• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.1
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• pp.78-86
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• 2009

Recently, there seems to besome problems in the urban visual landscape as a result of continuous economic growth and industrial development. At the same time, the public has begun to be aware of the importance of visual resources, and the necessity for visual landscape conservation and improvement. Therefore, the development of evaluative indicators for systematic visual landscape planning and design is urgent. The purpose ofthis study is to discover evaluative models and indicators for the diagnosis of urban visual landscapes. This study included the selection of 18 physical indicators(statistical data) by literature reviews, adoption of field and questionnaire surveys at 12 autonomous districts in Seoul and surrounding major mountain valleys and river streams(i.e. Mt. Nam and Han-River). The content of the questionnaire is scenic beauty. Moreover, the linear regression analysis between the scenic beauty mean scores and the physical indicator scores figure out the scenic beauty prediction model. As this study suggests, the most important indicators in urban visual landscapes are 'Greens', 'Park' and 'the number of apartment buildings(higher than 20 stories).' Based on the results, greens and parks should be priority elements to considerin urban landscape planning and design. Moreover, since the number of apartment buildings that are higher than 20 stories has a negative correlation with the scenic beauty score, it can be used as basic data for landscape planning. For the scenic beauty prediction models and evaluative indicators suggest a direction of urban management, each indicator becomes basic data for visual landscape planning and design. In following studies, if physical indicators and case studies are added, the scenic beauty prediction models and evaluative indicators could be more synthetic and systematic. Moreover, the development of physical indicators in three dimensions(3D)(i.e. results from visual district analysis, view surface analysis) could be expected to obtain more general and varied results.

• Progress in Medical Physics
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• v.26 no.4
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• pp.250-257
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• 2015

Multi-leaf collimator (MLC) systems are frequently used to deliver photon-based radiation, and allow conformal shaping of treatment beams. Many proton beam centers currently make use of aperture and snout systems, which involve use of a snout to shape and focus the proton beam, a brass aperture to modify field shape, and an acrylic compensator to modulate depth. However, it needs a lot of time and cost of preparing treatment, therefore, we developed the manual MLC for solving this problem. This study was carried out with the intent of designing an MLC system as an alternative to an aperture block system. Radio-activation and dose due to primary proton beam leakage and the presence of secondary neutrons were taken into account during these iterations. Analytical calculations were used to study the effects of leaf material on activation. We have fabricated tray model for adoption with a wobbling snout ($30{\times}40cm^2$) system which used uniform scanning beam. We designed the manual MLC and tray and can reduce the cost and time for treatment. After leakage test of new tray, we upgrade the tray with brass and made the safety tool. First, we have tested the radio-activation with usually brass and new brass for new manual MLC. It shows similar behavior and decay trend. In addition, we have measured the leakage test of a gantry with new tray and MLC tray, while we exposed the high energy with full modulation process on film dosimetry. The radiation leakage is less than 1%. From these results, we have developed the design of the tray and upgrade for safety. Through the radio-activation behavior, we figure out the proton beam leakage level of safety, where there detects the secondary particle, including neutron. After developing new design of the tray, it will be able to reduce the time and cost of proton treatment. Finally, we have applied in clinic test with original brass aperture and manual MLC and calculated the gamma index, 99.74% between them.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.1-27
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• 2011

