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1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2022) 1

1st International Virtual Conference on Visual Pattern Extra...

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1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding, VIPERC 2022

作者： Amelio, Alessia Montelpare, Sergio Ursino, Domenico InGeo University "G. d’Annunzio" Chieti-Pescara Viale Pindaro 42 Pescara65127 Italy DII Marche Polytechnic University Via Brecce Bianche 12 Ancona60131 Italy

This document introduces the 1st international Virtual conference on Visual Pattern Extraction and Recognition for Cultural Heritage Understanding (VIPERC 2022), a premier forum for presenting the state-of-the-art, new research, ongoing work, academic and project reports in advanced statistics and machine learning, 3D modelling and simulation, knowledge representation, intelligent systems, information retrieval and software engineering, for visual pattern extraction, analysis and recognition to preserve the cultural heritage. © 2022 Copyright for this paper by its authors.

关键词： 3D modeling

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Analysis of Algorithms' Performance in the Domain of Evolutionary Computation (EC) in Real-Life Applications

Analysis of Algorithms' Performance in the Domain of Evoluti...

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Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI), international conference on

作者： Vinod Mansiram Kapse Prashant Chaudhary N.R Solomon Jebaraj Department of Electronics and Communication Engineering Noida Institute Of Engineering and Technology Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Tula's Institute Dehradun India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

This research delves into the dynamic realm of evolutionary algorithms and examines their real-world applications. We methodically provide a variety of evolutionary techniques in the form of pseudo-code, including differential evolution, evolutionary algorithms, evolutionary programming, and evolutionary strategies. This makes it simple to include into a variety of programming languages. With rigorous study, the distinctive qualities of each algorithm were uncovered. We have compared and contrasted the GA, GP, DE, ES, and EP in this study.

关键词： Computer languages Heuristic algorithms Evolutionary computation programming artificial intelligence

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VSCODE- Code With Voice Using Natural Language Processing(NLP) 1

VSCODE- Code With Voice Using Natural Language Processing(NL...

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1st international conference on Computer, Power and Communications, ICCPC 2022

作者： Prakash, M. Gnana Ponmalar, A. Deeba, S. Akilandeswari, A. Rasool, Saira Banu Mohammed Lavanya, P. Sri Sai Ram Institute of Technology Department of Information Technology Tamil Nadu Chennai India Sri Manakula Vinayagar Engineering College Department of Computer Science and Engineering Tamil Nadu Puducherry India Saveetha School of Engineering Simats Tamil Nadu Chennai India Applied College Najran University Department of Information System Saudi Arabia

ISBN: (纸本)9798350397840

Physically Challenged people who are interested in coding, in the current scenario cannot code and exhibit their knowledge in programming skills. Our project enables them to code without using a keyboard. They can code entirely by their voice and execute their code. We are converting the user's speech to text by Natural Language Processing (NLP). With the use of text obtained from NLP model we generate code snippets using our custom code generator API. The code snippets are generated in the Visual studio Code text editor using our own VSCode extension. © 2022 IEEE.

关键词： Speech recognition

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A VIRTUAL REALITY BASED INTERACTIVE ANDROID EDUCATIONAL APPLICATION 1

A VIRTUAL REALITY BASED INTERACTIVE ANDROID EDUCATIONAL APPL...

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1st international conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Priya, L. Sathya, A. Kumar, P. Department of Information Technology Rajalakshmi Engineering College Chennai India Department of Computer Science Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9781607685395

programming is one of the most required skills set in today’s IT world. students find it difficult to learn complex programming structure with different syntax. In general, they can learn through online courses or by using books. However, sometimes, it shuttles the thrust of learning programming as it follows some traditional methodologies and it is true that, there is no innovative or interesting way to learn programming conceptually. Hence, an interactive and gamified mode of learning is essential and has been developed using unity 3D. As a result of the transition from the Information Age to the Experience Age, educators face significant challenges. students, for example, are passive and disengaged, and they might even struggle to see the significance of what they are learning to their existences;additionally, important skills required for 21st century learners – such as empathy, organizational theory, creativity, supercomputing literacy, and analytical thinking – are difficult to teach. Virtual reality, as an immersive, hands-on learning tool, has the potential to play a distinctive role in meeting these educational challenges. In this paper, we show how the attributes of virtual reality can lead to new possibilities for learners. We wrap up by discussing suggestions and next steps. © The Electrochemical Society.

