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.

Image Segment Matching Using Affine- Invariant Regions

In this paper, a method for matching image segments using triangle-based (geometrical) regions is proposed. Triangular regions are formed from triples of vertex points obtained from a keypoint detector (SIFT). However, triangle regions are subject to noise and distortion around the edges and vertices (especially acute angles). Therefore, these triangles are expanded into parallelogramshaped regions. The extracted image segments inherit an important triangle property; the invariance to affine distortion. Given two images, matching corresponding regions is conducted by computing the relative affine matrix, rectifying one of the regions w.r.t. the other one, then calculating the similarity between the reference and rectified region. The experimental tests show the efficiency and robustness of the proposed algorithm against geometrical distortion.

Cascade Kalman Filter Configuration for Low Cost IMU/GPS Integration in Car Navigation Like Robot

This paper introduces a low cost INS/GPS algorithm for land vehicle navigation application. The data fusion process is done with an extended Kalman filter in cascade configuration mode. In order to perform numerical simulations, MATLAB software has been developed. Loosely coupled configuration is considered. The results obtained in this work demonstrate that a low-cost INS/GPS navigation system is partially capable of meeting the performance requirements for land vehicle navigation. The relative effectiveness of the kalman filter implementation in integrated GPS/INS navigation algorithm is highlighted. The paper also provides experimental results; field test using a car is carried out.

An Assessment of Food Control System and Development Perspective: The Case of Myanmar

Food control measures are critical in fostering food safety management of a nation. However, no academic study has been undertaken to assess the food control system of Myanmar up to now. The objective of this research paper was to assess the food control system with in depth examination of five key components using desktop analysis and short survey from related food safety program organizations including regulators and inspectors. Study showed that the existing food control system is conventional, mainly focusing on primary health care approach while relying on reactive measures. The achievements of food control work have been limited to a certain extent due to insufficienttechnical capacity that is needed to upgrade staffs, laboratory equipment and technical assistance etc. associated with various sectors. Assessing food control measures is the first step in the integration of food safety management, this paper could assist policy makers in providing information for enhancing the safety and quality of food produced and consumed in Myanmar.

Experimental Study on Gas-Viscous Liquid Mixture Flow Regimes and Transitions Criteria in Vertical Narrow Rectangular Channels

In the study the influence of the physical-chemical properties of a liquid, the width of a channel gap and the superficial liquid and gas velocities on the patterns formed during two phase flows in vertical, narrow mini-channels was investigated. The research was performed in the channels of rectangular cross-section and of dimensions: 15 x 0.65 mm and 7.5 x 0.73 mm. The experimental data were compared with the published criteria of the transitions between the patterns of two-phase flows.

Delay Specific Investigations on QoS Scheduling Schemes for Real-Time Traffic in Packet Switched Networks

Packet switched data network like Internet, which has traditionally supported throughput sensitive applications such as email and file transfer, is increasingly supporting delay-sensitive multimedia applications such as interactive video. These delaysensitive applications would often rather sacrifice some throughput for better delay. Unfortunately, the current packet switched network does not offer choices, but instead provides monolithic best-effort service to all applications. This paper evaluates Class Based Queuing (CBQ), Coordinated Earliest Deadline First (CEDF), Weighted Switch Deficit Round Robin (WSDRR) and RED-Boston scheduling schemes that is sensitive to delay bound expectations for variety of real time applications and an enhancement of WSDRR is proposed.

Numerical Study of Iterative Methods for the Solution of the Dirichlet-Neumann Map for Linear Elliptic PDEs on Regular Polygon Domains

A generalized Dirichlet to Neumann map is one of the main aspects characterizing a recently introduced method for analyzing linear elliptic PDEs, through which it became possible to couple known and unknown components of the solution on the boundary of the domain without solving on its interior. For its numerical solution, a well conditioned quadratically convergent sine-Collocation method was developed, which yielded a linear system of equations with the diagonal blocks of its associated coefficient matrix being point diagonal. This structural property, among others, initiated interest for the employment of iterative methods for its solution. In this work we present a conclusive numerical study for the behavior of classical (Jacobi and Gauss-Seidel) and Krylov subspace (GMRES and Bi-CGSTAB) iterative methods when they are applied for the solution of the Dirichlet to Neumann map associated with the Laplace-s equation on regular polygons with the same boundary conditions on all edges.

Fast Calculation for Particle Interactions in SPH Simulations: Outlined Sub-domain Technique

A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.

Development of Reliable Web-Based Laboratories for Developing Countries

In online context, the design and implementation of effective remote laboratories environment is highly challenging on account of hardware and software needs. This paper presents the remote laboratory software framework modified from ilab shared architecture (ISA). The ISA is a framework which enables students to remotely acccess and control experimental hardware using internet infrastructure. The need for remote laboratories came after experiencing problems imposed by traditional laboratories. Among them are: the high cost of laboratory equipment, scarcity of space, scarcity of technical personnel along with the restricted university budget creates a significant bottleneck on building required laboratory experiments. The solution to these problems is to build web-accessible laboratories. Remote laboratories allow students and educators to interact with real laboratory equipment located anywhere in the world at anytime. Recently, many universities and other educational institutions especially in third world countries rely on simulations because they do not afford the experimental equipment they require to their students. Remote laboratories enable users to get real data from real-time hand-on experiments. To implement many remote laboratories, the system architecture should be flexible, understandable and easy to implement, so that different laboratories with different hardware can be deployed easily. The modifications were made to enable developers to add more equipment in ISA framework and to attract the new developers to develop many online laboratories.

