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arXiv 2022年

作者： Mathews, Noble Saji Chimalakonda, Sridhar Research in Intelligent Software & Human Analytics Lab Indian Institute of Technology Tirupati India

Game development-based approaches are increasingly used to design curricula that can engage students, as these can help them apply and practice learnt computer science concepts. However, it can become complex to develop a minimum working game or a prototype with the help of high-end game engines. Game prototyping is one of the most essential parts of the game design and development cycle as it allows developers to continuously test and improve their ideas. In recent years, computational notebooks have gained widespread popularity among developers. They can help run individual code snippets, visualize the output, consolidate the source code, and share live code easily. However, its use has not been explored in the field of game development and prototyping. In this paper, we propose NoteG, a computational notebook towards rapid game prototyping. We evaluated the tool with 18 novice game developers through a questionnaire-based user survey. A majority of the volunteers (66%) found it easy to use and were of the opinion that it saves time. A few of the participants successfully extended the existing framework to implement new game mechanics within their prototypes. © 2022, CC BY-NC-SA.

关键词： Surveys

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Resilience Evaluation for Power Distribution systems Impacted by Winter Storms

Resilience Evaluation for Power Distribution Systems Impacte...

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2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Simental, Orlando Quezada Mandal, Paras Galvan, Eric Kamalasadan, Sukumar Lab Ece Department El PasoTX79968 United States El Paso Electric The Load Research and Data Analytics Department El PasoTX79901 United States The University of North Carolina at Charlotte Power Energy and Intelligent Systems Laboratory Ece Department CharlotteNC28223 United States

ISBN: (纸本)9798350320169

Over the past years, electric power distribution blackouts have been caused by natural events, creating more than one trillion dollars in total damages in the U.S. These events mainly affect power distribution systems making them very vulnerable to extreme weather. Therefore, it is important to further study ways to enhance the resilience of power distribution systems impacted by dangerous weather, such as winter storms. This paper presents a new approach for resilience evaluation for a power distribution system composed of networked microgrids (MGs). This involves the integration of distributed roof-top photovoltaic systems (PV) and electric vehicles (EVs) into MGs for resilience enhancements. In the study, EVs are utilized as energy storage that can operate in vehicle-to-home (V2H) and vehicle-to-grid (V2G). To evaluate the utilization of EVs and roof-top PV as backup power sources, several case studies are shown and assessed with a variety of resilience metrics. Test results reveal that EVs, and roof-top PVs can meet the energy needs of residential users for up to 20 hours and provide distribution grid support through surplus energy of the EVs aggregated by the network MGs;enhancing the resilience of the power distribution system being impacted by extreme weather. © 2023 IEEE.

关键词： Roofs

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Speech-Based Alzheimer's Disease Classification System with Noise-Resilient Features Optimization

Speech-Based Alzheimer's Disease Classification System with ...

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Artificial Intelligence and Cognitive Science (AICS), Irish Conference on

作者： Virender Kadyan Puneet Bawa Mohd Mujtaba Akhtar Muskaan Singh Speech and Language Research Centre University of Petroleum and Energy Studies Dehradun India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Cognitive Analytics Research Lab Intelligent Systems Research Centre School of Computing Ulster University UK

Alzheimer's disease is a severe neurological disorder having a major influence on a substantial portion of the popu-lation. The prompt detection of this condition is crucial, and speech analysis may play a crucial role in facilitating efficient treatment and care. The main aim of this research has been to investigate the significance of timely identification of speech signal abnormalities associated with Alzheimer's disease in order to provide effective therapy interventions and improve disease man-agement. The study used the Mel Frequency Cepstral Coefficients (MFCC) framework, a well recognized technique for feature extraction known for its versatility across several domains. This research introduces an innovative approach that utilizes both individuals diagnosed with dementia and control participants to detect two unique types of cognitive impairment via the analysis of speech signals. The approach used in this work involves the extraction of acoustic properties from pre-processed speech data obtained from the Pitt Corpus of Dementia Bank. This is achieved by using several feature sets, which include a combination of MFCC, prosodic features, and statistical features. This study examines the attributes of optimum feature optimization in actual and noise-enhanced speech environments using machine learning techniques. The integration of MFCC,Statistical and prosodic features has shown remarkable outcomes, exhibiting a superior accuracy rate of 98.3%. This surpasses the performance of other feature combinations when using the Random Forest classifier.

