Search results for "Intelligence"
showing 10 items of 6959 documents
Drug Activity Characterization Using One-Class Support Vector Machines with Counterexamples
2013
The problem of detecting chemical activity in drugs from its molecular description constitutes a challenging and hard learning task. The corresponding prediction problem can be tackled either as a binary classification problem (active versus inactive compounds) or as a one class problem. The first option leads usually to better prediction results when measured over small and fixed databases while the second could potentially lead to a much better characterization of the active class which could be more important in more realistic settings. In this paper, a comparison of these two options is presented when support vector models are used as predictors.
Microstructure–property relation and machine learning prediction of hole expansion capacity of high-strength steels
2021
Abstract The relationship between microstructure features and mechanical properties plays an important role in the design of materials and improvement of properties. Hole expansion capacity plays a fundamental role in defining the formability of metal sheets. Due to the complexity of the experimental procedure of testing hole expansion capacity, where many influencing factors contribute to the resulting values, the relationship between microstructure features and hole expansion capacity and the complexity of this relation is not yet fully understood. In the present study, an experimental dataset containing the phase constituents of 55 microstructures as well as corresponding properties, su…
Fingerprints from fingerprints
2003
Besides ‘‘classical’’ biological materials such as blood and sperm, epithelial cells from latent fingerprints are targeted in forensic sciences. In addition to studies using latent fingerprints applied to beer glasses [1], T-shirts left on crime scenes [2] and various other objects [3], we report the detection of STR profiles from latent fingerprints deposited on ordinary sheets of paper. In contrast to the relatively high number of epithelial cells from saliva or from excessively pressured fingerprints during strangulation [4,5], the experiments with latent fingerprints are expected to generate only a very small number of epithelial cells. Moreover, cells remaining on objects touched only …
Evaluation of olfactory intensity : comparative study of two methods
2004
Two experimental procedures recommended for the evaluation of the psychophysical characteristics of odorous compounds, olfactory matching with the 1-butanol scale and cross-modality matching with the finger span are compared. The intensity of ethyl butyrate and guaiacol solutions presented at four different concentration levels was evaluated by a panel of sixteen subjects over five repetitions using the two methods. Each stimulus was delivered to the subject from a Teflon bag through a nose-shaped glass sniffing port. The discrimination ability, repeatability, panel homogeneity and within-subject variability of the methods were assessed. Results indicate that with both methods, subjects wer…
Emotional Intelligence in Child Molesters
2020
Various studies have examined intelligent quotients (IQs) in samples of pedophiles and child molesters. However, intelligence is not a monolithic construct; rather, it is made up of different dimen...
Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion
2020
Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning val…
A computer program suitable for analysis of choice of categories in biomedical data recognition problems.
1980
The optimum choice of categories in problems of medical data recognition is governed by the choice of categories, the selection of appropriate features, and by the choice of a loss function. Under these circumstances it is often difficult to find out the suitable classification scheme. The computer program described here serves for the design of the optimum recognition procedure. The Bayes rule is used as decision rule. A criterion for the comparison of different choice of categories is given. The program can be performed after estimation of the underlying prior probabilities and the conditional densities obtained from a training set, and before testing the decision rule with real data.
An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments
2014
In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one-to-one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks eve…
Automatic detection of large dense-core vesicles in secretory cells and statistical analysis of their intracellular distribution.
2010
Analyzing the morphological appearance and the spatial distribution of large dense-core vesicles (granules) in the cell cytoplasm is central to the understanding of regulated exocytosis. This paper is concerned with the automatic detection of granules and the statistical analysis of their spatial locations in different cell groups. We model the locations of granules of a given cell as a realization of a finite spatial point process and the point patterns associated with the cell groups as replicated point patterns of different spatial point processes. First, an algorithm to segment the granules using electron microscopy images is proposed. Second, the relative locations of the granules with…
Identification of Key Gin Aroma Compounds
2014
Potential impact aroma compounds of gin have been identified using Gas Chromatogry Olfactometry Mass-Spectrometry (GC-O-MS). In order to select some of them for a recombination study, we developed a specific procedure. Instead of only choosing the compounds on criteria such as their odor quality or their odor activity values, we also used physico-chemical parameters and information on their botanical origin. Data were organized in blocks homogeneous in terms of parameter type. Different statistical treatments were used in order to classify the compounds either by analyzing the parameters altogether or separately block by block.