• Asia Marketing Journal
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• v.20 no.1
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• pp.49-68
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• 2018

It is appropriate and useful to interpret some product classification schemes as buyer behavior models; such classifications permit investigations of discrepancies between classification predictions and actual buyer behavior. We review existing product classifications and identify underlying behavioral assumptions of various classification schemes that have been used in the marketing discipline for more than nine decades. Recognizing the irrelevance of existing product classifications for current products, we propose a new reclassification framework by incorporating transparency concepts. Based on this extended product classification, we highlight the potential roles of product classification study as an important link between consumer research and marketing strategy, emphasizing behavioral implications.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.18 no.1
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• pp.62-71
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• 2008

The use of chemical products to enhance and improve life is a widespread practice worldwide. But alongside the benefits of these products, there is also the potential for adverse effects to people or the environment. As a result, a number of countries or organizations have developed laws or regulations over the years that require information to be prepared and transmitted to those using chemicals, through labels or Material Safety Data Sheets (MSDS). While these existing laws or regulations are similar in many respects, their differences are significant enough to result in different labels or MSDS for the same product in different countries. Given the reality of the extensive global trade in chemicals, and the need to develop national programs to ensure their safe use, transport, and disposal, it was recognized that a Globally harmonization system of classification and labeling of chemicals(GHS) would provide the foundation for such programs. This study offered complementary details of GHS classification criteria adopted in Korea by analyzing the differences in chemical classification system between UN and Korea Ministry of Labor. Also it is proposed that mutual agreement of information DB used is required by comparing classification results of chemicals in Korea, Japan, and EU. We offered the lists of information sources useful for chemical classification.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.425-435
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• 2016

In this paper, we propose a classification model by analyzing raw material images recorded using a color CCD camera to automatically classify good and defective agricultural products such as rice, coffee, and green tea, and raw materials. The current classifying agricultural products mainly depends on visual selection by skilled laborers. However, classification ability may drop owing to repeated labor for a long period of time. To resolve the problems of existing human dependant commercial products, we propose a vision based automatic raw material classification combining mean shift clustering and stepwise region merging algorithm. In this paper, the image is divided into N cluster regions by applying the mean-shift clustering algorithm to the foreground map image. Second, the representative regions among the N cluster regions are selected and stepwise region-merging method is applied to integrate similar cluster regions by comparing both color and positional proximity to neighboring regions. The merged raw material objects thereby are expressed in a 2D color distribution of RG, GB, and BR. Third, a threshold is used to detect good and defective products based on color distribution ellipse for merged material objects. From the results of carrying out an experiment with diverse raw material images using the proposed method, less artificial manipulation by the user is required compared to existing clustering and commercial methods, and classification accuracy on raw materials is improved.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.175-191
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• 2017

The basis of economic statistics for evaluating the security industry's growth and inter-industry impacts is to create a standardized industry classification along with the scope of the security industry. The industrial classification should be written in such a way that it complies with and complies with the standards of the international and domestic standardized standard industrial classifications. Representative classifications of information security, physical security, and convergence security as well as classification of products and services related to security at present are not in line with the criteria of industrial classification based on the characteristics of production activities for products. The results of the convergence security industrial classification study are also consumer-oriented classification, which differs from the supplier-centric classification officially used in statistics, law, and policy enforcement in the present country. In this study, we first summarized the criteria of Korean and international industrial classification, and then examined whether the current classification of security meets these criteria. Next, to examine the classification directions of newly formed industries such as security industry, we reviewed some cases of domestic industrial special classification and types, and proposed the industrial classification criteria and direction of the security industry on the basis of them.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.13-24
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• 2004

Anthropometric data is a fundamental resource in developing ergonomic products and workplaces. However, designers often experience difficulty in searching anthropometric data relevant to the design due to the technicality of anthropometric terminologies, ambiguity in the description of measurement method for some anthropometric variables, and inefficiency of existing search methods for anthropometric data. The present study suggests a method to develop a classification system of anthropometric variables for systematic, efficient search of anthropometric data. The proposed method first classifies anthropometric variables according to body segment and type of variable, and then arranges anthropometric variables of the same body segment and variable type by comparing the heights of their reference points. The proposed classification method was applied to establish a classification system of 66 anthropometric variables that were selected for an automotive interior design. Then the established anthropometric classification system was utilized to design a search interface of a web-based anthropometric data retrieval system.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.760-762
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• 2003

