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48th Frontiers in Education Conference, FIE 2018

作者： Beck, Phyllis J. Jean Mohammadi-Aragh, M. Archibald, Christopher Jones, Bryan A. Barton, Amy Computer Science and Software Engineering Mississippi State University Mississippi StateMS United States Electrical and Computer Engineering Mississippi State University Mississippi StateMS United States Technical Communication Program Mississippi State University Mississippi StateMS United States

ISBN: (纸本)9781538611739

This is a Work in Progress Research to Practice Category paper. Research has shown that novice programmers struggle with learning introductory concepts and find it difficult to monitor their own progress. Teachers often have hundreds of students and multiple sections of programming courses to teach, making it infeasible to provide the amount of independent feedback each student may need to flourish. With limited instructor feedback, students who can self-monitor and self-assess their programming metacognition have a higher chance of developing a process for solving programming challenges. In this paper, we expand on the literate programming paradigm by using natural language processing and machine learning methods to automatically analyze and classify student programming metacognition levels through their source code comments. Our intent is to ultimately integrate our classification models into an interactive developer environment to provide real-time feedback to students about their metacognition while learning to program. © 2018 IEEE.

关键词： Students

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Control of a Quadcopter with Hybrid Brain-Computer Interface

Control of a Quadcopter with Hybrid Brain-Computer Interface

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IEEE International Conference on Systems, Man and Cybernetics

作者： Yih-Choung Yu Haley Garrison Alexandria Battison Lisa Gabel Department of Electrical and Computer Engineering Lafayette College Easton PA USA KioWare Kiosk Software York PA USA Department of Physiology and Neurobiology University of Connecticut Storrs CT USA Department of Psychology and the Neuroscience Program Lafayette College Easton PA USA

Brain-computer interface (BCI) devices are designed to bypass neuromuscular pathways enabling an individual to operate an external device using neural activity instead of motor activity. The use of BCIs in robotics control has important applications of assisting patients with severe motor disabilities, such as exploration, home assistance, and control of an electric wheelchair. This paper presents a development of a practical implementation of a BCI by utilizing low-cost technologies and asynchronous signal processing techniques for EEG signal acquisition and processing to navigate a quadcopter. A wireless EEG headset was used to acquire the occipital alpha and the frontal muscular artifacts from a user along with the gyroscope signals from the headset. These signals were transmitted wirelessly to a PC for further processing. Signal-processing algorithms were developed and implemented in the PC to extract the patterns from the acquired signals. These patterns, representing the intentions of the user, were then used to control a quadcopter. The design was successfully tested in a virtual environment and a physical device. The results from this preliminary pilot study proved that the design could be used with high accuracy to control a robotic device.

关键词： Conferences Cybernetics Navigation

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Automated risk identification of CMMI project planning using ontology 5

Automated risk identification of CMMI project planning using...

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5th International Conference on Applied Computing and Information Technology, 2017 4th International Conference on Computational Science/Intelligence and Applied Informatics and 2017 1st International Conference on Big Data, Cloud Computing, Data Science and engineering, ACIT-CSII-BCD 2017

作者： Rojrattanakorn, Chanapan Vatanawood, Wiwat Software Engineering Program Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781538633021

Risk management is an important part of software development. Risk identification is the first major step in the risk management process that determines possible risks in a software project and dictates how effective the risk management process will be. However, there are several approaches used to identify risk. The approaches depend on subjective decisions of risk or domain experts which increase cost and workload. Therefore, to make the risk identification more effective, a systematic and automated approach is necessary. In this paper, we propose an alternative risk identification scheme using knowledgeable ontology representing risk taxonomy and CMMI project planning guideline. The ontology provides the relations among risk factors and software project risks according to the structure of risk taxonomy and the relevant process areas in CMMI. In this paper, we focus and demonstrate the CMMI project planning process area as an initiative to construct our ontology. The resulting ontology is supportive as expected and scalable to handle more on the other process areas of CMMI and the addition of the software project risks. © 2017 IEEE.

关键词： Ontology

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Evaluation of an Instrument to Identify Factors that Impact the Motivation and Engagement of Undergraduate Students in Computing 48

Evaluation of an Instrument to Identify Factors that Impact ...

