Search results for "vector [form factor]"

2020

Human movements are characterized by highly non-linear and multi-dimensional interactions within the motor system. Recently, an increasing emphasis on machine-learning applications has led to a significant contribution to the field of gait analysis, e.g., in increasing the classification performance. In order to ensure the generalizability of the machine-learning models, different data preprocessing steps are usually carried out to process the measured raw data before the classifications. In the past, various methods have been used for each of these preprocessing steps. However, there are hardly any standard procedures or rather systematic comparisons of these different methods and their im…

Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies

2016

Mieth, Bettina et al.

LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs

2019

Abstract Novel 3D protein descriptors based on bilinear, quadratic and linear algebraic maps in R n are proposed. The latter employs the kth 2-tuple (dis) similarity matrix to codify information related to covalent and non-covalent interactions in these biopolymers. The calculation of the inter-amino acid distances is generalized by using several dis-similarity coefficients, where normalization procedures based on the simple stochastic and mutual probability schemes are applied. A new local-fragment approach based on amino acid-types and amino acid-groups is proposed to characterize regions of interest in proteins. Topological and geometric macromolecular cutoffs are defined using local and…

Characterization of Bacillus thuringiensis isolates by their insecticidal activity and their production of Cry and Vip3 proteins.

2018

WOS: 000449027600099 PubMed ID: 30383811 Bacillus thuringiensis (Bt) constitutes the active ingredient of many successful bioinsecticides used in agriculture. In the present study, the genetic diversity and toxicity of Bt isolates was investigated by characterization of native isolates originating from soil, fig leaves and fruits from a Turkish collection. Among a total of 80 Bt isolates, 18 of them were found carrying a vip3 gene (in 23% of total), which were further selected. Insecticidal activity of spore/crystal mixtures and their supernatants showed that some of the Bt isolates had significantly more toxicity against some lepidopteran species than the HD1 reference strain. Five isolate…

Defining classifier regions for WSD ensembles using word space features

2006

Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…

Building an Optimal WSD Ensemble Using Per-Word Selection of Best System

2006

In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method c…

Housing market shocks in italy: A GVAR approach

2020

Abstract In this paper, we use a Global Vector Autoregression (GVAR) model to assess the spatio-temporal mechanism of house price spillovers, also known as “ripple effect”, among 93 Italian provincial housing markets, over the period 2004 − 2016 . In order to better capture the local housing market dynamics, we use data not only on house prices but also on transaction volumes. In particular, we focus on estimating, to what extent, exogenous shocks, interpreted as negative housing demand shocks, arising from 10 Italian regional capitals, impact on their house prices and sales and how these shocks spill over to neighbours housing markets. The negative housing market demand shock hitting the G…

Cell state prediction through distributed estimation of transmit power

2019

Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of…

Attention-based Model for Evaluating the Complexity of Sentences in English Language

2020

The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…

Quenching of gA deduced from the β-spectrum shape of 113Cd measured with the COBRA experiment

2020

A dedicated study of the quenching of the weak axial-vector coupling strength gA in nuclear processes has been performed by the COBRA collaboration. This investigation is driven by nuclear model calculations which show that the β-spectrum shape of the fourfold forbidden non-unique decay of 113Cd strongly depends on the effective value of gA. Using an array of CdZnTe semiconductor detectors, 45 independent 113Cd spectra were obtained and interpreted in the context of three nuclear models. The resulting effective mean values are g‾A(ISM)=0.915±0.007, g‾A(MQPM)=0.911±0.013 and g‾A(IBFM-2)=0.955±0.022. These values agree well within the determined uncertainties and deviate significantly from th…