• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.1
• /
• pp.137-147
• /
• 2017

Wartime warship damage rate indicates how much damage of friend warships shall have occurred during naval battles accomplished under specific war operational plans. The wartime damage rate analysis provides the baseline of wartime resources requirements. If wartime damage rate is overestimated, the national finance will get to negative effects because of exceeding the budget for inventory, operation, and maintenance of resources. Otherwise, if wartime damage rate is underestimated, the national defense will lose in the war because of lack of critical resources. In this respect, it is important to estimate the wartime damage rate accurately and reasonably. This paper proposes a systematic procedure to estimate the wartime warship damage rate. The procedure consists of five steps; force analysis, operation plan analysis, input variable definition, simulation modeling, and output analysis. Since the combat simulation model is regarded as the main tool to estimate damage rate, the procedure is focused on the development of model and experiments using the model. A case study with virtual data is performed to demonstrate the effectiveness of the developed procedure.

• The Journal of the Korea Contents Association
• /
• v.18 no.8
• /
• pp.459-468
• /
• 2018

Cyberattacks on information systems used by applications related to weapon system and organizations associated with national defense put national security at risk. To reduce these threats, continuous efforts such as applying secure coding from the development stage or managing detected vulnerabilities systematically are being made. It also analyzes and detects vulnerabilities by using various analysis tools, eliminates at the development stage, and removes from developed applications. However, vulnerability analysis tools cause problems such as undetected, false positives, and overdetected, making accurate vulnerability detection difficult. In this paper, we propose a new vulnerability detection method to solve these problems, which can assess the risk of certain applications and create and manage secured application with this data.

• Journal of Positioning, Navigation, and Timing
• /
• v.6 no.1
• /
• pp.1-8
• /
• 2017

In this study, to design a multi-GNSS receiver using single RF front-end, the receiving performances for various frequency plans were evaluated. For the fair evaluation and comparison of different frequency plans, the same signal needs to be received at the same time. For this purpose, two synchronized RF front-ends were configured using USRP X310, and PC-based software was implemented so that the quality of the digital IF signal received at each front-end could be evaluated. The software consisted of USRP control, signal reception, signal acquisition, signal tracking, and C/N0 estimation function. Using the implemented software and USRP-based hardware, the signal receiving performances for various frequency plans, such as the signal attenuation status, overlapping of different systems, and the use of imaginary or real signal, were evaluated based on the C/N0 value. The results of the receiving performance measurement for the various frequency plans suggested in this study would be useful reference data for the design of a multi-GNSS receiver in the future.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.2
• /
• pp.317-320
• /
• 2006

Ships and their cargos have been managed safely by positioning report system. However, little attention has been paid to safety of crew's works with danger. The attempt that used PHS inboard was before by the present authors. However, the functions were just voice call and mail exchange. The data acquisition from the terminal by proper control was not possible. Thus the position of the terminal was not available. As for the cell phone of next generation, GPS receiver and wireless LAN are installed by manufacturers. Therefore, we propose a system which uses a cell-phone with GPS receiver on a ship in order to promote the safety of ship's crew. We checked the availability of cell-phone GPS receiver at thirty different points inboard. The positioning was not possible in the areas further than 4m from the window. Then, we proposed the system which follows the positions of the crews and confirms their safety inboard by using the VoIP (Voice over Internet Protocol) function by wireless LAN.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.22 no.2
• /
• pp.278-286
• /
• 2019

Conventional methods for selecting jamming techniques in electronic warfare are based on libraries in which a list of jamming techniques for radar signals is recorded. However, the choice of jamming techniques by the library is limited when modified signals are received. In this paper, we propose a method to predict the jamming technique for radar signals by using deep learning methods. Long short-term memory(LSTM) is a deep running method which is effective for learning the time dependent relationship in sequential data. In order to determine the optimal LSTM model structure for jamming technique prediction, we test the learning parameter values that should be selected, such as the number of LSTM layers, the number of fully-connected layers, optimization methods, the size of the mini batch, and dropout ratio. Experimental results demonstrate the competent performance of the LSTM model in predicting the jamming technique for radar signals.

