• Journal of Information Processing Systems
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• v.19 no.2
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• pp.189-202
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• 2023

In the era marked by information inundation, social network analysis is the most important part of big data analysis, with clique detection being a key technology in social network mining. Also, detecting maximal balance clique in signed networks with positive and negative relationships is essential. In this paper, we present two algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using the improved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). The second one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency of memory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.25-34
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• 2024

The paper investigates how the semiconductor and electric vehicle industries are addressing safety and security concerns in the era of autonomous driving, emphasizing the prioritization of safety over security for market competitiveness. Collaboration between these sectors is deemed essential for maintaining competitiveness and value. The research suggests solutions such as advanced autonomous driving technologies and enhanced battery safety measures, with the integration of AI chips playing a pivotal role. However, challenges persist, including the limitations of big data and potential errors in semiconductor-related issues. Legacy automotive manufacturers are transitioning towards software-driven cars, leveraging artificial intelligence to mitigate risks associated with safety and security. Conflicting safety expectations and security concerns can lead to accidents, underscoring the continuous need for safety improvements. We analyzed the expansion of electric vehicles as a means to enhance safety within a framework of converging security concerns, with AI chips being instrumental in this process. Ultimately, the paper advocates for informed safety and security decisions to drive technological advancements in electric vehicles, ensuring significant strides in safety innovation.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.7-11
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• 2024

In the era of the 4th Industrial Revolution, new technologies such as artificial intelligence, big data, cloud, Internet of Things, and blockchain are being developed and applied to new industries. Blockchain has the characteristics of decentralization, security, and transparency, so it can serve as a core technology for developing new growth industries. Blockchain is provided as BaaS (Blockchain as a Service), but it is not easy for users who are introducing or building blockchain to choose BaaS. In this study, we identify evaluation factors and develop a decision-making model using fuzzy theory and AHP for BaaS selection. Eventually we aim to help companies choose the best BaaS and develop and commercialize blockchain-based services by developing a new decision-making model for BaaS selection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

• The Journal of Information Systems
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• v.26 no.4
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• pp.379-400
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• 2017

Purpose The purpose of this study is to investigate the effects of ICT on multilevel marketing organizations (MLMs) whose members are both salespeople and consumers. This study explores the effects of the latest ICT convergence on the direct selling, which is the oldest sales method, and suggests the direction for the development of network marketing. Therefore, we will propose the changes in direct sales brought by ICT and predict the future direction of network marketing in preparation for the 4th Industrial Revolution era. Design/methodology/approach Exploratory case study was the methodology selected for this paper. The case study enables the use of multiple methods for data collection and analysis. This study applies qualitative case-study methodology on Amway Korea, which is the top seller of MLM organizations, to better understand the impact of ICT. This study conducted an in-depth interview with four different levels of MLM members (e.g. membership, ruby, emerald, diamond) which are based on the qualification system of MLM organizations and observed their behaviors. Findings This study revealed that the ICT impact on network marketing organizations(MLMs) could be summarized as follows : new membership growth, easier communication with customers, increase in work efficiency, increase in organizational trust, change in educational environment, and increase in the use of social media. Based on the interview, we propose the changes of network marketing organizations in the fourth industrial revolution era and the future strategy of Amway Korea as follows: (1) retention of royal ABOs, (2) harmony with SMEs, (3) utilization of Big Data, (4) creation of IoT business model, and (5) construction of successful O2O business platform.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.103-110
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• 2013

In Information Technology era, various amazing IT technologies, for example Big Data, are appearing and are available as the amount of information increase. The number of counselling for violation of personal data protection is also increasing every year that it amounts to over 160,000 in 2012. According to Korean Privacy Act, in the case of treating unique personal identification information, appropriate measures like encipherment should be taken. The technologies of encipherment are the most basic countermeasures for personal data invasion and the base elements in information technology. So various cryptography algorithms exist and are used for encipherment technology. Therefore studies on safer new cryptography algorithms are executed. Cryptography algorithms started from classical replacement enciphering and developed to computationally secure code to increase complexity. Nowadays, various mathematic theories such as 'factorization into prime factor', 'extracting square root', 'discrete lognormal distribution', 'elliptical interaction curve' are adapted to cryptography algorithms. RSA public key cryptography algorithm which was based on 'factorization into prime factor' is the most representative one. This paper suggests algorithm utilizing telescoping series as a safer cryptography algorithm which can maximize the complexity. Telescoping series is a type of infinite series which can generate various types of function for given value-the plain text. Among these generated functions, one can be selected as a original equation. Some part of this equation can be defined as a key. And then the original equation can be transformed into final equation by improving the complexity of original equation through the command of "FullSimplify" of "Mathematica" software.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.305-312
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• 2015

In Korea, institutions and universities to educate and train Bigdata manpower are not yet much. There are various causes, but major cause among them is lack of understanding and perception on Bigdata. Therefore, this study investigated the situation regarding the recognition on Bigdata of universities' faculties and presented a direction for educating Bigdata manpower at the university. As a result, it was investigated that their awareness about the impact of Bigdata is not so great, despite of the somewhat understanding for the Bigdata. In particular, it was investigated that their intentions of research and education for Bigdata are not high. So, for a while, it was identified that Bigdata specialist training will not be easy. In conclusion, this study suggested that the government should pay its attention more on policy for Bigdata manpower training policy of the universities according to direction of the government 3.0 policy that considers the Bigdata to the axis of the major policy.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.483-496
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• 2018

Purpose: This paper proposes a quality strategy based on the evolution of technology in the age of the 4th Industrial Revolution. Methods: We examine the theory of past quality activities and the changes in quality paradigm, and analyze key words for the technologies and key issues of the 4th Industrial Revolution. Based on existing quality management, we find a quality strategy that should be pursued during the 4th Industrial Revolution. Results: Quality has been recognized as an essential component of corporate competitiveness. The paradigm of quality has also changed with the pass of time and industry development. From this viewpoint, the following eight quality strategies are proposed for the development of the technology of the 4th Industrial Revolution period, such as Market-to-customer fusion quality, symbiotic quality, big data quality, technical accuracy and zero-defect quality, facility predictability quality, software quality, process flexibility quality, and information protection stability and security quality. Conclusion: Quality for customer satisfaction is still important nowadays. However, in the 4th Industrial Revolution era, where various business models and methods of manufacturing are expected, the big data utilization, software quality, and the reliability and security of information protection to support it are important.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.149-158
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• 2012

Much attention is being paid to social media because of their potentials to draw collective intelligence. In this context does this study attempt to draw some implications of social media as knowledge creation platform and suggest a conceptual framework of social media management. Information sharing among the public through social media literally produces profound influence throughout the society and thus not only business firms but all levels of public institutions, including government are seeking to take its advantage for various purposes such as public relations, crowd sourcing, etc. Especially considering that social media open the possibility of social knowledge creation platform in the Big Data era, this study is perhaps able to contribute to further development of social media management model together with a series of measuring indexes.