• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.81-91
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• 2013

정보 시각화는 컴퓨팅 장치의 디스플레이 성능, 연산 능력, 대량의 데이터 관리 등의 기반 기술 확충으로 더욱 발전할 수 있었으며, 웹과 함께 등장한 인터랙티브 미디어, 소셜 미디어와 같은 비정형적 빅데이터를 주요 대상으로 다루면서 최근 이슈가 되고 있다. 이러한 정보 시각화 기술은 인간의 정보 지각 능력의 중추가 되는 시각을 중심으로 집중됨에 따라 보다 직관적이고 효율적인 정보 지각과 인지를 가능하게 했지만 다른 한편으로는 시각장애인들의 정보 접근성 문제를 야기 시키기도 했다. 이에 본고에서는 정보 시각화라는 큰 틀에서 다양한 시각화 방법과 함께 시각장애인을 위한 정보 접근성에 대해서 다루고자 한다. 정보 시각화의 정의와 분류 및 최근 컴퓨팅 환경의 변화에 대응한 가시화 방법론 등의 기술 동향에 대해 살펴보고 시각장애인을 위한 정보 표현 기술의 발전 동향을 함께 서술한다.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• Journal of the Korean Orthopaedic Association
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• v.54 no.4
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• pp.353-360
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• 2019

Purpose: In the treatment of Dupuytren's contracture, the aim of optical treatment is to lower the recurrence rate and reduce complications. This paper reports the results of subtotal fasciectomy in Dupuytren's contracture, extending the excision of palmar fascial structures from the diseased to normal appearing adjacent fascial structure. Materials and Methods: From 2007 to 2017, 45 patients with Dupuytren's contracture treated by subtotal fasciectomy were reviewed retrospectively. The mean follow-up period was 45.9 months. Ninety-two digits were involved (index: 2, middle: 10, ring: 44, little: 36). The predisposing factors and affected joint were reviewed and the preoperative and postoperative contracture was measured. For clinical results, quick disabilities of the arm, shoulder, and hand (quick DASH) were used. Complications, including wound or skin problems, nerve injuries, hematoma, and complex regional pain syndrome, were assessed. Results: Preoperative flexion contracture was 43.2° in the proximal interphalangeal joint and 32.9° in the metacarpophalangeal joint. In nine cases, patients had residual contracture of 9.7° (range, 5°-20°) on average and if the total number of cases were included, the mean residual contracture was 2.3° on average. The quick DASH score at the 12 months follow-up was 12.4. The overall complication rate was 26.6%. Conclusion: Subtotal fasciectomy can be a good surgical treatment option for Dupuytren's contracture with a low recurrence and low complication rate compared to other open procedures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1049-1054
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• 2018

Keyword searching used in the past as a method of finding similar patents, and automated classification by machine learning is using in recently. Keyword searching is a method of analyzing data that is formalized through data refinement. While the accuracy for short text is high, long one consisted of several words like as document that is not able to analyze the meaning contained in sentences. In semantic analysis level, the method of automatic classification is used to classify sentences composed of several words by unstructured data analysis. There was an attempt to find similar documents by combining the two methods. However, it have a problem in the algorithm w the methods of analysis are different ways to use simultaneous unstructured data and regular data. In this paper, we study the method of extracting keywords implied in the document and using the LDA(Latent Semantic Analysis) method to classify documents efficiently without human intervention and finding similar patents.

• Journal of the Korean School Mathematics Society
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• v.22 no.3
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• pp.329-350
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• 2019

Productive struggle is a student's persevering effort to understand mathematical concepts and solve challenging problems that are not easily solved, but the problem can lead to curiosity. Productive struggle is a key component of students' learning mathematics with a conceptual understanding, and supporting it in learning mathematics is one of the most effective mathematics teaching practices. In comparison to research on students' productive struggles, there is little research on preservice mathematics teachers' productive struggles. Thus, this study focused on the productive struggles that preservice mathematics teachers face in solving a non-routine mathematics problem. Polya's four-step problem-solving process was used to analyze the collected data. Examples of preservice teachers' productive struggles were analyzed in terms of each stage of the problem-solving process. The analysis showed that limited prior knowledge of the preservice teachers caused productive struggle in the stages of understanding, planning, and carrying out, and it had a significant influence on the problem-solving process overall. Moreover, preservice teachers' experiences of the pleasure of learning by going through productive struggle in solving problems encouraged them to support the use of productive struggle for effective mathematics learning for students, in the future. Therefore, the study's results are expected to help preservice teachers develop their professional expertise by taking the opportunity to engage in learning mathematics through productive struggle.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.77-93
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• 2020

