• Proceedings of the International Union of Geodesy And Geophysics Korea Journal of Geophysical Research Conference
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• 2003.05a
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• pp.17-17
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• 2003

한반도에 있어서의 지진의 영향을 분석하기 위해서는 강지진동 연구가 필수적이다. 강지진동 자료가 부족한 한반도의 특성상 모사를 통해 연구하고 있다. 강지진동 분석을 하기 위해서는 되도록 노이즈가 포함되어 있지 않은 지진파자료를 선택하여 그 지진자료의 스펙트럼 분석을 통해 감쇠상수 k, Q 등을 구한다. 이러한 감쇠상수 값을 통해 한반도의 진동 특성을 이해할 수 있다. 그러나 감쇠상수를 구하는 과정에서 감쇠상수 분석에 사용된 지진자료에 노이즈가 더해졌을 경우, 어떤 형태로 스펙트럼 영역에 영향을 미치고, 감쇠상수에는 어떤 영향을 미치는 지를 연구하여 노이즈효과를 제거할 수 있는 최적화된 분석에 관한 연구가 선행되어야 한다고 본다. 따라서 이번 연구에서는 강지진동 모사프로그램을 가지고 노이즈효과를 적용하면서 감쇠상수에 노이즈가 어떤 영향을 미치는 지에 대한 수치 해석적 연구를 실시하였다. 합성지진파에 이 합성지진파와 전혀 다른 주파수 형태를 보이는 노이즈를 강도를 달리하면서 합성해 본 결과, 노이즈효과를 고려할 수 있는 몇 가지 요소가 있음을 알 수 있었다. 감쇠상수 k값을 강지진동 모사프로그램으로부터 값을 달리하며 합성해 본 결과 노이즈효과를 보이는 것을 알 수 있었으며, 감쇠상수 k를 선형회귀를 통해 $k_{s}$ 와 $k_{q}$를 구할 때의 적용 주파수 범위를 변화시켰을 때도 일정한 양상의 노이즈 효과를 보였다. 또 지진자료와 노이즈를 중첩시킨 지진파 시계열 자료의 정부분만을 감쇠상수 k를 구하는 선형회귀에 이용했을 경우에도 노이즈 효과를 보였다. 또한 계산되어 나온 감쇠상수 값으로부터 특정지역의 지반운동의 특성을 이해할 수 있는 스펙트럼 가속도, 최대 가속도, 및 최대속도 값에 따른 감쇠식을 구하였다. 이것을 한반도와 같은 판 내부 환경인 ENA 값과 비교하였으며 기존의 연구와도 비교하였다.심으로부터 지오이드까지의 거리, 지오이드로부터 지표까지의 거리를 정의해주었으며, 각 격자점의 수직구조를 정의하기 위해 깊이에 따른 각 매질의 밀도, P파의 속도, S파의 속도, P파에 대한 Q값, S파에 대한 Q값을 정의 해주었다. S파의 속도를 구하기 위해서 지구 내부 물질을 포아송 매질이라는 가정 하에, 관계식을 $Vp{\;}={\;}SQRT(3){\;}{\times}{\;}Vs$ 이용하였다. 획득한 모델치들을 이용해 동해와 동해 인근 지역에 대한 초기모델을 구축하였다. 약 1 × 10/sup 6/ e/sup -//sec·n㎡ 의 전자선량에 해당되며 이를 기준으로 각각의 illumination angle에 대한 임계전자선량을 평가할 수 있었다. 실질적으로 Cibbsite와 같은 무기수화물의 직접가열실험 시 전자빔 조사에 의해 야기되는 상전이 영향을 배제하고 실험을 수행하려면 illumination angle 0.2mrad (Dose rate : 8000 e/sup -//sec·n㎡)이하로 관찰하고 기록되어야 함을 본 자료로부터 알 수 있었다.운동횟수에 의한 영향으로써 운동시간을 1일 6시간으로 설정하여, 운동횟수를 결정하기 위하여 오전, 오후에 각 3시간씩 운동시키는 방법과 오전부터 6시간동안 운동시키는 두 방법을 이용하여 품질을 비교하였다. 각 조건에 따라 운동시킨 참돔의 수분함량을 나타낸 것으로, 2회(오전 3시간, 오후 3시간)에 나누어서 운동시키기 위한 육의 수분함량은 73.37±2.02%를 나타냈으며, 1회(6시간 운동)운동시키기 위한 육은 71.74±1.66%을 나타내었다. 각각의 운동조건에서 양식된 참돔은 사육초기에는 큰 변화가 없었으나, 사육 5일 이후에는 수분함량이 증가하여 15일에는 76.40±0.14, 75.62±0.98%의 수분함량을 2회와 1회 운동시킨 참돔의 육에서 각각 나타났다. 운동횟수에 따른 지

