• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.201-208
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• 2018

Purpose : The purpose of this study is to compare and analyze the set-up errors using the Combine IGRT with ExacTrac and CBCT phased in the treatment of Stereotatic Body Radiotherapy. Methods and materials : Patient who were treated Stereotatic Body Radiotherapy in the ulsan university hospital from May 2014 to november 2017 were classified as treatment area three brain, nine spine, three pelvis. First using ExacTrac Set-up error calibrated direction of Lateral(Lat), Longitudinal(Lng), Vertical(Vrt), Roll, Pitch, Yaw, after applied ExacTrac moving data in addition to use CBCT and set-up error calibrated direction of Lat, Lng, Vrt, Rotation(Rtn). Results : When using ExacTrac, the error in the brain region is Lat $0.18{\pm}0.25cm$, Lng $0.23{\pm}0.04cm$, Vrt $0.30{\pm}0.36cm$, Roll $0.36{\pm}0.21^{\circ}$, Pitch $1.72{\pm}0.62^{\circ}$, Yaw $1.80{\pm}1.21^{\circ}$, spine Lat $0.21{\pm}0.24cm$, Lng $0.27{\pm}0.36cm$, Vrt $0.26{\pm}0.42cm$, Roll $1.01{\pm}1.17^{\circ}$, Pitch $0.66{\pm}0.45^{\circ}$, Yaw $0.71{\pm}0.58^{\circ}$, pelvis Lat $0.20{\pm}0.16cm$, Lng $0.24{\pm}0.29cm$, Vrt $0.28{\pm}0.29cm$, Roll $0.83{\pm}0.21^{\circ}$, Pitch $0.57{\pm}0.45^{\circ}$, Yaw $0.52{\pm}0.27^{\circ}$ When CBCT is performed after the couch movement, the error in brain region is Lat $0.06{\pm}0.05cm$, Lng $0.07{\pm}0.06cm$, Vrt $0.00{\pm}0.00cm$, Rtn $0.0{\pm}0.0^{\circ}$, spine Lat $0.06{\pm}0.04cm$, Lng $0.16{\pm}0.30cm$, Vrt $0.08{\pm}0.08cm$, Rtn $0.00{\pm}0.00^{\circ}$, pelvis Lat $0.06{\pm}0.07cm$, Lng $0.04{\pm}0.05cm$, Vrt $0.06{\pm}0.04cm$, Rtn $0.0{\pm}0.0^{\circ}$. Conclusion : Combine IGRT with ExacTrac in addition to CBCT during Stereotatic Body Radiotherapy showed that it was possible to reduce the set-up error of patients compared to single ExacTrac. However, the application of Combine IGRT increases patient set-up verification time and absorption dose in the body for image acquisition. Therefore, depending on the patient's situation that using Combine IGRT to reduce the patient's set-up error can increase the radiation treatment effectiveness.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.41 no.4
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• pp.361-373
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• 2015

This study was carried out to evaluate the antioxidant and antibacterial activities of Glycyrriza uralensis Fisher (Jecheon, Korea) extracts obtained by various extraction conditions (85% ethanol, heating temperatures and times), and to establish the optimal extraction condition of G. uralensis for the application as cosmetic ingredients. The extracts obtained under different conditions were concentrated and made in the powdered (sample-1) and were the crude extract solutions without concentration (sample-2). The antioxidant effects were determined by free radical scavenging activity ($FSC_{50}$), ROS scavenging activity ($OSC_{50}$), and cellular protective effects. Antibacterial activity was determined by minimum inhibitory concentration (MIC) on human skin flora. DPPH free radical scavenging activity of sample-1 ($100{\mu}g/mL$) was 10% higher in group extracted for 6 h than 12 h, but sample-2 didn't show any significant differences. The extraction yield extracted with same temperature for 12 h was 2.6 times higher than 6 h, but total flavonoid content was 1.1 times higher. These results indicated that total flavonoid content hardly increased with increasing extraction time. Free radical scavenging activity, ROS scavenging activity and cellular protective effects were not dependent on the yield of extraction, but total flavonoid content of extraction. Antibacterial activity on three skin flora (S. aureus, B. subtilis, P. acnes)of sample-1 in different extraction conditions were evaluated on same concentration, and the group extracted at 25 and $40^{\circ}C$ showed 16 times higher than methyl paraben ($2,500{\mu}g/mL$). In conclusion, 85% ethanol extracts of G. uralensis extracted at $40^{\circ}C$ for 6 h showed the highest antioxidant and antibacterial activity. These results indicate that the extraction condition is important to be optimized by comprehensive evaluation of extraction yield with various conditions, yield of active component, and activity test with concentrations, and activity of 100% extract, for manufacturing process of products.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1232-1238
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• 2011

