• 한국실천공학교육학회논문지
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• 제4권2호
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• pp.129-135
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• 2012

전기자동차들을 수학적으로 모델링하고 시뮬레이션 하는 많은 방법들이 있다. 전기 자동차의 각 요소들은 다른 물리적인 배경과 모델들을 갖고 있으나, 하나의 수학적 모델로 구성하기란 어려우므로 다양한 물리적 모델이 요구된다. 시뮬레이션이 목적에 따라 수행할 시뮬레이션에 관한 디양한 레벨들이 있다. 즉, 개념 체계 레벨, 회로 레벨, 더 상세한 요소레벨로 구성된다. 본 연구에서는 전기 자동차에서 여러 가지 요소들에 대한 다양한 물리적 모델들과, 다중레벨 시뮬레이션에 관하여 연구하고자 한다. 또한, 본 시뮬레이션 방법은 공학교육에 학습효과를 향상 시킬 수 있다.

• 한국병원경영학회지
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• 제20권1호
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• pp.53-64
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• 2015

Our objective was to evaluate differences in linear regression versus multilevel(cross-level interaction model) modeling for affecting factors lumbar discectomy. The data were used in 2011 patients with HIRA sample data. Total number of analysis is 3,641 patients and 248 hospitals. The results of research model showed that the type and location of the hospital-level factors were significant. However, all factors of patient-level were similar in the two models. Therefore, it requires the selection of an appropriate model for a more accurate analysis of the influencing factors in the daily medical charge.

• Structural Engineering and Mechanics
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• 제61권6호
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• pp.807-816
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• 2017

In this paper, we introduce an efficient new model reduction method, named the automated static condensation method, which is developed for the local analysis of large finite element models. The algebraic multilevel substructuring procedure is modified appropriately, and then applied to the original static condensation method. The retained substructure, which is the local finite element model to be analyzed, is defined, and then the remaining part of the global model is automatically partitioned into many omitted substructures in an algebraic perspective. For an efficient condensation procedure, a substructural tree diagram and substructural sets are established. Using these, the omitted substructures are sequentially condensed into the retained substructure to construct the reduced model. Using several large practical engineering problems, the performance of the proposed method is demonstrated in terms of its solution accuracy and computational efficiency, compared to the original static condensation method and the superelement technique.

• Physical Therapy Rehabilitation Science
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• 제10권3호
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• pp.328-336
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• 2021

Objective: The purpose of this study was to investigate the effect of cervical range of motion training on the change in respiratory function growth rate at the group and individual level in stroke patients and stroke patients with tracheostomy tube. Design: A Multilevel Growth Model Methods: 8 general stroke patients and 6 stroke patients who had a tracheostomy tube inserted were subjected to cervical range of motion training 3 times a week for 4 weeks. Force vital capacity (FVC), Forced expiratory volume in the first second (FEV1), Forced expiration ratio (FEV1/FVC) and Manual assist peak cough flow (MPCF) were measured. Data were analyzed using descriptive statistics and multilevel analysis with HLM 8.0. Results: A significant difference was found in the respiratory function analysis growth rate of the entire group (p<0.05), and two groups were added to the research model. The linear growth rate of respiratory function in patients with general stroke increased with the exception of FEV1/FVC (p<0.05). Stroke patients with tracheostomy tube showed a decreasing pattern except for FVC. In particular, MPCF showed a significantly decreased result (p<0.05). Conclusions: This study found that the maintenance of improved respiratory function in stroke patients with tracheostomy tube decreased over time. However, cervical range of motion training is still a useful method for respiratory function in general stroke patients and stroke patients with tracheostomy tube.

• 한국조사연구학회지:조사연구
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• 제18권2호
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• pp.67-98
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• 2017

본 연구의 목적은 학교폭력 잠재집단이 각 유형별 피해경험과 가해경험에 따라 어떻게 나눠지는지 살펴보고, 이러한 잠재집단 분류에 개인과 학교 요인들이 미치는 영향을 검증하는 것이다. 이를 위해 서울교육종단연구(SELS2010)의 초등학교 4학년 패널의 5차 자료 중 학교폭력을 한번 이상 경험한 학생 2,195명의 학교폭력 피해 및 가해경험에 대해 다층 잠재프로파일 모형(multilevel latent profile model)을 적용하여 분석하였다. 분석 결과, 학교폭력 가해 및 피해경험을 종류별, 수준별로 모두 고려하였을 때 가해피해 고수준집단(1.7%), 가해위주집단(2.1%), 피해위주집단(3.7%), 언어적 폭력경험집단(92.5%)의 4가지의 집단으로 분류되었다. 영향요인 검증 결과, 학생수준에서 성별, 탄력성, 자기통제력, 친구관계, 부모자녀관계가 유의하게 나타났고, 학교수준에서 교사학생관계, 학교폭력 예방교육, 학교 내 성비가 유의하게 나타났다. 본 연구는 학교폭력 가해와 피해 경험을 모두 포함하여 빈도별, 유형별로 집단을 한 번에 분류하여 이론적 논의를 확장하였고, 다층자료임을 반영하여 개인수준과 학교수준의 영향요인을 동시에 검증했다는 점에서 의의가 있다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권14호
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• pp.5787-5792
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• 2015

