• Genomics & Informatics
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• v.17 no.2
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• pp.13.1-13.3
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• 2019

The usage of controlled biomedical vocabularies is the cornerstone that enables seamless interoperability when using a common data model across multiple data sites. The Observational Health Data Science and Informatics (OHDSI) initiative combines over 100 controlled vocabularies into its own. However, the OHDSI vocabulary is limited in the sense that it combines multiple terminologies and does not provide a direct way to link them outside of their own self-contained scope. This issue makes the tasks of enriching feature sets by using external resources extremely difficult. In order to address these shortcomings, we have created a linked data version of the OHDSI vocabulary, connecting it with already established linked resources like bioportal, bio2rdf, etc. with the ultimate purpose of enabling the interoperability of resources previously foreign to the OHDSI universe.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.133-139
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• 2023

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a quantitative method for analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.162-168
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• 2023

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a bibliometric analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.179-192
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• 2019

Additional frequencies are allocated in maritime digital data exchange to alleviate overload of the VHF data link. The shipborne ad-hoc network (SANET) for this frequencies was subsequently proposed, which provides various IP-based services to ships on behalf of satellite communications. In SANET, a ship should determine its own IP address to achieve IP connectivity to the shore. Accordingly, this paper proposes a SANET configuration (SANETconf) protocol as an IP configuration protocol. SANETconf propagates non-overlapping IP addresses across the network from the shore to ships. A ship obtains its IP address by exchanging Request and Response messages with its neighbors. Therefore, SANETconf eliminates the process of DAD and managing the movement of ships. Extensive simulations were performed to verify the applicability of SANETconf. Based on results, 85% of the ships can determine their own IP address within one frame. Also, SANETconf has a high resource efficiency by using 0.024 percent of resources for IP configuration.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.171-175
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• 1997

We have developed a remote diagnosis system using the LAN and MODEM which enables a routine check for a patient remotely. We used $LabVIEW^{TM}$ as the programing development tool and DAQ (Data Aquisition) board from National Instrument for data aquisition. The LAN card and MODEM are used for the transmission of patient's data. A patient data are aquired by DAQ board and signal processing is done by $LabVIEW^{TM}$, which is a graphical prgamming language. Two methods for the data of transmission. One is the Client-Server model using TCP/IP (Transmission Control Protocol / Internet Address) in the LAN (Local Area Network) Another is using MODEM to transmit the measured data from a patient. In this case, the data transmission is accomplished by the FTP (File Transfer Protocol).

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.487-492
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• 2008

The cooling of data centers has emerged as a significant challenge as the density of IT server increases. Server installations, along with the shrinking physical size of servers and storage systems, has resulted in high power density and high heat density. The introduction of high density enclosures into a data center creates the potential for "hot spots" within the room that the cooling system may not be able to address, since traditional designs assume relatively uniform cooling patterns within a data center. The cooling system for data center consists of a CRAC or CRAH unit and the associated air distribution system. It is the configuration of the distribution system that primarily distinguishes the different types of data center cooling systems, this is the main subject of this paper.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3716-3724
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• 2023

Loose parts monitoring and detecting alarm type in real Nuclear Power Plant have challenges such as background noise, insufficient alarm data, and difficulty of distinction between alarm data that occur during start and stop. Although many signal processing methods and alarm determination algorithms have been developed, it is not easy to determine valid alarm and extract the meaning data from alarm signal including background noise. To address these issues, this paper proposes a denoising autoencoder-based majority vote classification. Training and test data are prepared by acquiring alarm data from real NPP and simulation facility for data augmentation, and noisy data is reproduced by adding Gaussian noise. Using DAEs with 3, 5, 7, and 9 layers, features are extracted for each model and classified into neural networks. Finally, the results obtained from each DAE are classified by majority voting. Also, through comparison with other methods, the accuracy and the false alarm rate are compared, and the excellence of the proposed method is confirmed.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• East Asian Economic Review
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• v.23 no.4
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• pp.333-351
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• 2019

We use a data-mining bootstrap procedure to investigate the predictability test in the eight Asia-Pacific regional stock markets using in-sample and out-of-sample forecasting models. We address ourselves to the data-mining bias issues by using the data-mining bootstrap procedure proposed by Inoue and Kilian and applied to the US stock market data by Rapach and Wohar. The empirical findings show that stock returns are predictable not only in-sample but out-of-sample in Hong Kong, Malaysia, Singapore, and Korea with a few exceptions for some forecasting horizons. However, we find some significant disparity between in-sample and out-of-sample predictability in the Korean stock market. For Hong Kong, Malaysia, and Singapore, stock returns have predictable components both in-sample and out-of-sample. For the US, Australia, and Canada, we do not find any evidence of return predictability in-sample and out-of-sample with a few exceptions. For Japan, stock returns have a predictable component with price-earnings ratio as a forecasting variable for some out-of-sample forecasting horizons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2219-2236
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• 2017

With cloud storage services, users can handle an enormous amount of data in an efficient manner. However, due to the widespread popularization of cloud storage, users have raised concerns about the integrity of outsourced data, since they no longer possess the data locally. To address these concerns, many auditing schemes have been proposed that allow users to check the integrity of their outsourced data without retrieving it in full. Yuan and Yu proposed a public auditing scheme with a deduplication property where the cloud server does not store the duplicated data between users. In this paper, we analyze the weakness of the Yuan and Yu's scheme as well as present modifications which could improve the security of the scheme. We also define two types of adversaries and prove that our proposed scheme is secure against these adversaries under formal security models.