• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of Distribution Science
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• v.10 no.7
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• pp.33-41
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• 2012

The purpose of this study is to analyse the state of the energy industry and to determine the efficiency of its functioning on the basis of energy conservation principle and application of innovative technologies aimed at improving the ecological modernisation of agricultural sectors of Kazakhstan. The research methodology is based on an integrated approach of financial and economic evaluation of the effectiveness of the investment project, based on calculation of elasticity, total costs and profitability, as well as on comparative, graphical and system analysis. The current stage is characterised by widely spread restructuring processes of electric power industry in many countries through introduction of new technical installations of energy facilities and increased government regulation in order to enhance the competitive advantage of electricity market. Electric power industry features a considerable value of creating areas. For example, by providing scientific and technical progress, it crucially affects not only the development but also the territorial organisation of productive forces, first of all the industry. In modern life, more than 90% of electricity and heat is obtained by Kazakhstan's economy by consuming non-renewable energy resources: different types of coal, oil shale, oil, natural gas and peat. Therefore, it is significant to ensure energy security, as the country faces a rapid fall back to mono-gas structure of fuel and energy balance. However, energy resources in Kazakhstan are spread very unevenly. Its main supplies are concentrated in northern and central parts of the republic, and the majority of consumers of electrical power live in the southern and western areas of the country. However, energy plays an important role in the economy of industrial production and to a large extent determines the level of competitive advantage, which is a promising condition for implementation of energy-saving and environmentally friendly technologies. In these circumstances, issues of modernisation and reforms of this sector in Kazakhstan gain more and more importance, which can be seen in the example of economically sustainable solutions of a large local monopoly company, significant savings in capital investment and efficiency of implementation of an investment project. A major disadvantage of development of electricity distribution companies is the prevalence of very high moral and physical amortisation of equipment, reaching almost 70-80%, which significantly increases the operating costs. For example, while an investment of 12 billion tenge was planned in 2009 in this branch, in 2012 it is planned to invest more than 17 billion. Obviously, despite the absolute increase, the rate of investment is still quite low, as the total demand in this area is at least more than 250 billion tenge. In addition, industrial infrastructure, including the objects of Kazakhstan electric power industry, have a tangible adverse impact on the environment. Thus, since there is a large number of various power projects that are sources of electromagnetic radiation, the environment is deteriorated. Hence, there is a need to optimise the efficiency of the organisation and management of production activities of energy companies, to create and implement new technologies, to ensure safe production and provide solutions to various environmental aspects. These are key strategic factors to ensure success of the modern energy sector of Kazakhstan. The contribution of authors in developing the scope of this subject is explained by the fact that there was not enough research in the energy sector, especially in the view of ecological modernisation. This work differs from similar works in Kazakhstan in the way that the proposed method of investment project calculation takes into account the time factor, which compares the current and future value of profit from the implementation of innovative equipment that helps to bring it to actual practise. The feasibility of writing this article lies in the need of forming a public policy in the industrial sector, including optimising the structure of energy disbursing rate, which complies with the terms of future modernised development of the domestic energy sector.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.101-117
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• 2013

As the number of online game user has been rapidly increased thanks to the recent vitalization of online contents market, not only new business opportunity but also the opportunity to create high profits have been provided as well. However, the increase of the number of online game user and the rapid expansion of the market evoke a cutthroat completion among online game service providers, and also high barriers to entry to online game market have been erected. Thus, what kinds of efforts need for the business success and sales increase in online game market? In lots of researches regarding online contents business, the deepening of loyalty was considered as a critical factor for the business success. According to the study on user's behavior in online environment, users would experience the Flow while using online service, and then, if they were in state of the Flow, they would use the service constantly. High customer loyalty to online game means high will to use the online game too. The purpose of this research was i) to examine what factors enable users to be naturally immersed in online game while playing it, ii) to examine what properties of online game can make game more interesting and exciting, iii) to verify that such factors are critical in deepening customer loyalty, and iv) to suggest some essential factors to be fun and exciting games, on where the focus should be put, and the directionality for the development for sales expansion of online game developer or online game service provider. The research results are as below: First, the involvement and the perceived quality which were characteristics of brand appeared to be factors most affecting Flow. This shows that once game user get interested in online game that user has played frequently, even though new games are released, user will continuously flow the game not moving to new games, and also shows that users not only get more interested but also put more trust in games in the site to where users are frequently going than games in other sites, and consequently user can increasingly flow the game. Second, the compensation and graphics which are the characteristics of contents appeared to be factors affecting Flow. Proper compensation which is given to game users triggers fun and interests in game and makes them flow more and more. And graphics make users to feel game space as if real space and let them flow in game with more reality. Third, challenges, support, and the stability which are technical characteristics appeared to be factors affecting Flow. Challenges enable users to not only experience new virtual world but also solve various difficulties and obstacles. Once users feel fun and interests through this challenge, they can naturally flow games. In addition, the stability of network provides reliability in security and hacking. By doing so, it can induce users to flow more and more. Lastly, when aforementioned characteristics including contents characteristics, technical characteristics, and brand characteristics are organically combined each other, game users feel fun and total minutes are naturally increased, so that game users experience Flow, and consequently the customer loyalty will be deepened as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1288-1298
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• 2002

