The identification and discrimination of 2 closely related and morphologically similar species of Gyrodactylus, G. salaris and G. thymalli, were assessed using the statistical classification methodologies Linear Discriminant Analysis (LDA) and k-Nearest Neighbours (KNN). These statistical methods were applied to morphometric measurements made on the gyrodactylid attachment hooks. The mean estim...

Lead free potassium sodium niobate (KNN) piezoceramics were synthesized via conventional solid state sintering route. Nano and micron WO3 were separately added to KNN through ball-milling. Dielectric and piezoelectric properties of samples sintered in the temperature range of 1110°-1145°C were measured by precision LCR-meter and APC d33-meter devices. The results revealed that micron WO3 partic...

The spiral angle of the elementary cellulose fibril in the wood cell wall, often called microfibril angle, (MFA). Microfibril angle in hardwood is one of the key determinants of solid timber performance due to its strong influence on the stiffness, strength, shrinkage, swelling, thermal-dynamics mechanical properties and dimensional stability of wood. Variation of MFA (degree) in the S2 layer o...

According to the defects of KNN(K-Nearest Neighbor) algorithm and SVM(Support Vector Machine) algorithm in tracking a moving target such the large consumption and the low accuracy of target tracking error, a tracking model of moving target is proposed based on the combination of KNN algorithm and SVM algorithm with minimum distance optimization. First categories divided according to the princip...

K-Nearest Neighbor (KNN) classification and regression are two widely used analytic methods in predictive modeling and data mining fields. They provide a way to model highly nonlinear decision boundaries, and to fulfill many other analytical tasks such as missing value imputation, local smoothing, etc. In this paper, we discuss ways in SAS R © to conduct KNN classification and KNN Regression. S...

In pattern recognition, a kind of classical classifier called k-nearest neighbor rule (kNN) has been applied to many real-life problems because of its good performance and simple algorithm. In kNN, a test sample is classified by a majority vote of its k-closest training samples. This approach has the following advantages: (1) It was proved that the error rate of kNN approaches the Bayes error w...

Most marine mammal- strandings coincident with naval sonar exercises have involved Cuvier's beaked whales (Ziphius cavirostris). We recorded animal movement and acoustic data on two tagged Ziphius and obtained the first direct measurements of behavioural responses of this species to mid-frequency active (MFA) sonar signals. Each recording included a 30-min playback (one 1.6-s simulated MFA sona...

The paper investigates the application of the Mean Field Annealing (MFA) approach to graph colouring using the Petford and Welsh algorithm as a Generalised Boltzmann Machine. The operation of the MFA algorithm for a Generalised Boltzmann Machine is characterised by the deenition of an appropriate energy function which the algorithm attempts to minimise. In the case of graph colouring a relation...

Mean field annealing(MFA) is a promising tool in optimization and a neural network model based on the graph matching have attracted attention due to a number of benefits over conventional recognition models. We present a neural network model for hand-written digits recognition using graph matching and two annealing techniques, MFA and one-variable stochastic simulated annealing(OSSA). OSSA make...

Contamination of magnetoencephalogram (MEG) records by various artifacts seriously influences the estimation accuracy of magnetic sources. Although some methods have been proposed to reject contaminated records [1][2], most of them are ineffective when artifacts models are not available. In this study, we proposed to classify MEG records into contaminated records and others by mixture of factor...