• Journal of Information Technology Services
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• v.15 no.2
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• pp.169-184
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• 2016

Smartphone use is rapidly spreading due to the advantage of being able to connect to the Internet anytime, anywhere--and mobile app development is developing accordingly. The characteristic of the mobile app market is the ability to launch one's app into foreign markets with ease as long as the platform is the same. However, a large amount of prior research asserts that consumers behave differently depending on their culture and, from this perspective, various studies comparing the differences between consumer behaviors in different countries exist. Accordingly, this research, which uses online product reviews (OPRs) in order to analyze the cultural differences in consumer behavior comparatively by nationality, proposes to compare the U.S. and South Korea by selecting ten apps which were released in both countries in order to perform a sentimental analysis on the basis of star ratings and, based on those ratings, to interpret the sentiments in reviews. This research was carried out to determine whether, on the basis of ratings analysis, analysis of review contents for sentiment differences, analysis of LDA topic modeling, and co-occurrence analysis, actual differences in online reviews in South Korea and the U.S. exist due to cultural differences. The results confirm that the sentiments of reviews for both countries appear to be more negative than those of star ratings. Furthermore, while no great differences in high-raking review topics between the U.S. and South Korea were revealed through topic modeling and co-occurrence analyses, numerous differences in sentiment appeared-confirming that Koreans evaluated the mobile apps' specialized functions, while Americans evaluated the mobile apps in their entirety. This research reveals that differences in sentiments regarding mobile app reviews due to cultural differences between Koreans and Americans can be seen through sentiment analysis and topic modeling, and, through co-occurrence analysis, that they were able to examine trends in review-writing for each country.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.365-374
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• 2005

The B2B electronic product commerce needs intermediary system to provide an integrated interface for the parts libraries of multiple suppliers. However, it is difficult to automatically integrate the parts libraries because they are heterogeneous. Existing ontology-based approaches show a limited functionality of automated integration of information because Dey can not prevent ontologies from being modeled in different ways, so that the inter-ontology mappings to resolve the heterogeneity become complicated and arbitrary. In order to overcome such problems this paper proposes an ontology modeling framework for parts libraries based on the Guarino's theory of upper ontology. The framework provides knowledge modeling primitives which have explicit formal meanings and modeling principles based on ontological natures. Using the framework, ontology developers can model the knowledge of parts libraries systematically and consistently, so that the resulting ontologies become comparable and uniform and the ontology merging algorithm for the automated information integration can be easily developed.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.4
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• pp.488-495
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• 2017

In this study, we conducted the kinetic hydration modeling of OPC and the final product according to the substitution ratio of GGBS by using the geochemical code, GEMS, in order to calculate the thermodynamic equilibrium. The thermodynamic data was used by GEMS's 3rd party database, Cemdata18, and the cement hydration model, the Parrot & Killoh model was applied to simulate the hydration process. In OPC modeling, ion concentration of pore solution and hydration products by mass and volume were observed according to time. In the GGBS modeling, as the substitution rate increases, the amount of C-S-H, which contributes the long-term strength, increases, but the amount of Portlandite decreases, which leads to carbonation and steel corrosion. Therefore, it is necessary to establish prevention of some deterioration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.874-880
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• 2018

3D modeling is extensively used in the field of architecture, machinery and contents production such as movies. Modeling is a time-consuming task. In order to compensate for these drawbacks, attempts have recently been made to reduce the production period by applying 3D scanning technology. 3D scanning for small objects can be done directly with laser or optics, but large buildings and sculptures require expensive equipment, which makes it difficult to acquire data directly. In this study, 3D modeling data for a large object is acquired using photometry with using drones to acquire the image data. The maintenance method for uniform spacing between the sculpture and the drone, the measurement method for the flight line were presented. In addition, we presented a production environment that can utilize the obtained 3D point cloud data for animation and a rendered animation result to find ways to make it in various environments.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.5
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• pp.871-883
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• 2018

This study tests consumer responses to online product recommendation service offered by a website. A product recommendation service refers to a filtering system that predicts and shows items that consumers would like to purchase based on their searches or pre-purchase information. The survey is conducted on 300 people in an age group between 20 and 40 years in a panel of an online survey firm. Data are analyzed using confirmatory factor analysis and structural equation modeling by AMOS 20.0. The results show that personalization quality does not have a significant effect on trust, but relationship quality and technology quality have a positive effect on trust. Three types of quality of recommendation service also have a positive effect on commitment. Trust and commitment are factors that increase service usage intentions. In addition, this study reveals the moderating effect of light users vs heavy users based on online shopping time. Light users show a negative effect of personalization quality on trust, indicating that they are likely to be uncomfortable to the service using personal information, compared to heavy users. This study also finds that trust vs commitment is an important factor increasing service usage intentions for heavy users vs light users.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.107-128
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• 2015

