• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.885-896
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• 2003

The typws of service using location Information are being various and extending their domain as wireless internet tochnology is developing and its application par is widespread, so it is prospected that LBS(Location-Based Services) will be killer application in wireless internet services. This location information is basic and high value-added information, and this information services make prior GIS(Geographic Information System) to be useful to anybody. The acquisition of this location information from moving object is very important part in LBS. Also the interfacing of acquisition of moving object between MODB and telecommunication network is being very important function in LBS. After this, when LBS are familiar to everybody, we can predict that LBS system load is so heavy for the acquisition of so many subscribers and vehicles. That is to say, LBS platform performance is fallen off because of overhead increment of acquiring moving object between MODB and wireless telecommunication network. So, to make stable of LBS platform, in this MODB system, acquisition of moving object location par as reducing the number of acquisition of unneccessary moving object location. We study problems in acquiring a huge number of moving objects location and design some acquisition model using past moving patternof each object to reduce telecommunication overhead. And after implementation these models, we estimate performance of each model.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.3
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• pp.134-147
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• 2019

The purpose of this study was to analyze the functional unit system of NCS landscape field for correction and supplementation of NCS landscape field and the contents of the four-year college landscape course subject. First, 24 unconsolidated four-year universities were selected, and FGI was conducted and verified for 816 courses in 24 universities. The results of the study are summarized as follows, with three sections three, nine divisions and 65 sub-category. First, landscape design subjects accounted for 40.0% of the subjects organized by four-year universities. In addition, the ratio of 12.9% for ecological landscape, 11.3% for landscape construction, 10.2% for others, 10.0% for landscape information, 6.6% for landscape culture and 3.7% for landscape management was surveyed. Balanced and efficient modification and reinforcement of NCS is required in the future. Second, 10(18.9%) units with matching NCS performance criteria and educational objectives were found to be capable of different units(18.9%), 15(28.3%), and 37subjects with inconsistent NCS unit capability (56.9%). Third, looking at the criteria for the reference of each unit of capability presented by the NCS, it is deemed that one unit of capability should be organized separately to improve the practical ability, since it includes the contents of basic knowledge learning. Fourth, the objectives pursued on the basis of the contents of the NCS capability unit and four-year college curriculum were developed by focusing on the development of unit capabilities in the field of landscape construction and landscape management compared to the field of landscape design. It has been shown that a balance is needed for future development. This study is intended to put forward further research that re-examine specific curriculum assessment criteria that have not been classified in the course of classifications based on the curriculum handbook, which excludes interferences from each school.

• Proceedings of The Korean Society of Health Promotion Conference
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• 2004.10a
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• pp.1-16
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• 2004

This paper considers the possibilities of health promotion from the following perspectives; (1) IUHPE, (2) socio-cultural similarities, (3) action research, and (4) learning from our past. 1. The IUHPE values decentralized activities through regions, and countries such as Japan, Korea, Hong Kong, Taiwan and China belong to NPWP region. Since IUHPE World Conference was held in Japan in 1995, Japan used to occupy more than 60% of NPWP membership. After 2001, membership is increasing rapidly in Chinese speaking sub-region. The transnational collaboration is still in its beginning phase. 2. Confucianism is one of key points. Confucian tradition should not be seen only as obstacles but as advantages to seek a form of health promotion more acceptable in East Asia. 3. Within the new public health framework, people are expected to create and live their health. However, especially in Japan, the tendency of 'lacking of face-to-face explicit interactions' is still common at health-promotion settings as well as academic settings. Therefore, the author tried participatory approaches such as asking WlFY (interactive questions designed for subjects to review their daily life and environment) and as introducing round table interactions. So far, majority of participants welcome new trials. 4. The following social phenomena are comparatively discussed after Japanese invasion and occupation of Korea ended in 1945; ·status of oriental medicine, ·separation of dispensary services, and ·health promotion specialist as a national license. In contrast to Japanese' tendency of maintaining the status quo and postponing of substantial social change, trend toward rapid and dynamic social changes are more commonly observed in Korea. Although all of above possibilities are still in their beginning stages, they are going to offer interesting directions waiting for further challenges and accompanying researches.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.1
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• pp.46-55
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• 2011