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48th Frontiers in Education Conference, FIE 2018

作者： Schoeffel, Pablo Wazlawick, Raul Sidnei Ramos, Vinicius Faria Culmant Vahldick, Adilson Souza, Marcelo De Graduate Program in Computer Science Federal University of Santa Catarina Florianópolis Brazil Department of Information and Communication Technologies Federal University of Santa Catarina Araranguá Brazil Departament of Software Engineering University of Santa Catarina State Ibirama Brazil

ISBN: (纸本)9781538611739

This Research Paper presents the evaluation of an instrument to identify the impact of motivation and engagement factors in undergraduate students in computing. Although researches indicate a direct impact of motivation and engagement on student performance and retention, few studies have been found that address which factors are relevant in this process. The instrument is a questionnaire based on the compilation of several works of the literature containing 48 items divided into 6 groups: personal and demographic data, general perception about motivation, perception about the university, student behavior, perception about program and perception about classes/teachers. The questionnaire evaluation is based on a case study with 112 undergraduate students in software engineering. As a result, we found that the questionnaire can be considered reliable (Cronbach's alpha = 8904). Considering the validity of constructs, we found an acceptable degree of correlation between the most pair of items in each group (averaging 63%). We also found that the item-total correlation coefficient was only not adequate for one factor group, indicating satisfactory correlation for all other items. Finally, we found that the number of factors is coherent, but there are several items from different groups strongly correlated, indicating the need for a reorganization. © 2018 IEEE.

关键词： Students

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Identification of Pre-University Factors that Affect the Initial Motivation of Students in Computing programs: A multi-institutional case study 48

Identification of Pre-University Factors that Affect the Ini...

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48th Frontiers in Education Conference, FIE 2018

ISBN: (纸本)9781538611739

This Research to Practice Paper presents the results of the evaluation of pre-university factors that impact the initial motivation of undergraduate students in computing. Although there are studies in the literature that have investigated some previous factors, this paper replicates a previous work that aims to consolidate several pre-university factors and, as the main differential, uses the AMS (Academic Motivation Scale), a scale already consolidated in the literature to measure students' initial motivation, and evaluate the relation between motivation and candidate factors. We applied a questionnaire to 159 students from different computing programs in ten universities, which evaluates 20 factors divided into 4 groups: personal and demographic data, taste and knowledge of the program and area, computing experience, and school performance. To evaluate the correlation between factors and motivation, we used Spearman's coefficient, t-student test, and ANOVA to evaluate the correlation between factors and motivation. As main results, we found significant variation in the initial motivation according to following factors: taste for programming and technology, knowledge about the undergraduate program content, correct perception about computing professionals, knowledge and experience in computer programming, and general school performance. © 2018 IEEE.

关键词： Motivation

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Evaluation of Adherence to the Model Six Sigma Using Paraconsistent Logic

Evaluation of Adherence to the Model Six Sigma Using Paracon...

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2018 IEEE International Conference on Innovations in Intelligent Systems and Applications, INISTA 2018

作者： Kirilo, Caique Z. Abe, Jair M. Nogueira, Marcelo Nakamatsu, Kazumi Lozano, Luiz Carlos MacHi De Lima, Luiz A. Software Engineering Research Group Paulista University UNIP São Paulo Brazil Graduate Program in Production Engineering Paulista University UNIP São Paulo Brazil ALGORITMI Centre School of Engineering University of Minho Guimarães Portugal School of Human Science and Environment H.S.E University of Hyogo Hyogo Japan

This study aims to present a compliance analysis tool to Six Sigma by integrating indicative of success and Paraconsistent Method Decision. This way is contributing to a previous scenario analysis that can help the im... 详细信息

ISBN: (纸本)9781538651506

关键词： Six sigma

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Selection of supplier using analytical hierarchy process: Creating value added in the supply chain agribusiness 4

Selection of supplier using analytical hierarchy process: Cr...

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4th International Conference on Computer Applications and Information Processing Technology, CAIPT 2017

作者： Bukhori, Saiful Sukmawati, Diah Ayu Eka, Y.R. Windi Software Engineering Laboratory Computer Science Program University of Jember Jember Indonesia

ISBN: (纸本)9781538606001

The concept of Supply Chain Management (SCM) has significant potential for added value which can be utilized with the concepts of innovative economy. One of the added value in SCM is the supplier selection process. This research is model in SCM Agribusiness supplier selection using Analytical Hierarchy Process (AHP). The criteria used in this model is the price, past performance, delivery time, professionalism, quality, locations, responsive, and guarantee. The value of criteria entered by suppliers assessed with weights determined by the agro-industrial company by using AHP. Based on experiments with the value of each supplier, then processed using the AHP generated ranking of suppliers. The first ranking generated is the first option to supply the raw material in which the supplier register. © 2017 IEEE.

