• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.67-79
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• 2020

This study analyzed the start-up education curriculum and start-up education programs of seven universities in the U.S. to find out what courses are provided, what various programs exist, and what the characteristics of start-up education in each university are. California State University, San Bernardino / University of California, Irvine / Drexel University / Oklahoma State University / Florida State University / San Diego State University / University of Southern California where entrepreneurship education based on the Entrepreneurship Degree Course is being established based on the Entrepreneurship Center of seven universities in the United States, which is not well introduced in Korea. This study examined how the start-up education courses and start-up support systems at seven universities in the U.S. are progressing at the undergraduate, MBA, master's and doctoral levels, and comparative levels. Through the case studies of the universities presented, the primary analysis was carried out to explore the various characteristics of American university start-up education. The implications of start-up education at American universities in this study are as follows. First, in order for universities to take the initiative in providing start-up education, they should be organized to suit the course of start-up education suitable for the characteristics of universities and introduce support programs. Second, it is necessary to establish an independent center within domestic universities to be operated autonomously. Third, the start-up education of universities should include building university-industry partnerships, operating entrepreneurship degree courses and collaboration between departments of universities. Fourth, the independent center should lead the active participation of alumni and local start-ups and start-up-related programs should be operated based on this. Fifth, Differentiated programs for each university's characteristics should be introduced and applied to universities. Although case studies have limitations that cannot be generalized, they can provide a useful framework. Therefore, it is necessary to design a systematic start-up education that reflects the correct design direction and characteristics of each university.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.1-10
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• 2022

Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.63-84
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• 2022

One of the ancient nomadic cultures, the Saka is generally regarded as an important intermediary in the ancient Eurasian cultural network. This study is the reinterpretation of the excavations conducted on the Katartobe tombs site of the Saka culture through a joint three-year-long project by the National Research Institute of Cultural Heritage in Korea in collaboration with the Cultural Heritage Research Institute under the National Museum of the Republic of Kazakhstan. The main discussion of the study deals with the burial rituals performed by the community who built the Katartobe tombs by the comparison and review of the various researches on the Saka tombs based on the archaeological artifacts discovered during excavation. The research has shown that the Saka tribes maintained the tradition of burying domesticated animals, such as horses, with its owner and performed burial rituals which often involved the use of fire. The archaeological remains of the Saka also show that the burial rituals like these formed the key aspect of their cultural heritage. The archaeological discoveries also show that the Saka mourners built wooden cists under a single mound when they needed to bury multiple corpses at once and sustained the practice of excarnation when burying the bodies of those who died in the different periods of time. Some burials included a tomb passage which was used not only for carrying the deceased but also for a separate burial ritual. The main discussion of this study also deals with the remnants of bones of animals buried with their deceased owners in the same kurgan, as well as the animal species and their locations in the kurgan, resulting in the discovery of diverse meanings connected with them. The pottery buried in the tombs were largely ceremonial offering vessels, just like others excavated at nearby Saka tombs and located around the buried corpse's head facing toward the west. The excavation of the tombs also shows that two vessels were arranged at the corners of the coffin where the feet are located, revealing the characteristic features of the burial practices maintained by the tribe who built the Katartobe tombs. It may be too early to come to a definite conclusion on the burial practices of the Saka due to the relative lack of research on the kurgans across Central Asia. Excavations so far show that the kurgans clustered in a single archaeological site tend to display differences as well as uniformities. In conclusion, the ancient Central Asian tombs need more detailed surveys and researches to be able to make strides in an effort to restore the cultural heritage of the ancient Central Asian tribes who played a crucial role in the Eurasian cultural landscape.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.133-150
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• 2022

Calling the 21th century the age of 'cultural competition' is not an overstatement. In an era of globalization, we try to find the 'identity of our country' in our culture. 'Culture' is the unique ethnicity of the people of each country that reflects the traces of their lives. As the world is transforming into a multi-dimensional place, traditional patterns in reference to cultural uniqueness and original formativeness are the brands that represent the people. France's luxury brand, GOYARD's Y-shaped pattern naturally made during the persistent traditional handmade process is still France's representative corporate brand and is considered prestigious even after 150 years have passed. On the other hand, in low-income countries, patterns created in the natural process of weaving fabrics are succeeded as a unique cultural aesthetic and are loved by people all over the world. Like this, people living in the global multi-dimensional world look to attain the framework 'One Planet Perspective' which is to succeed their own native culture and preserve the unique culture of others. For example, in the process of international relief organizations delivering relief supplies to Columbia's "Wayu tribe" due to the water shortage in 2013, a handmade product, "Mochila Bag" was discovered. Triggered by this incident, Europe and Korea decide to import it to support the livelihood of the "Wayu tribe." Also, the aesthetic and cultural values of the traditional culture in minority tribes that have evolved through thousands of years have been listed on UNESCO and preserved worldwide. Likewise, culture doesn't suddenly appear overnight, but rather the brand representing the company is the pattern used in the trend of the era kept for over 100 years. Moreover, patterns that reflect the country's identity are inherited as the unique aesthetic of the culture. Our country does inherit the unique aesthetic of our culture, but doesn't have a 'strong image' that displays the practical value reinterpreted creatively and aesthetically to fit the modern trend. Traditional patterns are important in perspective of study and theoretical research, but the brand's image using those patterns is a new medium from the past existence continuing to the current tradition. Furthermore, this study suggests that the image of a company that uses traditional patterns will have high economical potential as a national brand.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.249-267
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• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.1
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• pp.89-104
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• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• 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.