• Smart Media Journal
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• v.9 no.4
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• pp.162-169
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• 2020

Design is a key factor that determines the competitiveness of products in the textile and fashion industry. It is very important to measure the similarity of the proposed design in order to prevent unauthorized copying and to confirm the originality. In this study, a deep learning technique was used to quantify features from images of textile designs, and similarity was measured using Spearman correlation coefficients. To verify that similar samples were actually detected, 300 images were randomly rotated and color changed. The results of Top-3 and Top-5 in the order of similarity value were measured to see if samples that rotated or changed color were detected. As a result, the VGG-16 model recorded significantly higher performance than did AlexNet. The performance of the VGG-16 model was the highest at 64% and 73.67% in the Top-3 and Top-5, where similarity results were high in the case of the rotated image. appear. In the case of color change, the highest in Top-3 and Top-5 at 86.33% and 90%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.79-86
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• 2023

Construction is one of the oldest fields of providing human living comfort. However, despite the continuous development not only in IT but also in other fields, productivity degradation due to low automation is still serious. In particular, the use of the 4th industrial revolution technologies in construction is just beginning. Blockchain, which is one of the 4th industrial revolution technologies, is a type of a distributed database that is used to replicate, share, and synchronize data spread across different geographical locations, such as multiple sites, countries, or organizations. In this paper, we introduce the block chain and analyze use cases according to seven themes in construction. As a result of the analysis, it is expected to increase the understanding of blockchain in construction and provide usefulness for the development of various services in the future.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.91-99
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• 2021

In the current business environment where dependence on IT has increased rapidly, the risk from disasters or cyber-attacks is also increasing. Business continuity, the ability to continue to provide service in the event of a business disruption caused by a disaster, is essential. In other words, you need to have a plan in place to keep your core business functions uninterrupted with rapid recovery within a predetermined Recovery Time Objective (RTO) and Recovery Point Objective (RPO) time frame. In this paper, we propose a disaster recovery system construction method that can minimize RTO and RPO to ensure business continuity. The system configuration adopts Tier 7 disaster recovery model, synchronous storage replication, hot disaster recovery site, and operation management automation solution. This ensures continuity of core business with virtually no data loss and minimal RTO and RPO.

• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.4
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• pp.254-261
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• 2020

Purpose: The purpose of this study was to assess the marginal and internal fit of interim crowns fabricated by two different manufacturing method (subtractive manufacturing technology and additive manufacturing technology). Materials and Methods: Forty study models were fabricated with plasters by making an impression of a master model of the maxillary right first molar for ceramic crown. On each study model, interim crowns (n = 40) were fabricated using three types of 3D printers (Meg-printer 2; Megagen, Zenith U; Dentis, and Zenith D; Dentis) and one type milling machine (imes-icore 450i; imes-icore GmbH). The internal of the interim crowns were filled with silicon and fitted to the study model. Internal scan data was obtained using an intraoral scanner. The fit of interim crowns were evaluated in the margin, absolute margin, axial, cusp, and occlusal area by using the superimposition of 3D scan data (Geomagic control X; 3D Systems). The Kruskal-wallis test, Mann-Whitney U test and Bonferroni correction method were used to compare the results among groups (α = 0.05). Results: There was no significant difference in the absolute marginal discrepancy of the temporary crown manufactured by three 3D printers and one milling machine (P = 0.812). There was a significant difference between the milling machine and the 3D printer in the axial and occlusal area (P < 0.001). The temporary crown with the milling machine showed smaller axial gap and higher occlusal gap than 3D printer. Conclusion: Since the marginal fit of the temporary crown produced by three types of 3D printers were all with in clinically acceptable range (< 120 ㎛), it can be sufficiently used for the fabrication of the temporary crown.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.435-447
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• 2016

As data can be permanently stored and freely distributed, in modern society, the Internet became a world that remembers everything forever. Because of that, there has been increasing the number of accident with never-forgetting data and, as a result, a movement has been emerged to apply a notion of 'oblivion' to internet world. The movement is called 'The right to be forgotten.' However, 'The right to be forgotten' in a higher level which internet users want to be guaranteed is very limited in the juridical approach because of the confliction with the other basic rights and problems. On the other hand, the requests of individuals to guarantee 'The right to be forgotten' has been urged digital extinction technology, such as volatile SNS, Digital Aging System, to be developed. With introduction of oblivion, digital extinction technology with setting expire date on digital information can present a new solution on assuring 'The right to be forgotten.' This research establishes the detail scope of, analyzes the level of assurance of, and, through digital extinction technology with the established scope, suggest the potential assurance of the 'The right to be forgotten'.

