Multiclass classification of Parkinson’s disease using different classifiers and LLBFS feature selection algorithm

Since approximately 90% of the people with PD (Parkinson’s disease) suffer from speech disorders including disorders of laryngeal, respiratory and articulatory function, using voice analysis disease can be diagnosed remotely at an early stage with more reliability and in an economic way. All previous works are done to distinguish healthy people from people with Parkinson’s disease (PWP). In this paper, we propose to go further by multiclass classification with three classes of Parkinson stages and healthy control. So we have used 40 features dataset, all the features are analyzed and 9 features are selected to classify PWP subjects in four classes, based on unified Parkinson’s disease Rating Scale (UPDRS). Various classifiers are used and their comparison is done to find out which one gives the best results. Results show that the subspace discriminant reach more than 93% overall classification accuracy.     

Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation

In this paper we present a CNN based approach for a real time 3D-hand pose estimation from the depth sequence. Prior discriminative approaches have achieved remarkable success but are facing two main challenges: Firstly, the methods are fully supervised hence require large numbers of annotated training data to extract the dynamic information from a hand representation. Secondly, unreliable hand detectors based on strong assumptions or a weak detector which often fail in several situations like complex environment and multiple hands. In contrast to these methods, this paper presents an approach that can be considered as semi-supervised by performing predictive coding of image sequences of hand poses in order to capture latent features underlying a given image without supervision. The hand is modelled using a novel latent tree dependency model (LDTM) which transforms internal joint location to an explicit representation. Then the modeled hand topology is integrated with the pose estimator using data dependent method to jointly learn latent variables of the posterior pose appearance and the pose configuration respectively. Finally, an unsupervised error term which is a part of the recurrent architecture ensures smooth estimations of the final pose. Experiments on three challenging public datasets, ICVL, MSRA, and NYU demonstrate the significant performance of the proposed method which is comparable or better than state-of-the-art approaches.      

A taxonomy of argumentation models used for knowledge representation

Understanding argumentation and its role in human reasoning has been a continuous subject of investigation for scholars from the ancient Greek philosophers to current researchers in philosophy, logic and artificial intelligence. In recent years, argumentation models have been used in different areas such as knowledge representation, explanation, proof elaboration, commonsense reasoning, logic programming, legal reasoning, decision making, and negotiation. However, these models address quite specific needs and there is need for a conceptual framework that would organize and compare existing argumentation-based models and methods. Such a framework would be very useful especially for researchers and practitioners who want to select appropriate argumentation models or techniques to be incorporated in new software systems with argumentation capabilities. In this paper, we propose such a conceptual framework, based on taxonomy of the most important argumentation models, approaches and systems found in the literature. This framework highlights the similarities and differences between these argumentation models. As an illustration of the practical use of this framework, we present a case study which shows how we used this framework to select and enrich an argumentation model in a knowledge acquisition project which aimed at representing argumentative knowledge contained in texts critiquing military courses of action.     

Infrastructure Deployment in Vehicular Communication Networks Using a Parallel Multiobjective Evolutionary Algorithm

This article describes the application of a multiobjective evolutionary algorithm for locating roadside infrastructure for vehicular communication networks over realistic urban areas. A multiobjective formulation of the problem is introduced, considering quality‐of‐service and cost objectives. The experimental analysis is performed over a real map of Málaga, using real traffic information and antennas, and scenarios that model different combinations of traffic patterns and applications (text/audio/video) in the communications. The proposed multiobjective evolutionary algorithm computes accurate trade‐off solutions, significantly improving over state‐of‐the‐art algorithms previously applied to the problem.     

Spent potliner treatment process optimization using a MADS algorithm

In this paper, the general problem of chemical process optimization defined by a computer simulation is formulated. It is generally a nonlinear, non-convex, non-differentiable optimization problem over a disconnected set. A brief overview of popular optimization methods from the chemical engineering literature is presented. The recent mesh adaptive direct search (MADS) algorithm is detailed. It is a direct search algorithm, so it uses only function values and does not compute or approximate derivatives. This is useful when the functions are noisy, costly or undefined at some points, or when derivatives are unavailable or unusable. In this work, the MADS algorithm is used to optimize a spent potliners (toxic wastes from aluminum production) treatment process. In comparison with the best previously known objective function value, a 37% reduction is obtained even if the model failed to return a value 43% of the time.     

The Effect of the Relief Wave on the Uniformity of an Air Blast Load

In most blast loading structure analyses, it is assumed that the load acts uniformly on a target area. For the rationable design, it is useful to have a quantitative criterion to determine at which maximum distance the standoff can be placed to assume a uniform pressure distribution. Surprisingly, no standard criterion was found in the literature and the effect of blast wave clearing was not considered as well. In this paper, pressure histories applied on structures are calculated considering the non‐uniform loading characteristic as well as pressure relief from the edges. Additionally, the effects of various parameters on uniformity of impulse distribution are investigated. The results have shown that the effect of pressure relief on impulse uniformity is very important, especially when the blast wave is attenuated. This phenomenon leads an optimum distance at which impulse distribution is the most uniform.     

Polymer negative birefringence films for compensation of twisted nematic devices

Compensation of the liquid crystal layer within twisted nematic displays operating in normally white and normally black modes was examined. Studies of commercially available compensation films allowed us to develop the optimum compensating configuration for normally white displays including negative C-plates, discotic splay layers and A-plates. The optimum compensation of the normally black display mode was achieved using a stack of A-plates. The compensation provides a wide viewing cone and no gray-scale inversion in the most important viewing directions for both optimized display types. The compensated devices exhibit an achromatic dark state.     

Low-bias performance of avalanche photodetector. A time-domainapproach

The performance of the InP-InGaAs avalanche photodiode (APD) at low bias voltages has been investigated directly from its impulse response without using any fitting parameters. The important mechanisms responsible for low-bias performance are the emission of holes from the InP-InGaAs interface potential-trap in the valence band, the velocity of the carriers, and the diffusion of photogenerated holes from the undepleted region to the depleted region of the absorption layer. A time-recurrence relation for the emission of holes from the trap has been derived and special attention has been paid to the velocity of carriers at low fields. The delay in the process of diffusion of photogenerated holes has been taken into account in obtaining the impulse response. The bandwidth at different gains have been calculated by taking the fast Fourier transform (FFT) of the current impulse response. The gain-bias and gain-bandwidth characteristics show reasonably good agreement between the data from the model and the experimental data of an earlier published work on InP-InGaAs APD