• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.35-39
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• 2019

Purpose Hepatitis B virus (hepatitis B virus, HBV) infection is a worldwide major public health problem and it is known as a major cause of chronic hepatitis, liver cirrhosis and liver cancer. And serologic tests of hepatitis B virus is essential for diagnosing and treating these diseases. In addition, with the development of molecular diagnostics, the detection of HBV DNA in serum diagnoses HBV infection and is recognized as an important indicator for the antiviral agent treatment response assessment. We performed HBeAg assay using Immunoradiometric assay (IRMA) and Chemiluminescent Microparticle Immunoassay (CMIA) in hepatitis B patients treated with antiviral agents. The detection rate of HBV DNA in serum was measured and compared by RT-PCR (Real Time - Polymerase Chain Reaction) method Materials and Methods HBeAg serum examination and HBV DNA quantification test were conducted on 270 hepatitis B patients undergoing anti-virus treatment after diagnosis of hepatitis B virus infection. Two serologic tests (IRMA, CMIA) with different detection principles were applied for the HBeAg serum test. Serum HBV DNA was quantitatively measured by real-time polymerase chain reaction (RT-PCR) using the Abbott m2000 System. Results The detection rate of HBeAg was 24.1% (65/270) for IRMA and 82.2% (222/270) for CMIA. Detection rate of serum HBV DNA by real-time RT-PCR is 29.3% (79/270). The measured amount of serum HBV DNA concentration is $4.8{\times}10^7{\pm}1.9{\times}10^8IU/mL$($mean{\pm}SD$). The minimum value is 16IU/mL, the maximum value is $1.0{\times}10^9IU/mL$, and the reference value for quantitative detection limit is 15IU/mL. The detection rates and concentrations of HBV DNA by group according to the results of HBeAg serological (IRMA, CMIA)tests were as follows. 1) Group I (IRMA negative, CMIA positive, N = 169), HBV DNA detection rate of 17.7% (30/169), $6.8{\times}10^5{\pm}1.9{\times}10^6IU/mL$ 2) Group II (IRMA positive, CMIA positive, N = 53), HBV DNA detection rate 62.3% (33/53), $1.1{\times}10^8{\pm}2.8{\times}10^8IU/mL$ 3) Group III (IRMA negative, CMIA negative, N = 36), HBV DNA detection rate 36.1% (13/36), $3.0{\times}10^5{\pm}1.1{\times}10^6IU/mL$ 4) Group IV(IRMA positive, CMIA negative, N = 12), HBV DNA detection rate 25% (3/12), $1.3{\times}10^3{\pm}1.1{\times}10^3IU/mL$ Conclusion HBeAg detection rate according to the serological test showed a large difference. This difference is considered for a number of reasons such as characteristics of the Ab used for assay kit and epitope, HBV of genotype. Detection rate and the concentration of the group-specific HBV DNA classified serologic results confirmed the high detection rate and the concentration in Group II (IRMA-positive, CMIA positive, N = 53).

• Korean Journal of Environment and Ecology
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• v.33 no.3
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• pp.280-291
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• 2019

