• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• Journal of Distribution Science
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• v.5 no.2
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• pp.101-117
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• 2007

Recently, in the process of distribution industry's growth, distribution environment is changing rapidly by appearance of new business condition and strategy of multiple store. According to the intensification of competition, recently large discount stores are developing private brand(PB) products for the purpose of product differentiation and profitability. But after the economic crisis in 1997, young housewives and salaried man's that have rational and practical buying pattern become the core consumer's in the large discount stores. Hence low price strategy is not new things for the consumer's anymore. In addition to, acquiring new consumer, many discount stores are establishing new stores at the rural area. But they undergo hardships of establishing new stores at the rural area because of disparity consumer's behavior, income level and consumption's pattern among regions. So, when they try to establish new stores, they need to know consumer's behavior at the region. Therefore the purpose of this study is to analyze preference property for the private brand(PB) of large discount stores in Gyeonggi-Do.

• Journal of Korean Society of Rural Planning
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• v.19 no.3
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• pp.13-24
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• 2013

With the increase of visitors to rural tourism villages, the direct selling at sites is getting vitalized. Accordingly, their display stores is getting more important. Therefore, this study has selected 30 domestic rural tourism villages as study objects for the attitude survey of 200 farming suppliers and the site examination for the designs of those display stores in order to analyze their status and classify the types of necessity. Such operation status as sale item, sale method, method of supply and demand, major customer, sales scale, manager, opening hour, and operation cost were examined, to identity and for design factors the pattern, material quality and color were investigated. For the attitude of farming suppliers, the tactics of sales, the reason for being positive or negative, the functionality and the features of display stores were examined through brainstorming. IBM SPSS Statistics 20 Program was employed for Frequency, which indicated that village chiefs and store managers with the sales scale of 1 to 20 million won are dealing with female customers in their 40's and 50's and that those stores are open at the time of experience or year round without any operation expense. Permanent type and Fixed type were found to be the design factors of the display-case type with the material and the color of wood and orange respectively. The result of investigation analysis of farming suppliers' attitude showed the followings: the need of display stores is quite high, structure type and permanent type have high fitness and from the viewpoint of display-on-table type as a standard moving type was very convenient. The analysis of significant items at the characteristics of those display stores revealed that their locations, quality conservation, sanitation, users' convenience, designs and promotion are very important. The result of status analysis revealed that though there is a correlation among the types of display stores depending on the visiting season of tourists their installing is not desirable. Three types have been analyzed: Type 1 is a structure type only in the villages with continuous visitors, Type 2 a moving-table type only in the villages with temporary visitors and Type 3 is a fixed display-case type.

• Fire Science and Engineering
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• v.12 no.1
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• pp.15-21
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• 1998

In this research, we studied reach the conclusion with more probability for predicting the severity which based on fire cases in domestic department stores for last 30 years. Considering the number of yearly fire cases in department stores and the cost of damage, we set the risk level. Moreover, this research shows the severity of fire in department stores through its scenario applying to FPETOOL program which NIST in USA has developed. By the result of FPETOOL program operation, we could acquired information about the time reaching the point where people are in danger in temperature, smoke layer and gas concentration. When a fire breaks out in a department store, a great loss of property and life is significant, as well as the potential risk is awfully considerable. Therefore, we should prevent a five from occuring.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.113-119
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• 2023

In this paper, we propose an optimization of a pose estimation deep learning model for recognition of abnormal behavior in unmanned stores using radio frequencies. The radio frequency use millimeter wave in the 30 GHz to 300 GHz band. Due to the short wavelength and strong straightness, it is a frequency with less grayness and less interference due to radio absorption on the object. A millimeter wave radar is used to solve the problem of personal information infringement that may occur in conventional CCTV image-based pose estimation. Deep learning-based pose estimation models generally use convolution neural networks. The convolution neural network is a combination of convolution layers and pooling layers of different types, and there are many cases of convolution filter size, number, and convolution operations, and more cases of combining components. Therefore, it is difficult to find the structure and components of the optimal posture estimation model for input data. Compared with conventional millimeter wave-based posture estimation studies, it is possible to explore the structure and components of the optimal posture estimation model for input data using genetic algorithms, and the performance of optimizing the proposed posture estimation model is excellent. Data are collected for actual unmanned stores, and point cloud data and three-dimensional keypoint information of Kinect Azure are collected using millimeter wave radar for collapse and property damage occurring in unmanned stores. As a result of the experiment, it was confirmed that the error was moored compared to the conventional posture estimation model.

