• Title/Summary/Keyword: Multi-level model

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Switching-Level Operation Analysis of MMC-based Back-to-Back Converter for HVDC Application (HVDC 적용을 위한 MMC 기반 Back-to-Back 컨버터의 스위칭레벨 동작분석)

  • Hong, Jung-Won;Jeong, Jong-Kyou;Yoo, Seong-Hwan;Choi, Jong-Yun;Han, Byung-Moon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.9
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    • pp.1240-1248
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    • 2013
  • This paper describes a switching-level operation analysis of BTB(Back-To-Back) converter for HVDC(high voltage DC) application based on MMC(modular multi-level converter). A switching-level operation analysis for BTB converter is very important to understand the converter operation in detail and check the voltage and current transients in each components. However, the development of switching-level simulation model for the actual size BTB Converter is very difficult because the MMC normally has more than 150 sub-modules for each arm. So, a switching level simulation model for the 11-level MMC-based BTB converter was developed with PSCAD/EMTDC software, which has 12 sub-modules for the positive arm and another 12 sub-modules for the negative arm. The DC-voltage balance algorithm, the circulating-current reduction algorithm, the harmonic reduction algorithm, and the redundancy operation algorithm were included in this simulation model. The developed simulation model can be utilized to analyze the MMC-based BTB converter for HVDC application in switching level and to develop the protection scheme for the MMC-based BTB converter for HVDC application.

Optimal Spare Part Level in Multi Indenture and Multi Echelon Inventory Applying Marginal Analysis and Genetic Algorithm (한계분석법과 유전알고리즘을 결합한 다단계 다계층 재고모형의 적정재고수준 결정)

  • Jung, Sungtae;Lee, Sangjin
    • Korean Management Science Review
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    • v.31 no.3
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    • pp.61-76
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    • 2014
  • There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

Social Work Practitioner's Job Performance - a Multi-Level Analysis - (사회복지 종사자의 직무수행에 관한 다수준 연구)

  • Cho, Sung-Woo;Um, Myung-Yong
    • Korean Journal of Social Welfare
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    • v.61 no.4
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    • pp.137-161
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    • 2009
  • In an effort to identify predictors of job performance, research studies in social work administration has been so far on the individual practitioners' levels of knowledge and skills, which could be used in a workplace. As the theoretical concept of organizational environment was fully introduced into social work administration research, however, studies on practitioners' job performance began to have interest in the team or the organizational level variables as well as individual level variables. Along the course of this tendency, this study attempted to test the effect of individual, team, and organizational level variables on the job performance of human service workers. The individual level variables consisted of knowledge, skills, job satisfaction, personality, and counter-productive work behaviors of workers. The team or the organizational level variables included situational constraint, organizational justice, job characteristics, government-dependency, and inter-organizational cooperation. Multi-level complex survey data collected by cluster sampling method from 314 practitioners in 23 organizations were analyzed using Hierarchial Linear Model. Results showed that both task and contextual performance were affected by individual, team, and organizational level variables in various ways.

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Multi-level structural modeling of an offshore wind turbine

  • Petrini, Francesco;Gkoumas, Konstantinos;Zhou, Wensong;Li, Hui
    • Ocean Systems Engineering
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    • v.2 no.1
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    • pp.1-16
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    • 2012
  • Offshore wind turbines are complex structural and mechanical systems located in a highly demanding environment. This paper proposes a multi-level system approach for studying the structural behavior of the support structure of an offshore wind turbine. In accordance with this approach, a proper numerical modeling requires the adoption of a suitable technique in order to organize the qualitative and quantitative assessment in various sub-problems, which can be solved by means of sub-models at different levels of detail, both for the structural behavior and for the simulation of loads. Consequently, in a first place, the effects on the structural response induced by the uncertainty of the parameters used to describe the environmental actions and the finite element model of the structure are inquired. After that, a meso-level FEM model of the blade is adopted in order to obtain the detailed load stress on the blade/hub connection.

Development of an IGVM Integrated Navigation System for Vehicular Lane-Level Guidance Services

  • Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • v.5 no.3
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    • pp.119-129
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    • 2016
  • This paper presents an integrated navigation system for accurate navigation solution-based safety and convenience services in the vehicular augmented reality (AR)-head up display (HUD) system. For lane-level guidance service, especially, an accurate navigation system is essential. To achieve this, an inertial navigation system (INS)/global positioning system (GPS)/vision/digital map (IGVM) integrated navigation system has been developing. In this paper, the concept of the integrated navigation system is introduced and is implemented based on a multi-model switching filter and vehicle status decided by using the GPS data and inertial measurement unit (IMU) measurements. The performance of the implemented navigation system is verified experimentally.

