• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.27-34
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• 2019

This paper presents a chamber pressure model development of K2 rifle by applying Gaussian mixture model. In order to materialize a real recoil force of a virtual reality shooting rifle in military combat training, the chamber pressure which is one of major components of the recoil force needs to be investigated and modeled. Over 200,000 data of the chamber pressure were collected by implementing live fire experiments with both K100 and M193 of 5.56 mm bullets. Gaussian mixture method was also applied to create a mathematical model that satisfies nonlinear, asymmetry, and deviations of the chamber pressure which is caused by irregular characteristics of propellant combustion. In addition, Polynomial and Fourier Regression were used for comparison of results, and the sum of squared errors, the coefficient of determination and root-mean-square errors were analyzed for performance measurement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.217-228
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• 2020

The ROK Army must detect the enemy's location and the type of artillery weapon to respond effectively at wartime. This paper proposes a radar positioning model by applying a scenario-based robust optimization method i.e., binary integer programming. The model consists of the different types of radar, its available quantity and specification. Input data is a combination of target, weapon types and enemy position in enemy's attack scenarios. In this scenario, as the components increase by one unit, the total number increases exponentially, making it difficult to use all scenarios. Therefore, we use partial scenarios to see if they produce results similar to those of the total scenario, and then apply them to case studies. The goal of this model is to deploy an artillery locating radar that maximizes the detection probability at a given candidate site, based on the probability of all possible attack scenarios at an expected enemy artillery position. The results of various experiments including real case study show the appropriateness and practicality of our proposed model. In addition, the validity of the model is reviewed by comparing the case study results with the detection rate of the currently available radar deployment positions of Corps. We are looking forward to enhance Korea Artillery force combat capability through our research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.98-104
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• 2016

With the development of modern science and technology, weapon systems such as tanks, submarines, combat planes, radar are also dramatically advanced. Among these weapon systems, the ballistic missile, one of the asymmetric forces, could be considered as a very economical means to attack the core facilities of the other country in order to achieve the strategic goals of the country during the war. Because of the current ballistic missile threat from the North Korea, establishing a missile defense (MD) system becomes one of the major national defense issues. This study focused on the optimization of air defense artillery units' deployment for effective ballistic missile defense. To optimize the deployment of the units, firstly this study examined the possibility of defense, according to the presence of orbital coordinates of ballistic missiles in the limited defense range of air defense artillery units. This constraint on the defense range is originated from the characteristics of anti-ballistic missiles (ABMs) such as PATRIOT. Secondly, this study proposed the optimized mathematical model considering the total covering problem of binary integer programming, as an optimal deployment of air defense artillery units for defending every core defense facility with the least number of such units. Finally, numerical experiments were conducted to show how the suggested approach works. Assuming the current state of the Korean peninsula, the study arbitrarily set ballistic missile bases of the North Korea and core defense facilities of the South Korea. Under these conditions, numerical experiments were executed by utilizing MATLAB R2010a of the MathWorks, Inc.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.6
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• pp.322-330
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• 2020

This study deals with underwater explosion (UNDEX) characteristics of various non-explosive underwater shock sources for the development of non-explosive underwater shock testing devices. UNDEX can neutralize ships' structure and the equipment onboard causing serious damage to combat and survivability. The shock proof performance of naval ships has been for a long time studied through simulations, but full-scale Live Fire Test and Evaluation (LFT&E) using real explosives have been limited due to the high risk and cost. For this reason, many researches have been tried to develop full scale ship shock tests without using actual explosives. In this study, experiments were conducted to find the characteristics of the underwater shock waves from actual explosive and non-explosive shock sources such as the airbag inflators and Vaporizing Foil Actuator (VFA). In order to derive the empirical equation for the maximum pressure value of the underwater shock wave generated by the non-explosive impact source, repeated experiments were conducted according to the number and distance. In addition, a Shock Response Spectrum (SRS) technique, which is a frequency-based function, was used to compare the response of floating bodies generated by underwater shock waves from each explosion source. In order to compare the magnitude of the underwater shock waves generated by each explosion source, Keel Shock Factor (KSF), which is a measure for estimating the amount of shock experienced by a naval ship from an underwater explosionan, was used.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.55-66
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• 2023

In recent years, naval vessels have been developed to fulfill a variety of missions by being equipped with various cutting-edge equipment and ICT technologies. One of the main missions of Korean naval vessels is anti-ballistic missile warfare to defend key units and areas against the growing threat of ballistic missiles. Because the process of detection and interception is too complex and the cost of failure is much high, a lot of preparation is required to effectively conduct anti-ballistic missile warfare. This paper describes the development of a simulation model of anti-ballistic missile warfare with combat systems and equipment to be installed on future naval vessels. In particular, the DEVS formalism providing a modular and hierarchical modeling manner was applied to the simulation model, which can be utilized to efficiently represent various anti-ballistic missile warfare situations. In the simulation results presented, experiments were conducted to analyze the effectiveness of the model for effective detection resource management in anti-ballistic missile warfare. This study is expected to be utilized as a variety of analysis tools necessary to determine the optimal deployment and configuration of combat resources and operational tactics required for effective anti-ballistic missile warfare of ships in the future.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.745-750
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• 2015