• Journal of Korean Medical classics
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• v.12 no.2
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• pp.176-183
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• 1999

Each life has its own properties that distinguish one another. With this property, Oriental medicine suggests original diagnosis and treament. Our process of aging shows typical outline of cycle, i. e. from one's birth to death. Understanding the life cycle of men gives us very good hint to predict one's state of health, possible diseases, characteristics of disease in each term of his/her life cycle. It's because body and mode of diseases change according to age. Aging starts when $\breve{U}$m Essence(陰精)-the essence one receive from parents-dries up or when Deficient Fire(虛火) soars. Parts that compose our body-bones, muscles, flesh, etc.-gradually weaken and worn out as they no longer get support from Yang-Ki(陽氣), In "Yellow Emperor's Classic", aging starts around one's forties when $\breve{U}$m Essence(陰精) is reduced to less than half. However, what is usually accepted is that women start aging from 49 and men 64, regarding significant geriatric disease. As it is mentioned, aging starts with exhaustion of $\breve{U}$m Essence(陰精) which results in soaring Deficient Fire. Main symptoms are weak mental state due to Sin(神) disorder, and weak physical state due to Spleen and Stomacn(脾胃) disorder. Main principle in treating and preventing diseases related to aging is preserving $\breve{U}$m Essence(陰精), as well as fortifying Ki and Blood(氣血). To do this, Lung(肺)-which collects $\breve{U}$m Essence(陰精), and Kidney(腎) stores-which stores $\breve{U}$m Essence(陰精).

• Journal of Fashion Business
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• v.18 no.3
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• pp.1-13
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• 2014

This study investigated the store switching behavior of fashion stores targeting college students. A random sample of college students completed a questionnaire that contained measurements of store property, relationship quality, switching intent of store, preference of on/offline store, purchase of brand/non-brand product and monthly clothing expenses. The factors extracted as switching behavior of on/offline fashion store are store property, relationship quality and switching intent of store. Dimensions of store switching behavior in online shopping mall is revealed to be composed of diversity/ easy to search, store reliability, home page layout, sales promotion, reliability, commitment and switching intent of store. Also those of offline store is revealed to be composed of store comfort/salespeople service, product diversity, store location, product price, reliability, commitment and switching intent of store. The significant differences were found between store switching behavior of college students by preference of on/offline store and purchase of national brand/non brand. It is expected that this results can be used as a basic material for further study and setting up the fashion retailing strategies in fashion store for selling non brand products.

• Transactions of Materials Processing
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• v.12 no.2
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• pp.110-115
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• 2003

This paper is concerned with the compression test and forming process of flange by using virtual reality and analysis(simulation) program. This virtual manufacturing can be carried out one personal computer without any expensive devices for experiment. The virtual manufacturing composed of three modules such as the imput, calculation and the output modules on internet. Internet user can give the material's property and process parameters to the sever computer at the input module. On the calculation module, a simulator computes the virtual manufacturing process by analysis program and stores the data as a file. The output module is the program in which internet user can confirm virtual manufacturing results by showing tables, graphs, and 3D animation. This programs is designed by an internet language such as HTML, CGI, VRML and JAVA ,while analysis programs use the finite increasing, the virtual manufacturing technique will substitute many real experiments in the future.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1764-1767
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• 2002

Recent explosive increases in information 'volume have led to a rapid development or a change of information technology which stores, searches, and manages a vast amount of information. It is considered that an effective share and utilization of a large amount of digital information produced by work performances is a pivotal element which can make decisive contributions to a great success of business management. This common property of information reflects a changing social paradigm including a change of business processes. This paper is aimed at designing and embodying the construction of knowledge base in an efficient project management system using unsupervised data mining techniques in order to extract information and utilize it as knowledge about standard data (statistical data, template etc.,), size prediction and a danger precaution notice which are needed for a plan and a scheduling of a new project from data coming from already-established projects.

• Management & Information Systems Review
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• v.33 no.5
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• pp.97-115
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• 2014

The purpose of this study is to illustrating how the store selection factors affect the customer's satisfaction about the store and the intention of revisit base on the analyzing the store selection factors. At the same time, the difference between the influence on the customer's satisfaction and revisit intention of that in Korea and in China is also compared. Accordingly, through the notional understanding of configuration variables and the investigation of previous research, the Research hypothesis was set and the relevance between the two was inspected. The survey was aimed at the Korean customers who visit the large supermarkets in Korea and Chinese customers who visit the large supermarkets in China. After that, the reliability and validity of the collected data was verified and the research hypothesis was validated by structure equation modeling. The result of this study can by concluded as follows: First, in Korea the customer's satisfaction is showed to be affected by store selection factors, product property, service property and physical environment. Second, in China the customer's satisfaction is showed to be affected by store selection factors, product property, service property and physical environment. Third, in Korea the revisit intention is showed to be affected by customer's satisfaction. Forth, in China the revisit intention is showed to be affected by customer's satisfaction. Fifth, it shows little difference between the store selection factors of the customers visiting large supermarkets in Korea and in China. According to the research results above, the implications can be drawn as the customer's satisfaction of those who visit the large supermarkets may be affected by store selection factors (store property, product property, service property and physical environment). In recent years, more and more overseas large supermarkets are opening in both Korea and China and the competition among each is become more intense day by day. Every larger supermarket is trying their best to refine their store property, product property, service property and physical environment, in order to enhance the customer's satisfaction. The biggest factor that affects the customer's satisfaction and revisit intention in Korea is service property, So that the services requires proper measures and improvement. In China, the factor that affects most on the customer's satisfaction and revisit intention is physical environment. In order to enhance the customer's positive consciousness of stores, the physical environment needs to be well constructed. Lastly, in the compared research between Korea and China, the distribution of survey responders was limited from certain areas. Therefore, the further study can be implemented by more research in various geographical areas and more development in store selection factors.