• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.41-49
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• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.

• Journal of Mushroom
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• v.16 no.4
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• pp.304-310
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• 2018

Beta glucan was purified from Phellinus baumii and tested for its effect on the group performance of ants, a principal model of eusociality and of superorganisms. Japanese carpenter ants (Camponotus japonicus) were reared on diets containing beta glucans to characterize their effects on eusociality. Culturing structures for ants were assembled by implanting autoclaved soil into polyethylene terephthalate bottles. Three different eusocial strength indices were used to study the effect of beta glucan extract (BGE) on eusocial activities - the number of residence chambers, cooperative defense index (CDI), and group size and composition. Control, low- BGE, and high-BGE diets were prepared with the following three levels of BGE supplements in sucrose powder: 0, 20, and 50% (g/g). More residence chambers were observed in the BGE-fed groups than in the control. The CDI against a foreign queen ant was calculated according to the time taken to subdue the foreign queen. The high-BGE group took less time to complete their defense formation than the other groups. Differences were evident between control and BGE-fed groups in the total numbers of ants and eggs. The BGE-fed groups showed a significant increase in both the number of workers and the number of eggs. When fed with BGE, ants responded positively for all three eusocial strength indices. These results show that BGE exerts beneficial effects on the eusociality of ants as a superorganism.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.47-60
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• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.17-27
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• 2022

A certain level of stability margin airworthiness criteria should be met to secure robustness against uncertainties between the real plant and the model in a flight control system design. The U.S. Department of Defense (DoD) specification of MIL-F-9490D and airworthiness certification standard of MIL-HDBK-516B uses gain and phase margin criteria of flight control system. However, the same stability margin criteria is applied at all development phases without considering the design maturity of each development phase of the aircraft. Ultimately, a problem arises when the aircraft operation envelope is excessively restricted. This paper proposes the relation of handling qualities and stability margin, and presents re-established stability margin criteria as a development phases and verification methods. The results of the research study are considered to contribute to the verification of the stability margin criteria more flexibly and effectively by applying the method to not only the currently manned developing aircrafts but also the unmanned vehicle to be developed in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.178-186
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• 2020

In the domain of Korean weapon system development, issues about software reliability have become crucial factors when developing a weapon system. There is a process required for weapon system software development and management that includes certain activities required to improve the reliability of software. However, these activities are biased toward static and dynamic analyses of source code and do not include activities necessarily required by the international standard. IEEE std. 1633-2016 defines a process for software reliability engineering and describes software reliability estimation as an essential activity in the process. Software reliability estimation means that collecting defective data during the test and estimating software reliability by using the statistical model. Based on the estimated model, developers could estimate the failure rate and make comparisons with the objective failure rate to determine termination of the test. In this study, we collected defective data and applied reliability estimation models to analyze software reliability in the development of a weapon system. To achieve objective software reliability, we continuously tested our software and quantitatively calculated software reliability. Through the research, we hope that efforts to include activities described by the international standard will be carried out in the domain of Korean weapon system development.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.37-44
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• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.35-48
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• 2018

The study of air defense against North Korean tactical ballistic missiles (TBM) should consider the rapidly changing battlefield environment. The study for target re-designation for intercept missiles enables effective operation of friendly defensive assets as well as responses to dynamic battlefield. The researches that have been conducted so far do not represent real-time dynamic battlefield situation because the hit probability for the TBM, which plays an important role in the decision making process, is fixed. Therefore, this study proposes a target re-designation algorithm that makes decision based on hit probability which considers real-time field environment. The proposed method contains a trajectory prediction model that predicts the expected trajectory of the TBM from the current position and velocity information by using random forest and moving window. The predicted hit probability can be calculated through the trajectory prediction model and the simulator of the intercept missile, and the calculated hit probability becomes the decision criterion of the target re-designation algorithm for the missile. In the experiment, the validity of the methodology used in the TBM trajectory prediction model was verified and the superiority of using the hit probability through the proposed model in the target re-designation decision making process was validated.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.47-53
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• 2017

A boundary layer integral combined with a 1-D isentropic core flow model has been successfully used to determine heat transfer rate on the surface of a supersonic nozzle. However its accuracy is affected by the core flow condition which is used as a boundary condition for the integral calculation. Because flow behavior near a nozzle throat deviates from 1-D isentropic condition due to 2-D flow turning and interaction between core flow and boundary layer, accuracy of heat transfer calculation decreases at a nozzle throat. Therefore, CFD is adopted to deduce improved core flow condition and increase accuracy of boundary layer integral at nozzle throat in this research. Euler model and SST $k-{\omega}$ model is solved by CFD code and used as a boundary condition for boundary layer integral. Developed code is tested in the supersonic nozzle from the previous research and improvement in accuracy is observed, especially at nozzle throat and diverging section of the nozzle. Error between experimental result and calculation result reduced by 16% when a calculation is made based on the SST $k-{\omega}$ model. Method developed in this research is expected to be used in thermal design of the rocket nozzle.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.491-505
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• 2020

The purpose of this study is to develop an evaluation index that can assess the Army training program of Green Camp. The result of the evaluation index phased-developed with the CIPP model is summarized below. First, the literature review with documents relevant to program evaluation, Green Camp field research, and expert discussions were used to select factors considered for evaluation and develop a preliminary evaluation area and item for the four areas within the CIPP evaluation model. Second, an initial survey targeting Green Camp and soldiers in the Capital Defense Command examined the preliminary reliability·validity, and the Focused Group discussions were used to supplement the evaluation index. Third, secondary surveys were conducted in four battalions in Gangwon-do and third surveys targeted officers from twelve different corps and personnels related to the Green Camp which verified descriptive statistics analysis, exploratory factor analysis, and correlation analysis in version SPSS 24. Fourth, with the validation verification procedure, 16 evaluation area and 36 evaluation index was confirmed. Fifth, the 36 evaluation index developed was subdivided into 57 indexes and the Delphi method was applied through the policy expert to formulate 43 generalized indexes. The significance of this phased research approach was considered for the institutionalization of the usage of scientific evaluation(index) and development in policy process.