• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.227-234
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• 2022

Seok Jeon Hwang Wook (18913~1999), a descendant of a traditional literary writer in the western part of Honam, did not join the flow of modern and contemporary calligraphy and painting. And throughout his life, he enjoyed himself without losing the appearance of a scholar, immersed himself in traditional calligraphy, and gained spotlight at his late age for his original hand grabbing calligraphy. Immediately after the Korean War, all of his property was lost due to his two sons' left-wing activities, causing great pain at home. Even in the most painful and difficult time in human history, he relied on brushes, poetry, and gayageum to keep his upright scholarly spirit and national love. And beyond the pleasures of the worldly senses, he played with self-satisfaction in the 'true pleasure(大樂)' without greed. In the course of his studies, he focused on honing the fonts of Wang Hui-ji, Gu Yang-sun, An Jin-gyeong, Jo Maeng-bu, and Xin-wi and Lee Sam-man without a special teacher. In particular, he faced a crisis of having to give up his brush due to tremor that came after his 60th birthday, but he showed a strong will. He transformed it into a new style of art, such as developing hand grabbing calligraphy(握筆法) with a strong and strong energy that no one could match. From 1965 to 1983, 'right hand grabbing calligraphy' was used, and from 1984 to 1993, 'left hand grabbing calligraphy' was used. She made her name as a calligrapher widely known in 1973 (age 76) with her first solo exhibition, The Calligraphy Exhibition commemorating her 60th wedding anniversary. His writing method is naturally rough and sloppy by breaking away from the previous calligraphy methods and artificial technique, and is unfamiliar yet full of muscle. And the calm, strong and rough chuhoegsa(錐劃沙) and the heavy yet majestic ininni(印印泥) individual handwriting expressed a strange feeling and achieved original Seokjeon calligraphy that went beyond the existing calligraphy writing methods, and his indomitable calligraphy spirit was As a unique existence in the history of calligraphy, he still remains as a model.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.479-486
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• 2023

This study is a descriptive research study to determine differences in conflict management types according to MBTI preference indicators among nursing students. Data collection was from August 30 to September 30, 2023. Data analysis was performed using independent t-test, one-way ANOVA, and Scheffe's. As a result of the study, among the MBTI indicators showing significant differences in conflict management types, 'i' had higher avoidance than 'E' in the energy direction (t=-3.776, <0.01). In the case of decision-making function, F had higher concession (t=-3.478, <0.01) and avoidance (t=-3.389, <0.01) than T, and T had higher dominance than F (t=2.070, <0.5). In terms of external life coping style, J had higher cooperation (t=2.756, <0.01) and compromise (t=2.044, <0.5) than P. In MBTI's psychological function types, the NF type had higher concessions than the ST type (F=4.174, <0.05), and the SF type had higher avoidance than the ST type (F=4.202, <0.05). The results of analyzing the differences in conflict management types by combining the MBTI decision-making function type and external life coping style showed that the FJ type was more cooperative than the FP type (F=2.907, <0.05), and the FJ type was more cooperative than the TP type (F =4.662, <0.01), and the FJ type had higher avoidance than the TJ type (F=3.327, <0.05). MBTI's attitude index showed that the EJ type had higher cooperation than the EP type (F=2.817, <0.05), and the IP type had significantly higher avoidance than the EP type (F=4.551, <0.01). This study is significant in confirming differences in conflict management types by combining MBTI decision-making function types (F, T) and external life coping styles (J, P), which have not been studied in Korea to date. In the follow-up study, we propose research on conflict management types by MBTI personality type by reflecting the results of this study and expanding the number of subjects, development of conflict management programs by MBTI indicators and personality types, and analysis of program effectiveness.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.173-189
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• 2023

As supreme technologies continue to be developed, industries such as artificial intelligence, biotechnology, robots, aerospace, electric vehicles, and solar energy are created, and the macro business environment is rapidly changing. Due to these large-scale changes and increased complexity, it is necessary to pay attention to the effect of social capital, which can create new value by utilizing capital increasing the importance of relationships rather than technology or asset ownership itself at the level of start-up strategy. Social capital is a concept first proposed by Hanifan in 1916, and refers to the overall sum of capabilities or resources that are latent or available for use in mutual, continuous, organic relationships or accumulated human relationship networks between individuals or social members. In addition, the diversity of start-up teams with diverse backgrounds, characteristics, and capabilities, rather than one exceptional founder, has been emphasized. Founding team diversity refers to the diversity of in-depth factors such as demographic factors, beliefs, and values of the founding team. In addition, changes in the macro environment are emphasizing the importance of technology start-ups and laboratory start-ups that lead industrial innovation and create the nation's core growth engines. This study focused on the I-Corps' program. I-Corps, which means innovation corps, is a laboratory startup program launched by the National Research Foundation (NSF) in 2011 to encourage entrepreneurship and commercialization of research results. It focuses on forming a startup team involving professors, researchers and market discovery activities. Taking these characteristics into account, this study empirically verified the impact of social capital from a network perspective and founding team diversity on I-Corps start-up performance. As a result of the analysis, the educational diversity of the founding team had a negative (-) effect on the financial performance of the founding team. On the other side, the gender diversity and the cognitive dimension of social capital had a positive (+) effect on the financial performance of the founding team. This study is expected to provide more useful theoretical and practical implications regarding the diversity, social capital, and performance interpretation of the I-Corps Lab startup team.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.2
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• pp.99-109
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• 2023

