• Journal of Korean Biological Nursing Science
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• 제23권3호
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• pp.170-179
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• 2021

Purpose: The aim of this study was to identify core keywords and topic groups in the 'Diabetes mellitus and mobile applications' field of research for better understanding research trends in the past 20 years. Methods: This study was a text-mining and topic modeling study including four steps such as 'collecting abstracts', 'extracting and cleaning semantic morphemes', 'building a co-occurrence matrix', and 'analyzing network features and clustering topic groups'. Results: A total of 789 papers published between 2002 and 2021 were found in databases (Springer). Among them, 435 words were extracted from 118 articles selected according to the conditions: 'analyzed by text network analysis and topic modeling'. The core keywords were 'self-management', 'intervention', 'health', 'support', 'technique' and 'system'. Through the topic modeling analysis, four themes were derived: 'intervention', 'blood glucose level control', 'self-management' and 'mobile health'. The main topic of this study was 'self-management'. Conclusion: While more recent work has investigated mobile applications, the highest feature was related to self-management in the diabetes care and prevention. Nursing interventions utilizing mobile application are expected to not only effective and powerful glycemic control and self-management tools, but can be also used for patient-driven lifestyle modification.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1181-1187
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• 2001

The radiation driven response function (R$\_$q/) for AP and HMX propellant was obtained and compared with experimental results by using a simple $\alpha$$\beta$γ flame model rather than with detailed chemistry. For an AP propellant, the profile of heat release was assumed by the experimental data. The calculated R$\_$q/ shows a frequency shift of the peak amplitude to the higher frequency and a decrease in the maximum amplitude as radiation increases. In addition, it was found the increase in the total flux could enhance the mean burning rate γ$\_$b/ while the phase differences between the radiation and resulting conduction could consequently reduce the fluctuating amplitude Δγ$\_$b/. Fortunately, this is the qualitative duplication of the behavior recently observed in the experiments of RDX propellants. For HMX, the response function R$\_$q/ has been calculated and showed a quite good agreement with the experimental data. Even though the fairly good agreement of R$\_$q/ with experimental ones, the unsteady behavior of HMX was not reproduced as the radiation input increased. This is due to lack of the material properties of HMX or the physical understanding of HMX burning at high pressure.

• Structural Monitoring and Maintenance
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• 제9권2호
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• 한국해양공학회지
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• 제36권3호
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• pp.194-210
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• 2022

Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted. Machine learning models are effective modeling tools for predicting specific parameters by learning complex relationships based on a specified dataset. In coastal and ocean engineering, various studies have been conducted to predict dependent variables such as wave parameters, tides, storm surges, design parameters, and shoreline fluctuations. Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering. Based on the results of various studies, machine learning models are an effective alternative to approaches involving data requirements, time-consuming fluid dynamics, and numerical models. In addition, machine learning can be successfully applied for solving various problems in coastal and ocean engineering. However, to achieve accurate predictions, model development should be conducted in addition to data preprocessing and cost calculation. Furthermore, applicability to various systems and quantifiable evaluations of uncertainty should be considered.

• 대한환경공학회지
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• 제36권6호
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• pp.421-428
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• 2014