Background: Reported age standardized incidence rates for esophageal cancer in Iran are 0.88 and 6.15 for females and males, at fifth and the eighth ranks, respectively, of cancers overall. The present study aimed to map relative risk using more realistic and less problematic methods than common estimators. Materials and Methods: In this ecological investigation, the studied population consisted of all esophageal cancer patients in Iran from 2005 to 2007. The Bayesian multilevel space-time model with three levels of county, province, and time was used to measure the relative risk of esophageal cancer. Analyses were conducted using R package INLA. Results: The total number of registered patients was 7,160. According to the results, the three-level model with adjustment for risk factors of physical activity and smoking had the best fit among all models. The overall temporal trend was significantly increasing. At county level, Ahar, Marand, Salmas, Bojnoord, Saghez, Sarakhs, Shahroud and Torbatejam had the highest relative risks. Physical activity was found to have significant direct association with risk of developing esophageal cancer. Conclusions: Given to great variation across geographical areas, many different factors affect the incidence of esophageal cancer. Conducting further studies at the individual level in areas with high incidence could provide more detailed information on risk factors of esophageal cancer.

• Journal of Power Electronics
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• 제15권3호
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• pp.685-694
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• 2015

The power loss of the controllable switches in modular multilevel converter (MMC) HVDC transmission systems is an important factor, which can determine the design of the operating junction temperatures. Due to the dc current component, the approximate calculation tool provided by the manufacturer of the switches cannot be used for the losses of the switches in the MMC. Based on the enabled probabilities of each SM in an arm, the current analytical models of the switches can be determined. The average and RMS currents can be obtained from the corresponding current analytical model. Then, the conduction losses can be calculated, and the switching losses of the switches can be estimated according to the upper limit of the switching frequency. Finally, the thermal resistance model of the switches can be utilized, and the junction temperatures can be estimated. A comparison between the calculation and PSCAD simulation results shows that the proposed method is effective for estimating the junction temperatures of the switches in the MMC.

• Journal of Power Electronics
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• 제18권2호
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• pp.467-481
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• 2018

Modular multilevel converter (MMC)-based high-voltage direct current (HVDC) presents attractive technical advantages and contributes to enhanced system operation and reduced oscillation damping in dynamic MMC-HVDC systems. We propose an advanced small-signal multi-terminal MMC-HVDC based on dynamic phasors and state space for power system stability analysis to enhance computational accuracy and reduce simulation time. In accordance with active and passive network control strategies for multi-terminal MMC-HVDC, the matchable small-signal stability models containing high harmonics and dynamics of internal variables are conducted, and a related theoretical derivation is carried out. The proposed advanced small-signal model is then compared with electromagnetic-transient and traditional small-signal state-space models by adopting a typical multi-terminal MMC-HVDC network with offshore wind generation. Simulation indicates that the advanced small-signal model can successfully follow the electromechanical transient response with small errors and can predict the damped oscillations. The validity and applicability of the proposed model are effectively confirmed.

• 한국측량학회지
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• 제25권6_1호
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• pp.565-574
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• 2007

Because of most current cadastral systems maintain 2D geometric descriptions of parcels linked to administrative records, the system may not reflect current tendency to use space above and under the surface. The land has been used in multi-levels, e.g. constructions of multi-used complex buildings, subways and infrastructure above/under the ground. This cadastre situation of multilevel use of lands cannot be defined as cadastre objects (2D parcel-based) in the cadastre systems. This trend has requested a new system in which right to land is clearly and indisputably recorded because a right of ownership on a parcel relates to a space in 3D, not any more relates to 2D surface area. Therefore, this article proposes a 3D spatial data model to represent geometrical and topological data of 3D (property) situation on multilevel uses of lands in 3D cadastre systems, and a conceptual 3D cadastral model in Korea to design a conceptual schema for a 3D cadastre. Lastly, this paper presents the results of an experimental implementation of the 3D Cadastre to perform topological analyses based on 3D Network Data Model to identify spatial neighbors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2103-2118
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• 2024

Chinese herbal slices (CHS) automated recognition based on computer vision plays a critical role in the practical application of intelligent Chinese medicine. Due to the complexity and similarity of herbal images, identifying Chinese herbal slices is still a challenging task. Especially, easily-confused CHS have higher inter-class and intra-class complexity and similarity issues, the existing deep learning models are less adaptable to identify them efficiently. To comprehensively address these problems, a novel tiny easily-confused CHS dataset has been built firstly, which includes six pairs of twelve categories with about 2395 samples. Furthermore, we propose a ResNeSt-CHS model that combines multilevel perception fusion (MPF) and perceptive sparse fusion (PSF) blocks for efficiently recognizing easilyconfused CHS images. To verify the superiority of the ResNeSt-CHS and the effectiveness of our dataset, experiments have been employed, validating that the ResNeSt-CHS is optimal for easily-confused CHS recognition, with 2.1% improvement of the original ResNeSt model. Additionally, the results indicate that ResNeSt-CHS is applied on a relatively small-scale dataset yet high accuracy. This model has obtained state-of-the-art easily-confused CHS classification performance, with accuracy of 90.8%, far beyond other models (EfficientNet, Transformer, and ResNeSt, etc) in terms of evaluation criteria.