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Comprehensive Phonological Analysis for Clinical Implication Using Self-Attention Based Grapheme to Phoneme Modeling Under Low-Resource Conditions

Comprehensive Phonological Analysis for Clinical Implication...

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Artificial Intelligence and Cognitive Science (AICS), Irish Conference on

作者： Puneet Bawa Virender Kadyan Muskaan Singh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Speech and Language Research Centre University of Petroleum and Energy Studies Dehradun India Cognitive Analytics Research Lab Intelligent Systems Research Centre School of Computing Ulster University UK

Within the field of speech recognition, a significant obstacle occurs when faced with low-resource situations charac-terized by a scarcity of accessible speech data, which is also het-erogeneous in nature. This becomes more challenging considering the aspect of clinical environments, where accurate transcription of speech is of utmost significance in the identification and man-agement of speech and language disorders. The current manual methodologies used for the development of language models (LMs) and the recognition of speech often encounter difficulties in low-resource scenarios, exhibiting limited ability to adjust to the distinct speech patterns shown by diverse demographics. The present study aims to tackle a significant issue within the field of voice recognition by proposing a solution centered on the advancement of automated language modeling. Specifically, the study highlights the importance of n-gram LMs in this context. The study sheds light on an innovative method that utilizes automated language model development using the multi-head self-attention transformer-based Grapheme-to-Phoneme (G2P) modeling. The results clearly indicate that automated language models outperform humanly created alternatives, highlighting their impressive adaptability and dependability. Furthermore, this research investigates the potential for metamorphosis offered by n-gram language models, resulting in a notable increase in recognition accuracy for the speech recognition system based on the Deep Neural Network-Hidden Markov Model (DNN-HMM).

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Data Fusion Learning Enhanced Xabilities Analysis 31

Data Fusion Learning Enhanced Xabilities Analysis

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Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI 2022

作者： Blasch, Erik P. Kadar, Ivan Grewe, Lynne Chong, Chee-Yee Chen, Genshe Chen, Yu Savakis, Andreas Zheng, Yufeng MOVEJ Analytics Air Force Research Lab United States Interlink Systems Sciences Inc. United States California State Univ. United States Intelligent Fusion Technology Inc. United States Binghamton University United States Rochester Institute of Technology United States University of Mississippi Medical Center United States

ISBN: (纸本)9781510651203

The panel brings together experts to focus on the Xabilities analysis over multi-source data, modeling, and tasks in domains of static (off-line), dynamic (on-line), and usable (in-line) learning methods. All of these requirements motivate the need for addressing data curation, metrics development, relevance assessment, human involvement, and system coordination. Looking holistically, these Xabilities motivate pragmatic thought and analysis for SDF design of concepts and outputs. (1) design (explainability, interpretability), (2) evaluation (verifiability, robustness), (3) test (validity, certifiability) and (4) deployment (reliability, accountability, sustainability). There are a variety of questions to be discussed, explored, and analyzed for fusion-based AI tool. © 2022 SPIE.

