Automatic Diagnosis of Distortion Type of Arabic /r/ Phoneme Using Feed Forward Neural Network

The paper is not for recognizing normal formed speech but for distorted speech via examining the ability of feed forward Artificial Neural Networks (ANN) to recognize speech flaws. In this paper we take the Arabic /r/ phoneme distortion that is somewhat common among native speakers as a case study.To do this, r-Distype program is developed as a script written using Praat speech processing software tool. r-Distype program automatically develops a feed forward ANN that tests the spoken word (which includes /r/ phoneme) to detect any possible type of distortion. Multiple feed forward ANNs of different architectures have been developed and their achievements reported. Training data and testing data of the developed ANNs are sets of spoken Arabic words that contain /r/ phoneme in different positions so they cover all distortion types of Arabic /r/ phoneme. These sets of words were produced by different genders and different ages.The results obtained from developed ANNs were used to draw a conclusion about automating the detection of pronunciation problems in general.Such computerised system would be a good tool for diagnosing speech flaws and gives a great help in speech therapy. Also, the idea itself may open a new research subarea of speech recognition that is automatic speech therapy. Keywords: Distortion, Arabic /r/ phoneme, articulation disorders, Artificial Neural Network, Praa

The Definition of Intelligent Computer Aided Software Engineering (I-CASE) Tools

The growing complexity of the software systems being developed and the use of different methodologies indicate the need for more computer support for automating software development process and evolution activity. Currently, Computer-Aided Software Engineering (CASE), which is a set of software systems aimed to support set of software process activities, does this automation. While CASE tools prove its importance to develop high quality software, unfortunately CASE tools doesn’t cover all software development activities. This is because some activities need intellectual human skills, which are not currently available as computer software. To solve this shortcoming, Artificial Intelligence (AI) approaches are the ones that can be used to develop software tools imitating these intellectual skills. This paper presents the definition of Intelligent Computer Aided Software Engineering (I-CASE). The definition encompasses two steps. The first step is a clear decomposition of each basic software development activity to sub activities, and classify each one of them whether it is an intellectual or procedural job. The second step is the addressing of each intellectual (un-automated) one to proper AI-based approach. These tools may be integrated into a package as an Integrated Development Environment (IDE) or could be used individually. The discussion and the next implementation step are reported. Keywords: Software Engineering, CASE tools, Artificial Intelligenc

PAAD: POLITICAL ARABIC ARTICLES DATASET FOR AUTOMATIC TEXT CATEGORIZATION

Now day’s text Classification and Sentiment analysis is considered as one of the popular Natural Language Processing (NLP) tasks. This kind of technique plays significant role in human activities and has impact on the daily behaviours. Each article in different fields such as politics and business represent different opinions according to the writer tendency. A huge amount of data will be acquired through that differentiation. The capability to manage the political orientation of an online article automatically. Therefore, there is no corpus for political categorization was directed towards this task in Arabic, due to the lack of rich representative resources for training an Arabic text classifier. However, we introduce political Arabic articles dataset (PAAD) of textual data collected from newspapers, social network, general forum and ideology website. The dataset is 206 articles distributed into three categories as (Reform, Conservative and Revolutionary) that we offer to the research community on Arabic computational linguistics. We anticipate that this dataset would make a great aid for a variety of NLP tasks on Modern Standard Arabic, political text classification purposes. We present the data in raw form and excel file. Excel file will be in four types such as V1 raw data, V2 preprocessing, V3 root stemming and V4 light stemming

Carbon dioxide adsorption and interaction with formation fluids of Jordanian unconventional reservoirs

Shales are mostly unexploited energy resources. However, the extraction and production of their hydrocarbons require innovative methods. Applications involving carbon dioxide in shales could combine its potential use in oil recovery with its storage in view of its impact on global climate. The success of these approaches highly depends on various mechanisms taking place in the rock pores simultaneously. In this work, properties governing these mechanisms are presented at technically relevant conditions. The pendant and sessile drop methods are utilized to measure interfacial tension and wettability, respectively. The gravimetric method is used to quantify CO2 adsorption capacity of shale and gas adsorption kinetics is evaluated to determine diffusion coefficients. It is found that interfacial properties are strongly affected by the operating pressure. The oil-CO2 interfacial tension shows a decrease from approx. 21 mN/m at 0.1 MPa to around 3 mN/m at 20 MPa. A similar trend is observed in brine-CO2 systems. The diffusion coefficient is observed to slightly increase with pressure at supercritical conditions. Finally, the contact angle is found to be directly related to the gas adsorption at the rock surface: Up to 3.8 wt% of CO2 is adsorbed on the shale surface at 20 MPa and 60 °C where a maximum in contact angle is also found. To the best of the author’s knowledge, the affinity of calcite-rich surfaces toward CO2 adsorption is linked experimentally to the wetting behavior for the first time. The results are discussed in terms of CO2 storage scenarios occurring optimally at 20 MPa

A stand-alone hydrogen photovoltaic fuel cell hybrid system for efficient renewable energy generation