This experiment was conducted to measure concentration of dissolved $N_2O$ in ground-water of 59 wells and to make emission factor for assessment of indirect $N_2O$ emission at agricultural sector in agricultural areas of Gyeongnam province from 2007 to 2010. Concentrations of dissolved $N_2O$ in ground-water of 59 wells were ranged trace to $196.6{\mu}g-N\;L^{-1}$. $N_2O$ concentrations were positively related with $NO_3$-N suggesting that denitrification was the principal reason of $N_2O$ production and $NO_3$-N concentration was the best predictor of indirect $N_2O$ emission. The ratio of dissolved $N_2O$-N to $NO_3$-N in ground-water was very important to make emission factor for assessment of indirect $N_2O$ emission at agricultural sector. The mean ratio of $N_2O$-N to $NO_3$-N was 0.0035. It was greatly lower than 0.015, the default value of currently using in the Intergovernmental Panel on Climate Change (IPCC) methodology for assessing indirect $N_2O$ emission in agro-ecosystems (IPCC, 1996). It means that the IPCC's present nitrogen indirect emission factor ($EF_{5-g}$, 0.015) and indirect $N_2O$ emission estimated with IPCC's emission factor are too high to use adopt in Korea. So we recommend 0.0034 as national specific emission factor ($EF_{5-g}$) for assessment of indirect $N_2O$ emission at agricultural sector. Using the estimated value of 0.0034 as the emission factor ($EF_{5-g}$) revised the indirect $N_2O$ emission from agricultural sector in Korea decreased from 1,801,576 ton ($CO_2$-eq) to 964,645 ton ($CO_2$-eq) in 2008. The results of this study suggest that the indirect Emission of nitrous oxide from upland recommend 0.0034 as national specific emission factor ($EF_{5-g}$) for assessment of indirect $N_2O$ emission at agricultural sector.

• The Korean Journal of Archival Studies
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• no.22
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• pp.157-199
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• 2009

The organization for managing records and archives did not emerge together with the founding of the Chinese Communist Party. Such management became active with the establishment of the Department of Documents (文書科) and its affiliated offices overseeing reading and safekeeping of official papers, after the formation of the Central Secretariat(中央秘書處) in 1926. Improving the work of the Secretariat's organization became the focus of critical discussions in the early 1930s. The main criticism was that the Secretariat had failed to be cognizant of its political role and degenerated into a mere "functional organization." The solution to this was the "politicization of the Secretariat's work." Moreover, influenced by the "Rectification Movement" in the 1940s, the party emphasized the responsibility of the Resources Department (材料科) that extended beyond managing documents to collecting, organizing and providing various kinds of important information data. In the mean time, maintaining security with regard to composing documents continued to be emphasized through such methods as using different names for figures and organizations or employing special inks for document production. In addition, communications between the central political organs and regional offices were emphasized through regular reports on work activities and situations of the local areas. The General Secretary not only composed the drafts of the major official documents but also handled the reading and examination of all documents, and thus played a central role in record processing. The records, called archives after undergoing document processing, were placed in safekeeping. This function was handled by the "Document Safekeeping Office(文件保管處)" of the Central Secretariat's Department of Documents. Although the Document Safekeeping Office, also called the "Central Repository(中央文庫)", could no longer accept, beginning in the early 1930s, additional archive transfers, the Resources Department continued to strengthen throughout the 1940s its role of safekeeping and providing documents and publication materials. In particular, collections of materials for research and study were carried out, and with the recovery of regions which had been under the Japanese rule, massive amounts of archive and document materials were collected. After being stipulated by rules in 1931, the archive classification and cataloguing methods became actively systematized, especially in the 1940s. Basically, "subject" classification methods and fundamental cataloguing techniques were adopted. The principle of assuming "importance" and "confidentiality" as the criteria of management emerged from a relatively early period, but the concept or process of evaluation that differentiated preservation and discarding of documents was not clear. While implementing a system of secure management and restricted access for confidential information, the critical view on providing use of archive materials was very strong, as can be seen in the slogan, "the unification of preservation and use." Even during the revolutionary movement and wars, the Chinese Communist Party continued their efforts to strengthen management and preservation of records & archives. The results were not always desirable nor were there any reasons for such experiences to lead to stable development. The historical conditions in which the Chinese Communist Party found itself probably made it inevitable. The most pronounced characteristics of this process can be found in the fact that they not only pursued efficiency of records & archives management at the functional level but, while strengthening their self-awareness of the political significance impacting the Chinese Communist Party's revolution movement, they also paid attention to the value possessed by archive materials as actual evidence for revolutionary policy research and as historical evidence of the Chinese Communist Party.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.25-32
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• 2019