关键词： Data fusion

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A Mocktail of Source Code Representations 21

A Mocktail of Source Code Representations

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IEEE International Conference on Automated Software Engineering (ASE)

作者： Dheeraj Vagavolu Karthik Chandra Swarna Sridhar Chimalakonda Research in Intelligent Software & Human Analytics (RISHA) Lab Indian Institute of Technology Tirupati Tirupati India

ISBN: (纸本)9781665447843

Efficient representation of source code is essential for various software engineering tasks such as code classification and code clone detection. Most recent approaches for representing source code still use AST and do not leverage semantic graphs such as CFG and PDG. One effective technique for representing source code involves extracting paths from the AST and using a learning model to capture program properties. Code2vec is one such path-based approach that uses an attention-based neural network to learn code embeddings which can then be used for various downstream tasks. However, this approach uses only AST and does not leverage CFG and PDG. Even though an integrated graph approach (Code Property Graph) exists for representing source code, it has only been explored in the domain of software security. Moreover, it does not leverage the paths from the individual graphs. Our idea is to extend the path-based approach code2vec to include the semantic graphs CFG and PDG with AST, which is largely unexplored in software engineering. We evaluate our approach on the task of METHODNAMING using a C dataset of 730K methods collected from GitHub. In comparison to code2vec, our approach improves the F1 score by 11% on the full dataset and up to 100% with individual projects. We show that semantic features from the CFG and PDG paths drastically improve the performance of the software engineering tasks. We envision that looking at a mocktail of source code representations for various software engineering tasks can lay the foundation for a new line of research and a re-haul of existing research.

关键词： Adaptation models Codes Semantics Neural networks Syntactics Software Security

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APIScanner - Towards Automated Detection of Deprecated APIs in Python Libraries

APIScanner - Towards Automated Detection of Deprecated APIs ...

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International Conference on Software Engineering - Companion, ICSE, Companion

作者： Aparna Vadlamani Rishitha Kalicheti Sridhar Chimalakonda Research in Intelligent Software & Human Analytics (RISHA) Lab Indian Institute of Technology Tirupati Tirupati India

ISBN: (纸本)9781665429757

Python libraries are widely used for machine learning and scientific computing tasks today. APIs in Python libraries are deprecated due to feature enhancements and bug fixes in the same way as in other languages. These deprecated APIs are discouraged from being used in further software development. Manually detecting and replacing deprecated APIs is a tedious and time-consuming task due to the large number of API calls used in the projects. Moreover, the lack of proper documentation for these deprecated APIs makes the task challenging. To address this challenge, we propose an algorithm and a tool APIScanner that automatically detects deprecated APIs in Python libraries. This algorithm parses the source code of the libraries using abstract syntax tree (ASTs) and identifies the deprecated APIs via decorator, hard-coded warning or comments. APIScanner is a Visual Studio Code Extension that highlights and warns the developer on the use of deprecated API elements while writing the source code. The tool can help developers to avoid using deprecated API elements without the execution of code. We tested our algorithm and tool on six popular Python libraries, which detected 838 of 871 deprecated API elements. Demo of APIScanner: https://***/1hy_ugf-iek. Documentation, tool, and source code can be found here: https://***/APIScanner.

关键词： Visualization Software algorithms Documentation Tools Libraries Task analysis Python

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Resilience Evaluation for Power Distribution systems Impacted by Winter Storms

Resilience Evaluation for Power Distribution Systems Impacte...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Orlando Quezada Simental Paras Mandal Eric Galvan Sukumar Kamalasadan ECE Department The Power & Renewable Energy Systems (PRES) Lab The University of Texas at El Paso El Paso TX USA The Load Research and Data Analytics Department El Paso Electric El Paso TX USA ECE Department Power Energy and Intelligent Systems Laboratory The University of North Carolina at Charlotte Charlotte NC USA

Over the past years, electric power distribution blackouts have been caused by natural events, creating more than one trillion dollars in total damages in the U.S. These events mainly affect power distribution systems making them very vulnerable to extreme weather. Therefore, it is important to further study ways to enhance the resilience of power distribution systems impacted by dangerous weather, such as winter storms. This paper presents a new approach for resilience evaluation for a power distribution system composed of networked microgrids (MGs). This involves the integration of distributed roof-top photovoltaic systems (PV) and electric vehicles (EVs) into MGs for resilience enhancements. In the study, EVs are utilized as energy storage that can operate in vehicle-to-home (V2H) and vehicle-to-grid (V2G). To evaluate the utilization of EVs and roof-top PV as backup power sources, several case studies are shown and assessed with a variety of resilience metrics. Test results reveal that EVs, and roof-top PVs can meet the energy needs of residential users for up to 20 hours and provide distribution grid support through surplus energy of the EVs aggregated by the network MGs; enhancing the resilience of the power distribution system being impacted by extreme weather.

