• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.391-403
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• 2005

Vision is the most important sense of the five senses in our body. This represents that an eye is for the mysterious organ playing the essential role in our body. Alain Mikli known as a famous spectacle designer in France said that glasses exists for seeing and for being seen. This saying is one of the philosophically well-organized definition of the most fundamental function of eye-glasses described in and out of itself. Today, in the world, there are a number of works of glasses design and lots of glasses designers are designing hard in order to convey the goods with the best value and philosophy to customers. They work for the goal that glasses is used as seeing and try to give customers satisfaction and enjoyment of it. And they think that glasses should play the role of the interface. At this point, we need to catch hold of the interface of glasses. That means that glasses has to have the communication between eyes and objects and be the mediation of the connection between the image of oneself and that of one by others. For the character of the interface of glasses, glasses designers should plan and investigate this character at the being of design. This study of optical art has been researched for the necessary and sufficient condition between consumers and products.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.91-95
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• 2004

Several MRI studies have reported reductions in temporal lobe volumes in Alzheimer's disease (AD). Measures have been usually obtained with regions-of-interest (ROI) drawn manually on selected medial and lateral portions of the temporal lobes, with variable choices of anatomical borders across different studies. We used the automated voxel-based morphometry (VBM) approach to investigate gray matter abnormalities over the entire extension of the temporal lobe in 10AD patients (MM5E 22)and 22 healthy controls. Foci of significantly reduced gray matter volume in AD patients were detected in both medial and lateral temporal regions, most significantly in the right and left posterior parahippocarmpal gyri. At a more flexible statistical threshold (P<0.01, uncorrected for multiple comparisons), circumscribed foci of significant gray matter reduction were also detected in the right amygdala/enthorinal cortex, the anterior and posterior borders of the superior temporal gyrus bilaterally, and the anterior portion of the left middle temporal gyrus. These VBM results confirm previous findings of temporal lobe atrophic changes in AD, and suggest that these abnormalities may be confined to specific sites within that lobe, rather than showing a widespread distribution.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.831-845
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• 1997

In this paper,we proposed and developed a compiler and interactive programming enviroments for C++ wich is mostly worth of nitice among the object -oriented languages.To develope the compiler for C++ we took front=end/back-end model using EM virtual machine.In develpoing Front-End,we formailized C++ gram-mar with the context semsitive tokens which must be manipulated by dexical scanner and designed a AST class li-brary which is the hierarchy of AST node class and well defined interface among them,In develpoing Bacik-End,we proposed model for three major components :code oprtimizer,code generator and run-time enviroments.We emphasized the retargatable back-end which can be systrmatically reconfigured to genrate code for a variety of distinct target computers.We also developed terr pattern matching algorithm and implemented target code gen-erator which produce SPARC code.We also proposed the theroy and model for construction interative pro-gramming enviroments. To represent language features we adopt AST as internal reprsentation and propose uncremental analysis algorithm and viseal digrams.We also studied unparsing scheme, visual diagram,graphical user interface to generate interactive environments automatically Results of our resarch will be very useful for developing a complier and programming environments, and also can be used in compilers for parallel and distributed enviroments.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.1-16
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• 2016

In this study, we explore the characteristics of directors' network structure and investigate the relationship among the network of board directors in the Korean logistics industry. Social network analysis reveals hidden patterns of the interlocking directors' network. We construct a directors' network index using social network analysis of the Korean logistics industry. Empirical results have showed that of the 23 companies analyzed, the network index of Korean Air is the highest. The interlocking network index of Korean Air, Hanjin and Hanjin Logistics Company is 0.4, 0.32 and 0.24 respectively. Korean Air has a strong central interlocking network that can create social power through the logistics industry. Our paper contributes to the broad literature in two ways. First, unlike the existing literature on director structure, this paper concentrates on the relationship among interlocking directors. Second, logistics firms need to be aware of the importance of networks and recognize the occurrence of power.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.101-109
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• 2006

Recently, according to the number of internet in widely use and the development of the related application program, the distribution and use of multimedia content(text, images, video, audio etc.) is very easy. Digital signal may be easily duplicated and the duplicated data can have same quality of original data so that it is difficult to warrant original owner. For the solution of this problem, the protection method of copyright which is encipher and watermarking. Digital watermarking is used to protect IP(Intellectual Property) and authenticate the owner of multimedia content. In this paper, the proposed watermarking algerian embeds watermark into multiple lower bitplanes of digital image. In the proposed algorithm, original and watermark images are decomposed to bitplanes each other and the watermarking operation is executed in the corresponded bitplane. The position of watermark image embedded in each bitplane is used to the watermarking key and executed in multiple lower bitplane which has no an influence on human visual recognition. Thus this algorithm can present watermark image to the multiple inherent patterns and needs small watermarking quantity. In the experiment, the author confirmed that it has high robustness against attacks of JPEG, MEDIAN and PSNR but it is weakness against attacks of NOISE, RNDDIST, ROT, SCALE, SS on spatial domain when a criterion PSNR of watermarked image is 40dB.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.619-624
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• 2016

Social-aware video displays not only the relationships between characters but also diverse information on topics such as economics, politics and culture as a story unfolds. Particularly, the speaking habits and behavioral patterns of people in different situations are very important for the analysis of social relationships. However, when dealing with this dynamic multi-modal data, it is difficult for a computer to analyze the drama data effectively. To solve this problem, previous studies employed the deep concept hierarchy (DCH) model to automatically construct and analyze social networks in a TV drama. Nevertheless, since location knowledge was not included, they can only analyze the social network as a whole in stories. In this research, we include location knowledge and analyze the social relations in different locations. We adopt data from approximately 4400 minutes of a TV drama Friends as our dataset. We process face recognition on the characters by using a convolutional- recursive neural networks model and utilize a bag of features model to classify scenes. Then, in different scenes, we establish the social network between the characters by using a deep concept hierarchy model and analyze the change in the social network while the stories unfold.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.649-657
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• 2019

An essential part of the development of an autonomous ship is supporting technology that can effectively check and diagnose the operational status of the ship form the shore control center on land. This development has recently occurred in the shipbuilding and shipping industries. In this paper, we present a smart ship solution that operates, as a single system, a data collection platform that gathers ship operation data and a service platform that provides various services. When this smart ship solution was applied to an operating ship, it was determined that a variety of high-quality data could be collected compared to existing ship data collection systems. In addition, it was shown that of the operation data collected, analysis of parameters related to the main engine can be used to determine the overall state by deriving valid results and visualizing patterns. In conclusion, it was suggested that a ship's operation status could be checked more effectively and a comprehensive evaluation could be possible at the shore control center if the results of this study were extended to various ship equipment and analyzed together with the operational environment data.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.