Perineuronal nets (PNNs) are lattice-like extracellular matrix structures composed of chondroitin sulfate proteoglycans (CSPGs). The appearance of PNNs parallels the decline of neural plasticity, and disruption of PNNs reactivates neural plasticity in the adult brain. We previously reported that sulfation patterns of chondroitin sulfate (CS) chains on CSPGs influenced the formation of PNNs and ...

Tujuan penelitian ini untuk mengklasifikasikan citra Songket Aceh. Data menggunakan sepuluh motif Aceh dan data diperoleh dari tempat usaha tenun Nyak Mu. Tahapan adalah akuisisi citra, pra-proses, ekstraksi fitur, klasifikasi evaluasi. Ekstraksi fitur tekstur metode Gray Level Co-occurrence Matrix (GLCM). Fitur-fitur yang digunakan pada entropy, energy, sum of squares: variance, difference ent...

This paper presents a new framework based on modified EMD method for detection of single and multiple PQ issues. In modified EMD, DWT precedes traditional EMD process. This scheme makes EMD better by eliminating the mode mixing problem. This is a two step algorithm; in the first step, input PQ signal is decomposed in low and high frequency components using DWT. In the second stage, the low freq...

There are some deficiencies in the improved three-ratio method even though it has been widely used in power transformer fault diagnosis. Using artificial neural networks, the power transformer fault diagnosis is improved in this article. With Matlab programming, three different kinds of neural networks, which are Radial Basis Function (RBF) neural network, Learning Vector Quantization (LVQ) neu...

Article history: Received July 20, 2011 Accepted 7 October 2011 Available online 8 October 2011 The purpose of this paper is to predict the S&P500 down moves with technical analysis indicators using learning vector quantization (LVQ) neural networks and probabilistic neural networks (PNN). In addition, entropy-based input selection technique is employed to improve the prediction accuracies. The...

The application of chemometrics to analyze the information of the cis/trans structure of alkenes in infrared spectra (IR) is introduced. For data from the OMNIC IR spectral database, two feature selection methods, Fisher ratios and genetic algorithm-partial least squares (GA-PLS), and two classification methods, support vector machine (SVM) and probabilistic neural network (PNN), have been used...

In this paper, we propose another version of help-training approach by employing a Probabilistic Neural Network (PNN) that improves the performance of the main discriminative classifier in the semi-supervised strategy. We introduce the PNN-training algorithm and use it for training the support vector machine (SVM) with a few numbers of labeled data and a large number of unlabeled data. We try t...

This paper presents the combination of advanced signal processing techniques and the machine intelligence approach to classify the power quality events. The Wavelet Transform (WT) and the S – Transform (ST) are utilized to extract the important useful features of the disturbance signal. The features extracted by using the above approaches are used to train a PNN classifier for automatic classif...

Using protein stitchery with appropriate attachment of cysteines linking to either C or N termini of the basic region of the v-Jun leucine zipper gene-regulatory protein, we constructed three dimers--pCC, pCN, and pNN. All three bind specifically to the appropriately rearranged DNA recognition sites for v-Jun: ATGAcgTCAT, ATGAcgATGA, and TCATcgTCAT, respectively (Kd, approximately 4 nM at 4 deg...