• Journal of Conservation Science
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• v.35 no.5
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• pp.470-479
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• 2019

The objective of this study is to identify the reason behind the expansion of exhaust holes and inhalational holes through high-definition filming and measurement of The Gilt-bronze Incense Burner of Baekje. In the proposed experiment, based on the original data obtained after a precise three-dimensional (3D) scan of the said incense burner, the precision replica and the commercial replica of the incense burner were subjected to a 3D scan. The overall shape and detailed patterns were subsequently compared with the original data. Furthermore, the incense-burning experiment was conducted according to the sizes and opened or unopened states of the exhaust and inhalational holes by employing the precision replica of the actual real relic for examining the internal structure of the lid and for studying the sizes and locations of the smoke holes. The results indicate that depending on the sizes of the exhaust and inhalational holes, the lower-line air intake holes can cause incomplete combustion in the incense burner. Depending on the opened or unopened states of the exhaust and inhalational holes, the phoenix air exhaust holes and upper-line air exhaust holes play a primary role in releasing the smoke, whereas the lower-line air intake holes play a primary role in smoke inhalation.

• Smart Media Journal
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• v.10 no.3
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• pp.39-47
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• 2021

Enhanced index tracking is a problem of optimizing the objective function to generate returns above the index based on the index tracking that follows the market return. In order to avoid problems such as large transaction costs and illiquidity, we used a method of constructing a portfolio by selecting only some of the stocks included in the index. Commonly used enhanced index tracking methods tried to find the optimal portfolio with only one objective function in all tested periods, but it is almost impossible to find the ultimate strategy that always works well in the volatile financial market. In addition, it is important to improve generalization performance beyond optimizing the objective function for training data due to the nature of the financial market, where statistical characteristics change significantly over time, but existing methods have a limitation in that there is no direct discussion for this. In order to solve these problems, this paper proposes ensemble learning that composes a portfolio by combining several objective functions and a 3-stage portfolio selection algorithm that can select a portfolio by applying criteria other than the objective function to the training data. The proposed method in an experiment using the S&P500 index shows Sharpe ratio that is 27% higher than the index and the existing methods, showing that the 3-stage portfolio selection algorithm and ensemble learning are effective in selecting an enhanced index portfolio.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.187-193
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• 2019

Key-value storage engines are an essential component of growing demand in many computing environments, including social networks, online e-commerce, and cloud services. Recent key-value storage engines offer many features such as transaction, versioning, and replication. In a key-value storage engine, transaction processing provides atomicity through Write-Ahead-Logging (WAL), and a synchronous commit method for transaction processing flushes log data before the transaction completes. According to our observation, flushing log data to persistent storage is a performance bottleneck for key-value storage engines due to the significant overhead of fsync() calls despite the various optimizations of existing systems. In this article, we propose a group synchronization method to improve the performance of the key-value storage engine. We also design and implement a transaction scheduling method to perform other transactions while the system processes fsync() calls. The proposed method is an efficient way to reduce the number of frequent fsync() calls in the synchronous commit while supporting the same level of transaction provided by the existing system. We implement our scheme on the WiredTiger storage engine and our experimental results show that the proposed system improves the performance of key-value workloads over existing systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.12
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• pp.831-841
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• 2014

The attacker can access the RFID systems illegally because authentication operation on the RFID systems are performed in wireless communication. Authentication methods based on the PUF were presented to defend attacks. Because of Hash and AES, the cost is expensive for the low-cost RFID tag. In this paper, the PUF-based encryption processor and the mutual authentication protocol are proposed for low-cost RFID authentication. The challenge-response pairs (PUF's input and output) are utilized as the authentication key and encrypted by the PUF's characteristics. The encryption method is changed each session and XOR operation with random number is utilized. Therefore, it is difficult for the attacker to analyze challenge-response pairs and attack the systems. In addition, the proposed method with PUF is strong against physical attacks. And the method protects the tag cloning attack by physical attacks because there is no authentication data in the tag. Proposed processor is implemented at low cost with small footprint and low power.

• Journal of IKEEE
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• v.24 no.2
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• pp.529-535
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• 2020

As the main technology of the 4th industrial revolution, immersive 360-degree video contents are drawing attention. The market size of immersive 360-degree video contents worldwide is projected to increase from $6.7 billion in 2018 to approximately $70 billion in 2020. However, most of the immersive 360-degree video contents are distributed through illegal distribution networks such as Webhard and Torrent, and the damage caused by illegal reproduction is increasing. Existing 2D video industry uses copyright filtering technology to prevent such illegal distribution. The technical difficulties dealing with immersive 360-degree videos arise in that they require ultra-high quality pictures and have the characteristics containing images captured by two or more cameras merged in one image, which results in the creation of distortion regions. There are also technical limitations such as an increase in the amount of feature point data due to the ultra-high definition and the processing speed requirement. These consideration makes it difficult to use the same 2D filtering technology for 360-degree videos. To solve this problem, this paper suggests a feature point extraction and identification technique that select object identification areas excluding regions with severe distortion, recognize objects using deep learning technology in the identification areas, extract feature points using the identified object information. Compared with the previously proposed method of extracting feature points using stitching area for immersive contents, the proposed technique shows excellent performance gain.