LiDAR(Light Detection and Ranging) technology provides realistic 3-dimension image information, and it has been widely utilized in various fields. However, the utilization of this technology in the military domain requires prompt responses to dynamically changing tactical environment and is therefore limited since LiDAR technology requires complex processing in order for extensive amounts of LiDAR data to be utilized. In this paper, we introduce an Unmanned Aircraft Platform Based Real-time LiDAR Data Processing Architecture that can provide real-time detection information by parallel processing and off-loading between the UAV processing and high-performance data processing areas. We also conducted experiments to verify the feasibility of our proposed architecture. Processing with ARM cluster similar to the UAV platform processing area results in similar or better performance when compared to the current method. We determined that our proposed architecture can be utilized in the military domain for tactical and combat purposes such as unmanned monitoring system.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.37-44
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• 2018

In applying modeling and simulation (M&S) techniques to analyze complex discrete event dynamic systems, conventionally users had to use different simulation environments depending on the user-level. To solve the inconvenience, this paper proposes an integrated development environment for M&S depending on user-level and a formalized interface to manage the model in the development environment efficiently. The interface consists of an extended DEVS formalism and model making rules. The development environment is divided into a modeling environment and a simulation environment. In the modeling environment, three modeling methods are provided for each level of the users. Users inputs several parameters to the model generated as a result of the modeling process, and experiments in various cases by using the simulation environment. The case study shows the implementation of the proposed M&S environment, and using the implemented environment, it shows the M&S process of the complex defense combat system.

• Proceedings of the Microbiological Society of Korea Conference
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• 2000.10a
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• pp.78-82
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• 2000

The AIDS epidemic continues unabated in many part of the world. After near two decades, no vaccine is available to combat the spread of this deadly disease. Much of the HIV -1 vaccine effort during the past decade has focused on the viral envelope glycoprotein, largely because it is the only protein that can elicit neutralizing antibodies (Nabs). Eliciting broadly cross-reactive Nabs has been a primary goal. The intrinsic genetic diversity of the viral envelope, however, has been one of the major impediments in vaccine development. We have recently completed a comprehensive study examining whether it is possible to elicit broadly acting Nabs by immunizing monkeys with mixtures of envelope proteins from multiple HIV -1 isolates. We compared the humoral immune responses elicited by vaccination with either single or multiple envelope proteins and evaluated the importance of humoral and non-humoral immune response in protection against a challenge virus with a homologous or heterologous envelope protein. Our results show that (1) Nab is the correlate of sterilizing immunity, (2) Nabs against primary HIV -1 isolates can be elicited by the live vector-prime/protein boost approach, and (3) polyvalent envelope vaccines elicit broader Nab response than monovalent vaccines. Nonetheless, our findings clearly indicate that the increased breadth of Nab response is by and large limited to strains included in the vaccine mixture and does not extend to heterologous non-vaccine strains. Our study strongly demonstrates how difficult it may be to elicit broadly reactive Nabs using envelope proteins and sadly predicts a similar fate for many of the vaccine candidates currently being evaluated in clinical trials. We have started to evaluate other vaccine candidates (e.g. genetically modified envelope proteins) that might elicit broadly reactive Nabs. We are also exploring other vaccine strategies to elicit potent cytotoxic T lymphocyte responses. Preliminary results from some of these experiments will be discussed.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.481-490
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• 2013

In this paper, an investigation of weapon tracking performance is shown in regard to improving individual weapon performance of aiming objects. On the battlefield, a battle can last only a few hours, sometimes it can last several days until finished. In these long-lasting combats, a wide variety of factors will gradually lower the visual ability of soldiers. The experiments were focusing on enhancing the degraded aiming performance by applying visual tracking technology to roof mounted sights so as to track the movement of troops automatically. In order to select the optimal algorithm among the latest visual tracking techniques, performance of each algorithm was evaluated using the real combat images with characteristics of overlapping problems, camera's mobility, size changes, low contrast images, and illumination changes. The results show that VTD (Visual Tracking Decomposition)[2], IVT (Incremental learning for robust Visual Tracking)[7], and MIL (Multiple Instance Learning)[1] perform the best at accuracy, response speed, and total performance, respectively. The evaluation suggests that the roof mounted sights equipped with visual tracking technology are likely to improve the reduced aiming ability of forces.