• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.730-731
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• 2015

This study aims at giving the framework to estimate the environmental load at planning and schematic phase. With increasing awareness of environmental issues, the effort to reduce the environmental impacts caused by human activity has been increasingly enlarged. So far most of researches estimating CO₂ emissions have analyzed energy consumption based on BOQ (Bills of Quantity) acquired after detailed design. There is also lack of reliability in the estimated environmental impact using the basic unit of a facility at the planning stage, because it uses a limited specific section of historical data. Thus, this study is targeted at developing framework to assess reliable environmental loads based on information available at project early phases by making case-bases from historical design information on PSC Beam Bridge. Historical database is built on the basis of the LCA (Life Cycle Assessment) and in order to set input information for estimating model, the literature about information in an early project phase are reviewed. Using the information available in the planning and schematic design stage, the Framework is presented to estimate the environmental load in an early stage in the project. Developing an environmental load estimation model in accordance with the Framework presented in this study, it is expected that the environmental load in the initial project phase can be estimated more quickly and accurately.

• 한국IT서비스학회지
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• 제10권2호
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• pp.235-245
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• 2011

Early criticality prediction models that determine whether a design entity is fault-prone or not are becoming more and more important as software development projects are getting larger. Effective predictions can reduce the system development cost and improve software quality by identifying trouble-spots at early phases and proper allocation of effort and resources. Many prediction models have been proposed using statistical and machine learning methods. This paper builds a prediction model using Support Vector Machine(SVM) which is one of the most popular modern classification methods and compares its prediction performance with a well-known prediction model, BackPropagation neural network Model(BPM). SVM is known to generalize well even in high dimensional spaces under small training data conditions. In prediction performance evaluation experiments, dimensionality reduction techniques for data set are not used because the dimension of input data is too small. Experimental results show that the prediction performance of SVM model is slightly better than that of BPM and polynomial kernel function achieves better performance than other SVM kernel functions.

• 한국실내디자인학회논문집
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• 제33호
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• pp.27-35
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• 2002

The qualify of preschool education is related to the qualify of the physical environment, This research is aiming to develop and validate the set of scales for the measurement of physical quality of the interior spaces in child care facilities. The research has been in three major phases: (1)the development of indicative sub-scales for the description, measurement and evaluation of the physical designed quality of early childhood environments (2)two rounds of iterative phases of reliability and validity testing of the scales through expert panels and observational field-testing and (3)implications for future research to be done. 13 sub-scales were developed, which are based on Moore's 15 design principal for child care environments. And each sub-scale includes several evaluation items based upon developmental theory, existing empirical literature, and Korean, Australian and American child care standards. This set of scales will (1)aid research on the effects of environmental variables on quality of child care facilities for infants, toddlers, and preschoolers; (2)permit evaluation of such environments to identify areas of needed improvement; and (3)provide information for policy makers, parents, administrators, and designers/architects.

• Educational Technology International
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• 제20권1호
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• pp.25-55
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• 2019

The core purpose of the study is to develop and validate an ADDIE model based instructional model for English Language Teaching (ELT) in early childhood classroom in Bangladesh as an aid to teachers to reconstruct their knowledge and experience more strategically, and for them to design and implement their instruction more structurally. This study is developmental in nature which has been divided in five phases as follows. Phase I: Existing methods and instructional strategy review, Phase II: Instructional model development, Phase III: Delphi 1st round, Phase IV: Delphi 2nd round and Phase V: Model validation. After reviewing relevant literature and existing strategy in phase I, the 1st version of instructional model is made phase II. Next in phase III and phase IV, two rounds of Delphi have been conducted where experts related to different concerning areas of this study reviewed the 1st version and gradually the final version of the instructional model is made. Finally, the instructional model for English teachers of early childhood classroom in Bangladesh got validated by the same Delphi panelists in Phase V. In respect with each phases of ADDIE, the instructional model elaborates the 1) representative key points, 2) instructors' activities prescribed for the instructors, 3) supporting strategies. Both the conceptual and procedural models are included in this study for clearer identification of the whole process. Lastly the study provides some recommendations for instructors and practitioners on choosing the instructional model like doing prior need analysis, incorporating teacher training programs, training students, keeping on researching for finding effective teaching technique and tools and being open to changes etc. In addition, the study also acknowledges its limitations like not being able to consider the psychological factors due to time limitation. Finally, at the end the study points out the areas that welcome further research.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.643-646
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• 2002

