• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.174-181
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• 2004

Recently, many studies have been undergoing to reduce working time in field of machine tool. There are two ways of reducing working time to reduce actual working time by heighten spindle speed and to reduce stand-by time by shortening tool exchange time. Auto tool changer belongs to latter case. Fixed address type auto tool changer can store more number of tools in small space than magazine transfer Ope and can shorten tool exchange time. This study focuses on the topology optimization to reduce the weight of the fixed address type ATC. The optimization program using a real number coding genetic algorithm is developed and is applied to the 10-bar truss optimization problem to verify the developed program. And, it is shown that the developed program gives better results than other methods. Finally, The developed program applied to optimize the fixed address type ATC.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.2
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• pp.199-215
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• 1997

The Internet has gained popularity because it provides various information in digital format. However, it is very difficult to provide methods which make it possible to search adequate information resource from bulk of Internet information. In this paper, we define a SGML metadata DTD, named SeriCore, and design and implement a metadata retrieval and management system which can store, retrieve and manage the Internet metadata efficiently.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1453-1459
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• 2016

Recently, vector map has developed, used in many domains, and in most cases vector map data contains confidential information which must be kept away from unauthorized users. Moreover, the manufacturing process of a vector map is complex and the maintenance of a digital map requires substantial monetary and human resources. This paper presents the selective encryption scheme based on polyline simplification methods for GIS vector map data protection to store, transmit or distribute to authorized users. Main advantages of our algorithm are random vertices and transformation processes but it still meets requirements of security by random processes, and this algorithm can be implement to many types of vector map formats.

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.2
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• pp.61-69
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• 2015

Undifferentiated stem cells are being studied to obtain information on the therapeutic potential of isolates that are produced. Dental Pulp Stem Ccell (DPSC) may provide an abundant supply of highly proliferative, multipotent Mesenchymal Stem Cells (MSC), which are now known to be capable of regenerating a variety of human tissues including bone and other dental structures. Many factors influence DPSC quality and quantity, including the specific methods used to isolate, collect, concentrate, and store these isolates once they are removed. Ancillary factors, such as the choice of media, the selection of early versus late passage cells, and cryopreservation techniques may also influence the differentiation potential and proliferative capacity of DPSC isolates. This literature review concludes that due to the delicate nature of DPSC, more research is needed for dental researchers and clinicians to more fully explore the feasibility and potential for isolating and culturing DPSCs extracted from adult human teeth in order to provide more accurate and informed advice for this newly developing field of regenerative medicine.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.111-116
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• 2018

Recently, IoT and Big Data dealing with voluminous and complex sensitive information is one of the key issues in the era of the 4th industrial revolution. There have been a lot of studies to store the collected and processed sensitive information safely in storage data. Especially biometric information, if it is leaked and becomes identity theft, is hard to be corrected and results in serious event. To fix the problem, methods such as FIDO or KFTC have been proposed. In this paper, we propose a modified method of TTAK.KO-12.0098 according to the environment of this paper and propose a method of safely storing the generated disposable template in a block chain. We show that our method is better by comparing the existing method and the security analysis.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.43-55
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• 2021

The amount of Big Data generated from multiple sources is continuously increasing. Traditional storage methods lack the capacity for such massive amounts of data. Consequently, most organizations have shifted to the use of cloud storage as an alternative option to store Big Data. Despite the significant developments in cloud storage, it still faces many challenges, such as privacy and security concerns. This paper discusses Big Data, its challenges, and different classifications of security and privacy challenges. Furthermore, it proposes a new classification of Big Data security and privacy challenges and offers some perspectives to provide solutions to these challenges.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1156-1157
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• 2013

The mobile application market has been growing extensively in recent years. Currently, Apple's App Store has more than 400,000 applications and Google's Android Market has above 150,000 applications. Such growth in volumes of mobile applications has created a need to develop a recommender system that assists the users to take the right choice, when searching for a mobile application. In this paper, we study the recommendation system building tools based on collaborative filtering. Specifically, we present a study on comparison analysis of collaborative filtering in Java and R statistical software. We implement the collaborative filtering using Java's Apache Mahout and R's recommenderlab package. We evaluate both methods and describe the advantages and disadvantages of using them in order to implement collaborative filtering.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.214-222
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• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

• Journal of the Korean Society for Precision Engineering
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• v.5 no.2
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• pp.56-61
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• 1988

For the use of computer to store, modify and retieve technical data, GT coding system has been considered as one of the effective methods. Effective data management is important for Computer Intergrated Manufacturing. Based on actual data obtained from a hand-tool maker, a die/tool coding system is developed as an example and its data base is designed susing a linked list structure. It is suggested that industries use this method to make their own data base.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.119-130
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• 2023

Worldwide organizations use the benefits offered by Cloud Computing (CC) to store data, software and programs. While running hugely complicated and sophisticated software on cloud requires more energy that causes global warming and affects environment. Most of the time energy consumption is wasted and it is required to explore opportunities to reduce emission of carbon in CC environment to save energy. Many improvements can be done in regard to energy efficiency from the software perspective by considering and paying attention on the energy consumption aspects of software's that run on cloud infrastructure. The aim of the current research is to propose a framework with an additional phase called parameterized development phase to be incorporated along with the traditional Software Development Life cycle (SDLC) where the developers need to consider the suggested techniques during software implementation to utilize low energy for running software on the cloud and contribute in green computing. Experiments have been carried out and the results prove that the suggested techniques and methods has enabled in achieving energy consumption.