This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS’s rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment. K

Because sows are industrially vital for swine production, monitoring for their health or disorder status is important to ensure high reproductive performance. Especially, ambient temperature changes in different season, especially during summer, are directly influenced to the reproductive performance of sows. Although the serum biochemical parameters are widely applied in the veterinary medicine with wide ranges for the physiological process, the values are also influenced by several factors such as age, breed, gender, and stress. In addition, domestic sows in Koreaspecific reference interval (RI) for serum biochemistry has not been established yet. Therefore, the present study was aimed to evaluate seasonal variation of RIs in the serum biochemistry in domestic sows in Korea at different seasons and to establish normal RIs using a RI finding program (Reference Value Advisor). Significant difference (p < 0.05) on the different seasons were identified in several serum biochemical parameters including BUN, CRE, GGT, GLU, ALB, TP, LDH and Na in sows. Therefore, we further established RIs, specific in domestic sows in Korea regardless of season. The established RIs based on the serum biochemical values provide a baseline for interpreting biochemical results in the domestic sows in Korea, regardless of seasonal effect. It may contribute to develop a strategy for better reproductive performance by improving breeding management practice and evaluating health of pig herds, which facilitate to avert the economic loss in summer infertility in sows.

최근 들어 연구기관 및 기업에서 특허 출원 및 등록이 지속적으로 증가함에 따라 특허 관련 비용뿐만 아니라 특허의 양적 질적 관리도 매우 중요한 요소로 대두되고 있다. 따라서 기업 및 기관이 보유하고 있는 많은 특허 중에서 활용 목적에 맞는 우수 특허를 선별 하고 관리하는 것이 특허경영의 한 방안으로 강조되고 있다. 본 연구는 기업이 보유하고 있는 특허를 대상으로 QFD를 적용하여 가치 있는 우수 특허를 효과적으로 선별하는 방안을 제시하였다. QFD를 이용하여 특허를 분류하고 품질을 정량적으로 평가하기 위해서 우선 특 허에 대한 기업의 요구사항 및 특허품질 특성지표를 도출하였다. 기업의 요구사항의 경우 AHP의 쌍대비교 방식으로 중요도를 결정하였으며, 이를 바탕으로 고객의 요구를 충족시킬 수 있는 특허지표의 값을 결정하고, 이에 대한 해석 및 활용방안에 대해서 논했다. 본 연구에서 제시한 우수특허 선별 방식을 실제 기업의 보유 특허에 적용하여 결과를 비교 분석하였으며 개별 특허지표 및 특허복합지표를 통해 우수 특허를 비교적 손쉽게 선별할 수 있음을 보여 주었다.

Pilot Aptitude Research Equipment (PARE) is a simulator developed to measure or research pilot aptitude and train for student pilots. Design of an ergonomic PARE operation console is required to operate the equipment effectively. This study carried out five steps : (S1) operator questionnaire survey, (S2) anthropometric design formula development, (S3) usability evaluation, (S4) improvement design, and (S5) validation considering both Physical User Interface (PUI) and Graphic User Interface (GUI) of PARE operation console. The operator questionnaire surveyed needs for each PUI and GUI part of the console from two PARE actual operators. In terms of PUI, the anthropometric design formula was developed by using design variables, body dimensions, target population characteristics, and reference posture related to the PARE console. In terms of GUI, the usability evaluation was conducted by three usability testing experts with a 7-point scale (1 : very low, 4 : neutral, 7 : very high) on GUI of the PARE operation console by seven usability criteria. The improved PARE operation console was designed to reflect the optimal values of design variables calculated from design formula, the results from usability testing, and the operator’s needs. The improvement effect was observed by 20 people who had experience with the PARE operation console. As a result of the validation, monitor visibility and cockpit visibility for the improved PUI design and visibility and efficiency for the improved GUI design were significantly increased by more than 90% respectively. The improved design of the PARE operation console in this study can contribute to enhance operation performance of the PARE.

This paper studied balanced regional development focused on employment in Korea, by analyzing regional disparity between regional and industrial employment. A Gini-coefficient decomposition method and Panel Granger causality test were conducted, using raw data of the Census on Establishments reported by the Statistics Korea. The regional and industrial disparity of employment, based on the Gini-coefficient decomposition method, have increased by year. However, the growth rates of disparity are on the decrease. Most of employment disparity occurred from regional disparity between SMA (Seoul Metropolitan Area) and Non-SMA. Industrial disparity are occurred mainly by the service industry. The amount of contribution to the whole disparity of inter/intra regional employment was differed by each industrial sector. Also the causal relationship between employment growth of manufacture and that of service industry was analyzed by Panel Granger causality test. In national level, the employment growth in manufacture industry has conduced that in service industry. On the other hand, in the Non-SMA, only the employment growth in manufacture industry has augmented that in service industry. In conclusion, to reduce employment disparity, the strategy for balanced regional development should be emphasized. Different strategies are needed across regions and industries. Basically creating new job in the Non-SMA is inevitable. In view of stable employment, manufacture industry is more desirable rather than service industry.

