• Journal of the Korea Society for Simulation
• /
• v.19 no.4
• /
• pp.199-208
• /
• 2010

Positions of tactical objects are represented as Time, Space and Position Information(TSPI) in modeling and simulations(M&S). The format and required information record for TSPI is investigated by referring the TSPI object model of the Test and Training Enabling Architecture(TENA), which has been developed by the United States Department of Defense. The most sophisticated tactical data link, Link-16 has a Precise Participant Location and Information (PPLI) message. We study the data format for exchanging TSPI data based on the PPLI message. To evaluate and track positions of tactical objects, we consider the Kalman filter for linear systems, and the extended Kalman filter and the unscented Kalman filter for nonlinear systems. Based on motion equations of a ballistic missile, the tracking performance for the trajectory of the ballistic missile is simulated by the unscented Kalman filter.

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.33-39
• /
• 2010

As future warfare becomes network-centric, war-game simulators require high interoperability between networked forces and dynamic reconfiguration in accordance with war events. In this paper, we propose an event-driven methodology to develop dynamic war-game simulations. Federates are developed by event-driven web services. The event-driven web services consistently sense war events and response them only if they are interested. By the sense-and-response mechanism and asynchronous event processing, we are able to save simulation time. An Anti-Surface-Warfare simulator is constructed to demonstrate the methodology and suggests that event-driven web services are efficient to model and simulate warfare where numerous events are generated from hardware systems and people dispersed on the network.

• Journal of the Korea Society for Simulation
• /
• v.19 no.4
• /
• pp.249-259
• /
• 2010

Synthetic environment data used in defense M&S fields, which came from various organization and source, are consumed and managed by their own native database system in distributed environment. But to manage these diverse data while interoperation in HLA/RTI environment, neutral synthetic environment data model is necessary to transmit the data between native database. By the support of DMSO, SEDRIS was developed to achieve this requirement and this specification guarantees loss-less data representation, interchange and interoperability. In this research, to use SEDRIS as a standard simulation database, base research, visualization for validation, data interchange experiment through test-bed was done. This paper shows each research case, result and future research direction, to propose standardized SEDRIS usage process.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.3
• /
• pp.161-166
• /
• 2023

In recent years, new and variant hacking of binary codes has increased, and the limitations of techniques for detecting malicious codes in source programs and defending against attacks are often exposed. Advanced software security vulnerability detection technology using machine learning and deep learning technology for binary code and defense and response capabilities against attacks are required. In this paper, we propose a malware clustering method that groups malware based on the characteristics of the taint information after entering dynamic taint information by tracing the execution path of binary code. Malware vulnerability detection was applied to a three-layered Few-shot learning model, and F1-scores were calculated for each layer's CPU and GPU. We obtained 97~98% performance in the learning process and 80~81% detection performance in the test process.

• Smart Structures and Systems
• /
• v.32 no.1
• /
• pp.1-7
• /
• 2023

In modal analysis, the mode shape reflects the vibration characteristics of the structure, and thus it is widely performed for finite element model updating and structural health monitoring. Generally, the acceleration-based mode shape is suitable to express the characteristics of structures for the translational vibration; however, it is difficult to represent the rotational mode at boundary conditions. A tilt sensor and gyroscope capable of measuring rotational mode are used to analyze the overall behavior of the structure, but extracting its mode shape is the major challenge under the small vibration always. Herein, we conducted a feasibility study on a multi-mode shape estimating approach utilizing a single physical quantity signal. The basic concept of the proposed method is to receive multi-metric dynamic responses from two sensors and obtain mode shapes through bridge loading test with relatively large deformation. In addition, the linear transformation matrix for estimating two mode shapes is derived, and the mode shape based on the gyro sensor data is obtained by acceleration response using ambient vibration. Because the structure's behavior with respect to translational and rotational mode can be confirmed, the proposed method can obtain the total response of the structure considering boundary conditions. To verify the feasibility of the proposed method, we pre-measured dynamic data acquired from five accelerometers and five gyro sensors in a lab-scale test considering bridge structures, and obtained a linear transformation matrix for estimating the multi-mode shapes. In addition, the mode shapes for two physical quantities could be extracted by using only the acceleration data. Finally, the mode shapes estimated by the proposed method were compared with the mode shapes obtained from the two sensors. This study confirmed the applicability of the multi-mode shape estimation approach for accurate damage assessment using multi-dimensional mode shapes of bridge structures, and can be used to evaluate the behavior of structures under ambient vibration.

• Journal of Aerospace System Engineering
• /
• v.18 no.2
• /
• pp.1-11
• /
• 2024

This paper applies a relative impact angle control guidance law to a communication-based multi-missile network system with uncertainties and disturbances. The multi-missile network system is represented as a transitive reduction directed acyclic graph. Furthermore, this paper introduces both centralized and decentralized guidance laws based on the graph's structure. The relationship between these guidance laws is analyzed by comparing them based on the communication structure and the presence of system noise. To analyze the effects of decentralized optimal cooperative guidance law, this paper assumes uncertainty in missile dynamics and predicted impact point information for the relative impact angle control mission. Monte Carlo simulations are conducted for various mission environments to analyze the impact of communication and its structure on the system.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.2
• /
• pp.1-12
• /
• 2024

Predicting path loss is one of the important factors for wireless network design, such as selecting the installation location of base stations in cellular networks. In the past, path loss values were measured through numerous field tests to determine the optimal installation location of the base station, which has the disadvantage of taking a lot of time to measure. To solve this problem, in this study, we propose a path loss prediction method based on machine learning (ML). In particular, an ensemble learning approach is applied to improve the path loss prediction performance. Bootstrap dataset was utilized to obtain models with different hyperparameter configurations, and the final model was built by ensembling these models. We evaluated and compared the performance of the proposed ensemble-based path loss prediction method with various ML-based methods using publicly available path loss datasets. The experimental results show that the proposed method outperforms the existing methods and can predict the path loss values accurately.

