• Journal of Korea Multimedia Society
• /
• v.21 no.3
• /
• pp.423-431
• /
• 2018

In this paper, we try to verify a normative module based house design procedure consisted of several sequential steps. The first step is to suggest formalization of designing so that we could clarify each phase and operation we are adopting in our design process. The second step is the clearing up the conceptual schema of traditional skills that we adopt and utilize from traditional Hanok framing techniques. The third step is to formulate adequate modular kits for the assembly of house design solutions for the schematic, conceptual and preliminary phases of designing. The fourth step is to implementing our ideas and methods to a proper computational platform such as Unity3D. The final step is to verify our symbolic descriptions of design formalization with the output of our experiments so that we have better understanding of design reasoning characteristics such as in house design.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.10
• /
• pp.397-406
• /
• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• The Mathematical Education
• /
• v.63 no.3
• /
• pp.505-526
• /
• 2024

The goal of this study was to derive implications for the design of teacher training programs related to boxplots by examining the statistical reasoning patterns of mathematics teachers in group comparison tasks using boxplots. For this purpose, 48 secondary mathematics teachers who participated in a teacher statistics camp at a local office of education were selected as participants. Four sessions of teacher training were then conducted, including basic statistical concepts related to boxplots and group comparison activities using them. Afterwards, surveys with group comparison questions using boxplots and online interviews were conducted. The collected data were analyzed with a focus on the research questions. As a result, most participants relied on summary and spread elements to reason when comparing two groups using boxplots. On the other hand, participants paid little attention to shift and signal elements, and no responses using sampling elements were identified. Additionally, the overall comparative reasoning level of the participants was primarily at level 1 with the highest frequency (44%), and no responses reached level 3. Based on these research results, this paper derives implications for the design of teacher training programs related to boxplots and provides suggestions for follow-up research.

• Korean Journal of Computational Design and Engineering
• /
• v.10 no.4
• /
• pp.262-273
• /
• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.114-117
• /
• 2005

An expert system is a system that employs human knowledge captured in a computer to solve problem that ordinarily require human expertise. Well-designed expert systems imitate the reasoning processes experts use to solve specific problem. Specially, expert systems are used to the engineer in manufacturing industry for the process control, production management and system management. In this paper, we propose the design process expert system for product design process in manufacturing industry and we present introduction and contents of design process expert system methodology and software for the air purifier design system. This system will be helpful to improvement of design process for the air purifier production.

• Journal of the Ergonomics Society of Korea
• /
• v.17 no.1
• /
• pp.37-46
• /
• 1998

A human sensibility ergonomics design supporting system was applied to the product development for the customer's satisfaction based on ergonomics technology. The system is composed of three major subsystems such as customer's sensibility analysis, inference mechanism, and presentation technology. The main approaches of the system are to analyze customer's sensibilities and to translate them into product design elements. The purpose of this paper is to develop a design supporting system in which the relationship between customer's sensibility and product design elements is reasoned by a MADM(Multi-Attribute Decision Making) fuzzy model. In this model, three variables such as multiple correlation coefficients, partial correlation coefficients, and category scores were used in reasoning process. The weighted value of the words were also considered in fuzzy decision process. As a case study, the design supporting system with the MADM fuzzy model was applied to the personnel computer design.

• Journal of Christian Education in Korea
• /
• v.78
• /
• pp.231-262
• /
• 2024

This study aims to explore the impact of learners' gratitude tendencies on computer reasoning and digital efficacy in a Christian program utilizing metaverse, generative AI, and Scratch at each stage based on design thinking (Chapter I). The subjects of the study are learners who participated in a youth Christian program for two weeks on January 20th and 27th, 2024, consisting of 22 middle and high school students. Gratitude tendencies, computer reasoning, and digital efficacy were measured through post-program surveys, and simple regression analysis was conducted. Open-ended survey questions were used for learner perception analysis (Chapter II). The research results showed that learners' gratitude tendencies significantly influence computer reasoning. Additionally, learners' gratitude tendencies significantly affect confidence and familiarity among the sub-dimensions of digital efficacy, while not showing a significant impact on usefulness. The significance of this study lies in specifically exploring learners' experiential perceptions in metaverse, generative AI, and Scratch utilization in design thinking-based edutech programs in Christian education. It is hoped that the results.

• KIISE Transactions on Computing Practices
• /
• v.21 no.12
• /
• pp.774-779
• /
• 2015

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner using Apache Spark, an in-memory high speed cluster computing environment, which is effective for sequencing and iterating component reasoning jobs. The proposed reasoner can not only check the integrity of a large-scale spatial knowledge base representing topological and directional relationships between spatial objects, but also expand the given knowledge base by deriving new facts in highly efficient ways. In general, qualitative reasoning on topological and directional relationships between spatial objects includes a number of composition operations on every possible pair of disjunctive relations. The proposed reasoner enhances computational efficiency by determining the minimal set of disjunctive relations for spatial reasoning and then reducing the size of the composition table to include only that set. Additionally, in order to improve performance, the proposed reasoner is designed to minimize disk I/Os during distributed reasoning jobs, which are performed on a Hadoop cluster system. In experiments with both artificial and real spatial knowledge bases, the proposed Spark-based spatial reasoner showed higher performance than the existing MapReduce-based one.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.107-114
• /
• 2020

This study was conducted to examine the effects of simulation-based education on the clinical reasoning competence, clinical competence, and satisfaction with simulation experience (SSE). The research design was one group pretest-posttest. Study participants were 89 third-year nursing students from C University in G city, who were engaged the simulation-based education for eight weeks from August to October 2019. Learning scenario titles were blood transfusion reaction patient care with postoperative total hip replacement, hypoglycemia patient care with diabetes mellitus, and hyperkalemia patient care with liver cirrhosis. The data were analyzed by paired t-test using SPSS Win 23.0 program. After applying simulation-based education, nursing students' clinical reasoning competence (t=-17.082, p<.001) and clinical competence(t=-18.40, p<.001) improved significantly. SSE score was 4.65 out of 5 points. The results indicate that the simulation-based education in this study gave the students the experience of providing qualified and secure nursing care under conditions similar to those in the real clinical field. To improve the clinical reasoning competence and clinical competence of nursing students, various cases scenarios are developed and simulation-based education should be applied to more subjects in the nursing curriculum.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.3
• /
• pp.42-52
• /
• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.