• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.373-376
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• 2001

In this paper to cope with the reduction of products life-cycle as the variety of products along with the various demands of consumers, a virtual simulator is developed to make the changeover of manufacturing line efficient to embody a virtual simulation similar to a real manufacturing line. The developed virtual simulator can design a layout of a factory and make the time scheduling. Every factory has one simulator so that one product can be manufactured in the factories to use them as virtual factories. We suggest a scheme that heightens the ability to the diversity of manufacturing models by making the information of manufacturing lines and products models to be shared. The developed system embodies a virtual manufacturing line on the simulation using various manipulators and work cells as manufacturing components. we develop a virtual simulator system on Window 98/NT environment of Microsoft, operating system using of the greater part of PC user. Window program have a merit making GUI environment that programmer can use without the expert knowledge about hardware. A suer with the simulator can utilize an interface that makes one to manage the separate task process for each manufacturing module, change operator components and work cells, and easily teach tasks of each task module.

• 패션비즈니스
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• 제7권6호
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• pp.21-31
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• 2003

The CLI(Consumer Life Information) is a new study to unite and create new values recognizing the importance of knowledge and information in information-oriented society based on domestic science and digital technology. The objective of this research is to define academic identity of consuming science and CLI, to analyze the theory, styles, manners, psychology and the concept of consumption, which is the base of consuming life, and to present the direction of CLI with tasks and three major axises of CLI. Nowadays, international order demands new paradigms from human beings. Especially, vision and creation of the values are settled as methodological ways considering the economic power. The CLI should be on the same horizon adjusting social change of pointing values and quality in consuming patterns of diversity and variety. Therefore, I would suggest the ways for the CLI to head for as follows. First, it is to perceive the 3 major Axises & Task of CLI. Second, it is to develope service (experiencing goods) and goods that can lead consuming lives. Third, it is to study merchandising strategy, to create new signs and symbols of goods, and to collaborate of R & D(reseach and developement) and Business. Fourth, it is to head for globalization. Consequantly, this study will be helpful to establish the theory of relationship between producer and consumer in fashion business included research and developments of qualitative goods.

• 보건행정학회지
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• 제12권4호
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• pp.68-90
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• 2002

The purpose of this study is to investigate the determinants of intent to leave among hospital physicians. A causal model of intent to leave among hospital physicians was constructed based on the exchange theory. The sample of this study consisted of 185 physicians from 8 general hospitals located in Seoul, Taegu, Kyunggi-province, and Kyungsangnam-province in Korea. Data were collected with self-administered questionnaires and analyzed using LISREL. The results of this study indicate that the following variables, listed in order of size, have significant negative effects on intent to leave among hospital physicians; job satisfaction, organizational commitment, task variety, promotional chances, task significance, and pay. Sex (female=0, male=1) was found to have significant positive effects on the intent to leave among hospital physicians. The results imply that hospital administrators should make an effort to improve job satisfaction and organizational commitment which are the key determinants of intent to leave among hospital physicians.

• 대한임베디드공학회논문지
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• 제6권2호
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• pp.55-61
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• 2011

We propose power-saving real-time scheduling method for mixed task sets which consist of both time-based periodic and event-based aperiodic tasks in the automotive operating system. In this system, we have to pursue maximization of power-saving using the slack time estimation and minimization of response time of aperiodic tasks simultaneously. However, since these two goals conflict each other, one has to make a compromise between them according to the given application domain. In this paper, we find the adjustment factor which gives better response time of aperiodic tasks with slight power consumption increase. The adjustment factor denotes the gravity of response time for aperiodic tasks. We apply the ccEDF scheduling for time-based periodic tasks and then calculate new utilization to be applied to the adjustment factor. In this paper, we suggest the lccEDF algorithm to make a tradeoff between the two goals by systematically adjusting the factor. Simulation results show that our approach is excellent for variety of task sets.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.49-60
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• 2019

Plants are very crucial for life on Earth. There is a wide variety of plant species available, and the number is increasing every year. Species knowledge is a necessity of various groups of society like foresters, farmers, environmentalists, educators for different work areas. This makes species identification an interdisciplinary interest. This, however, requires expert knowledge and becomes a tedious and challenging task for the non-experts who have very little or no knowledge of the typical botanical terms. However, the advancements in the fields of machine learning and computer vision can help make this task comparatively easier. There is still not a system so developed that can identify all the plant species, but some efforts have been made. In this study, we also have made such an attempt. Plant identification usually involves four steps, i.e. image acquisition, pre-processing, feature extraction, and classification. In this study, images from Swedish leaf dataset have been used, which contains 1,125 images of 15 different species. This is followed by pre-processing using Gaussian filtering mechanism and then texture and color features have been extracted. Finally, classification has been done using Multiclass-support vector machine, which achieved accuracy of nearly 93.26%, which we aim to enhance further.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4408-4428
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• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.