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Striving for Authentic and Sustained Technology Use In the Classroom: Lessons Learned from a Longitudinal Evaluation of a Sensor-based Science Education Platform

arXiv

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arXiv 2023年

作者： Chua, Yvonne Cooray, Sankha Cortes, Juan Pablo Forero Denny, Paul Dupuch, Sonia Garbett, Dawn L. Nassani, Alaeddin Cao, Jiashuo Qiao, Hannah Reis, Andrew Reis, Deviana Scholl, Philipp M. Sridhar, Priyashri Kamlesh Suriyaarachchi, Hussel Taimana, Fiona Tang, Vanessa Weerasinghe, Chamod Wen, Elliott Wu, Michelle Wu, Qin Zhang, Haimo Nanayakkara, Suranga Augmented Human Lab. Auckland Bioengineering Institute The University of Auckland New Zealand Augmented Human Lab. Department of Information Systems and Analytics National University of Singapore Singapore School of Computer Science The University of Auckland New Zealand Faculty of Education The University of Auckland Auckland New Zealand Engineering Product Development Singapore University of Technology and Design Singapore OPPO Research Institute Shanghai China

Technology integration in educational settings has led to the development of novel sensor-based tools that enable students to measure and interact with their environment. Although reports from using such tools can be positive, evaluations are often conducted under controlled conditions and short timeframes. There is a need for longitudinal data collected in realistic classroom settings. However, sustained and authentic classroom use requires technology platforms to be seen by teachers as both easy to use and of value. We describe our development of a sensor-based platform to support science teaching that followed a 14-month user-centered design process. We share insights from this design and development approach, and report findings from a 6-month large-scale evaluation involving 35 schools and 1245 students. We share lessons learnt, including that technology integration is not an educational goal per se and that technology should be a transparent tool to enable students to achieve their learning goals. © 2023, CC BY-NC-ND.

关键词： Students

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Simulating the Dilution of Sulfuric Acid on Mixed Reality Platform 8

Simulating the Dilution of Sulfuric Acid on Mixed Reality Pl...

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8th International Conference on Virtual Reality, ICVR 2022

作者： Pan, Zhipeng Miao, Jinda Cai, Ning Luo, Tianren Zhang, Mingmin Pan, Zhigeng Research Institute of Virtual Reality and Intelligent Systems Hangzhou Normal University Hangzhou China Zhejiang University College of Computer Science and Technology Hangzhou China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science and Beijing Key Lab of Human-Computer Interaction Beijing China Nanjing University of Information Science and Technology School of Artificial Intelligence Nanjing China

ISBN: (数字)9781665479110

ISBN: (纸本)9781665479110

Augmented reality technology has been widely used in experimental education. Augmented reality provides virtual-real integration, real-Time interaction and three-dimensional immersion, which provides a new development direction for simulating the teaching environment and promoting learning interaction. We have developed an MR experiment of diluting concentrated sulfuric acid, which helps students learn experimental manipulations and scientific concepts before conducting real chemical experiments. Virtual experiments can avoid the risks of real chemical experiments and reduce the waste of chemical materials. At the same time, we correctly render the occlusion relationship between the hand, the beaker and the virtual liquid, providing a realistic experimental effect. The tracking of multiple cameras allows students to interact more naturally. We compared the availability and students' attitudes of three virtual experiments about diluting concentrated sulfuric acid. The results show that the usability of the MR experimental system reaches the level of user satisfaction. The realistic visual effects and natural interaction method of the MR experiment have been recognized by the students. © 2022 IEEE.

关键词： Students

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