• Journal of the Ergonomics Society of Korea
• /
• v.23 no.3
• /
• pp.73-88
• /
• 2004

This study was contrived Hierarchical Information Search (HIS) model. HIS model is based on a “cognitive process” in which model, comprising basic human information processing mechanize and information interaction. Its process include 3 semantic cognitive processes: Schema-Association LTM, Form Domain, and Alternative Selection. Design methodology consists to elicitate memory, thinking and cognitive response variables. In case study, menu structure of mobile phone was applied. In result, a correlation between predictive error rate and real error rate was .892. and a correlation between selective and real reaction time was .697. This present to suggest a model of how the methodology could be applied to real system design effectively when this was used. HIS model could become one of the most important factors for success of product design. In the perspective, the systemic methodology would contribute to design a quantitative and predictive system.

• Knowledge Management Research
• /
• v.9 no.4
• /
• pp.35-49
• /
• 2008

The purpose of the study is to develop and validate an instructional design model from the perspective of the knowledge creation. To serve the purpose, the researcher conducted 1) literature review to find causal relationship model among knowledge creation factors and to propose a hypothetical instructional design model, 2) data analysis with 50 senior level e-Learning instructional designers, and 3) testing the fitness of the proposed model and relevant causal-relational hypotheses. Results indicate; 1) the proposed model fit to the empirical evidence, 2) 6 hypotheses among 11 were validated. A typical instructional designer's personal competency was evidenced as the most powerful independent variable that predicted knowledge acquisition, knowledge sharing, and the application of the instructional models. However, the expected effect of instructional design models toward other dependent variable was not be found. In addition, further suggestions for the future research are addressed.

• Korean Institute of Interior Design Journal
• /
• no.19
• /
• pp.121-127
• /
• 1999

The objective of this study was to criticize the model house of apartment and suggest a evaluation model which could be used as an effective tool. The evaluation model had been developed based on the theoretical framework suggested by previous results of research related on housing design, which comprised the following four components : 1) the paradigm of future home and life-style, 2) marketing effects of housing developer, 3) goals and principles of housing design and 4) results of user-preferences study, an evaluation model was suggested as a preliminary form which would be modified in detail after series of tests in the field. The evaluation model will be used to provide standardized criteria for the quality of model houses, and eventually help to improve the quality of apartment housing design by balanced information from theorist, user and developer.

• Korean Journal of Computational Design and Engineering
• /
• v.12 no.2
• /
• pp.101-108
• /
• 2007

As 3D solid modeling has been widely used in designing products, solid models of the products are directly used in various applications such as engineering analysis and process planing. However, the fully-detailed solid models may not be necessary in some application. For example, it is often more efficient to use simplified model of part of engineering analysis. Generation of mesh for the complex original model requires a quite amount of time, and the consequence of finite element analysis may not be desirable due to small and detailed geometry in the model. In this paper, a method to simplify solid models of machined part is presented. This method decomposes the delta volume of machined part, and uses the decomposed volumes to simplify the solid model. Since this method directly recognizes the features to be removed from the final model, it is independent of not only design features of specific CAD system, but also designer's design practice of design sequences.

• Advances in Computational Design
• /
• v.5 no.4
• /
• pp.381-396
• /
• 2020

This study aimed to develop an optimal model of transportation for people with disabilities. To achieve this goal, powers of research and design should be involved, including CAD software. This paper investigates both: the concept of optimal model of transportation for people with disabilities (functional, ergonomic, constructive, technological and aesthetic solutions included); and its implementation as a fully-fledged 3D-model designed in SolidWorks environment. The optimal model of transportation is complex and consists of two objects. The first object is for indoors that is a wheelchair, the second one is for street driving that is an individual vehicle. The optimal model of transportation is universal and multifunctional, which have become possible with parametric feature-based approach utilized in SolidWorks.

• Korean Journal of Hydrosciences
• /
• v.7
• /
• pp.61-75
• /
• 1996

The purpose of this study is to develop an efficient model for the least cost design of multi-site detention systems. The IDP (Incremental Dynamic Programming) model for optimal design is composed of two sub-models : hydrologic-hydraulic model and optimization model. The objective function of IDP is the sum of costs ; acquisition cost of the land, construction cost of detention basin and pumping system. Model inputs include channel characteristics, hydrologic parameters, design storm, and cost function. The model is applied to the Jung-Rang Cheon basin in Seoul, a watershed with cetention basins in multiple branching channels. The application results show that the detention system can be designed reasonably for various conditions and the model can be applied to multi-site detention system design.

• Advances in Computational Design
• /
• v.3 no.4
• /
• pp.367-384
• /
• 2018

The consideration of constructability issues at the design stage can lead to improved construction performance with smooth project delivery and savings in time and money. Empirical studies demonstrate the value obtained by integrating construction knowledge with the building design process, and its benefits for owners, contractors and designers. However, it is still a challenge to implement the concept into current design practice. There is a need for a decision support tool to aid designers in reviewing their design constructability, deploying current technological tools, such as BIM. Such tools are beneficial at the conceptual design stage when there is a room to improve the design significantly with less incurred cost. This research investigates how current process- and object-oriented models can be used to assess design constructability. It proposes a BIM-based model using embedded information within the design environment to conduct the assessment. The modelling framework is demonstrated in four key parts; namely, the conceptual design model, the constructability assessment model, the assessment process model and the decision-making phase. Each is associated with a set of components and functions that contribute towards the targeted constructability assessment outcomes. The proposed framework is the first to combine a numerical assessment system and a rule-based system, allowing for both quantitative and qualitative approaches. The modelling framework and its implementation through a prototype are described in this paper. It is believed that this framework is the first to enable users to transfer their construction knowledge and experience directly into a design platform linked to BIM models. The assessment criteria can be customised by the users who can reflect their own constructability preferences into various specialised profiles that can be added to the constructability assessment model. It also allows for the integration of the assessment process with the design phase, facilitating the optimisation of constructability performance from the early design stage.

• Journal of Power System Engineering
• /
• v.11 no.3
• /
• pp.66-72
• /
• 2007

This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

• Journal of the Korean Society of Safety
• /
• v.27 no.5
• /
• pp.148-157
• /
• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.1
• /
• pp.47-55
• /
• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.