关键词： Virtual reality

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PredRacer: Predictively Detecting Data Races in Android Applications 31

PredRacer: Predictively Detecting Data Races in Android Appl...

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31st IEEE international conference on Software Analysis, Evolution and Reengineering, SANER 2024

作者： Guo, Xin Qi, Xiaofang Li, Yanhui Wu, Chao School of Computer Science and Engineering Southeast University China Nanjing University State Key Laboratory for Novel Software Technology China

ISBN: (纸本)9798350330663

Android platform offers a hybrid concurrency model encompassing multi-threading and asynchronous messaging for concurrent programming. The model is powerful but complex, making it difficult for developers to analyze concurrent behaviors. Data race, a prevalent concurrency defect in real-world Android applications, often results in abnormal executions of mobile applications, even crashes. Despite quite a few studies on detecting data races, it still suffers from high false positives with static analysis techniques and high false negatives with dynamic analysis techniques. To address this issue, this paper presents a predictive approach, PredRacer, for detecting data races in Android applications. It first captures an execution trace of an Android application, and then reorders the events within the trace based on partial orders. Finally, it checks the feasibility of the generated event sequence, which contains a potential data race. PredRacer increases the search scope and reduces false negatives while mitigating false positives by incorporating the happen-before relations specific to the Android concurrency model. The effectiveness of PredRacer is evaluated using the BenchERoid data set. Experimental results demonstrate that PredRacer achieves high precision, recall, and F1 score, outperforming the state-of-the-art techniques. A collection of 20 open-source Android applications is further utilized to assess the effectiveness of PredRacer, and an evaluation of 300 wild apps is conducted to assess its efficiency and scalability. © 2024 IEEE.

关键词： static analysis

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Data Analysis on Hypothyroid Profiles using Machine Learning Algorithms 1

Data Analysis on Hypothyroid Profiles using Machine Learning...

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1st IEEE international conference on Contemporary Computing and Communications, InC4 2023

作者： Leisha, R. Medows, Katelyn Prathap, Boppuru Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350335774

Machine learning algorithms enable computers to learn from data and continuously enhance performance without explicit programming. Machine learning algorithms have significantly improved the accuracy and efficacy of thyroid diagnosis. This study identified and analysed the usefulness of several machine-learning algorithms in predicting hypothyroid profiles. The main goal of this study was to see the extent to which the algorithms adequately assessed whether a patient had hypothyroidism. Age, sex, health, pregnancy, and other factors are among the many factors considered. Extreme Gradient Boosting Classifier, Logistic Regression, Random Forest, Long-Term Memory, and K-Nearest Neighbors are some of the machine learning methods used. For this work, two datasets were used and analysed. Data on hypothyroidism was gathered via DataHub and Kaggle. These algorithms were applied to the collected data based on metrics such as Precision, Accuracy, F1 score and Recall. The findings showed that the Extreme Gradient Boosting classification method outperformed the others regarding F1 score, accuracy, precision, and recall. The research demonstrated how machine learning algorithms might predict thyroid profiles and identify thyroid-related illnesses. © 2023 IEEE.

关键词： Random forests

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Topic Relation Graph Construction to Identify Challenges in Introducing programming in Indonesian K-12 Education

Topic Relation Graph Construction to Identify Challenges in ...

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Smart Technology (ICE-SMartec), IEEE international conference on

作者： Mewati Ayub Oscar Karnalim Hapnes Toba Maresha Caroline Wijanto Hans Dulimarta Williyandie Saputra Tabitha Emanuella Kotambunan Master Program of Computer Science Maranatha Christian University Bandung Indonesia Dept. of Computer Science and Engineering Ewha Womans University Seoul South Korea School of Computing Grand Valley State University Michigan USA Informatics Engineering Maranatha Christian University Bandung Indonesia

programming can help K-12 students to develop their 21st-century core skills. Despite the benefits, programming is not common to be delivered in Indonesian K-12 education. There is a need to understand potential challenges in introducing programming to K-12 students. We developed a questionnaire survey covering four identified dimensions of challenges: administrative, facilities, teachers, and students. We also asked about common programming assessments and their preferred software features for teaching programming. Forty K-12 teachers were invited to complete the survey. The responses were analyzed with thematic analysis using a bigram-based Latent Dirichlet Allocation topic modeling and descriptive statistics. Our study shows that the challenges include limited learning modules, an insufficient number of computers, limited programming skills, and limited computational thinking skills. Scratch was the most common programming language used and many programming assessments were about debugging a program or writing a small program. Visualization and animation can be helpful in teaching programming.

