• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.414-422
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• 2006

Deterministic techniques have been applied in power system planning for many years and there is a growing interest in combining these techniques with probabilistic considerations to assess the increased system stress due to the restructured electricity environment. The overall reliability framework proposed in this paper incorporates the deterministic N-1 criterion in a probabilistic framework, and results in the joint inclusion of both adequacy and security considerations in system planning. The combined framework is achieved using system well-being analysis and traditional adequacy assessment. System well-being analysis is used to quantify the degree of N-1 security and N-1 insecurity in terms of probabilities and frequencies. Traditional adequacy assessment is Incorporated to quantify the magnitude of the severity and consequences associated with system failure. The concepts are illustrated by application to two test systems. The results based on the overall reliability analysis framework indicate that adequacy indices are adversely affected by a generation deficient environment and security indices are adversely affected by a transmission deficient environment. The combined adequacy and security framework presented in this paper can assist system planners to realize the overall benefits associated with system modifications based on the degree of adequacy and security, and therefore facilitate the decision making process.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.8
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• pp.1304-1316
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• 2014

The aims of this study were to estimate daily intakes of artificial sweeteners from beverages and liquid teas as well as evaluate their potential health risks in Korean children and adolescents (1 to 19 years old). Dietary intake assessment was conducted using actual levels of aspartame, acesulfame-K, and sucralose in non-alcoholic beverages (651 beverages and 87 liquid teas), and food consumption amounts were drawn from "The Fourth Korea National Health and Nutrition Examination Survey (2007~2009)". To estimate dietary intake of non-alcoholic beverages, a total of 6,082 children and adolescents (Scenario I) were compared to 1,704 non-alcoholic beverage consumption subjects (Scenario II). The estimated daily intake of artificial sweeteners was calculated based on point estimates and probabilistic estimates. The values of probabilistic artificial sweeteners intakes were presented by a Monte Carlo approach considering probabilistic density functions of variables. The level of safety for artificial sweeteners was evaluated by comparisons with acceptable daily intakes (ADI) of aspartame (0~40 mg/kg bw/day), acesulfame-K (0~15 mg/kg bw/day), and sucralose (0~15 mg/kg bw/day) set by the World Health Organization. For total children and adolescents (Scenario I), mean daily intakes of aspartame, acesulfame-K, and sucralose estimated by probabilistic estimates using Monte Carlo simulation were 0.09, 0.01, and 0.04 mg/kg bw/day, respectively, and 95th percentile daily intakes were 0.30, 0.02, and 0.13 mg/kg bw/day, respectively. For consumers-only (Scenario II), mean daily intakes of aspartame, acesulfame-K, and sucralose estimated by probabilistic estimates using Monte Carlo simulation were 0.52, 0.03, and 0.22 mg/kg bw/day, respectively, and 95th percentile daily intakes were 1.80, 0.12, and 0.75 mg/kg bw/day, respectively. For scenarios I and II, neither aspartame, acesulfame-K, nor sucralose had a mean and 95th percentile intake that exceeded 5.06% of ADI.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2005-2010
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• 2004

As robots become more prevalent in human daily life, situations requiring interaction between humans and robots will occur more frequently. Therefore, human-robot interaction (HRI) is becoming increasingly important. Although robotics researchers have made many technical developments in their field, intuitive and easy ways for most common users to interact with robots are still lacking. This paper introduces a new approach to enhance human-robot interaction using a semantic symbol language and proposes a method to acquire the intentions of robot users. In the proposed approach, each semantic symbol represents knowledge about either the environment or an action that a robot can perform. Users'intentions are expressed by symbolized multimodal information. To interpret a users'command, a probabilistic approach is used, which is appropriate for interpreting a freestyle user expression or insufficient input information. Therefore, a first-order Markov model is constructed as a probabilistic model, and a questionnaire is conducted to obtain state transition probabilities for this Markov model. Finally, we evaluated our model to show how well it interprets users'commands.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.3
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• pp.332-339
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• 2013

The network nodes in a tactical network moves continuously and due to the physical and electronic obstacles, the connections are not always available. Due to the frequent disconnections, it is hard to discover the path among the nodes in a DTN. According to PROPHET(Probabilistic Routing Protocol using History of Encounters and Transitivity), one of the most well-known DTN routing protocols, a DTN node determines whom to forward a packet according to the packet delivery probability. From the viewpoint of a node, the packet delivery probability of another node is degraded while the nodes are disconnected whereas it is improved when they encounter. In this paper, we enhance the algorithm estimating the packet probability by considering the encounter count as an additional parameter. Our algorithm prefers the node that encounters the destination more frequently in selecting the next hop toward the destination. We evaluated the performance of our algorithm by simulating military operations using a DTN-dedicated simulator. Through the simulations, we show that our proposed algorithm achieve higher packet delivery ratio with similar overhead compared with PROPHET.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.95-101
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• 2002