MULTI-LAYERED PRODUCT KNOWLEDGE MODEL (다중 레이어 기반 제품 지식 모델)

  • Lee J.H.;Suh H.W.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.65-70
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    • 2005
  • This paper introduces an approach to multi-layered product knowledge model for collaborative engineering environment. The participants in collaborative engineering want to share and reason product knowledge through internet without any heterogeneity and ambiguity. However the previous knowledge models are limited in providing those aspects. In this paper, the collaborative engineering domain is analyzed and then the product knowledge is organized into four levels such as product context model, product specific model, product design model and product manufacturing model. The four levels are represented by first-order logic in layered fashion. The concepts and the instances of a formal ontology are used for recursive representation of the four levels. The instances of the concepts of an upper level like product context model are considered as the concepts of an adjacent lower level like product specific model, and this mechanism is applied to the other levels. These logic representations are integrated with the schema and the instances of a relational database. OWL representation of the four levels is defined through the integration of the logic representation and OWL primitives. The four product knowledge models have their major representation according to the characteristics of each model. This approach enables engineer to share product knowledge through internet without any ambiguity and utilize it as basis for additional reasoning.

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A 3-cell CCI(Cell-to-Cell Interference) model and error correction algorithm for Multi-level cell NAND Flash Memories (다중셀 낸드 플래시 메모리의 3셀 CCI 모델과 이를 이용한 에러 정정 알고리듬)

  • Jung, Jin-Ho;Kim, Shi-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.48 no.10
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    • pp.25-32
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    • 2011
  • We have analyzed adjacent cell dependency of threshold voltage shift caused by the cell to cell interference, and we proposed a 3-adjacent-cell model to model the pattern dependency of the threshold voltage shift. The proposed algorithm is verified by using MATLAB simulation and measurement results. In the experimental results, we found that accuracy of the proposed simple 3-adjacient-cell model is comparable to the widely used conventional 8-adjacient-cell model. The Bit Error Rate (BER) of LSB and of MSB is improved by 28.9% and 19.8%, respectively, by applying the proposed algorithm based on 3-adjacent-cell model to 20nm-class 2-bit MLC NAND flash memories.

Factors Affecting Patient Moving for Medical Service Using Multi-level Analysis (환자이동에 영향을 미치는 개인 및 병원요인 분석)

  • Kim, Sun Hee;Lee, Hae Jong;Lee, Kwang Soo;Shin, Hyun Woung
    • Korea Journal of Hospital Management
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    • v.19 no.4
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    • pp.9-20
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    • 2014
  • The purpose of this study is to find out factors affecting patient moving to receive medical service. This study is analyzed by multi-level model with patient and hospital level by using SAS 9.3. Total number of patients is 600,000 persons for inpatients and 550,000 patients for outpatients. The degree of the factors, which is combined with personnel factor and hospital factor, can be analyzed by Intra-Class Correlation (ICC). The percentage of group(hospital) level variance of the total variance for out-bound moving case are 30.6% at inpatients, and 28.3% at outpatients. And the percentage of hospital level variance of the total variance for moving distance, are 26.7%, 32,5% respectively. Conclusionally, although the main factor of moving is patient level, hospital is also very important factor to make decision to go out-bound. It contributed to about 1/3 for hospital choice. And, when the one make decision, he will consider the hospital type, number of bed, and training institute in hospital level. Through this study to find out hospital factors affecting patient moving for medical service, it must be continued to find out which factors have more influence to choice the hospital among disease type after this.

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Small Target Detection in Multi-Resolution Image Using Facet Model (다중 해상도 영상에서 페이싯 모델을 이용한 초소형 표적 검출)

  • Park, Ji-Hwan;Lee, Min-Woo;Lee, Chul-Hun;Joo, Jae-Heum;Nam, Ki-Gon
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.2
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    • pp.76-82
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    • 2011
  • In this paper, we propose the technique to detect the location and size of the small target in multi-resolution image using cubic facet model. The input image is reduced by the multi-resolution and we obtain the multi-resolution images. We apply the facet model and the local maxima conditions to the multi-resolution images of each level. And then, we detect the location of the small target. We estimate that the location at the maximum of the $D_2$ which means the local maxima value of the facet model in the multi-resolution images is the location of the small target. We can detect the small target of the various size about the multi-resolution images of each level. In this paper, we experimented in the various infrared images with the small target. The method using the typical facet model applies a mask. However, the proposed method applies a mask in the multi-resolution images. We verified to vary the mask size and differ the size of the small target. The proposed algorithm can detect the location and size of the small target.

Application of Multi-periodic Harmonic Model for Classification of Multi-temporal Satellite Data: MODIS and GOCI Imagery

  • Jung, Myunghee;Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.35 no.4
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    • pp.573-587
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    • 2019
  • A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.