• Clean Technology
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• v.29 no.4
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• pp.255-261
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• 2023

Power semiconductors are semiconductors used for power conversion, transformation, distribution, and control. Recently, the global demand for high-voltage power semiconductors is increasing across various industrial fields, and optimization research on high-voltage IGBT components is urgently needed in these industries. For high-voltage IGBT development, setting the resistance value of the wafer and optimizing key unit processes are major variables in the electrical characteristics of the finished chip. Furthermore, the securing process and optimization of the technology to support high breakdown voltage is also important. Etching is a process of transferring the pattern of the mask circuit in the photolithography process to the wafer and removing unnecessary parts at the bottom of the photoresist film. Ion implantation is a process of injecting impurities along with thermal diffusion technology into the wafer substrate during the semiconductor manufacturing process. This process helps achieve a certain conductivity. In this study, dry etching and wet etching were controlled during field ring etching, which is an important process for forming a ring structure that supports the 3.3 kV breakdown voltage of IGBT, in order to analyze four conditions and form a stable body junction depth to secure the breakdown voltage. The field ring ion implantation process was optimized based on the TEG design by dividing it into four conditions. The wet etching 1-step method was advantageous in terms of process and work efficiency, and the ring pattern ion implantation conditions showed a doping concentration of 9.0E13 and an energy of 120 keV. The p-ion implantation conditions were optimized at a doping concentration of 6.5E13 and an energy of 80 keV, and the p+ ion implantation conditions were optimized at a doping concentration of 3.0E15 and an energy of 160 keV.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.17-32
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• 2023

The entrepreneurial activities of college students play a significant role in modern economic and social development, particularly as a solution to the changing economic landscape and youth unemployment issues. Introducing innovative ideas and technologies into the market through entrepreneurship can contribute to sustainable economic growth and social value. Additionally, the entrepreneurial intentions of college students are shaped by various factors, making it crucial to deeply understand and appropriately support these elements. To this end, this study systematically explores the importance and impact of role models through a multiple serial mediation analysis. Through a survey of 300 college students, the study analyzed how two psychological variables, growth mindset and entrepreneurial self-efficacy, mediate the influence of role models on entrepreneurial intentions. The presence and success stories of role models were found to enhance the growth mindset of college students, which in turn boosts their entrepreneurial self-efficacy and ultimately strengthens their entrepreneurial intentions. The analysis revealed that exposure to role models significantly influences the formation of a growth mindset among college students. This mindset fosters a positive attitude towards viewing challenges and failures in entrepreneurship as learning opportunities. Such a mindset further enhances entrepreneurial self-efficacy, thereby strengthening the intention to engage in entrepreneurial activities. This research offers insights by integrating various theories, such as mindset theory and social learning theory, to deeply understand the complex process of forming entrepreneurial intentions. Practically, this study provides important guidelines for the design and implementation of college entrepreneurship education. Utilizing role models can significantly enhance students' entrepreneurial intentions, and educational programs can strengthen students' growth mindset and entrepreneurial self-efficacy by sharing entrepreneurial experiences and knowledge through role models. In conclusion, this study provides a systematic and empirical analysis of the various factors and their complex interactions that impact the entrepreneurial intentions of college students. It confirms that psychological factors like growth mindset and entrepreneurial self-efficacy play a significant role in shaping entrepreneurial intentions, beyond mere information or technical education. This research emphasizes that these psychological factors should be comprehensively considered when developing and implementing policies and programs related to college entrepreneurship education.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.59-70
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• 2024

