• Genomics & Informatics
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• v.9 no.1
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• pp.39-43
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• 2011

MicroRNAs (miRNAs) are recently discovered small RNA molecules usually resulting in translational repression and gene silencing. Despite the fact that specific cloning of small RNA's is a method in practice, computational identification of miRNA's has been a major focus recent days, since is a rapid process following AB initio and sequence alignment methods. Here we developed new software called MiRPI that aims to identify the highly conserved miRNAs without any mismatches from given fasta formatted gene sequences by using non-repeated miRNA dataset of the user's interest. The new window embedded with the software is used to identify the targets for inputted mature miRNAs in the mRNA sequences. Also MiRPI is designed to measure the precursor miRNA statistics, majorly focusing the Adjusted Minimum Folding free Energy (AMFE) and Minimum Folding free Energy Index (MFEI), the most important parameters in miRNA confirmation. MiRPI is developed by PERL (Practical Extraction and Report Language) and Tk (Tool kit widgets) scripting languages. It is user friendly, portable offline software that works in all windows OS, sized to 3 MB.

• Structural Engineering and Mechanics
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• v.38 no.3
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• pp.349-359
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• 2011

Input excitation and output response of structure are needed in conventional modal analysis methods. However, input excitation is often difficult to be obtained in the dynamic load test of bridge structures. Therefore, what attracts engineers' attention is how to get dynamic parameters from the output response. In this paper, a structural experimental modal analysis method is introduced, which can be used to conveniently obtain dynamic parameters of the structure from the free decay response. With known damping coefficients, this analysis method can be used to identify the natural frequencies and the mode shapes of MDOF structures. Based on the modal analysis theory, the mathematical relationship of damping ratio and frequency is obtained. By using this mathematical relationship to improve the previous method, an improved experimental modal analysis method is proposed in this paper. This improved method can overcome the deficiencies of the previous method, which can not identify damping ratios and requires damping coefficients in advance. Additionally, this improved method can also identify the natural frequencies, mode shapes and damping ratios of the bridge only from the free decay response, and ensure the stability of identification process by using modern mathematical means. Finally, the feasibility and effectiveness of this method are demonstrated by a numerical example of a simply supported reinforced concrete beam.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.5
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• pp.94-100
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• 2003

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of detect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode But, in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion own. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.354-361
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• 2015

The building energy audit is an important process when collecting basic information for improving the energy performance of existing buildings. Audit parameters should be associated with the energy performance of the building. Such audit parameters will vary according to an individual building's characteristics and energy consumption patterns, but most building energy audits are performed in the same way. The sensitivity analysis (SA) is a statistical method to quantify the correlation between inputs and outputs that can determine which input is influential to which output. Therefore, an SA can identify influential parameters when applied to building energy analysis. In this paper, we adopted the Morris method to identify building energy audit parameters and performed a Monte Carlo simulation for uncertainty analysis. As a result, this method was able to identify an influential parameter for building energy audits and reduce uncertainty in energy consumption in buildings.

• YAKHAK HOEJI
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• v.52 no.5
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• pp.407-411
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• 2008

Phosphorylation plays the most important role in cell signaling mechanism. Various methods to identify the phosphorylation sites of proteins using tandem mass spectrometry (MS/MS) have been reported recently. Furthermore, the enrichment strategy such as Titanium dioxide ($TiO_2$) method should be combined with MS/MS analysis to effectively identify phosphorylation sites. It is necessary to optimize phosphopeptide-enrichment strategy, $TiO_2$ method in this study, due to the low amount of phosphorylated form followed by analyzing them by MS/MS. To evaluate the several conditions to enrich phosphopeptides using $TiO_2$ method, we used ${\apha}$-casein as a standard phosphoprotein and analyzed a representative phosphopeptide (VPQLEIVPNpSAEER) peak of MS spectrum. Batch is better than column method for binding and 300 g/l DHB in loading buffer is better than lower concentration of DHB. 3% TFA and pH 10.5 shows high efficiency of phosphopeptide-enrichment for washing and elution steps, respectively. Finally we identified various efficient conditions of phosphopeptide-enrichment method using $TiO_2$. This optimized method would assist in reliable identifying thousands of phosphorylation sites existed in low abundance from various complex proteins.

