• Journal of Software Engineering Society
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• v.26 no.1
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• pp.1-16
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• 2013

Variable length information message is a communication protocol standard in order for computer network systems to provide efficient delivery of information. The variable length information messages were developed for varying and controlling details of information in accordance with message receiver's required information level or information access level. In the previous studies, data compressing techniques have been in use for information message optimization technologies in order to reduce physical sizes of information messages. In optimization technologies for information messages, accuracy of information is considered as the most important factor; therefore, only non-loss compression techniques are applied to the optimization technologies. However, the non-loss compression based information message optimization methods are not efficient in data compression, and these are limited to efficient delivery of information in wireless network environments that have constraint bandwidth. In this paper, we attempt to optimize information in the variable length information messages at message fields in order to reduce physical sizes of messages more efficiently. To demonstrate the efficiency of our approach, we conduct optimization experiments for variable length information messages.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.205-224
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• 2020

Purpose - This study aimed to identify the effects of ownership structures on agency costs in internationally diversified firms listed on the KOSDAQ market. Design/methodology/approach - A total of 5,824 samples were finally selected and empirically analyzed for a total of nine years from 2011 to 2019, during which the International Accounting Standards had been mandatory for firms listed on the KOSDAQ market. Findings - The results of this study showed that the effects of ownership structures on the ratio of asset turnover are positive for the major share and foreign equity ratios of international diversified firms. Moreover, by selecting the ratio of entertainment expenses as a proxy for agency expenses, this study confirmed that the effects of the ownership structure of an international diversified entity on entertainment expenditure were determined to show a significantly negative relation to entertainment expenditure, thus indicating that the higher the ratio of major shareholders, the more appropriately control the expenditure of entertainment expenses through arbitrary private deviations of the management.Furthermore, considering the effect of the ownership structure on the expenditure of sales and administrative expenses as a proxy variable for agency costs, this study verified that the majority share ratio of international diversified firms was negative to the expenditure of sales and administrative expenses, confirming that the higher the share of major shareholders, the lower the selling and administrative costs, but insignificant.Finally, as a result of determining whether the ownership structure of an international diversified firm affects the holding of free cash, the majority share of this firm shows a significantly negative relation to the ratio of the holding of surplus cash, indicating that the higher the proportion of major shareholders, the more appropriately control the holding of the entity's free cash through arbitrary private deviance by the manager. Research implications or Originality - Major shareholders of an internationally diversified firm listed on the KOSDAQ market play a positive role in the firm's performance by properly controlling agency costs that may be incurred by the management.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.33-38
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• 2019

In this paper, we propose a new blockchain technology that could comply with GDPR. The proposed model can prevent illegal access by controlling access to the personal information according to a access policy. For example, it can control access to the information on a role-basis and information validation period. The core mechanism of the proposed model is to encrypt the personal information with public key which is associated with users attributes policy, and then decrypt it with a private key and users attributes based on a Attribute-based Encryption scheme. It can reduce a trusted third-part risk by replacing it with a number of nodes selected from the blockchain. And also the private key is generated in the form of one-time token to improve key management efficiency. We proved the feasibility by simulating the proposed model using the chaincode of the Hyperledger Fabric and evaluate the security.

• Tribology and Lubricants
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• v.37 no.1
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• pp.25-30
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• 2021

The surface texture produced via surface texturing is an important approach for controlling the tribological behavior of friction behavior of mechanical devices. The purpose of this study is to investigate the effect of grooves generated via ultrasonic nanocrystal surface modification (UNSM) technology on the tribological performance of AISI 4150 steel against stainless steel 316L. In the study, tribological tests are performed under two different regimes, namely mixed and hydrodynamic lubrication, by varying the applied normal load and reciprocating speed during the tests. According to the test results, the friction coefficient decreases as static load (10 N, 30 N, and 50 N) of UNSM technology increases in the mixed lubrication regime. Conversely, the friction coefficient increases as the static load (10 N, 30 N, and 50 N) of UNSM technology increases in the hydrodynamic lubrication regime. Hence, the results indicate that micro-grooves generate hydrodynamic pressure in the outlet, which increases the oil film thickness between the two mating surfaces. This potentially leads to a reduction in friction in the mixed lubrication regime due to the prevention of contact of asperities and debris. However, the results indicate an adverse effect in the hydrodynamic lubrication regime. In this regard, additional experiments should be performed to investigate the effect of grooves generated by UNSM technology at varying conditions on the friction behavior of AISI 4150 steel, which in turn can be controlled by the generated pressure and oil film thickness at the contact interface.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.1-8
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• 2021

In this paper, we propose an approach that combines the technological advantages of P2P and cloud computing to support MMOGs that allowing a huge amount of users worldwide to share a real-time virtual environment. The proposed P2P system based on cloud computing can provide a greater level of scalability because their more resources are added to the infrastructure even when the amount of users grows rapidly. This system also relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. In this paper, we describe the concept and basic architecture of cloud computing-based P2P Systems for scalability of MMOGs. An efficient and effective provisioning of resources and mapping of load are mandatory to realize this architecture that scales in economical cost and quality of service to large communities of users. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed P2P system can reduce the bandwidth at the server while utilizing their enough bandwidth when the number of simultaneous users keeps growing.

