• Title/Summary/Keyword: Integrated modeling system

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Design Information Management System Core Development Using Industry Foundation Classes (IFC를 이용한 설계정보관리시스템 핵심부 구축)

  • Lee Keun-hyung;Chin Sang-yoon;Kim Jae-jun
    • Korean Journal of Construction Engineering and Management
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    • v.1 no.2 s.2
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    • pp.98-107
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    • 2000
  • Increased use of computers in AEC (Architecture, Engineering and Construction) has expanded the amount of information gained from CAD (Computer Aided Design), PMIS (Project Management Information System), Structural Analysis Program, and Scheduling Program as well as making it more complex. And the productivity of AEC industry is largely dependent on well management and efficient reuse of this information. Accordingly, such trend incited much research and development on ITC (Information Technology in Construction) and CIC (Computer Integrated Construction) to be conducted. In exemplifying such effort, many researchers studied and researched on IFC (Industry Foundation Classes) since its development by IAI (International Alliance for Interoperability) for the product based information sharing. However, in spite of some valuable outputs, these researches are yet in the preliminary stage and deal mainly with conceptual ideas and trial implementations. Research on unveiling the process of the IFC application development, the core of the Design Information management system, and its applicable plan still need be done. Thus, the purpose of this paper is to determine the technologies needed for Design Information management system using IFC, and to present the key roles and the process of the IFC application development and its applicable plan. This system play a role to integrate the architectural information and the structural information into the product model and to group many each product items with various levels and aspects. To make the process model, we defined two activities, 'Product Modeling', 'Application Development', at the initial level. Then we decomposed the Application Development activity into five activities, 'IFC Schema Compile', 'Class Compile', 'Make Project Database Schema', 'Development of Product Frameworker', 'Make Project Database'. These activities are carried out by C++ Compiler, CAD, ObjectStore, ST-Developer, and ST-ObjectStore. Finally, we proposed the applicable process with six stages, '3D Modeling', 'Creation of Product Information', 'Creation and Update of Database', 'Reformation of Model's Structure with Multiple Hierarchies', 'Integration of Drawings and Specifications', and 'Creation of Quantity Information'. The IFCs, including the other classes which are going to be updated and developed newly on the construction, civil/structure, and facility management, will be used by the experts through the internet distribution technologies including CORBA and DCOM.

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A Water Quality Modeling Study of Chunggye Stream during Combined Sewer OverFlow Period (합류식 하수관거 월류수 유입 기간 동안에 나타나는 청계천 수질 변화 모델 연구)

  • Yi, Hye-Suk;Park, Seok-Soon
    • Journal of Korean Society of Environmental Engineers
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    • v.27 no.12
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    • pp.1340-1346
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    • 2005
  • A water quality modeling study was performed for Chunggye stream during combined sewer overflow(CSO) period, utilizing the diagnostic system for water management in small watershed, CREEK-1(Cyber River for Environment and Economy in Korea). This system integrated geogaphic information system, data base, landscape ecological model(FRAGSTATS), watershed model(SWMM), water quality model (WASP5), and computer graphic. In this study, the watershed model and water quality model were extensively utilized so as to simulate water qualities and flow in Chunggye stream during wet periods. The Chunggye stream watershed was divided into 18 sub-basins in the watershed model and the stream reach into 11 segments in the water quality model. The watershed model was validated against field measurements of BOD, TN, TP, and flow at the downstream location, where the model results showed a reasonable agreement with the field measurements at all parameters. From this study, it was shown that the stream water quality would change along with elapsed time from rainfall start as well as rainfall intensity. The model results indicated that the water quality would significantly upgrade due to the first flush and high sewage ratio of CSO at the beginning of rainfall event, but become degraded along with the runoff increase due to dilution effect.

Analysis of Survivability for Combatants during Offensive Operations at the Tactical Level (전술제대 공격작전간 전투원 생존성에 관한 연구)

  • Kim, Jaeoh;Cho, HyungJun;Kim, GakGyu
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.921-932
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    • 2015
  • This study analyzed military personnel survivability in regards to offensive operations according to the scientific military training data of a reinforced infantry battalion. Scientific battle training was conducted at the Korea Combat Training Center (KCTC) training facility and utilized scientific military training equipment that included MILES and the main exercise control system. The training audience freely engaged an OPFOR who is an expert at tactics and weapon systems. It provides a statistical analysis of data in regards to state-of-the-art military training because the scientific battle training system saves and utilizes all training zone data for analysis and after action review as well as offers training control during the training period. The methodologies used the Cox PH modeling (which does not require parametric distribution assumptions) and decision tree modeling for survival data such as CART, GUIDE, and CTREE for richer and easier interpretation. The variables that violate the PH assumption were stratified and analyzed. Since the Cox PH model result was not easy to interpret the period of service, additional interpretation was attempted through univariate local regression. CART, GUIDE, and CTREE formed different tree models which allow for various interpretations.