Purpose: CT scan makes up for the weak point of the nuclear medicine image having a low resolution and also were used for attenuation correction on image reconstruction. Recently, many studies try to make use of CT images additionally, one of them is to measure the bone mineral density(BMD) using Quantitative CT(QCT) software. BMD exams are performed to scan lumbar and femur with DXA(Dual-Energy X-Ray Absorptiometry) in order to diagnose bone disease such as osteopenia, osteoporosis. The purpose of this study is to identify the usefulness of QCT_BMD analyzed with low dose CT images on L-spine Bone SPECT/CT comparing with DXA_BMD. Materials and Methods: Fifty five women over 50 years old (mean 66.4 ± 9.1) who took the both examinations(L-spine Bone SPECT/CT with SIEMENS Intevo 16 and DXA scan with GE Lunar prodigy advance) within 90 days from April 2017 to July 2022, BMD, T-score and disease classification were analyzed. Three-dimensional BMD was analyzed with low dose CT images acquired on L-spine Bone SPECT/CT scan on Mindways QCT PRO^TM software and two-dimensional BMD was analyzed on DXA scan. Basically, Lumbar 1-4 were analyzed and the patients who has lesion or spine implants on L-spine were excluded for this study. Pearson's correlation analysis was performed in BMD and T-score, chi-square test was performed in disease classification between QCT and DXA. Results: On 55 patients, the minimum of QCT_BMD was 18.10, maximum was 166.50, average was 82.71 ± 31.5 mg/cm³. And the minimum of DXA-BMD was 0.540, maximum was 1.302, average was 0.902 ± 0.201 g/cm², respectively. The result shows a strong statistical correlation between QCT_BMD and DXA_BMD(p<0.001, r=0.76). The minimum of QCT_T-score was -5.7, maximum was -0.1, average was -3.2 ± 1.3 and the minimum of DXA_T-score was -5.0, maximum was 1.7, average was -2.0 ± 1.3, respectively. The result shows a statistical correlation between QCT T-score and DXA T-score (p<0.001, r=0.66). On the disease classification, normal was 5, osteopenia was 25, osteoporosis was 25 in QCT and normal was 10, osteopenia was 25, osteoporosis was 20 in DXA. There was under-estimation of bone decrease relatively on DXA than QCT, but there was no significant differences statistically by chi-square test between QCT and DXA. Conclusion: Through this study, we could identify that the QCT measurement with low dose CT images QCT from L-Spine Bone SPECT/CT was reliable because of a strong statistical correlation between QCT_BMD and DXA_BMD. Bone SPECT/CT scan can provide three-dimensional information also BMD measurement with CT images. In the future, rather than various exams such as CT, BMD, Bone scan are performed, it will be possible to provide multipurpose information via only SPECT/CT scan. In addition, it will be very helpful clinically in the sense that we can provide a diagnosis of potential osteoporosis, especially in middle-aged patients.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• Analytical Science and Technology
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• v.5 no.1
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• pp.41-49
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• 1992

