• 정보처리학회논문지D
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• 제18D권2호
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• pp.111-122
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• 2011

오늘날 RFID 응용 시스템은 점차 발전되고 물류, 유통, 항만 그리고 제조 등 다양한 산업분야에서 적용되고 있다. RFID 응용 시스템 개발을 위한 국제 표준으로 EPCglobal 에서는 EPC Network 아키텍처를 제시하고 있다. EPC Network 아키텍처를 통해 개체의 고유정보(master information) 및 이력정보(event information)를 수집해야 한다. 그러나 개체의 고유정보 및 이력정보를 저장하고 있는 EPCIS의 경우는 수집된 EPC와 각 개체가 가지는 이력정보의 수에 의존적으로 통신 횟수가 증가하며, 개별적인 EPC에 대한 처리로 인해 동일한 EPCIS와 여러 번 통신해야 하는 문제점이 존재한다. 이러한 문제점은 EPCIS와의 통신시간의 증가로 인해 RFID 응용 시스템의 성능을 저하 시키게 된다. 따라서 본 논문에서는 EPCIS와의 통신 시간을 감소시키기 위하여 동일한 EPCIS와의 통신을 제거하는 EPCIS 주소별 그룹 질의 기법을 제시한다. 또한, 본 논문에서 제시한 기법을 적용하고 실제 EPC Network 환경을 구축하고 다양한 실험을 통하여 효용성을 검증하였으며 EPCIS의 통신 시간이 최대 99% 감소하는 것을 확인할 수 있었다.

• 대한치과기공학회지
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• 제40권3호
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• pp.151-162
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• 2018

Purpose: The main purpose of this study is to develop assessment measures for the quality of service for dental labs. Methods: In order to construct the measure of service quality assessment for dental labs, relevant modifications were extracted around theoretical studies, and the survey was conducted on dental technician workers through internet survey. final scale questions were extracted through exploratory factor analysis and confirmed factor analysis of measurement variables, the demographic characteristics of the subjects and the perceptual difference of dental labs were analyzed for the extracted variables. Results: The final five variants of the interactive factor analysis that include the ability to change employee growth, reliability, responsiveness, materiality, interoperability, confirmatory factor analysis excludes variations in employee growth wages, welfare benefits, by changing its name to network capabilities, the quality of service factors for the final dental labs consisted of five variations: network competence, reliability, responsiveness, materiality and interoperability. Conclusion : The service quality of the dental labs showed that the reliability of the product related to the dental materials and the product production responsiveness related to the production order, the Materiality of the materials and equipment of the dental labs, the Interoperability responsiveness related to dental orders, And the importance of network capability to form a mutual network.

• Journal of Communications and Networks
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• 제16권5호
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• pp.479-484
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• 2014

In this paper, we consider the construction of cyclic and quasi-cyclic structured q-ary low-density parity-check (LDPC) codes over a designated small field. The construction is performed with a pre-defined sliding-window, which actually executes the regular mapping from original field to the targeted field under certain parameters. Compared to the original codes, the new constructed codes can provide better flexibility in choice of code rate, code length and size of field. The constructed codes over small fields with code length from tenths to hundreds perform well with q-ary sum-product decoding algorithm (QSPA) over the additive white Gaussian noise channel and are comparable to the improved spherepacking bound. These codes may found applications in wireless sensor networks (WSN), where the delay and energy are extremely constrained.

• 제어로봇시스템학회논문지
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• 제18권9호
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• pp.854-862
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• 2012

The optimal design of batch-storage network by using periodic square wave model provides analytical lot sizing equations for a complex supply chain network characterized as multi-supplier, multi-product, multi-stage, non-serial, multi-customer, cyclic system including recycling and/or remanufacturing. The network structure includes multiple currency flows as well as material flows. The processes are represented by multiple feedstock/product materials with fixed composition which are very suitable for production processes. In this study, transportation processes that carry multiple materials with unknown composition are added and the time frame is changed from single period into multiple periods in order to represent nonperiodic parameter variations. The objective function of the optimization involves minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders in the numeraire currency. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a multiperiod subproblem for average flow rates and analytical lot-sizing equations. The multiperiod lot sizing equations are different from single period ones. The effects of corporate income taxes, interest rates and exchange rates are incorporated.

