• Journal of Plant Biotechnology
• /
• v.37 no.2
• /
• pp.144-152
• /
• 2010

As the International Rice Genome Sequencing Project (IRGSP) was completed in 2005 and opened to the public, many countries are making a lot of investments in researches on the utilization of sequence information along with system development. Also, the necessity of the functional genomics researches using microarray is increased currently to secure unique genes related with major agricultural traits and analyze metabolic pathways. Microrarray enables efficient analysis of large scale gene expression and related transcription regulation. This review aims to introduce available microarrays made based on rice genome information and current status of gene expression analysis using these microarrays integrated with the databases available to the public. Also, we introduce the researches on the large scale functional analysis of genes related with useful traits and genetic networks. Understanding of the mechanism related with mutual interaction between proteins with co-expression among rice genes can be utilized in the researches for improving major agricultural traits. The direct and indirect interactions of various genes would provide new functionality of rice. The recent results of the various expression profiling analysis in rice will promote functional genomic researches in plants including rice and provide the scientists involved in applications researches with wide variety of expression informations.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.5
• /
• pp.1117-1127
• /
• 2017

With the advent of Internet of Things (IoT), the number of devices connected to Internet has rapidly increased, but the security for IoT is still vulnerable. It is difficult to integrate existing security technologies due to generating a large amount of traffic by using different protocols to use various IoT devices according to purposes and to operate in a low power environment. Therefore, in this paper, we propose a normal network behavior profiling method based on big data analysis techniques. The proposed method utilizes a Hadoop/Hive for Big Data analytics and an R for statistical computing. Also we verify the effectiveness of the proposed method through a simulation.

• Journal of Korea Technology Innovation Society
• /
• v.19 no.3
• /
• pp.511-544
• /
• 2016

Standards boost technological innovation by promoting information sharing, compatibility, stability and quality. Identifying groups of companies that particularly benefit from these functions of standards in their technological innovation and commercialization helps to customize planning and implementation of standards-related policies for demand groups. For this purpose, this study engages in profiling of SMEs whose R&D objective is to respond to standards as well as those who need to implement standards system for technological commercialization. Then it suggests a prediction model that can distinguish such companies from others. To this end, decision tree analysis is conducted for profiling of characteristics of subject SMEs through data mining. Subject SMEs include (1) those that engage in R&D to respond to standards (Group1) or (2) those in need of product standard or technological certification policies for commercialization purposes (Group 2). Then the study proposes a prediction model that can distinguish Groups 1 and 2 from others based on several variables by adopting discriminant analysis. The practicality of discriminant formula is statistically verified. The study suggests that Group 1 companies are distinguished in variables such as time spent on R&D planning, KoreanStandardIndustryClassification (KSIC) category, number of employees and novelty of technologies. Profiling result of Group 2 companies suggests that they are differentiated in variables such as KSIC category, major clients of the companies, time spent on R&D and ability to test and verify their technologies. The prediction model proposed herein is designed based on the outcomes of profiling and discriminant analysis. Its purpose is to serve in the planning or implementation processes of standards-related policies through providing objective information on companies in need of relevant support and thereby to enhance overall success rate of standards-related projects.

• Mass Spectrometry Letters
• /
• v.3 no.3
• /
• pp.74-77
• /
• 2012

Organic acid (OA) profiling analysis was performed in culture media from Lactobacillus pentosus K34 (L. pentosus K34) and Pediococcus lolli PL24 (P. lolli PL24) by gas chromatography-mass spectrometry (GC-MS) following methoxime/tert-butyldimethylsilyl derivatives. 12 OAs were positively identified in culture media. Most of OA levels from L. pentosus K34 of hetero lactic fermentation were found to be higher when compared with those from P. lolli PL24 of homo lactic fermentation, which may explain different OA metabolism in each strain. In addition, the distorted dodecagonal star patterns were readily distinguishable, and the characteristics of each strain were well represented. The present study demonstrates that the OA metabolic profiling method by GC-MS combined with star pattern recognition is useful for the monitoring study of characteristic OA metabolism in various microorganisms.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.6
• /
• pp.1067-1078
• /
• 2020

