Selective Feature Generation Method for Classification of Low-Dimensional Data

We propose a method that generates input features to effectively classify low-dimensional data. To do this, we first generate high-order terms for the input features of the original low-dimensional data to form a candidate set of new input features. Then, the discrimination power of the candidate input features is quantitatively evaluated by calculating the ‘discrimination distance’ for each candidate feature. As a result, only candidates with a large amount of discriminative information are selected to create a new input feature vector, and the discriminant features that are to be used as input to the classifier are extracted from the new input feature vectors by using a subspace discriminant analysis. Experiments on low-dimensional data sets in the UCI machine learning repository and several kinds of low-resolution facial image data show that the proposed method improves the classification performance of low-dimensional data by generating features

Dynamical mean-field theory of Hubbard-Holstein model at half-filling: Zero temperature metal-insulator and insulator-insulator transitions

We study the Hubbard-Holstein model, which includes both the electron-electron and electron-phonon interactions characterized by $U$ and $g$, respectively, employing the dynamical mean-field theory combined with Wilson's numerical renormalization group technique. A zero temperature phase diagram of metal-insulator and insulator-insulator transitions at half-filling is mapped out which exhibits the interplay between $U$ and $g$. As $U$ ($g$) is increased, a metal to Mott-Hubbard insulator (bipolaron insulator) transition occurs, and the two insulating states are distinct and can not be adiabatically connected. The nature of and transitions between the three states are discussed.Comment: 5 pages, 4 figures. Submitted to Physical Review Letter

Automatic classification using concept knowledge of web documents

In order to classify web documents, we suggest a method using concept knowledge of category.In our study, the concept relations between keywords are extracted using hyperlink information and after the extracted keywords are classified into each category, these are used as an index.Then TFIDF for each category is extended to determine index weight value.The system is constructed for experimenting and estimating,which is consist of web robot, indexer, concept knowledge database for each category and the document classifier.Our system to be applied the extended TFIDF method shows an accuracy of 88% in automatic classifying of web documents

Transmission Electron Microscopy (TEM) Sample Preparation of Si(1-x)Gex in c-Plane Sapphire Substrate

The National Aeronautics and Space Administration-invented X-ray diffraction (XRD) methods, including the total defect density measurement method and the spatial wafer mapping method, have confirmed super hetero epitaxy growth for rhombohedral single crystalline silicon germanium (Si1-xGex) on a c-plane sapphire substrate. However, the XRD method cannot observe the surface morphology or roughness because of the method s limited resolution. Therefore the authors used transmission electron microscopy (TEM) with samples prepared in two ways, the focused ion beam (FIB) method and the tripod method to study the structure between Si1-xGex and sapphire substrate and Si1?xGex itself. The sample preparation for TEM should be as fast as possible so that the sample should contain few or no artifacts induced by the preparation. The standard sample preparation method of mechanical polishing often requires a relatively long ion milling time (several hours), which increases the probability of inducing defects into the sample. The TEM sampling of the Si1-xGex on sapphire is also difficult because of the sapphire s high hardness and mechanical instability. The FIB method and the tripod method eliminate both problems when performing a cross-section TEM sampling of Si1-xGex on c-plane sapphire, which shows the surface morphology, the interface between film and substrate, and the crystal structure of the film. This paper explains the FIB sampling method and the tripod sampling method, and why sampling Si1-xGex, on a sapphire substrate with TEM, is necessary

Inhibitory effect of a tyrosine-fructose Maillard reaction product, 2,4-bis(p-hydroxyphenyl)-2-butenal on amyloid-β generation and inflammatory reactions via inhibition of NF-κB and STAT3 activation in cultured astrocytes and microglial BV-2 cells

<p>Abstract</p> <p>Background</p> <p>Amyloidogenesis is linked to neuroinflammation. The tyrosine-fructose Maillard reaction product, 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal, possesses anti-inflammatory properties in cultured macrophages, and in an arthritis animal model. Because astrocytes and microglia are responsible for amyloidogenesis and inflammatory reactions in the brain, we investigated the anti-inflammatory and anti-amyloidogenic effects of 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal in lipopolysaccharide (LPS)-stimulated astrocytes and microglial BV-2 cells.</p> <p>Methods</p> <p>Cultured astrocytes and microglial BV-2 cells were treated with LPS (1 μg/ml) for 24 h, in the presence (1, 2, 5 μM) or absence of 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal, and harvested. We performed molecular biological analyses to determine the levels of inflammatory and amyloid-related proteins and molecules, cytokines, Aβ, and secretases activity. Nuclear factor-kappa B (NF-κB) DNA binding activity was determined using gel mobility shift assays.</p> <p>Results</p> <p>We found that 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal (1, 2, 5 μM) suppresses the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) as well as the production of nitric oxide (NO), reactive oxygen species (ROS), tumor necrosis factor-α (TNF-α), and interleukin-1β (IL-1β) in LPS (1 μg/ml)-stimulated astrocytes and microglial BV-2 cells. Further, 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal inhibited the transcriptional and DNA binding activity of NF-κB--a transcription factor that regulates genes involved in neuroinflammation and amyloidogenesis via inhibition of IκB degradation as well as nuclear translocation of p50 and p65. Consistent with the inhibitory effect on inflammatory reactions, 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal inhibited LPS-elevated Aβ₄₂levels through attenuation of β- and γ-secretase activities. Moreover, studies using signal transducer and activator of transcription 3 (STAT3) siRNA and a pharmacological inhibitor showed that 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal inhibits LPS-induced activation of STAT3.</p> <p>Conclusions</p> <p>These results indicate that 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal inhibits neuroinflammatory reactions and amyloidogenesis through inhibition of NF-κB and STAT3 activation, and suggest that 2,4-bis(<it>p</it>-hydroxyphenyl)-2-butenal may be useful for the treatment of neuroinflammatory diseases like Alzheimer's disease.</p

Effect of Total Leaf Numbers on the Growth and Fruit Quality in Muskmelon Plants Showing Leaf Yellowing Symptoms

This study was conducted to evaluate the influence of total leaf numbers on the growth, net formation of fruits, and occurrence of leaf yellowing symptoms (LYS) in muskmelon plants. The growth and development of LYS on muskmelon plants having 25, 30, and 35 fully expanded leaves on the vine were compared to those of the control plant having 20 leaves. Plant height, leaf area, root fresh weight, and root dry weight increased as the number of leaves increased. Plants with 35 leaves showed the greatest plant growth. Net photosynthetic rate was positively related to increasing leaf numbers with plants having over 25 leaves showing the greatest photosynthetic rates. On the other hand, there were no significant differences in chlorophyll content and root activity among treatments with different leaf numbers. The ratio of LYS infection was also greater in plants having 25-30 leaves, than in those having leaf numbers. Plants with different leaf numbers and LYS infection showed a variation in fruit quality, although LYS did not significantly affect fruit quality except net index. The plants having 20 leaves that showed LYS developed fruits that had significantly smaller flesh (mesocarp) thickness than, the plants having greater numbers of leaves. The higher sugar contents of fruits were found in the plants having 35 leaves whether they showed LYS (12.1°Bx) or not (12.5°Bx). Therefore, leaving more than 25 healthy leaves per plant was recommended for minimizing damage from LYS.OAIID:oai:osos.snu.ac.kr:snu2015-01/104/0000027607/11ADJUST_YN:NEMP_ID:A075898DEPT_CD:517CITE_RATE:0FILENAME:(이희주)effect_of_total_leaf_numbers_on_the_growth_and_fruit_quality_in_muskmelon_plants_showing_leaf_yell··.pdfDEPT_NM:식물생산과학부CONFIRM: