• Title/Summary/Keyword: Product Space Model

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Prediction of Spring-in of Curved Laminated Composite Structure (굴곡 형상 복합재 구조물의 스프링-인 예측)

  • Oh, Jae-Min;Kim, Wie-Dae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.43 no.1
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    • pp.1-7
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    • 2015
  • This paper predicts the spring-in effect of curved laminated composite structure for various stacking sequence using finite element analysis(ABAQUS). In composite manufacturing process, large temperature difference, different coefficient of thermal expansion and chemical shrinkage effect cause distortion of composite parts such as spring-in and warpage. Distortion of composite structure is important issue on quality of product, and it should be considered in manufacturing process. In finite element analysis, a CHILE(Cure Hardening Instantaneously Linear Elastic) model and chemical shrinkage effects are considered developing user subroutine in ABAQUS and some cases are simulated.

The Impact of the Internet Channel Introduction Depending on the Ownership of the Internet Channel (도입주체에 따른 인터넷경로의 도입효과)

  • Yoo, Weon-Sang
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.1
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    • pp.37-46
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    • 2009
  • The Census Bureau of the Department of Commerce announced in May 2008 that U.S. retail e-commerce sales for 2006 reached $ 107 billion, up from $ 87 billion in 2005 - an increase of 22 percent. From 2001 to 2006, retail e-sales increased at an average annual growth rate of 25.4 percent. The explosive growth of E-Commerce has caused profound changes in marketing channel relationships and structures in many industries. Despite the great potential implications for both academicians and practitioners, there still exists a great deal of uncertainty about the impact of the Internet channel introduction on distribution channel management. The purpose of this study is to investigate how the ownership of the new Internet channel affects the existing channel members and consumers. To explore the above research questions, this study conducts well-controlled mathematical experiments to isolate the impact of the Internet channel by comparing before and after the Internet channel entry. The model consists of a monopolist manufacturer selling its product through a channel system including one independent physical store before the entry of an Internet store. The addition of the Internet store to this channel system results in a mixed channel comprised of two different types of channels. The new Internet store can be launched by the independent physical store such as Bestbuy. In this case, the physical retailer coordinates the two types of stores to maximize the joint profits from the two stores. The Internet store also can be introduced by an independent Internet retailer such as Amazon. In this case, a retail level competition occurs between the two types of stores. Although the manufacturer sells only one product, consumers view each product-outlet pair as a unique offering. Thus, the introduction of the Internet channel provides two product offerings for consumers. The channel structures analyzed in this study are illustrated in Fig.1. It is assumed that the manufacturer plays as a Stackelberg leader maximizing its own profits with the foresight of the independent retailer's optimal responses as typically assumed in previous analytical channel studies. As a Stackelberg follower, the independent physical retailer or independent Internet retailer maximizes its own profits, conditional on the manufacturer's wholesale price. The price competition between two the independent retailers is assumed to be a Bertrand Nash game. For simplicity, the marginal cost is set at zero, as typically assumed in this type of study. In order to explore the research questions above, this study develops a game theoretic model that possesses the following three key characteristics. First, the model explicitly captures the fact that an Internet channel and a physical store exist in two independent dimensions (one in physical space and the other in cyber space). This enables this model to demonstrate that the effect of adding an Internet store is different from that of adding another physical store. Second, the model reflects the fact that consumers are heterogeneous in their preferences for using a physical store and for using an Internet channel. Third, the model captures the vertical strategic interactions between an upstream manufacturer and a downstream retailer, making it possible to analyze the channel structure issues discussed in this paper. Although numerous previous models capture this vertical dimension of marketing channels, none simultaneously incorporates the three characteristics reflected in this model. The analysis results are summarized in Table 1. When the new Internet channel is introduced by the existing physical retailer and the retailer coordinates both types of stores to maximize the joint profits from the both stores, retail prices increase due to a combination of the coordination of the retail prices and the wider market coverage. The quantity sold does not significantly increase despite the wider market coverage, because the excessively high retail prices alleviate the market coverage effect to a degree. Interestingly, the coordinated total retail profits are lower than the combined retail profits of two competing independent retailers. This implies that when a physical retailer opens an Internet channel, the retailers could be better off managing the two channels separately rather than coordinating them, unless they have the foresight of the manufacturer's pricing behavior. It is also found that the introduction of an Internet channel affects the power balance of the channel. The retail competition is strong when an independent Internet store joins a channel with an independent physical retailer. This implies that each retailer in this structure has weak channel power. Due to intense retail competition, the manufacturer uses its channel power to increase its wholesale price to extract more profits from the total channel profit. However, the retailers cannot increase retail prices accordingly because of the intense retail level competition, leading to lower channel power. In this case, consumer welfare increases due to the wider market coverage and lower retail prices caused by the retail competition. The model employed for this study is not designed to capture all the characteristics of the Internet channel. The theoretical model in this study can also be applied for any stores that are not geographically constrained such as TV home shopping or catalog sales via mail. The reasons the model in this study is names as "Internet" are as follows: first, the most representative example of the stores that are not geographically constrained is the Internet. Second, catalog sales usually determine the target markets using the pre-specified mailing lists. In this aspect, the model used in this study is closer to the Internet than catalog sales. However, it would be a desirable future research direction to mathematically and theoretically distinguish the core differences among the stores that are not geographically constrained. The model is simplified by a set of assumptions to obtain mathematical traceability. First, this study assumes the price is the only strategic tool for competition. In the real world, however, various marketing variables can be used for competition. Therefore, a more realistic model can be designed if a model incorporates other various marketing variables such as service levels or operation costs. Second, this study assumes the market with one monopoly manufacturer. Therefore, the results from this study should be carefully interpreted considering this limitation. Future research could extend this limitation by introducing manufacturer level competition. Finally, some of the results are drawn from the assumption that the monopoly manufacturer is the Stackelberg leader. Although this is a standard assumption among game theoretic studies of this kind, we could gain deeper understanding and generalize our findings beyond this assumption if the model is analyzed by different game rules.

