• Journal of Korean Ophthalmic Optics Society
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• v.13 no.4
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• pp.25-30
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• 2008

Purpose: In this paper, we have analyzed the problems of the Oh's report which is used to the basic data for supply and demand of medical technicians and studied a proposal for improvement to control system and supply and demand of korean optometrists. Methods: We have analyzed errors of Oh's report including supply and demand for medical technicians and management policy, expecting number for future optician, inaccurate estimation by limited data (employment rate, retirement rate, mortality rate) and an incorrect method of measurement for future supply and demand. Results: Oh's report showed the 18% error for estimation of supply which exclude the irregular entrance students. The estimation of supply was calculated by graduation rate 62.6% (college and University of Technology are 78.9% and 85.98% respectively), employment rate 65.8% (the average employment between 2002 and 2007 is 73.96%) and retirement rate is 2.3% (the retirement of pharmacists is 1.3%) but it showed the significant differences to objective data. For estimate the suitable ratio of optometrists to the population, the ratio use of medical facilities by an age group was used, and suggested spectacle wearers 1,280 persons (populations 2,928 persons) per optometrist but the different from reference of Germany (4,706 persons), America (1,789 persons) and Korea (1,825 persons/an optometrist) are applied to estimation on supply. This report applied the low employment rate and argued that maintain the present situation, but claimed that utilize unemployment persons. The above result has induced double weighting effect on estimation of supply. Conclusions: To solve the related problems of supply and demand, we have to make a search for exact data and optimum application model, have to take an example of nation similar job category as Germany and the research result of the job satisfaction into consideration. After we get the integrated research result, we must carried out the policy with fairness and balance for the estimation of supply and demand. Therefore exact research is required prior to beginning policy establishment, government and related group have to make a clear long-term plan and permanent organization for medical technician to establish supply and demand of medical technician.

• Journal of Distribution Science
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• v.9 no.3
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• pp.15-23
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• 2011

This study examined the effects educational service elements have on the satisfaction of educational service; it also analyzed how such satisfaction influenced educational institutions' registration renewal and word-of-mouth communications about the schools. The key factors of educational services included the following four components: physical environment, education programs, instructors, and tuition fee. An investigation into how the factors of educational services in private educational institutions may affect consumer satisfaction was an additional goal of this study. Based on the cause-and-effect analysis of the above constructs, the degree of influence that each of the attributes and the component factors have on consumers' educational service selection, as well as the consumers' satisfaction, were explored. An empirical analysis was conducted on students who were taking classes in cram schools; the analysis was also conducted on the students' parents. The results indicated that the hypotheses regarding the elements of educational service, educational program, and the instructor factor were supported. Furthermore, a hypothesis concerning the effects educational service satisfaction has on re-registration and word of mouth was supported, as well. Upon aggregating the above study results, it was concluded that when determining the effects of satisfaction on educational service, the educational program, and the instructor factor played a crucial role, while physical surroundings and tuition did not. When addressing the influence of the educational services factors on educational services satisfaction, education programs and instructors had a positive effect, whereas physical environment and tuition fee had no statistically significant impact. According to the influence of educational services satisfaction on registration renewal and word-of-mouth effects, educational services satisfaction was found to be a positive influential factor for both. In addition, it was found that satisfaction of educational service had a positive effect on renewing enrollment and forming word-of-mouth recommendations. Although the research seems simple, some theoretical implications can be drawn, as follows: First, one interpretation of the findings that the programs' and instructors' factors had a positive effect on educational services satisfaction but the physical environment and tuition fee factors did not have a significant effect suggests that the greatest influence factors in educational services are educational programs and instructors. Second, increased educational services satisfaction may result in consumer behavior changing, resulting in more registration renewals and more favorable word-of-mouth comments. Third, increased educational services satisfaction may result in enhancing consumer responses, resulting in more registration renewals and more favorable word-of-mouth opinions. Further research directions should include developing an integrated model that will allow for variation over time, before and after purchases, in relation to consumers' choices of educational services.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.223-234
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• 2008

Recently the web service area provides the efficient integrated environment of the internal and external of corporation and enterprise that wants the introduction of it is increasing. Also the web service develops and the new business model appears, the domestic enterprise environment and e-business environment are changing caused by web service. The web service which provides the similar function increases, most the method which searches the suitable service in demand of the user is more considered seriously. When it needs to choose one among the similar web services, service consumer generally needs quality information of web service. The problem, however, is that the advertised QoS information of a web service is not always trustworthy. A service provider may publish inaccurate QoS information to attract more customers, or the published QoS information may be out of date. Allowing current customers to rate the QoS they receive from a web service, and making these ratings public, can provide new customers with valuable information on how to rank services. This paper suggests the agent-based quality broker architecture which helps to find a service providing the optimum quality that the consumer needs in a position of service consumer. It is able to solve problem which modify quality requirements of the consumer from providing the architecture it selects a web service to consumer dynamically. Namely, the consumer is able to search the service which provides the optimal quality criteria through UDDI browser which is connected in quality broker server. To quality criteria value decision of each service the user intervention is excluded the maximum. In the existing selection architecture, the objective evaluation was difficult in subjective class of service selecting of the consumer. But the proposal architecture is able to secure an objectivity with the quality criteria value decision where the agent monitors binding information in consumer location. Namely, it solves QoS information of service which provider does not provide with QoS information sharing which is caused by with feedback of consumer side agents.

