Earticle

Concerns about food safety continue to rise and under this situation, governments of some countries have reinforced their regulations more strictly for food safety. In order to prevent food safety incidents or, at least to minimize the impact, the preparedness is very important. As a consequence of this, traceability system has become an essential tool for food safety. Recently, it requires more prevention-based food safety control system. One of the most generally used systems for food safety control is Hazard Analysis and Critical Control Point (HACCP). Both traceability and HACCP systems can be integrated through Electronic Product Code (EPC) Sensor Network technologies which have four value propositions. In this paper, we will introduce the concept of product and process traceability system (P2TS) through the integration of three systems to improve food safety management. The final aim is to find out the added values of the P2TS.

좋은 제품 품질은 기업의 성공을 가능하게 하는 데에 매우 필수적이기 때문에 기술 개발을 통한 제품 품질 개선 방안은 많은 최고경영자들이 숙고하는 가장 중요한 문제들 중 하나이다. 기술 개발을 통한 제품 품질 개선과 관련하여, 본 연구는 정보 기술 분야의 중소기업들의 외부 정보 네트워크의 다양성이 생산 공정 개선을 통해 제품 품질 개선에 미치는 영향에 대한 실증 분석을 시도 하였다. 본 연구는 최소자승 회귀분석을 통해 310개의 IT 중소기업을 실증 분석하여 다음과 같은 2가지 중요 사항을 조명한다. 첫째, IT 중소기업의 외부 정보 네트워크의 다양성은 기술 개발을 통한 제품 품질 개선 에 정(+)의 영향을 미친다. 둘째, IT 중소기업의 생산 공정 개선은 외부 정보 네트워크의 다양성이 제품 품질 개선에 미치 는 정(+)의 영향을 부분 매개 한다.

Good product quality is so essential to enabling firms to succeed that how to make the product quality better through technology development is one of the most important issues that many CEOs think over. With regard to the product quality improvement from firms’ technology development, this study has made an attempt to empirically investigate the effect of the external information network diversity on the product quality improvement of the small and medium-sized enterprises (SMEs) in the information technology (IT) sector, mediated by their production process improvement. This research illuminates the following two points by empirically analyzing the 310 IT SMEs through the ordinary least squares regression analysis. First, IT SMEs’ external information network diversity has a positive influence on their product quality improvement from technology development. Second, IT SMEs’ production process improvement partially mediates the impact of their external information network diversity on the product quality improvement.

This paper presents a method of detecting chatter vibration in end-mill process. The detecting system consists of an adaptive signal processing scheme which uses an autore- gressive time-series model and a neural network is proposed and is verified its effectiveness by using acceleration and cutting force signals recorded during slotting in end-mill operations. Expeerimental results indicate that the proposed system provides excellent detection when chatter is occured within the ranges of cutting conditions considered in this study and an effectiveness of the integration of signals is confirmed.

In the stereolithography process, the accuracy of product depends on laser power, scan speed, scan width, scan pattern, layer thickness, resin characteristics and so on. Therefore, appropriate process parameters are required for an accurate prototype. This paper presents a method to determine the key process parameters, i.e., laser scan speed, hatching space, and layer thickness based on scan length, scan area, and layer slope. In order to determine these parameters, three neural networks are employed to represent operator’s experience and knowledge. Optimum values on scan speed, hatching space and layer thickness are recommended to improve the surface roughness and build time on the developed SLA machine.

본 논문은 <셰익스피어 인 러브> 시청자가 영화를 보는 과정에서 어떻게 스토리를 이해하고 감흥하는 지, 영화의 인물관계망을 중심으로 관객의 인지 감성 스키마를 분석하는 데에 목적이 있다. 본 논문에서는 4개의 인물 관계망 그림을 절차적으로 제시함으로써, 이들은 왜, 그리고 어떻게 셰익스피어가 『로미오와 줄리엣』이라는 불후의 명작을 젊은 나이에 성숙하게 비극으로 만들어 낼 수 있었는지에 대한 스토리 개연적 증거를 제시한다. 필자는 주인공 셰익스피어의 심리를 라캉의 “주체의 열망” 이론을 방법론으로, 셰익스피어의 글쓰기 과정이 셰익스피어로 하여금 영국 르네상스 시기의 대가로 도약하는 계기임을 분석했다. 본 연구는 어떻게 셰익스피어가 엘리자베스 여왕 영국 제국주의의 전성기 시대에 비올라를 욕망의 주체로 삼아서, 크리스토퍼 말로를 제치고 상류 사회로의 진입을 통해 예술적 대가로 도약하게 되었는지, 시청자의 스토리텔링 아키텍처를 인지 감성 과정으로 분석하였다.

