Voice Disorders Identification Using Hybrid Approach: Wavelet Analysis and Multilayer Neural Networks

This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standard values thanks to a programmable database. Sounds are collected from normal people and patients, and then classified into two different categories. Speech data base is consists of several pathological and normal voices collected from the national hospital “Rabta-Tunis". Speech processing algorithm is conducted in a supervised mode for discrimination of normal and pathology voices and then for classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Designing and Implementing an Innovative Course about World Wide Web, Based on the Conceptual Representations of Students

Internet is nowadays included to all National Curriculums of the elementary school. A comparative study of their goals leads to the conclusion that a complete curriculum should aim to student-s acquisition of the abilities to navigate and search for information and additionally to emphasize on the evaluation of the information provided by the World Wide Web. In a constructivistic knowledge framework the design of a course has to take under consideration the conceptual representations of students. The following paper presents the conceptual representation of students of eleven years old, attending the Sixth Grade of Greek Elementary School about World Wide Web and their use in the design and implementation of an innovative course.

Characterization and Development of Anthropomorphic Phantoms Liver for Use in Nuclear Medicine

The objective this study was to characterize and develop anthropomorphic liver phantoms in tomography hepatic procedures for quality control and improvement professionals in nuclear medicine. For the conformation of the anthropomorphic phantom was used in plaster and acrylic. We constructed three phantoms representing processes with liver cirrhosis. The phantoms were filled with 99mTc diluted with water to obtain the scintigraphic images. Tomography images were analyzed anterior and posterior phantom representing a body with a greater degree cirrhotic. It was noted that the phantoms allow the acquisition of images similar to real liver with cirrhosis. Simulations of hemangiomas may contribute to continued professional education of nuclear medicine, on the question of image acquisition, allowing of the study parameters such of the matrix, energy window and count statistics.

Performance Analysis of an Adaptive Threshold Hybrid Double-Dwell System with Antenna Diversity for Acquisition in DS-CDMA Systems

In this paper, we consider the analysis of the acquisition process for a hybrid double-dwell system with antenna diversity for DS-CDMA (direct sequence-code division multiple access) using an adaptive threshold. Acquisition systems with a fixed threshold value are unable to adapt to fast varying mobile communications environments and may result in a high false alarm rate, and/or low detection probability. Therefore, we propose an adaptively varying threshold scheme through the use of a cellaveraging constant false alarm rate (CA-CFAR) algorithm, which is well known in the field of radar detection. We derive exact expressions for the probabilities of detection and false alarm in Rayleigh fading channels. The mean acquisition time of the system under consideration is also derived. The performance of the system is analyzed and compared to that of a hybrid single dwell system.

A Computer Model of Language Acquisition – Syllable Learning – Based on Hebbian Cell Assemblies and Reinforcement Learning

Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.

Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device

The purpose of this paper is to present a Dynamic Time Warping technique which reduces significantly the data processing time and memory size of multi-dimensional time series sampled by the biometric smart pen device BiSP. The acquisition device is a novel ballpoint pen equipped with a diversity of sensors for monitoring the kinematics and dynamics of handwriting movement. The DTW algorithm has been applied for time series analysis of five different sensor channels providing pressure, acceleration and tilt data of the pen generated during handwriting on a paper pad. But the standard DTW has processing time and memory space problems which limit its practical use for online handwriting recognition. To face with this problem the DTW has been applied to the sum of the five sensor signals after an adequate down-sampling of the data. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of performance in single character and word recognition. Further excellent accuracy in recognition was achieved which is mainly due to the reduced dynamic time warping RDTW technique and a novel pen device BiSP.

Stereotype Student Model for an Adaptive e-Learning System

This paper describes a concept of stereotype student model in adaptive knowledge acquisition e-learning system. Defined knowledge stereotypes are based on student's proficiency level and on Bloom's knowledge taxonomy. The teacher module is responsible for the whole adaptivity process: the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. The adaptation of courseware is realized according to student-s knowledge stereotype.

