• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.175-181
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• 2024

The U.N. Security Council's North Korea Sanctions Committee estimated that the amount of North Korea's cyberattacks on virtual asset-related companies from 2017 to 2023 was about 4 trillion won. North Korea's cyberattacks have secured funds through cryptocurrency hacking as it has been restricted from securing foreign currency due to economic sanctions by the international community, and it also shows the form of technology theft against defense companies, and illegal assets are being used to maintain the Kim Jong-un regime and develop nuclear and missile development. When North Korea conducted its sixth nuclear test on September 3, 2017, and declared the completion of its national nuclear armament following the launch of an intercontinental ballistic missile on November 29 of the same year, the U.N. imposed sanctions on North Korea, which are considered the strongest economic sanctions in history. In these difficult economic situations, North Korea tried to overcome the crisis through cyberattacks, but as a result of analyzing the changes through the North's cyber attack cases, the strategic goal from the first period from 2009 to 2016 was to verify and show off North Korea's cyber capabilities through the neutralization of the national network and the takeover of information, and was seen as an intention to create social chaos in South Korea. When foreign currency earnings were limited due to sanctions against North Korea in 2016, the second stage seized virtual currency and secured funds to maintain the Kim Jong-un regime and advance nuclear and missile development. The third stage is a technology hacking of domestic and foreign defense companies, focusing on taking over key technologies to achieve the five strategic weapons tasks proposed by Chairman Kim Jong-un at the 8th Party Congress in 2021. At the national level, security measures for private companies as well as state agencies should be established against North Korea's cyberattacks, and measures for legal systems, technical problems, and budgets related to science are urgently needed. It is also necessary to establish a system and manpower to respond to the ever-developing cyberattacks by focusing on cultivating and securing professional manpower such as white hackers.

• Therapeutic Science for Rehabilitation
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• v.13 no.3
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• pp.51-67
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• 2024

Objective : This study investigated trends in the use of assessment tools by occupational therapists working with adults and older adults. Methods : Occupational therapists were surveyed to gather data on general characteristics, assessment tool usage, assessment time and frequency, usage trends by area, and education. The tools were categorized by the Occupational Therapy Practice Framework (OTPF) into Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), and play and leisure for occupations, and cognitive functions, motor functions, and psychosocial aspects for client factors. Data from 98 respondents were analyzed using frequency analysis and one-way ANOVA with SAS. Results : Most surveyed occupational therapists worked in university or general hospitals (40.82%). The assessment time per patient was under 30 min (62.25%), and re-assessment frequency was one~three months (68.38%). The most frequently used assessment tools by the OTPF were as follows: ADL: Modified Barthel Index (94.90%), IADL: Canadian Occupational Performance Measure (31.63%), cognitive functions: Mini-Mental Status Examination (89.80%), visual perception: Motor-free Visual Perception Test (56.12%), dementia: Global Deterioration Scale (63.27%), motor functions: Jamar Dynamometer & Pinch Gauge (59.18%), dysphagia: Video Fluoroscopic Swallowing Study (28.57%), physical examination: Range of Motion (59.18%), and psychosocial: Geriatric Depression Scale (33.67%). Conclusion : This study identified the use and rationale of assessment tools for occupational therapy in adults and older adults. These findings aim to enhance the curriculum and continuing education of occupational therapists.

• Journal of Nutrition and Health
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• v.57 no.4
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• pp.451-467
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• 2024

Purpose: This study aimed to develop a four-hour food additive education program for elementary school students to provide them with accurate information on food additives. Methods: A survey was conducted among 133 elementary school students living in Gyeonggi Province to identify the level of food additive awareness. A four-hour food additive education program and educational materials (PPT, activity sheets, and teacher guidelines) were developed based on the results of the food additive awareness survey. The developed educational programs were based on the Theoretical Model of Stages of Behavior Change. An elementary school nutrition teacher conducted a pilot education for 83 elementary school students to evaluate the feasibility of the developed education program. A survey was conducted to evaluate the effectiveness and satisfaction of the pilot education program. Results: The results of the Food Additive Awareness Survey showed that only 42.1% of people were aware of food additives; 46.3% wanted to know more about food additives, and 54.3% required food additive education. Food coloring (44.7%) and artificial sweeteners (18.7%) were the most common food additives of interest. What they wanted to know about food additives was the safety of food additives (36.8%) and the role and function of food additives (20.3%). After the pilot training on food additives, the level of awareness of food additives was improved significantly, and the percentage of participants who recognized the need for food additive education and promotion increased. According to the satisfaction survey of the food additives education, the interest, understanding, real-life application, learning method, and content amount were approximately 90%. Conclusion: The educational program developed through this study will change the negative perceptions of food additives in elementary school students to a positive one. It will do so by helping nutrition educators educate students on this important subject.

