• The Journal of Korean Association of Computer Education
• /
• v.21 no.3
• /
• pp.11-20
• /
• 2018

One major change in the 2015 revised national curriculum is that computational thinking ability is becoming an essential competency for students. Computational thinking is divided into abstraction, automation, and creative convergence in the curriculum for secondary schools' Information subject. And, the curriculum contains problem solving and programming area. Among the components of computational thinking, data representation emphasizes the ability to structure data and information for problem solving of learners. Pre-service teachers of Information subject at secondary schools also learn how to structure information through diagramming. There are differences in the ability to structure diagrams among students, but the studies on learning methods that help students develop their structuring abilities have rarely been performed. The purpose of this paper is to analyze the differences of abstract thinking disposition and gender perspective among college students. As a result, female students had more concrete thinking disposition than male students. Also, there were gender differences according to the characteristics of diagrams. Differences in abstract thinking disposition also made a difference in structuring diagrams. It is useful for achieving the education purpose of improving computational thinking ability by finding out the differences in thinking tendency between males and females and finding the education method that can complement them.

• The Journal of Korean Association of Computer Education
• /
• v.18 no.2
• /
• pp.1-9
• /
• 2015

Excessive cognitive burdens caused by learning grammar should be reduced to cultivate high-level thinking skills in students through programing education. To this end, various educational programing languages have been developed. In recent years, block-based App Inventor that can used in real life have been introduced. This study intends to suggest an educational environment in which programing can be utilized as a leading problem solving tool by designing and producing an app that can be easily used by students in their real life. In particular, given the developmental phase of elementary school students, specific operational activities are important. For this reason, an App Inventor that can be proposed to enable dynamic interactions with the real world based on various smartphone sensors during the process of programing has significance as an educational programing language for elementary school students. In this regard, this study designed App Inventor programing education for elementary school students, which can be used in their daily life. The results of applying the education in fifth graders showed its positive effects on learning programing. LT collaborative learning where the students cooperated with each other, the theme of learning, which enables the utilization of various smartphone sensors in real life, and the app inventor may have generated and sustained the students' interest and attention.

• Journal of the Korean Society of Safety
• /
• v.11 no.2
• /
• pp.150-159
• /
• 1996

In this paper, an A-team(Asynchronous Team ) based approach for Reactive power and volage control considering static security assessment in a power system with infrastructural deficiencies is proposed. Reactive power and voltage control problem is the one of optimally establishing voltage level given several constraints such as reactive generation, voltage magnitude, line flow, and other switchable reactive power sources. It can be formulated as a mixed-integer linear programming(MILP) problem without deteriorating of solution accuracy to a certain extent. The security assessment is to estimate the relative robustness of the system in Its present state through the evaluation of data provided by security monitoring. Deterministic approach based on AC load flow calculations is adopted to assess the system security, especially voltage security. A security metric, as a standard of measurement for power system security, producting a set of discrete values rather than binary values, is employed. In order to analyze the above two problems, reactive power/voltage control problem and static security assessment problem, in an integrated fashion for real-time operations, a new organizational structure, called an A-team, is adopted. An A-team is an organization for agents which ale all autonomeus, work in parallel and communicate asynchronously, which is well-suited to the development of computer-based, multi-agent systems for operations. This A-team based approach, although it is still in the beginning stage, also has potential for handling other difficult power system problems.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.7
• /
• pp.377-392
• /
• 2005

A lot of studies to measure and analyze the system performance have been done in areas such as system modeling, performance measurement, monitoring, and performance prediction since the advent of a computer system. Studies on a framework to unify the performance related areas have rarely been performed although many studies in the various areas have been done, however. In the case of TMO(Time-Triggered Message-Triggered Object), a real-time programming model, it hardly provides tools and frameworks on the performance except a simple run-time monitor. So it is difficult to analyze the performance of the real-time system and the process based on TMO. Thus, in this paper, we propose a framework for the dynamic analysis of the real-time system based on TMO, TDAF(TMO based Dynamic Analysis Framework). TDAF treats all the processes for the performance measurement and analysis, and Provides developers with more reliable information systematically combining a load model, a performance model, and a reporting model. To support this framework, we propose a load model which is extended by applying TMO model to the conventional one, and we provide the load calculation algorithm to compute the load of TMO objects. Additionally, based on TMO model, we propose performance algorithms which implement the conceptual performance metrics, and we present the reporting model and algorithms which can derive the period and deadline for the real-time processes based on the load and performance value. In last, we perform some experiments to validate the reliability of the load calculation algorithm, and provide the experimental result.

