Trajectory compression is widely used in spatial-temporal databases as it can notably reduce (i) the computation/communication load of clients (GPS-enabled mobile devices) and (ii) the storage cost of servers. Compared with original trajectories, compressed trajectories have clear advantages in data processing, transmitting, storing, etc. In this paper, we investigate a novel problem of searchi...

Well placement and control scheme optimization is crucial for hydrocarbon, groundwater geothermal development, generally involves a large number of discrete correlated decision variables. Meta-heuristic algorithms have showed good performance in solving complex, nonlinear non-continuous problems. However, numerical simulation runs are involved during the process. In this work, novel efficient d...

Chondroitin sulfate (CS) proteoglycans in perineuronal nets (PNNs) from the central nervous system (CNS) are involved in the control of plasticity and memory. Removing PNNs reactivates plasticity and restores memory in models of Alzheimer's disease and ageing. Their actions depend on the glycosaminoglycan (GAG) chains of CS proteoglycans, which are mainly sulfated in the 4 (C4S) or 6 (C6S) posi...

Clustering of a data set can be done by the well-known Pairwise Nearest Neighbor (PNN) algorithm. The algorithm is conceptionally very simple and gives high quality solutions. A drawback of the method is the relatively large running time of the original (exact) implementation. Recently, an efficient version of the exact PNN algorithm has been introduced in literature. In this paper we give a fa...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...

This paper presents the application of Probabilistic Neural Networks (PNN) for the classification automatic detection of QRS-complexes in Electrocardiogram (ECG). Raw ECG signal contains the power line interference and baseline wander. This can be removed by using Digital filtering techniques. For the QRS-detection, Probabilistic Neural Networks is used as pattern classifier. MATLAB is applied ...

We propose a method for indoor versus outdoor scene classification using a probabilistic neural network (PNN). The scene is initially segmented (unsupervised) using fuzzy C-means clustering (FCM) and features based on color, texture, and shape are extracted from each of the image segments. The image is thus represented by a feature set, with a separate feature vector for each image segment. As ...

Cardioinhibitory cardiac vagal neurons (CVNs) do not receive inspiratory-related excitatory inputs under normal conditions. However, excitatory purinergic and serotonergic pathways are recruited during inspiratory activity after episodes of hypoxia and hypercapnia (H/H). Prenatal nicotine (PNN) exposure is known to dramatically change cardiorespiratory responses and decrease the ability to resu...

Fault diagnosis is essential for the reliable, safe, and efficient operation of the plant and for maintaining quality of the products in industrial system. This paper presents an ensemble fault diagnosis algorithm based on fuzzy c-means algorithm (FCM) with the Optimal Number of Clusters (ONC) and probabilistic neural network (PNN), called FCM-ONC-PNN. In clustering methods, the estimation of t...

Classifying power quality (PQ) disturbances is one of the most important issues for power quality control. A novel high-performance classification system based on the S-transform and a probabilistic neural network (PNN) is proposed. The original power quality signals are analysed by the S-transform and processed into a complex matrix named the S-matrix. Eighteen types of time–frequency features...