• Proceedings of the Korea Technology Innovation Society Conference
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• 2015.05a
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• pp.545-570
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• 2015

Korea is among the ten countries with the largest R&D budget and the highest R&D investment-to-GDP ratio, yet the subject of security and protection of R&D results remains relatively unexplored in the country. Countries have implemented in their legal systems measures to properly protect cutting-edge industrial technologies that would adversely affect national security and economy if leaked to other countries. While Korea has a generally stable legal framework as provided in the Regulation on the National R&D Program Management (the "Regulation") and the Act on Industrial Technology Protection, many difficulties follow in practice when determining details on security management and obligations and setting standards in carrying out national R&D projects. This paper proposes to modify and improve security level classification standards in the Regulation. The Regulation provides a dual security level decision-making system for R&D projects: the security level can be determined either by researcher or by the central agency in charge of the project. Unification of such a dual system can avoid unnecessary confusions. To prevent a leakage, it is crucial that research projects be carried out in compliance with their assigned security levels and standards and results be effectively managed. The paper examines from a practitioner's perspective relevant legal provisions on leakage of confidential R&D projects, infringement, injunction, punishment, attempt and conspiracy, dual liability, duty of report to the National Intelligence Service (the "NIS") of security management process and other security issues arising from national R&D projects, and manual drafting in case of a breach. The paper recommends to train security and technological experts such as industrial security experts to properly amend laws on security level classification standards and relevant technological contents. A quarterly policy development committee must also be set up by the NIS in cooperation with relevant organizations. The committee shall provide a project management manual that provides step-by-step guidance for organizations that carry out national R&D projects as a preventive measure against possible leakage. In the short term, the NIS National Industrial Security Center's duties should be expanded to incorporate national R&D projects' security. In the long term, a security task force must be set up to protect, support and manage the projects whose responsibilities should include research, policy development, PR and training of security-related issues. Through these means, a social consensus must be reached on the need for protecting national R&D projects. The most efficient way to implement these measures is to facilitate security training programs and meetings that provide opportunities for communication among industrial security experts and researchers. Furthermore, the Regulation's security provisions must be examined and improved.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.141-148
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• 2022

The development of the education system and the labor market today requires new conditions for unification and functioning, the introduction of an innovative culture in the field of Education. The construction of modern management of innovative development of a higher education institution requires consideration of the existing theoretical, methodological and practical planes on which its formation is based. The purpose of the article is to substantiate the modern paradigm of organizing the mechanism of managing the innovative development of higher education institutions. Innovation in education is represented not only by the final product of applying novelty in educational and managerial processes in order to qualitatively improve the subject and objects of management and obtain economic, social, scientific, technical, environmental and other effects, but also by the procedure for their constant updating. The classification of innovations in education is presented. Despite the positive developments in the development of Education, numerous problems remain in this area, which is discussed in the article. The concept of innovative development of higher education institutions is described, which defines the prerequisites, goals, principles, tasks and mechanisms of university development for a long-term period and should be based on the following principles: scientific, flexible, efficient and comprehensive. The role of the motivational component of the mechanism of innovative development of higher education institutions is clarified, which allows at the strategic level to create an innovative culture and motivation of innovative activity of each individual, to make a choice of rational directions for solving problems, at the tactical level - to form motives for innovative activity in the most effective directions, at the operational level - to monitor the formation of a system of motives and incentives, to adjust the directions of motivation. The necessity of the functional component of the mechanism, which consists in determining a set of steps and management decisions aimed at achieving certain goals of innovative development of higher education institutions, is proved. The monitoring component of the mechanism is aimed at developing a special system for collecting, processing, storing and distributing information about the stages of development of higher education institutions, prediction based on the objective data on the dynamics and main trends of its development, and elaboration of recommendations.