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Development of UAV Flight Control Software using Model-Based Development(MBD) Technology (모델기반 개발기술을 적용한 무인항공기 비행제어 소프트웨어 개발)

  • Moon, Jung-Ho;Shin, Sung-Sik;Choi, Seung-Kie;Cho, Shin-Je;Rho, Eun-Jung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.12
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    • pp.1217-1222
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    • 2010
  • This paper describes the Model-Based Development(MBD) process behind the flight control software of a close-range unmanned aerial vehicle(KUS-9). An integrated development environment was created using a commercial tool(MATLAB $Simulink^{(R)}$), which was utilized to design models for linear/nonlinear simulation, flight control law, operational logic and HILS(Hardware In the Loop Simulation) system. Software requirements were validated through flight simulations and peer reviews during the design process, whereas the models were verified through the application of a DO-178B verification tool. The integrity of automatically generated C code was verified by using a separate S/W testing tool. The finished software product was embedded on two different types of hardware and real-time operating system(uC/OS-II, VxWorks) to perform HILS and flight tests. The key findings of this study are that MBD Technology enables the development of a reusable and an extensible software product and auto-code generation technology allows the production of a highly reliable flight control software under a compressed time schedule.

A Study on the Improvement of Recommendation Accuracy by Using Category Association Rule Mining (카테고리 연관 규칙 마이닝을 활용한 추천 정확도 향상 기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.27-42
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    • 2020
  • Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

Strategy for Store Management Using SOM Based on RFM (RFM 기반 SOM을 이용한 매장관리 전략 도출)

  • Jeong, Yoon Jeong;Choi, Il Young;Kim, Jae Kyeong;Choi, Ju Choel
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.93-112
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    • 2015
  • Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

Designing an Intelligent Advertising Business Model in Seoul's Metro Network (서울지하철의 지능형 광고 비즈니스모델 설계)

  • Musyoka, Kavoya Job;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.1-31
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    • 2017
  • Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

