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A Study of Enhancing Computational Thinking Skills through STEAM Robotics Activities

Journal of Physics: Conference Series 2021年第1期1835卷

作者： Muneeroh Phadung Atcharaporn Yokkhun Sulaiman Persoh Computer Education Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand Information Technology Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand Computer Science Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala 95000 Thailand

STEAM robotics activities are designed to be an enhancement on students' computational thinking skills, which are claimed to be essential for the 21st century. The aims of this study were to examine the learning outcomes of secondary students' computational thinking skills through the use of STEAM robotics activities, and to investigate the students' satisfaction after the implementation of STEAM robotics activities. A quasi-experimental research design was deployed in this study. The research participants were 37 eleventh-grade students of Private Islamic Schools in Yala province, Thailand. A quiz with pre- and post-test and satisfaction questionnaires were employed as data. Descriptive statistics – including mean, standard deviation and a pair sample t-test – was used to analyse the collected data. The findings were that students' learning outcomes indicated a significant improvement in their computational skills after the use of STEAM robotics activities as compared with before, with the statistical level of significance of 0.05. In response to the second research question, the overall satisfaction of the students after the use of such STEAM robotics activities was high (mean=4.01; SD=0.54).

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On Solving a class of stochastic multiobjective integer linear programming problems with Interactive Based Approach 1

On Solving a class of stochastic multiobjective integer line...

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1st International Conference on computer Science and Applied Mathematic, ICCSAM 2018

作者： Suparni Mawengkang, Herman Sitompul, Opim Salim Suwilo, Saib Mathematics Doctorate Program University of Sumatera Utara Medan Indonesia Department of Mathematics University of Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia

Decision problems of stochastic or probabilistic optimization arise when certain coefficient of an optimization model are not fixed or known but are instead, to some extent, stochastic(or random or probabilistic) quantities. This paper focused on multiobjective stochastic optimization. We propose a method for solving a multiobjective chance constraints integer programming problem based on interactive approach. We assume that there is randomness in the right-hand sides of the constraints only and that the random variables are normally distributed. Some examples are presented. © Published under licence by IOP Publishing Ltd.

关键词： Integer programming

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Analysis of the passive fragments influence in broadband signals with manipulated information entropy on the data transmission reliability

Analysis of the passive fragments influence in broadband sig...

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2019 IEEE International Scientific-Practical Conference: Problems of Infocommunications Science and technology, PIC S and T 2019

作者： Melnychuk, Stepan Manuliak, Iryna National Technical University of Oil and Gas Computer Systems and Networks Department of Ivano-Frankivsk Ivano-Frankivsk Ukraine Engineering of King Danylo University Department of Information Technology and Program Ivano-Frankivsk Ukraine

ISBN: (纸本)9781728141848

Current methods of digitally processing communication signals, which are distorted in the computer systems communication channels, are often based on the use of amplitude, phase and spectral characteristics. Correlation methods are also used to ensure immunity. A common disadvantage of these methods is the need for significant computational cost. One of the partial solutions to the described problem may be to use the signals probabilistic characteristics, in particular information entropy. This approach is based on the representation of digital message bits to the corresponding fragments of broadband signals with manipulated information entropy. In fact, signals are formed on the basis of random processes with normal distribution of possible states. The use of passive fragments in such signals can reduce the energy cost of data transmission. When passing through a communication channel, passive fragments are filled with their own channel noise. As a result, the channel's own noise extends the number of possible signal amplitude states and can be used to improve the resolution. According to the results of studies, the dependence of the probability of distortion of the information message binary symbol on the normalized signal/noise ratio is obtained. It is shown that the use of passive fragments improves noise immunity by 3-4 dB within the normalized signal/noise ratio at the input from-5 dB to 14 dB. However, at 14 dB or more, noise immunity worsens. Thus, the main scope of the proposed method can be problematic channels with low signal/noise ratio. © 2019 IEEE.

关键词： Correlation methods

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Big Data Governance for Building A Smart Cities 10

Big Data Governance for Building A Smart Cities

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10th International Conference on ICT for Smart Society, ICISS 2019

作者： Zulkarnain, Novan Kosala, Raymond Ranti, Benny Supangkat, Suhono Harso Bina Nusantara University Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Jakarta11480 Indonesia Universitas Indonesia Computer Science Department Depok16424 Indonesia Institute of Technology Bandung School of Electrical and Informatics Engineering Bandung40132 Indonesia

ISBN: (纸本)9781728148809

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data. © 2019 IEEE.

