纸本)9783031705175;9783031705182

Artificial intelligence has been used to construct numerous intelligent tutorial systems over the years with varying degrees of complexity and capability. They generally are constructed on top of a domain model of knowledge, some form of model of the student's learning, a pedagogical strategy that presents material to the student, and an interface. Automated question generation is often considered a subproblem within the larger tutorial domain (although not all automated question generation systems use artificial intelligence). Perhaps simpler to construct, the ability to generate questions to test a student is a very valuable tool. As with tutorial systems, question generation approaches vary widely. In recent years, approaches have concentrated on the use of large language models. Between tutorial system and question generation attempts, research indicates a significant investment in time and effort to construct such systems. This paper presents an AI-based approach to automated question generation that foregoes the language model/language interface and uses a much shallower domain model to simplify construction, yet provides beneficial results to the student. This paper introduces the QuizGenie system to demonstrate the approach taken. The work is still in progress but shows promise as a study resource for students.

关键词： Artificial intelligence tutorial system question generation tool

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Automatic Speech Recognition of Finnish-Swedish Dialects: A Comparison of Three Cutting-Edge Technologies 21st

Automatic Speech Recognition of Finnish-Swedish Dialects: A ...

引用

21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Espinosa-Leal, Leonardo Adolfsson, Kristoffer Kuvaja Shcherbakov, Andrey Arcada Univ Appl Sci Grad Sch & Res Jan Magnus Janssons Plats 1 Helsinki 00560 Finland Arcada Univ Appl Sci Sch Engn Culture & Wellbeing Jan Magnus Janssons Pl 1 Helsinki 00560 Finland

ISBN: (纸本)9783031619045;9783031619052

This paper explores the performance of two different automatic speech recognition models for the Finnish-Swedish language. The first model, Whisper V1 released by OpenAI and the second, the KBLab model trained using a large dataset by the National Library of Sweden. These models were trained initially using data from the Swedish language from Sweden, and the results were compared with previous work trained using a dataset of Finnish-Swedish audio. Our results indicate that general models perform at the same level, opening up the possibility of using these in Finland for the inclusion of the Finnish-Swedish minority.

关键词： Speech recognition Finnish-Swedish Dialects

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Sudden Cardiac Arrests in Individuals Who Over-Exercise, Its Etiology, Use of Wearable IoT Technology, and the Role of COVID-19: A Systematic Review 8th

Sudden Cardiac Arrests in Individuals Who Over-Exercise, Its...

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Annadate, Prutha Bedekar, Mangesh Annadate, Mrunal Dr Vishwanath Karad MIT World Peace Univ Pune 411038 India

ISBN: (纸本)9789819713196;9789819713202

The incidence of sudden cardiac arrest (SCA) in individuals, who undergo intense physical exertion, be it as professional competitive athletes or recreational fitness enthusiasts is a consequential incident which may result in sudden cardiac death (SCD) and/or extreme mental stress. It is vital to investigate the etiology as interest of the general public increases in high-intensity sports. Additionally, this literature investigates the advent and widespread use of wearable "smart" technology (IoT wearable technology) that enables users to constantly monitor health. The benefits, gaps, and possible detrimental factors associated with wearable technology with regards to sports will be discussed. Lastly, effects of COVID-19 on cardiovascular health and its implications for individuals who partake in high-intensity sports activities are investigated.

关键词： Sudden cardiac arrest (SCA) Internet of Things (IoT) Wearable devices COVID-19 Sports cardiology

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Data-Driven Decision Support systems in E-Governance: Leveraging AI for Policymaking 1

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International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Arora, Anudeep Vats, Prashant Tomer, Neha Kaur, Ranjeeta Saini, Ashok Kumar Shekhawat, Sayar Singh Roopak, Monika GGSIPU Kamal Inst Higher Educ & Adv Technol New Delhi India Manipal Univ Jaipur Dept CSE SCSE Jaipur Rajasthan India ICFAI Univ ICFAI Business Sch Dehra Dun Uttarakhand India Univ Huddersfield Sch Comp & Engn Dept Comp Sci Artificial Intelligence & Cyber Secur Huddersfield W Yorkshire England

ISBN: (数字)9789819984794

ISBN: (纸本)9789819984787;9789819984794

Data-driven decision support systems have been used more and more in e-governance as a result of the digital revolution. In order to improve the efficacy and efficiency of policymaking, this research article investigates the integration of artificial intelligence (AI) approaches into e-governance systems. Governments can access enormous volumes of data, and AI algorithms are used to analyze and extract insightful data that enables decision-making based on facts. The article emphasizes the advantages of using AI in the e-governance space while formulating policy. Decision support systems can analyze and understand complicated information by utilizing cutting-edge machine learning and data analytics approaches, revealing trends, patterns, and correlations that would be challenging for human analysts to manually find. As a result, decision-makers in government may make well-informed choices based on impartial research and data. The paper also examines the difficulties and factors to be considered when implementing AI in decision support systems for e-governance. With an emphasis on the significance of responsible AI governance frameworks, ethical issues, including algorithmic bias, transparency, and accountability are addressed. The article also explores the effects of incorporating AI into decision-making processes, including potential sociopolitical effects and the requirement for stakeholder participation and public confidence. The results of this study show how data-driven decision support systems may revolutionize e-governance policies when equipped with AI technology. Governments may enhance their decision-making processes and the outcomes of governance by using the power of big data and sophisticated analytics. This will lead to better public service delivery.