Aircraft landing is a complex and challenging flight phase in which pilots are required to allocate attention efficiently to the surrounding environment. A comprehensive understanding of pilot situation awareness (SA) is needed for successful landing. This study was to predict pilot SA during landing using eye tracking data. The experiments were carried out with 5 repetitive simulated landings for four expert and four novice pilots using eye tracking equipment. Three eye tracking features (visit frequency, dwell time ratio, scan path entropy) were developed for reflecting three level of SA model (perception, comprehension, projection). Prediction of SA was performed by developing multiple regression model. Visit frequency of expert pilots was 138%, 47%, 85%, 67%, 117%, and 91% higher than novice pilots in RPM, VVI, altimeter, heading, airspeed, and attitude areas of interest (AOIs) respectively; while 50% and 33% lower in runway and outside AOIs respectively. Dwell time ratio of expert pilots was 38% and 42% higher than novice pilots in runway and outside AOIs respectively; while 62%, 62%, and 65% lower in altimeter, airspeed, and attitude AOIs respectively. Scan path entropy of expert pilots was 33% higher than novice pilots in outside AOI; while 29% lower in attitude AOI. Coefficient of determination for the prediction model for SA was 80.6%. The results of this study can be used as objective data of strategy establishment or training feedback for novice pilots.

To identify the cause of the error and maintain the health of system, an administrator usually analyzes event log data since it contains useful information to infer the cause of the error. However, because today’s systems are huge and complex, it is almost impossible for administrators to manually analyze event log files to identify the cause of an error. In particular, as OpenStack, which is being widely used as cloud management system, operates with various service modules being linked to multiple servers, it is hard to access each node and analyze event log messages for each service module in the case of an error. For this, in this paper, we propose a novel message-based log analysis method that enables the administrator to find the cause of an error quickly. Specifically, the proposed method 1) consolidates event log data generated from system level and application service level, 2) clusters the consolidated data based on messages, and 3) analyzes interrelations among message groups in order to promptly identify the cause of a system error. This study has great significance in the following three aspects. First, the root cause of the error can be identified by collecting event logs of both system level and application service level and analyzing interrelations among the logs. Second, administrators do not need to classify messages for training since unsupervised learning of event log messages is applied. Third, using Dynamic Time Warping, an algorithm for measuring similarity of dynamic patterns over time increases accuracy of analysis on patterns generated from distributed system in which time synchronization is not exactly consistent.

Recently, Live-Virtual-Constructive (L-V-C) integrate training system has proposed as a solution for the problems such as limitation of training areas, increase of mission complexity, rise in oil prices. In order to integrate each training system into the one effectively, we should solve the issue about stress of pilots by the environmental differences between Live and Virtual simulation which could be occurred when each system is connected together. Although it was already examined in previous study that the psychological effects on pilots was occurred by the environmental differences between actual and simulated flights, the study did not include what the causal factors affecting psychological effects are. The aim of this study is to examine which environmental factors that cause pilots’ psychological effects. This study analyzed the biochemical stress hormone, cortisol to measure the pilots’ psychological effects and cortisol was measured using Enzyme-linked immunoassay (EIA). A total of 40 pilots participated in the experiment to compare the differences in pilots’ cortisol response among live simulation, virtual simulation, and the virtual simulation applying three environmental factors (gravity force, noise, and equipment) respectively. As a result, there were significant differences in cortisol level when applied the gravity force and equipment factors to the virtual simulation, while there was no significant difference in the case of the noise factor. The results from this study can be used as a basis for the future research on how to make L-V system by providing minimum linkage errors and design the virtual simulator that can reduce the differences in the pilots’ psychological effects.

The sintering mechanisms of nanoscale copper powders have been investigated. A molecular dynamics (MD) simulation with the embedded-atom method (EAM) was employed for these simulations. The dimensional changes for initial-stage sintering such as characteristic lengths, neck growth, and neck angle were calculated to understand the densification behavior of copper nano-powders. Factors affecting sintering such as the temperature, powder size, and crystalline misalignment between adjacent powders have also been studied. These results could provide information of setting the processing cycles and material designs applicable to nano-powders. In addition, it is expected that MD simulation will be a foundation for the multi-scale modeling in sintering process.