The literature has reported that hierarchical classification methods generally outperform the flat classification methods for a multi-class document classification problem. Unlike the literature that has constructed a class hierarchy, this paper evaluates the performance of hierarchical and flat classification methods under a situation where the class hierarchy is predefined. We conducted numerical evaluations for two data sets; research papers on climate change adaptation technologies in water sector and 20NewsGroup open data set. The evaluation results show that the hierarchical classification method outperforms the flat classification methods under a certain condition, which differs from the literature. The performance of hierarchical classification method over flat classification method depends on class similarities at levels in the class structure. More importantly, the hierarchical classification method works better when the upper level similarity is less that the lower level similarity.

• Korean Journal of Construction Engineering and Management
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• v.7 no.1 s.29
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• pp.73-79
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• 2006

Even though graphical simulation is very useful for construction planning, the application of graphical simulation has a limitation in dealing with objects without fixed form like earthmoving process. In this case, the mathematical/statistical simulation about the productivity of the whole processes based on the numerical data of working time, waiting time and working capacity of using equipment becomes effective. The mathematical/statistical simulation is not fully utilized in the field of construction due to the difficulties of creating process models and securing trust the numerically expressed results of simulation. In this research, the output of discrete-event simulation programs which are the most common mathematical/statistical simulation tool for construction processes were analyzed for the purpose of earthmoving process visualization. The purpose of this research is to develop a graphical simulation system that can help the construction planner select most suitable equipment and construction methods through the visualize the numerical simulation results of the working time, the queuing time as well as the amount resources etc.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.4
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• pp.7-16
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• 2005

Computer applications for engineering design evolve rapidly. Many design frameworks were developed by the simulation based systems so that organizations could achieve significant benefits due to cost reduction in designing. However, today’s transient design issue requires being adaptable to more complicated and atypical problems. In this paper the Multidisciplinary Language Runtime (MLR) design framework is developed. The MLR provides flexible and extensible interface between analysis modules and numerical analysis codes. It also supports Meta Modeling, Meta Variable, and XML script for atypical design formulation. By applying object-oriented design scheme to implement abstractions of the key components required for iterative systems analyses, the MLR provides flexible and extensible problem-solving environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.283-286
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• 2003

군집화 시 일반적으로 개별 클래스(class) 혹은 카테고리(category) 당 하나의 군집이 형성되는 결과가 선호된다. 하지만 데이터가 비정형적인 분포를 따르는 경우에는 하나의 군집으로 개별 클래스를 온전히 표현하는 것이 불가능하거나 오히려 부자연스러운 경우가 발생할 수 있다. 본 논문에서는 예제의 클래스를 알고 있는 즉, 레이블(label)된 예제들을 그렇지 않은(unlabeled) 예제들과 함께 활용하여 군집화하는 제약된 K-means (constrained K-means) 알고리즘을 위하여 보다 자연스러운 형태의 군집이 형성될 수 있도록 초기 씨드(seed, 씨앗)를 생성하는 방안을 제안한다. 레이블된 예제들을 계층적으로 군집화하면 다양한 단계에서 제약된 K-means를 위한 씨드집합을 생성할 수 있다. 본 연구에서는 각 단계의 씨드집합을 기반으로 형성된 군집결과간의 변화정도를 측정하여 가장 적절한 것으로 추정되는 씨드집합을 선정하였다. 제안한 방안을 문서 군집화 문제에 적용하여 실험한 결과 개별 클래스마다 하나의 군집을 가정하는 경우보다 더 나은 군집을 형성할 수 있음을 확인하였다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.769-778
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• 2023

This study compared and analyzed parental leave and child allowance, two major policies among solutions to the current serious low fertility rate problem, using unstructured data, and sought future directions and implications for related response policies based on this. The collection keywords were "low fertility + parental leave" and "low fertility + child allowance", and data analysis was conducted in the following order: text frequency analysis, centrality analysis, network visualization, and CONCOR analysis. As a result of the analysis, first, parental leave was found to be a realistic and practical policy in response to low fertility rates, as data analysis showed more diverse and systematic discussions than child allowance. Second, in terms of child allowance, data analysis showed that there was a high level of information and interest in the cash grant benefit system, including child allowance, but there were no other unique features or active discussions. As a future improvement plan, both policies need to utilize the existing system. First, parental leave requires improvement in the working environment and blind spots in order to expand the system, and second, child allowance requires a change in the form of payment that deviates from the uniform and biased system. should be sought, and it was proposed to expand the target age.