The importance of forests and plants are appreciated by all of us, but it is often overlooked because we are surrounded by it. The arboretum is one of facilities which provide users with education on the environment, knowledge about plants, and recreation, playing a role as a nature school by exhibiting and collecting plants of various ecosystems. Anyone can enjoy fresh air, a pleasant environment, and knowledge about a wide variety of plants on the condition that they aactually visit it and pay the entrance fee. However, it has not been measured whether the expense which users pay to enjoy an arboretum is a true value of arboretums. The environment that arboretums offer is extra-market goods, or public goods. A variety of ideas and methods to measure the value of public goods have been researched among economists, statisticians, and mathematicians. The Contingent Valuation Method(CVM) is most widely used a s an assessment method on environment goods and adopted as an estimation method for compensation for restoration of the environment by the American Supreme Court. The purpose of this study is to suggest a current monetary value correspondingent to the value of arboretums by applying the CVM. The survey suggested that when an arboretum provides a high educational value and when the respondents have a higher income, it is more likely that they would be willing to pay for entrance into the arboretum. The quantified value in monetary terms for the environmental value of Gyeongnam Arboretum is WTP mean \15,648; WTP median \13,648; and WTP truncated \15,449 per visitor. In annual terms, the amounts are calculated at WTP mean \8,408,265,024; WTP median \7,333,589,024; and WTP truncated \8,301,334,762. These quantified amounts can be thought to represent the value of conservation of arboretums and awaken users to the precious value of nature. Also, they are helpful to let the general public have proper knowledge about and recognize the value of arboretums and forests.

• Journal of Korean Home Economics Education Association
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• v.33 no.3
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• pp.85-105
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• 2021

The purpose of this study is to develop and implement cooperative consumption education programs using design thinking in middle school home economics education classes to understand the impact on students' cooperative problem solving competency. Accordingly, a cooperative consumption education program based on design thinking was developed according to the ADDIE model, and the evaluation was conducted on a total of 25 students. The results of the study were as follows. First, based on prior research, we developed a consumption education program based on D. school's design thinking process under the theme of 'Creating a Shared School' for the practice of cooperative consumption. As a result of expert validity verification of the teaching/learning course plan and workbook for the eight sessions, the average question was 4.72 (out of 5 points) and the average CVI was 0.93, indicating that the content validity and field suitability were excellent. Second, to summarize the results achieved from the implementation of the cooperative consumption education program, the pre-/post-test using the revised and supplemented cooperative problem-solving competency tool, and the open-ended survey, It was confirmed that the developed program had a significant effect on improving not only the students' knowledge and perceived necessity for cooperative consumption along with the awareness of practice, but also the cooperative problem-solving competency. As a follow-up study, we propose to expand the research to a wider audience, and to further conduct research and develop programs applied with design thinking in home economics curriculum and in consumer competency development. This study confirmed that cooperative consumption education programs using design thinking are effective in improving youth's cooperative problem-solving competency and is meaningful in that they developed consumption education programs under the theme of 'cooperative consumption' in response to changing consumer education needs.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.91-107
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• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Journal of Nutrition and Health
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• v.57 no.4
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• pp.451-467
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• 2024

Purpose: This study aimed to develop a four-hour food additive education program for elementary school students to provide them with accurate information on food additives. Methods: A survey was conducted among 133 elementary school students living in Gyeonggi Province to identify the level of food additive awareness. A four-hour food additive education program and educational materials (PPT, activity sheets, and teacher guidelines) were developed based on the results of the food additive awareness survey. The developed educational programs were based on the Theoretical Model of Stages of Behavior Change. An elementary school nutrition teacher conducted a pilot education for 83 elementary school students to evaluate the feasibility of the developed education program. A survey was conducted to evaluate the effectiveness and satisfaction of the pilot education program. Results: The results of the Food Additive Awareness Survey showed that only 42.1% of people were aware of food additives; 46.3% wanted to know more about food additives, and 54.3% required food additive education. Food coloring (44.7%) and artificial sweeteners (18.7%) were the most common food additives of interest. What they wanted to know about food additives was the safety of food additives (36.8%) and the role and function of food additives (20.3%). After the pilot training on food additives, the level of awareness of food additives was improved significantly, and the percentage of participants who recognized the need for food additive education and promotion increased. According to the satisfaction survey of the food additives education, the interest, understanding, real-life application, learning method, and content amount were approximately 90%. Conclusion: The educational program developed through this study will change the negative perceptions of food additives in elementary school students to a positive one. It will do so by helping nutrition educators educate students on this important subject.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.