• Industry Promotion Research
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• v.8 no.2
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• pp.1-9
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• 2023

To bridge the research gap in the area of the Fourth Industrial Revolution, we explore the correlation between the core technologies of the Fourth Industrial Revolution and the economic performance of companies. The results show that the technologies have a statistically significant positive (+) correlation with company sales. The size of the correlation is highest for 3D printing (139%), followed by big data (129%), cloud computing (127%), artificial intelligence (78%), and the internet of things (70%). We also found a statistically significant negative (-) interaction effect between the internet of things and 3D printing, cloud computing and big data, and cloud computing and 3D printing when examining the interaction effect of introducing core technologies of the Fourth Industrial Revolution on company sales. This paper represents an early attempt to examine the correlation between the core technologies of the Fourth Industrial Revolution and the economic performance of companies and may serve as a basis for further empirical research.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.46-54
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• 2021

As the realization of the 4th industrial revolution is approaching, the paradigm of the corporate work environment is changing to digital, from the traditional work environment. In particular, technologies like RPA(robotic process automation) and chatbot reduce the need for human labor or task by automating simple repetitive tasks, enabling humans to focus on more valuable tasks. In this study, corporates operating expense management services in public cloud computing environments develop a cloud module that simplifies expense report management by grafting robotic process automation and chatbot technology. According to the result of the expert evaluation, the developed system marked 80.3% of satisfaction levels and the highest satisfaction level 94% was confirmed in terms of easy of use. Based on the research result, future research can be suggested to expand the works occurring inside and outside the company to a single RPA environment by additionally linking the work system related to expense management.

• IE interfaces
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• v.25 no.1
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• pp.1-12
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• 2012

The challenges facing manufacturing companies today span across the industry, independent of company size or product. Especially, big manufacturers must overcome these challenges, and information technology (IT) collaboration with small and medium enterprises (SMEs) will play a major role in this effort. In this research, the strategy and way to promote IT collaboration between SMEs and large firms in heavy industries are proposed. A pre-consultation was performed to derive the strategy and way for the collaboration, and an IT collaboration system was developed reflection the results of pre-consultation. The IT collaboration system consists of two parts. One is ERP based on BPM for SMEs to standardize and visualize the entire business process from order placement to release. This system also provides their parent company with visibility into the status of orders and user can easily access the system on the web at a low price through cloud computing service. The other is interface part for data changes between large firms and SMEs. Thus far, this paper demonstrates the importance of strategy for the collaboration, and the applicability of IT collaboration system to elevate the speed and efficiency of business.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5972-5989
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• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.15-30
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• 2015

SMBA (Small and Medium Business Administration) and TIPA (Korea Technology and Information Promotion Agency for SMEs) have operated the Business Innovation Platform for SME Informatization based on cloud computing technology with the cooperation of seven industry cooperatives since 2013. This project will evolve into the open market platform where service providers and users voluntarily participate and transact. This research conducts the literature review about the concept of open market and the empirical analysis through survey for the software providers and the future users regarding the future operation methods. The policy about how the open market strategy for the business innovation platform needs to be designed and implemented are organized as the three differentiated government support strategies. The first is to provide free IT services including specialized core operation support S/W which is developed only for the small or home office group of firms which lack minimal informatization capability and budget. The second is to augment IT platform service through incorporating ERP supplier initiated commercial S/W sales window for those firms having medium level informatization capability. This includes to provide IT support for customization and system integration with existing government subsidized S/W. The third is to provide upgrading services of existing S/W functions to facilitate better system utilization. The results provide useful insight for government role to enhance SME competitiveness using IT.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.503-509
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• 2019

Order-revealing encryption which enables a range query over encrypted data is attracting attention as one of the important security technologies in industry such as IoT, smart manufacturing, and cloud computing. In 2015, an ideally-secure order-revealing encryption whose ciphertexts reveal no additional information beyond the order of the underlying plaintexts has been proposed. However, their construction is too inefficient for practical use and some security analysis of multilinear maps, which their construction relies on, have been proposed. Recently, more practical schemes have been proposed, focusing on achieving practically usable efficiency rather than the ideal security. In this paper, we propose a more storage-efficient order-revealing encryption scheme than the Lewi et al.'s scheme most recently published by presenting an idea that can generate shorter ciphertexts without any security loss.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.586-590
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• 2009

The objective of this paper describes the design of MapReduce over Peer-to-Peer network for dynamic environments applications. MapReduce is a software framework used for Cloud Computing which processing large data sets in a highly-parallel way. Based on the Peer-to-Peer network character which node failures will happen anytime, we focus on using a DHT routing protocol which named Pastry to handle the problem of node failures. Our results are very promising and indicate that the framework could have a wide application in P2P network systems while maintaining good computational efficiency and scalability. We believe that, P2P networks and parallel computing emerge as very hot research and development topics in industry and academia for many years to come.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Convergence Security Journal
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• v.23 no.1
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• pp.79-87
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• 2023

Precision Medicine, which utilizes personal health information, genetic information, clinical information, etc., is growing as the next-generation medical industry. In Korea, medical institutions and information communication companies have coll aborated to provide cloud-based Precision Medicine Hospital Information Systems (P-HIS) to about 90 primary medical ins titutions over the past five years, and plan to continue promoting and expanding it to primary and secondary medical insti tutions for the next four years. Precision medicine is directly related to human health and life, making information protecti on and healthcare information protection very important. Therefore, this paper analyzes the preliminary research on inform ation protection models that can be utilized in cloud-based Precision Medicine Hospital Information Systems and ultimately proposes research on ways to improve information protection in P-HIS.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.93-100
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• 2017

Recently, demands for high-performance flash-based storage devices (i.e., flash SSD) have rapidly grown in social network services, cloud computing, super-computing, and enterprise storage systems. The industry and academic communities made the NVMe specification for high-performance storage devices, and NVMe-based flash SSDs can be now obtained in the market. In this article, we evaluate performance of NoSQL databases that social network services and cloud computing services heavily adopt by using NVMe-based flash SSDs. To this end, we use NVMe SSD that Samsung Electronics recently developed, and the SSD used in this study has performance up to 3.5GB/s for sequential read/write operations. We use WiredTiger for NoSQL databases, and it is a default storage engine for MongoDB. Our experimental results show that log processing in NoSQL databases is a major overhead when high-performance NVMe-based flash SSDs are used. Furthermore, we optimize components of log processing and optimized WiredTiger show up to 15 times better performance than original WiredTiger.