• Journal of Chest Surgery
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• v.36 no.9
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• pp.638-645
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• 2003

The purposes of this study were to evaluate the effect of myocardial protection with our cold blood cardioplegic solution and to observe the relationship between ultrastructural study and other evaluation methods and its effectiveness. Material and Method: We evaluated the changes of myocardial ultrastructure using semi-quantitative scoring system, CK-MB fraction, SGOT and LDH1/LDH2, and EKG in 18 patients undergoing valvular heart surgery and coronary artery bypass grafting (CABG). Right atrial auricular biopsies were taken before the cardiopulmonary bypass (CPB) and shortly after the end of CPB. Myocardium-related serum enzymes ＆ EKG were checked for 3 days of postoperative period and their postoperative peak enzyme value and observed new Q wave ＆ ST segment elevation in EKG were choosen. Result: There were 8 males and 10 females, and their mean age was 55.6$\pm$13. Eight patients underwent valvular heart surgery and ten coronary artery bypass grafting, The mean CPB time was 119$\pm$29 minutes and the mean aortic cross-clamp (ACC) time was 75.4$\pm$24 minutes. Before the start of CPB, the mean mitochondrial score was 4.28$\pm$0.53 and after the end of CPB, it significantly increased to 2.35$\pm$0.79. There was no evidence of perioperative myocardial infarction in terms of myocardiumrelated serum enzyme value and Q wave and ST change in EKG. There was no significant relationship between pre-CPB and post-CPB mitochondrial score and the mean time of CPB and ACC, and the mean value of postoperative peak CK-MB, SGOT and LDH1/LDH2, but there was relatively positive correlation of CPB time with peak LDH1/LDH2. Conclusion: Despite the apparent satisfactory results in myocardium-related serum enzymes ＆ EKG, with this study using the cold blood cardioplegic solution, there were many changes in myocardial ultrastructures, and more studies are needed to obtain further information.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Nuclear Engineering and Technology
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• v.18 no.3
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• pp.200-208
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• 1986

The loss of coolant accident based on a double-ended cold leg break is analyzed with the discharge coefficient (Ca) of 0.4. This analysis covers the whole transient period from the start of depressurization to the complete refilling of the core by using RELAP4/MOD6-EM and RELAP4/ MOD6-HOT CHANNEL for the system thermal-hydraulics and the fuel performance during the blowdown phase respectively, and RELAP4/MOD6-FLOOD and TOODEE2 during the reflood phase. A simple analytical method has been developed to account for the lower plenum filling by approximating steam-water countercurrent flows and superheated wall effects at the downcomer during the refill period. Based on the informations. at the time of EOB (end-of-bypass), the refill duration time and the initial reflooding temperature were estimated and compared with the results from the RELAP4/MOD6, resulting in a good agreement. In addition, some parametric studies on the EOB were performed. The form loss coefficient between upper head and upper downcomer was found to be sensitive to the occurrence of the spurious EOB. Appropriate form loss coefficients should be taken into account to avoid the flow oscillations at the downcomer. The analyses with the six and three volume core nodalizations, respectively, show much similar trends in the system thermal-hydraulic performance, but the former case is recommended to obtain good results.

• Horticultural Science & Technology
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• v.33 no.2
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• pp.233-241
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• 2015

Kimchi cabbage 'Choon Gwang' cultivar that was grown in highlands in Gangneung was subjected to predrying, room cooling, and forced air cooling, and then packed with/without 0.02 mm HDPE film to investigate the effect of postharvest treatment on quality characteristics during 8 weeks storage at $2^{\circ}C$ (RH $90{\pm}5%$). Weight loss in forced air cooling and room cooling was lower than 3-4% with 0.02 mm HDPE film liner treatment during storage. However, it was only below 10% in room cooling without liner treatment and forced air cooling without liner treatment led to the highest weight loss, above 15%. Conversely, the control had lower weight loss than the others. SSC was $2-4^{\circ}brix$ for all treatments and there was no difference between postharvest treatments and liner treatments. Color index and firmness both showed no differences with/without 0.02 mm HDPE film and postharvest treatments. In sensory evaluation, forced air cooling with liner treatment was effective, with the highest score, especially in appearance and crispness. After 6 weeks, control kimchi cabbage without liner treatment was damaged seriously in appearance and the internal color had changed to brown. Room cooling and predrying with liner treatment changed the start of internal browning to after 8 weeks storage.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.119-140
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• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.123-140
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• 2009

