• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.5
• /
• pp.1087-1097
• /
• 2017

As the penetration rate of smartphones increases, the number of malicious codes targeting smartphones is increasing. I 360 Security 's smartphone malware statistics show that malicious code increased 437 percent in the first quarter of 2016 compared to the fourth quarter of 2015. In particular, malicious applications, which are the main means of distributing malicious code on smartphones, are aimed at leakage of user information, data destruction, and money withdrawal. Often, it is operated by an API, which is an interface that allows you to control the functions provided by the operating system or programming language. In this paper, we propose a mechanism to detect malicious application based on the similarity of API pattern in normal application and malicious application by learning pattern of API in application derived from static analysis. In addition, we show a technique for improving the detection rate and detection rate for each label derived by using the corresponding mechanism for the sample data. In particular, in the case of the proposed mechanism, it is possible to detect when the API pattern of the new malicious application is similar to the previously learned patterns at a certain level. Future researches of various features of the application and applying them to this mechanism are expected to be able to detect new malicious applications of anti-malware system.

• 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.

• Korean Chemical Engineering Research
• /
• v.57 no.5
• /
• pp.628-636
• /
• 2019

In various industrial processes, piping serves as a link between unit processes and is an essential installation for internal flow. Therefore, the optimum design of the piping system is very important in terms of safety and cost, which requires the estimation of the pressure drop, flow rate, pipe size, etc. in the piping system. In this study, we developed a software that determines pressure drop, flow rate, and pipe size when any two of these design variables are known. We categorized the flows into single phase, homogeneous two phase, and separated two phase flows, and applied suitable calculation models accordingly. We also constructed a system library for the calculation of the pipe material, relative roughness, fluid property, and friction coefficients to minimize user input. We further created a costing library according to the piping material for the calculation of the investment cost of the pipe per unit length. We implemented all these functions in an integrated environment using a graphical user interface for user convenience, and C # programming language. Finally, we verified the accuracy of the software using literature data and examples from an industrial process with obtained deviations of 1% and 8.8% for the single phase and two-phase models.

• Communications of Mathematical Education
• /
• v.33 no.1
• /
• pp.1-19
• /
• 2019

This study deals with the case of student-centered discrete mathematics class with cyber lab. First, we provided lecture notes and cyber labs we developed. In particular, discrete mathematics is a course that covers the principles of algorithms. The purpose of this study is to provide students with basic mathematics, aiming to actively participate in the learning process, to improve their abilities and to reach the ultimate goal of student success with confidence. Second, based on interactions, students were able to prepare for the lectures, review, question, answer, and discussion through an usual learning management system of the school. Third, all the students generated materials through one semester, which were reported, submitted, presented and evaluated. It was possible to improve the learning effectiveness through the discussions and implementation of using some easy open source programming language and codes. Our discrete math laboratory could be practiced without any special knowledge of coding. These lecture models allow students to develop critical thinking skills while describing and presenting their learning and problem-solving processes. We share our experience and our materials including lecture note and cyber lab as well as a possible model of student-centered mathematics class that does not give too much of work load for instructors. This study shares a model that demonstrates that any professor will be able to have an individualized, customized, and creative discrete education without spending much of extra time and assistant, unlike previous research.

• Journal of the Korean Society for Library and Information Science
• /
• v.55 no.1
• /
• pp.5-36
• /
• 2021

This study attempted to present the direction of development of the curriculum of Library & Information Science by investigating and analyzing the current status of the curriculum of Library & Information Science in Korea and the perception of the necessity of each major subject. To this end, the curriculum of the Department of Library and Information Sciences nationwide was thoroughly investigated. Based on the subjects, a questionnaire survey was conducted for all professors of the Department of Library and Information Science on the degree of consent for required and elective subjects. As a result, first, the total number of courses opened in the Department of Library and Information Science has recently decreased. It was confirmed that the proportion of the required subjects and basic subjects decreased, and the proportion of elective subjects increased. Second, it was found that the importance and weight of informatics are constantly increasing, and there is a high demand for new subjects such as big data, programming, and data analysis. Third, the proportion of library management in all subjects is decreasing, but the necessity of detailed subjects is highly recognized. Fourth, it was confirmed that the proportion of bibliography was gradually decreasing. Fifth, although records management was not a required major subject, its weight increased as an elective subject, while language subjects showed almost no awareness of the necessity.

• KNOM Review
• /
• v.24 no.1
• /
• pp.29-37
• /
• 2021

With the spread of the Internet, users can easily receive various services and exchange information through the web. There are several requirements for building a web system, and it must be developed using a programming language or platform for user purposes. Residual material information refers to information on medicines and pesticides added to food, and residual material standards are used to measure the level of residues in food produced by companies and farmers to determine whether those levels meet domestic or international standards. Currently, the Ministry of Food and Drug Safety provides residual acceptance standards for food additives, including food, pesticides and animal medicines, in the form of documents, which must be serviced smoothly and conveniently by users through the establishment of a web system. It must also meet a variety of requirements, including user accessibility, such as scalability and compatibility. This paper proposes react-based residual material information web system that allows users to access more conveniently and receive residual material information smoothly. We measured the speed for the three inportant functions of information provision and compared them with existing residual material information web systems and qualitatively evaluated the seven essential requirements: scalability, compatibility, and accessibility.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.187-192
• /
• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.31-31
• /
• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.365-368
• /
• 2021

In this study, a plastic bottle recycling bin system that utilizes an infrared sensor was implemented. The proposed system consists of a recognition unit, a control unit, an alarm unit, and a driving unit. The recognition unit detects the plastic bottle, measures the distance between the plastic bottle and the infrared sensor, extracts the value of the bottle, compares the extracted value with a standard range, and then transmits the control value to the control unit if the extracted value of the bottle is outside the standard range. In this case, the result of the presence or absence of a brand label or bottle cap is transmitted to the controller. The control unit opens the entrance of the recycling bin or alerts the alarm unit according to the result value transmitted from the sensor unit. In order to implement the proposed system, the recognition unit was implemented with an infrared sensor, and the control unit was made with an Arduino IDE controller, based on the C programming language. Additionally, the recognition unit and the control unit are able to communicate using analog signals. The proposed system accurately judges the presence or absence of a brand label and bottle cap of plastic bottles according to a predetermined algorithm. It then blocks the entrance of the recycling bin when a brand label or bottle cap is still attached. As the amount of waste discharged per person is relatively high and the majority of such waste is incinerated rather than recycled, the system proposed in this study is expected to increase the recycling rate of plastic bottles.

• 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.