A Study on the Action Potential Generations of the Vestibular Hair Cell Model with Negative Stiffness Feature (반강성 특성이 반영된 전정 유모세포 모델의 활동전위 생성에 관한 연구)

  • Kim, Dongyoung;Hong, Kihwan;Kim, Kyu-Sung;Lee, Sangmin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.9
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    • pp.190-199
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    • 2014
  • In this paper, the vestibular hair bundle feature model and integrated vestibular hair cell model were proposed. In conventional modeling studies of vestibular system, only partial mechanisms were modeled, such as the characteristics of the vestibular hair bundles without external forces or the action potential of synapse, and the study about action potential of vestibular afferent considering the characteristics of the vestibular hair bundle was not performed. The proposed integrated vestibular hair cell model reflects external forces considering negative stiffness features of each hair bundles with different regularities of hair cells and our model was compared with conventional model without external forces. As a result, irregular afferent and intermediate afferent with high ratio of firing frequency variations to the changes of external stimulation had small width of negative stiffness section, but the width of the negative stiffness of regular afferent with low ratio was similar to that of conventional negative stiffness features. And the proposed integrated vestibular hair cell model showed almost same results with conventional data with animal experiments in 11 chosen frequency bands. It is verified that our proposed hair bundle feature model is adequately modeled.

Response Modeling for the Marketing Promotion with Weighted Case Based Reasoning Under Imbalanced Data Distribution (불균형 데이터 환경에서 변수가중치를 적용한 사례기반추론 기반의 고객반응 예측)

  • Kim, Eunmi;Hong, Taeho
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.29-45
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    • 2015
  • Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

Numerical Modeling of Water Transfer among Precipitation, Surface Water, Soil Moisture and Groundwater

  • Chen, Xi;Zhang, Zhicai;Chen, Yongqin
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.2-11
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    • 2006
  • In the processes of hydrological cycle, when precipitation reaches the ground surface, water may become surface runoff or infiltrate into soil and then possibly further percolate into groundwater aquifer. A part of the water is returned to the atmosphere through evaporation and transpiration. Soil moisture dynamics driven climate fluctuations plays a key role in the simulation of water transfer among ground surface, unsaturated zone and aquifer. In this study, a one-layer canopy and a four-layer soil representation is used for a coupled soil-vegetation modeling scheme. A non-zero hydraulic diffusivity between the deepest soil layer modeled and groundwater table is used to couple the numerical equations of soil moisture and groundwater dynamics. Simulation of runoff generation is based on the mechanism of both infiltration excess overland flow and saturation overland flow nested in a numerical model of soil moisture dynamics. Thus, a comprehensive hydrological model integrating canopy, soil zone and aquifer has been developed to evaluate water resources in the plain region of Huaihe River basin in East China and simulate water transfer among precipitation, surface water, soil moisture and groundwater. The newly developed model is capable of calculating hydrological components of surface runoff, evapotranpiration from soil and aquifer, and groundwater recharge from precipitation and discharge into rivers. Regional parameterization is made by using two approaches. One is to determine most parameters representing specific physical values on the basis of characterization of soil properties in unsaturated zone and aquifer, and vegetations. The other is to calibrate the remaining few parameters on the basis of comparison between measured and simulated streamflow and groundwater tables. The integrated modeling system was successfully used in the Linhuanji catchment of Huaihe plain region. Study results demonstrate that (1) on the average 14.2% of precipitation becomes surface runoff and baseflow during a ten-year period from 1986 to 1995 and this figure fluctuates between only 3.0% in drought years of 1986, 1988, 1993 and 1994 to 24.0% in wet year of 1991; (2) groundwater directly deriving from precipitation recharge is about 15.0% t of the precipitation amount, and (3) about half of the groundwater recharge flows into rivers and loses through evaporation.