Flour and Bread Quality of Spring Spelt

The article contains results of the flour and bread quality assessment from the grains of spring spelt, also called as an ancient wheat. Spelt was cultivated on heavy and medium soils observing principles of organic farming. Based on flour and bread laboratory studies, as well as laboratory baking, the technological usefulness of studied flour has been determined. These results were referred to the standard derived from common wheat cultivated in the same conditions. Grain of spring spelt is a good raw material for manufacturing bread flour, from which to get high-quality bakery products, but this is strictly dependent on the variety of ancient wheat.

Synthesis and Characterization of Plasma Polymerized Thin Films Deposited from Benzene and Hexamethyldisiloxane using (PECVD) Method

Polymer-like organic thin films were deposited on both aluminum alloy type 6061 and glass substrates at room temperature by Plasma Enhanced Chemical Vapor Deposition (PECVD) methodusing benzene and hexamethyldisiloxane (HMDSO) as precursor materials. The surface and physical properties of plasma-polymerized organic thin films were investigated at different r.f. powers. The effects of benzene/argon ratio on the properties of plasma polymerized benzene films were also investigated. It is found that using benzene alone results in a non-coherent and non-adherent powdery deposited material. The chemical structure and surface properties of the asgrown plasma polymerized thin films were analyzed on glass substrates with FTIR and contact angle measurements. FTIR spectra of benzene deposited film indicated that the benzene rings are preserved when increasing benzene ratio and/or decreasing r.f. powers. FTIR spectra of HMDSO deposited films indicated an increase of the hydrogen concentration and a decrease of the oxygen concentration with the increase of r.f. power. The contact angle (θ) of the films prepared from benzene was found to increase by about 43% as benzene ratio increases from 10% to 20%. θ was then found to decrease to the original value (51°) when the benzene ratio increases to 100%. The contact angle, θ, for both benzene and HMDSO deposited films were found to increase with r.f. power. This signifies that the plasma polymerized organic films have substantially low surface energy as the r.f power increases. The corrosion resistance of aluminum alloy substrate both bare and covered with plasma polymerized thin films was carried out by potentiodynamic polarization measurements in standard 3.5 wt. % NaCl solution at room temperature. The results indicate that the benzene and HMDSO deposited films are suitable for protection of the aluminum substrate against corrosion. The changes in the processing parameters seem to have a strong influence on the film protective ability. Surface roughness of films deposited on aluminum alloy substrate was investigated using scanning electron microscopy (SEM). The SEM images indicate that the surface roughness of benzene deposited films increase with decreasing the benzene ratio. SEM images of benzene and HMDSO deposited films indicate that the surface roughness decreases with increasing r.f. power. Studying the above parameters indicate that the films produced are suitable for specific practical applications.

Compressed Adobe Technology Analyses as Local Sustainable Materials for Retrofitting against Earthquake Approaching India Experiences

Due to its geographical location, Iran is considered one of the earthquake-prone areas where the best way to decrease earthquake effects is supposed to be strengthening the buildings. Even though, one idea suggests that the use of adobe in constructing buildings be prohibited for its weak function especially in earthquake-prone areas, however, regarding ecological considerations, sustainability and other local skills, another idea pays special attention to adobe as one of the construction technologies which is popular among people. From the architectural and technological point of view, as strong sustainable building construction materials, compressed adobe construction materials make most of the construction in urban or rural areas ranging from small to big industrial buildings used to replace common earth blocks in traditional systems and strengthen traditional adobe buildings especially against earthquake. Mentioning efficient construction using compressed adobe system as a reliable replacement for traditional soil construction materials , this article focuses on the experiences of India in the fields of sustainable development of compressed adobe systems in the form of system in which the compressed soil is combined with cement, load bearing building with brick/solid concrete block system, brick system using rat trap bond, metal system with adobe infill and finally emphasizes on the use of these systems in the earthquake-struck city of Bam in Iran.

Hourly Electricity Load Forecasting: An Empirical Application to the Italian Railways

Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly electricity load curve of the Italian railways. The results of the analysis confirm the accuracy of the two models and therefore the relevance of forecasting inside public utilities.

Pt(IV) Complexes with Polystrene-bound Schiff Bases as Antimicrobial Agent: Synthesis and Characterization

Novel polystrene-bound Schiff bases and their Pt(IV) complexes have been prepared from condensation reaction of polystyrene-A-NH2 with 2-hydroxybenzaldehyde and 5-fluoro-3- bromo-2-hydroxybenzaldehyde. The structures of Pt(IV) complexes with polystyrene including Schiff bases have been determined by elemental analyses, magnetic susceptibility, IR, 1H-NMR, UV-vis, TG/DTA and AAS. The antibacterial and antifungal activities of the synthesized compounds have been studied by the well-diffusion method against some selected microorganisms: (Bacillus cereus spp., Listeria monocytogenes 4b, Micrococcus luteus, Staphylococcus aureus, Staphylococcus epidermis, Brucella abortus, Escherichia coli, Pseudomonas putida spp., Shigella dysenteria type 10, Salmonella typhi H).

