• Journal of the Korean Vacuum Society
• /
• v.6 no.S1
• /
• pp.59-65
• /
• 1997

Efficient Si(100) etching by thermal H atoms at low substrate temperatures has been achieved. Gas-phase etching product $SiH_4$(g) upon H atom bombardment resulting from direct abstraction of $SiH_3$(a) by impinging H atoms was detected with a quadrupole mass spectrometer over the substrate temperature range of 105-408 K Facile depletion of all surface silyl ($SiH_3$) groups the dissociative adsorption product of disilane ($Si_2H_6$) at 105K from Si(100)2$\times$1 by D atoms and continuous regeneration and removal of $SiD_3$(a) were all consumed. These results provide direct evidence for efficient silicon surface etching by thermal hydrogen bombardment at cryogenic temperatures as low as 105K We attribute the high etching efficiency to the formation and stability of $SiH_3$(a) on Si(100) at lowered surface temperatures allowing the $SiH_3$(a) abstraction reaction by additional H atom to produce $SiH_4$((g).

• Journal of Community Nutrition
• /
• v.7 no.1
• /
• pp.58-63
• /
• 2005

Identifying quality attributes with the greatest value to the residents is important if the Continuing Care Retirement Community (CCRC) is to increase the frequency of residents' dining. However, it is not known which specific attribute is relatively more important than others to evaluate foodservice. The purpose of this study is to identify the relative importance of food and service quality attributes in the evaluation of foodservice in CCRe. This study surveyed the independent living residents of three CCRCs in the Midwestern states. Respondents placed great importance on taste and flavor of food which has the highest percentage of utility range ($28.28\%$) and the second greatest on appearance of the server ($23.46\%$) . The important attributes were ultimately used to predict the most preferred choice of food-service for residents. Knowledge of the importance of the attributes would enable the foodservice managers in CCRCs to manipulate those attributes to enhance the residents' perceptions of quality and identify strategies for continuous improvement.

• Journal of Applied Tourism Food and Beverage Management and Research
• /
• v.17 no.1
• /
• pp.21-40
• /
• 2006

This researches aimed to find out the influence of Attribution making Image of hotel on Brand Loyalty at the Service Encounter. To achieve its goal, variables corresponding to the actual circumstances of hotels have been sampled on the basis of documentary studies. In addition, the research model, hypothesis, range of the research, and samples were selected and set up. Bellow Theoretical Results show us how effectively hotel's Image properties attributed at the Service Encounter can affect in making the Image of hotel positively and form the higher Brand Loyalty. Brand Loyalty can not be established at a time. Hotel's marketer will have to trace every single change of Band Loyalty through Marketing Research and Maintain a dominant position through a continuous relationship with guests.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.13 no.1
• /
• pp.140-149
• /
• 2006

Purpose: The concept of sensibility as sensitive perception is a part of the most important elements in human relations and nursing. However, sensibility has not been a focus of nursing research and it seems important to clarify the meaning of sensibility. Therefore, in this study the meaning of sensibility as a cognitive faculty of humans was explored. The results will contribute to the development of nursing science and art. Method: The process described by Walker and Avant to analyze concepts was used to define the concept of sensibility. Results: Attributes of sensibility were defined as 'emotional ability to feel', 'delicate, sensitive awareness of emotion' 'appreciative, tender hearted about oneself and others', 'awareness of intellectual, moral values', 'liability to be vulnerable', 'direct interrelation with individual'. Conclusion: The sensibility mentioned above included the attribute of caring within nurses intrinsic disposition which is achieved through the process of interrelational communication. Therefore continuous study and development of this concept should not only provide resources for nursing but also have a positive effect in therapeutic personal relationships.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.05a
• /
• pp.217-220
• /
• 2003

본 논문에서는 특정 매개변수의 입력 없이 속성(attribute)에 따른 목적속성(class)값의 분포를 고려하여 연속형(conti-nuous) 값을 범주형(categorical)의 형태로 변환시키는 새로운 방법을 제안하였다. 각각의 속성에 대해 목적속성의 분포를 1차원 공간에 사상(mapping)하고, 각 목적속성의 밀도, 다른 목적속성과의 중복 정도 등의 기준에 따라 구간을 군집화 한다. 이렇게 생성된 군집들은 각각 목적속성을 예측할 수 있는 확률적 수치에 기반한 것으로, 각 속성이 제공하는 정보의 손실을 최소화하는 이산화 경계선을 갖고 있다. 제안된 데이터 이산화 방법의 향상된 성능은 C4.5 알고리즘과 UCI Machine Learning Data Repository 데이터를 사용하여 확인할 수 있다.