As urbanization progresses, the demand for parks and green space is increasing. Park green spaces in the city are important spaces in the city because they are recognized as spaces where people can freely engage in outdoor activities. The park service area is a measure that shows the extent to which services are provided based on distance. In this process, the concept of accessibility plays an important role, and walking, in particular, as the most basic means of transportation for people and has a great influence on the use of parks. However, the current park service area analysis focuses on discovering underprivileged areas, so detailed evaluation of beneficiary areas is insufficient. This study seeks to evaluate park service areas based on the pedestrian accessibility and the pedestrian network. Park services are services that occur when users directly visit the park, and accessibility is expected to be reflected in terms of usability. To quantify the pedestrian network, this study used space syntax to analyze pedestrian accessibility based on integration values. The integration values are an indicators that quantify the level of accessibility of the pedestrian network, and in this study, the higher the integration value, the higher the possibility of park use. The results of the study are as follows. First, Bundang-gu's park service area accounts for 43%, and includes most sections with high pedestrian accessibility, but some sections with good pedestrian accessibility are excluded. This can be seen as a phenomenon that occurs when residential areas and commercial and business areas are given priority during the urban planning process, and then park and green areas are selected. Second, based on Bundang-gu, the park service area and pedestrian accessibility within the park service area were classified by neighborhood unit. Differences appear for each individual neighborhood unit, and it is expected that the availability of the park will vary accordingly. In addition, even in areas created during the same urban planning process, there were differences in the evaluation of park service areas according to pedestrian accessibility. Using this, it is possible to evaluate individual neighborhood units that can be reflected in living area plans, and it can be used as a useful indicator in park and green space policies that reflect this in the future.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.674-684
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• 2023

The purpose of this study was to investigate the effect of acute listening to music on the cardiovascular reactivity to sympathoexcitation. In this crossover design study, 15 healthy adults(23.1±1.94(yrs) were randomized to either (1)acute listen to the subject's preferred music for 30 minutes and (2)sat as a time control by an experiment coordinator. After completing each trial, the cold pressor test(CPT) was conducted. Heart rate(HR) and blood pressure(BP) were measured for 4 times at baseline, during and after the CPT. Heart rate variability(HRV) were measured for 3 times at baseline, prior and after the CPT. HR and BP increased during the CPT in both trial and returned to baseline after CPT(time effect, p < .001). After CPT, brachial systolic BP reactivity to the CPT was attenuated in listening to music trial compared to control trial(p = . 008). As a result of heart rate variability(HRV), the difference values between the baseline and prior to the CPT showed a significant increase in standard deviation of the NN intervals(SDNN), total power(TP) and high frequency(HF) only in the music trial (p = .001, p = .002, p = .011). The difference value between prior to and after the CPT did not show significance. But compared with the control trial, the music trial was confirmed that SDNN, TP and HF were more activated. Therefore, listening to music alleviated anxiety and tension before the CPT, and it is estimated that it had a favorable effect on stability after the CPT. This findings showed that listening to music may have a positive effect on brachial systolic BP and HRV to sympathoexcitation.

• Journal of The Korean Society of Grassland and Forage Science
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• v.44 no.2
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• pp.64-70
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• 2024

The experiment was conducted to determine the changes in seed productivity of Italian ryegrass (Lolium multiflorum Lam.) according to nitrogen fertilization levels in the southern region of Korea. Italian ryegrass (IRG) variety 'Green Call' was sown in the fall of 2021 in Jinju, Gyeongsangnam-do. The experiment consisted of three nitrogen fertilizer levels (100, 120, and 140 N kg/ha) with three replications using a randomized complete block design. Harvesting was done approximately 30 days after heading on May 18th. There was no difference in heading date among treatments, which occurred on April 18th. The longest IRG was observed in the 140 N kg/ha treatment, but there was no significant difference. No significant differences were observed in lodging, disease resistance, and cold tolerance among treatments, but lodging was severe in all treatments. The length of the spike averaged 44.95 cm, with no difference among treatments, and the number of seeds per spike was highest in the 120 N kg/ha treatment. Seed yield increased with increasing nitrogen fertilizer levels, averaging 3,707 kg/ha (as-fed basis). DM content of seed and straw averaged 76.95% and 62.19%, respectively, with no significant differences among treatments. The remaining straw after harvesting averaged 6,525 kg/ha on a dry matter basis, with the highest value observed in the 140 N kg/ha treatment. Overall, considering the results, the optimal nitrogen fertilizer application rate for seed production of Italian ryegrass in the southern region when sown in autumn was found to be 120 N kg/ha.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.17-27
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• 2009