关键词： Supply chain management

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Bitcoin’s future carbon footprint

arXiv

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arXiv 2020年

作者： Qin, Shize Klaaßen, Lena Gallersdörfer, Ulrich Stoll, Christian Zhang, Da Institute of Energy Environment and Economy Tsinghua University Beijing100084 China TUM School of Management Technical University of Munich Munich Germany TUM Software Engineering for Business Information Systems Department of Informatics Technical University of Munich Munich Germany MIT Center for Energy and Environmental Policy Research Massachusetts Institute of Technology CambridgeMA United States TUM Center for Energy Markets TUM School of Management Technical University of Munich Munich Germany MIT Joint Program on the Science and Policy of Global Change CambridgeMA02139 United States

The carbon footprint of Bitcoin has drawn wide attention, but Bitcoin’s long-term impact on the climate remains uncertain. Here we present a framework to overcome uncertainties in previous estimates and project Bitcoin’s electricity consumption and carbon footprint in the long term. If we assume Bitcoin’s market capitalization grows in line with the one of gold, we find that the annual electricity consumption of Bitcoin may increase from 50 to 400 TWh between 2020 and 2100. The future carbon footprint of Bitcoin strongly depends on the decarbonization pathway of the electricity sector. If the electricity sector achieves carbon neutrality by 2050, Bitcoin’s carbon footprint has peaked already. However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6% of global emissions in 2018. Therefore, we also discuss policy instruments to reduce Bitcoin’s future carbon footprint. Copyright © 2020, The Authors. All rights reserved.

关键词： Carbon footprint

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Multi-Coil MRI reconstruction challenge - Assessing brain MRI reconstruction models and their generalizability to varying coil configurations

arXiv

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arXiv 2020年

作者： Beauferris, Youssef Teuwen, Jonas Karkalousos, Dimitrios Moriakov, Nikita Caan, Matthan Yiasemis, George Rodrigues, Lúvia Lopes, Alexandre Pedrini, Helio Rittner, Letícia Dannecker, Maik Studenyak, Viktor Gröger, Fabian Vyas, Devendra Faghih-Roohi, Shahrooz Jethi, Amrit Kumar Raju, Jaya Chandra Sivaprakasam, Mohanasankar Lasby, Mike Nogovitsyn, Nikita Loos, Wallace Frayne, Richard Souza, Roberto Radiology and Clinical Neurosciences University of Calgary Canada Hotchkiss Brain Institute University of Calgary Canada Seaman Family Mr Research Centre Foothills Medical Center Canada Department of Medical Imaging Radboud University Medical Center Netherlands Department of Radiation Oncology Netherlands Cancer Institute Netherlands ICAI-AI for Oncology University of Amsterdam Netherlands Department of Biomedical Engineering and Physics Amsterdam Umc University of Amsterdam Netherlands School of Electrical and Computer Engineering University of Campinas Brazil Institute of Computing University of Campinas Brazil Computer Aided Medical Procedures Technical University of Munich Germany India Iitm India Department of Electrical and Software Engineering University of Calgary Canada Centre for Depression and Suicide Studies St. Michael's Hospital Canada Mood Disorders Program Department of Psychiatry and Behavioural Neurosciences McMaster University Canada

Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific community lacks appropriate benchmarks to assess MRI reconstruction quality of high-resolution brain images, and evaluate how these proposed algorithms will behave in the presence of small, but expected data distribution shifts. The Multi-Coil Magnetic Resonance Image (MC-MRI) Reconstruction Challenge provides a benchmark that aims at addressing these issues, using a large dataset of high-resolution, threedimensional, T1-weighted MRI scans. The challenge has two primary goals: 1) to compare different MRI reconstruction models on this dataset and 2) to assess the generalizability of these models to data acquired with a different number of receiver coils. In this paper, we describe the challenge experimental design, and summarize the results of a set of baseline and state of the art brain MRI reconstruction models. We provide relevant comparative information on the current MRI reconstruction state-of-the-art and highlight the challenges of obtaining generalizable models that are required prior to broader clinical adoption. The MC-MRI benchmark data, evaluation code and current challenge leaderboard are publicly available. They provide an objective performance assessment for future developments in the field of brain MRI reconstruction. Copyright © 2020, The Authors. All rights reserved.

关键词： Inverse problems

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Transient Thermal Analysis of Welding Fixtures Design 2

Transient Thermal Analysis of Welding Fixtures Design

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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Anual, M.T. Sahroni, T.R. Akmal, S. Nasution, F.A. Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Manufacturing Engineering Innovative Software System and Services Research Group Centre for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia

This paper presents the design and analysis of welding fixtures based on transient thermal analysis. Welding fixtures is designed to hold and support the workpiece securely during the welding process. The heat transformation from the workpiece could lead the temperature rises and impacts to the welding fixtures. Therefore, the study introduces the development of welding fixtures as one of a safety measure prevents the welder from injury while handling welding process. The conceptual design of welding fixtures and material were applied to conduct the simulation. Transient thermal analysis was performed on temperature and total heat flux by using computer aided engineering software. The result shows the analysis of equivalent stress, total deformation, factors of safety, fatigue life and fatigue damage. Furthermore, the equivalent stress failure theory used to predict yielding in welding fixture design. The design of welding fixtures and material selection were proposed to hold and support the workpiece securely. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Heat flux

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