• 간호행정학회지
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• 제16권4호
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• pp.488-496
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• 2010

Purpose: This study was done to explore the relationship in hospital nurses' of communication competence, communication types, and organizational commitment and to provide basic data for developing programs to improve internal communication and to promote nurses' commitment to their organizations. Methods: The participants included 316 nurses who worked in two general hospitals. The tools used for this study were the Global Interpersonal Communication Competence Scale (GICC) and Communication Satisfaction Questionnaire by Downs & Hazen (1981), revised by Seo (2002) and Mowday's tool (1979) for organizational commitment. Data were analyzed using SPSS/PC+12.0. Results: The mean score for communication competence was 3.46, and for organizational commitment, 3.19. For communication types, the mean score for formal communication was 3.18 and informal communication, 2.59. Communication competence had a positive relationship with formal communication (r=.32) and with informal communication (r=.16). Organizational commitment had a positive relationship with formal communication (r=.53), communication competence (r=.30), and informal communication (r=.27). Conclusion: The results indicate the necessity of developing programs to promote nurses' communication competence and also developing a system that will enrich active communication. Systematic and continuous training in communication is also highly recommended.

• Journal of Information Technology Applications and Management
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• 제15권4호
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• pp.123-136
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• 2008

This study tried to find out the effect of change management on the ERP performance in small and medium size companies. Communication, BPR management, education and training were selected as independent variables which might bring an effect on ERP performances which were classified as quality and quantity one. Structure equation model was built and analyzed with AMOS 5.0 version from data gathered through 127 companies which already implemented ERP systems. The result of this study shows that all the three independent variables give positive impacts on two dependent variables, which means change management is critical when small and medium size companies want to implement ERP systems.

• 대한임상검사과학회지
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• 제45권4호
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• pp.188-192
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• 2013

This study was conducted to develop the strategy for more effective internal marketing and promoting internal customer satisfaction by grasping the level of internal marketing operations targeting employees within hospital and empirically analyzing the effect of internal marketing operations on internal customer satisfaction. The findings reveal that there is a significant correlation between factors for internal marketing components and internal customer satisfaction. The average factor score for internal customer satisfaction is 3.230 out of 5, which is a little higher than normal levels. Counting down the five factors is as follows: internal communication, education and training, delegation of authority, welfare, compensation system, with compensation system shown as the lowest level and internal communication as the highest level. In addition, the result of multiple regression analysis conducted to inspect the effect of factors for internal marketing components on internal customer satisfaction indicates that among 5 factors, delegation of authority, education and training, and welfare have positive influences on internal customer satisfaction; whereas, compensation system has little effect on it.

• 한국정보전자통신기술학회논문지
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• 제6권4호
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• pp.238-242
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• 2013

We consider the problem of constructing observers for nonlinear systems with unknown inputs. Connectionist networks, also called neural networks, have been broadly applied to solve many different problems since McCulloch and Pitts had shown mathematically their information processing ability in 1943. In this thesis, we present a genetic neuro-control scheme for nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 한국정보전자통신기술학회논문지
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• 제6권4호
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• pp.243-248
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• 2013

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.106-109
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• 1998

Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

• 한국실천공학교육학회논문지
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• 제5권1호
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• pp.28-33
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• 2013

본 논문에서는 스마트기기의 출현으로 급변하는 정보통신환경을 반영한 스마트러닝 모델을 제시한다. 스마트 기기들은 화면크기와 성능이 다양하지만 크게 스마트폰, 스마트 패드, 개인용 컴퓨터(PC), 스마트 TV로 구분할 수 있다. 본 논문에서는 각 기기 유형별로 서비스에 적합한 교육 콘텐츠와 상호작용 방법들에 대하여 살펴보고, 각 기기 특성에 맞는 스마트러닝 서비스 모델과 향후 정보통신환경을 반영한 스마트 러닝의 발전 방향을 제시하였다.

• Journal of information and communication convergence engineering
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• 제2권2호
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• pp.61-66
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• 2004

This paper presents a way to maximize transmission efficiency and reception ability through transmission diversity technology, which can be adapted to wireless multimedia Wireless LAN system. The presented method is a comparative analysis between a case where parameter a for time average is 0.3.1 with consideration of channel presumption with two types of rms delayed spread, which is 50nsec. 150nsec, for the performance analysis of STTC (Space-Time Trellis Code) adopting time-space ciphering method appropriate for MIMO channel, and performance in the case where presumed channel value from long training column section is applied to according frame in a single frame. The result showed that BER brought SNR improvement of l.0dB in $10^{-3}$ when a was 0.3 than adopting only the long training column, and showed increase of general performance improvement for the sake of time average rather than the case without.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

• International Journal of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.124-131
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• 2024

Breast cancer classification using ultrasound, while widely employed, faces challenges due to its relatively low predictive value arising from significant overlap in characteristics between benign and malignant lesions, as well as operator-dependency. To alleviate these challenges and reduce dependency on radiologist interpretation, the implementation of automatic breast cancer classification in ultrasound image can be helpful. To deal with this problem, we propose a semi-supervised deep learning framework for breast cancer classification. In the proposed method, we could achieve reasonable performance utilizing less than 50% of the training data for supervised learning in comparison to when we utilized a 100% labeled dataset for training. Though it requires more modification, this methodology may be able to alleviate the time-consuming annotation burden on radiologists by reducing the number of annotation, contributing to a more efficient and effective breast cancer detection process in ultrasound images.