• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.1
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• pp.105-117
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• 2018

In this study, we identify the obstacles that occur through the relationship between I-U cooperation and look for factors that can overcome them in the 'university administration's efforts' and 'Trust between I-U'. In the study of existing I-U cooperation, the relationship between industry and university has accumulated experiences and various channels of bilateral cooperation by sustaining interactions and absorbing capacity of knowledge by path dependence. However, as cooperation increases, 'I-U cooperation barrier' are inevitable, which is explained by two perspectives: 'Difference in mutual recognition' and 'Institutional barriers'. In order to induce the achievement of effective I-U cooperation, it is necessary to overcome these obstacles stemming from mutual relations, and it will be possible to maintain the relationship of continuous I-U cooperation. The researchers conducted research on companies participating in the I-U cooperation technology development project of the 'Ministry of Small and Medium Venture Business', which is a representative I-U cooperation program in Korea. This project will be promoted in the 'Small & Medium Business I-U cooperation Center', an administration-dedicated organization of the university. The researchers measure 'University administration's efforts' and 'Trust between I-U'to overcome'I-U cooperation barrier' In order to clarify the data of the research sample, a questionnaire survey of organizational units was conducted for all companies participating in the 'I-U cooperation technology development projects' of the SMEs and Startups between 2011 and 2015, and the responses of 356 organizations were drawn. The results showed that the higher the level of 'University administration's efforts' and Trust between I-U', the lower 'Difference in mutual recognition' and 'Institutional barriers'. Particularly, it showed higher explanatory power to overcome 'Institutional barriers' among obstacles. Therefore, it should be accompanied by the interest, implementation and institutional support of I-U-R subjects to raise the level of these two factors that can overcome 'I-U cooperation barrier'.

• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.545-553
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• 2019

This study was conducted to determine whether the water in which nitrate accumulated during long-term fish culture in an aquaponics system without water exchange could be removed and reused as catfish-culturing water. The catfish (Silurus asotus) were cultured in the urban aquaculture system using BFT (Biofloc Technology) aquaculture and an aquaponics system (two rearing tanks, 3 tons each) without exchanging the rearing water. After 151 days (from March to August) of rearing, 2.8 g of fry had grown to an average weight of 171.3 g (total weight, 56.53 kg) and 235.5 g (total weight 71.1 kg), respectively. The overall survival rate was 65% in the urban aquaculture system. However, the survival rate was 77.7% before separation into the two tanks. The survival rates after the separation were 92.9% and 78.0%. In the early biofloc watermaking process, there was a high mortality rate. After water stabilization, the mortality rate decreased and some mortality occurred during the period when the total amount of suspended solids (TSS) increased. The results of monthly blood analysis of the catfish showed that the AST concentration was significantly higher in April. Blood ALT levels and triglycerides showed no difference in the rearing period and the glucose, cholesterol, and total protein levels were significantly higher in July. There was no difference in the other periods. The plants produced by the aquaponics system using catfish-rearing water were lettuce, basil, chard, and red chicory. These showed smooth growth and a total of 148.85 kg of plants were harvested in five months. It was possible to remove nitric acid from the aquaponics system and reuse it as catfish-rearing water. Maintaining proper plant quantity according to the capacity of the catfish showed that the combination of agricultural and aquatic products was possible.

• Korean Journal of Weed Science
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• v.30 no.2
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• pp.122-134
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• 2010

We investigated the levels of resistance and accumulation of terapyrroles, reactive oxygen species, lipid peroxidation, and antioxidative enzymes for reasons of growth reduction in herbicide-transgenic rice overexpressing Myxococcus xanthus, Arabidopsis thaliana, and human protoporphyrinogen oxidase (Protox) genes. The transgenic rice overexpressing M. xanthus (MX, MX1, PX), A. thaliana (AP31, AP36, AP37), and human (H45, H48, H49) Protox genes showed 43~65, 41~72 and 17~70-fold more resistance to oxyfluorfen, respectively, than the wild type. Among transgenic rice lines overexpressing Protox genes, several lines showed normal growth compared with the wild type, but several lines showed in reduction of plant height and shoot fresh weight under different light conditions. However, reduction of plant height of AP37 was much higher than other lines for the experimental period. On the other hand, the reduction of plant height and shoot fresh weight in the transgenic rice was higher in high light condition than in low light condition. Enhanced levels of Proto IX were observed in transgenic lines AP31, AP37, and H48 at 7 days after seeding (DAS) and transgenic lines PX, AP37, and H48 at 14 DAS relative to wild type. There were no differences in Mg-Proto IX of transgenic lines except for H41 and H48 and Mg-Proto IX monomethyl ester of transgenic lines except for MX, MX1, and PX. Although accumulation of tetrapyrrole intermediates was observed in transgenic lines, their tetrapyrrole accumulation levels were not enough to inhibit growth of transgenic rice. There were no differences in reactive oxygen species, MDA, ALA synthesizing capacity, and chlorophyll between transgenic lines and wild type indicating that accumulated tetrapyrrole intermediate were apparently not high enough to inhibit growth of transgenic rice. Therefore, the growth reduction in certain transgenic lines may not be caused by a single factor such as Proto IX, but by interaction of many other factors.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.149-157
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• 2013