This paper proposes an evolutionary computation approach for automated design of mechanical structures especially in its early stage of design phases. Due to the known characteristics of the stage, the approach basically involves a synthetic design method with the composition of building blocks representing the elements of mechanical objects. In order for the building blocks to be more suitable for representation and evolution of mechanical structures, Elementary Cell Blocks (ECBs) are introduced as new building blocks. A new Darwinian evolution process for the new building blocks is also necessarily involved in the approach. We have demonstrated the implementation of the approach with the design of multi-step gear systems.

• Journal of Computing Science and Engineering
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• 제2권4호
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• pp.340-356
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• 2008

The cognitive constraints of the human mind must drive the decisions in architecture and methodology design in order that the systems we build are comprehensible. This paper presents a methodology for the design of time-triggered embedded systems that leads to understandable artifacts. We lift the design process to a higher level of abstractionto the level of computational components that interact solely by the exchange of messages. The time-triggered architecture makes it possible to specify the temporal properties of component interfaces precisely and provides temporally predictable message communication, such that the precise behavior of a large design can be studied in the early phases of a design on the basis of the component interface specifications. This paper shows how the cognitive simplification strategies of abstraction, partitioning and segmentation are supported by the time-triggered architecture and its associated design methodology to construct evolvable embedded systems that can be readily understood and modified.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.417-424
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• 2009

For a construction project to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need effective estimation strategies. Practically, parametric cost estimates are the most commonly used method in these initial phases, which utilizes historical cost data (Karshenas 1984, Kirkham 2007). Hence, compilation of historical data regarding appropriate cost variance governing parameters is a prime requirement. However, precedent practice of data mining (data preprocessing) for denoising internal errors or abnormal values is needed before compilation. As an effort to deal with this issue, this research proposed a statistical methodology for data preprocessing and verified that data preprocessing has a positive impact on the enhancement of estimate accuracy and stability. Moreover, Statistically Preprocessed data Based Parametric (SPBP) cost models are developed based on multiple regression equations and verified their effectiveness compared with conventional cost models.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권1호
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.

• 한국정보처리학회논문지
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• 제7권4호
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• pp.1112-1121
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• 2000

Design metrics that quantify the design phase play an important role in reducing system development cost because the problems in early phases of software development seriously affected the quality of the late products. Real-time systems such as telecommunication systems are so large that design quantification is more important in real-time system design. Although many metrics have been proposed, few of them are correctly validated. This paper revises the SDL metrics set proposed in earlier study [9] and perform an analytical validation o the metrics set. Axiomatic approach and dimensional analysis are used for metrics validation and the old metrics are revised ot satisfy the validation criteria.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.578-582
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• 2015

Lack of client involvement in construction of public projects has been identified as the main cause of many operational problems. Clients need to perform their roles and responsibilities effectively and efficiently at the right time and through the use of correct methods in order to have the optimum involvement required during all the construction project phases, namely, the planning, design, construction, handover, and operation and maintenance phase. This paper investigates the influence of clients' individual factors on their involvement in construction project delivery. A questionnaire survey was distributed to various government agencies of the Kingdom of Saudi Arabia (KSA). Explanatory Factory Analysis was performed to group nineteen individual factors. The factor analysis result suggests that the individual factors that can involve clients' involvement in construction projects can be grouped into five, which are: adequacy of knowledge and experience for decision making in the early stage of design; ability to communicate clearly; job satisfaction; personal skills; and expertise in design and construction.