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End-to-end Packet Statistics Analysis using OPNET Modeler Wireless Suite (OPNET Modeler Wireless Suite를 이용한 종단간 패킷 통계 분석)

  • Kim, Jeong-Su
    • The KIPS Transactions:PartC
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    • v.18C no.4
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    • pp.265-278
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    • 2011
  • The objective of this paper is to analyze and characterize end-to-end packet statistics after modeling and simulation of WiFi (IEEE 802.11g) and WiMAX (IEEE 802.16e) of a virtual wireless network using OPNET Modeler Wireless Suite. Wireless internal and external network simulators such as Remcom's Wireless InSite Real Time (RT) module, WinProp: W-LAN/Fixed WiMAX/Mobile WiMAX, and SMI system, are designed to consider data transfer rate based on wireless propagation signal strength. However, we approached our research in a different perspective without support for characteristic of these wireless network simulators. That is, we will discuss the purpose of a visual analysis for these packets, how to receive each point packets (e.g., wireless user, base station or access point, and http server) through end-to-end virtual network modeling based on integrated wired and wireless network without wireless propagation signal strength. Measuring packet statistics is important in QoS metric analysis among wireless network performance metrics. Clear packet statistics is an especially essential metric in guaranteeing QoS for WiMAX users. We have found some interesting results through modeling and simulation for virtual wireless network using OPNET Modeler Wireless Suite. We are also able to analyze multi-view efficiency through experiment/observation result.

A Spatial Projection of Demand for Green Infrastructure and Its Application to GeoDesign - Evidence-Based Design for Urban Resilience - (융합도시모델링을 통한 그린인프라 수요 예측 및 지오디자인 적용 - 도시 레질리언스를 위한 근거 기반 디자인 -)

  • Kwak, Yoonshin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.5
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    • pp.30-43
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    • 2023
  • Green infrastructure(GI) is considered a key strategy in establishing sustainable communities. However, research on GI from the perspective of urban system dynamics and resilience lacks depth, as does its integration with physical design. This research addresses two primary causes. First, there is a gap in methods between existing GI planning, which considers static variables, and urban modeling research, which addresses dynamic variables. Second, there is a gap in information between landscape design and urban modeling research. To address these issues, this study proposes an integrated modeling approach in consideration of design decision-making. By combining the LEAM model and MCDA model, this study evaluates the relationship between GI services and socioeconomic growth, while spatially forecasting the geographies of GI demand in 2050. The resulting information reveals a potential degradation in ecosystem services over the region due to Chicago's sub-urbanization. This indicates that there would be a spatial shift in GI demand, emphasizing the need for comprehensive, dynamic GI strategies. This study further discusses the applications of evidence-based design in a studio environment. This study aims to contribute to the GeoDesign literature in terms of the creation of a more resilient urban environment by facilitating efficient evidence-based decision-making.

New Model-based IP-Level Power Estimation Techniques for Digital Circuits (디지털 회로에서의 새로운 모델 기반 IP-Level 소모 전력 추정 기법)

  • Lee, Chang-Hee;Shin, Hyun-Chul;Kim, Kyung-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.43 no.2 s.344
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    • pp.42-50
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    • 2006
  • Owing to the development of semiconductor processing technology, high density complex circuits can be integrated in a System-on-Chip (SoC). However, increasing energy consumption becomes one of the most important limiting factors. Power estimation at the early stage of design is essential, since design changes at lower levels may significantly lengthen the design period and increase the cost. In this paper, logic level circuits ire levelized and several levels are selected to build power model tables for efficient power estimation. The proposed techniques are applied to a set of ISCAS'85 benchmark circuits to illustrate their effectiveness. Experimental results show that significant improvement in estimation accuracy and slight improvement in efficiency are achieved when compared to those of a well-known existing method. The average estimation error has been reduced from $9.49\%\;to\;3.84\%$.

Developing an Estimation Model for Safety Rating of Road Bridges Using Rule-based Classification Method (규칙 기반 분류 기법을 활용한 도로교량 안전등급 추정 모델 개발)

  • Chung, Sehwan;Lim, Soram;Chi, Seokho
    • Journal of KIBIM
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    • v.6 no.2
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    • pp.29-38
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    • 2016
  • Road bridges are deteriorating gradually, and it is forecasted that the number of road bridges aging over 30 years will increase by more than 3 times of the current number. To maintain road bridges in a safe condition, current safety conditions of the bridges must be estimated for repair or reinforcement. However, budget and professional manpower required to perform in-depth inspections of road bridges are limited. This study proposes an estimation model for safety rating of road bridges by analyzing the data from Facility Management System (FMS) and Yearbook of Road Bridges and Tunnel. These data include basic specifications, year of completion, traffic, safety rating, and others. The distribution of safety rating was imbalanced, indicating 91% of road bridges have safety ratings of A or B. To improve classification performance, five safety ratings were integrated into two classes of G (good, A and B) and P (poor ratings under C). This rearrangement was set because facilities with ratings under C are required to be repaired or reinforced to recover their original functionality. 70% of the original data were used as training data, while the other 30% were used for validation. Data of class P in the training data were oversampled by 3 times, and Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was used to develop the estimation model. The results of estimation model showed overall accuracy of 84.8%, true positive rate of 67.3%, and 29 classification rule. Year of completion was identified as the most critical factor on affecting lower safety ratings of bridges.