상수관망의 수리학적 거동을 해석함에 있어 현재까지 제안된 일반적인 방법은 유량기반 수리해석(Demand Driven Analysis, DDA)과 압력기반 수리해석(Pressure Driven Analysis, PDA)이다. DDA는 상수관망이 정상적으로 운영되는 상태에서 수리해석 결과를 빠르게 제시할 수 있으며, PDA는 관파괴 및 관내 저압력 상태시 DDA 방법으로는 모의할 수 없는 각 절점의 실질적인 공급가능유량을 제시할 수 있다. PDA 수행에 있어 우선적으로 각 절점에서 특정 압력마다 공급가능유량을 산정할 수 있는 관계식(Head-Outflow Relationship, HOR)을 결정해야 한다. 기존 연구들에서는 상수관망을 구성하는 각 절점에서 HOR이 다르고 각 절점의 HOR 검증을 위해서는 현장데이터의 실측이 필요하다고 지적하였다. 또한 다중 관파괴 상황과 같이 수리학적 조건이 변경된 상태에서 각 절점의 HOR 특성을 파악하기 위해서는 모든 절점에 모니터링 시스템이 구축되어 있어야 하는 제약조건이 있다. 본 연구는 실제 상수관망 형태의 모의 상수관망을 제작하여 상수관망의 정상상태 및 현장에서 측정이 어려운 비정상상태 운영조건을 시나리오별로 구성하고 각 조건 하에서 절점들의 압력 및 유량을 실시간으로 확인하였다. 또한 측정된 실험결과와 기존 HOR 관계식을 비교 평가하여 최소 오차 결과를 보이는 HOR을 제시하였으며, 특정 절점에서 다중 관파괴 발생시 HOR 특성을 파악하였다. 이로부터 관파괴 위치가 다르거나 다중 관파괴가 발생하더라도 특정 절점의 압력(수두) 저하에 따른 공급가능유량의 축소 현상은 본래 대상 절점이 가지고 있는 지수함수 형태인 고유한 HOR을 따라 감소하는 것으로 확인되었다. 본 연구에서 실험을 통해 측정한 압력-유량 관계와 기존 HOR 식들을 비교한 결과 최소 오차를 보이는 지수함수 형태의 Wagner 등1)이 제안한 식을 최적의 HOR 관계식으로 제안하며, 해당 식의 지수 m은 3.0으로 적용할 것을 제안한다.

• 한국CDE학회논문집
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• 제11권1호
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• pp.49-56
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• 2006

In this study, the modeling support system was developed which can make easy and fast FE-modeling and verify the results of static and durability analysis for the lower arm, one of the important parts in automobile suspension module. It took into account of the whole complicated design processes verifying the durability coefficients evaluated by fatigue analysis, which should be used to satisfy a design criteria. To guide the FE-modeling the drive page was constructed by using HTML and XML, which was based on expert's know-hows. It is able to integrate the processes to design the lower arm in practice, so that the standardization of its FE-Modeling is achieved, consequently. The 3 dimensional CAD's geometrical data were changed automatically into pre-defined shell elements under the concept of mesh-offset technique, and then welding elements were treated to connect between target and basic surfaces constructed by the shell elements. This system has also a user interface to control boundary and load ing conditions applied in performing of the static and durability analysis, in which many load cases can be applied simply with the MPCs driven by just few mouse clicks. These were implemented on the platform of MSC.Patran and utilized ANSYS, MSC.Nastran and MSC.Fatigue as the solver of the analysis performed. The developed system brings not only significant decreasing of man-hours required in FE-modeling process, but also obtaining of satisfied qualities in analyzed results. It will be integrated in a part of virtual prototyping module of the developing e-engineering framework.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.139-150
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• 2021

Object orientation has become the predominant paradigm for conceptual modeling (e.g., UML), where the notions of class and object form the primitive building blocks of thought. Classes act as templates for objects that have attributes and methods (actions). The modeled systems are not even necessarily software systems: They can be human and artificial systems of many different kinds (e.g., teaching and learning systems). The UML class diagram is described as a central component of model-driven software development. It is the most common diagram in object-oriented models and used to model the static design view of a system. Objects both carry data and execute actions. According to some authorities in modeling, a certain degree of difficulty exists in understanding the semantics of these notions in UML class diagrams. Some researchers claim class diagrams have limited use for conceptual analysis and that they are best used for logical design. Performing conceptual analysis should not concern the ways facts are grouped into structures. Whether a fact will end up in the design as an attribute is not a conceptual issue. UML leads to drilling down into physical design details (e.g., private/public attributes, encapsulated operations, and navigating direction of an association). This paper is a venture to further the understanding of object-orientated concepts as exemplified in UML with the aim of developing a broad comprehension of conceptual modeling fundamentals. Thinging machine (TM) modeling is a new modeling language employed in such an undertaking. TM modeling interlaces structure (components) and actionality where actions infiltrate the attributes as much as the classes. Although space limitations affect some aspects of the class diagram, the concluding assessment of this study reveals the class description is a kind of shorthand for a richer sematic TM construct.