• Journal of the Korea Safety Management & Science
• /
• v.11 no.1
• /
• pp.131-136
• /
• 2009

The research develops the calculation steps of Z sigma level, process capability index(PCI) and process performance index(PPI) applicable to the discrete process in the service industry. The paper presents three following topics used related process indexes according to the precision and accuray in the continuous process. The contents include diverse process indexs for nonconformities by SPC attribute control charts and bias coefficient. The same technique of the nonconformites is also used in the nonconforming units. The practical examples are provided to help easier understanding for users.

• Speech Sciences
• /
• v.10 no.1
• /
• pp.71-84
• /
• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.4
• /
• pp.908-922
• /
• 1997

In this paper,we present an dffcient way to describe the commplex meaning embedded in video data for the cintent-based retrival in a video database.Intead of viewing the data stored in a file as continuous bit stream,we associate the desired interval in the stream with a set of atteibute and value pairs which describe its meaning.Since the meaning of video data can be cimplex and can change dyamically. It is necessary to com-bine the fixed schema of attributes used in the traditional database systrm with a description method through a set of attribute and value pairs that can be defined dynamically.As the cintent of viedo data can be expressed differently according to the view point of a user,it is important ot maintain the meaning of the attribute and value pairs cinsistently for different users.This paper proposes the dffctive way to manage the set of attri-bute and value pairs.In addition,it also describes a way to define a new video presentation by separating a video stream phsycally or by sharing the portion of a bit stream,and the new method can minimize the required storage space.

• Journal of the Korea Convergence Society
• /
• v.9 no.7
• /
• pp.69-75
• /
• 2018

The key technology of Industry 4.0, Smart factory is evaluated as the driving force of our economic development hereafter and a lot of researches have been established. Various entities including devices, products and managers exist in smart factory, but roles of these entities may be continuous or variable and can become extinct not long after. Existing methods for access control are not suitable to adapt to the variable environment. If we don't consider certain security level, important industrial data can be the targets of attacks. We need a new access control method satisfying desired level of efficiency and security without excessive system loads. In this paper, we propose a new RBAC-PAC which extend AC defined for PKC to the authority attribute of roles. We distribute PACs for roles through block chain method to provide the efficient access control. We verified that RBAC-PAC is more efficient in the smart factory with large number of entities which need a frequent permission update.

• Journal of Sensor Science and Technology
• /
• v.15 no.6
• /
• pp.433-441
• /
• 2006

Because of the low power and low rate of a sensor network, outlier is frequently occurred in the time series data of sensor network. In this paper, we suggest periodic pattern analysis that is applied to the time series data of sensor network and predict outlier that exist in the time series data of sensor network. A periodic pattern is minimum period of time in which trend of values in data is appeared continuous and repeated. In this paper, a quantization and smoothing is applied to the time series data in order to analyze the periodic pattern and the fluctuation of each adjacent value in the smoothed data is measured to be modified to a simple data. Then, the periodic pattern is abstracted from the modified simple data, and the time series data is restructured according to the periods to produce periodic pattern data. In the experiment, the machine learning is applied to the periodic pattern data to predict outlier to see the results. The characteristics of analysis of the periodic pattern in this paper is not analyzing the periods according to the size of value of data but to analyze time periods according to the fluctuation of the value of data. Therefore analysis of periodic pattern is robust to outlier. Also it is possible to express values of time attribute as values in time period by restructuring the time series data into periodic pattern. Thus, it is possible to use time attribute even in the general machine learning algorithm in which the time series data is not possible to be learned.