Collaborative filtering recommends products using customers' preferences, so it cannot recommend products to the new customer who has no preference information. This paper proposes a novel approach to new customer recommendations using the social network analysis which is used to search relationships among social entities such as genetics network, traffic network, organization network, etc. The proposed recommendation method identifies customers most likely to be neighbors to the new customer using the centrality theory in social network analysis and recommends products those customers have liked in the past. The procedure of our method is divided into four phases : purchase similarity analysis, social network construction, centrality-based neighborhood formation, and recommendation generation. To evaluate the effectiveness of our approach, we have conducted several experiments using a data set from a department store in Korea. Our method was compared with the best-seller-based method that uses the best-seller list to generate recommendations for the new customer. The experimental results show that our approach significantly outperforms the best-seller-based method as measured by F1-measure.

• The Journal of Art Theory & Practice
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• no.4
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• pp.203-239
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• 2006

As it is known, during the Second World War Greece has fought on the side of the allies and the end of the war found the country on the winners' side. However, the struggle for authority right after 1945 was merciless and extremely difficult, as well as dangerous for the course of the country to the future. The political powers were divided between the legal authorities that were represented by the king and formed the exiled government on the one hand and the part of the resistance teams and the rebels of the left that had a soviet friendly direction on the other. Thus, the start of a civil war was just a matter of time. It fin ally started in 1947 and lasted for more than two years. The consequences were disastrous for the country's economy and decisive for the future course of Greece. The national army prevailed with the help of, mostly, the English. Royal parliamentary democracy was established with a clear political turn to the west, as a completion and adaptation of the Agreement of the Great Powers at Yalta. Art had a 'similar' route. Dipolar, contradictory: conservative choices on the one side, and a will for pioneering inspiration and perspective on the other side. The 'dominate' trend was first evident in sculpture and mainly in the public monuments. Their construction aimed mostly at the public propaganda and at the promotion of the sovereign ideology. On the one side we have the public sculptures composed of faces of contemporary heroes or leading figures of the civic war and the national resistance. On the other side we have monumental statues mainly that appeal to a 'public' outside of the country's borders and mostly of the north borders, where there are countries with a communistic regime, like Bulgaria, Serbia and Albania. Their subject is derived from the heroic events of the Balkan Wars (1912-1913) and ancient historical figures like Alexander the Great as the Greek army leader, his father, Philippos II and Aristotle, who was of a north-Greek origin. The political message is twofold: on the one side the 'inner enemy' the communists that were defeated and the promotion of the new liberal social system and on the other side the north neighbours, which not only represent the East Block, but they also conspire the history and the culture of the Greeks. This is the way how the 'Cold War' was resulted in a full and totalitarian expression in art.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.3
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• pp.140-147
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• 2005

We investigated the interactions between coastal waters of the Yeongil Bay, Korea, and oceanic waters of the Eastern Sea, as wet 1 as the development mechanism of vertical circulation currents in the bay. The oceanic waters of the bay have an average water temperature of $12.2{\sim}18.4^{\circ}C$ and salinity of $33.32{\sim}34.43$ PSU. Results of spectral analysis have shown that the period of revolution between oceanic and coastal waters is about 0.84-0.91 years in the surface waters and 1.84 years in the bottom layer. The wind direction in the bay shifts between SW and NE, with the main wind direction being SW during the winter period, and water mass movement is influenced by such seasonal variations in wind direction. Vertical circulation currents in the bay are structured by two phenomena: the surface riverine outflow layer from the Hyeong-san River into the open sea and the bottom oceanic inflow layer with high-temperature and salinity into the bay. These phenomena start the spring when the water mass is stable and become stronger in the summer when the surface cold water develops over a 10-day period. Consequently, tidal currents have little influence in the bay; rather, these vertical and horizontal circulation currents play an important role in the transport of the pollutant load from the inner bay to the open sea.