Technology innovation is a competitive weapon of sustainable economic growth at the urban and regional level and the growth of firms. In this study, we empirically investigate the effects of collaborative R&D activity on product innovative outputs and process innovative outputs in manufacturing firms in Korea. We analyze the links between collaborative R&D activity and two types of innovative outputs using an alternative negative binomial regression model. The major finding is that collaborative R&D activity has significant positive effects on both product and process innovation. The results also identify a positive link between all types of innovative outputs and other R&D activities including internal R&D activity, patent activity, external technology and capital goods acquisitions. To induce corporate growth that enhances the productivity of individual firms and produces prolonged economic growth, policy makers should place greater emphasis on creating effective arrangements to promote establishing collaborative R&D strategies for manufacturing firms.

• KSCI Review
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• v.14 no.2
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• pp.159-164
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• 2006

MES(Manufacturing Execution System) is a control system which supports basic activities(scheduling, working process and qualify management, etc) to execute working on the shop floor. As especially MES is a system to decrease the gap between production planning and operating, it executes functions that make decision between management and labor using real-time data. MES for real-time information processing requires certain conditions such as data modeling of RFID, which has recently attracted attentions, and monitoring of each product unit from manufacture to sales. However, in the middle of processing the unit with a RFID tag, transponders(readers) can't often read the tag due to reader's malfunctions, intentional damages, loss and the circumstantial effects; for that reason, users are unable to confirm the location of the product unit. In this case, users cannot avoid tracing the path of units with uncertain clues. In this paper, we suggest that the unique MES based on RFID and Bayesian Network can immediately track the product unit, and show how to evaluate it.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.21-21
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• 2018

Natural product substances have historically served as the most significant also be prepared by source of new leads for pharmaceutical development. They can chemical synthesis(both semisynthesis and total synthesis) and have played a important role in the field of organic chemistry by providing synthetic targets. Rcently, they have also been extended for commercial purpose to refer to medicinal products, health functional foods, dietary supplements and cosmetics from natural sources. A large number of currently prescribed drugs have been either directly derived from or inspired by natural products. However, with the advent of robotics, bioinformatics, high throughput screening(HTS), molecular biology-biotechnology, combinatorial chemistry, in silico(molecular modeling) and other methodologies, the pharmaceutical industry has largely moved away from plant derived natural products as a source for leads and prospective drug candidates. The strategy for natural prduct industry is now changing from drug approaches to health foods by identifying effective natural products as preparations. In Korea, a lot of development of natural product based drugs have been done, but very few on health functional foods. The concept of natural product based health foods is not active components as lead compounds but standardized extracts or preparation mixed with other medicinal plants. The representative material has been recently known to be a standardized ginseng extract "Ginsana G 115" developed by Swiss Pharmaton company. The purpose of this presentation is to underline how natural products research continues to make significant contributions in the domain of discovery and development of new health functional foods. It is proposed to present the development of high value added health food or health functional foods through scientific investigation on efficacy and standardization of new materials form natural products.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.27-39
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• 2006

Many real world cases in material failure analysis do not follow perfectly the normal distribution. Forcing of the normality assumption may lead to inaccurate predictions and poor product quality. We examine the failure process of the internal bond (IB or tensile strength) of medium density fiberboard (MDF). We propose a forced censoring technique that closer fits the lower tails of strength distributions and better estimates extremely smaller percentiles, which may be valuable to continuous quality improvement initiatives. Further analyses are performed to build an accelerated common-shaped Weibull model for different product types using the $JMP^{(R)}$ Survival and Reliability platform. In this paper, a forced censoring technique is implemented for the first time as a software module, using $JMP^{(R)}$ Scripting Language (JSL) to expedite data processing, which is crucial for real-time manufacturing settings. Also, we use JSL to automate the task of fitting an accelerated Weibull model and testing model homogeneity in the shape parameter. Finally, a package script is written to readily provide field engineers customized reporting for model visualization, parameter estimation, and percentile forecasting. Our approach may be more accurate for product conformance evaluation, plus help reduce the cost of destructive testing and data management due to reduced frequency of testing. It may also be valuable for preventing field failure and improved product safety even when destructive testing is not reduced by yielding higher precision intervals at the same confidence level.