• Molecules and Cells
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• v.40 no.9
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• pp.685-695
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• 2017

Obesity and the metabolic disorders that constitute metabolic syndrome are a primary cause of morbidity and mortality in the world. Nonetheless, the changes in the proteins and the underlying molecular pathways involved in the relevant pathogenesis are poorly understood. In this study a proteomic analysis of the visceral adipose tissue isolated from metabolically healthy and unhealthy obese patients was used to identify presence of altered pathway(s) leading to metabolic dysfunction. Samples were obtained from 18 obese patients undergoing bariatric surgery and were subdivided into two groups based on the presence or absence of comorbidities as defined by the International Diabetes Federation. Two dimensional difference in-gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was carried out. A total of 28 proteins were identified with a statistically significant difference in abundance and a 1.5-fold change (ANOVA, $p{\leq}0.05$) between the groups. 11 proteins showed increased abundance while 17 proteins were decreased in the metabolically unhealthy obese compared to the healthy obese. The differentially expressed proteins belonged broadly to three functional categories: (i) protein and lipid metabolism (ii) cytoskeleton and (iii) regulation of other metabolic processes. Network analysis by Ingenuity pathway analysis identified the $NF{\kappa}B$, IRK/MAPK and PKC as the nodes with the highest connections within the connectivity map. The top network pathway identified in our protein data set related to cellular movement, hematological system development and function, and immune cell trafficking. The VAT proteome between the two groups differed substantially between the groups which could potentially be the reason for metabolic dysfunction.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.64-75
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• 2018

With the development of location-aware technologies and the activation of smart phones, location based social networks(LBSN) have been activated to allow people to easily share their location. In particular, studies on recommending the location of user interests by using the user check-in function in LBSN have been actively conducted. In this paper, we propose a location recommendation scheme considering time and user activities in LBSN. The proposed scheme considers user preference changes over time, local experts, and user interest in rare places. In other words, it uses the check-in history over time and distinguishes the user activity area to identify local experts. It also considers a rare place to give a weight to the user preferred place. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Biomolecules & Therapeutics
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• v.27 no.3
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• pp.302-310
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• 2019

Melanoma cells have been shown to respond to BRAF inhibitors; however, intrinsic and acquired resistance limits their clinical application. In this study, we performed RNA-Seq analysis with BRAF inhibitor-sensitive (A375P) and -resistant (A375P/Mdr with acquired resistance and SK-MEL-2 with intrinsic resistance) melanoma cell lines, to reveal the genes and pathways potentially involved in intrinsic and acquired resistance to BRAF inhibitors. A total of 546 differentially expressed genes (DEGs), including 239 up-regulated and 307 down-regulated genes, were identified in both intrinsic and acquired resistant cells. Gene ontology (GO) analysis revealed that the top 10 biological processes associated with these genes included angiogenesis, immune response, cell adhesion, antigen processing and presentation, extracellular matrix organization, osteoblast differentiation, collagen catabolic process, viral entry into host cell, cell migration, and positive regulation of protein kinase B signaling. In addition, using the PAN-THER GO classification system, we showed that the highest enriched GOs targeted by the 546 DEGs were responses to cellular processes (ontology: biological process), binding (ontology: molecular function), and cell subcellular localization (ontology: cellular component). Ingenuity pathway analysis (IPA) network analysis showed a network that was common to two BRAF inhibitorresistant cells. Taken together, the present study may provide a useful platform to further reveal biological processes associated with BRAF inhibitor resistance, and present areas for therapeutic tool development to overcome BRAF inhibitor resistance.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.375-380
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• 2022

The purpose of this study is to find out consumers' perception and meaning of convenience store convenience food by using big data. For this study, NNAVER and Daum analyzed news, intellectuals, blogs, cafes, intellectuals(tips), and web documents, and used 'convenience store convenience food' as keywords for data search. The data analysis period was selected as 3 years from January 1, 2019 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted using TEXTOM, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, convenience store convenience foods were clustered into health, diversity, convenience, and economy according to consumers' selection attributes. It is expected to be the basis for the development of a new convenience menu that pursues convenience and convenience based on consumers' meaning of convenience store convenience foods such as appropriate prices, discount coupons, and events.

• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.196-204
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• 2010

With the completion of genome sequencing of several organisms, attention has been focused to determine the function and functional network of proteins by proteome analysis. The recent techniques of proteomics have been advanced quickly so that the high-throughput and systematic analyses of cellular proteins are enabled in combination with bioinformatics tools. Furthermore, the development of proteomic techniques helps to elucidate the functions of proteins under stress or diseased condition, resulting in the discovery of biomarkers responsible for the biological stimuli. Ultimate goal of proteomics orients toward the entire proteome of life, subcellular localization, biochemical activities, and their regulation. Comprehensive analysis strategies of proteomics can be classified as three categories: (i) protein separation by 2-dimensional gel electrophoresis (2-DE) or liquid chromatography (LC), (ii) protein identification by either Edman sequencing or mass spectrometry (MS), and (iii) quanitation of proteome. Currently MS-based proteomics turns shiftly from qualitative proteome analysis by 2-DE or 2D-LC coupled with off-line matrix assisted laser desorption ionization (MALDI) and on-line electrospray ionization (ESI) MS, respectively, to quantitative proteome analysis. Some new techniques which include top-down mass spectrometry and tandem affinity purification have emerged. The in vitro quantitative proteomic techniques include differential gel electrophoresis with fluorescence dyes, protein-labeling tagging with isotope-coded affinity tag, and peptide-labeling tagging with isobaric tags for relative and absolute quantitation. In addition, stable isotope labeled amino acid can be in vivo labeled into live culture cells through metabolic incorporation. MS-based proteomics extends to detect the phosphopeptide mapping of biologically crucial protein known as one of post-translational modification. These complementary proteomic techniques contribute to not only the understanding of basic biological function but also the application to the applied sciences for industry.