To implement elliptic curve cryptosystem in GF(2$\^$m/) at high speed, a fast divider is required. Although bit-parallel architecture is well suited for high speed division operations, elliptic curve cryptosystem requires large m(at least 163) to support a sufficient security. In other words, since the bit-parallel architecture has an area complexity of 0(m$\^$m/), it is not suited for this application. In this paper, we propose a new serial-in serial-out systolic array for computing division operations in GF(2$\^$m/) using the standard basis representation. Based on a modified version of tile binary extended greatest common divisor algorithm, we obtain a new data dependence graph and design an efficient bit-serial systolic divider. The proposed divider has 0(m) time complexity and 0(m) area complexity. If input data come in continuously, the proposed divider can produce division results at a rate of one per m clock cycles, after an initial delay of 5m-2 cycles. Analysis shows that the proposed divider provides a significant reduction in both chip area and computational delay time compared to previously proposed systolic dividers with the same I/O format. Since the proposed divider can perform division operations at high speed with the reduced chip area, it is well suited for division circuit of elliptic curve cryptosystem. Furthermore, since the proposed architecture does not restrict the choice of irreducible polynomial, and has a unidirectional data flow and regularity, it provides a high flexibility and scalability with respect to the field size m.

• Management & Information Systems Review
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• v.36 no.5
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• pp.45-60
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• 2017

This study aims to elucidate the key improvements through the current state of customer support for smart home services based on the Internet of things and the evaluation of user's usage. Smart home services typically provide a wide range of value in terms of security, safety, manageability (electricity and water use), convenience, and remote management accessibility. In this study, we analyzed the current state of smart home service based on Internet of Samsung, SKT and LG U + companies in Korea. However, since LG U+ is the only company providing user reviews, there is a limit to generalization, but we are trying to figure out whether the customer value is conveyed properly or not, and in which part the customer support is focused to support the service. As a result of analyzing the results of the study, we found that the smart home service is commercialized and marketed in various forms. However, it is questionable whether the technological level and user satisfaction level are sufficiently satisfied. The results of this study are as follows. First, although each company provides usage guidance, they still ask many questions about joining products and using products. Second, there are many defects in the product itself, and it is found that the companies are not satisfied with the overall response. Third, the three companies are focusing on switches, outlets, sensors, and lamps. This is an individual intelligent product rather than an interlocking or linking level, and it can be seen that there are many parts that are not compatible with the concept of the original Internet of things. In conclusion, this study shows that there are still many areas to improve on the level of customer service provision of smart home service, in particular, the ease of use is low and the quality of products is not reliable. We would like to present the improvement of this in detail through this study and reflect the companies that provide it and the service providers.

• Journal of Legislation Research
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• no.44
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• pp.725-756
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• 2013

In this paper, the possibility of extension of falsification conception was investigated to discuss the validity of this precedent. Consequently this extension was indispensible according to the article 237-2 of criminal code which regards the reproduced document as the document in the document crime. However, this is against the security of human right. On the contrary, there is not this kind of article in the German criminal code and the German precedents and majority theory are negative to regard it as the criminal document. And also, there is the pont of view that the reproduced document is not the criminal document because it's not the expression itself of document nominee's intention, so the article 237-2 should be demolished in Korea. According to this opinion, the serious reconsideration should be required in the legislation of this article 237-2. Nevertheless, if this extended conception is needed and it's possible, the meaning of the computer monitor's image is not able to be ignored in the conception of falsification. Therefore this should be regarded as the element of the falsification conception. In other words, this can't be evaluated as the object of falsification but the target of falsification, according to the conception extension, though the precedents do not regard it as the document in document crime.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Journal of Public Diplomacy
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• v.2 no.2
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• pp.27-52
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• 2022

Objectives: The neighboring countries of South Korea and Japan in Northeast Asia have interacted in both positive and negative ways, at times as close partners and other times adversaries, throughout their long and thorny history of extensive dynamics. The controversial dispute over Dokdo is one of the most critical issues evoking harsh tensions and arguments asserting wholly opposite claims. Dokdo is a small island between two coastal states, but significant in terms of territorial, botanical, and marine resources, and thus ownership of the island has become a point of conflict accompanied by a troubled history. But why has Dokdo been a source of conflicts and how should the controversial Dokdo issue be addressed in a way that fosters positive influence and co-prosperity? Methods: This study provides comprehensive and critical insights from a wealth of previous research and strategic suggestions for the Korean government. It utilizes the three perspectives of historical documents and political context, international regulations and legal frames, and public diplomacy. Furthermore, it applies these resources to negotiation theories and strategies to propose reasonable solutions. Results: This study suggests that it is important for Korea and Japan to try to build mutual trust through more active communication and interaction in order to understand each other before attempting to create a formal resolution via negotiation. In addition to these efforts, Korea needs to be ready for the inevitable need to take decisive action in terms of negotiation, using analytic and efficient strategies. The study proposes three solutions: 1) Strong Action Strategy, 2) International Legal Strategy, and 3) Public Diplomacy Strategy. Conclusions: From the perspective of public diplomacy, the Dokdo issue needs to be converted from a symbol of conflicts between Korea and Japan into a symbol of peace and co-prosperity. In addition to promoting a positive relationship between the two states, it can also contribute to the security environment of the Northeast Asian region and global peace.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.