In an attempt to cope with widespread, dynamic, and accelerating changes in both internal and external business environments, companies often utilize information technologies such as SCM(Supply Chain Management). To date, SCM research has mainly focused on the effects of dynamic factors on SCM success and emphasized adoption strategies and critical success factors. Consequently, the effects of more static factors such as interdependency between SCM partners have been largely ignored. The purpose of this study, therefore, is to examine the effects of both dynamic and static factors on SCM performance by controlling for information quality and partnership quality. The five factors examined in this study include innovative ness, mutual dependency, quality of information, partnership quality, and SCM performance. All factors were examined from the perspective of part suppliers, except the mutual dependency which was examined from two aspects: supplier's dependency on customer and customer's dependency on supplier. Data was collected through five hundred survey questionnaires distributed to the part supplier companies that have implemented SCM systems for at least one year. As a result, a total of 170 valid responses were obtained. A structural equation research model was fitted using SAS 9.1.3 and SMART-PLS 2.0. The results of this study can be summarized as follows. First, innovativeness positively affected SCM information quality. SCM partnership quality, and ultimately SCM performance. The path coefficient between innovativeness and information quality was 0.387, with a t-value of 3.528. Innovativeness also had a positively direct effect on partnership quality. The path coefficient was 0.351 with a t-value of 3.366. The total effect of innovativeness on partnership quality was significant, although its indirect effect on partnership quality by altering information quality was negligible. The total indirect effect of innovativeness on SCM performance by affecting information quality and partnership quality was significant with a p-value of 0.014. Innovativeness played an important role in determining SCM performance. Second, mutual dependency showed no significant effect on SCM information quality. This result contradicts the earlier assertion that the more dependent two companies are, the more accurate and timely the information they exchange ought to be. This study showed that this may not be the case; a partner may provide information of poor quality even when it is strongly dependent on the other. Mutual dependency showed significant effect on partnership quality. However, when the mutual dependency perceived by suppliers was divided into two parts, one being a supplier's dependency on its customer company and the other being a customer's dependency on the supplier, the latter showed a significant impact on the perceived SCM partnership quality. This result indicates that a customer company can hardly improve the partnership quality perceived by suppliers by making them more dependent. It improves only when the suppliers perceive that their partners, typically having more bargaining power, are more dependent on them. The overall effect of mutual dependency of any kind on SCM performance, however, was not significant. Although mutual dependency has been mentioned as an important static factor influencing almost every aspect of cooperation on a supply chain, its influences may not be as significant as it was initially perceived to be. Third, the correlation between information quality and partnership quality was 0.448 with a p-value of less than 0.001. Information quality had a path coefficient of 0.256 to partnership quality with a t-value of 2.940. The quality of information exchanged between partners may have an impact on their partnership quality. Fourth, information quality also had a significant impact on SCM performance with a path coefficient of 0.325 with a t-value of 3.611. In this study, SCM performance was divided into four categories: product quality, cost saving, service quality, and order fulfillment. Information quality has Significant impacts on product quality, cost saving and service quality, but not on order fulfillment. Fifth, partnership quality, as expected, had a significant impact on SCM performance. The path coefficient was 0.403 with a t-value of 3.539. Partnership quality, like information quality, had positive impacts on product quality, cost saving and service quality, but showed no impact on order fulfillment. It seemed that order fulfillment is the hardest category of performance that SCM can satisfy. One major limitation of this study is that it surveyed only the suppliers. To better understand the dual aspects of SCM, it is important to survey both suppliers and the assemblers, especially in pairs. This research, to our best knowledge, was the first attempt to study the level of dependency between the two groups by measuring the dual aspects of SCM and studying mutual dependency from the categories of suppliers and assemblers each.. In the future, a more comprehensive and precise measurement of SCM characteristics needs to be achieved by examining from both the supplier's and assembler's perspectives.

• Journal of Korean Home Economics Education Association
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• v.16 no.1
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• pp.79-91
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• 2004