• Journal of Food Hygiene and Safety
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• v.27 no.2
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• pp.194-201
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• 2012

Facing a number of global food-related accidents, the concept and system for food traceability have been designed and introduced in many countries to manage the food-safety risks. To connect and harmonize the various food traceability-information in food traceability system according to the food supply chain, the coding system of identification-number for food-traceability has to be standardized. The GTIN (Global Trade Item Number) barcode system which has been globally standardized and implemented, is reviewed with the mandatory food-labeling regulation in expiration date of processed foods. The integration of GTIN-13 bar-code system for food-traceability is a crucial factor to expand its function in the food-related industrial areas. In this literature, the standard coding system of identification-number for food-traceability is proposed with 20 digit coding number which is combined with GTIN-13 bar-code (13 digit), expiration date (6 digit), and additional classification code (1 digit). This proposed standard coding system for identification-number has a several advantages in application for prohibiting the sale of hazard goods, food-recall, and inquiring food traceability-information. And also, this proposed coding system could enhance the food traceability system by communicating and harmonizing the information with the national network such as UNI-PASS and electronic Tax-invoice system. For the global application, the identification-number for food-traceability needs to be cooperated with the upcoming global standards such as GTIN-128 bar-code and GS1 DataBar.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.153-164
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• 2014

This study is to investigate the effects of intangible assets such as research & development, education & training and advertisement on firm values of high-technology firms and low-technology firms listed in the KOSDAQ market, and to analyze the value-relativeness between the audit quality of companies and the expenditure of intangible assets. The substitute measurement of firm values is Tobin's Q model. The sample period for positive analysis is from 2003 to 2008, and the samples, excepting for financial business, are manufacturing companies of closing accounts corporate on December, based on companies of KOSDAQ that are listed in security. Finally, data from about 305 companies are used in this analysis. Followings are the results of the analysis. First, research & development, education & training of high-technology firms have an effect on firm values, and education & training of low-technology have an effect on firm values. Second, we find that audit quality(BIG4) increases the value relevance of R&D expenditures of high-technology firms and audit quality(BIG4) increases the value relevance of education & training expenditures of low-technology firms. This paper is meaningful in that it verified the value-relativeness of cost of intangible assets compared with high-technology firms to low-technology firms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2899-2905
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• 2010

To be applicable under electronic health record system in order to ensure semantic interoperability of clinical information, the development principle for clinical information model to reflect objective and function is required. The aim of this study is to develop the development principles for clinical information model and evaluate the Clinical Contents Model. In order to develop the principle, from November 2008 to March 2009, the surveys about 1) definition, 2) function and 3) quality criteria were done, and 4) the components of advanced model were analyzed. The study was processed in 3 levels. Firstly in the development level, key words and key words-paragraph were driven from the references, and the principles were drawn based on the clinical or functional importance and frequency. In the application level, the 3 experts of clinical information model assessed 30 Clinical Contents Models by applying it. In the feedback level, the Clinical Contents Model in which errors were found was modified. As the results, 18 development principles were derived with 3 categories which were structure, process and contents. The Clinical Contents Models were assessed with the principles, and the 17 models were found that they did not follow it. During the feedback process, the necessity of the advanced education of the principle and the establishment of the regular quality improvement strategy to use it is raised. The proposed development principle supports the consistent model-development between clinical information model developers, and could be used as evaluation criteria.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.