This paper illustrates a new fuzzy effective load model for probabilistic and fuzzy production cost simulation of the load point of the composite power system. A model for reliability evaluation of a transmission system using the fuzzy set theory is proposed for considering the flexibility or ambiguity of capacity limitation and overload of transmission lines, which are subjective matter characteristics. A conventional probabilistic approach was also used to model the uncertainties related to the objective matters for forced outage rates of generators and transmission lines in the new model. The methodology is formulated in order to consider the flexibility or ambiguity of load forecasting as well as capacity limitation and overload of transmission lines. It is expected that the Fuzzy CMELDC (CoMposite power system Effective Load Duration Curve) proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems in a competitive environment in the future. The characteristics of this new model are illustrated by some case studies of a very simple test system.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.204-212
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• 2020

For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.740-746
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• 2010

Rainwater has been used in many countries as a way of minimizing water availability problems. Rainwater harvesting system (RHS) has been successfully implemented as alternative water supply sources even in Korea. Although RHS is an effective alternative to water supply, its efficiency is often heavily influenced by temporal distribution of rainfall. Since natural precipitation is a random process and has probabilistic characteristics, it will be more appropriate to describe these probabilistic features of rainfall and its relationship with design storage capacity as well as supply deficit of RHS. This study presents the methodology to establish the relationships between storage capacities and deficit rates using probability distributions. In this study, the real three-story building was considered and nine scenaries were developed because the daily water usage pattern of the study one was not identified. GEV, Gumbel and the generalized logistic distribution ware selected according to the results of Kolmogorov-Smirnov test and Chi-Squared test. As a result, a set of curves describing the relationships under different exceedance probabilities were generated as references to RHS storage design. In case of the study building, the deficit rate becomes larger as return period increases and will not increase any more if the storage capacity becomes the appropriate quantity. The uncertainties between design storage and the deficit can be more understood through this study on the probabilistic relationships between storage capacities and deficit rates.

• Journal of Korean Society on Water Environment
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• v.22 no.6
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• pp.1068-1074
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• 2006

For receiving water quality protection a control systems of urban drainage for CSOs reduction is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as storm-water detention storage is highly dependant on the temporal variability of storage capacity available as well as the infiltration capacity of soil and recovery of depression storage. For the continuous long-term analysis of urban drainage system this study used analytical probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model has evolved that offers much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics of the subject area using analytical probabilistic model. Runoff characteristics manifested the unique characteristics of the subject area with the infiltration capacity of soil and recovery of depression storage and was examined appropriately by sensitivity analysis. This study presented the average annual CSOs, number of CSOs and event mean CSOs for the decision of storage volume.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.361-368
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• 2007

The storage space requirement is a very important decision variable which determines the storage capacity of a container terminal. Generally, the storage space requirement is dependent upon such factors as ship headway, allowable dwell time of containers, loading/winding time per ship, and so on. Until now, the storage space requirement is estimated under the assumption that the factors are deterministic in several studies. However, this study proposes how to estimate a storage space requirement satisfying the required service level under the assumption that a containership's load size is probabilistic. Numerical experiments, which use a simulation show that the proposed method can estimate more adequately the storage space requirement than other methods under a probabilistic environment.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.490-497
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• 2007

A Combined sewer overflows (CSOs) are themselves a significant source of water pollution. Therefore, the control of urban drainage for CSOs reduction and receiving water quality protection is needed. Examples in combined sewer systems include downstream storage facilities that detain runoff during periods of high flow and allow the detained water to be conveyed by an interceptor sewer to a centralized treatment plant during periods of low flow. The design of such facilities as stormwater detention storage is highly dependant on the temporal variability of storage capacity available (which is influenced by the duration of interevent dry periods) as well as the infiltration capacity of soil and recovery of depression storage. As a result, a continuous approach is required to adequately size such facilities. This study for the continuous long-term analysis of urban drainage system used analytical probabilistic model based on derived probability distribution theory. As an alternative to the modeling of urban drainage system for planning or screening level analysis of runoff control alternatives, this model have evolved that offer much ease and flexibility in terms of computation while considering long-term meteorology. This study presented rainfall and runoff characteristics of the subject area using analytical probabilistic model. This study presented the average annual COSs and number of COSs when the interceptor capacity is in the range $3{\times}DWF$ (dry weather flow). Also, calculated the average annual mass of pollutant lost in CSOs using Event Mean Concentration. Finally, this study presented a decision of storage volume for CSOs reduction and water quality protection.