This paper has the aim to track down the viewers’ cognitive emotion of how they are interacting with the story of Shakespeare in Love. Human minds have cognitive and emotional flows while plots, characters, and action-ideas are intertwined in the story of the film. This paper especially focused on the analysis of characters’ networks with four statistical data pictures in order to schematize the storytelling architecture on how and why Shakespeare has strongly motivated to write a great star-crossed love play, Romeo and Juliet in his very young age. This paper examines that Shakespeare’s subject of desire is to accomplish both a true love and a sincere play which can make the nature of love true. The desire of subject is always slipped aside into scattering with “object a.” In the film of Shakespeare in Love, the “object a” is a writing process and has a product of Romeo and Juliet as well.

As the IC(Integrated Circuit) has been densified and complicated, it is required to thorough process control to improve yield. Experts, for this purpose, focused on the process analysis automation, which is came from the strict data management in semiconductor manufacturing. In this paper, we presents the process analysis system that can analyze causes, for a output after processes. Also, the plasma etching process that highly affects yield among semiconductor process is modeled to predict a output before the process. To approach this problem, we use adaptively trained neural networks that exhibit superior accuracy over statistical techniques. And in comparison with methods in other paper, a method that history of trend for input data is considered is shown to offer advantage in both learning and prediction capability. This research regards CD(Critical Dimension) that is considerable in high integrated circuit as output variable of the prediction model.

In highly automated milling process, in-process monitoring of the malfunction is indispensable to ensure efficient cutting operation. Among many malfunctions in milling process, chatter vibration deteriorates surface finish, tool life and productivity. In this study, the monitoring system of chatter vibration for face milling process is proposed and experimentally estimated. The monitoring system employs two types of sensor such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are extracted in time domain for the input patterns of neural network to reduce time delay in signal processing state. The resultes of experimental evaluation show that the system works well over a wide range of cutting conditions.

This study aimed to describe the process of building an allergic rhinitis practice-based research network (PBRN) in Korean Medicine clinics, identify barriers, and propose solutions for future PBRN studies. The PBRN study was designed to evaluate the therapeutic effects of “decoction forms of herbal medicine,” which are difficult to study through clinical trials in South Korea. Based on the research experience of this study, seven solutions were proposed. It is necessary to develop a plan for KM doctors to increase their understanding of research, collect comprehensive endpoint data, and set widely applicable study designs. There is also a need to create mandatory research monitoring plans and foster networking among PBRN participants. Before participating in the study, rehearsal programs for new KM doctors and close relationships between primary care doctors and researchers will help ensure a successful PBRN clinical study. PBRNs can be an effective platform for providing KM clinical data and a source of KM big data. Given the growing demand for evidence-based practices in KM, clinical studies conducted in KM clinics are likely to be actively pursued in the future.

도서정가제란 2003년 2월부터 시행된 출판 및 인쇄 진흥법에 따라 책을 정가에 판매토록 의무화한 제도이다. 이의 적용수준을 더욱 강화하려는 출판계의 노력에 따라 할인율을 낮추고 적용 기관 범위를 넓히는 것을 주요 골자로 한 출판문화산업 진흥법 개정안이 2014년 4월 국회 본회의를 통과하여 11월에 시행되었다. 도서관계의 관점에서는 이 개정으로 도서정가제 적용 예외 기관이었던 도서관이 적용 기관으로 변경됨에 따라 자료 구입 축소와 구입 비용 상승 등의 문제가 발생하였고, 이에 대한 대안으로 예산 확충에 대한 필요성이 인식되었다. 본 연구의 목적은 도서관계의 정책행위자들이 개정안 통과와 시행 과정에서 어떠한 입장과 역할을 하였는지 분석하는 것이다. 이를 통해 정책행위자 간의 상호작용 구조를 파악하는데 용이한 정책네트워크 모형을 적용하여 이의 유용성을 확인하고 개선점을 제안한다. 본 연구는 기존의 정책네트워크 모형 적용 연구에서 살펴보지 못했던 행위자 내부의 특성을 분석하였다는 점에서 의의가 있다.

The Fixed book price policy, a portion of publication and printing promotion act applied from February 2003 in the South Korea, is a system of fixed book prices that administered by a government body. The publishing industries had been attempted to lower the discount rate and to extend the application scope. The amendment for the attempts was passed in April 2014, and implemented from November 2014. From the library point of view, this amendment caused a reduction of buying library materials. For this reason, the agenda about expansion of material budget in libraries has been recognized as the alternative. The purpose of this study is to analyze the stance and role of libraries as actors in the policy process. Based on this, this study also attempt to identify usefulness and improvement point of Policy Network Model. For this purpose, this study identifies actor's internal characteristics as an improvement point that previous studies did not identified.