• The Journal of Information Systems
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• v.18 no.2
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• pp.35-59
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• 2009

The study of Information Systems(IS) is a relatively new discipline area, thus an analysis of the latest research literature could be useful to identify what the researchers are doing and what can be done to improve our discipline. With that purpose in mind, this study analyzes the total 208 articles published in "The Journal of Information Systems~ between 2001 and 2008. The classification system that comprises three key characteristics of diversity (research topic, research method, and reference discipline) was developed based on a review of prior literature. The results of this study were also compared with Kim et al.(2005)'s and Vessey et al.(2002)'s results to identify issues in current Information Systems research and 10 suggest some recommendations for future In formation Systems research. The findings identify popular research topic:s, the dominant research method, and reference discipline. The popular research topics consists of organizational concepts, problem domain-specific concepts, and systems/software management concepts. Field study was characterized as the dominant research method in the papers included in the study. Information Systems itself represents the major theoretical reference of the studies. However, many papers in this study relied on a number of reference disciplines., none of which was dominant, or they did not rely on a specific reference discipline. Finally, this study suggests more research on the disciplinary issues, more training on the research method, more accurate and specific reference discipline, and controlled diversity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• Water Engineering Research
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• v.7 no.1
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• pp.21-28
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• 2006

The scouring process is complex and subject to many factors. Recently, experiments for real-time bridge scour monitoring have been active as means for a more reliable scour prediction. Riverbed materials are an important factor in bridge scouring; therefore, an accurate estimation of riverbed material is critical in predicting a scour. As a part of this approach, an ultrasonic sensor, which can not only detect river bottom during floods but can also be installed lose to the underwater structures, was developed. This sensor is able to map the river bottom using an ultrasonic waves with the characteristics of the returning wave, reflected from an object or bottom ground. The reflected wave is unique according to the situations, or materials below. Therefore, it would be possible to identify the consisting materials of a riverbed if we could reveal each characteristic in the received signals. In this study, a preliminary experiment was performed in the laboratory to identify and classify received signals, which is unique to each material. The analysis of this experiment gives the graph, which makes it possible to identify materials of the river bottom through the ultrasonic signals. The proposed graph was verified through a comparison with the actual field data measured in river.

• KIEAE Journal
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• v.16 no.4
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• pp.21-30
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• 2016

Purpose: Energy saving in the built facilities is getting important due to energy crisis. The Korea government has been implemented several energy and green building policies and practices. The both of government and industry also developed green building strategies ant technologies to reduce energy consumption and carbon emission. The purpose of this research is to identify applicable green building strategies and technologies for that can be cost effective and applicable to a multiplex house. Method: This research identified appropriate green building strategies from analysing green building strategies from G-SEED certified apartment projects and popular green building strategies. This study also adopted a survey research method to find out the applicable green building strategies for a multiplex housing. In addition, this research also conduct cost estimating to identify initial cost premium of green building strategies. Results: The research outcomes in this study guide a building owner to know about initial cost premiums of green building strategies and technologies and an architect and contractor to identify appropriate and cost effective green building strategies that can be applicable to a multiplex house.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1655-1664
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• 2013

Recently, it becomes essential to forecast the future and identify emerging technologies in order to improve R&D efficiency and gain a competitive advantage under rapidly changing environment of science and technology. Therefore this research aims to identify the future and emerging technologies especially for the industry and applied it to list top ten emerging technologies. In this study, we identify research fronts across all areas of science and technology through verifying and comparing the 2008 and the 2012 surge in research activities. Finally we detect rapidly increasing 10 promising technology areas. This research results are expected to provide valuable information to support stragegic and policy decision making.