• Korean Journal of Environmental Biology
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• v.26 no.4
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• pp.311-322
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• 2008

The objectives of the study were to analyze chemical water quality and physical habitat characteristics in the urban streams (Miho and Gap streams) along with evaluations of fish community structures and ecosystem health, throughout fish composition and guild analyses during 2006$\sim$2007. Concentrations of BOD and COD averaged 3.5 and 5.7 mg L$^{-1}$, in the urban streams, while TN and TP averaged 5.1 mg L$^{-1}$ and 274 ${\mu}g$ L$^{-1}$, indicating an eutrophic state. Especially, organic pollution and eutrophication were most intense in the downstream reach of both streams. Total number of fish was 34 species in the both streams, and the most abundant species was Zacco platypus (32$\sim$42% of the total). In both streams, the relative abundance of sensitive species was low (23%) and tolerant and omnivores were high (45%, 52%), indicating an typical tolerance and trophic guilds of urban streams in Korea. According to multi-metric models of Stream Ecosystem Health Assessments (SEHA), model values were 19 and 24 in Miho Stream and Gap Stream, respectively. Habitat analysis showed that QHEI (Qulatitative Habitat Evaluation Index) values were 123 and 135 in the two streams, respectively. The minimum values in the SEHA and QHEI were observed in the both downstreams, and this was mainly attributed to chemical pollutions, as shown in the water quality parameters. The model values of SEHA were strongly correlated with conductivity (r=-0.530, p=0.016), BOD (r=-0.578, p< 0.01), COD (r=-0.603, p< 0.01), and nutrients (TN, TP: r>0.40, p<0.05). This model applied in this study seems to be a useful tool, which could reflect the chemical water quality in the urban streams. Overall, this study suggests that consistent ecological monitoring is required in the urban streams for the conservations along with ecological restorations in the degradated downstrems.

• Journal of the Korean Arthroscopy Society
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• v.9 no.2
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• pp.132-136
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• 2005

Purpose: The purpose of this study was to compare the clinical results of the arthroscopic anterior cruciate ligament reconstruction used by Bone-Patella tendon-Bone autograft and Achilles tendon allograft. Materials and Methods: We reviewed the results of patients who had been managed with arthroscopic anterior cruciate ligament reconstruction using different graft such as Bone-Patella tendon-Bone autograft and Achilles les tendon allograft. 60patients (average age, 33.5 years)were retrospectively evaluated. The one group(average age, 33.4 years) was 32 patient who had been managed with arthroscopic anterior cruciate ligament reconstruction using Bone-Patella tendon-Bone autograft. The other group(average age, 32.1 years) was 28 patient who had been managed with arthroscopic anterior cruciate ligament reconstruction using Achilles tendon allograft. 2 groups were evaluated subjectively by Lysholm knee scoring scale and objectively by KT-2000 arthrometer. The follow-up period was more than a year(average, 18 month). An early rehabilitation protocol was instituted. Results: On Lysholm knee scoring scale, the final evaluation was nearly normal in all patients. We could not find statistical difference among the two groups by KT-2000TM arthrometer. Conclusion: The use of allografts may be an acceptable choice for ACL reconstruction.

• Korean Journal of Ecology and Environment
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• v.41 no.2
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• pp.188-197
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• 2008

This research was a preliminary case study to determine the levels of total mercury in the tissues of sentinel species (Zacco platypus) and ecological health in relation to habitat characteristics and chemical conditions. We collected fishes in Gap Stream during June$\sim$October 2007 and analyzed the total mercury from five types of tissues such as liver, kidney, gill, vertebrae and muscle of Zaceo platypus using Direct Mercury Analyzer (DMA-80, US EPA Method 7473). Mean concentrations of total [Hg], based on all tissues, was 67.2 and $20.7\;{\mu}g\;kg^{-1}$, in the upstream and downstream site, respectively, indicating 3 times greater level in the upstream. In other words, the levels were higher in the pristine upstream than the downstream influenced by the wastewater disposal plant. Chemical water quality, based on BOD, COD and nutrients (TN, TP) showed that severe degradation occurred in the downstreams than the upstreams. Index of Biological Integrity (IBI) using fish multi-metric model averaged 32, indicating a "good$\sim$fair" condition and varied from 42 (excellent$\sim$good) at S2 to 22 (fair$\sim$poor) at S5 depending on the sites sampled. Qualitative Habitat Evaluation Index (QHEI) in the all sites averaged 142, which was judged as "good" habitat health, but showed a high variation (181 in Site 2 vs. 67 in Site 5). Overall data suggest that health conditions, based on IBI and QHEI, was better in the upstream sites but the mercury bioaccumulation levels in the fish tissues were opposite. We believe that measurements of various parameters are required for a diagnosis of integrative ecosystem health.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• The Journal of Engineering Geology
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• v.28 no.2
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• pp.217-246
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• 2018

During the selection and characterization of target formations in the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin, we have carefully investigated the possibility of induced earthquakes and leakage of $CO_2$ during the injection, and have designed the storage processes to minimize these effects. However, people in Pohang city have a great concern on $CO_2$-injection-intrigued seismicity, since they have greatly suffered from the 5.4 magnitude earthquake on Nov. 15, 2017. The research team of the project performed an extensive self-investigation on the safety issues, especially on the possible $CO_2$ leakage from the target formation and induced earthquakes. The target formation is 10 km apart from the epicenter of the Pohang earthquake and the depth is also quite shallow, only 750 to 800 m from the sea bottom. The project performed a pilot injection in the target formation from Jan. 12 to Mar. 12, 2017, which implies that there are no direct correlation of the Pohang earthquake on Nov. 15, 2017. In addition, the $CO_2$ injection of the storage project does not fracture rock formations, instead, the supercritical $CO_2$ fluid replaces formation water in the pore space gradually. The self-investigation results show that there is almost no chance for the injection to induce significant earthquakes unless injection lasts for a very long time to build a very high pore pressure, which can be easily monitored. The amount of injected $CO_2$ in the project was around 100 metric-tonne that is irrelevant to the Pohang earthquake. The investigation result on long-term safety also shows that the induced earthquakes or the reactivation of existing faults can be prevented successfully when the injection pressure is controlled not to demage cap-rock formation nor exceed Coulomb stresses of existing faults. The project has been performing extensive studies on critical stress for fracturing neighboring formations, reactivation stress of existing faults, well-completion processes to minimize possible leakage, transport/leakage monitoring of injected $CO_2$, and operation procedures for ensuring the storage safety. These extensive studies showed that there will be little chance in $CO_2$ leakage that affects human life. In conclusion, the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin would not cause any induced earthquakes nor signifiant $CO_2$ leakage that people can sense. The research team will give every effort to secure the safety of the storage site.