This study confirmed the usefulness of short-wavelength infrared (SWIR) in the discrimination and classification of evergreen forest types. A forested area near Hisayama and Sasaguri in Fukuoka Prefecture, Japan, served as the study area. Warm-temperate forest vegetation dominates the study site vegetation. Coniferous plantation forest, natural broad-leaved forest, and bamboo forest were analyzed using LANDSAT5/TM and SPOT4/HRVIR remote sensing data. Samples were extracted for the three forest types, and reflectance factors were compared for each band. Kappa coefficients of various band combinations were also compared by classification accuracy. For the LANDSAT5/TM data observed in April, October, and November, Bands 5 and 7 showed significant differences between bamboo, broad-leaved, and coniferous forests. The same significant difference was not recognized in the visible or near-infrared regions. Classification accuracy, determined by supervised classification, indicated distinct improvements in band combinations with SWIR, as compared to those without SWIR. Similar results were found for both LANDSAT5/TM and SPOT4/HRVIR data. This study identified obvious advantages in using SWIR data in forest-type discrimination and classification.

• Journal of Pharmaceutical Investigation
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• v.36 no.3
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• pp.161-167
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• 2006

The objective of this study was to investigate the dissolution patterns of variety of orally administered drug products available on the market. It aimed to understand their dissolution behaviors on the basis of the biopharmaceutics classification system (BCS) concept. On the tenets of BCS, several active pharmaceutical ingredients were selected: fluoxetine hydrochloride (class I), naproxen sodium (class ll), pyridostigmine bromide (class III), furosemide (class IV) and simvastatin (class IV). Typical dissolution media used in this study were pH 1.2, pH 4 & 6.8 phosphate buffers, and water. In cases, particular dissolution media specified in the KP and/or USP were used. Dissolution patterns of fluoxetine hydrochloride and pyridostigmine bromide products were characterized by their rapid release In addition, their dissolution characteristics were relatively unaffected by the type of a dissolution medium. Similar dissolution patterns were observed with pH 1.2, pH 4 & 6.8 phosphate buffers and water. By sharp contrast, poor dissolution patterns were noticed with naproxen sodium products, when pH 1.2 and pH 4 phosphate buffer were used. Improvements in its dissolution were achieved by switching the dissolution media to pH 6.8 phosphate buffer or water. Unsatisfactory dissolution data also were observed with a simvastatin product, when it was subject to dissolution tests by use of a surfactant-free pH 1.2, pH 4 & 6.8 phosphate buffers and water. All the release patterns reported in this study were best understood when BCS concepts were implemented. Our results demonstrated that a BCS-based drug classification should be considered first to choose a dissolution test/method and set up dissolution specification.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.1-24
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• 2016

With the innovation of information technology, non-face-to-face robo advisor with high accessibility and convenience is spreading. The current robot advisor recommends appropriate investment products after understanding the investment propensity based on the structured data entered directly or indirectly by individuals. However, it is an inconvenient and obtrusive way for financial consumers to inquire or input their own subjective propensity to invest. Hence, this study proposes a way to deduce the propensity to invest in unstructured data that customers voluntarily exposed during consultation or online. Since prediction performance based on unstructured document differs according to the characteristics of text, in this study, classification algorithm optimized for the characteristic of text left by financial consumers is selected by performing prediction performance evaluation of various learning discrimination algorithms and proposed an intelligent method that automatically recommends investment products. User tests were given to MBA students. After showing the recommended investment and list of investment products, satisfaction was asked. Financial consumers' satisfaction was measured by dividing them into investment propensity and recommendation goods. The results suggest that the users high satisfaction with investment products recommended by the method proposed in this paper. The results showed that it can be applies to non-face-to-face robo advisor.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.189-196
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• 1999

Until now, Many approach to use the layer or attribute items in GIS the classification results of remotely sensed images is going on, but It was rarely ever tried to use the results of fuzzy classification in GIS. The fuzzy classification can be accurate than any other classification methods of remotely sensed images and can separately extract the result for each classification items. In this study, We applied to GIS database implementation with fuzzy classification result. In the process of this study, We convert the fuzzy classification image into the grid of GIS database, and Membership Grade Value files transformed to table database into the GIS. And then Membership Grade Values related to each grid-cell of database be able to verify with pointer layer. Finally, we can use the fuzzy classification images in GIS database.