A Virtual Reality Laboratory for Distance Education in Chemistry

Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.

A New Hybrid Model with Passive Congregation for Stock Market Indices Prediction

In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.

Efficient Numerical Model for Studying Bridge Pier Collapse in Floods

High level and high velocity flood flows are potentially harmful to bridge piers as evidenced in many toppled piers, and among them the single-column piers were considered as the most vulnerable. The flood flow characteristic parameters including drag coefficient, scouring and vortex shedding are built into a pier-flood interaction model to investigate structural safety against flood hazards considering the effects of local scouring, hydrodynamic forces, and vortex induced resonance vibrations. By extracting the pier-flood simulation results embedded in a neural networks code, two cases of pier toppling occurred in typhoon days were reexamined: (1) a bridge overcome by flash flood near a mountain side; (2) a bridge washed off in flood across a wide channel near the estuary. The modeling procedures and simulations are capable of identifying the probable causes for the tumbled bridge piers during heavy floods, which include the excessive pier bending moments and resonance in structural vibrations.

A New Method for Extracting Ocean Wave Energy Utilizing the Wave Shoaling Phenomenon

Fossil fuels are the major source to meet the world energy requirements but its rapidly diminishing rate and adverse effects on our ecological system are of major concern. Renewable energy utilization is the need of time to meet the future challenges. Ocean energy is the one of these promising energy resources. Threefourths of the earth-s surface is covered by the oceans. This enormous energy resource is contained in the oceans- waters, the air above the oceans, and the land beneath them. The renewable energy source of ocean mainly is contained in waves, ocean current and offshore solar energy. Very fewer efforts have been made to harness this reliable and predictable resource. Harnessing of ocean energy needs detail knowledge of underlying mathematical governing equation and their analysis. With the advent of extra ordinary computational resources it is now possible to predict the wave climatology in lab simulation. Several techniques have been developed mostly stem from numerical analysis of Navier Stokes equations. This paper presents a brief over view of such mathematical model and tools to understand and analyze the wave climatology. Models of 1st, 2nd and 3rd generations have been developed to estimate the wave characteristics to assess the power potential. A brief overview of available wave energy technologies is also given. A novel concept of on-shore wave energy extraction method is also presented at the end. The concept is based upon total energy conservation, where energy of wave is transferred to the flexible converter to increase its kinetic energy. Squeezing action by the external pressure on the converter body results in increase velocities at discharge section. High velocity head then can be used for energy storage or for direct utility of power generation. This converter utilizes the both potential and kinetic energy of the waves and designed for on-shore or near-shore application. Increased wave height at the shore due to shoaling effects increases the potential energy of the waves which is converted to renewable energy. This approach will result in economic wave energy converter due to near shore installation and more dense waves due to shoaling. Method will be more efficient because of tapping both potential and kinetic energy of the waves.

Text Mining Technique for Data Mining Application

Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In decision tree approach is most useful in classification problem. With this technique, tree is constructed to model the classification process. There are two basic steps in the technique: building the tree and applying the tree to the database. This paper describes a proposed C5.0 classifier that performs rulesets, cross validation and boosting for original C5.0 in order to reduce the optimization of error ratio. The feasibility and the benefits of the proposed approach are demonstrated by means of medial data set like hypothyroid. It is shown that, the performance of a classifier on the training cases from which it was constructed gives a poor estimate by sampling or using a separate test file, either way, the classifier is evaluated on cases that were not used to build and evaluate the classifier are both are large. If the cases in hypothyroid.data and hypothyroid.test were to be shuffled and divided into a new 2772 case training set and a 1000 case test set, C5.0 might construct a different classifier with a lower or higher error rate on the test cases. An important feature of see5 is its ability to classifiers called rulesets. The ruleset has an error rate 0.5 % on the test cases. The standard errors of the means provide an estimate of the variability of results. One way to get a more reliable estimate of predictive is by f-fold –cross- validation. The error rate of a classifier produced from all the cases is estimated as the ratio of the total number of errors on the hold-out cases to the total number of cases. The Boost option with x trials instructs See5 to construct up to x classifiers in this manner. Trials over numerous datasets, large and small, show that on average 10-classifier boosting reduces the error rate for test cases by about 25%.

A Hidden Markov Model for Modeling Pavement Deterioration under Incomplete Monitoring Data

In this paper, the potential use of an exponential hidden Markov model to model a hidden pavement deterioration process, i.e. one that is not directly measurable, is investigated. It is assumed that the evolution of the physical condition, which is the hidden process, and the evolution of the values of pavement distress indicators, can be adequately described using discrete condition states and modeled as a Markov processes. It is also assumed that condition data can be collected by visual inspections over time and represented continuously using an exponential distribution. The advantage of using such a model in decision making process is illustrated through an empirical study using real world data.