• International Journal of Advanced Culture Technology
• /
• v.12 no.2
• /
• pp.236-248
• /
• 2024

This study aims to empirically analyze the effects of leadership level and toxic leadership on leadership performance results among male and female military leaders in the Army, and to verify whether the leader's gender has a moderating effect in this process. Additionally, by comparing and analyzing the leadership level, toxic leadership, and leadership performance results of female military leaders by position, this study seeks to examine the characteristics of female military leadership according to position. The research model was established with leadership level and toxic leadership as independent variables, leadership performance results as the dependent variable, and the leader's gender as a moderating variable. Data were collected through a survey of 216 male and female officers serving in the positions of platoon leader, company commander, and battalion commander in the Army. The collected data were analyzed using descriptive statistics, reliability analysis, correlation analysis, and hierarchical regression analysis. The results showed that leadership level had a significant positive effect on leadership performance results, while toxic leadership had a significant negative effect. The leader's gender moderated the relationship between leadership level and leadership performance results, with female leaders receiving lower evaluations than male leaders at the same level of leadership competency. Gender also moderated the relationship between toxic leadership and leadership performance results, with female leaders exhibiting the same level of toxic leadership receiving lower performance evaluations than male leaders. In the comparative analysis of female military leadership characteristics by position, the leadership level of the platoon leader and company commander groups was not significantly different from that of male soldiers, but the battalion commander group showed slightly lower leadership competency compared to male soldiers. Based on these results, this study suggests ways to improve the leadership level of female military leaders, reduce toxic leadership, and prepare support measures to strengthen the leadership competency of female military officers at the battalion commander level and above from policy, institutional, and educational perspectives.

• Nuclear Engineering and Technology
• /
• v.56 no.4
• /
• pp.1153-1164
• /
• 2024

In recent years, unmanned ground vehicles (UGVs) have been used to search for lost or stolen radioactive sources to avoid radiation exposure for operators. To achieve autonomous localization of radioactive sources, the UGVs must have the ability to automatically determine the next radiation measurement location instead of following a predefined path. Also, the radiation field of radioactive sources has to be reconstructed or inverted utilizing discrete measurements to obtain the radiation intensity distribution in the area of interest. In this study, we propose an effective source localization framework and method, in which UGVs are able to autonomously explore in the radiation area to determine the location of radioactive sources through an iterative process: path planning, radiation field reconstruction and estimation of source location. In the search process, the next radiation measurement point of the UGVs is fully predicted by the design path planning algorithm. After obtaining the measurement points and their radiation measurements, the radiation field of radioactive sources is reconstructed by the Gaussian process regression (GPR) model based on machine learning method. Based on the reconstructed radiation field, the locations of radioactive sources can be determined by the peak analysis method. The proposed method is verified through extensive simulation experiments, and the real source localization experiment on a Cs-137 point source shows that the proposed method can accurately locate the radioactive source with an error of approximately 0.30 m. The experimental results reveal the important practicality of our proposed method for source autonomous localization tasks.

• IMMUNE NETWORK
• /
• v.21 no.6
• /
• pp.42.1-42.20
• /
• 2021

Eosinophils play critical roles in the maintenance of homeostasis in innate and adaptive immunity. Although primarily known for their roles in parasitic infections and the development of Th2 cell responses, eosinophils also play complex roles in other immune responses ranging from anti-inflammation to defense against viral and bacterial infections. However, the contributions of pattern recognition receptors in general, and NOD-like receptors (NLRs) in particular, to eosinophil involvement in these immune responses remain relatively underappreciated. Our in vivo studies demonstrated that NLRC4 deficient mice had a decreased number of eosinophils and impaired Th2 responses after induction of an allergic airway disease model. Our in vitro data, utilizing human eosinophilic EoL-1 cells, suggested that TLR2 induction markedly induced pro-inflammatory responses and inflammasome forming NLRC4 and NLRP3. Moreover, activation by their specific ligands resulted in caspase-1 cleavage and mature IL-1β secretion. Interestingly, Th2 responses such as secretion of IL-5 and IL-13 decreased after transfection of EoL-1 cells with short interfering RNAs targeting human NLRC4. Specific induction of NLRC4 with PAM3CSK4 and flagellin upregulated the expression of IL-5 receptor and expression of Fc epsilon receptors (FcεR1α, FcεR2). Strikingly, activation of the NLRC4 inflammasome also promoted expression of the costimulatory receptor CD80 as well as expression of immunoregulatory receptors PD-L1 and Siglec-8. Concomitant with NLRC4 upregulation, we found an increase in expression and activation of matrix metalloproteinase (MMP)-9, but not MMP-2. Collectively, our results present new potential roles of NLRC4 in mediating a variety of eosinopilic functions.