• Vending industry
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• v.2 no.6 s.7
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• pp.71-80
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• 2003

자판기 관련 기술의 발달은 이제 자판기를 단순 유형의 내용상품 만을 적용 판매하는 수준을 넘어 서게 한지 오래이다. 단일상품으로서 상품가치 극대화와 활용도 증가를 위해 여러 기능을 한 제품에 묶는 퓨전 성능화 동향이 최근 들어 급속화되고 있다. 따라서 어떤 성능을 메인 성능으로 보아야 할지 모호한 제품군이 등장하기도 하고, 심지어 자판기로서의 정체성까지 의심되는 경우도 있다. 자판기 기술발달과 적용 가능한 콘텐츠의 다양화에 따라 등장한 퓨전 자판기들은 분명 자판기 영역과 위상확대에 도움이 되는 것이 사실이지만 그 이면에는 확실한 하나의 기능으로서가 아닌 어중간한 제품 성격으로 제대로 소비자에게 어필하지 못하는 위험 수 역시 적지 않다. 하지만 기존 단순기능 위주의 자판기 시장은 한계가 있음에 미루어 볼 때 퓨전 성능화 동향은 거부 할 수 없는 신조류로 산업계에 새로운 가능성을 제시하고 있다. 이제 과제는 산업계가 그 흐름을 얼마나 발전적인 방향으로 유도해 내느냐에 달려 있다. 금호에서는 최근 부쩍 가속화되고 있는 자판기의 퓨전 성능화 동향을 집중진단해 보는 시간을 마련했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.709-712
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• 2011

본 논문은 AMI(Advanced Metering Infrastructure) 네트워크의 성능 시뮬레이터를 구현하기 위해 필요한 설계 모듈들을 제안한다. AMI 네트워크는 스마트 그리드의 핵심시스템으로 네트워크를 구성하는 장치들이 스스로 통신하여 서로 간에 필요한 정보를 수집 분석하고 사용자가 원하는 정보를 제공하기 위한 환경이다. 이러한 AMI 네트워크를 실제로 전국에 구현 할 시 발생할 수 있는 시행착오를 최소화하기 위해 성능, 위험요소 등을 사전 시뮬레이션 해 볼 필요가 있다. 본 논문에서는 AMI 네트워크를 시뮬레이션하고 적정 성능을 분석하기 위한 성능 시뮬레이터의 모듈을 제안한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.501-506
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• 2017

An infrared seeking missile does not emit any signal by itself as it is guided by passive heat signature from an aircraft. Therefore, it is difficult for the target aircraft to notice the existence of incoming missile, making it a serious threat. The usage of MAW(missile approach warning) that can notify the approaching infrared seeking missile is currently limited due to its high cost. Furthermore, effectiveness of MAW against infrared seeking missile is not available in open literature. Therefore, effect of evasive maneuver by MAW on the survivability of the aircraft is simulated to evaluate the benefit of the MAW in this research. The lethal range is used as a measure of aircraft survivability. An aircraft flying at an altitude of 5km with Mach 0.9 being tracked by air-launched AIM-9 infrared seeking missile is considered in this research. As a variable for the evasive maneuver, the MAW recognition distance of 5~7km and the G-force of 3~7G that limits maximum directional change of the aircraft are considered. Simulation results showed that the recognition of incoming missile by MAW and following evasive maneuver can reduce the lethal range considerably. Maximum reduction in lethal range is found to be 29.4%. Also, the MAW recognition distance have a greater importance than the aircraft maneuverability that is limited by structural limit of the aircraft.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.245-253
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• 2021

Purpose: This study develops a risk prediction model that predicts the risk of a fire site by using initial information such as building information and reporter acquisition information, and supports effective mobilization of fire fighting resources and the establishment of damage minimization strategies for appropriate responses in the early stages of a disaster. Method: In order to identify the variables related to the fire damage scale on the fire statistics data, a correlation analysis between variables was performed using a machine learning algorithm to examine predictability, and a learning data set was constructed through preprocessing such as data standardization and discretization. Using this, we tested a plurality of machine learning algorithms, which are evaluated as having high prediction accuracy, and developed a risk prediction model applying the algorithm with the highest accuracy. Result: As a result of the machine learning algorithm performance test, the accuracy of the random forest algorithm was the highest, and it was confirmed that the accuracy of the intermediate value was relatively high for the risk class. Conclusion: The accuracy of the prediction model was limited due to the bias of the damage scale data in the fire statistics, and data refinement by matching data and supplementing the missing values was necessary to improve the predictive model performance.

• Applied Chemistry for Engineering
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• v.33 no.4
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• pp.373-380
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• 2022

In this study, Chung's equations 1, 2, and 3 were extended to standardize smoke safety rating evaluation in case of fire, and Chung's equations-V, smoke performance index-V, and smoke growth index-V were calculated. Five types of wood were selected and their smoke indices were measured using the cone calorimeter method according to ISO 5660-1. The smoke risk was graded by the smoke risk index-VI according to Chung's equation-VI. Smoke risk index-VI increased in the order of PMMA (1) ≈ maple (1.01) < ash (1.57) < needle fir (4.98) < paulownia (46.15) < western red cedar (106.26). It was predicted that maple and ash had the lowest smoke risk, and paulownia and western red cedar had the highest. The five samples' CO mean production rate (COP_mean) was 0.0009~0.0024 g/s, indicating that these woods were incompletely burned than the polymethyl methacrylate (PMMA) reference material. Regarding the smoke properties of the chosen woods, the smoke performance index-V (SPI-V) increased as the bulk density increased, and the smoke risk index-VI (SRI-VI) decreased.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.34-48
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• 2019

The purpose of this study was two-fold; first, to develop safety performance functions (SPF) using transportation-related big data for all types of roads in Korea were developed, Second, to provide basic information to develop measures for relatively dangerous roads by evaluating the safety grade for various roads based on it. The coordinates of traffic accident data are used to match roads across the country based on the national standard node and link system. As independent variables, this study effort uses link length, the number of traffic volume data from ViewT established by the Korea Transport Research Institute, and the number of dangerous driving behaviors based on the digital tachograph system installed on commercial vehicles. Based on the methodology and result of analysis used in this study, it is expected that the transportation safety improvement projects can be properly selected, and the effects can be clearly monitored and quantified.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.143-154
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• 2008

Since the concerns for safety of highway traffic safety facilities inherent in various environmental risk is increased, systematic performance, cost, and effect analysis process is needed for this. In case of median barrier among various traffic safety facilities, quantitative risk assessment is inevitable because it has lots of direct/indirect risk factors. Thus, this study suggests an advanced VE(Value Engineering) approach incorporating quantitative risk analysis. For the applicability, suggested VE approach considering alternative 1(140cm) and 2(127cm) is applied to median barrier in fields. Also, major improvement objects are extracted from governing factors of cost and performance based on functional analysis. It is concluded that the proposed risk assessment methodology will provide rational and practical solutions for best value and the approach could effectively applied for various traffic safety facilities by slight modification of suggest process.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.180-181
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.523-528
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• 2015

This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.