关键词： Decision support system E-governance Artificial intelligence Blockchain Data security Policymaking

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The Problem of Many Vehicles: An Explainable System for Autonomous Multi-agent Accidents

The Problem of Many Vehicles: An Explainable System for Auto...

引用

Intelligent systems Conference

作者： Mansy, Yasmin Ehab, Nourhan ElMougy, Amr German Univ Cairo New Cairo Egypt Amer Univ Cairo New Cairo Egypt

ISBN: (纸本)9783031664304;9783031664311

Given the need for trustworthy autonomous vehicles, this research paper presents an explanatory framework for multi-agent autonomous vehicle crashes, leveraging the FCI causal algorithm to generate a Full Time Causal Graph (FTCG). The framework's performance is evaluated using simulated scenarios within the MetaDrive environment, employing key metrics such as accuracy, time, scalability, and stability. Results demonstrate promising accuracy in crash explanation, showcasing the effectiveness of the FCI causal algorithm. The scalability analysis reveals that the framework operates within reasonable time constraints as the dataset size increases. However, the introduction of uniform noise poses a challenge to stability, adversely affecting the system's reliability in identifying crash sequences under random variations. While the framework exhibits strengths in accuracy and scalability, addressing stability concerns, especially in the presence of uniform noise, presents an avenue for future research and improvement.

关键词： Autonomous vehicles Multi-agents Explainable AI Counterfactual explanations

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Big Mart Sales Prediction Using Machine Learning

Big Mart Sales Prediction Using Machine Learning

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Kumar, Vimal Garg, Hardik Gandhi, Anshul Gupta, Bhavy Bennett Univ Times Grp Techzone 2 Greater Noida India

ISBN: (纸本)9789819984756;9789819984763

This paper developed a prediction model that will forecast product sales at a particular shop using numerous datasets. This study is able to get findings with a required degree of accuracy using the method employed to create a comprehensive model. Additionally, this information can be used to take decisions to additionally foster arrangements. This paper proposed many issues to predict sales of Big Mart and how to predict by employing five different types of regression algorithms to forecast it, including XGBoost regressor, linear regression, decision trees, random forest regressor, and grid search CV. These algorithms were employed to build models, compared the correctness of those models, and prepared them to fit the board's assumptions so that cautious actions could be done to accomplish the affiliation's purpose. These models may be applied in many districts. It has also been addressed how to anticipate how different kinds of items will be arranged and how different conditions will affect those arrangements. In this research, there are many implementation challenges in practical models. Various models are created and after comparing their R2-Score the best R2-score is of random forest grid search which is equal to 0.5588858290914282. Somehow R2-score is low, but it is due to the variability and lack of data, and it is good enough to predict the output.

关键词： Big Mart sale Label encoder Linear regression Prediction Random forest XGBoost regressor

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Interactive Digitally Supported Design of Human-Centric Workplaces in Learning Factories 14th

Interactive Digitally Supported Design of Human-Centric Work...

引用

14th International Conference on Learning Factories (CLF)

作者： Bittencourt, Victor Spitzhirn, Michael Thiede, Sebastian Univ Twente Fac Engn Technol Dept Design Prod & Management Chair Mfg Syst Horst 2Bldg 20 NL-7522 LW Enschede Netherlands Imk Ind Intelligence GmbH Amselgrund 30 D-09128 Chemnitz Germany

ISBN: (纸本)9783031654107;9783031654114

Industrial workplaces must adapt to the worker to guarantee the sustainability proposed by the concept of Industry 5.0. This research aims at contributing to the human-centered development of processes based on an integrated framework supported by three pillars: design, assessment and modelling. Through the combination of manufacturing tools such as an ergonomically adapted value stream map, Digital Human Model simulation using ema Work Designer (emaWD), and collaborative design with Nvidia Omniverse, a case study was applied at the learning factory of the University of Twente. The employment of the framework allowed a systematic analysis of the process and gathered insights for triggering improvement cycles to balance the system's performance and worker's well-being.

