• Magazine of the Korean Society of Agricultural Engineers
• /
• v.45 no.3
• /
• pp.103-115
• /
• 2003

This study examines groundwater movement system analysis and movement forecast algorithm using finite element method. The target is Cheongha-myeon area, Bukgu, Pohang-city which has many difficulties in water supply during drought period. From the comparison of the differences between obtained values by WINFlOW model and observed values, it is thought that groundwater head distribution under steady flow is reflected well at the level of reliability Groundwater movement of study area shows stable pattern from western watershed to eastern coastal area while flow path is dense and steep in the center of the coastal area. The results of particle tracing for each well show a comparatively straight line from the western boundary side to the observation position at the upper area of the well, and are analyzed as it diffuses according to getting closer to the coast at the lower area of the well. The result of effect circle examination attendant on pumping amount in study area shows variation tendency that groundwater head decreases at the side and the lower area more than at the upper area of the well when groundwater flows from west to east(coast). As mentioned above, satisfactory results of groundwater movement analysis using WINFlOW model, two dimensional groundwater movement analysis model, are obtained through the great decrease of physical uncertainty of groundwater movement system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.2948-2963
• /
• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.181-183
• /
• 2003

본 연구에서는 현재 국내-외 논문을 참조하여 배전계통에 적용된 조류계산 알고리즘의 적용사례를 조사하였다. 배전계통에 적용된 조류계산알고리즘은 Power Summation Method와 Current Summation Method가 있다. 배전계통은 선로의 구조가 거의 대부분 방사상으로 성되어 있기 때문에 Newton Raphson, Gauss Seidel, Fast Decoupled 방법을 그대로 사용하기는 문제가 있다. 그래서 DistFlow, Forward/Backward sweeping 법 등이 주로 사용되어 왔다. 그러나 미래의 계통은 현재와는 또 다른 Topology로 방사상과 루프가 혼합된 형태로 다르게 구성되어야 할 것이다. 이러한 상황에서 미래의 배전계통에 대하여 적용 가능한 알고리즘을 전망하고져 한다.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.9
• /
• pp.123-134
• /
• 1999

A new forming technology has been developed to fabricate near-net shape components by using aluminum alloys with globular microstructure. The estimations of filling characteristic in the forging simulation with arbitrarily shaped dies of SSM are calculated by finite element method with proposed algorithm. The proposed model and various boundary conditions for arbitrarily shaped die are investigated with the coupling calculation between the liquid phase flow and the solid phase deformation. The simulation processes with arbitrarily shaped dies are performed on the isothermal conditions and axisymmetric problems. To analyze the forging process simulation with SSM, new stress-strain relationship for semi-solid behaviour is described, and forging the liquid flow. Furthermore, For the purpose of getting net shape of SSM, it is important to be obtain a solid fraction in forging process with arbitrarily shaped dies. To produce a automotive part which have good mechanical properties, the filling pattern in accordance with die velocity and solid fraction distribution has to be estimated for arbitrarily shaped die.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.8
• /
• pp.2805-2826
• /
• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.34 no.11
• /
• pp.73-79
• /
• 2018

In this study, for the prediction of energy consumption in the ventilator, one of the components of the air conditioning system, the predicted results were analyzed and accurate by the change in the number of neurons and inputs. The input variables of the prediction model for the energy volume of the fan were the supply air flow rate, the exhaust air flow rate, and the output value was the energy consumption of the fan. A predictive model has been developed to study with the Levenbarg-Marquardt algorithm through 8760 sets of one-minute resolution. Comparison of actual energy use and forecast results showed a margin of error of less than 1% in all cases and utilization time of less than 3% with very high predictability. MBE was distributed with a learning period of 1.7% to 2.95% and a service period of 2.26% to 4.48% respectively, and the distribution rate of ${\pm}10%$ indicated by ASHRAE Guidelines 14 was high.8.

• Industrial Engineering and Management Systems
• /
• v.15 no.4
• /
• pp.374-384
• /
• 2016

The efficiency of a supply chain can be extremely affected by its design which includes determining the flow pattern of material from suppliers to costumers, selecting the suppliers, and defining the opened facilities in network. In this paper, a multi-objective multi-echelon multi-product supply chain design model is proposed in which several suppliers, several manufacturers, several distribution centers as different stages of supply chain cooperate with each other to satisfy various costumers' demands. The multi-objectives of this model which considered simultaneously are 1-minimize the total cost of supply chain including production cost, transportation cost, shortage cost, and costs of opening a facility, 2-minimize the transportation time from suppliers to costumers, and 3-maximize the service level of the system by minimizing the maximum level of shortages. To configure this model a graph theoretic approach is used by considering channels among each two facilities as links and each facility as the nodes in this configuration. Based on complexity of the proposed model a multi-objective Pareto-based vibration damping optimization (VDO) algorithm is applied to solve the model and finally non-dominated sorting genetic algorithm (NSGA-II) is also applied to evaluate the performance of MOVDO. The results indicated the effectiveness of the proposed MOVDO to solve the model.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.781-786
• /
• 2019

We should give a realistic value on the large amounts of relevant data obtained from these studies to achieve effective objectives of the disease study which is dealing with various vital phenomenon today. In this paper, the proposed MKSV algorithm is estimated by optimal probability distribution, and the input pattern is determined. After classifying it into data mining, it is possible to obtain efficient computational quantity and recognition rate. MKSV algorithm is useful for studying the relationship between disease and gene in the present society by simulating the probabilistic flow of gene data and showing fast and effective performance improvement to classify data through the data mining process of big data.

• Journal of Korea Water Resources Association
• /
• v.38 no.3 s.152
• /
• pp.223-233
• /
• 2005

In this study, a two-dimensional model for identifying areas of erosion and deposition over a basin was developed based on the mass balance principle in a distributed model. The program consists of three steps: (a) estimation of soil erosion; (b) determination of flow amount and direction; and (c) estimation of mass balance. Soil erosion was estimated with USLE. A single-direction (SF) and a multi-direction flow algorithm (MF) were applied to estimate slope length (L). The Maximum Downhill Slope Method (MDS) and the Neighborhood Method (NBH) were used to estimate the slope degree (S). Sediment transport resulting from eroded soil was estimated using Ferro's (1998) and Swift's (2000) sediment delivery ratio (DR). The model was validated by comparing the predicted sediment yields for three basins with measured data. The developed algorithm showed that Ferro's DR method combined with the MDS and MF produced the best agreement with the dredging records of three agricultural reservoir basins in Korea.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.11
• /
• pp.1910-1915
• /
• 2008

The load analysis for the distribution system and facilities has relied on measurement equipment. Moreover, load monitoring incurs huge costs in terms of installation and maintenance. This paper presents a new model to analyze wherein facilities load under a feeder every 15 minutes using meter reading data that can be obtained from a power consumer every 15 minute or a month even without setting up any measuring equipment. After the data warehouse is constructed by interfacing the legacy system required for the load calculation, the relationship between the distribution system and the power consumer is established. Once the load pattern is forecasted by applying clustering and classification algorithm of temporal data mining techniques for the power customer who is not involved in Automatic Meter Reading(AMR), a single-line diagram per feeder is created, and power flow calculation is executed. The calculation result is analyzed using various temporal and spatial analysis methods such as Internet Geographic Information System(GIS), single-line diagram, and Online Analytical Processing (OLAP).