Remaining Service Life Prediction of Concrete Structures under Chloride-induced Loads (염해환경하의 콘크리트 구조물의 잔존수명 예측)

  • Song, Ha-Won;Luc, Dao Ngoc The
    • Proceedings of the Korea Concrete Institute Conference
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    • 2008.04a
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    • pp.1037-1040
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    • 2008
  • In order to predict the remaining life of marine concrete structures under climatic loads, it is necessary to develop an analytical approach to predict the time and space dependent deterioration of concrete structures due to mainly chloride attack up to corrosion initiation and additional deterioration like cracking of cover concrete. This study aims to introduce FEM model for life-time simulation of concrete structures subjected to chloride attack. In order to consider uncertainties in materials as well as environmental parameters for the prediction, Monte Carlo Simulation is integrated in that FEM modeling for reliability-based remaining service life prediction. The paper is organized as follows: firstly general scheme for reliability-based remaining service life of concrete structures is introduced, then the FEM models for chloride penetration, corrosion product expansion and cover cracking are briefly explained, finally an example is demonstrated and the effects of localization of chloride concentration and corrosion product expansion on service life using above model are discussed.

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A characteristic-based technology measurement with market factor considered (시장요인이 고려된 특성치 준거 기술측정)

  • 김성철;유평일
    • Korean Management Science Review
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    • v.11 no.2
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    • pp.237-253
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    • 1994
  • Technology measurement is related with how to construct indicators of technological change and relative ranking of technological sophistication. Many attempts have been made to understand the measurement of technology. However, technology measurement still remains little understood problem in spite of its importance. This article is concerned with improving the measurement of technology by introducing market factors into the model. It illustrate a simple approach to the measurement of technology. This approach is based on the characteristic-space paradigm of technology. A relative ranking of technological sophistication for a product is measurable as a set of characteristics. The main feature of the proposed approach is the combination of technical factors and market factors. Technical factors are reflected in the definition of technological sophistication. Market factors are embraced in the determination of the relative importance assigned to each technology defining characteristics. Thus, the weight is determined by technical factors and market factors, which differentiates the study from the past based on judgmental technique such as experts' opinion.

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Stochastic response spectra for an actively-controlled structure

  • Mochio, Takashi
    • Structural Engineering and Mechanics
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    • v.32 no.1
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    • pp.179-191
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    • 2009
  • A stochastic response spectrum method is proposed for simple evaluation of the structural response of an actively controlled aseismic structure. The response spectrum is constructed assuming a linear structure with an active mass damper (AMD) system, and an earthquake wave model given by the product of a non-stationary envelope function and a stationary Gaussian random process with Kanai-Tajimi power spectral density. The control design is executed using a linear quadratic Gaussian control strategy for an enlarged state space system, and the response amplification factor is given by the combination of the obtained statistical response values and extreme value theory. The response spectrum thus produced can be used for simple dynamical analyses. The response factors obtained by this method for a multi-degree-of-freedom structure are shown to be comparable with those determined by numerical simulations, demonstrating the validity and utility of the proposed technique as a simple design tool. This method is expected to be useful for engineers in the initial design stage for structures with active aseismic control.

Approach to Characterization of a Diode Type Corona Charger for Aerosol Size Measurement

  • Intra Panich;Tippayawong Nakorn
    • KIEE International Transactions on Electrophysics and Applications
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    • v.5C no.5
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    • pp.196-203
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    • 2005
  • A semi-empirical method to determine the electrostatic characteristics of a diode type corona aerosol charger based on ion current measurement and electrostatic charging theory was presented. Results from mathematical model were in agreement with those from experimental investigation of the charger. Current-voltage characteristics, $N_{i}t$ product and charge distribution against aerosol size were obtained. It was shown that the space charge was significant and must be taken into account at high ion number concentration and low flow rate. Additionally, significant particle loss was evident for particles smaller than 20 nm in diameter where their electrical mobility was high. Increase in charging efficiency may be achieved by introducing surrounding sheath flow and applying AC high voltage. Overall, the approach was found to be useful in characterizing the aerosol charger.