关键词： Big data

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On Performance Prediction of Big Data Transfer in High-performance Networks

On Performance Prediction of Big Data Transfer in High-perfo...

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IEEE International Conference on Communications (ICC)

作者： Wuji Liu Daqing Yun Chase Q. Wu Nageswara S.V. Rao Aiqin Hou Wei Shen Department of Computer Science New Jersey Institute of Technology Newark NJ USA Computer and Information Sciences Program Harrisburg University Harrisburg PA USA Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak Ridge TN USA School of Information Science and Technology Northwest University Xi’an Shaanxi China School of Informatics Science and Technology Zhejiang Sci-Tech University Hangzhou Zhejiang China

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

关键词： Data transfer Big Data Throughput Bandwidth Measurement Predictive models Protocols

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QoSTCP: Provide Consistent Rate Guarantees to TCP flows in Software Defined Networks

QoSTCP: Provide Consistent Rate Guarantees to TCP flows in S...

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IEEE International Conference on Communications (ICC)

作者： Chien Chen Hoa-Chuan Fang Muhammad Shahid Iqbal Department of Computer Science and Information Technology Service Center National Chiao Tung University Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan EECS International Graduate Program National Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

The Quality of Service (QoS) for applications is becoming increasingly important with the expansion of the Internet. A software-defined network offers flexibility and scalability in the use of network resources, like a meter table, which enables OpenFlow switches to measure flow rates and can be used to realize the rate limiter QoS. However, this drops packets when the flow-rate is over the limit, making the TCP congestion window reduce and grow periodically. The QoS of the upper layer using TCP will suffer regularly because of packet losses and bandwidth oscillation. Therefore, we propose a QoSTCP protocol using the meter and Rate Limiting Notification (RLN) to improve the QoS of TCP in SDN. The meter in the switch measures the flow rate to mark RLNs in the packets when the flow rate exceeds the threshold. A QoSTCP sender gets marking information to reduce the window size proportional to the marking packet ratio to avoid packet drop. We also provide a theoretical analysis to estimate when to mark packets at specific thresholds under two kinds of bandwidth demands in QoS, maximum and average rate. In order to verify QoSTCP performance, we implement a Two Rate Three Color Marker (trTCM) meter to measure the flow rate and mark RLNs using a programming protocol-independent Packet Processors (P4) switch. To simplify our implementation, the existing Explicit Congestion Notification (ECN) and Data Center TCP (DCTCP) are modified to emulate QoSTCP behavior. Experiment results confirm not only that QoSTCP provides a consistent rate guarantee by avoiding packet drop but also that it matches our theoretical analytical results.

关键词： Quality of service Bandwidth Meters Oscillators Protocols Data centers Control systems

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Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicle Communication for Local File Sharing 15th

Reliable Collaborative Semi-infrastructure Vehicle-to-Vehicl...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Mokhtar, Bassem Azab, Mohamed Fathalla, Efat Ghourab, Esraa M. Magdy, Mohamed Eltoweissy, Mohamed Electrical Engineering Department Alexandria University Alexandria Egypt Computer Engineering Program School of Engineering and Applied Sciences Nile University Giza Egypt Computer and Information Sciences Virginia Military Institute LexingtonVA24450 United States Department of Electrical and Computer Engineering Old Dominion University NorfolkVA United States College of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Alexandria Egypt

ISBN: (纸本)9783030301453

Recently, Vehicular Cloud Communication (VCC) has been gaining momentum targeting intelligent and efficient data transmission. VCC is a type of mobile ad-hoc network comprising heterogeneous vehicles sharing their resources to perform collaborative activities. In this paper, we propose a new semi-infrastructure file-browsing in order to provide Network as a service (NaaS) enabling internet-independent browsing. In our scenario, a central management platform plays the role of controlling and managing the selection of relaying vehicles supporting the source to destination file transmission procedure. Nagel-Schreckenberg rules for traffic cellular automata (CA) are used as the basis for our scenario simulation. Nagel-Schreckenberg rules simulate the behavior of a group of hypothetical vehicles moving across a highway. We study the reliability and efficiency of file transfer in such settings. Simulation results show that the number of selected relays required to establish the network highly impacts the probability of successfully sending the requested files. In addition, the distances between the selected relays influence the network throughput and the probability of network failure. Moreover, the density of relays strongly affects the overall delay that occurs due to the continuous re-transmission of the selected files among different hops. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Vehicle to vehicle communications