• Journal of Positioning, Navigation, and Timing
• /
• v.7 no.4
• /
• pp.189-203
• /
• 2018

In this paper, a Software Defined Radio (SDR) architecture was designed and implemented for rapid prototyping of GNSS receiver. The proposed SDR can receive various GNSS and direct sequence spread spectrum (DSSS) signals without software modification by expanded input parameters containing information of the desired signal. Input parameters include code information, center frequency, message format, etc. To receive various signal by parameter controlling, a correlator, a data bit extractor and a receiver channel were designed considering the expanded input parameters. In navigation signal processing, pseudorange was measured based on Coordinated Universal Time (UTC) and appropriate navigation message decoder was selected by message format of input parameter so that receiver position can be calculated even if SDR is set up various GNSS combination. To validate the proposed SDR, the software was implemented using C++, CUDA C based on GPU and USRP. Experimentation has confirmed that changing the input parameters allows GPS, GLONASS, and BDS satellite signals to be received. The precision of the position from implemented SDR were measured below 5 m (Circular Error Probability; CEP) for all scenarios. This means that the implemented SDR operated normally. The implemented SDR will be used in a variety of fields by allowing prototyping of various GNSS signal only by changing input parameters.

• Journal of Distribution Science
• /
• v.19 no.2
• /
• pp.25-36
• /
• 2021

Purpose: This paper attempts to explore a Christian perspective on the process leading to growth after complex trauma caused by family violence experience. To achieve it, the article tackles the analysis of relationship between the inflictor father and victim, interpersonal relationship, and relationship with God in terms of growth after suffering from the trauma of family violence with a Christian perspective. Research design, data, and methodology: This study employed an in-depth interview as a methodology. Seven Christian adults who have experienced family violence in childhood are selected for the qualitative case study. 58 concepts, 24 low-level categories, and eight high-level categories are derived from each interview case. Results: The results of the case study show that the negative emotion caused by family violence during childhood is likely to lead to narcissistic rage. It is found that the reflection for posttraumatic growth starts with crying to God, simultaneously expressing pain and suffering. Conclusions: The interesting thing is that they are willing to forgive in the process of trauma therapy. It should be noted that the research results also demonstrate that relationship restoration entails the meaning reconstruction in the interpersonal relations.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.4
• /
• pp.203-210
• /
• 2019

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.1
• /
• pp.125-130
• /
• 2018

Linear discriminant analysis is a statistical analysis method that is generally used for dimensionality reduction of the feature vectors or for class classification. However, in the case of a data set that cannot be linearly separated, it is possible to make a linear separation by mapping a feature vector into a higher dimensional space using a nonlinear function. This method is called generalized discriminant analysis or kernel discriminant analysis. In this paper, we carried out target classification experiments with active sonar target signals available on the Internet using both liner discriminant and generalized discriminant analysis methods. Experimental results are analyzed and compared with discussions. For 104 test data, LDA method has shown correct recognition rate of 73.08%, however, GDA method achieved 95.19% that is also better than the conventional MLP or kernel-based SVM.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.2
• /
• pp.132-140
• /
• 2019

In this paper, we propose a classification method for radar signals depending on the type of threat by applying machine learning to parameter data of radar signals. Currently, the army uses a library of mapping relations between the parameters and the types of threat to recognize threat signals. This approach has certain limitations when classifying signals and recognizing new types of threat or types of threat that do not exist in the current libraries. In this paper, we propose an automatic radar signal classification method depending on the type of threat that uses only parameter data without a library. A convolutional neural network is used as the classifier and machine learning is applied to train the classifier. The proposed method does not use a library, and hence, can classify threat signals that are new or do not exist in the current library.