Purpose: The size, shape, and volume of prosthetic appliance depend on the metal artifacts resulting from dental implant during head and neck treatment with radiation. This reduced the accuracy of contouring targets and surrounding normal tissues in radiation treatment plan. Therefore, the purpose of this study is to obtain the images of metal representing the size of tooth through MVCT, SMART-MAR CT and KVCT, evaluate the volumes, apply them into the proton therapy plan, and analyze the difference of dose distribution. Materials and Methods : Metal A ($0.5{\times}0.5{\times}0.5cm$), Metal B ($1{\times}1{\times}1cm$), and Metal C ($1{\times}2{\times}1cm$) similar in size to inlay, crown, and bridge taking the treatments used at the dentist's into account were made with Cerrobend ($9.64g/cm^3$). Metal was placed into the In House Head & Neck Phantom and by using CT Simulator (Discovery CT 590RT, GE, USA) the images of KVCT and SMART-MAR were obtained with slice thickness 1.25 mm. The images of MVCT were obtained in the same way with $RADIXACT^{(R)}$ Series (Accuracy $Precision^{(R)}$, USA). The images of metal obtained through MVCT, SMART-MAR CT, and KVCT were compared in both size of axis X, Y, and Z and volume based on the Autocontour Thresholds Raw Values from the computerized treatment planning equipment Pinnacle (Ver 9.10, Philips, Palo Alto, USA). The proton treatment plan (Ray station 5.1, RaySearch, USA) was set by fusing the contour of metal B ($1{\times}1{\times}1cm$) obtained from the above experiment by each CT into KVCT in order to compare the difference of dose distribution. Result: Referencing the actual sizes, it was appeared: Metal A (MVCT: 1.0 times, SMART-MAR CT: 1.84 times, and KVCT: 1.92 times), Metal B (MVCT: 1.02 times, SMART-MAR CT: 1.47 times, and KVCT: 1.82 times), and Metal C (MVCT: 1.0 times, SMART-MAR CT: 1.46 times, and KVCT: 1.66 times). MVCT was measured most similarly to the actual metal volume. As a result of measurement by applying the volume of metal B into proton treatment plan, the dose of $D_{99%}$ volume was measured as: MVCT: 3094 CcGE, SMART-MAR CT: 2902 CcGE, and KVCT: 2880 CcGE, against the reference 3082 CcGE Conclusion: Overall volume and axes X and Z were most identical to the actual sizes in MVCT and axis Y, which is in the superior-Inferior direction, was regular in length without differences in CT. The best dose distribution was shown in MVCT having similar size, shape, and volume of metal when treating head and neck protons. Thus it is thought that it would be very useful if the contour of prosthetic appliance using MVCT is applied into KVCT for proton treatment plan.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.371-379
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• 2019

