• 한국조리학회지
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• 제2권
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• pp.209-235
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• 1996

This study assesses consumer's eating-out pattern for Foodservice industry in Korea. Foodservice industry has become increasingly important because many businessman are looking it difficult to develop successful business as a consequence of the rapid growth in Foodservice industry in Korea This exploratory study originally nation-wide surveyed a 1450 consumer over the country. A research was conducted from July 1, to July 10, 1996 using as its subject domestic consumer over the country. The data obtained from the returned questionnaires was coded and transcribed for statistical analysis. The Statistical Package for social science program (SPSS) was used for computer analysis of the data. Findings indicated the problems of management structures, managerial techniques, and laggard counter measure against the korean government's open-door policy for dining-out industry. It is found that taste, F/B price, atmosphere are considered important in choice of restaurant. And korean consumer think it is that restaurant location, physical, evidence, quality of service, Ads of mouth and cleanliness. With the importance of dining-out industry to the business, economic, and social development of korea, it is imperative to bridge this gap for sustained growth and development. Moreover, this study for advancement and improvement through concrete and multi-directional data collection and in-depth analysis of consumer's eating-out pattern realities is required.

• 한국정보과학회논문지:시스템및이론
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• 제32권6호
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• pp.314-323
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• 2005

본 논문은 전장지역에서 벌어지는 공중작전에 대한 상황의 자료를 통합하여 3차원으로 가시화 함으로써 공중작전의 최고결정권자가 올바른 상황인식 및 지휘결정을 할 수 있게 지원하는 시스템을 제안한다. 공중작전 상황판단을 위한 다양한 자료들, 레이더 항적정보, 비행계획 데이타베이스, 지도 및 위성사진 정보 둥을 하나의 자료로 통합하여 3차원으로 가시화 시킴으로써, 작전의 최고 결정권자가 한 순간에 종합적인 작전 결정을 할 수 있는 정보를 지원하는 시스템이다. 대량의 데이타를 종합적이고 체계적으로 가시화 하기 위하여 Out-of-Core 방법을 사용함으로써 휴대용 노트북에서도 운용이 가능함을 실험을 통하여 보여 주고 있으며, 공군의 공중작전 수행 시 상황인식을 지원하는 시스템으로 활용될 수 있는 가능성을 보이고 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2927-2941
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• 2022

The primary task of machine fault diagnosis is to judge whether the current state is normal or damaged, so it is a typical binary classification problem with mutual exclusion. Mutually exclusive events and out-of-domain detection have one thing in common: there are two types of data and no intersection. We proposed a fusion model method to improve the accuracy of machine fault diagnosis, which is based on the mutual exclusivity of events and the commonality of out-of-distribution detection, and finally generalized to all binary classification problems. It is reported that the performance of a convolutional neural network (CNN) will decrease as the recognition type increases, so the variational auto-encoder (VAE) is used as the primary model. Two VAE models are used to train the machine's normal and fault sound data. Two reconstruction probabilities will be obtained during the test. The smaller value is transformed into a correction value of another value according to the mutually exclusive characteristics. Finally, the classification result is obtained according to the fusion algorithm. Filtering normal data features from fault data features is proposed, which shields the interference and makes the fault features more prominent. We confirm that good performance improvements have been achieved in the machine fault detection data set, and the results are better than most mainstream models.

• Nutrition Research and Practice
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• 제8권6호
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• pp.670-678
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• 2014

BACKGROUND/OBJECTIVES: Eating-out among Korean people has become an important part of modern lifestyle due to tremendous growth of the food service industry and various social and economic changes. This study examined trends in meal patterns and meal sources while eating-out among Korean adults aged 19 years and older. SUBJECTS/METHODS: Data were from the 1998-2012 KNHNES (Korea National Health and Nutrition Examination Survey) by the 24-hour dietary recall method. This study included 55,718 adults aged 19 years and older. For analysis of eating-out frequency, data were categorized by source of meals and serving place. RESULTS: Average frequency of meals consumed away from home increased from 1998 to 2012, although it remained lower than that of meals at home. In addition, male, unmarried, employed, higher educated, and high income individuals more frequently consumed meals away from home. Moreover, sodium intake while eating-out significantly increased from 2,370 mg in 1998 to 2,935 mg in 2012. Lastly, percentage contributions of daily total protein intake, fat intake, and sodium intake from eating-out increased to more than half (53-55%) in 2012 compared with 47-48% in 1998. CONCLUSIONS: As eating-out has grown in popularity, greater recognition of public health and nutritional education aimed at promoting healthy food choices is needed. In addition to developing consumer education for overall healthier eating patterns, individuals who are younger, unmarried, higher educated, and males are especially at risk and require attention.