The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.

This study aimed to explore influencing factors on the establishment of the network system between public hospitals and to make a process evaluation of it. we analyzed the case of a strategic alliance contracted by a National University Hospital(NUH) and a Community Hospital(CH). Main points of the project were regular dispatch of clinical specialists in the NUH such as gastroenterologist and running teleradiology program. The NUH considered the improvement of it's image as a public hospital as a successful element of the network program. The provincial office which have to manage the CH satisfied with these program in terms of helping CH in need of clinical specialists. Staffs in the CH pointed out the problem of discontinuity for patients who visited the CH. Three institutes argued that continuous support of central government in the relevant institution and budget could play the most important role in the advance of the network system between public hospitals.

The wireless sensor network (WSN), is a type of self-organized distribution system without complex infrastructure requirement. However, WSN’s independence and un-attended usage limit its power supply and life expectancy. These become a critical issue for any WSN implementation. The in-network processing which, intends to minify data volume locally can greatly reduce the energy consumption of data delivery over a long distance to the sink. However, open problems are still remain with in-network processing, such as how to carry out in-network processing, and how to combine routing scheme to the sink (e.g. the long distance delivery). For any WSN application, the following pre-assumption is vital. There exists a physical signal field which bridges physical events to the sensors of WSN, otherwise WSN does not work. In fact, the physical signal field can be depicted by sensory data of all the nodes, and can even be used for local data convergence (e.g. in-network processing). An immediate solution which we propose is that, sensory data of the nodes can be converged to local extremes of the physical signal field along its gradient direction. Furthermore, the physical signal field is integrated with the cost field routing scheme. The cost field routing is in charge of delivering data to the sink. During the in-network processing, the delivery direction is derived by combining linearly the gradient directions of the cost field and physical signal field. Also simulation results show that the proposed schemes are robust, adaptable, and reliable to the variation of physical events.

Analytic Network Process (ANP) has been widely used in solving many complicated decision making problems. An approach to acquire the comprehensive weights of interval-valued Analytic Network Process (IV-ANP) is proposed. Firstly, the independent local interval-valued weights are obtained by solving the goal programming for interval-valued pairwise comparison matrices. Based on the interaction and feedback relationships among criteria and/or indices, an unweighted interval-valued supermatrix is formed. To avoid loss of information, an extreme value method is developed for acquiring the global weights of IV-ANP. Secondly, the alternatives are ranked on the basis of interval-valued preference order. Finally, with the interaction and feedback relationships between criteria and/or indices being considered, an index system for assessing the risk of dynamic alliance is presented. With the uncertain and inaccurate information during the evaluation process being considered, the proposed IV-ANP method is applied for risk assessment of dynamic alliance, and sensitivity analyses for some key risk factors are performed to show their impacts on the risk levels of alliance enterprises.

The Steam Assisted Gravity Drainage (SAGD) process is an enhanced method to extract oil from bitumen which involves surface and central process facilities. This paper describes the Central Process Facilities (CPF) of SAGD and proposes several retrofit plans to the Heat Exchanger Network (HEN). In this approach, the process integration scheme is applied to estimate the energy saving in HENs, and various cases are modeled in favor of a commercial simulator. Throughout this work, a minimum approach temperature of 10℃ is assumed. The results reveal that, due to the HEN optimization using process integration, the heating and cooling duties can be reduced to 29.68MW and 1.886MW, respectively. Compared with the Husky case, all cases considered in this study indicate a potential reduction of at least 6% in total cost, including investment and operation costs.

The power generation prediction problem can be seen as a time series prediction problem in nature. The traditional time series prediction methods based on regression analysis do not take account into the time accumulation effect existed in the time series due to their discrete input values. This limitation causes the low prediction accuracy of the time series prediction methods based on regression analysis. To solve this problem, a power generation time series prediction model based on the process neural network is proposed. The inputs of the proposed prediction model can be continuous time-varying functions. The time accumulation effect existed in the power generation time series can be expressed and computed by the integration operator of the process neural network. The proposed prediction model is trained and the efficiency of the proposed prediction model is tested by the month power generation data form January 2001 to April 2012, and the comparison experiment results indicate that the process neural network performs better than the auto regression analysis.

The improvement of the communication systems is conducted through communication protocol engineering and optimization process. This paper presents an effort to upgrade the IEEE 802.16 and IEEE 802.16e protocol performance regarding the delay during subscriber network entry or base station handover. Our communication protocol engineering process of WiMax protocol and its optimization resulted in a new UCD-aware initial ranging transmission opportunity slots distribution. Using an analytical and numerical performance evaluation, we prove the relevance of the new algorithm and the increase of the IEEE 802.16-based network performance.