The purpose of this study was to examine how much secondary school home economics teachers paid attention to performance assessment, to what extent and in which way they carried it out and how much support was given to that. It's basically meant to help provide more systematic support for performance assessment. The instrument used in this study was an Interest-Based Reform Adoption Model developed by Hall. Hord and et. al. at Texas University Research & Development Center for Teacher Education. and the subjects in this study were home economics teachers from 95 secondary schools in Gyeonggi province. After a survey was conducted by mail. the responses from 157 teachers were chosen for analysis. For data handling. SPSS/WIN program was utilized, and statistical data on mean. standard deviation and percentage were obtained. In addition. t-test and ANOVA were employed. The major findings of this study were as follows: First. as for their type of interest in performance assessment. influential type(35.0%) was most common. followed by confident type (29.3%). indifferent type(20.4%) and task type(15.3%). Second, regarding their implementation. every teacher carried out performance assessment. The largest group of the teachers fulfilled it as part of routine daily schedule(60 teachers. 38.2%). which could be called the level 4. The second largest group tried to integrate performance assessment to education programs(53 teachers. 33.8%). which could be called the level 5. The third largest group implemented it without making careful preparations for that(26 teachers. 16.6%). which could be called the level 3. and the fourth largest group tried to reinvent it(11 teachers. 7.0%), which could be called the level 6. The fifth largest group was in the middle of researching it(5 teachers, 3.2%). which could be called the level 1. And the sixth largest group was in the course of making preparations for that(2 teachers. 1.3%) . which could be named the level 2. Third. concerning how much they found themselves to be supported about performance assessment. they eave three or less marks to that. which showed that they weren't supported sufficiently There was little gap among them in their concern for performance assessment and its implementation levels. and this fact suggested that there wasn't satisfactory backup for their performance assessment.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.97-117
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• 2006

The purpose of this study was to investigate the teachers' recognition on the optimization of the educational contents of Clothing & Textiles in subjects of :he Practical Arts or the Technology & Home Economics in the course of elementary, middle and high schools. The statistical data for this research were collected from 203 questionnaires of teachers who work on elementary, middle and high schools. Mean. standard deviation, percentage were calculated using SPSS/WIN 12.0 program. Also. these materials were verified by t-test, One-way ANOVA and post verification Duncan. The results were as follows; First, The equipment ratio of practice laboratory were about 24% and very poor in elementary schools but those of middle and high school were 97% and 78% each and higher than elementary schools. Second, More than 50% of teachers recognized the amount of learning 'proper'. The elementary school teachers recognized the mount of learning in 'operating sewing machines' too heavy especially, the same as middle school teachers in 'making shorts': the same as high school teachers in 'making tablecloth and curtain' and 'making pillow cover or bag'. Third, All of the elementary, middle and high school teachers recognized the levels of total contents of clothing and textiles 'common'. The 80% of elementary school teachers recognized 'operating sewing machines' and 'making cushions' difficult especially. The same as middle school teachers in 'hand knitting handbag by crochet hoop needle', 'the various kinds of cloth' and 'making short pants'. The same as high school teachers in 'making tablecloth or curtain'. Fourth, Elementary school teachers recognized 'practicing basic hand needlework' and 'making pouch using hand needlework' important in the degree of educational contents importance. Middle school teachers recognized 'making short pants unimportant. High school teachers considered the contents focusing on practice such as 'making tablecloth and curtain' and 'making pillow cover or bags' unimportant. My suggestions were as follows; Both laboratories and facilities for practice should be established for making clothing and textiles lessons effective in Practical Arts in elementary schools. The 'operating sewing machines' which were considered difficult should be dealt in upper grade, re-conditioning to easier or omitted. The practical contents should be changed to student-activity-oriented and should be recomposed in order to familiar with students' living. It was needed to various and sufficient supports for increasing the teachers' practical abilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.217-220
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• 2004

According as utilization for web increases rapidly, it is demanded that model about support interaction between web-based applications systematically and solutions can integrate new distributed platforms and existing environment effectively, accordingly, Web Services appeared by solution in reply. These days, a lot of software and hardware companies try to adoption of Web Services to their market, attenpt to construct their applications associationing components from various Web Services providers. However, to execute Web Services completely. it must have interoperability and need the standardization work that avoid thing which is subject to platform, application as well as service and programming language from other companies. WS-I (Web Services Interoperability organization) have established Basic Profile 1.0 based on XML, UDDI, WSDL and SOAP for web services interoperability and developed usage scenario Profile to apply Web Services in practice. In this paper, to verify suitability Web Services interoperability between heterogeneous two applications, have design and implements the Book Information Web Services that based on the Web Services Client of J2SE platform and the Web Services Server of .NET platform, so that analysis and verify the service by adaptation of WS-I Basic Profile.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.297-309
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• 2023

The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.