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Comparison analysis of weighting using fuzzy logic and centroid order rank (ROC) on simple Additive Weighting (SAW) method

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AIP Conference Proceedings 2023年第1期2601卷

作者： Alfin Ghazali Poltak Sihombing Muhammad Zarlis Informatics Postgraduate Program Universitas Sumatera Utara Jl. Universitas No. 9A Medan 20155 Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Jl. Universitas No. 9A Kampus USU Padang Bulan Medan 20155 Indonesia

The simple Additive Weighting method is one of the methods of Decision Support System which is often referred to as weighted summation method. But the weight value on this method is not officially the calculation used. Therefore, usually, several researchers combine this method with other methods to be more precise and accurate in supporting the decision. In this study, the authors compared the results of the SAW method decisions between weighting based on the Fuzzy Logic method and weighting based on the Rank Order Centroid (ROC) method. The case studied was the amount of student satisfaction with learning outcomes during the Covid-19 pandemic. The result is the number of students who expressed satisfaction with learning during the Covid-19 pandemic as many as 26 students for weighting Fuzzy Logic method and 23 students for weighting Rank Order Centroid method (ROC).

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IDeBlurInfo: An Assessment and Evaluation Study of Image Deblurring Techniques 4

IDeBlurInfo: An Assessment and Evaluation Study of Image Deb...

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4th IEEE International Conference on technology, Informatics, Management, Engineering and Environment, TIME-E 2019

作者： Pagaduan, Roxanne A. Aragon, Ma. Christina R. Medina, Ruji P. Technological Institute of the Philippines Information Technology Department Quezon City Philippines Technological Institute of the Philippines Computer Science Department Quezon City Philippines Technological Institute of the Philippines Graduate Program Quezon City Philippines

ISBN: (纸本)9781728131344

Quality of images used in a variety of systems contributes to the success of discovering beneficial details used in different fields of computing. The quality of the image plays a vital role in increasing the success rate of image recognition and related fields. Image quality can be degraded due to distortion, imperfection during image capture, inappropriate light balancing, and exposure to name a few. Various deblurring techniques were introduced to address blurred issues, transforming an image to lesser imperfections, successfully reading and/or identifying available details on it. This study aims to identify, define, and evaluate deblurring techniques in a way that demonstrates comprehension of the tradeoffs involved in the design. Significantly, the study compares various techniques that can be used to recover hidden details in the presence of image noise. The MA TLAB was used as a tool for testing and evaluating the deblurring techniques. PSNR, MSE, and computational time were used to compare each identified deblurring techniques. Based on the comparative performance results of each technique, in terms of accuracy measure, Lucy-Richardson got the highest PSNR ratio of 25.8312 that leads the best result while wiener filter got the lowest PSNR ratio of 21.3012. While, based on the MSE results, Wiener Filter got a higher rate of 0.0074;while blind deconvolution and Lucy-Richardson got the lowest value of 0.0026. And in terms of execution time, Wiener Filter performs the fastest computational time. © 2019 IEEE.

关键词： MATLAB

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Prediction of traffic congestion based on time series dataset number of vehicles using neural network algorithm

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AIP Conference Proceedings 2024年第1期2982卷

作者： Prasetyo Wibowo Yunanto Rahmat Gernowo Oky Dwi Nurhayati Doctoral Program of Information System Diponegoro University Jl. Imam Bardjo SH No.5 Semarang Indonesia Information Systems and Technology Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta Indonesia Department of Physics Diponegoro University Jl. Prof. H. Soedarto Semarang Indonesia Computer Engineering Department Diponegoro University Jl. Prof. H. Soedarto Semarang Indonesia

The increasing number of vehicles that was not accompanied by an adequate road infrastructure readiness causes traffic jams. Traffic jams often occur repeatedly every day, especially at certain times, such as when people are going to and from work. The same traffic jams can also occur at the beginning or the end of the week; this usually repeats every week. As a result, if the congestion dataset is known, the repeating traffic congestion for daily and weekly congestion can be anticipated. In this study, traffic congestion predictions are modeled using the Neural Network Algorithm based on traffic congestion data collected within 24 hours for one to two weeks. The parameters used in optimizing Neural Network performance are learning rate, momentum, and epochs (training cycles). Based on these experiments, the Neural Network Algorithm successfully modeled traffic density patterns which are recurring congestion patterns, with quite good results.

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