• Journal of Food Hygiene and Safety
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• v.23 no.4
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• pp.338-342
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• 2008

Choline is important an organic compound for normal membrane function, acetylcholine synthesis, lipid transport, and methyl metabolism. In biological tissues and foods, there are multiple choline compounds that contribute to choline content. Many researches suggest that memory and intelligence are improved by the supplement of choline. Recently, according to the effects of choline for memory, choline has been added to milk. In this study, the content of choline was analyzed the commercial whole milks and flavored milks by enzymatic method. The standard curve was linear with 0.00316 slope and 0.994 correlation coefficient. Recoveries varied between 89.8 and 97.6%. Contents of choline in whole milks and flavored milks were 14.56-15.19 and 4.11-11.50 mg/100g, respectively. The results of this study may be usable for the establishment of choline adequate intake for Korean.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.109-116
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• 2004

Petroleum reservoir characterization is a process for quantitatively describing various reservoir properties in spatial variability using all the available field data. Porosity and permeability are the two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. In un-cored intervals and well of heterogeneous formation, porosity and permeability estimation from conventional well logs has a difficult and complex problem to solve by conventional statistical methods. This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear regression method to develop transformation between the selected well logs and core analysis data. The intelligent technique is demonstrated with an application to the well data in offshore Korea. The results show that this technique can make more accurate and reliable properties estimation compared with previously used methods. The intelligent technique can be utilized a powerful tool for reservoir characterization from well logs in oil and natural gas development projects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.22-33
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• 2005

In this paper, an efficient signal interference control technique to improve the high convergence speed of LMS algorithms is introduced in the adaptive transversal filter of DS/SS. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, is analyzed to prove theoretically the improvement of high convergence speed. According as the step-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Also, an increase in the stop-size parameter ${\mu}$ has the effect of reducing the variation in the experimentally computed learning curve. Increasing the eigenvalue spread has the effect of controlling which is downed the rate of convergence of the adaptive equalizer. Increasing the steady-state value of the average squared error, proposed algorithm also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS technique.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.628-641
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• 2012

This research investigates a dynamic mechanism underlying the co-evolution between network and space by applying hype-curve model, typical phenomenon which shows how new technologies and ideas initially adapted in the society. This study analysis the knowledge intensive industry of digital contents using social network analysis (SNA) in terms of structural, spatial, and temporal aspects, year of 2000, 2005, and 2010 focused on Seoul area. First of all, network and space establish 'inter-feedback' as a result of evolution and differentiation process. Second, it happen temporal 'delay' through the learning process stage of 'peak of inflated expectation' and 'trough of disillusionment.' As a result, Seoul develops with the technology commercialized-orient strategy affect government policy. This trend changes to technology-oriented development in Seoul area in the late of 2000 established 'self-organization' with geographical proximity organizations through learning process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.57-62
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• 2014

This paper proposes the improving the equalization performance using the adaptive modulus concept to the MCMA blind equalizer in order to the reduction of intersymbol interference which occurs in the band limited and time dispersive communication channel. In MCMA blind algorithm, it is possible to reducing the amplitude and phase rotation of intersymbol interference without training sequence, the fixed constant modulus of transmission signal is used. But in proposed algorithm, the modulus are adaptively varies according to the equalizer output signal, then the improved equalization performance were obtained by the computer simulation. For this, the recovered signal constellation that is the output of the equalizer, the convergence performance by MSE, MD (maximum distortion) and residual isi characteristic learning curve were used. The propose algorithm has fairly good performance compared to the traditional MCMA algorithm in the same adaptive equalization algorithm.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.1-8
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• 2005

As a trial to find an efficient technique for determining hydraulic conductivity, a test application of electrical conductivity measurement technique was made using a signal conditioning data acquisition system in borehole. The experiment was made in two test boreholes BM-2 and BM-3 which are located in the Experiment forests of Kangwon National University in Bongmyongri, Chunchon. We obtained series of electric conductivity variation curves after the beginning and completion of saline water injection using these two bore-holes as the pumping well and the observing well alternatively, The analysis of time series electrical conductivity data suggests kinds of valuable information about aquifer properties by holes and depths, and we could confirm the potential of this method as an efficient tool for in situ aquifer test.

• Journal of the Korean GEO-environmental Society
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• v.14 no.9
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• pp.31-37
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• 2013

In this study installation diameter, interval, area replacement ratio and ground hardness of applicable ground in C.G.S method should be mastered through surrounding ground by conducting modeling. Optimum artificial neural network was selected through the study of the parameter of artificial neural network and prediction model was developed by the relationship with numerical analysis and artificial neural network. As this result, C.G.S pile settlement and ground settlement were found to be equal in terms of diameter, interval, area replacement ratio and ground hardness, presented in a single curve, which means that the behavior pattern of applied ground in C.G.S method was presented as some form, and based on such a result, learning the artificial neural network for 3D behavior was found to be possible. As the study results of artificial neural network internal factor, when using the number of neural in hidden layer 10, momentum constant 0.2 and learning rate 0.2, relationship between input and output was expressed properly. As a result of evaluating the ground behavior of C.G.S method which was applied to using such optimum structure of artificial neural network model, is that determination coefficient in case of C.G.S pile settlement was 0.8737, in case of ground settlement was 0.7339 and in case of ground heaving was 0.7212, sufficient reliability was known.

• Journal of the Korean Arthroscopy Society
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• v.13 no.3
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• pp.212-219
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• 2009

Medially retracted large-sized rotator cuff tears includes large-sized tears, massive tears and irreparable tears. Generally arthroscopic repair or open repair of rotator cuff tears is used in reparable tears. However, arthroscopic repair requires long period practice and endurance. In irreparable tears, arthroscopic debridement, partial repair, latissimus dorsi transfer and retrograde arthroplasty can be the option. Arthoscopic debridement gives temporal relief who experienced improvement in pain and increase in range of motion after subacromial local anesthetic injection. Also arthroscopic partial repair gives good results in irreparable cases, especially in suprascapular nerve traction neurapraxia. Tendon transfer can be used in mild to moderate muscle weakness in shoulder abduction for long term treatment. Pectoralis major transfer can be used in anterosupeior tears and latissimus dorsi transfer can be used in posterosuperior tears. Reverse shoulder prosthesis is used in extreamly weakened shoulder pseudoparalysis. The authors discussed the method of arthroscopic repair in irreparable tears. The debridement, partial repair, and tendon transfer could be used in medially retracted large-sized rotator cuff tears.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.3
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• pp.263-276
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• 2023

The purpose of this study was to evaluate the performance of a model using You Only Look Once (YOLO) for object detection of proximal caries in periapical radiographs of children. A total of 2016 periapical radiographs in primary dentition were selected from the M6 database as a learning material group, of which 1143 were labeled as proximal caries by an experienced dentist using an annotation tool. After converting the annotations into a training dataset, YOLO was trained on the dataset using a single convolutional neural network (CNN) model. Accuracy, recall, specificity, precision, negative predictive value (NPV), F1-score, Precision-Recall curve, and AP (area under curve) were calculated for evaluation of the object detection model's performance in the 187 test datasets. The results showed that the CNN-based object detection model performed well in detecting proximal caries, with a diagnostic accuracy of 0.95, a recall of 0.94, a specificity of 0.97, a precision of 0.82, a NPV of 0.96, and an F1-score of 0.81. The AP was 0.83. This model could be a valuable tool for dentists in detecting carious lesions in periapical radiographs.