• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.509-517
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• 2020

Geographic information system (GIS) sewer network data are a fundamental input material for urban inundation modeling, which is important to reduce the increasing damages from urban inundation due to climate change. However, the essential attributes of the data built by a local government are often missing because the purpose of building the data is the maintenance of the sewer system. Inconsistent simplification and supplementation of the sewer network data made by individual researchers may increase the uncertainty of flood simulations and influence the inundation analysis results. Therefore, it is necessary to develop a basic algorithm to convert the GIS-based sewage network data into input data that can be used for inundation simulations in consistent way. In this study, the format of GIS-based sewer network data for a watershed near the Sadang Station in Seoul and the Oncheon River Basin in Busan was investigated, and a missing data supplementing algorithm was developed. The missing data such as diameter, location, elevation of pipes and manholes were assumed following a consistent rule, which was developed referring to government documents, previous studies, and average data. The developed algorithm will contribute to minimizing the uncertainty of sewer network data in an urban inundation analysis by excluding the subjective judgment of individual researchers.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.476-484
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• 2012

Family member network of kings in Chosun dynasty shows scale free network properties as if most social networks do. One of distinct topological properties of the network is relatively high diameter that reflects dataset composed of the one generation continuously falling to next one. When k-core algorithm as a useful tool for obtaining a core network from the complex family member network was employed, it is possible to obtain hidden and valuable information from a complex network. Unfortunately, it is found that k-core algorithm is not useful tool for applying narrow and deep structural network. The family member network is composed of kings, queens, princes, and princesses. It is possible to separate sub-family members and to construct sub-family member networks such as queen-centered, prince-centered, and princess-centered networks. Sub-family member networks provide an useful and hidden information. These results provide new insight that is analyzed by network-based approaches for the family member of the kings in the Chosun dynasty.

• Journal of the Korean GEO-environmental Society
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• v.14 no.9
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• pp.31-37
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• 2013

In this study installation diameter, interval, area replacement ratio and ground hardness of applicable ground in C.G.S method should be mastered through surrounding ground by conducting modeling. Optimum artificial neural network was selected through the study of the parameter of artificial neural network and prediction model was developed by the relationship with numerical analysis and artificial neural network. As this result, C.G.S pile settlement and ground settlement were found to be equal in terms of diameter, interval, area replacement ratio and ground hardness, presented in a single curve, which means that the behavior pattern of applied ground in C.G.S method was presented as some form, and based on such a result, learning the artificial neural network for 3D behavior was found to be possible. As the study results of artificial neural network internal factor, when using the number of neural in hidden layer 10, momentum constant 0.2 and learning rate 0.2, relationship between input and output was expressed properly. As a result of evaluating the ground behavior of C.G.S method which was applied to using such optimum structure of artificial neural network model, is that determination coefficient in case of C.G.S pile settlement was 0.8737, in case of ground settlement was 0.7339 and in case of ground heaving was 0.7212, sufficient reliability was known.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.333-340
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• 2002

Embedding is a mapping an interconnection network G to another interconnection network H. If a network G can be embedded to another network H, algorithms developed on G can be simulated on H. In this paper, we first propose a method to embed between Hierarchical Cubic Network HCN(n, n) and Hierarchical Folded-hypercube Network HFN(n, n). HCN(n, n) and HFN(n, n) are graph topologies having desirable properties of hypercube while improving the network cost, defined as degree${\times}$diameter, of Hypercube. We prove that HCN(n, n) can be embedded into HFN(n, n) with dilation 3 and congestion 2, and the average dilation is less than 2. HFN(n, n) can be embedded into HCN(n, n) with dilation 0 (n), but the average dilation is less than 2. Finally, we analyze the fault tolerance of HCN(n, n) and prove that HCN(n, n) is maximally fault tolerant.

• Computers and Concrete
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• v.22 no.2
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• pp.249-259
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• 2018

This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi-Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.560-567
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• 2020

Incremental Sheet Forming (ISF) is a unique sheet-forming technique. The process is a die-less sheet metal manufacturing process for rapid prototyping and small batch production. In the forming process, the critical parameters affecting the formability of sheet materials are the tool diameter, step depth, feed rate, spindle speed, etc. This study examined the effects of these parameters on the formability in the forming of the varying wall angle conical frustum model for a pure Al3004 sheet with 1mm in thickness. Using Minitab software based on Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA), a second order mathematical prediction model was established to predict and optimize the wall angle. The results showed that the maximum forming angle was 87.071° and the best combination of these parameters to give the best performance of the experiment is as follows: tool diameter of 6mm, spindle speed of 180rpm, step depth of 0.4mm, and feed rate of 772mm/min.

• Journal of the Korea Concrete Institute
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• v.16 no.2 s.80
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• pp.277-282
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• 2004

In a hardened concrete, diffusion of oxygen, carbon dioxide, aggressive ions, and moisture from the environment to the concrete takes place through the pore network. It is well known that making dense cement matrix enhances the durability of concrete as well as all the characteristics including strength of concrete. In this paper,9 mix concretes with water to cementitious material ratio (40,45, and $50\%$) and replacement ratio of GGBFS (40 and $60\%$ of cement by weight) were studied on the micro-pore structure by mercury intrusion porosimetry and the accelerated chloride diffusion test by potential difference. From the results the average pore diameter and accelerated chloride diffusivity of concrete were ordered NPC > G4C > G6C. It is concluded that there is a good correlation between the average pore diameter and the chloride diffusivity, and the mineral admixtures has a filling effect, which increases the tortuosity of pore and makes large pores finer, on the pore structure of cement matrix due to the latent hydraulic reaction with hydrates of cement.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.6
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.1081-1084
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• 2006

MVPN(Mobile Virtual Private Network)은 이동단말을 사용하는 이동근무자가 지역적 제한 없이 VPN 서비스를 제공받을 수 있도록 하는 기술이다. 현재 IPsec-based VPN의 비중을 고려해볼 때, MVPN 기술은 Mobile 사용자에게 이동성을 제공하기 위한 Mobile IP프로토콜과 IPsec 기반 VPN 기술의 공존이 주된 연구 내용이다. mobile IP가 IPsec-based VPN GW(Gateway)와 동작할 경우 비호환성 문제가 발생한다. IETF에서는 두 프로토콜 간의 비호환성을 해결하기 위해VPN GW의 외부에 홈 에이전트(x-HA)를 새롭게 추가하는 방안이 연구되고 있다. 이에, AAA(Authentication, Authorization, Accounting) 서버를 이용하여 신뢰성 있는 x-HA를 동적으로 할당하는 방안이 제시되었으나, 세션 키의 외부 노출과 네트워크 간 이동 시 최초 핸드오프 시간이 오래 걸리는 한계를 지닌다. 본 논문은 이와 같은 문제점을 해결하여 이동하는 원격 VPN 사용자에게 보다 안전하며 핸드오프 지연시간이 최소화된 통신을 제공하는 방안을 제안한다.

• Journal of electromagnetic engineering and science
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• v.4 no.4
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• pp.150-155
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• 2004

Universal design equations are presented for the H-plane T-junction power divider with a circular conducting post in a rectangular waveguide. For a given operating frequency and power split ratio, the post offset from the T-junction center line, the distance between the post and the waveguide wall, and the post diameter can be adjusted to obtain a minimum reflection at the input waveguide. Optimum values of the post offset are given in terms of the normalized frequency and the power split ratio. Corresponding values of the post diameter and the distance of the post from the waveguide wall are given in terms of the normalized frequency and the post offset.