• Wind and Structures
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• 제28권4호
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• pp.239-253
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• 2019

Accurate numericalsimulation of wind field over complex terrain is an important prerequisite for wind resource assessment. In this study, numerical simulation of wind field over complex terrain was further carried out by taking the complex terrain around Siu Ho Wan station in Hong Kong as an example. By artificially expanding the original digital model data, Gambit and ICEM CFD software were used to create high-precision complex terrain model with high-quality meshing. The equilibrium atmospheric boundary layer simulation based on RANS turbulence model was carried out in a flat terrain domain, and the approximate inflow boundary conditions for the wind field simulation over complex terrain were established. Based on this, numerical simulations of wind field over complex terrain under different inflow wind directions were carried out. The numerical results were compared with the wind tunnel test and field measurement data for land and sea fetches. The results show that the numerical results are in good agreement with the wind tunnel data and the field measurement data which can verify the accuracy and reliability of the numerical simulation. The near ground wind field over complex terrain is complex and affected obviously by the terrain, and the wind field characteristics should be fully understood by numerical simulation when carrying out engineering application on it.

• Restorative Dentistry and Endodontics
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• 제44권4호
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• pp.37.1-37.10
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• 2019

Objectives: This study evaluated the bond strength of various fiberglass post cementation techniques using different resin-based composites. Materials and Methods: The roots from a total of 100 bovine incisors were randomly assigned to 5 treatment groups: G1, post + Scotchbond Multi-Purpose (SBMP) + RelyX ARC luting agent; G2, relined post (Filtek Z250) + SBMP + RelyX ARC; G3, individualized post (Filtek Z250) + SBMP; G4, individualized post (Filtek Bulk-Fill) + SBMP; G5, individualized post (Filtek Bulk-Fill Flow) + SBMP. The samples were subjected to the push-out (n = 10) and pull-out (n = 10) bond strength tests. Data from the push-out bond strength test were analyzed using 2-way analysis of variance (ANOVA) with the Bonferroni post hoc test, and data from the pull-out bond strength test were analyzed using 1-way ANOVA. Results: The data for push-out bond strength presented higher values for G2 and G5, mainly in the cervical and middle thirds, and the data from the apical third showed a lower mean push-out bond strength in all groups. No significant difference was noted for pull-out bond strength among all groups. The most frequent failure modes observed were adhesive failure between dentine and resin and mixed failure. Conclusions: Fiberglass post cementation using restorative and flowable bulk-fill composites with the individualization technique may be a promising alternative to existing methods of post cementation.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.11-19
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• 2022

Data mining has broad applications that reach beyond scholarly and scientific research and provide internet search engine services that are commonly used forms of Text and Data Mining('TDM') of websites. The exceptions and limitations for data mining provide a competitive advantage in the global race for policy innovation because it permits researchers to conduct computational analysis - TDM on any materials to which they have access. For this purpose, Japan and the EU added limitations on copyright to legalize some TDM research through amendments to copyright law, and the U.S. copyright law has allowed data mining by the fair use provision. On the other hand, there are no explicit exceptions and limitations for data mining under the Korean Copyright Act, and there are no cases considering data mining fair use. We review comparatively exceptions and limitations on copyright which will help to encourage AI-related business by using more data smoothly through the mining process and extracting more valuable information.

• 한국경영과학회지
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• 제21권3호
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• pp.197-214
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• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• 동굴
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• 제5호
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• pp.96-106
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• 1997

The reduction of cave survey data is an essentially straightforward but repetitive mathematical task which can be carried out to advantage using virtually any type of computer from a programmable calculator upwards. The obvious benefits are speed and accuracy in reducing and adjusting the raw data to obtain the x,y,z coordinates (eastings, northings and elevations) of the surveyed points. Additionally, depending on the functionality of the software (program) and power of the hardware (computer), the user may be able to build up a data base of surveys, plot out on paper scaled plans and elecations of the cave and possibly even see a three-dimensional model of the cave, in perspective or some other projection, as an aid to understanding the spatial relationships of cave passages.(omitted)

• Smart Structures and Systems
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• 제21권4호
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• pp.521-535
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• 2018

The main purpose of this paper is to predict missing absolute out-of-plane displacements and failure limits of infill walls by artificial neural network (ANN) models. For this purpose, two shake table experiments are performed. These experiments are conducted on a 1:1 scale one-bay one-story reinforced concrete frame (RCF) with an infill wall. One of the experimental models is composed of unreinforced brick model (URB) enclosures with an RCF and other is composed of an infill wall with bed joint reinforcement (BJR) enclosures with an RCF. An artificial earthquake load is applied with four acceleration levels to the URB model and with five acceleration levels to the BJR model. After a certain acceleration level, the accelerometers are detached from the wall to prevent damage to them. The removal of these instruments results in missing data. The missing absolute maximum out-of-plane displacements are predicted with ANN models. Failure of the infill wall in the out-of-plane direction is also predicted at the 0.79 g acceleration level. An accuracy of 99% is obtained for the available data. In addition, a benchmark analysis with multiple regression is performed. This study validates that the ANN-based procedure estimates missing experimental data more accurately than multiple regression models.