• Journal of Environmental Impact Assessment
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• v.28 no.5
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• pp.427-439
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• 2019

Natural environmental ecology ofthe environmental impact assessment(EIA)is very much lacking in quantitative evaluation. Thus, this study attempted to evaluate quantitative assessment for ecosystem service in the site of Eco-delta project in Busan. As a part of climate change adaptation, this study evaluated and compared with the value for carbon fixation and habitat quality using the InVEST model before and after development with three alternatives of land-use change. Carbon fixation showed 216,674.48 Mg of C (year 2000), and 203,474.25 Mg of C (year 2015)reducing about 6.1%, and in the future of year 2030 the value was dropped to 120,490.84 Mg of C which is 40% lower than year 2015. Alternative 3 of land use planning was the best in terms of carbon fixation showing 6,811.31 Mg of C. Habitat quality also changed from 0.57 (year 2000), 0.35 (year 2015), and 0.21 (year 2030) with continued degradation as development goes further. Alternative 3 also was the highest with 0.21(Alternative 1 : 0.20, Alternative 2 : 0.18). In conclusion,this study illustrated that quantitative method forland use change in the process of EIA can helpdecision making for stakeholders anddevelopers with serving the best scenario forlow impact of carbon. Also it can help better for land use plan, greenhouse gas and natural environmental assets in EIA. This study could be able to use in the environmental policy with numerical data of ecosystem and prediction. Supplemented with detailed analysis and accessibility of basic data, this method will make it possible for wide application in the ecosystem evaluation.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.507-517
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• 2018

The probability of T/S cargo volume to decrease is the most notable problem associated with inappropriate mix of terminal operators in Busan port. Other problems include, the deterioration of the national carriers' competitiveness from non-operation of own terminal, excessively high proportion of financial operators in the engagement of operation which may result in their passiveness in timely investment, additional cost burden to carriers' in the handling inter-terminal T/S cargo transportation and inefficiency in terminal operation by the multiplicity of operators proved to be same recognized as so through the analysis. Therefore, in order to provide solutions for the problems and to strengthen Busan port's competitiveness, this research suggests the restructuring of operators mix as follows. To achieve sustainable growth of T/S cargo, global carriers' participation in terminal operation should be of utmost priority. To enhance the operational efficiency, the operators should be integrated. Similarly, the integration of operators will play a key role in verifying that national carriers' own terminal operation is an important factor in raising its competence. Finally, BPA's active engagement in the entire operation of port is also critical in public-oriented operation of the port. Whereas in the interactive analysis by taking the merits of Busan port into consideraion, global carrier's participation in operation, integration of operators and BPA's engagement in operation proved to contribute to the increase of T/S cargo and strengthening of operational efficiencies of Busan port.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.114-120
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• 2019

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.

• The Korean Journal of Archival Studies
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• no.50
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• pp.273-309
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• 2016

Unlike other government agencies, the city of Seoul experienced a three-year gap between the establishment of a function classification system and the introduction of a business management system. As a result, the city has been unable to manage the current status of the function classification system, and this impeded the establishment of standards for records management. In September 2012, the Seoul Metropolitan Government integrated the department in charge of the standard sheet for record management with the department of function classification system into a new department: "Information Disclosure Policy Division." This new department is mainly responsible for record management and information disclosure, and taking this as an opportunity, the city government has pushed ahead with the maintenance project on BRM and Standards for Record Management (hereby "BRM maintenance project") over the past two years, from 2013 to 2014. The study was thus conducted to introduce the case for the improvement of standards for record management through the BRM maintenance project by mainly exploring the case of Seoul. During the BRM maintenance project, Seoul established a unique methodology to minimize the gap between the operation of a business management system and the burden of the person in charge of the BRM maintenance project. Furthermore, after the introduction of the business management system, the city government developed its own processes and applied the maintenance result to the system in close cooperation with the related departments, despite the lack of precedence on the maintenance of the classification system. In addition, training for the BRM managers of the department has taken place twice -before and after the maintenance-for the successful performance of the BRM maintenance project and the stable operation of the project in the future. During the period of maintenance, newsletters were distributed to all employees in an effort to induce their active participation and increase the importance of records management. To keep the performance of the maintenance project and to systematically manage BRM in the future, the city government has mapped out several plans for improvement: to apply the "BRM classification system of each purpose" to the service of the "Seoul Open Data Plaza"; to reinforce the function for task management in the business management system; and to develop the function of a records management system for the unit tasks. As such, the researchers hope that this study would serve as a helpful reference so that the organizations-which had planned to introduce BRM or to perform the maintenance project on classification system-experience fewer trials and errors.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.