• 전자공학회논문지A
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• 제28A권11호
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• pp.894-901
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• 1991

Contact-type linear image sensors have been fabricated by means of RF glow discharge decomposition method of silane and hydrogen mixtures. The dependences of the electrical and optical properties of these sensor on thickness, RF power, substrate temperature and ambient gas pressure have been investigated. the ITO/i-a-Si:H/Al structure film shows photosensitivity of 0.85 and photocurrent to dark current ratio ($I_{ph}/I_{d}$) of 150 at 5V bias voltage under 200${\mu}W/cm^[2}$ red light intensity. Under 200${\mu}W/cm^[2}$ green light intensity, the ratio is 100. In order to investigate photocarrier transport mechanism and to obtain ${\mu}{\gamma}$ product we have measured the I-V characteristics of these sensors favricated with several different deposition parameters under various light sources. The linear inage sensor for document reading has been operated under reverse bias condition with green light source, resulting in ${\mu}{\gamma}$ product of about 1.5$[\times}10^{-9}cm^{2}$/V.

• 경영과학
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• 제10권1호
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• pp.193-205
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• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• Bulletin of the Korean Chemical Society
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• 제9권3호
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• pp.161-164
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• 1988

Infrared multiphoton decompositions (IRMPD) of $BrCH_2CH_2CH_2CH_2Cl$ were studied by using the pulsed $CO_2$laser. At 0.3 J laser energy the experimentally observed product ratios could be reasonably explained by the RRKM calculation with initial excitation energy of ca. 80 Kcal/mol. The pressure dependence of product yields led us to conclude that the collisional deactivation by the inert gas decreased the yield of low energy dissociation channel more significantly.

• 한국산업보건학회지
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• 제16권1호
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• pp.27-35
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• 2006

The aim of this study was to identify the sources of benzene detected in airborne of casting workplace where benzene was not used as raw material. We have identified benzene by GC/FID and GC/MSD. In this pilot test, small size iron chamber(diameter 30 cm, height 20 cm) was used. As the raw materials, new sand, recovered sand, and mixed casting sand(new sand + solidifying agent + organic resin + coating material) was tested, respectively. In the new sand benzene was not detected, but in the recovered sand and the mixed casting sand was detected. Xylenesulfonic acid(solidifying agent), one of the mixed casting sand ingredients was thought to product benzene by thermal decomposition above $400^{\circ}$..., but the other raw materials(organic resin and coating material) were thought not to product benzene. In this experiment, the most of benzene by thermal decomposition was produced within 1 hour after pouring the iron solution($1560^{\circ}$...) in small size iron chamber. When the mixed casting sand with coating material was used, the concentration of the produced benzene was average 2.91 ppm(range 1.98~3.72 ppm), and without coating material, benzene concentration was average 0.11 ppm(range 0.08~0.14 ppm).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• 한국정밀공학회지
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• 제27권4호
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• pp.63-71
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• 2010

Modular design is a very important design methodology that allows designers to develop a product family at low product development and production cost. This design methodology is also very powerful for products that require frequent design changes due to customer requirements. Most research on modular design is focused on the modularization based on functional decomposition, physical interface and manufacturing process of parts. In this paper, we propose a modularization method that takes size of human body parts into consideration for products which have physical interactions with the products such as office chairs and sport machines. Evaluation of modular design is based on dependence measurement between every pair of components in the design. In addition we proposed a module sizing method for the maximization of customer satisfaction in MC(Mass Customization) environment.

• 한국경영과학회지
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• 제31권3호
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• pp.63-79
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• 2006

In this study we consider a CONWIP system in which the processing times at each station follow a Coxian distribution and the demands for the finished products arrive according to a compound Poisson process. The demands that are not satisfied immediately are either backordered or lost according to the number of demands that exist at their arrival Instants. For this system we develop an approximation method to calculate performance measures such as steady state probabilities of the number of parts at each station, proportion of lost demands and the mean number of backordered demands. For the analysis of the proposed CONWIP system, we model the CONWIP system as a closed queueing network with a synchronization station and analyze the closed queueing network using a product-form approximation method. A recursive technique is used to solve the subnetwork in the application of the product-form approximation method. To test the accuracy of the approximation method, the results obtained from the approximation method are compared with those obtained by simulation. Comparisons with simulation show that the approximation method provides fairly good results.

• 한국IT서비스학회지
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• 제13권2호
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• 품질경영학회지
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• 제30권4호
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• pp.137-153
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• 2002

Viewed as a more systematic approach of creating high quality products and bringing them into market at a lower cost and in significantly less time, it attracts the attention of quality designers to quality function deployment (QFD) approach. In attempt to reduce the design cycle, the industry has responded with concurrent design effort. In a sense, concurrent engineering refers to the integration of various activities within the broad scope of the product life cycle ［17］. Over the last ten years, much has been written about QFD but little has been available in terms of the underlying guide methodology. The methodology of QFD is quite simple and many will say that they have done it in the past but just have not formalized it into the form that this discipline requires. QFD ties the product, user, value, and manufacturing viewpoints together in a continuous process of defining the product design and manufacturing requirements. The value viewpoint recognizes the cost to obtain certain functionality, and the manufacturing viewpoint addresses conformance to requirements, but in a broader sense, the variability in production. In this paper, the QFD system acquisitions are described, and two heuristic approaches solving for the complex design process, especially the size reduction of design process and precedence-constrained relationship in QFD are proposed, and the empirical example is illustrated.

• Journal of Information Technology Applications and Management
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• 제29권3호
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• pp.43-55
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• 2022

In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.