• 한국음향학회지
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• 제26권5호
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• pp.194-198
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• 2007

본 논문에서는 음성의 통계적 모델에 기반한 음성검출기의 성능향상을 위해 변별적 가중치 학습(discriminative weight training) 기반의 최적화된 우도비 테스트(Likelihood Ratio Test, LRT)를 제안한다. 먼저, 기존의 통계모델기반의 음성검출기를 분석하고, 이를 기반으로 MCE(minimum classification error)방법을 도입하여, 각 주파수 채널별로 다른 가중치를 가지는 우도비 기반의 음성검출 결정법(decision rule)을 제시한다. 제안된 알고리즘은 비정상(non-stationary)잡음환경에서 기존의 동일 가중치를 가지는 기하 평균 기반의 음성검출기와 비교하였으며, 우수한 성능을 보인다.

• 통상정보연구
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• 제6권3호
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• pp.41-61
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• 2004

Today, most companies are needed to become interested on e-Biz and information management system. Especially, Data classification format system was very important for application to effective and efficiency management decision support. They should include main entry which consists of department, employee's name, title, publication date. Now, each company is using eleven different methods on data classification format system. In this paper finding result was as follows, in other words, general management document case using the nine date classification methods and special report management document ca se using the twodata classification methods. The aim of this study is to investigate problems that the present data classification format system has and some concerns that should be taken into account in case of the modification of the data classification system and change into a new one. This study is based on the survey in that the company managergave to 35 companies throughout the nation. As a result, the survey indicates that the crucial concerns of the participating managers are ineffective management information source and the duplication of data classification systems. This paper is the transcendental study the introduction of data classification format systems to business companies in Korea. This paper provided the fundamental data for the effective business process reengineering in business activity for management information.

• 한국과학교육학회지
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• 제26권1호
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• pp.40-48
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• 2006

이 연구의 목적은 초등학교 6학년 학생의 분류활동에서 나타나는 사고 유형, 과정과 특징을 분석하는 것이다. 이러한 목적을 달성하기 위하여 분류활동 수행에 적합한 2가지 도구를 개발하였다. 첫 번째는 속성이 분명하게 드러나는 인공자극카드이고, 두 번째는 속성이 잘 드러나지 않는 자연자극카드이다. 서울시 영등포구 소재 D초등학교 6학년 8명을 대상으로 질적 연구를 수행하였다. 자료는 피험자의 과제 수행과정을 녹화한 비디오테이프, 피험자의 분류 기록지, 연구자의 피험자 행동 관찰, 피험자와의 면담 등 자료 삼각측정법에 의해 획득하였다. 연구결과, 6학년 학생들은 분류활동에서 속성 관찰, 속성 평가, 예비 점검, 기준 선택, 샘플 동정의 다섯 가지 유형의 사고를 하였으며, 모든 항목을 분류할 때까지 속성 관찰 $\rightarrow$ 속성 평가 $\rightarrow$ 예비 점검 $\rightarrow$ 기준 선택 $\rightarrow$ 샘플 동정의 과정을 반복하였다. 그리고 인지 경제성을 활용하여 분류하여 분류하였다. 이상의 연구 결과는 과학 분류 학습 지도에 다음과 같은 시사점을 줄 수 있다. 첫째,교사가 학생들의 분류 사고과정을 이해한다면, 보다 효과적인 분류학습 지도가 가능할 것이다. 둘째, 분류사고 과정의 각 단계를 고려한 단계별 학습지도가 필요하다.

• Journal of Information Science Theory and Practice
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• 제10권spc호
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• pp.39-45
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• 2022

For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.

• 인터넷정보학회논문지
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• 제21권4호
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• pp.127-135
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• 2020

The purpose of this study is to develop a human activity recognition (HAR) system, which distinguishes 13 activities, including five activities commonly dealt with in conventional HAR researches and eight activities from the Eastern-Asian culture. The eight special activities include floor-sitting/standing, chair-sitting/standing, floor-lying/up, and bed-lying/up. We used a 3-axis accelerometer sensor on the wrist for data collection and designed a machine learning model for the activity classification. Data clustering through preprocessing and feature extraction/reduction is performed. We then tested six machine learning algorithms for recognition accuracy comparison. As a result, we have achieved an average accuracy of 99.7% for the 13 activities. This result is far better than the average accuracy of current HAR researches based on a smartwatch (89.4%). The superiority of the HAR system developed in this study is proven because we have achieved 98.7% accuracy with publically available 'pamap2' dataset of 12 activities, whose conventionally met the best accuracy is 96.6%.

• 한국게임학회 논문지
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• 제16권6호
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• pp.7-18
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• 2016

본 연구는 놀이와 웃음활동을 인성교육과 접목하여 프로그램을 구안하고자 초등학교 5, 6학년 학생들을 대상으로 놀이(규칙놀이 영역, 전통놀이 영역, 보드게임 영역), 웃음활동, 디지털 게임의 실태와 선호도를 설문조사하였다. 학생들의 선호도는 보드게임 영역에서 가장 높았고, 그 다음으로 디지털 게임, 규칙놀이 영역, 전통놀이 영역, 웃음활동 순으로 나타났다. 규칙놀이 영역에서는 그룹놀이를 가장 선호했고, 전통놀이 영역에서는 윷놀이를 가장 선호하였다. 보드게임 영역에서는 7세 이상 대상 2연령의 보드게임을 가장 선호하였고, 디지털 게임은 모바일 게임을 가장 선호하였다. 따라서 초등학생들에게 양질의 놀이 교육 프로그램을 개발할 때에는 학생들의 놀이 실태를 잘 파악하고 성별에 따라 선호도가 다름을 이해하는 등 놀이의 특성을 고려하는 것이 매우 중요하다고 사료된다.