• Journal of Distribution Science
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• v.14 no.1
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• pp.85-91
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• 2016

Purpose - Recently, the importance of rapid change in business models is more and more increasing as the change of information technology environment. Therefore, a variety of business models have emerged. On the other hand, there is no company that can generate revenue. Many enterprises are still maintained while they are changing only their appearance of the business model. Business model is important in e-commerce. However, a lot of researches are targeted only in Web sites. Thus, e-commerce companies do not have the infrastructure for measuring and business models. The purpose of paper is to evaluate factors which are related with the structuring of the e-commerce success. And it proposed a financial items and non-financial items. From the perspectives of administrators and managers, the paper researches the possibility for E-Commerce Evaluation Model as a valuable criteria in measuring business model. Research design, data and methodology - The methods are taken by the classification for the type of business-to-business transactions, transactions subject, and the degree of integration and innovation capabilities. Financial and Non-financial value is used to build E-Commerce Evaluation Model. Evaluation items in Administration's perspective are composed with enhance the effectiveness of the mission, improving efficiency of the administration, and control of costs. Evaluation items in the customer's perspective were measured by customer participation and cooperation with customer Satisfaction. In the case of researching the information system's perspective, three criteria are used such as adequacy of the development process, improvement of the quality of service, and maintenance of standardized information technology. In researching for the ICT competence's perspective, evaluation items were composed of enhanced user capabilities, utilizing new technologies, and empowerment of information workers. Results - In this paper, E-Commerce Evaluation Model with financial and non-financial perspectives shows the possibility to be criteria in the case of measuring business model. Moreover, it gives the positive expectation to be successful criteria. But the research may have ambiguity in its essential concept because it cannot avoid the limitation in selecting evaluation tools from merely the model. It is impossible to exclude the possibility in omitting specific properties which may take place in actual case study. Therefore, In hereafter research, it is necessary to include actual case study research in selecting evaluation tools in order to improve the limit point. Actual measurement items which are derived from actual case study should be subdivided, and it would be more effective to complete the research. Conclusions - In rapid change in business models, there are various kinds of business models. But it is general situation that companies which adopted business models have not brought in revenue. For this reason, E-Commerce Evaluation Model is needed as an important factor for the structuring of the e-commerce success. Although it has the limitation in selecting evaluation tools from model, E-Commerce Evaluation Model proposes the implication for measuring business models as a valuable criteria.

• 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 Distribution Science
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• v.14 no.5
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• pp.97-106
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• 2016

Purpose - Social commerce is a certain way of how people buy some products together with others through the internet sites with mutual interactions among customers with the benefits of SNS when buying some products. At present, China market has some problems due to its rapid growing. However, empirical research or academic approach to social commerce has not been made enough. So, it is important for Chinese social market to develop and enlarge the customers with stability under the reliability and satisfaction. Also it is important for them to have repurchase intention. Nowadays, it is necessary to find the factors on customer satisfaction and trust, whereas consumers' dissatisfaction and unreliability are increasing on social commerce recently. In addition, researches on social commerce have been actively pursued by a variety of domestic and foreign scholars. However, researches on social commerce and Chinese market are short of, and they have some limitations because of the rapid growth of the market even though it is the early stage. The current situation requires researches on consumers' repurchase intention for continuing growth in the future according to the growth of Chinese social commerce. Research design, data, and methodology - The literature and the empirical studies are combined in order to achieve the purpose of the study. Deriving social commerce features and consumer properties as factors affecting the repurchase intention through the literature, and these factors have modeled a series of assumptions about the impact on satisfaction and trust, and have established hypotheses to verify them. The survey which is conducted to test the hypothesis and questionnaires are derived based on the variables discussed in the previous study. Appropriate measures were developed and tested on 227 respondents in China with a cross-sectional questionnaire survey. The path relationships of the research model were analyzed by SPSS 23.0 and Amos 23.0. Results - Research results about social commerce characteristics and factors affecting the repurchase intention are presented to Chinese market companies that adopt business models and consumer characteristics. In addition, this study focuses on the characteristics of social commerce, from two-dimensional characteristics of the consumer satisfaction, trust and the impact on the repurchase. Therefore, social commerce features and consumer properties based on the results of this study may lead the strategic implications that may increase the repurchase intention. Conclusions - The classification reviewing the previous findings related to social commerce and social commerce features affects social commerce repurchase (price discount, interactivity) and consumer characteristics (impulsivity, innovation, collectivism). It affects repurchase on factors and analyzes empirically. The empirical results identify major characteristics (social commerce characteristics, attributes) that affect the repurchase intention, and give the practical implications as well as the business strategies that are able to enhance social commerce repurchase consumers. Social commerce is a certain way of how people buy some products together with others through the internet sites with mutual interactions among customers with the benefits of SNS when buying some products.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.137-157
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• 2023

The scale of research and development (R&D) investment is increasing to strengthen national competitiveness through technological innovation, leading to an increased interest in investment efficiency. In records management, the National Archives of Korea has been leading the national research and development project since 2008. Accordingly, this study analyzed R&D projects in records management regarding implementing organization, performance or outcomes, and subjects, targeting 111 National Archives of Korea contract research projects from 2008 to 2022. The analysis showed that small and medium-sized enterprises (SMEs) were the most likely to conduct research, the majority of the research outcomes were academic publications, and there were some discrepancies between the reported performance in research and the actual performance. In terms of research subjects, the most common type of records are paper or print documents, establishing an electronic management system among the National Archives' works. In terms of the frequency of keywords in the records management process and research projects, it was found that research was mainly conducted on "preservation." Meanwhile, only 10 cases, or 9% of the 111 projects, were found to be relevant in terms of utilizing big data and developing intelligent technologies related to digital transformation. Therefore, the effectiveness of the R&D project must be improved through follow-up management of the results even after the research project is completed. In addition, in terms of research topics, it was identified that aside from "preservation," studies focusing on "transfer," "classification," "evaluation," and "collection," as well as research that responds to digital transformation, are needed.

• Journal of the Korean earth science society
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• v.41 no.1
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• pp.31-39
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• 2020

Cheonji, the largest caldera lake in Asia, is located at the summit of Baekdu Mountain. Cheonji is covered with snow and ice for about six months of the year due to its high altitude and its surrounding environment. Since most of the sources of water are from groundwater, the water temperature is closely related to the volcanic activity. However, in the 2000s, many volcanic activities have been monitored on the mountain. In this study, we analyzed the dimension of ice produced during winter in Baekdu Mountain using Sentinel-1 satellite image data provided by the European Space Agency (ESA). In order to calculate the dimension of ice from the backscatter image of the Sentinel-1 satellite, 20 Gray-Level Co-occurrence Matrix (GLCM) layers were generated from two polarization images using texture analysis. The method used in calculating the area was utilized with the Support Vector Machine (SVM) algorithm to classify the GLCM layer which is to calculate the dimension of ice in the image. Also, the calculated area was correlated with temperature data obtained from Samjiyeon weather station. This study could be used as a basis for suggesting an alternative to the new method of calculating the area of ice before using a long-term time series analysis on a full scale.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• Korean Journal of Construction Engineering and Management
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• v.18 no.4
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• pp.27-35
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• 2017

Based on Income-approach, this study develops the evaluation model which reflects construction industry's traits. Using Income approach, we derive future income's present value and evaluates the technological value by contribution to future income. As there exist more random variables in construction technology than in standardized manufactured products, we cannot help relying on not only quantitative estimation method but also qualitative evaluation by technology and market experts when we estimates construction technology value. Also, conservative estimation is needed for discount rate and cash-flow estimation, because of high uncertainty in sales and profits in construction industry. In empirical analysis, we applied economic periods of duration and cash-flow based on the standard guideline, and analyzed discount rate and technology factor based on characteristics of construction industry. The discount rate is estimated to 15% because of risk-premium increase by conservative evaluation. Technology factor is estimated to 46.7%, because technological intensity is estimated to 72% by technological superiority. Such implications can be inferred. Firstly, we need to build a database to diversify categories for division of sectors by activity or industrial classification which is now categorized only by two sectors in standard guideline. Secondly, the roles of experts who participate in technology evaluation are important because of volatility of construction technology.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.2
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• pp.137-143
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• 2016

The sedimentary environment and sediment were surveyed at the West-Northern site of Chagwi-do nearby Jeju Island for the design of the embedded suction anchor system of 10 MW-class floating wave-offshore wind hybrid power generation system. According to the classification scheme of Chough et al.[2002], the echo type of the seismic profiles using the chirp III was classified. As a results, the center and west-northern area of survey site were proved to be type I-3 where subbottom layer with thickness 5~15 m exists under the flat seafloor. On the other hands, the east-southern area were regarded to be type I-1, I-2 and III-1 where seafloor reflection is much stronger than type I-3. Also, the physical tests (unit weight, moisture content, grain size, liquid limit, specific gravity) were performed with samples taken from 8 fixed locations. It is found that the sand (SP), the sand blended with silt (SM) and the mixture of SP-SM are distributed uniformly on the survey area.