Price promotion typically reduces the price for a given quantity or increases the quantity available at the same price, thereby enhancing value and creating an economic incentive to purchase. It often is used to encourage product or service trial among nonusers of products or services. Thus, it is important to understand the effects of price promotions on quality perception made by consumer who do not have prior experience with the promoted brand. However, if consumers associate a price promotion itself with inferior brand quality, the promotion may not achieve the sales increase the economic incentives otherwise might have produced. More specifically, low qualitative perception through price promotion will undercut the economic and psychological incentives and reduce the likelihood of purchase. Thus, it is important for marketers to understand how price promotional informations about a brand have impact on consumer's unfavorable quality perception of the brand. Previous literatures on the effects of price promotions on quality perception reveal inconsistent explanations. Some focused on the unfavorable effect of price promotion on consumer's perception. But others showed that price promotions didn't raise unfavorable perception on the brand. Prior researches found these inconsistent results related to the timing of the price promotion's exposure and quality evaluation relative to trial. And, whether the consumer has been experienced with the product promotions in the past or not may moderate the effects. A few studies considered differences among product categories as fundamental factors. The purpose of this research is to investigate the effect of price promotional informations on consumer's unfavorable quality perception under the different conditions. The author controlled the timing of the promotional exposure and varied past promotional patterns and information presenting patterns. Unlike previous researches, the author examined the effects of price promotions setting limit to pretrial situation by controlling potentially moderating effects of prior personal experience with the brand. This manipulations enable to resolve possible controversies in relation to this issue. And this manipulation is meaningful for the work sector. Price promotion is not only used to target existing consumers but also to encourage product or service trial among nonusers of products or services. Thus, it is important for marketers to understand how price promotional informations about a brand have impact on consumer's unfavorable quality perception of the brand. If consumers associate a price promotion itself with inferior quality about unused brand, the promotion may not achieve the sales increase the economic incentives otherwise might have produced. In addition, if the price promotion ends, the consumer that have purchased that certain brand will likely to display sharply decreased repurchasing behavior. Through a literature review, hypothesis 1 was set as follows to investigate the adjustive effect of past price promotion on quality perception made by consumers; The influence that price promotion of unused brand have on quality perception made by consumers will be adjusted by past price promotion activity of the brand. In other words, a price promotion of an unused brand that have not done a price promotion in the past will have a unfavorable effect on quality perception made by consumer. Hypothesis 2-1 was set as follows : When an unused brand undertakes price promotion for the first time, the information presenting pattern of price promotion will have an effect on the consumer's attribution for the cause of the price promotion. Hypothesis 2-2 was set as follows : The more consumer dispositionally attribute the cause of price promotion, the more unfavorable the quality perception made by consumer will be. Through test 1, the subjects were given a brief explanation of the product and the brand before they were provided with a $2{\times}2$ factorial design that has 4 patterns of price promotion (presence or absence of past price promotion * presence or absence of current price promotion) and the explanation describing the price promotion pattern of each cell. Then the perceived quality of imaginary brand WAVEX was evaluated in the scale of 7. The reason tennis racket was chosen is because the selected product group must have had almost no past price promotions to eliminate the influence of average frequency of promotion on the value of price promotional information as Raghubir and Corfman (1999) pointed out. Test 2 was also carried out on students of the same management faculty of test 1 with tennis racket as the product group. As with test 1, subjects with average familiarity for the product group and low familiarity for the brand was selected. Each subjects were assigned to one of the two cells representing two different information presenting patterns of price promotion of WAVEX (case where the reason behind price promotion was provided/case where the reason behind price promotion was not provided). Subjects looked at each promotional information before evaluating the perceived quality of the brand WAVEX in the scale of 7. The effect of price promotion for unfamiliar pretrial brand on consumer's perceived quality was proved to be moderated with the presence or absence of past price promotion. The consistency with past promotional behavior is important variable that makes unfavorable effect on brand evaluations get worse. If the price promotion for the brand has never been carried out before, price promotion activity may have more unfavorable effects on consumer's quality perception. Second, when the price promotion of unfamiliar pretrial brand was executed for the first time, presenting method of informations has impact on consumer's attribution for the cause of firm's promotion. And the unfavorable effect of quality perception is higher when the consumer does dispositional attribution comparing with situational attribution. Unlike the previous studies where the main focus was the absence or presence of favorable or unfavorable motivation from situational/dispositional attribution, the focus of this study was exaus ing the fact that a situational attribution can be inferred even if the consumer employs a dispositional attribution on the price promotional behavior, if the company provides a persuasive reason. Such approach, in academic perspectih sis a large significance in that it explained the anchoring and adjng ch approcedures by applying it to a non-mathematical problem unlike the previous studies where it wis ionaly explained by applying it to a mathematical problem. In other wordn, there is a highrspedency tmatispositionally attribute other's behaviors according to the fuedach aal attribution errors and when this is applied to the situation of price promotions, we can infer that consumers are likely tmatispositionally attribute the company's price promotion behaviors. Ha ever, even ueder these circumstances, the company can adjng the consumer's anchoring tmareduce the po wibiliute thdispositional attribution. Furthermore, unlike majority of previous researches on short/long-term effects of price promotion that only considered the effect of price promotions on consumer's purchasing behaviors, this research measured the effect on perceived quality, one of man elements that affects the purchasing behavior of consumers. These results carry useful implications for the work sector. A guideline of effectively providing promotional informations for a new brand can be suggested through the outcomes of this research. If the brand is to avoid false implications such as inferior quality while implementing a price promotion strategy, it must provide a clear and acceptable reasons behind the promotion. Especially it is more important for the company with no past price promotion to provide a clear reason. An inconsistent behavior can be the cause of consumer's distrust and anxiety. This is also one of the most important factor of risk of endless price wars. Price promotions without prior notice can buy doubt from consumers not market share.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of Science of Art and Design
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• v.11
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• pp.221-249
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• 2007