• 간호행정학회지
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• 제14권2호
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• pp.118-130
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• 2008

Purpose: The purpose of this study was to estimate of home-visiting nursing costs for low-income elderly with chronic disease in a metropolitan city using the severity classification and ABC(active-based costing). Methods: First, the HHC activity pool was established. The performance time of each nursing activity were estimated. Second, nursing resources(labor costs, operating costs, and traffic expenses) were analyzed and nursing cost per minute was calculated. And then the cost of each activity was estimated. Third, 202 visiting cases were classified into three group by their severity. And then nursing cost per visit according to their severity was estimated. Results: 59 nursing activities were included in HHC activity pool. The average working time of 59 nursing activity was 6.7minutes and nursing cost per minute was 489 won. According severity, nursing cost per visit were in class I, 54,296 (won), class II 83,124(won), and class III 93,455(won).

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권2호
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• pp.87-92
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• 2014

본 논문에서는 스마트폰 내장 가속도 센서를 이용한 2단계 행위 인식 시스템을 제안한다. 제안하는 행위 인식 시스템에서는 각 행위 별 가속도 데이터의 시간적 변화 패턴을 충분히 반영하기 위해, 1단계에서는 결정트리(DT) 학습을 수행하고, 2단계에서는 1단계 분류 결과들의 시퀀스를 이용하여 은닉 마코프 모델(HMM) 학습을 수행한다. 또한, 견고한 행위 인식기를 얻기 위해, 동일한 행위에 대해 서로 사용자와 서로 다른 스마트폰 위치와 방향으로부터 수집한 다양한 대용량 데이터를 이용하여 본 시스템을 훈련하였다. 6가지 실내 행위들에 대해 수집한 6720개의 가속도 센서 데이터를 이용한 실험을 통해, 본 시스템은 앞서 설명한 설계 방식을 기초로 높은 인식 성능을 보여주었다.

• 대한의용생체공학회:의공학회지
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• 제33권1호
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• pp.15-24
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• 2012

Classification of human thought is an emerging research field that may allow us to understand human brain functions and further develop advanced brain-computer interface (BCI) systems. In the present study, we introduce a new approach to classify various mental states from noninvasive electrophysiological recordings of human brain activity. We utilized the full spatial and spectral information contained in the electroencephalography (EEG) signals recorded while a subject is performing a specific mental task. For this, the EEG data were converted into a 2D spatiospectral pattern map, of which each element was filled with 1, 0, and -1 reflecting the degrees of event-related synchronization (ERS) and event-related desynchronization (ERD). We evaluated the similarity between a current (input) 2D pattern map and the template pattern maps (database), by taking the inner-product of pattern matrices. Then, the current 2D pattern map was assigned to a class that demonstrated the highest similarity value. For the verification of our approach, eight participants took part in the present study; their EEG data were recorded while they performed four different cognitive imagery tasks. Consistent ERS/ERD patterns were observed more frequently between trials in the same class than those in different classes, indicating that these spatiospectral pattern maps could be used to classify different mental states. The classification accuracy was evaluated for each participant from both the proposed approach and a conventional mental state classification method based on the inter-hemispheric spectral power asymmetry, using the leave-one-out cross-validation (LOOCV). An average accuracy of 68.13% (${\pm}9.64%$) was attained for the proposed method; whereas an average accuracy of 57% (${\pm}5.68%$) was attained for the conventional method (significance was assessed by the one-tail paired $t$-test, $p$ < 0.01), showing that the proposed simple classification approach might be one of the promising methods in discriminating various mental states.

• 임상간호연구
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• 제24권1호
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• pp.113-126
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• 2018

Purpose: The purpose of this study was to revise the KPCS-1 and to standardize the three patient classification systems for general ward, ICU and NICU. The actual utilization of the KPCS-1 score and each nursing activity was evaluated and the relationships between KPCS-1 score and nursing related variables were reviewed. Methods: The 47,711 KPCS-1 scores of 6,931 patients who discharged from $1^{st}$ to $30^{th}$ April 2017 were analyzed and the statistical significance between KPCS-1 score and nursing related variables was reviewed by Generalized Estimating Equation. The revision of the KPCS-1 was carried out by Partial Least Square model. The 3 patient classification systems (KPCS-1,KPCSC and KPCSN) were standardized by professional reviews. Results: KPCS-1 was a valid instrument to express nursing condition adequately and was revised as a new version which has 34 nursing activity items. The names and terminologies of pre-existing 3 patient classification systems developed by KHNA were standardized as KPCS-GW, KPCS-ICU, KPCS-NICU. Conclusion: KPCS-1 was a valid instrument to represent diverse nursing conditions precisely and was revised as a 34-item KPCS-GW. The terminologies of the other patient classification systems by KHNA were standardized as KPCS-ICU and KPCS-NICU.