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Learn to Code, an Interactive Application to Promote Mobile Student-Centred Learning 13th

Learn to Code, an Interactive Application to Promote Mobile ...

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13th international conference on Interactive Mobile Communication, Technologies and Learning (IMCL)

作者： Colom, Anne-Gaelle Purdy, Wendy Univ Westminster 115 New Cavendish St London W1W 6UW England

ISBN: (纸本)9783030499327;9783030499310

this paper discusses the first two phases in the development of a Learn to Code online web-based application, presents our initial findings and outlines the next stage of the research. First year computer science students start university with a wide range of qualifications, competencies, learning styles and experience with respect to computer programming. Research has found that the way programming is taught impacts on students' confidence, their level of interest for the subject and whether they continue with programming. A common criticism of the teaching of computer programming is that it is too 'abstract' and hard to grasp, leading to students losing interest in the subject. the application is a digital resource developed to build students' confidence in three common programming languages. the application uses code visualisation, web animation, lessons and video. the code visualiser analyses the code entered by the student and shows them graphically - in real-time - the code in the form of a flowchart. the application promotes learner autonomy and was designed to be accessible from multiple platforms and devices to enable students to be mobile learners. Feedback has been positive. Future work will extend the functionality of the application and the collaboration with students as co-creators.

关键词： Learn to Code Dynamic flowcharts technology enhanced-learning Mobile learning

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Effects of Stimulus Sequences on Brain-computer Interfaces Using Code-Modulated Visual Evoked Potentials: An Offline Simulation 17th

Effects of Stimulus Sequences on Brain-Computer Interfaces U...

引用

17th international Work-conference on Artificial Neural Networks (IWANN)

作者： thielen, Jordy Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Thomas van Aquinostr 4 NL-6525 GD Nijmegen Netherlands

ISBN: (纸本)9783031430770;9783031430787

Brain-computer interfaces (BCIs) translate brain activity into computer commands opening a novel non-muscular channel for communication and control. Before BCIs can be used effectively, they require extensive calibration of their machine learning algorithms using labeled training data. this tedious calibration process is not only time-consuming and costly but also restricts the exploration and optimization of stimulus parameters that could greatly enhance BCI performance. To overcome the challenge of acquiring large training datasets, a simulation framework was developed to eliminate the need for recording calibration data. Unlike previous studies, this simulation framework incorporates a biologically plausible forward model of the code-modulated visual evoked potential (c-VEP). By utilizing synthetic data generated by this improved simulation framework, an offline study was conducted to systematically compare five different stimulus conditions: almost perfect autocorrelation (APA) sequence, de Bruijn sequence, Golay sequence, Gold code, and m-sequence. the results of the study revealed that the Golay sequence achieved the highest grand average performance, followed by the APA sequence, m-sequence, Gold code, and finally the de Bruijn sequence. Furthermore, when the stimulus sequence was optimized for individual participants, typically the Golay and APA sequences exhibited the highest classification accuracy, leading to a significant improvement in overall accuracy as compared to using the Golay sequence for all participants. this research represents an important initial step towards optimizing stimulus parameters for BCIs using simulated data. this approach has the potential to accelerate the development and optimization of BCIs, resulting in more effective applications that can be tailored to individual users.

关键词： Brain-computer interfacing Code-modulated visual evoked potentials Electroencephalography Simulation

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A Multiobjective Memetic Algorithm for Multiobjective Unconstrained Binary Quadratic Programming Problem 12th

A Multiobjective Memetic Algorithm for Multiobjective Uncons...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Zhou, Ying Kong, Lingjing Yan, Lijun Liu, Shaopeng Hong, Jiaming School of Computer Sciences Shenzhen Institute of Information Technology Shenzhen China Department of Computer Science Guangdong Polytechnic Normal University Guangzhou China School of Medical Information Engineering Guangzhou University of Chinese Medicine Guangzhou China

ISBN: (纸本)9783030788100

this study introduces a multiobjective memetic algorithm for multiobjective unconstrained binary quadratic programming problem (mUBQP). It integrates multiobjective evolutionary algorithm based on decomposition and tabu search to search an approximate Pareto front with good convergence and diversity. To further enhance the search ability, uniform generation is introduced to generate different uniform weight vectors for decomposition in every generation. the proposed algorithm is tested on 50 mUBQP instances. Experimental results show the effectiveness of the proposed algorithm in solving mUBQP. © 2021, Springer Nature Switzerland AG.

关键词： Tabu search

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WHY ARE PEOPLE STILL NOT WALKING? thE NEED FOR A MICRO-SCALED MULTI-CRITERIA SPATIO-TEMPORAL DESIGN APPROACH TO IMPROVE WALK-QUALITY 7

WHY ARE PEOPLE STILL NOT WALKING? THE NEED FOR A MICRO-SCALE...