• 대한임베디드공학회논문지
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• 제17권2호
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• pp.77-83
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• 2022

In this paper, the two-stage object detection approach is proposed to implement a deep learning-based label inspection system on edge computing environments. Since the label printed on the products during the production process contains important information related to the product, it is significantly to check the label information is correct. The proposed system uses the lightweight deep learning model that able to employ in the low-performance edge computing devices, and the two-stage object detection approach is applied to compensate for the low accuracy relatively. The proposed Two-Stage object detection approach consists of two object detection networks, Label Area Detection Network and Character Detection Network. Label Area Detection Network finds the label area in the product image, and Character Detection Network detects the words in the label area. Using this approach, we can detect characters precise even with a lightweight deep learning models. The SF-YOLO model applied in the proposed system is the YOLO-based lightweight object detection network designed for edge computing devices. This model showed up to 2 times faster processing time and a considerable improvement in accuracy, compared to other YOLO-based lightweight models such as YOLOv3-tiny and YOLOv4-tiny. Also since the amount of computation is low, it can be easily applied in edge computing environments.

• Design & Manufacturing
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• 제17권4호
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• 대한전자공학회논문지
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• 제22권1호
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• pp.28-33
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• 1985

비가구 회로망에 대한 회로망 함수의 공자를 구하기 위한 변형된 방향성 지선각를 이수한다. 이를 이용하므로 위상수학적으로 Mason공식의 부소건에 관계없이 조직적으로 회로망 함수의 양자를 구 할 수 있다. 또한 각 결점에 대한 부선원를 칠함으로서 대부분의 소법항을 미리 기계적으로 제거할 수 있으며 그 만큼 간편하게 빨리 구할 수 있다. 또한 본 이론에 의한 회로망 함수를 구하는 방법은 과정전체를 통해서 주어진 회로망의 위상수학적 성질에 변화를 주지 아니한다.

• 한국경영과학회지
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• 제30권4호
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• pp.117-130
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• 2005

It is effective and desirable for a proper customer relationship management or marketing to focus on the specific customers rather than a number of non specific customers. This study forecasts the prospective purchasers with high probability to purchase a specific product. Artificial Neural Network( ANN) can classily the characteristics of the prospective purchasers but ANN has a limitation in comprehending of outputs. ANN is integrated into IRANN with IR of decision tree program C5.0 to comprehend and analyze the outputs of ANN. We compare and analyze the accuracy of ANN, IR, and IRANN each other.

• 지식경영연구
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• 제12권5호
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• pp.1-10
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• 2011

Forming a network, through Social Network Services (SNS), among a group of people who share the same hobby or interests could increase the information sharing among the members at an exponential rate. Moreover, SNS users' behavior extends beyond the traditional introverted consumption behavior to a proactive behavior by owning or actively sharing product information. For firms, such proactive consumer behavior translates into marketing effects such as the word of mouth (WOM) effect. Therefore, SNSs are accepted not only as a communications channel between firms and consumers but also as marketing channel, suggesting the possibility of a new revenue source. In this context, we will explore into the factors of SNS contents which conserve firms' image and product information, and effects of the factors on consumer attitude and WOM.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 춘계학술대회
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• pp.111-123
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• 2000

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a novel approach to the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy clustering algorithm and Fuzzy-ART neural network are applied to describe the states of disposal product with the membership functions and to make recycling cell formation. This approach leads to recycling and reuse of the materials, components, and subassemblies and can evaluate the value at each cell of disposal products. Application examples are illustrated by disposal refrigerators, compared fuzzy clustering with Fuzzy-ART neural network performance in cell formation.