• Journal of Multimedia Information System
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• 제1권2호
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• pp.119-126
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• 2014

We propose a bicycle detection system riding on people based on modified projected local binary pattern(PLBP) for vision based intelligent vehicles. Projection method has robustness for rotation invariant and reducing dimensionality for original image. The features of Local binary pattern(LBP) are fast to compute and simple to implement for object recognition and texture classification area. Moreover, We use uniform pattern to remove the noise. This paper suggests that modified LBP method and projection vector having different weighting values according to the local shape and area in the image. Also our system maintains the simplicity of evaluation of traditional formulation while being more discriminative. Our experimental results show that a bicycle and motorcycle riding on people detection system based on proposed PLBP features achieve higher detection accuracy rate than traditional features.

• 한국지진공학회논문집
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• 제10권2호
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• pp.63-71
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• 2006

동반논문(II-지반분류 개선방법)에서는 지반의 고유주기를 기준으로 지반을 분류하는 방법이 국내 지반조건에 적합한 지반분류 방법으로 제시하였다. 그러나, 지반분류 방법을 개선하여도 해석결과의 평균 스펙트럼 가속도 값과 재산정된 응답스펙트럼과 차이가 나타나는 부분이 존재한다. 이는 설계응답스펙트럼을 작성에 필요한 증폭계수를 계산하는 방법을 변경해야 해결할 수 있다. 본 논문에서는 국내 지반조건에 적합하도록 증폭계수를 재산정하기 위한 적분구간 변경에 대하여 검토하였다. 검토 결과 장주기 영역의 증폭계수 $F_v$의 적분구간은 현재 주기 0.4초${\sim}$2.0초에서 주기 0.4초${\sim}$1.5초로 변경할 경우 해석결과의 평균 스펙트럼 가속도 값과 설계응답스펙트럼이 비교적 잘 일치하는 결과를 얻을 수 있었고, 기존의 방법보다 국내 지반특성에 더 적합한 설계응답스펙트럼을 작성할 수 있었다.

• 임상간호연구
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• 제18권2호
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• pp.251-263
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• 2012

Purpose: It was necessary for developing a neonatal classification system based on nursing needs and direct care time. This study was, thus, aimed at identifying nursing activities and measuring the standard nursing practice time for developing a neonatal patient classification system in Neonatal Intensive Care Unit (NICU). Methods: The study was taken place in 8 general hospitals located in Seoul and Kyungi province, South Korea from Dec, 2009 to Jan, 2010. By using 'the modified Workload Management System for critical care Nurses' (WMSN), nursing categories, activities, standard time, and task frequencies were measured with direct observation. The data were analyzed by using descriptive statistics. Results: Neonatal nursing activities were categorized into 8 areas: vital signs (manual), monitoring, activity of daily living (ADL), feeding, medication, treatment and procedure, respiratory therapy, and education-emotional support. The most frequent and time-consuming area was an ADL, unlike that of adult patients. Conclusion: The findings of the study provide a foundation for developing a neonatal patient classification system in NICU. Further research is warranted to verify the reliability and validity of the instrument.

• 산업공학
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• 제11권2호
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• pp.119-124
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• 1998

This paper proposes a new part family classification system (IPFACS: Image Processing and Fuzzy ART based Clustering System), which incorporates image processing techniques and a modified fuzzy ART neural network algorithm. IPFACS can classify parts based on geometrical shape and manufacturing attributes, simultaneously. With a proper reduction and normalization of an image data through the image processing methods and adding method in the modified Fuzzy ART, different types of geometrical shape data and manufacturing attribute data can be simultaneously classified in the same system. IPFACS has been tested for an example set of hypothetical parts. The results show that IPFACS provides a good feasible approach to form families based on both geometrical shape and manufacturing attributes.

• 간호행정학회지
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• 제14권3호
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• pp.229-240
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• 2008

Purpose: To develop the patient classification system based on the resource utilization for reimbursement of long-term care hospitals in Korea. Method: Health Insurance Review & Assessment Service (HIRA) conducted a survey in July 2006 that included 2,899 patients from 35 long-term care hospitals. To calculate resource utilization, we measured care time of direct care staff (physicians, nursing personnel, physical and occupational therapists, social workers). The survey of patient characteristics included ADL, cognitive and behavioral status, diseases and treatments. Major category criteria was developed by modified delphi method from 9 experts. Each category was divided into 2-3 groups by ADL using tree regression. Relative resource use was expressed as a case mix index (CMI) calculated as a proportion of mean resource use. Result: This patient classification system composed of 6 major categories (ultra high medical care, high medical care, medium medical care, behavioral problem, impaired cognition and reduced physical function) and 11 subgroups by ADL score. The differences of CMI between groups were statistically significant (p<.0001). Homogeneity of groups was examined by total coefficient of variation (CV) of CMI. The range of CV was 29.68-40.77%. Conclusions: This patient classification system is feasible for reimbursement of long-term care hospitals.