• 한국식생활문화학회지
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• 제9권5호
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• pp.479-487
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• 1995

The purposes of this study were to: 1) measure the levels of job satisfaction with five facets of a job: the work itself, promotion, pay, supervision and co-workers, 2) investigate the degree of job characteristics inventory which employees perceived, 3) investigate relationships between job characteristics and job satisfaction levels of the employees in hospital foodservice, 4) measure the levels of organizational commitment and investigate its relationships between job satisfaction and job characteristics, 5) investigate the relationships between job performance and job satisfaction, job characteristics of the employees in hospital foodservice. The questionnaire was developed based on modifying Job Descriptive Index developed by Smith, Kendall, Hulin and Job Characteristics Inventory developed by Sims, Szilagyi, Keller and Affective commitment Scale developed by Meyer and Allen. Subjects consisted of 76 employees in hospital foodservice. Data were analyzed for frequency, means, ANOVA, Duncan multiple range test, and pearson correlation using SAS PC Package. The results of this study were as follows. 1) Most of the respondents were 41 years up(39.5%) and married (92%). High school graduates were 59.2%. 10 years working experienced employees were 35%. 2) A majority of the respondents(44.7%) ranked work itself as the most important aspect. 3) They were the most satisfied with co-workers. 4) Satisfaction with work itself, wage, and supervision were found significantly related to age(p<0.05). 5) Task identify was the most prevalent job characteristics and then task identity. 6) Satisfaction with co-workers were found significantly related to job variety(p<0.05). Satisfaction with supervision and promotion were found significantly related to friendship(p<0.05). 7) Job satisfaction have not correlation with job performance. Satisfaction with supervision, co-workers were positively correlated with organizational commitment(p<0.01). 8) Job characteristics of dealing with others were positively correlated with job performance (p<0.05). Job characteristics of variety, autonomy, task identity were positively correlated with organizational commitment(p<0.05, p<0.01).

• 한국콘텐츠학회논문지
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• 제12권8호
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• pp.29-36
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• 2012

CCPM 기법에서는 프로젝트 버퍼의 크기를 결정하기 위해 일반적으로 자르고 붙이는 방법과 루트-제곱하는 방법을 사용한다. 하지만 이러한 방법은 프로젝트의 특성을 고려하지 않고 고정된 공식을 통해서만 계산하기 때문에 버퍼의 크기가 너무 커지거나 작아지는 경우가 자주 발생했다. 본 논문에서는 위의 문제점을 해결하기 위해 이전 작업의 결과를 통계 분석하여 각 작업자에 대한 각 임무의 종류에 따른 작업의 특징을 파악하고 이를 CCPM 기법에 활용하여 해당 특징을 기준으로 버퍼 크기를 산정하는 새 방법을 제시하였다. 몬테카를로 시뮬레이션 환경에서 임무의 수, 임무의 어려운 정도 등의 요소를 반영하여 나온 결과를 비교분석 해서 본 논문에서 제안한 방법이 기존의 방법에 비해 임무 수와 상관없이 안정된 완공확률을 유지할 수 있음을 확인하였다. 또한 특정 작업자가 일찍 완공할 수 있는 임무들의 경우 제안한 방법은 기존 방법보다 버퍼의 크기를 더 단축하는 것을 확인하였다.

• 인터넷정보학회논문지
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• 제20권1호
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• pp.25-37
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• 2019

심층 학습 및 온라인 생체 인식 기반 인증의 급속한 개발에 영감을 받아, 본 논문에서는 심층 학습을 기반으로 필체 인식 및 작성자 검증을 수행하는 수기 일회성 암호 인증 시스템을 제안한다. 본 논문에서는 수기로 작성된 숫자를 인식할 수 있는 합성곱 신경망과, 입력된 필체와 실제 사용자의 필체 사이 유사성을 계산할 수 있는 Siamese 신경망을 설계한다. 본 논문에서는 작성자 검증을 위한 NIST Speical Database 19 제 2판의 첫 번째 응용 사례를 제시한다. 본 논문이 제안하는 시스템은 네 장의 입력 이미지를 기반으로 한 숫자 인식 작업에서 98.58%, 작성자 검증 작업에서 93%의 정확도를 달성했다. 본 논문의 저자들은 제안한 필체 기반 생체 인식기술이 FIDO 프레임워크 기반의 다양한 온라인 인증 서비스에 활용될 수 있을 것이라 예상한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.