• Journal of Microbiology and Biotechnology
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• v.31 no.12
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• pp.1701-1708
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• 2021

Food safety is the most important global health issue due to foodborne pathogens after consumption of contaminated food. Foodborne bacteria such as Escherichia coli, Salmonella enterica, Staphylococcus aureus, Campylobacter spp., Bacillus cereus, Vibrio spp., Yersinia enterocolitica and Clostridium perfringens are leading causes of the majority of foodborne illnesses and deaths. These foodborne pathogens often come from the livestock feces, thus, we analyzed fecal microbial communities of three different livestock species to investigate the prevalence of foodborne pathogens in livestock feces using metagenomics analysis. Our data showed that alpha diversities of microbial communities were different according to livestock species. The microbial diversity of cattle feces was higher than that of chicken or pig feces. Moreover, microbial communities were significantly different among these three livestock species (cattle, chicken, and pig). At the genus level, Staphylococcus and Clostridium were found in all livestock feces, with chicken feces having higher relative abundances of Staphylococcus and Clostridium than cattle and pig feces. Genera Bacillus, Campylobacter, and Vibrio were detected in cattle feces. Chicken samples contained Bacillus, Listeria, and Salmonella with low relative abundance. Other genera such as Corynebacterium, Streptococcus, Neisseria, Helicobacter, Enterobacter, Klebsiella, and Pseudomonas known to be opportunistic pathogens were also detected in cattle, chicken, and pig feces. Results of this study might be useful for controlling the spread of foodborne pathogens in farm environments known to provide natural sources of these microorganisms.

• Journal of Microbiology and Biotechnology
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• v.32 no.2
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• pp.220-227
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• 2022

The spread of antibiotic-resistant strains of Staphylococcus aureus, a gram-positive opportunistic pathogen, has increased due to the frequent use of antibiotics. Inhibition of the quorum-sensing systems of biofilm-producing strains using plant extracts represents an efficient approach for controlling infections. Torilis japonica is a medicinal herb showing various bioactivities; however, no studies have reported the anti-biofilm effects of T. japonica extracts against drug-resistant S. aureus. In this study, we evaluated the inhibitory effects of T. japonica ethanol extract (TJE) on biofilm production in methicillin-sensitive S. aureus (MSSA) KCTC 1927, methicillin-resistant S. aureus (MRSA) KCCM 40510, and MRSA KCCM 40511. Biofilm assays showed that TJE could inhibit biofilm formation in all strains. Furthermore, the hemolysis of sheep blood was found to be reduced when the strains were treated with TJE. The mRNA expression of agrA, sarA, icaA, hla, and RNAIII was evaluated using reverse transcription-polymerase chain reaction to determine the effect of TJE on the regulation of genes encoding quorum sensing-related virulence factors in MSSA and MRSA. The expression of hla reduced in a concentration-dependent manner upon treatment with TJE. Moreover, the expression levels of other genes were significantly reduced compared to those in the control group. In conclusion, TJE can suppress biofilm formation and virulence factor-related gene expression in MSSA and MRSA strains. The extract may therefore be used to develop treatments for infections caused by antibiotic-resistant S. aureus.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.65-77
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• 2022

Schedule management is one of pivotal project success factors during construction projects. However, there are many difficulties in rapid scheduling and controlling since the existing planning techniques require considerable amount of manual work and manager's judgment in a construction project. This research aims to propose a new scheduling method and algorithm for automating and visualizing the planning process, which is called Countable-grid scheduling method. In this method, if the scope of work is defined via a visualized tool, the schedule plan is created automatically according to the productivity and workable conditions of each activity. The location of the work for each date can be visualized in grid-based approach. Moreover, the work schedule can be updated automatically according to the progress. The industrial applicability of the proposed method was verified in construction projects via case study with sample data. This research can contribute to the construction industry by automating the construction schedule management process.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.195-207
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• 2022

COVID-19 has remained one of the most serious health crises in recent history, resulting in the tragic loss of lives and significant economic impacts on the entire world. The difficulty of controlling COVID-19 poses a threat to the global health sector. Considering that Artificial Intelligence (AI) has contributed to improving research methods and solving problems facing diverse fields of study, AI algorithms have also proven effective in disease detection and early diagnosis. Specifically, acoustic features offer a promising prospect for the early detection of respiratory diseases. Motivated by these observations, this study conceptualized a speech-based diagnostic model to aid in COVID-19 diagnosis. The proposed methodology uses speech signals from confirmed positive and negative cases of COVID-19 to extract features through the pre-trained Visual Geometry Group (VGG-16) model based on Mel spectrogram images. This is used in addition to the K-means algorithm that determines effective features, followed by a Genetic Algorithm-Support Vector Machine (GA-SVM) classifier to classify cases. The experimental findings indicate the proposed methodology's capability to classify COVID-19 and NOT COVID-19 of varying ages and speaking different languages, as demonstrated in the simulations. The proposed methodology depends on deep features, followed by the dimension reduction technique for features to detect COVID-19. As a result, it produces better and more consistent performance than handcrafted features used in previous studies.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.13-23
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• 2021

In this paper, we proposed a framework that generates the trajectory of a single rigid body based on its COM configuration and contact pose. Because we use a smaller input dimension than when we use a full body state, we can improve the learning time for reinforcement learning. Even with a 68% reduction in learning time (approximately two hours), the character trained by our network is more robust to external perturbations tolerating an external force of 1500 N which is about 7.5 times larger than the maximum magnitude from a previous approach. For this framework, we use centroidal dynamics to calculate the next configuration of the COM, and use reinforcement learning for obtaining a policy that gives us parameters for controlling the contact positions and forces.