• Corrosion Science and Technology
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• v.9 no.4
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• pp.147-152
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• 2010

Conventional paints for conversion coating applications in steel production derived mainly from water-based polymer dispersions containing several additives actually show good general performance, but suffer from poor scratch and abrasion resistance during use. The reason for this is because the relatively soft organic binder matrix dominates the mechanical surface properties. In order to maintain the high quality and decorative function of coated steel sheets, the mechanical performance of the surface needs to be improved significantly. In fact the wear resistance should be enhanced without affecting the optical appearance of the coatings by using appropriate nanoparticulate additives. In this direction, nanocomposite coating compositions (Nanomer$^{(R)}$) have been derived from water-based polymer dispersions with an increasing amount of surface-modified nanoparticles in aqueous dispersion in order to monitor the effect of degree of filling with rigid nanoparticles. The surface of nanoparticles has been modified for optimum compatibility with the polymer matrix in order to achieve homogeneous nanoparticle dispersion over the matrix. This approach has been extended in such a way that a more expanded hybrid network has been condensed on the nanoparticle surface by a hydrolytic condensation reaction in addition to the quasi-monolayer type small molecular surface modification. It was expected that this additional modification will lead to more intensive cross-linking in coating systems resulting in further improved scratch-resistance compared to simple addition of nanoparticles with quasi-monolayer surface modification. The resulting compositions have been coated on zinc-galvanized steel and cured. The wear resistance and the corrosion protection of the modified coating systems have been tested in dependence on the compositional change, the type of surface modification as well as the mixing conditions with different shear forces. It has been found out that for loading levels up to 50 wt.-% nanoparticles, the mechanical wear resistance remains almost unaffected compared to the unmodified resin. In addition, the corrosion resistance remained unaffected even after $180^{\circ}$ bending test showing that the flexibility of coating was not decreased by nanoparticle addition. Electron microscopy showed that the inorganic nanoparticles do not penetrate into the organic resin droplets during the mixing process but rather formed agglomerates outside the polymer droplet phase resulting in quite moderate cross linking while curing, because of viscosity. The proposed mechanisms of composite formation and cross linking could explain the poor effect regarding improvement of mechanical wear resistance and help to set up new synthesis strategies for improved nanocomposite morphologies, which should provide increased wear resistance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1C
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• pp.89-96
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• 2012

Since tactical robots are going to be grown and tactical data communications will be more network-centric, the reliability of wireless tactical data networks is going to be very important in the future. However, the connectivity of such wireless tactical data networks can be extremely uncertain in practical circumstances. In this paper, we propose a searching technique to find out the weak boundary area of the network connectivity using a small UAV(unmanned aerial vehicle) which has a simple polling access function to wireless nodes on the ground in wireless tactical data networks. The UA V calculates the network topology of the wireless tactical data networks and coverts it to the Lapalcian matrix. In the proposed algorithm, we iteratively search the eigenvalues and find a minimum cut in the network resulting in finding the weak boundary of the connectivity for the wireless tactical data networks. If a UAV works as a relay nodes for the weak area, we evaluate that the throughput performance of the proposed algorithm outperforms star connection method and MST(minimum Spanning Tree) connection method. The proposed algorithm can be applied for recovering the connectivity of wireless tactical data networks.

• Convergence Security Journal
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• v.15 no.5
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• pp.29-35
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• 2015

The network security encryption type is divided into two, one is point-to-point, second method is link type. The level of security quality attributes are a system security quality requirements in a networked environment. Quality attributes can be observed and should be able to be measured. If the quality requirements can be presented as exact figures, quality requirements are defined specifically setting quality objectives. Functional requirements in the quality attribute is a requirement for a service function which can be obtained through the encryption. Non-functional requirements are requirements of the service quality that can be obtained through the encryption. Encryption quality evaluation system proposed in this study is to derive functional requirements and non-functional requirements 2 groups. Of the calculating measure of the evaluation index in the same category, the associated indication of the quality measure of each surface should be created. The quality matrix uses 2-factor analysis of the evaluation for the associated surface quality measurements. The quality requirements are calculated based on two different functional requirements and non-functional requirements. The results are calculated by analyzing the trend of the average value assessment. When used this way, it is possible to configure the network security encryption based on quality management.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.27-36
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• 2004

Detection and recognition of human faces in images can be considered as an important aspect for applications that involve interaction between human and computer. In this paper, we propose a face recognition method using eigenfaces and fuzzy neural networks. The Principal Components Analysis (PCA) is one of the most successful technique that have been used to recognize faces in images. In this technique the eigenvectors (eigenfaces) and eigenvalues of an image is extracted from a covariance matrix which is constructed form image database. Face recognition is Performed by projecting an unknown image into the subspace spanned by the eigenfaces and by comparing its position in the face space with the positions of known indivisuals. Based on this technique, we propose a new algorithm for face recognition consisting of 5 steps including preprocessing, eigenfaces generation, design of fuzzy membership function, training of neural network, and recognition. First, each face image in the face database is preprocessed and eigenfaces are created. Fuzzy membership degrees are assigned to 135 eigenface weights, and these membership degrees are then inputted to a neural network to be trained. After training, the output value of the neural network is intupreted as the degree of face closeness to each face in the training database.