The weirs built so far are mainly overflow type weirs overflowing to the upstream. Main advantages of overflow type weirs are, effective water resources management and easy design, construction and maintenance due to many accumulated studies. However, due to the special feature of the overflow type weir where water overflows through the upstream of the weir, the silt coming from the upstream is not discharged to the downstream of the weir. This increases the river bed and reduces the reservoir capacity, and as a result, the weir loses its function. A underflow type weir with a water gate has been implemented in order to solve such sediment deposit and weir maintenance problems. However due to the design problem of recently constructed underflow type weirs, the river bed of the downstream of a weir has been scoured. And this leds to a structural problem. In this study, the flow characteristics of overflow type weirs and underflow type weir, hydraulic jump length analysis depending on change of water depth and the amount of specific energy loss generated per unit length depending on a weir type have been compared and analyzed, for the effective design and management of the weirs. The experiment results show that, when identical upstream conditions of underflow type weir and an overflow type weir were maintained, the hydraulic jump length was up to twice longer with Fr(Froude number) 3.5 of the hydraulic jump length at the underflow type weir, and the hydraulic jump length gradually decreased as the downstream water depth increased. The comparative analysis result of the amount of specific energy loss generated per unit length showed that the amount of energy loss per unit length was twice higher for an overlfow type weir than a underflow type weir. Therefore, in case of a underflow type facility, an additional energy reduction facility is determined to be necessary for safety of water construction structures.

• Korean Journal of Food Science and Technology
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• v.7 no.3
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• pp.128-134
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• 1975

For development of long-term storage method of sweet-persimmons using polyethylene film bags, basic experiment was conducted with 30 boxes of sweet-persimmons in 1973 and the same experiment was extended for industrial application with 2,500 boxes of the persimmons in the cold storage of Jinyoung Sweet-persimmon Association in 1974. Investigation was made on change of the quality by storage period. At the same time, persimmons put in the cold storage test were shipped to market at different time in order to monitor consumer response and commercial feasibility. The followings are conclusion obtained from the result of this experiment. 1. Storage of sweet-persimmon, Buyu, produced in Jinyoung, Kimhae was possible for 1 month at $2^{\circ}C{\pm}1^{\circ}C$ cold storage. This storage period was extended to 4 months until the end of February in case that the fruits were hermetically sealed in P.E. film bags of 0.08 to 0.1 mm thickness. 2. During the storage period of sweet-persimmons packed in the film bags, the loss of weight due to evaporation was effectively prevented with use of the film of bag thicker than 0.04 mm. 3. The storage ability of 3-5 persimmons per small bag was somewhat superior to that of many persimmons packed in the large box of 15kg capacity. 4. The thicker the film of bags, the more $CO_2$ gas was accumulated inside, however, from 1 month after beginning of the storage the rate of $CO_2$ accumulation became very low maintaining the stabilized level of 5-6% at the plot of 0.06-0.08mm thick bags. 5. While the persimmons were in storage, decreased was the content of total sugars, total acids, and vitamin C, of which the phenomenon was remarkable especially with the fruits of non-packed plot. 6. The sweet-persimmons in the film bags subjected to cold storage when shipped to market in their intact condition were more beneficial than when they were shipped out in unpacked condition. The intact fruits packed in the P.E. film bags were able to keep their commercial value for 10days in the outdoor situation. 7. The sweet-persimmons that were packed in the film bags and put in the cold storage had maintained promissing marketability and the economic feasibility was acknowledged when the experimental practice was applied to industrial scale.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.290-298
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• 2021

This study was conducted to evaluate the possibility of applying phytoremediation technology by investigating soil and native plants in waste coal landfills exposed to heavy metal contamination for a long period of time. The ability of native plants to accumulate heavy metals using greenhouse cultivation experiments was alse evaluated. Plants were investigated at an abandoned coal mine in Hwajeolyeong, Jeongseon, Gangwon-do. Two species of native plants (Carex breviculmis. R. B. and Salix koriyanagi Kimura ex Goerz.) located in the study area and three Korean native plants (Artemisia japonica Thunb. Hemerocallis hakuunensis Nakai., and Saussurea pulchella (Fisch.) Fisch.) were cultivated in a greenhouse for 12 weeks in artificially contaminated soil. Soils contaminated with arsenic and lead were generated with arsenic concentration gradients of 25, 62.5, 125, and 250 mg kg^-1 and lead concentration gradients of 200, 500, 1000, and 2000 mg kg^-1, respectively. Results showed that none of the five plants could survive at high arsenic concentration treatment (125 and 250 mg kg^-1) and some plants died in 2000 mg kg^-1 lead concentration treatment soil. The plant translocation factor (TF) was highest in H. hakuunensis in arsenic treatments, and A. japonica in lead treatments, respectively. The bioaccumulation factor (BF) of plants was more than 1 in all species in arsenic treatment, whereas it was highest in H. hakuunensis. BF for all species was less than 1 in lead treatment. Particularly, in 2000 mg kg^-1 concentration lead treatment, A. japonica accumulated more than 1000 mg kg^-1 lead and was expected to be a lead hyperaccumulator. In conclusion, A. japonica and H. hakuunensis were excellent in the accumulation of arsenic heavy metals, and S. koriyanagi was excellent in lead accumulation ability. Therefore, the above mentioned three plants are considered to be strong contenders for application of the phytoremediation technology.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.