• Journal of Multimedia Information System
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• 제3권3호
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• pp.53-61
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• 2016

This research proposes the index optimization as a classification task and application of the graph based KNN. We need the index optimization as an important task for maximizing the information retrieval performance. And we try to solve the problems in encoding words into numerical vectors, such as huge dimensionality and sparse distribution, by encoding them into graphs as the alternative representations to numerical vectors. In this research, the index optimization is viewed as a classification task, the similarity measure between graphs is defined, and the KNN is modified into the graph based version based on the similarity measure, and it is applied to the index optimization task. As the benefits from this research, by modifying the KNN so, we expect the improvement of classification performance, more graphical representations of words which is inherent in graphs, the ability to trace more easily results from classifying words. In this research, we will validate empirically the proposed version in optimizing index on the two text collections: NewsPage.com and 20NewsGroups.

• ETRI Journal
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• 제35권6호
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• pp.1134-1143
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• 2013

The rising pace of technological change in information and communications technology (ICT) has provoked technological convergence by providing a new mode of diversification. This paper investigates the nature of ICT-based converging technologies by examining comparative empirical evidence on converging versus nonconverging technologies in relation to the following issues: patent application trends, concentration across technologies, the concentration of patenting activity across firms, R&D efforts, and a technology impact index. For this study, a new operational definition of ICT-based converging technology is derived, and a massive quantity of patents, up to around 600,000, is analyzed. This study follows the International Patent Classification as well as the modified European Commission's industry classification system for the classification of technologies and industries, respectively.

• 한국지진공학회논문집
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• 제10권2호
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• pp.51-62
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• 2006

동반논문 (I)에서는 국내 지반특성에 적합하도록 국내 내진설계기준이 개선되어야 한다는 결론을 얻었다. 본 논문에서는 우수한 지반분류 방법을 찾기 위하여 상부 토층 30m의 평균 전단파속도$(V_{S30})$, 지반의 고유주기$(T_G)$ 및 기반암 깊이를 이용한 지반분류 방법에 대하여 심도있게 검토하였다. 증폭계수$(F_a,\;F_v)$의 표준편차, 해석결과의 평균 스펙트럼 가속도와 재산정된 응답스펙트럼을 비교한 결과 각각의 방법에서 큰 차이가 발생하지 않아 특정한 방법이 우수하다고 판단하기 힘들었다. 그러나, $T_G$를 이용한 방법에서 RRS 값의 증폭구간이 좁은 구간에 집중되는 경향을 보여 지진시 유사한 거동특성을 나타내는 지반을 같은 지반그룹으로 분류할 수 있는 장점이 있었다. 또한, 증폭계수와 $T_G$의 상관관계를 나타내는 추세선의 경우, $V_{S30}$ 방법 보다 입력 가속도의 증가에 따른 지반의 비선형성 효과를 더욱 명확하게 나타낼 수 있었다. 마지막으로, $V_{S30}$을 이용하여 지반을 분류할 경우 기반암이 30m 보다 얕은 곳에 존재하는 경우에도 무조건 심도 30m까지 기반암의 전단파속도를 가정하여 계산해야 하나, $T_G$를 이용할 경우 이러한 불확실성을 제거할 수 있어 우수한 방법으로 판단된다. 본 논문에서는 지반의 고유주기를 이용한 방법을 기반암 깊이가 얕은 국내지반특성에 적합한 지반분류 방법으로 제안하였다.

• Journal of applied mathematics & informatics
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• 제8권1호
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• pp.129-136
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• 2001

We introduce and discuss a new numerical method for solving system of second order boundary value problems, where the solution is required to satisfy some extra continuity conditions on the subintervals in addition to the usual boundary conditions. We show that the present method gives approximations which are better than that produced by other collocation, finite difference and spline methods. Numerical example is presented to illustrate the applicability of the new method. AMS Mathematics Subject Classification : 65L12, 49J40.

• Journal of Gastric Cancer
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• 제11권2호
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• pp.94-100
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• 2011

Purpose: The 7th AJCC tumor node metastasis (TNM) staging system modified the classification of the lymph node metastasis widely compared to the 6th edition. To evaluate the prognostic predictability of the new TNM staging system, we analyzed the survival rate of the gastric cancer patients assessed by the 7th staging system. Materials and Methods: Among 2,083 patients who underwent resection for gastric cancer at the department of surgery, Hanyang Medical Center from July 1992 to December 2009, This study retrospectively reviewed 5-year survival rate (5YSR) of 624 patients (TanyN3M0: 464 patients, TanyNanyM1: 160 patients) focusing on the number of metastatic lymph node and distant metastasis. We evaluated the applicability of the new staging system. Results: There were no significant differences in 5YSR between stage IIIC with more than 29 metastatic lymph nodes and stage IV (P=0.053). No significant differences were observed between stage IIIB with more than 28 metastatic lymph nodes and stage IV (P=0.093). Distinct survival differences were present between patients who were categorized as TanyN3M0 with 7 to 32 metastatic lymph nodes and stage IV. But patients with more than 33 metastatic lymph nodes did not show any significant differences compared to stage IV (P=0.055). Among patients with TanyN3M0, statistical significances were seen between patients with 7 to 30 metastatic lymph nodes and those with more than 31 metastatic lymph nodes. Conclusions: In the new staging system, modifications of N classification is mandatory to improve prognostic prediction. Further study involving a greater number of cases is required to demonstrate the most appropriate cutoffs for N classification.