• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.107-116
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• 2019

The purpose of this study is to develop a Python sorting algorithm training program based on execution time as an educational method for enhancing the logical thinking power of elementary students and then to verify the effect. The education program was developed based on the results of the pre-demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed educational program, I teached 25 students of the volunteer sample of the elementary school education donation program conducted at ${\bigcirc}{\bigcirc}$ University conducted 42 hours, 7 days. The results of the pre-test and post-test were analyzed using the 'Group Assessment of Logical Thinking(GALT)' developed by the Korea Educational Development Institute. The results showed that the Python sorting algorithm training centered on execution time was effective in improving the logical thinking ability of elementary school students.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.545-558
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• 2021

Recently, Confidential computing plays an important role in next-generation cloud technology along with the development of trusted execution environments(TEEs), as it guarantees the trustworthiness of applications despite of untrusted nature of the cloud. Both academia and industry have actively proposed commercialized confidential computing solutions based on Intel SGX technology. However, the lack of clear criteria makes developers difficult to select a proper confidential computing framework among the possible options when implementing TEE-based cloud applications. In this paper, we derive baseline metrics that help to clarify the pros and cons of each framework through in-depth comparative analysis against existing confidential computing frameworks. Based on the comparison, we propose criteria to application developers for effectively selecting an appropriate confidential computing framework according to the design purpose of TEE-based applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.347-363
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• 2024

As the number of cyberattacks against the National Critical Information Infrastructure (NCII) is steadily increasing, many countries are strengthening the protection of National Critical Information Infrastructure (NCII) through the enactment and revision of related policies and legal systems. Therefore, this paper selects countries such as the United States, the United Kingdom, Japan, Germany, and Australia, which have established National Critical Information Infrastructure (NCII) protection systems, and compares and analyzes the promotion system of each country's National Critical Information Infrastructure (NCII) protection policy. This paper compares the National Critical Information Infrastructure (NCII) protection system of each country with the cybersecurity system and analyzes the promotion structure. Based on the policy model theory, which is a modification of Allison's theory and Nakamura & Smallwood's theory, this paper analyzes the model of each country's promotion system from the perspective of policy-making and policy-execution. The United States, Japan, Germany, and Australia's policy-promotion model is a system-strengthening model in which both policy-making and policy-execution are organized around the protection of the National Critical Information Infrastructure (NCII), while the United Kingdom and South Korea's policy-promotion model is an execution-oriented model that focuses more on policy-execution.

• Korean Security Journal
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• no.38
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• pp.7-32
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• 2014

This study is aimed to analyze problems of police budgetary execution and to suggest better ways for establishing effective budget implementation as well as legitimacy of securing budget in the field of police work. For this purpose, this paper analyzed the annual reports on police budgetary execution, from 2009 to 2012, conducted by National Assembly Budget Office. In result, most parts of the police budgetary execution were not satisfied with the audit standard, and especially in terms of management of budgetary execution, it showed 40% in inappropriateness. In addition, excessive and underestimate appropriation in the police budgetary execution, which happened frequently in other offices, was recorded on the second place. 10% of the amount of budget was executed for ordinance violence. Given results analyzed from each division, Transportation Division occupied 40% of the amount of related problems and all of types in the field did not meet the audit standard, thus it is required to manage budgetary execution effectively. In terms of Public Safety Division, the problem was related to budgetary allocation prior to execution, such as overlap in other works, excessive and underestimate appropriation, and inappropriate business plans. Director General for Planning and Coordination did not meet the standard of law system maintenance, Given the light of the result of analyzing programs, traffic safety and securing communication was the most problematic and support for police administration, crime prevention and protecting the disadvantaged, educating professional police officers, and establishment of policing infrastructure were required to be reformed in sequence. In order to resolve these problems, it is demanded to check budgetary execution and the process in business plans on a regular basis. Additionally, in case of using budget in inappropriate parts, tough penality including reduction of budget in related to the local police should be implemented to increase the importance of budgetary execution. Moreover, because of the fact that a part of problem of budgetary execution was originally caused by the budgetary allocation, it is advised to allocate police budget using the budget proposal of National Finance Act and Ministry of Strategy and Finance.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.37-43
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• 2017

A registry is a hierarchy database which is designed to store information necessary for operating system and application programs in Windows operating system, and it is involved in all activities such as booting, logging, service execution, application execution, and user behavior. Digital forensic is widely used. In recent years, malicious codes have penetrated into systems in a way that is not recognized by the user, and valuable information is leaked or stolen, causing financial damages. Therefore, this study proposes a method to detect malicious code by using a shareware application without using expensive digital forensic program, so as to analysis hacking methods and prevent hacking damage in advance.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.171-172
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• 2018

Performance measurement and management in the construction industry has traditionally been regarded as the major factor for successful business execution. In addition, there is emphasis on the function of performance measurement and management that can early warn potential risks and poor performance in project execution environment changes. Previous studies have made various attempts to measure the quantitative performance of construction projects, and the research to derive the link between the results and the issue that can meet the future needs is expected to provide valuable information. The purpose of this study is to analyze the research trends based on the keywords presented in previous studies on the performance measurement and management of construction projects. Considering that the results presented in the existing literature can be an indicator of the evolution of the sector before it is applied to industry, the result of this study is expected to be used as a basic data to support the establishment of research direction in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.91-101
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• 2014

In this study, we presented a timing verification method for a passenger car diesel engine management system (EMS) using measurement-based worst-case execution time (WCET) analysis. In order to cope with AUTOSAR-compliant software architecture, a development process model is proposed. In the process model, a runnable is regarded as a test unit and its temporal behavior (i.e. maximum observed execution time, MOET) is obtained along with on-target functionality evaluation results during online unit test. Furthermore, a cost-effective framework for online unit test is proposed. Because the runtime environment layer and the standard calibration environment are utilized to implement test interface, additional resource consumption of the target processor is minimized. Using the proposed development process model and unit test framework, the MOETs of 86 runnables for diesel EMS are obtained with 213 unit test cases. Using the obtained MOETs of runnables, the WCETs of tasks are estimated and the schedulability is evaluated. From the schedulability analysis results, the problems of the initially designed schedule table is recognized and it is fixed by redesigning of the runnable mapping and task offset. Through the various test scenarios, the proposed method is validated.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.221-239
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• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.