• KEPCO Journal on Electric Power and Energy
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• v.5 no.2
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• pp.103-111
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• 2019

The combined cycle plant is an integration of gas turbine and steam turbine, combining the advantages of both cycles. It recovers the heat energy from gas turbine exhaust to use it to generate steam. The heat recovery steam generator plays a crucial role in combined cycle plants, providing the link between the gas turbine and the steam turbine. Simulation of the performance of the HRSG is required to study its effect on the entire cycle and system. Computational fluid dynamics has potential to become a useful to validate the performance of the HRSG. In this study a solver has been implemented in the open source code, OpenFOAM, for combustion simulation in the heat recovery steam generator. The solver is based on the steady laminar flamelet model to simulate detailed chemical reaction mechanism. Thereafter, the solver is used for simulation of HRSG system. Three cases with varying fuel injections and gas turbine exhaust gas flow rates were simulated and the results were compared with measurements at the system outlet. Predicted temperature and emissions and those from measurements showed the same trend and in quantitative agreement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3258-3279
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• 2019

Recently, ransomware has earned itself an infamous reputation as a force to reckon with in the cybercrime landscape. However, cybercriminals are adopting other unconventional means to seamlessly attain proceeds of cybercrime with little effort. Cybercriminals are now acquiring cryptocurrencies directly from benign Internet users without the need to extort a ransom from them, as is the case with ransomware. This paper investigates advances in the cryptovirology landscape by examining the state-of-the-art cryptoviral attacks. In our approach, we perform digital autopsy on the malware's source code and execute the different malware variants in a contained sandbox to deduce static and dynamic properties respectively. We examine three cryptoviral attack structures: browser-based crypto mining, memory resident crypto mining and cryptoviral extortion. These attack structures leave a trail of digital forensics evidence when the malware interacts with the file system and generates noise in form of network traffic when communicating with the C2 servers and crypto mining pools. The digital forensics evidence, which essentially are IOCs include network artifacts such as C2 server domains, IPs and cryptographic hash values of the downloaded files apart from the malware hash values. Such evidence can be used as seed into intrusion detection systems for mitigation purposes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.595-598
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• 2014

The cyber attacks of recent attacks that target zero-day exploit security vulnerabilities before the security patch is released (Zero Day) attack, the web site is without the Lord. These attacks, those that use the vulnerability of security that is built into the software itself is in most cases, cyber attacks that use the vulnerability of the security of the source code, in particular, has a characteristic response that are difficult to security equipment. Therefore, it is necessary to eliminate the security vulnerability from step to implement the software to prevent these attacks. In this paper, we try to design a Secure Coding Guide support tool to eliminate the threat of security from the stage of implementation.

• Genomics & Informatics
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• v.16 no.4
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• pp.36.1-36.3
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• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.424-431
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• 2019

The aim of the present study was to develop model for detonation cell sizes prediction based on a deep artificial neural network of hydrogen, methane and propane mixtures with air and oxygen. The discussion about the currently available algorithms compared existing solutions and resulted in a conclusion that there is a need for a new model, free from uncertainty of the effective activation energy and the reaction length definitions. The model offers a better and more feasible alternative to the existing ones. Resulting predictions were validated against experimental data obtained during the investigation of detonation parameters, as well as with data collected from the literature. Additionally, separate models for individual mixtures were created and compared with the main model. The comparison showed no drawbacks caused by fitting one model to many mixtures. Moreover, it was demonstrated that the model may be easily extended by including more independent variables. As an example, dependency on pressure was examined. The preparation of experimental data for deep neural network training was described in detail to allow reproducing the results obtained and extending the model to different mixtures and initial conditions. The source code of ready to use models is also provided.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1234-1245
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• 2018

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.10
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• pp.19-26
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• 2018

The purpose of this study was to analyze characteristics and to develop estimation model of IHG(Internal Heat Gain) from appliance in domestic apartment units. To do this, it was defined the source of IHG from appliance and the calculation method through the case study of international and domestic codes. And the equipment related datum such possession, usage or not, etc were collected through field survey in apartment units, and the appliances' electricity consumption were measured separately from overall electricity consumption. Annual electricity consumption value were calculated with field survey datum and appliances' electricity consumption measurement datum, and then IHG value was calculated by applying PHPP v9 method. And it was conducted correlation analysis between IHG value and the area for exclusive use, the number of occupants, and then the IHG from applianace estimation model was deducted with regression analysis. Finally, it was analyzed the present level and of the domestic code(The Building Energy Efficiency Rating System) comparing with the value of estimation model, and the various international codes(HERS, Building America, SAP).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.901-911
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• 2012

The removal of security vulnerabilities during the developmental stage is found to be much more effective and much more efficient than performing the application during the operational phase. The underlying security vulnerabilities in software have become the major cause of cyber security incidents. Thus, secure coding is drawing much attention for one of its abilities includes minimizing security vulnerabilities at the source code level. Removal of security vulnerabilities at the software's developmental stage is not only effective but can also be regarded as a fundamental solution. This thesis is a research about the methods of Mobile-Secure Coding Self Assessment in order to evaluate the security levels in accordance to the application of mobile secure coding of every individual, groups, and organizations.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.58-66
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• 2021

The user's password must be encrypted one-way through the hash function and stored in the database. Widely used hash functions such as MD5 and SHA-1 have also been found to have vulnerabilities, and hash functions that are considered safe can also have vulnerabilities over time. Salt enhances password security by adding it before or after the password before putting it to the hash function. In the case of the existing Salt, even if it is randomly assigned to each user, once it is assigned, it is a fixed value in a specific column of the database. If the database is exposed to an attacker, it poses a great threat to password cracking. In this paper, we suggest variable-dynamic Salt that dynamically changes according to the user's password during the login process. The variable-dynamic Salt can further enhance password security during login process by making it difficult to know what the Salt is, even if the database or source code is exposed.

• Smart Media Journal
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• v.11 no.3
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• pp.18-25
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• 2022

Neuromorphic computing generally shows significantly better power, area, and speed performance than neural network computation using CPU and GPU. These characteristics are suitable for resource-constrained IoT environments where energy consumption is important. However, there is a problem in that it is necessary to modify the source code for environment setting and application operation according to heterogeneous IoT devices that support neuromorphic computing. To solve these problems, NAAL was proposed and implemented in this paper. NAAL provides functions necessary for IoT device control and neuromorphic architecture abstraction and inference model operation in various heterogeneous IoT device environments based on common APIs of NAAL. NAAL has the advantage of enabling additional support for new heterogeneous IoT devices and neuromorphic architectures and computing devices in the future.