Today, photography is facing to the crisis of identity and dilemma of ontology from the digital imaging process in the new technology form. It is very important points to say rethinking of the traditional photographic medium, that has changed the way we view the world and ourselves is perhaps an understatement and that photography has transformed our essential understanding of reality. Now, no longer are photographic images regarded as the true automatic recording, innocent evidence and the mirror to the reality. Rather, photography constructs the world for our entertainment, helping to create the comforting illusions by which we live. The recognition that photographs are not constructions and reflections of reality, is the basis for the actual presence within the contemporary photographic world. It is shock. This thesis's aim is to look for the problems of photographic identity and ontological crisis that is controlling and regulating digital photographic imagery, allowing the reproduction of the electronic simulations era. Photography loses its special aesthetic status and becomes no more true information and, exclusively evidence by traditional film and paper that appeared both as a technological accuracy and as a medium-specific aesthetic. The result, photography is facing two crises, one is the photographic ontology(the introduction of computerized digital images) and the other is photographic epistemology(having to do broader changes in ethics, knowledge and culture). Taken together, these crises apparently threaten us with the death of photography, with the 'end' of photography and the culture it sustains. The thesis's meaning is to look into the dilemma of photography's ontology and epistemology, especially, automatical index and digital codes from its origin, meaning, and identity as the technological medium. Thus, in particular, thesis focuses on the analog imagery presence, from the nature in the material world, and the digital imagery presence from the cultural situations in our society. And also thesis's aim is to examine the main issues of the history of photography has been concentrated on the ontological arguments since the discovery of photography in 1839. Photography has never been only one static technology form. Rather, its nearly two centuries of technological development have been marked by numerous, competing of technological innovation and self revolution from the dual aspects. This thesis examines recent account of photography by the analysis of the medium's concept, meaning, identity between film base image and digital base image from the aspects of photographic ontology and epistemology. Thus, the structure of thesis is fairy straightforward to examine what appear to be two opposing view of photographic conditions and ontological situations. Thesis' view contrasts that figure out the value of photography according to its fundamental characteristic as a medium. Also, it seeks a possible solution to the dilemma of photographic ontology through the medium's origin from the early years of the nineteenth century to the raising questions about the different meaning(analog/digital) of photography, now. Finally, this thesis emphasizes and concludes that the photographic ontological crisis reflects to the paradoxical dynamic structure, that unsolved the origins of the medium, itself. Moreover, even photography is not single identity of the photographic ontology, and also can not be understood as having a static identity or singular status from the dynamic field of technologies, practices, and images.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.1
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• pp.107-119
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• 2014