본 연구는 소규모학교와 대학 통폐합 갈등을 네트워크 구조 측면에서 분석하였다. 전북지역․강원지역의 소규모학교와 강원대․삼척대와 전남대․여수대의 국립대학 통폐합 사례를 대상으로 사회 네트워크 분석방법을 적용하였다. 분석내용은 소규모학교와 대학 통폐합 갈등 네트워크 구조의 특성으로 갈등관계의 핵심 및 중간 연결자에 대한 소시오그램, 규모 및 집중도, 중심성 등에 대한 분석을 실시하였다. 그 분석결과는 다음과 같다. 첫째, 소규모학교는 별형, 대학은 순환형과 별형의 네트워크 구조 특성을 보였다. 학교에 부여된 자율성 정도에 따라 갈등 네트워크 구조의 차이가 나타났다. 둘째, 전북․강원지역의 소규모학교와 강원대․삼척대는 특정 행위자에 갈등이 집중된 반면, 전남대․여수대는 갈등관계 구조가 복잡하였다. 갈등관계가 많고 복잡할수록 갈등해소가 어려움을 보여준다. 셋째, 소규모학교는 교육부, 대학은 통폐합 추진 대학이 갈등 관계의 핵심 행위자로 나타났다. 교육기관 수준별로 주요 갈등당사자가 다르게 나타났다.

This study examined conflicts involved in the merger of small schools and national universities in South Korea in terms of network structure. Using the case studies of merged small schools in the Jeonbuk and Gangwon regions and of amalgamated national universities Kangwon-Samcheok and Chonnam-Yeosu, the study applied the social network analysis(SNA) method. The analysis addressed the characteristics of conflict network structure, including sociogram representing the core and nodes in conflict network, network size and centralization, and centrality. According to the analysis, first, the small schools showed the star-shaped network structure while the universities exhibited both the circular and star-shaped structure. The conflict network structure varied depending on the degree of autonomy. Second, in the case of small schools in Jeonbuk and Gangwon and of the amalgamated Kangwon-Samcheok University, the relationship conflict was found to be concentrated on specific actors, whereas the merged Chonnam-Yeosu University showed a complex conflict network structure. The study found that the more extensive and complex the conflict network, the more difficult to resolve the conflict. Third, the Ministry of Education was the key actor of conflict network for small schools, while the university leading the merger was the key actor. Primary conflict parties varied depending on the level of educational institutions.

본 연구에서는 인공신경망 알고리즘을 이용하여 생물공정에서 수집된 형광스펙트럼 데이터를 분류, 분석하고 공정변수들을 예측하기 위한 공정의 모델링에 대해서 논의하였다. SOM에 의해 분류된 전파장 스펙트럼 데이터들은 발효공정의 변수와 형광데이터 사이에 비선형관계를 설명하기 위하여 사용되었다. BPNN알고리즘은 SOM에서 분류된 데이터들을 입력자료로 이용하여 공정에 대한 모델식을 세우고, 이를 이용하여 배출가스 내 CO2 농도 및 발효액 중 세포농도와 같은 공정변수들을 예측하는데 사용되었다. 또한 BPNN 모델은 강력하면서도 훈련데이터의 범위를 넘어서는 공정의 데이터들을 예측할 수 있기 때문에 폭넓은 활용가능성을 가지고 있다.

A two-dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E. coli for the production of 5-aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyed using artificial neural networks, i.e. self-organizing map (SOM) and feedforward backpropagation neural network (BPNN).Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process performance, e.g. forecasting the process performance.

Outliers, unexpected extraordinary observations that look discordant from most observation in a data set are commonplace in various kinds of data analysis. Since the effect of outliers on model identification could be serious, the aim of this paper is to present some ways of handling outliers in given data set and to specify a model in the presence of outliers. A procedure based on neural network which identifies outliers, removes their effects, and specifies a model for the underlying process is proposed. In contrast with traditional parametric methods requiring to estimate the model's structure and parameters before detecting outliers, the proposed procedure is a nonparametric method without the estimation of model's structure and parameters before handling outliers and could be applied for real problems in the presence of outliers. The proposed methodology is performed as followings. Firstly, outliers are detected and the detected outliers replace the prediction values using outliers detection neural network. The data set removing the effect of outliers is retraining using neural network. Therefore the effects of outliers are removed and the modeling precision can be improved. Experimental results show that the proposed method is suitable for predicting data set in the presence of outliers.