Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the “drone” keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI’s power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

This study examines and proposes standardization approaches to address the heterogeneous issues of metadata in drone imagery within the agricultural sector. Image metadata comes in various formats depending on different camera manufacturers, with most utilizing EXIF and XMP. The metadata of cameras used in fixed-wing and rotary-wing platforms, along with the metadata requirements in image alignment software, were analyzed for sensors like DJI XT2, MicaSense RedEdge-M, and Sentera Double4K. In the agricultural domain, multispectral imagery is crucial for vegetation analysis, making the provision of such imagery essential. Based on Pix4D SW, a comparative analysis of metadata attributes was performed, and necessary elements were compiled and presented as a proposed standardization (draft) in the form of tag information.

At a time when the demand for drones is increasing, a plan to utilize drone images was sought for efficient promotion of cadastral resurvey. To achieve the purpose of this study, the technical and legal status of drone images was reviewed, and through this, the possibility of using it for cadastral resurvey was primarily reviewed. subsequently, an experiment was conducted targeting the project district to examine whether drone images were applied to boundary extraction, which is the primary process of cadastral resurvey. As a result of the experiment, it was found that boundary extraction from images is possible. However, in some cases, it is impossible due to field conditions or image quality. Therefore, it is necessary first to apply cases where boundary extraction is possible to cadastral resurvey and seek solutions for some impossible cases. In particular, the image quality problem may have problems with the current technology, but it will also have problems with the existing drone equipment. So, standard for drone calibration should also be established. Finally, the cadastral resurvey surveying procedure using drones was also presented.

Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.

Explainable AI (XAI) is an approach that leverages artificial intelligence to support human decision-making. Recently, governments of several countries including Korea are attempting objective evidence-based analyses of R&D investments with returns by analyzing quantitative data. Over the past decade, governments have invested in relevant researches, allowing government officials to gain insights to help them evaluate past performances and discuss future policy directions. Compared to the size that has not been used yet, the utilization of the text information (accumulated in national DBs) so far is low level. The current study utilizes a text mining strategy for monitoring innovations along with a case study of smart-farms in the Honam region.

Recently the meaning of the road name address is expended as an information through the revision of the Road Name Address Act. As this revision, the address of things (AoT) become more important indicating the possibility for the expansion to the related business. However, recent study about AoT does not concern how the current priority system works from the first research. In this study, we analyze perception about addressable object between AoT experts and public using AHP analysis. We structured the importance of addressable objects as two categories; urgency and value creation. The necessity in emergency or daily, accessibility and welfare conform the urgency index. Meanwhile, public value creation in public domain or profitability in the business area and economics conform value creation index. We conducted survey for total of 89 of experts and public. The results of this study indicate the relative importance of AoT measured by experts and public. Generally, public tend to concern more about accessibility conforming the urgency index than experts. Moreover, the public WiFi and the sports complex scored the high priority among the remain addressable objects, in respect of the urgency and the value creation. This result could be implemented for the activation of the smart city industry base on the geospatial information including AoT.

Smart City operates with the purpose of solving urban problems. The important thing in smart city operation is that spatial information must be managed at a high level. In addition, it has the characteristics of being managed by one platform. This study presented the core value dimension of smart city based on analysis of various domestic and overseas smart city operation cases. Smart cities are basically operated based on spatial information, and the higher the level of spatial information, the more smart city services can be connected and managed in an integrated manner. The performance dimension of smart city core values presented in the study includes prosperity, personalization, convenience, accuracy, sustainability, safety, environment, integration, etc., and there is a connectivity dimension, a concept that can be managed in an integrated manner. This study will be useful for empirical research on smart city performance dimension design and surveys based on case studies. It will also help field managers who develop, operate, and manage smart cities when quantifying performance dimensions.

Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users’ needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30’s, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

In this paper, we compared the efficiencies of national R&D investments between NT (Nanotechnology) areas in terms of papers, patents, and commercializations, and found ways to improve the efficiencies of national R&D investments for each NT area. This is in response to huge R&D investments government has made recently in NT areas.Here, we collected data on investments, papers, patents, and commercializations for the R&D projects in NT areas through National Science & Technology Information Service. Based on the data, we analyzed the investment and performances (papers, patents, and commercializations) for each NT area, calculated the efficiency for each NT area, and compared the efficiencies between NT areas. Next, using cluster analysis, we identified several NT areas with similar characteristics in terms of paper efficiency, patent efficiency and commercialization efficiency. Finally, we derived implications for the efficiency enhancement for each grouping.The cluster analysis showed that there could be two groups, one being low in terms of technological outcome (papers and patents) efficiencies and high in terms of commercialization efficiencies, while the other being high in terms of technological outcome (papers and patents) efficiencies and low in terms of commercialization efficiencies. Therefore, the strategy for one group calls for support for technology transfer or technology introduction from other R&D performers and grant of guidance for improving R&D performers’ commercialization ability to other R&D performers while the strategy for the other group calls for R&D support for transfer of technology to other R&D performers, activation of technology transfer and support for commercialization of R&D performers.

Recently, nanotechnology has grown as one of the leading science technology along with other converging technologies such as biology, information, medicine etc., bringing the continuous investment of the government in nano-related field. However, it is difficult to measure and evaluate the performance of the national research and development programs because of the multidimensional character of the expected outcomes. This study aims to measuring efficiency of the national nanotechnology research and development programs using DEA model. The decision making units are nine nano-related ministries including the Ministry of Science, ICT and Future Planning. The input variables are total expenditure, number of the programs and average expenditure per program. The output variables are science, technology and economic indicator, and the combination of these outputs are respectively measured as seven different DEA cases. The Ministry of Science, ICT and Future was the first efficient ministry in total technical efficiency. Ministry of Agriculture, Food and Rural Affairs and the Ministry of Food and Drug Safety were efficient in pure technical efficiency, when the Ministry of Commerce Industry and Energy took the first in the scale efficiency. The program efficiency was affected by organizational characteristics such as the institution’s scale, the concentration of the research paper or the patent, technology transfer or the commercialization. The result of this study could be utilized in development of the policy in the nanotechnology and the related field. Furthermore, it could be applied for the modification of expenditure management or the adjustment of the research and development programs’ input and output scale for each ministry.

Nanotechnology has been growing constantly and it is becoming the leading technology in scientific research and development. Although nanotechnology has important applications in broad variety of fields without boundary of any particular industrial area, the study of nanotechnology related to its commercialization has been conducted in a few ways. To put that figure in context, this study investigates public and expert perceptions about negative potentials of nanotechnology. Through a series of surveys with public (N = 541) and experts (N = 62), we analyzed about public willingness to pay for nano-applied products. Survey results showed that public and experts preferred nano-applied products in the order of electronics, cosmetics, and food and medicine. Experts express high payment intention to electronics rather than public intention. In addition, the survey results showed the purchasing intention of both public and expert group was affected by the attributes of nano-applied products in the order of risk fatality, risk chance, certification, and labeling. But experts put more importance in risk fatality than risk chance comparing to public. Through the case analysis of the effects of labeling and certification, we revealed either labeling or certification can induce both public and experts to buy the nano-applied products with high risk chance and low risk fatality. However, for the nano-applied product with high risk fatality and low risk chance, both labeling and certification are simultaneously required to make customers have positive purchasing intention. The result of this study could be utilized for the nanotechnology-based company to get the consumer behavior information about nano-based product and to establish their marketing strategy.

The study aims at quantifying the effect of nano technology in the fields of economics and social aspects by using the methodology of system dynamics. A case study which using selenium oxide nanoparticles as additive agent in order to enhance fuel efficiency was selected as an example of nano technology in economic and societal benefits. Additionally, models for exhaust gas from combustion of fuel (diesel) and related issues are developed to evaluate real-time assessment of the effect of nano technology. It was found that the selenium oxide nanoparticles increase fuel efficiency, and it also affects on the amount of exhaust gas and the respiratory disease related issues. The results of this study which give quantitative value for the effect of nano technology can be used as objective references in development of national policy.