• Journal of KIISE:Computing Practices and Letters
• /
• v.5 no.5
• /
• pp.583-594
• /
• 1999

With the advance of VLSI and network technologies, it has now become a common practice to deploy a various forms of distributed computing environments. A study shows that a lot of network-aware computers are in an idle state for considerable amount of time depending on the types of users and time frames of the day. If we can take the full advantage of those idle computers, we can obtain the enormous combined processing power without further costly investment. In this paper, we present a distributed batch-processing system, called the Java Distributed Batch-processing System (JDBS), which allows us to execute CPU-intensive, independent jobs across a pool of idle workstations on top of extant distributed computing environments. Since JDBS is implemented using a Java programming language, it not only extends the scope of machine types that can be joined to the pool, but makes it a lot easier to build an entire system. Besides, JDBS is scalable and fault-tolerant due to its multi-cluster organization and intelligent strategies. A graphical user interface is also provided to facilitate the registration and unregistration, job submission, and job monitoring.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.1
• /
• pp.219-226
• /
• 2010

Recently most parking control systems provide customers with various services, but most of the services are just the extension of parking spaces, automatic parking control system and so on. It is essential to use the satisfaction degree as the extent that customer are satisfied with parking control system to improve the quality of the system services and diversify the system services. The degree of satisfaction is different from customer to customer in same condition and can be represented as linguistic variables. In this paper, we present therefore a technique that quantify how much customer are satisfied with parking control system and fuzzy inference system architecture as a solution that can help us to make a efficient decision for these parking problems. In this architecture, inference engine using fuzzy logic compares context data with the rules in the fuzzy rule-based system, gets the sub-results, aggregates them and defuzzifies the aggregated result using MATLAB application programming to obtain crisp value. Fuzzy inference system architecture presented in this paper, can be used as a efficient method to analyze the satisfaction degree which is represented as fuzzy linguistic variables by human emotion. And it can be used to improve the satisfaction degree of not only parking system but also other service systems of various domains.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.5
• /
• pp.612-620
• /
• 2019

The increasing use of curved beams in buildings, vehicles, ships, and aircraft has results in considerable effort being directed toward developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic curved beams has been the subject of a large number of investigations. Solutions of the relevant differential equations have traditionally been obtained by the standard finite difference. These techniques require a great deal of computer time as the number of discrete nodes becomes relatively large under conditions of complex geometry and loading. One of the efficient procedures for the solution of partial differential equations is the method of differential quadrature. The differential quadrature method(DQM) has been applied to a large number of cases to overcome the difficulties of the complex algorithms of programming for the computer, as well as excessive use of storage due to conditions of complex geometry and loading. In this study, the in-plane extensional vibration for asymmetric curved beams with linearly varying cross-section is analyzed using the DQM. Fundamental frequency parameters are calculated for the member with various parameter ratios, boundary conditions, and opening angles. The results are compared with the result by other methods for cases in which they are available. According to the analysis of the solutions, the DQM, used only a limited number of grid points, gives results which agree very well with the exact ones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.360-363
• /
• 2022

According to the 2018 Kaggle ML & DS Survey, among the proportions of frameworks for machine learning and data science, TensorFlow and Keras each account for 41.82%. It was found to be 34.09%, and in the case of development programming, it is confirmed that about 82% use Python. A significant number of machine learning and deep learning structures utilize the Keras framework and Python, but in the case of Python, distribution and execution are limited to the Python script environment due to the script language, so it is judged that it is difficult to operate in various environments. This paper implemented a machine learning and deep learning system using C# and Keras running in Visual Studio 2019. Using the Mnist dataset, 100 tests were performed in Python 3.8,2 and C# .NET 5.0 environments, and the minimum time for Python was 1.86 seconds, the maximum time was 2.38 seconds, and the average time was 1.98 seconds. Time 1.78 seconds, maximum time 2.11 seconds, average time 1.85 seconds, total time 37.02 seconds. As a result of the experiment, the performance of C# improved by about 6% compared to Python, and it is expected that the utilization will be high because executable files can be extracted.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.273-285
• /
• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.45-52
• /
• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.