关键词： Learning Factory Digital Human Modelling Value Stream Map

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AI Driven Medical Prediction and Suggestive System to Establish Good Health and Well Being in Society - A Real Time Case Study

AI Driven Medical Prediction and Suggestive System to Establ...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Verma, Sunita Jain, Anjana Shukla, Sangeeta Kothari, Vineeta Shri GS Inst Technol & Sci Indore India SAGE Univ Indore Indore India Cent Pathol Lab Indore India

ISBN: (纸本)9783031671913;9783031671920

To Achieve one of the goal of United Nation for 2030 to Establish good health & well being for sustainable development, various steps are being taken globally. To achieve the objectives of good health, monitoring and prediction based suggestive system is required specific to specific class. The emergence of Artificial Intelligent techniques and algorithms may play a vital role in fast, reliable and accurate data analysis and prediction. Further the echo system may be developed and policies may be reframed to achieve the UN goal 2030. In this paper a case study is presented, which is carried out in the host city Indore situated in central India. The city has uniform climate and living style across it's boundary & inner part. Hence the data taken can be categorized under one class. The sampling has been done in real time for the Medical Parameters like B Glucose, Cholesterol, Keratinize and Protein. Different subclasses were created for recognizing pattern of specific class. The classification is done on urban and Rural population, on Gender basis, on caste and age wise. Almost ten subclasses are described which are having unique and distinguishable characteristics in their food style. Present Data is compared with data set of interval of 10 years. With the use of AI algorithm the estimation on medical health has been predicted while considering different parameters. These algorithms generate functions that map inputs to desire outputs and consist of a dependent variable which is predicted from a given set of independent variables. The predicted values are compared with the original value to determine the accuracy of the model. The machine learning algorithm include Naive-Bayes, k-NN, Decision Tree, Support Vector Machines, Random Forest, bagging etc. The results are derived formentioned subclasses and specific groups. Based on the analysis and prediction a specific suggestive health care system can be developed for specific class or subclass. The relevant society may

关键词： UN 2030 Artificial Intelligent techniques Health care Lifestyle Predictive analysis ML algorithm

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Media Steganography Using CNN with Blockchain-Enabled Secure File Transfer 1

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4th Congress on Intelligent systems (CIS)

作者： Yadav, Bhagavatiraj Narvekar, Omkar Patil, Rishabh Shaikh, Sanober Thadomal Shahani Engn Coll Informat Technol Dept Mumbai Maharashtra India

ISBN: (数字)9789819990405

ISBN: (纸本)9789819990399;9789819990405

Secure data transfer through Internet has become highly important because of the loopholes and vulnerabilities of the existing data transfer systems. Steganography is an effective technique to achieve this goal, where data is hidden within multimedia files to prevent detection. In our implementation, we have incorporated a technique, CNN-based image and video steganography, which leverage Blockchain technology for efficient storage and transfer of hidden data. Our technique involves compressing and dispersing the original secret image pixels across all of the available bits of the container image, in contrast to traditional steganography methods which encrypt the secret message by embedding it within the least significant bits (LSBs) of the container image. Convolutional neural network (CNN) can help achieve two goals in steganography: to increase security and increase hiding capacity. CNNs can be used to identify the best areas for hiding data, which increases hiding capacity, and it becomes complex for steganalysis programs to detect the hidden data. The averaged pixel-wise discrepancy value (APD) (with a dynamic range 0 to 255) was 4.16 between original cover and modified container image/video frame and 4.24 between the original secret and final secret image/video frame retrieved. The proposed methodology also includes a decentralized cloud system which uses Blockchain technology to store and transmit private media files providing decentralization, transparency, and tamper-evidence. For Blockchain, smart contracts have been designed with better optimization logic which aims to reduce gas consumption and enhance the efficiency of Blockchain transaction.

关键词： CNN Blockchain Steganography Transparency Encryption

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Limitations and Benefits of the ChatGPT for Python Programmers and Its Tools for Evaluation 1

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13th Computer Science Online Conference

作者： Arias, Ricardo Martinez, Grecia Caceres, Didier Garces, Eduardo Univ Tecnolog Peru Natalio Sanchez St 125 Lima Peru

ISBN: (数字)9783031703003

ISBN: (纸本)9783031702990;9783031703003

The artificial intelligence called ChatGPT exhibits an outstanding feature, which is its ability to automatically generate code;in this case, the scope is with programming in Python. This paper focuses on evaluating the quality of the code generated and its limitations by ChatGPT compared to the code created by an advanced human programmer. To achieve this purpose, a systematic research is carried out with an exhaustive analysis of the artificial intelligence with a new tool and survey for the evaluation, in order to clarify the capabilities and constraints with its context in the field of artificial intelligence. Through a rigorous systematic review process, following PRISMA guidelines, a total of 6879 relevant publications are initially identified. After applying inclusion and exclusion criteria, the sample was reduced to 165 publications, and after eliminating irrelevant publications, a set of 15 quality articles that fit the study objectives was finally selected. The results of the articles selected in the research reveal an in-depth evaluation of ChatGPT, the understanding of the integration of Artificial Intelligence in education, the analysis of the motivations behind the use of generative chatbots, the challenges and paradigms that arise from the use of AIs in programming, the perception of AI with human attributes, the evaluation of metrics for software quality, the detection of irregularities in the code, the categorization of clones and the exploration of software quality and errors in the code. The PICOC methodology included the use of software related to quality testing, which allows achieving an astonishing 95.66% accuracy in the evaluation of the code generated, both by the programmer and by ChatGPT. This resulted in a 30.28% decrease in human errors and 96.2% effectiveness in evaluating the quality of the generated code, the evaluation considered 3 surveys for Python programmers in 1000 of advanced programmers from October to December 2023. In summar

关键词： Artificial intelligence chatGPT software performance quality Assurance

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