A. antiquum, first observed in Jeju Samdo Island in 1949, was designated as the Natural Monument No. 18 in December 1962 in recognition of its academic value. In Korea, it grows in nature only in Samdo in Jeju Island. Although its natural habitat was greatly damaged and almost destroyed due to firewood, stealing, etc. After the emancipation, it has been maintained by the transplantation and restoration. The site observed by this study has been managed as a restricted area since 2011. Since it has been about 20 years since the restoration of the native site in the 2000s, it is necessary to check the official management history records, such as the origin of transplantation and restoration to monitor the changes in the growth status and to control the habitat. As the results of this study, we have secured the records of cultural property management history, such as the identification of native species and the transplantation and restoration records. We also examined the change of the growth and development of A. antiquum 20 years after the restoration. There are no official records of the individuals transplanted to the restored natural habitat of A. antiquum in the 1970s and 1980s, and there was a controversy about the nativeness of those individuals that were restored and transplanted in 1974 since they were Japanese individuals. The studies of identifying native as the results of this study, we have secured the records of cultural property management history, such as the identification of native species and the transplantation and restoration records. We also examined the change of the growth and development of A. antiquum 20 years after the restoration. There are two sites in natural habitat in Samdo Island. A total of 65 individuals grow in three layers on three stone walls in a site while 29 individuals grow in two columns in the other site. A. antiquum grows in an evergreen broad-leaved forest dominated by Neolitsea sericea, and we did not find any other individuals of naturally growing A. antiquum outside the investigated site. This study checked the distribution of A. antiquum seedlings observed initially after the restoration. There were more than 300 seedling individuals, and we selected three densely populated sites for monitoring. There were 23 A. antiquum seedlings with 4 - 17 leaves per individual and the leaf length of 0.5 - 20 cm in monitoring site 1. There were 88 individuals with 5 - 6 leaves per individual and the leaf length of 1.3 - 10.4 cm in monitoring site 2 while there were 22 individuals with 5 - 9 leaves per individual and the leaf length of 4.5 - 12.1 cm in monitoring site 3. Although the natural habitat of A. antiquum was designated as a restricted public area in 2011, there is a high possibility that the habitat can be damaged because some activities, such as fishing and scuba diving are allowed. Therefore, it is necessary to enforce the law strictly, to provide sufficient education for the preservation of natural treasures, and to present accurate information about cultural assets.

• 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.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.75-81
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• 2019

Purpose: Helmet type bolus for 3D printer is being manufactured because of the disadvantages of Bolus materials when photon beam is used for the treatment of scalp malignancy. However, PLA, which is a used material, has a higher density than a tissue equivalent material and inconveniences occur when the patient wears PLA. In this study, we try to treat malignant scalp tumors by using M3 wax helmet with 3D printer. Methods and materials: For the modeling of the helmet type M3 wax, the head phantom was photographed by CT, which was acquired with a DICOM file. The part for helmet on the scalp was made with Helmet contour. The M3 Wax helmet was made by dissolving paraffin wax, mixing magnesium oxide and calcium carbonate, solidifying it in a PLA 3D helmet, and then eliminated PLA 3D Helmet of the surface. The treatment plan was based on Intensity-Modulated Radiation Therapy (IMRT) of 10 Portals, and the therapeutic dose was 200 cGy, using Analytical Anisotropic Algorithm (AAA) of Eclipse. Then, the dose was verified by using EBT3 film and Mosfet (Metal Oxide Semiconductor Field Effect Transistor: USA), and the IMRT plan was measured 3 times in 3 parts by reproducing the phantom of the head human model under the same condition with the CT simulation room. Results: The Hounsfield unit (HU) of the bolus measured by CT was $52{\pm}37.1$. The dose of TPS was 186.6 cGy, 193.2 cGy and 190.6 cGy at the M3 Wax bolus measurement points of A, B and C, and the dose measured three times at Mostet was $179.66{\pm}2.62cGy$, $184.33{\pm}1.24cGy$ and $195.33{\pm}1.69cGy$. And the error rates were -3.71 %, -4.59 %, and 2.48 %. The dose measured with EBT3 film was $182.00{\pm}1.63cGy$, $193.66{\pm}2.05cGy$ and $196{\pm}2.16cGy$. The error rates were -2.46 %, 0.23 % and 2.83 %. Conclusions: The thickness of the M3 wax bolus was 2 cm, which could help the treatment plan to be established by easily lowering the dose of the brain part. The maximum error rate of the scalp surface dose was measured within 5 % and generally within 3 %, even in the A, B, C measurements of dosimeters of EBT3 film and Mosfet in the treatment dose verification. The making period of M3 wax bolus is shorter, cheaper than that of 3D printer, can be reused and is very useful for the treatment of scalp malignancies as human tissue equivalent material. Therefore, we think that the use of casting type M3 wax bolus, which will complement the making period and cost of high capacity Bolus and Compensator in 3D printer, will increase later.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.49-65
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• 2019