It is difficult to make an accurate estimate of the economic value and effects on societal economy of Nano-technologies. This research measures an economic value of Nano-technologies quantitatively and analyzes its influences on societal economy. This paper chooses some major industries as analysis targets and adapts the DEFRA comparative methodology model which has been developed in the UK and recommended by OECD. For this reason, some industries which are in range of economic value assessment were investigated and related data were collected. Also, the economic value and societal influences of Nano-technologies were calculated, through the procedure of the model. In addition, this study conducts a questionnaire to experts for the validity of measurement results and procedures. This paper suggests a guideline for economic value and effects on societal economy of Nano-technologies assessments through quantitative Defra comparative methodologies.

This study was conducted to investigate the variation of growth characteristics and reproductive physiology in cloned Hanwoo male calves during growing stage. The hematological parameters, body weight, and plasma hormonal levels, birth to 12 months, were analyzed in the cloned calves (n=3). Differences among treatment means were determined by a student t-test. A probability of P<0.05 was considered statistically significant. The hematological parameters, such as white blood cell, red blood cell, and platelet, were not different in both normal and cloned calves. The difference of body weight, however, was significantly higher in the cloned calves, months (p<0.05) and months (p<0.01), than that of the comparators, respectively. The plasma IGF-1 level was statistically significant in the cloned calves, months, compared to that of the normal calves (p<0.05). However, the plasma testosterone level was not different in both normal and clone calves according to growing stage. Taken together, the cloned Hanwoo male calves are growing faster and maintaining a normal reproductive physiology.

This study was performed to identify and analyze the specifically expressed plasma proteins during early pregnancy in both pregnant and non-pregnant Hanwoo. Blood samples were collected at 0 (the day of AI), 2, 3, 4, 7, and 11 weeks after AI from pregnant (n=3) and non-pregnant (n=4) Hanwoo, respectively. The hematological parameters were measured. After 2-dimensional electrophoresis using serum, normalized protein spots were selected for the significant expression variation deviated over two fold in its expression level between two groups. Among 17 spots selected, 15 were identified as albumin, IgG1 heavy chain constant region, haptoglobin, ferrochelatase, fibrinogen, hemopexin. 5 spots were expressed only in non-pregnant specific. The spot identification of 1105 and 6106 was decreased after 3 weeks from AI. However, 2/17 spots were still unidentified. Further studies are needed to analyze the function of the proteins associated with early pregnancy.

본 연구는 체세포를 이용하여 생산된 복제 한우 수소의 번식능력을 검토하기 위해 실시하였다. 복제 한우 수소(C-38 및 C-39) 또는 일반 한우 종모우로부터 정액을 채취하여 정자의 수 및 동결 전후의 생존성 등을 살펴보았으며, 정자의 운동성 등은 computer assisted sperm analysis(CASA)를 이용하여 측정하였다. 또한, 이들의 수정 능력을 확인하기 위하여 체외수정과 인공수정을 각각 실시하였다. 정액 성상에서는 복제 수소들과 일반 종모우 간에 정액의 양, 정자의 농도 및 동결융해 후의 생존성 등에서 차이가 나타나지 않았다. CASA를 이용한 분석에서 운동성, 곡선 운동 속도(VCL), 직선 운동 속도(VSL) 및 평균 진행 속도(VAP) 등은 복제 수소의 정액이 일반 종모우의 정액에 비하여 유의적으로 높았다(p<0.05). 체외수정에 따른 수정란의 분화율 및 배반포로의 발달율은 복제 수소와 일반 종모우 간에 차이가 나타나지 않았다. 복제소 정액(C-38)을 이용하여 인공수정을 한 5두의 체세포 복제 대리모에서 암수 각각 한 두씩의 건강한 복제 후대 송아지 2두를 생산하였다. 이상의 결과를 종합하여 보면, 실험에 공시된 복제 수소 개체 간의 차이가 나타나기는 하였지만, 복제 수소는 정액 성상과 정자의 운동성 등에서 일반 종모우와 차이가 없었으며. 또한 인공수정을 통해 송아지를 생산함으로써 정상적인 번식능력이 있음을 확인하였다.