• Microbiology and Biotechnology Letters
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• v.52 no.3
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• pp.255-263
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• 2024

In this study, antioxidant and anti-inflammatory activity was studied to confirm the value of kailan (Brassica oleracea L.) as a natural material for cosmetics. For this study measure the antioxidative activity, total polyphenol content was measured, and DPPH and ABTS scavenging activity assays were conducted. As a result of measuring the total polyphenol content of hot water extract of kailan (KRD) and 70% ethanol extract of kailan (KRE), it was found to contain 124.3 mg TAE/100 g and 144.1 mg TAE/100 g, respectively. As a result of DPPH and ABTS radical scavenging ability, it was confirmed that the efficacy was concentration dependent. After treating the cells with LPS, a stimulant, for 2 hours, an experiment was conducted by treating RAW 264.7 cells with KRD and KRE at concentrations of 10, 50, and 100 ㎍/ml. The nitric oxide production inhibitory activity of KRD and KRE showed an inhibitory effect of about 30% at a concentration of 100 ㎍/ml. Cells cultured for 18 hours after stimulant treatment were obtained and used in experiments. The cells obtained in this way were lysed, protein and mRNA were extracted, and the expression of inflammatory mediators' inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) was confirmed. It was confirmed that the protein mRNA expression of iNOS and COX-2, measured through western blot and reverse transcription-PCR, was inhibited in a concentration-dependent manner. Based on this, it is judged that has the potential to be used as a natural material in cosmetics.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Journal of the Korean Society of Food Culture
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• v.32 no.5
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• pp.383-393
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• 2017

This study was conducted to analyze the dietary lifestyle of local Chinese consumers and to classify dietary characteristics according to their dietary lifestyle factors and dietary behaviors. This investigation was conducted for 1 month from 1 January 2017 targeting 300 adult males and females living in China using the online survey company surveymonkey. Four factors relating to dietary lifestyle were identified, gourmet factor, healthy factor, convenience factor and economic factor, and these were grouped into 4 clusters according to their dietary lifestyle factor scores. Group 1, the gourmet economy group, showed a high percentage of living alone and a high frequency of eating out, but a relatively low percentage of three regular meals per day. Their dietary lifestyle was sensitive to gourmet factors and economic factors, but less sensitive to health and convenience factors. Group 2, the wide interest group, contained a high percentage of individuals in their 30s, as well as more highly educated individuals and a higher income than other groups. Because their dietary lifestyle scores tended to be higher than those of other groups, they sought a variety of new foods and gourmet meals for enjoyment of dining and life, as well as well-being food materials and foods related to health. Group 3, the health economic group, constituted a family-type consumer group with lower income level than the other groups. Members of this group were seeking health food and natural food in their dietary lifestyle and tended to pursue a high economic profit ratio when purchasing food. Finally, group 4 showed a relatively higher percentage of women over 30 and individuals with a college level or higher education than the other groups. This group was more interested in health and taste than price and convenience, and showed the highest LOHAS orientation among middle aged Chinese women. Moreover, members of this group directly utilized their knowledge regarding nutrition in real life.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.54-59
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• 2017

Purpose The present study aimed at assessing the effectiveness of the respiratory gating method used in the flow mode and additional localized respiratory-gated imaging, which differs from the step and go method. Materials and Methods Respiratory gated imaging was performed in the flow mode to twenty patients with lung cancer (10 patients with stable signals and 10 patients with unstable signals), who underwent PET/CT scanning of the torso using Biograph mCT Flow PET/CT at Bundang Seoul University Hospital from June 2016 to September 2016. Additional images of the lungs were obtained by using the respiratory gating method. SUVmax, SUVmean, and Tumor Volume ($cm^3$) of non-gating images, gating images, and additional lung gating images were found with Syngo,bia (Siemens, Germany). A paired t-test was performed with GraphPad Prism6, and changes in the width of the amplitude range were compared between the two types of gating images. Results The following results were obtained from all patients when the respiratory gating method was applied: $SUV_{max}=9.43{\pm}3.93$, $SUV_{mean}=1.77{\pm}0.89$, and $Tumor\;Volume=4.17{\pm}2.41$ for the non-gating images, $SUV_{max}=10.08{\pm}4.07$, $SUV_{mean}=1.75{\pm}0.81$, and $Tumor\;Volume=3.56{\pm}2.11$ for the gating images, and $SUV_{max}=10.86{\pm}4.36$, $SUV_{mean}=1.77{\pm}0.85$, $Tumor\;Volume=3.36{\pm}1.98$ for the additional lung gating images. No statistically significant difference in the values of $SUV_{mean}$ was found between the non-gating and gating images, and between the gating and lung gating images (P>0.05). A significant difference in the values of $SUV_{max}$ and Tumor Volume were found between the aforementioned groups (P<0.05). The width of the amplitude range was smaller for lung gating images than gating images for 12 from 20 patients (3 patients with stable signals, 9 patients with unstable signals). Conclusion In PET/CT scanning using the respiratory gating method in the flow mode, any lesion movements caused by respiration were adjusted; therefore, more accurate measurements of $SUV_{max}$, and Tumor Volume could be obtained from the gating images than the non-gating images in this study. In addition, the width of the amplitude range decreased according to the stability of respiration to a more significant degree in the additional lung gating images than the gating images. We found that gating images provide information that is more useful for diagnosis than the one provided by non-gating images. For patients with irregular signals, it may be helpful to perform localized scanning additionally if time allows.