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7th international conference on Smart Data and Smart Cities, SDSC 2022

作者： White, M. Huang, X. Langenheim, N. Yang, T. Schofield, R. Young, M. Livesley, S.J. Seneviratne, S. Stevenson, M. Centre for Design Innovation Swinburne University of Technology Australia School of Architecture and Art North China University of Technology Beijing China Melbourne School of Design University of Melbourne Australia School of Geography Earth and Atmospheric Sciences University of Melbourne Australia Ecosystem and Forest Sciences Faculty of Science University of Melbourne Australia Melbourne Schools of Design| Engineering| Population and Global Health University of Melbourne Australia

Walking is essential for the health and well-being of communities as well as meeting environmental challenges of the 21st Century. there have been significant research contributions in recent decades to understanding factors that can influence the likelihood of citizens choosing active travel modes, with great advances in understanding the built environment, particularly macro-scaled urban factors such as land-use mix, population density, and street patterns. So why are people still not walking? And is there anything we can do to try to change this? To answer these questions, this paper explores walking environment assessment approaches using a trans-disciplinary narrative approach, touching on multiple critical disciplinary knowledge areas. We find that while much of the research into the built environment's influence on walking has made positive contributions in helping identify areas of cities that discourage active travel, the capacity to improve these areas has been limited. While macro-scaled factors commonly considered in 'walkability' analysis are highly influential to mode choice, unless working on green-field development, these factors may require re-zoning private land, substantial demolition and renewal, and may be financially or politically infeasible and thus extremely difficult to change. there is a need to augment macro-scaled analysis with micro-scaled tools, and to establish multi-criterion spatio-temporal design decision support approaches drawing from emerging technologies to make informed, integrated and effective urban design changes. these methods applied at precinct and streetscape levels have the potential to make feasible improvements to the 'walk-quality' of the built environment and contribute to facilitating active travel. © Author(s) 2022.

关键词： computer vision

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Integrated Model for the Prediction of Disease and Treatment Recommendation 8th

Integrated Model for the Prediction of Disease and Treatment...

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

作者： Sharma, Ashish Shuman, Prashant Gourisaria, Mahendra Kumar Department of Computer Engineering and Applications GLA University UP Mathura India School of Computer Engineering KIIT Deemed to be University Odisha Bhubaneswar India

ISBN: (纸本)9783031709050

Health care is provided by health care professionals in the related fields of health and social care. the healthcare system provides healthcare services to ensure the health of the target groups. there is an increase in infectious diseases, and non-communicable diseases, which will create a double burden on the health of the public against it. It is best to try and find the right doctor and ask for a certain amount. It is not an easy task. this is for the health information management systems, helping you to find and match a specialist doctor for a particular illness in the immediate mode, and will also provide advice and information on the disease can be cured. this health management system makes it easy to find a doctor who will help the patients to recover more quickly from illnesses. Health care, in combination with information technology in a new direction to it is full, complete, and consistent information directly affects the quality and efficiency of the health service, as well as the safety, security, diagnostics, and treatment. However, the level of information is defined as a reflection of the degree of its application, and the degree of integration of the information systems, processes, and procedures. this concept can be defined as the integration of the information systems (is) and other applications are being used together, and can be accessed via a variety of communication networks. In order to fully carry out the integration of the IP, security, and a lot of medical information, as well as an effective, easy, and fast exchange, as well as for scientific analysis, and processing of tasks employing all available technologies—including cloud computing, Internet of things, Internet technology, and data analytics—is essential. this research explains the pertinent principles and talks about earlier studies in this field. To integrate machine learning and other methods to examine the literature on health care management. Finally, the more accurate solution

关键词： Electronic health record

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Automatic Detection of Buildings Using High Resolution Images for Medium Density Regions 4th

Automatic Detection of Buildings Using High Resolution Image...

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4th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2021

作者： Kirwale, Karuna Sitaram Kawathekar, Seema S. Deshmukh, Ratnadeep R. Department of Computer Science and IT Dr. Babasaheb Ambedkar Marathwada University Aurangabad India

ISBN: (纸本)9783030925994

As the construction material of the building is different hence building detection is critical task from the HRI. the image qualities, resolution, weather type of image sensor are important factors to produce accuracy. Building detection in dense urban areas having problems due to factors like shape, size, color and texture, and image sensor. For the find, the building has to consider the characters of the building like contrast, shape, and the building allocation in high, low, and medium density. In the present study, the mathematical morphological operation is used for the separation of the building. the building is indicated with a boundary. © 2021, IFIP international Federation for Information Processing.