The purpose of this study is to examine the current status of vascular plants and naturalized plants growing in the Seongeup Folk Village in Jeju and to consider and compare their distribution patterns and the characteristics of emergence of naturalized plants in other folk villages and all parts of Jeju, thereby exploring measures to well manage naturalized plants. The result of this study is as follows.11) The total number of vascular plants growing in Seongeup Folk Village is identified to be 354 taxa which include 93 families, 260 genus, 298 species, 44 varieties and 12 breeds. Among them, the number of naturalized plants is 55 taxa in total including 22 families, 46 genus, 53 species, and 2 varieties, which accounts for 21.7% of the total of 254 taxa identified all over the region of Jeju. The rate of naturalization in Seongeup Folk Village is 15.5%, which is far higher than the rates of plant naturalization in Hahoi Village in Andong, Yangdong Village in Gyeongju, Hangae Village in Seongju, Wanggok Village in Goseong, and Oeam Village in Asan. Among the naturalized plants identified within the targeted villages, the number of those growing in Jeju is 9 taxa including Silene gallica, Modiola caroliniana, Oenothera laciniata, Oenothera stricta, Apium leptophyllum, Gnaphalium purpureum, Gnaphalium calviceps, Paspalum dilatatum and Sisyrinchium angustifolium. It is suggested that appropriate management measures that consider the characteristics of the gateway to import and the birthplace of the naturalized plants are necessary. In the meantime, 3 more taxa that have not been included in the reference list of Jeju have been identified for the first time in Seongeup Folk Village, which include Bromus sterilis, Cannabis sativa and Veronica hederaefolia. The number of naturalized plants identified within the gardens of unit-based cultural properties is 20 taxa, among which the rate of prevalence of Cerastium glomeratum is the highest at 62.5%. On the other hand, the communities of plants that require landscape management are Brassica napus and other naturalized plants, including Cosmos bipinnatus, Trifolium repens, Medicago lupulina, Oenothera stricta, O. laciniata, Lotus corniculatus, Lolium perenne, Silene gallica, Hypochaeris radicata, Plantago virginica, Bromus catharticus and Cerastium glomeratum. As a short-term measure to manage naturalized plants growing in Seongeup Folk Village, it is important to identify the current status of Cosmos bipinnatus and Brassica napus that have been planted for landscape agriculture, and explore how to use flowers during the blooming season. It is suggested that Ambrosia artemisiifolia and Hypochaeris radicata, designated as invasive alien plants by the Ministry of Health and Welfare, should be eradicated initially, followed by regular monitoring in case of further invasion, spread or expansion. As for Hypochaeris radicata, in particular, some physical prevention measures need to be explored, such as for example, identifying the habitat density and eradication of the plant. In addition, it is urgent to remove plants, such as Sonchus oleraceus, Houttuynia cordata, Crassocephalum crepidioides, Erigeron annuus and Lamium purpureum with high index of greenness visually, growing wild at around high Jeongyi town walls. At the same time, as the distribution and dominance value of the naturalized plants growing in deserted or empty houses are high, it is necessary to find measures to preserve and manage them and to use the houses as lodging places.