A New Failure Analysis for Maintenance Management in Complex Hospitals

management of medical devices in hospitals includes the planning of medical equipment acquisition and maintenance. The presence of critical and non-critical areas together with technological proliferation render the management of medical devices very complex. This study creates an easy and objective methodology for the analysis of medical equipment maintenance, that makes the management of medical devices more feasible. The study has been carried out at Florence Hospital Careggi and it aims to help the clinical engineering department to manage medical equipment by clarifying the hospital situation through a characterization of the different areas, technologies and fault typologies.

Design, Modeling and Fabrication of a Tactile Sensor and Display System for Application in Laparoscopic Surgery

One of the major disadvantages of the minimally invasive surgery (MIS) is the lack of tactile feedback to the surgeon. In order to identify and avoid any damage to the grasped complex tissue by endoscopic graspers, it is important to measure the local softness of tissue during MIS. One way to display the measured softness to the surgeon is a graphical method. In this paper, a new tactile sensor has been reported. The tactile sensor consists of an array of four softness sensors, which are integrated into the jaws of a modified commercial endoscopic grasper. Each individual softness sensor consists of two piezoelectric polymer Polyvinylidene Fluoride (PVDF) films, which are positioned below a rigid and a compliant cylinder. The compliant cylinder is fabricated using a micro molding technique. The combination of output voltages from PVDF films is used to determine the softness of the grasped object. The theoretical analysis of the sensor is also presented. A method has been developed with the aim of reproducing the tactile softness to the surgeon by using a graphical method. In this approach, the proposed system, including the interfacing and the data acquisition card, receives signals from the array of softness sensors. After the signals are processed, the tactile information is displayed by means of a color coding method. It is shown that the degrees of softness of the grasped objects/tissues can be visually differentiated and displayed on a monitor.

Iterative Way to Acquire Information Technology for Defense and Aerospace

Defense and Aerospace environment is continuously striving to keep up with increasingly sophisticated Information Technology (IT) in order to remain effective in today-s dynamic and unpredictable threat environment. This makes IT one of the largest and fastest growing expenses of Defense. Hundreds of millions of dollars spent a year on IT projects. But, too many of those millions are wasted on costly mistakes. Systems that do not work properly, new components that are not compatible with old ones, trendy new applications that do not really satisfy defense needs or lost through poorly managed contracts. This paper investigates and compiles the effective strategies that aim to end exasperation with low returns and high cost of Information Technology acquisition for defense; it tries to show how to maximize value while reducing time and expenditure.

Totally Integrated Smart Energy System through Data Acquisition via Remote Location

This paper discusses the approach of real-time controlling of the energy management system using the data acquisition tool of LabVIEW. The main idea of this inspiration was to interface the Station (PC) with the system and publish the data on internet using LabVIEW. In this venture, controlling and switching of 3 phase AC loads are effectively and efficiently done. The phases are also sensed through devices. In case of any failure the attached generator starts functioning automatically. The computer sends command to the system and system respond to the request. The modern feature is to access and control the system world-wide using world wide web (internet). This controlling can be done at any time from anywhere to effectively use the energy especially in developing countries where energy management is a big problem. In this system totally integrated devices are used to operate via remote location.

Information System for Data Selection and New Information Acquisition for Reconfigurable Multifunctional Machine Tools

The purpose of the paper is to develop an informationcontrol environment for overall management and self-reconfiguration of the reconfigurable multifunctional machine tool for machining both rotation and prismatic parts and high concentration of different technological operations - turning, milling, drilling, grinding, etc. For the realization of this purpose on the basis of defined sub-processes for the implementation of the technological process, architecture of the information-search system for machine control is suggested. By using the object-oriented method, a structure and organization of the search system based on agents and manager with central control are developed. Thus conditions for identification of available information in DBs, self-reconfiguration of technological system and entire control of the reconfigurable multifunctional machine tool are created.

Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Social Networks and Absorptive Capacity

The resource-based view of the firm regards knowledge as one of the most important organizational assets and a key strategic resource that contributes unique value to organizations. The acquisition, absorption and internalization of external knowledge are central to an organization-s innovative capabilities. This ability to evaluate, acquire and integrate new knowledge from its environment is referred to as a firm-s absorptive capacity (AC). This research in progress paper explores the link between interorganizational Social Networks (SNs) and a firm-s Absorptive Capacity (AC). Based on an in-depth literature survey of both concepts, four propositions are proposed that explain the link between AC and SNs. These propositions suggest that SNs are key to a firm-s AC. A qualitative research method is proposed to test the set of propositions in the next stage of this research.

Non-Invasive Technology on a Classroom Chair for Detection of Emotions Used for the Personalization of Learning Resources

Emotions are related with learning processes and physiological signals can be used to detect them for the personalization of learning resources and to control the pace of instruction. A model of relevant emotions has been developed, where specific combinations of emotions and cognition processes are connected and integrated with the concept of 'flow', in order to improve learning. The cardiac pulse is a reliable signal that carries useful information about the subject-s emotional condition; it is detected using a classroom chair adapted with non invasive EMFi sensor and an acquisition system that generates a ballistocardiogram (BCG), the signal is processed by an algorithm to obtain characteristics that match a specific emotional condition. The complete chair system is presented in this work, along with a framework for the personalization of learning resources.

A Side-Peak Cancellation Scheme for CBOC Code Acquisition

In this paper, we propose a side-peak cancellation scheme for code acquisition of composite binary offset carrier (CBOC) signals. We first model the family of CBOC signals in a generic form, and then, propose a side-peak cancellation scheme by combining correlation functions between the divided sub-carrier and received signals. From numerical results, it is shown that the proposed scheme removes the side-peak completely, and moreover, the resulting correlation function demonstrates the better power ratio performance than the CBOC autocorrelation.

Investigation of the Tattooed Skin by OCT

The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Entropy based Expeditive Methodology for Rating Curves Assessment

The river flow forecasting represents a crucial point to employ for improving a management policy addressed to the right use of water resources as well as for conjugating prevention and defense actions against environmental degradation. The difficulties occurring during the field activities encourage the development and implementation of operative computation and measuring methods addressed to time reduction for data acquisition and processing maintaining a good level of accuracy. Therefore, the aim of the present work is to test a new entropy based expeditive methodology for the evaluation of the rating curves on three gauged sections with different geometric and morphological characteristics. The methodology requires the choice of only three verticals along the measure section and the sampling of only the maximum velocity. The results underline how in most conditions the rating curves drawn can replace those built with classic methodologies, simplifying thus the procedures of data monitoring and calculation.

The Experimental and Numerical Analysis of a Lightpipe using a Simulation Software

A lightpipe is an about 99 percent specular reflective mirror pipe or duct that is used for the transmission of the daylight from the outside into a building. The lightpipes are usually used in the daylighting buildings, in the residential, industrial and commercial sectors. This paper is about the performances of a lightpipe installed in a laboratory (3 m x 2.6 m x 3 m) without windows. The aim is to analyse the luminous intensity distribution for several sky/sun conditions. The lightpipe was monitored during the year 2006. The lightpipe is 1 m long and the diameter of the top collector and of the internal diffuser device is 0.25 m. In the laboratory there are seven illuminance sensors: one external is located on the roof of the laboratory and six internal sensors are connected to a data acquisition system. The internal sensors are positioned under the internal diffusive device at an height of 0.85 m from the floor to simulate a working plane. The numerical data are obtained through a simulation software. This paper shows the comparison between the experimental and numerical results concerning the behavior of the lightpipe.

Color View Synthesis for Animated Depth Security X-ray Imaging

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.