• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.663-674
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• 2005

We propose a system aimed at achieving high energy-delay efficiency by using adaptive victim caches. Particularly, we investigate methods to improve the hit rates in the first level of memory hierarchy, which reduces the number of accesses to mort power consuming memory structures such as L2 cache. Victim cache is a memory element for reducing conflict misses in a direct-mapped L1 cache. We present two techniques to fill the victim cache with the blocks that have higher probability to be re-reqeusted by processor. Hit-based victim cache ks tilled with the blocks which were referenced frequently by processor. Replacement-based victim cache is filled with the blocks which were evicted from the sets where block replacements had happened frequently According to our simulations, replacement-based victim cache scheme outperforms the conventional victim cache scheme about $2\%$ on average and refutes the power consumption by up to $8\%$.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.173-189
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• 2022

This study presents an experimental and numerically study about the effects of fiber reinforcement ratio on the behavior of concrete-filled steel tubes (CFST) under dynamic impact loading. In literature have examined the behavior of GFRP and FRP wrapped strengthened CFST elements impact loads. However, since the direction of potential impact force isn't too exact, there is always the probability of not being matched the impact force of the area where the reinforced. Therefore, instead of the fiber textile wrapping method which strengthens only a particular area of CFST element, we used fiber-added concrete-filled elements which allow strengthening the whole element. Thus, the effect of fiber-addition in concrete on the behavior of CFST elements under impact loads was examined. To do so, six simply supported CFST beams were constructed with none fiber, 2% fiber and 10% fiber reinforcement ratio on the concrete part of the CFST beam. CFST beams were examined under two different impact loads (75 kg and 225 kg). The impactors hit the beam from a 2000 mm free fall during the experimental study. Numerical models of the specimens were created using ABAQUS finite element software and validated with experimental data. The obtained results such as; mid-span displacement, acceleration, failure modes and energies from experimental and numerical studies were compared and discussed. Furthermore, the Von Misses stress distribution of the CFST beams with different ratio of fiber reinforcements were investigated numerically. To sum up, there is an optimum amount limit of the fiber reinforcement on CFST beams. Up to this limit, the fiber reinforcement increases the structural performances of the beam, beyond that limit the fiber reinforcement decreases the performances of the CFST beam under transverse impact loadings.

• Journal of IKEEE
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• v.18 no.1
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• pp.45-56
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• 2014

Recently, damages from disasters such as downpours, earthquakes and typhoons are increasing throughout the world. The downpour days of Korean Peninsula are also increasing every year due to rapid climate change. According to statistics over the last 30 years of the earthquakes in Korean Peninsula, the probability of a future earthquake is very high. In addition, super typhoons will hit Korean Peninsula due to the temperature rise in the nearby sea caused by the deepening of global warming. Thus, damage costs of the waterfront structures by natural disasters are also growing. But damage information system for integrated management of waterfront structures are insufficient. In this paper, we designed and implemented a damage information system for integrated management of waterfront structures. First, we classified damage information caused by natural disaster. Then we designed the databases of damage information and implemented damage information system. Lastly, we checked operations and the feasibility by testing queries on the proposed system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.241-250
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• 2005

New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.535-546
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• 2011

This study develops statistical models for the binary forecast of Asian dust days over South Korea in the winter season. For this study, we used three kinds of data; the rst one is the observed Asian dust days for a period of 31 years (1980 to 2010) as target values, the second one is four meteorological factors(near surface temperature, precipitation, snowfall, ground wind speed) in the source regions of Asian dust based on the NCEP reanalysis data and the third one is the large-scale climate indices. Four kinds of statistical models(multiple regression models, logistic regression models, decision trees, and support vector machines) are applied and compared based on skill scores(hit rate, probability of detection and false alarm rate).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.78-85
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• 2012

Space debris is the collection of objects in orbit around the Earth that were created by humans but no longer serve any useful purpose. Since the beginning of spacecraft launch in 1957, the number of space debris has been increasing. According to USSTRATCOM, the number of space debris which were bigger than 10 cm is more than 15,000. Recently there were two critical events: One is that China shot down their satellite using missile and the other is that two satellite, United States's Iridium 33 and Russia's Cosmos 2251, collided with each other. Thanks to these events, Space environment in which KOMPSAT-2 operates has become severer. This paper presents the analysis of the number of space debris which are close to KOMPSAT-2 and the maximum conjunction probability via minimum range. Especially, this paper makes it possible to continuously monitor the space debris that is possible to hit KOMPSAT-2 through the identification and analysis.

• Journal of the Korea Society for Simulation
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• v.26 no.1
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• pp.13-19
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• 2017

6-DOF flight simulation program is most generally used M&S tool in domestic missile development procedure. The 6-DOF M&S method, however, cannot validate the performance of a imaging seeker-adopted missile in various conditions. A M&S tool for the analysis of the integrated-flight simulation is required since the tracking performance of the imaging seeker is highly dependent on the missile maneuvering, which introduces the displacement and rotation of the target in the seeker imagery. Through the development of the $3^{rd}$ generation anti-tank missile, Raybolt, the integrated-flight M&S tool was developed and applied to the missile configuration design. It integrates synthetic image generation S/W, imaging tracker, and flight simulation program and computes the main system performance criteria, hit probability by Monte-Carlo Simulation. In this paper, the issues in the $3^{rd}$ generation anti-tank missile configuration and the integrated-flight M&S method and results are described.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• The Journal of Information Systems
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• v.27 no.1
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.334-341
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• 2020

The optimum solutions of the instability of the target velocity were studied to solve the case of the target velocity of the ship approaching at a speed of ◯◯knots and deviated by more than ± 10knots, while the surveillance radar rotating speed was varied, while the maximum search range of the radar was evaluated during the operational test & evaluation. The instability of the target velocity did not enable the radar to calculate the information of the target precisely and to degrade the probability of hit and the quality of the target management. The improvement to handle the deviation of the target velocity was optimally determined by using a fishbone diagram to find 9 reasons based on 4M1E, and the algorithm of the target management was identified as the crucial reason. In this study, the improvement was applied to the filter algorithm to stabilize the target velocity in the target tracking management SW by reviewing the current algorithm to find the velocity of the target and recognizing that the problem does not apply to different 𝜶, 𝞫 values when the antenna changed the rotating speed. The ability of the improvement to work was tested on board.