An attempt was made to prepare two series of tetrakis eight-coordinate tungsten(IV) and cerium(IV) complexes containing the 5,7-dichloro-8-quinolinol(N:${\pi}$-acceptor atom, O:${\pi}$-donor atom) ligand. Tetrakis eight-coordinate tungsten(IV) complex of 2-mercaptopyrimidine(N:${\pi}$-acceptor atom, S:${\pi}$-donor atom) ligand have also been prepared. And the new series of mixed-ligand eight-coordinate tungsten(IV) complexes containing bidentate ligands 5,7-dichloro-8-quinolinol and 2-mercaptopyrimidine have been prepared, isolated by TLC and characterized. $W(dcq)_4$, $W(dcq)_3(mpd)_1$, $W(dcq)_2(mpd)_2$, $W(dcq)_1W(dcq)_3$ and $W(mpd)_4$ complexes of MLCT absorption band appeared to 710nm, 680nm, 625nm, 581nm, and 571nm(${\varepsilon}\;max={\sim}>{\times}10^4$) on low-energy respectively. The specific absorption wave length of $Ce(dcq)_4$ is appeared 520nm(${\varepsilon}\;max={\sim}>{\times}10^4$). The Chemical shift values by proton of coordinated position appeared to $W(dcq)_4$ [$H_2:8.9ppm$]; $W(dcq)_3(mpd)_1$ [$H_2:9.3$,$H_6:9.2ppm$]; $W(dcq)_2(mpd)_2$ [$H_2:9.7$,$H_6:8.95ppm$]; $W(dcq)_1(mpd)_3$ [$H_2:9.8$,$H_6:9.4ppm$]; $W(mpd)_4$ [$H_6:8.8ppm$]; $Ce(dcq)_4$ [$H_2:9.3ppm$] with $^1H$-NMR. The inertness of mixed-ligand eight coordinate tungsten(IV) complexes have been investigated by UV-Vis. spectroscopic method in dimethylsulfoxide at $90^{\circ}C$. The inertness of $W(dcq)_n(mpd)_{4-n}$ complexes showed the following order, $W(dcq)_3(mpd)_1;k_{obs.}=3.8{\times}10^{-6}$ > $W(mpd)_4;k_{obs.}=6.0{\times}10^{-6}$ > $W(dcq)_4;k_{obs.}=6.4{\times}10^{-6}$ > $W(dcq)_2(mpd)_2;k_{obs.}=7.0{\times}10^{-6}$ > $W(dcq)_1(mpd)_3;k_{obs.}=1.7{\times}10^{-5}$, which showed the inertness until 16days, 10days, 9days, 8days, and 4days. The $W(mpd)_4$ is very inert as $k_{obs.}=3.6{\times}10^{-6}$(16days) in xylene at $90^{\circ}C$ and $k_{obs.}=6.0{\times}10^{-6}$(10days) in DMSO at $90^{\circ}C$.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.159-165
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• 2010

Purpose: Positron emission tomography scan has been growing diagnostic equipment in the development of medical imaging system. Compare to $^{99m}Tc$ emitting 140 keV, Positron emission radionuclide emits 511 keV gamma rays. Because of this high energy, it needs to reduce radioactive emitting from patients for radiotechnologist. We searched the external dose rates by changing distance from patients and measure the external dose rates when we used shielder investigate change external dose rates. In this study, the external dose distribution were analyzed in order to help managing radiation protection of radiotechnologists. Materials and Methods: Ten patients were searched (mean age: $47.7{\pm}6.6$, mean height: $165.5{\pm}3.8$ cm and mean weight: $65.9{\pm}1.4$ kg). Radiation were measured on the location of head, chest, abdomen, knees and toes at the distance of 10, 50, 100, 150 and 200 cm. Then, all the procedure was given with a portable radiation shielding on the location of head, chest and abdomen at the distance of 100, 150 and 200 cm and transmittance was calculated. Results: In 10 cm, head (105.40 ${\mu}Sv/h$) was the highest and foot (15.85 ${\mu}Sv/h$) was the lowest. In 200 cm, head, chest and abdomen showed similar. On head, the measured dose rates were 9.56 ${\mu}Sv/h$, 5.23 ${\mu}Sv/h$, and 3.40 ${\mu}Sv/h$ in 100, 150 and 200 cm respectively. When using shielder, it shows 2.24 ${\mu}Sv/h$, 1.67 ${\mu}Sv/h$, and 1.27 ${\mu}Sv/h$ in 100, 150 and 200 cm on head. On chest, the measured dose rates were 8.54 ${\mu}Sv/h$, 4.90 ${\mu}Sv/h$, 3.44 ${\mu}Sv/h$ in 100, 150 and 200 cm, respectively. When using shielder, it shows 2.27 ${\mu}Sv/h$, 1.34 ${\mu}Sv/h$, and 1.13 ${\mu}Sv/h$ in 100, 150 and 200 cm on chest. On abdomen, the measured dose rates were 9.83 ${\mu}Sv/h$, 5.15 ${\mu}Sv/h$ and 3.18 ${\mu}Sv/h$ in 100, 150 and 200cm respectively. When using shielder, it shows 2.60 ${\mu}Sv/h$, 1.75 ${\mu}Sv/h$ and 1.23 ${\mu}Sv/h$ in 100, 150 and 200 cm on abdomen. Transmittance was increased as the distance was expanded. Conclusion: As the distance was further, the radiation dose were reduced. When using shielder, the dose were reduced as one-forth of without shielder. The Radio technologists are exposed of radioactivity and there were limitations on reducing the distance with Therefore, the proper shielding will be able to decrease radiation dose to the radiotechnologists.