This study was carried out to investigate the domestic and international development of a new cultivar of the Rose of Sharon (Hibiscus syriacus L.), the Korean national flower, and the protection of the new plant variety. In addition, it will be used as basic data for the expansion of domestic distribution, promoting oversea export, and expanding the range of landscape architectural use. A total of 97 varieties received plant variety protection rights from the Korea Seed & Variety Service from 2004 to 2018. The selection criteria were plants having unique flowers, growth habits, and variegated leaves. Some cultivars with unique features, such as flower size, shape, and red eyes were available for focus planting. Plant varieties with tall and strong growth patterns have been highly valuable for street and focus planting. Cultivars with dwarf stems and compact branches are utilized for pot planting and bonsai. The protected cultivars were mostly single flower varieties, with two semi-double flowers. There were 57 cultivars of pink flowers with red eyes and 21 cultivars of white flowers with red eyes. There were 61 cultivars developed by crossing, 23 cultivars through interspecific hybridization and 7 cultivars developed through radiation treatment and mutation. The Hibiscus cultivars registered to the United States Patent and Trademark Office (USPTO) consisted of seven cultivars each from the United States, the United Kingdom, and the Netherlands, four from South Korea, and three from Belgium. The Hibiscus cultivars registered to the European Community Plant Variety Office (CPVO) consisted of 16 cultivars from France, 9 from the Netherlands, 5 from the UK and 1 from Belgium. The cultivars that received both plant patent and plant breeder rights in the United States and Canada were 'America Irene Scott', 'Antong Two', 'CARPA', 'DVPazurri', 'Gandini Santiago', 'Gandini van Aart', 'ILVO347', 'ILVOPS', 'JWNWOOD 4', 'Notwood3', 'RWOODS5', 'SHIMCR1', 'SHIMRR38', 'SHIMRV24', and 'THEISSHSSTL'. 'SHIMCR1' and 'SHIMRV24' acquired both domestic plant protection rights and overseas plant patents. The 14 cultivars that received both US plant patents and European protection rights were 'America Irene Scott', 'Bricutts', 'DVPAZURRI', 'Gandini Santiago', 'Gandini van Aart', 'JWNWOOD4', 'MINDOUB1', 'MINDOUR1', 'MINDOUV5', 'NOTWOOD3', 'RWOODS5', 'RWOODS6', 'Summer Holiday', and 'Summer Night'. The cultivars that obtained US patents consisted of 18 cultivars (52.9%) with double flowers, 4 cultivars (11.8%) with semi-double flowers, and 12 cultivars (35.3%) with single flowers. The cultivars that obtained European new variety protection rights, consisted of 11 cultivars (34.3%) with double flowers, 12 cultivars (21.9%) with semi-double flowers, and 14 cultivars (43.8%) with single flowers. In the future, new cultivars of H. syriacus need to be developed in order to expand domestic distribution and export abroad. In addition, when developing new cultivars, it is required to develop cultivars with shorter branches for use in flower beds, borders, hedges, and pot planting.

• Korean Journal of Heritage: History & Science
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• v.52 no.2
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• pp.80-105
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• 2019