With the development of internet technology, a lot of content is produced, and the demand for it is increasing. Accordingly, the number of contents in circulation is increasing, while the number of distributing illegal copies that infringe on copyright is also increasing. The Korea Copyright Protection Agency operates a illegal content obstruction program based on substring matching, and it is difficult to accurately search because a large number of noises are inserted to bypass this. Recently, researches using natural language processing and AI deep learning technologies to remove noise and various blockchain technologies for copyright protection are being studied, but there are limitations. In this paper, noise is removed from data collected online, and keyword-based illegal copies are searched. In addition, the same heavy uploader is estimated through profiling analysis for heavy uploaders. In the future, it is expected that copyright damage will be minimized if the illegal copy search technology and blocking and response technology are combined based on the results of profiling analysis for heavy uploaders.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.19 no.2
• /
• pp.69-74
• /
• 2020

In this study, we proposed a method for surface profiling aspheric lens molds using a precision displacement sensor with a spatial scanning mechanism. The precision displacement sensor is based on the confocal principle using a broadband light source, providing a 10 nm resolution over a 0.3 mm measurable range. The precision of the sensor, depending on surface slope, was evaluated via Allan deviation analysis. We then developed an automatic surface profiling system by measuring the cross-sectional profile of a lens mold. The precision of the sensor at the flat surface was 10 nm at 10 ms averaging time, while 200 ms averaging time was needed for identical precision at the steepest slope at 25 deg. When we compared the measurement result of the lens mold to a commercial surface profiler, we found that the accuracy of the developed system was less than 90 nm (in terms of 3 sigmas of error) between the two results.

• ETRI Journal
• /
• v.42 no.2
• /
• pp.292-304
• /
• 2020

As side-channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side-channel analysis. However, a drawback of machine learning algorithms is that their performance depends on human engineering. Therefore, recent studies in the field focus on exploiting deep learning algorithms, which can extract features automatically from data. In this study, we survey recent advances in deep learning-based side-channel analysis. In particular, we outline how deep learning is applied to side-channel analysis, based on deep learning architectures and application methods. Furthermore, we describe its properties when using different architectures and application methods. Finally, we discuss our perspective on future research directions in this field.

• BMB Reports
• /
• v.44 no.5
• /
• pp.291-297
• /
• 2011

Aging is one of the most complicated biological processes in all species. A number of different model organisms from yeast to monkeys have been studied to understand the aging process. Until recently, many different age-related genes and age-regulating cellular pathways, such as insulin/IGF-1-like signal, mitochondrial dysfunction, Sir2 pathway, have been identified through classical genetic studies. Parallel to genetic approaches, genome-wide approaches have provided valuable insights for the understanding of molecular mechanisms occurring during aging. Gene expression profiling analysis can measure the transcriptional alteration of multiple genes in a genome simultaneously and is widely used to elucidate the mechanisms of complex biological pathways. Here, current global gene expression profiling studies on normal aging and age-related genetic/environmental interventions in widely-used model organisms are briefly reviewed.

• Genomics & Informatics
• /
• v.17 no.1
• /
• pp.8.1-8.10
• /
• 2019

Alveolar type II cells constitute a small fraction of the total lung cell mass. However, they play an important role in many cellular processes including trans-differentiation into type I cells as well as repair of lung injury in response to toxic chemicals and respiratory pathogens. Transcription factors are the regulatory proteins dynamically modulating DNA structure and gene expression. Transcription factor profiling in microarray datasets revealed that several members of AP1, ATF, $NF-{\kappa}B$, and C/EBP families involved in diverse responses were expressed in mouse lung type II cells. A transcriptional factor signature consisting of Cebpa, Srebf1, Stat3, Klf5, and Elf3 was identified in lung type II cells, Sox9+ pluripotent lung stem cells as well as in mouse lung development. Identification of the transcription factor profile in mouse lung type II cells will serve as a useful resource and facilitate the integrated analysis of signal transduction pathways and specific gene targets in a variety of physiological conditions.

• 한국약용작물학회:학술대회논문집
• /
• 2008.11a
• /
• pp.321-322
• /
• 2008