The purpose of this study was to investigate the effect of the change in the X-ray condition on the entrance surface dose (ESD) and dose area product (DAP) in the cine imaging of coronary angiography (CAG), and to analyze the usefulness of the condition change on the dose relation and image quality by measuring and analyzing the Signal to Noise Radio (SNR) and Contrast to Nois Ratio (CNR) of the angiographic images taken by the Image J program. Data were collected from 33 patients (24 males and 9 females) who underwent CAG at this hospital from November 2017 to March 2018. In terms of imaging condition and data acquisition, the ESD and DAP of group A with a high tube current of 397.2 mA and group B with a low tube current of 370.7 mA were retrospectively obtained for comparison and analysis. For the SNR and CNR measurement and analysis via Image J, the result values were derived by substituting the obtained data into the formula. The correlations among ESD and DAP according to the change in the imaging condition, SNR, and CNR were analyzed by using the SPSS statistical analysis software. The relationships of groups A and B, having a difference in the imaging condition, mA, with ESD ($A:483.5{\pm}60.1$; $B: 464.4{\pm}39.9$) and DAP ($A:84.3{\pm}10.7$; $B:81.5{\pm}7$) were not statistically significant (p>0.05). In the relationships with SNR and CNR based on Image J, the SNR ($5.451{\pm}0.529$) and CNR ($0.411{\pm}0.0432$) of the images obtained via the left coronary artery (LCA) imaging of group B showed differences of $0.475{\pm}0.096$ and $-0.048{\pm}0.0$, respectively, from the SNR ($4.976{\pm}0.433$) and CNR ($0.459{\pm}0.0431$) of the LCA of group A. However, the differences were not statistically significant (p<0.05). In the SNR and CNR obtained via the right coronary artery (RCA) imaging, the SNR ($4.731{\pm}0.773$) and CNR ($0.354{\pm}0.083$) of group A showed increased values of $1.491{\pm}0.405$ and $0.188{\pm}0.005$, respectively, from the SNR ($3.24{\pm}0.368$) and CNR ($0.166{\pm}0.033$) of group B. Among these, CNR was statistically significant (p<0.05). In the correlation analysis, statistically significant results were shown in SNR (LCA) and CNR (LCA); SNR (RCA) and CNR (RCA); ESD and DAP; ESD and sec; DAP and CNR (RCA); and DAP and sec (p<0.05). As a result of the analyses on the image quality evaluation and usefulness of the dose change, the SNR and CNR were increased in the RCA images of the CAG obtained by increasing the mA. Based on the result that CNR showed a statistically significant difference, it is believed that the contrast in the image quality can be further improved by increasing the mA in RCA imaging.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Korean Journal of Poultry Science
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• v.46 no.2
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• pp.65-75
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• 2019

A number of Korean native chicken(KNC) populations were registered in FAO (Food and Agriculture Organization) DAD-IS (Domestic Animal Diversity Information Systems, http://www.fao.org/dad-is). But there is a lack of scientific basis to prove that they are unique population of Korea. For this reason, this study was conducted to prove KNC's uniqueness using 25 Microsatellite markers. A total of 548 chickens from 11 KNC populations (KNG, KNB, KNR, KNW, KNY, KNO, HIC, HYD, HBC, JJC, LTC) and 7 introduced populations (ARA: Araucana, RRC and RRD: Rhode Island Red C and D, LGF and LGK: White Leghorn F and K, COS and COH: Cornish brown and Cornish black) were used. Allele size per locus was decided using GeneMapper Software (v 5.0). A total of 195 alleles were observed and the range was 3 to 14 per locus. The MNA, $H_{\exp}$, $H_{obs}$, PIC value within population were the highest in KNY (4.60, 0.627, 0.648, 0.563 respectively) and the lowest in HYD (1.84, 0.297, 0.286, 0.236 respectively). The results of genetic uniformity analysis suggested 15 cluster (${\Delta}K=66.22$). Excluding JJC, the others were grouped in certain cluster with high genetic uniformity. JJC was not grouped in certain cluster but grouped in cluster 2 (44.3%), cluster 3 (17.7%) and cluster8 (19.1%). As a results of this study, we can secure a scientific basis about KNC's uniqueness and these results can be use to basic data for the genetic evaluation and management of KNC breeds.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.