With the increasing complexity and irregularity of disaster types, the need for cultural asset preservation and management from a proactive perspective has increased as a number of cultural properties have been destroyed and damaged by various natural and humanistic factors. In consideration of these circumstances, the Cultural Heritage Administration enacted an Act in December 2005 to enforce the regular commission of surveys for the systematic preservation and management of cultural assets, and through a recent revision of this Act, the investigation cycle has been reduced from five to three years, and the object of regular inspections has been expanded to cover registered cultural properties. According to the ordinance, a periodic survey of city- or province-designated heritage is to be carried out mainly by metropolitan and provincial governments. The Seoul Metropolitan Government prepared a legal basis for commissioning regular surveys under the Seoul Special City Cultural Properties Protection Ordinance 2008 and, in recognition of the importance of preventive management due to the large number of cultural assets located in the city center and the high demand for visits, conducted regular surveys of the entire city-designated cultural assets from 2016 to 2018. Upon the first survey being completed, it was considered necessary to review the policy effectiveness of the system and to conduct a comprehensive review of the results of the regular surveys that had been carried out to enhance the management of cultural assets. Therefore, the present study examined the comprehensive management status of the cultural assets designated by the Seoul Metropolitan Government for three years (2016-2018), assessing the performance and identifying limitations. Additionally, ways to improve it were sought, and a DB establishment plan for the establishment of an integrated management system under the auspices of the Seoul Metropolitan Government was proposed. Specifically, survey forms were administered under the Guidelines for the Operation of Periodic Surveys of National Designated Cultural Assets; however, the types of survey forms were reclassified and further subdivided in consideration of the characteristics of the designated cultural assets, and manuals were developed for consistent and specific information technologies in respect of the scope and manner of the survey. Based on this analysis, it was confirmed that 401 cases (77.0%) out of 521 cases were generally well preserved; however, 102 cases (19.6%) were found to require special measures such as attention, precision diagnosis, and repair. Meanwhile, there were 18 cases (3.4%) of unsurveyed cultural assets. These were inaccessible to the investigation at this time due to reasons such as unknown location or closure to the public. Regarding the specific types of cultural assets, among a total of 171 cultural real estate properties, 63 cases (36.8%) of structural damage were caused by the failure and elimination of members, and 73 cases (42.7%) of surface area damage were the result of biological damage. Almost all plants and geological earth and scenic spots were well preserved. In the case of movable cultural assets, 25 cases (7.1%) among 350 cases were found to have changed location, and structural damage and surface area damage was found according to specific material properties, excluding ceramics. In particular, papers, textiles, and leather goods, with material properties that are vulnerable to damage, were found to have greater damage than those of other materials because they were owned and managed by individuals and temples. Thus, it has been confirmed that more proactive management is needed. Accordingly, an action plan for the comprehensive preservation and management status check shall be developed according to management status and urgency, and the project promotion plan and the focus management target should be selected and managed first. In particular, concerning movable cultural assets, there have been some cases in which new locations have gone unreported after changes in ownership (management); therefore, a new system is required to strengthen the obligation to report changes in ownership (management) or location. Based on the current status diagnosis and improvement measures, it is expected that the foundation of a proactive and efficient cultural asset management system can be realized through the establishment of an effective mid- to long-term database of the integrated management system pursued by the Seoul Metropolitan Government.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.227-234
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• 2019

An analytical method was developed for the determination of oxytetracycline in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). After the samples were extracted with methanol, the extracts were adjusted to pH 4 by formic acid and sodium chloride was added to remove water. Dispersive solid phase extraction (d-SPE) cleanup was carried out using $MgSO_4$ (anhydrous magnesium sulfate), PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed with LC-MS/MS using ESI (electrospray ionization) in positive ion MRM (multiple reaction monitoring) mode. The matrix-matched calibration curves were constructed using six levels ($0.001{\sim}0.25{\mu}g/mL$) and coefficient of determination ($r^2$) was above 0.99. Recovery results at three concentrations (LOQ, $10{\times}LOQ$, and $50{\times}LOQ$, n=5) were from 80.0 to 108.2% with relative standard deviations (RSDs) less than of 11.4%. For inter-laboratory validation, the average recovery was in the range of 83.5~103.2% and the coefficient of variation (CV) was below 14.1%. All results satisfied the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for oxytetracycline determination in agricultural commodities. This study could be useful for safety management of oxytetracycline residues in agricultural products.

• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.