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The impact of inlet mach number and domain shape on subsonic nozzle flow via small disturbance equation 1

The impact of inlet mach number and domain shape on subsonic...

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1st international conference on Fluid Dynamics and Computational science, FDCS 2022

作者： Qian, Xuehui School of Science and Engineering The Chinese University of HongKong Shenzhen518000 China

Computational fluid dynamics (CFD) is a cross-disciplinary field that combines mathematics, fluid dynamics, and computer programming to simulate and analyze fluid flow problems using numerical methods. Nowadays, the use of CFD to conduct numerical simulations rather than costly and time-consuming ignition experiments has become an essential aspect of nozzle design. Therefore, it is significant to study the nozzle by numerical simulation. In this paper, a numerical method called small disturbance equation (SDE) is adopted to investigate the impact of inlet Mach number and domain shape on subsonic nozzle flow. Conducting the small disturbance equation via python code, the impact of the inlet Mach number and domain shape is revealed by comparing the different errors of the method, streamlines of the nozzle flow, velocity fields. It is found that with the increase of inlet Mach number, the error of the SDE method grows, and the velocity in x-direction increases while the velocity in y-direction stays the same. Besides, with the shrink of the domain shape, the error of the SDE method gets larger, meanwhile, the maximum of the velocity in each direction increases while the minimum of the velocity decreases. This research would make advantages to identify the optimal designs of a subsonic nozzle. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Computational fluid dynamics

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Deep Learning Based Software Vulnerability Detection in Code Snippets and Tag Questions Using Convolutional Neural Networks 1

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1st international conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies, AMRIT 2023

作者： Khanra, Anurag Krishna, Arvind Jeevan Samrudh, L.H. Makhija, Rahul D. Prasad, V. R. Badri Department of Computer Science and Engineering PES University Bengaluru560003 India

ISBN: (数字)9783031472213

ISBN: (纸本)9783031472206

With the increase in the usage of the internet for gaining and providing information and knowledge, questionnaire forums are becoming popular means of the same for both teenagers and adults. Users post questions and mark them with the topic that they are related to (known as tags). Post this, users always expect quick answers/solutions from known and reliable sources. However, a large number of posted questions remain unanswered due to erroneous and huge number of tags. In our system, we propose an automated method to generate these tags using machine learning and deep learning techniques. This mainly helps in standardizing the tag content for similar questions and the total number of tags that the system needs to deal with. These tags can be generated from the content of the question provided by the user. In addition to this, for questionnaire forums related to programming questions like stackOverflow and stackExchange, our system aims to use the code snippets provided by the user to detect some common software vulnerabilities using deep learning techniques. Software vulnerabilities are weaknesses in software that may be exploited by malicious individuals. These vulnerabilities can arise from coding errors, flaws in design, or inadequate security measures, and can result in unauthorized access, data breaches, or system availability. Detection of these vulnerabilities beforehand will benefit the user and prevent any sort of security threats in their system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Learning algorithms

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Development of Weather Forecast Application using API

Development of Weather Forecast Application using API

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Advances in Computing, Communication and Networking (ICAC2N), international conference on

作者： Shikha Chadha Neha Gupta Rosey Chauhan Department of Computer Science Engineering Sharda University Greater Noida ABES Engineering College Ghaziabad

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

This research paper presents the development of a weather forecasting model that incorporates real-time data through Application programming Interfaces. This model utilises simple algorithms to analyse meteorological parameters from diverse API data sources, aiming to improve forecast accuracy compared to traditional methods. Extensive datasets are used for training and validation, demonstrating the model’s effectiveness in providing more precise predictions. The study highlights the significance of API integration in advancing weather forecasting methodologies and fostering innovation in the field. The model created has yielded highly reliable results with minimal error.

关键词： Training Technological innovation Soft sensors Weather forecasting Predictive models programming Data models Real-time systems Reliability Application programming interfaces

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