关键词： Buildings

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Rule Based Combined Tagger for Marathi Text 4th

Rule Based Combined Tagger for Marathi Text

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4th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2021

作者： Khandale, Kalpana B. Namrata Mahender, C. Department of Computer Science and IT Dr. Babasaheb Marathwada University Maharashtra Aurangabad India

ISBN: (纸本)9783030925994

Part of speech (POS) tagging is most necessary concept in the natural language processing categorized each word in the corpus. this paper focus on the development of Marathi part of speech tagger using the N-gram models. For this we have designed rules for the development of the POS tagger. these rules are framed on the basis of the Marathi grammar. the corpus is of 635 Marathi sentences written in considering variations, for better evaluation of the POS tagger. Total 5715 words has been tagged from in which 1918 words unigram tagger and 106 words are tagged by the bigram tagger. the overall accuracy of POS tagger is 79.34%. © 2021, IFIP international Federation for Information Processing.

关键词： Natural language processing systems

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REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes 23

REEF: A Framework for Collecting Real-World Vulnerabilities ...

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Proceedings of the 38th IEEE/ACM international conference on Automated Software Engineering

作者： Chaozheng Wang Zongjie Li Yun Peng Shuzheng Gao Sirong Chen Shuai Wang Cuiyun Gao Michael R. Lyu School of Computer Science and Technology Harbin Institute of Technology Shenzhen China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China Computer Science and Engineering Department The Chinese University of Hong Kong Hong Kong China

ISBN: (纸本)9798350329964

Software plays a crucial role in our daily lives, and therefore the quality and security of software systems have become increasingly important. However, vulnerabilities in software still pose a significant threat, as they can have serious consequences. Recent advances in automated program repair have sought to automatically detect and fix bugs using data-driven techniques. Sophisticated deep learning methods have been applied to this area and have achieved promising results. However, existing benchmarks for training and evaluating these techniques remain limited, as they tend to focus on a single programming language and have relatively small datasets. Moreover, many benchmarks tend to be outdated and lack diversity, focusing on a specific codebase. Worse still, the quality of bug explanations in existing datasets is low, as they typically use imprecise and uninformative commit messages as *** address these issues, we propose an automated collecting framework REEF to collect REal-world vulnErabilities and Fixes from open-source repositories. We focus on vulnerabilities since they are exploitable and have serious consequences. We develop a multi-language crawler to collect vulnerabilities and their fixes, and design metrics to filter for high-quality vulnerability-fix pairs. Furthermore, we propose a neural language model-based approach to generate high-quality vulnerability explanations, which is key to producing informative fix messages. through extensive experiments, we demonstrate that our approach can collect high-quality vulnerability-fix pairs and generate strong explanations. the dataset we collect contains 4,466 CVEs with 30,987 patches (including 236 CWE) across 7 programming languages with detailed related information, which is superior to existing benchmarks in scale, coverage, and quality. Evaluations by human experts further confirm that our framework produces high-quality vulnerability explanations.

关键词： vulnerability

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Learning 21^st Century Skills through Educational Robotics Competitions Selected Results of an Evaluation Study of the World Robot Olympiad in Germany in 2019 1

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11th international conference on Robotics in Education (RiE)

作者： Poehner, Nicolai Hennecke, Martin Fleige, Markus Univ Wurzburg Emil Fischer Str 30 D-97074 Wurzburg Germany Tech Begeistert eV Franz Kissing Str 7 D-58706 Menden Germany

ISBN: (数字)9783030674113

ISBN: (纸本)9783030674106;9783030674113

Educational robotics competitions such as the World Robot Olympiad (WRO) are popular out-of-school learning settings for science, technology, Engineering and Mathematics (STEM) education, especially computer science (CS) education. the aim of this competition (alike many other initiatives) is to prepare students for a life in the digital age by fostering their 21(st) century skills and motivate them to choose a profession the field of STEM. Regardless, many initiatives fail to monitor their impact. In 2019, the organizers of the WRO conducted an impact evaluation study in collaboration with the CS education group of the University of Wurzburg to address this issue. In this article we present the results of this evaluation study regarding the students' learning of 21(st) century skills.

关键词： Educational robotics Competitions 21(st) century skills Evaluation Impact

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Estimating the Concrete Compressive Strength of Regression Model for Machine Learning 8th

Estimating the Concrete Compressive Strength of Regression M...

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

作者： Vaidya, Anagha Vaidya, Pranjal Sharma, Sarika MKSSS’s K. B. Joshi Institute of Information Technology Pune India AbbVie South San FranciscoCA United States Pune India

ISBN: (纸本)9783031709050

One of the key method in the machine learning process is regression analysis. there are several regression models available, and hence choosing the best regression model for a specific dataset might be challenging. this paper aims to conduct an experimental study for implementing eight regression models in context of machine learning. Eight regression models with various parameter values and regression measurement matrices are covered in this work. the experiment is conducted using several benchmarking datasets in order to determine the optimal regression model that is produced. Detailed comparative analysis is presented as the results. the experiment shows that the optimal regression model result depends more on the features selection and appropriate data imputing procedures, proper data cleaning than it does on the data type. the data cleaning process, which comprised appropriate methods for data imputation, feature scaling, feature extraction, and feature selection, determines the correctness of the regression model. Even though the data cleansing is done effectively, more research on data scaling strategies is necessary. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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