• 대한산업공학회지
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• 제12권1호
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• pp.119-131
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• 1986

Described in this paper is a modelling methodology for mass production system simulation. The mass production system under consideration consists of various types of flow lines, special purpose production facilities, conveyor lines, palletized carts, and storage facilities. This type of production system is typical in home appliance industry, automobile industry, footwear industry, etc. where a variety of product mix are mass-produced. The modelling methodology is based on the "discrete-event formalism", and an "activity-oriented world view" is adopted to formalize the system description. A distinctive feature of the modelling methodology is that only the static structure (ie, system components) is included in the fixed model. The dynamic structure of the system is specified through a "data-driven" mechanism, which is an extension of the "experimental frame" concept. Each type of system components (ie, flow line, conveyors, carts, etc.) is formally modeled by using Activity Cycle Diagrams. The issue of "model structuring" is also addressed. The modeling methodology has been successfully applied in a real simulation study of a mass production system.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2004년도 학술대회지
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• pp.47-84
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• 2004

Principal Component Analysis나 Partial Least Squares와 같은 다변량 통계 기법은 변수간의 correlation structure로부터 공정의 variance를 설명할 수 있는 latent variable를 얻고 이를 이용하여 공정을 효과적으로 modeling할 수 있는 방법으로 최근 들어 많은 관심을 얻고 있다. 하지만 PLS는 공정이 stationary state에 있다고 가정하기 때문에, 생물학적 공정의 non-stationary and time-varying behavior를 설명하기에 부적절하다. 본 논문에서는 PLS 알고리즘의 혐기성 폐수처리 공정에의 적용에 있어, 이와 같은 문제를 해결하기 위해서 adaptive PLS 알고리즘을 사용함으로써 변화하는 공정의 특성에 대응하여 모델을 update하는 방법을 이용하였다. 하지만 실시간 데이터로부터 adaptive PLS 방법을 적용하는 데에는 많은 어려움이 존재하며, 특히 outlier나 abnormal disturbance에 모델이 부적절하게 adaptation하는 문제가 발생할 수 있다. 따라서 이의 해결을 위해 adaptive PLS를 적용하는데 있어 robustness를 향상시키기 위해 monitoring index를 이용하여 abnormal data에 weight를 주고 안정적인 모델의 update가 가능하게 하는 방법을 제안하였으며, 이를 적용하여 성공적으로 혐기성 폐수처리 공정의 Output을 예측하고 효과적으로 공정을 모니터링할 수 있었다. 만들어진 PLS 모델은 산업폐수를 처리하기 위한 industrial plan에서 측정된 실제 데이터에 적용하여 그 효용성을 입증하였으며, 그 결과는 mechanistic model을 적용하기 힘든 실공정에 비교적 쉽게 implementation할 수 있는 장점이 있다.

• 한국컴퓨터그래픽스학회논문지
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• 제8권4호
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• pp.1-7
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• 2002

본 논문에서는 3차원 인체 형상 스캔 데이터로부터 팔, 다리형상을 복원하는 방법을 제시한다. 이 방법에서는 팔, 다리 스캔 데이터의 대략적인 형상을 나타내는 기반 곡면과 자세한 세부 현상을 나타내는 displacement 맵의 이중구조로 형상을 복원한다. 팔, 다리 부분의 스캔 데이터 형상은 골격을 따라 스윕하는 타원체로 근사되며, 이 타원체 스윕을 부드럽게 감싸는 envelope 곡면으로 기반 곡면을 생성한다. 타원체 스윕의 envelope 곡면은 빠른 계산을 위해 골격을 따라 추출되는 타원의 스윕 곡면으로 근사된다. 기반 곡면에 대한 스캔 데이터 점들의 displacement는 각 단면 타원으로의 매핑을 통해 스칼라 값으로 구해지며, 다단계 스플라인 함수를 이용하여 매개화된 displacement 맵을 구성한다. 이 과정에서 복원된 형상 위의 점들은 해당하는 타원체 상으로 매핑된다. 본 방법을 통하여 팔, 다리의 간결한 형상 표현을 추출할 수 있으며, 매핑된 타원체를 이용하여 형상을 빠르고 사실적으로 변형할 수 있다.