Today the main concern for World is energy and power age. By and by, out of around 7 billion populaces, just 65-69% approaches power. Essentially to carry the populaces into the office of power access however much as could be expected inside the restricted assets, we have used the regular assets like sun oriented and wind to satisfy this assumption. Utilizing sun based and wind energy in relationship with the power gadgets, we can supply the power to the buyers inside their capacity and we will want to limit the power issue as could really be expected. Hydrogen Photovoltaic Fuel (HPF) cell is the mix of force gadgets which lessens the major sun oriented emergency of expenses, where expenses are the enormous issue for non-industrial nations. Presently a-days, the coordinated circuits (IC) are entirely solid and modest, to the point that make the conveying and reversing or changing over components simplest than the massive and expensive instruments utilized in the traditional power supply framework. The examination expects that the lattice joining of the environmentally friendly power assets utilizing HPF inverter might cause a colossal comment in satisfying the absence of force use across the world. Solar energy is a rapidly growing resource, already providing 4.5% of electricity in the World and projected to supply up to 35% by 2050. On the other hand, the default model’s predictions were far from the actual metered HPF data. For renewability, the simulated renewable energy consumption with modified inputs is 3.9% below of actual metered renewable data while the default model’s prediction was more than 52% below actual renewable use. Using PV-HPF hybrid model indices to represent how well a simulated model describes the variability in the measured data; the modified model has achieved accurate renewability results; with a Solar of 10.99 % and Wind of 9.90%, while the hybrid model has a solar of 57.16% and a Wind of 57.20% in renewable energy comparison being performed in MATLAB

Using Many Objective Bat Algorithms for Solving Many Objective Nonlinear Functions

In this paper, we have relied on the dominant control system as an important tool in building the group of leaders because it allows leaders to contain less dense areas, avoid local areas, and produce a more compact and diverse Pareto front. Nine standard nonlinear functions yielded this result. MaBAT/R2 appears to be more efficient than MOEAD, NSGAII, MPSOD, and SPEA2. MATLAB was used to generate all the results of the proposed method and other methods in the same field of work

The Cleo III Ring Imaging Cherenkov Detector

The CLEO detector has been upgraded to include a state of the art particle identification system, based on the Ring Imaging Cherenkov Detector (RICH) technology, in order to take data at the upgraded CESR electron positron collider. The expected performance is reviewed, as well as the preliminary results from an engineering run during the first few months of operation of the CLEO III detector.Comment: 5 pages, 2 Figures Talk given by M. Artuso at 8th Pisa Meeting on Advanced Detectors, May 200

Thermal behavior of natural convection flow in an inclined solar air heater

The thermal behavior of hot air in a natural convection mode on a solar absorber-plate has not been, so far, modeled experimentally. The present work aimed to assess the performance of the inclined solar air heater [SAH] experimentally by investigating the temperature distribution field in the natural convection flow. The solar plate collector is designed based on the aspect ratio of length to height, L / H, of 6 and 12. The measurements are carried out for the collector tilt angles of 30°, 45°, 60° and 75°. The present investigation demonstrates the temperature distribution of hot air floated in an inclined channel of the SAH. The investigation showed 2D thermal stratification increases when increasing the distance along the collector plate, which looks clear in the SAH with a height of 10 cm. The results of the study show that the thickness of the thermal layers increases with increasing the tilt angle from 30 ̊ to 75 ̊. The reason dates back to increasing the buoyancy force of the hot air overthe absorber. The results demonstrated that the air temperatures for the height of 0.1 m and 45 ̊ tilt angle are higher than that for the height of 0.2 m by 23%

Mapping of ferric (Fe3+) and ferrous (Fe2+) iron oxides distribution using band ratio techniques with ASTER data and geochemistry of Kanjamalai and Godumalai, Tamil Nadu, south India

The iron ores found in Tamil Nadu State, South India, are major varieties that have been confined with banded magnetite quartzite. The occurrence, distribution, and grade of these deposits significantly vary according to their geological structure and geomorphologic control. In this article, presents a novel approach, based on spectral remote sensing and digital processing of ASTER data, to identify and characterize the iron ores of Kanjamalai and Godumalai areas located in Tamil Nadu, India. By analyzing the ASTER images, the abundance of iron oxides including ferric (Fe3+) and ferrous (Fe2+) components was determined. The band ratioing technique, a multiband analysis was used to generate the abundance of iron oxide content in various parts of the study area using different band combinations such as band 2/band 1 (for Fe3+) and band 5/band 3 + band 1/band 2 (for Fe2+). The geochemical analysis is an important part of this work to arrive with the outcome of band ratio techniques to decipher the relationship of the band ratio to the chemical composition of the ore samples. Accordingly, the correlation between the results of the geochemical analysis of the samples collected from the random locations was determined by Pearson's coefficient of correlation (ρ) and compared with the corresponding locations in the abundance image. In addition to ρ, various factors such as mean (μ), variance (σ2) and corresponding standard deviations (σ) were also analyzed for a comparative analysis. This comparative analysis indicated that most of the samples have considerably high iron oxide content in the locations. Thus, this study shows the possibility of detecting iron oxide content and its spatial distribution by using ASTER satellite images analysis. Hence, from the mapping results, it is evident that the band ratio technique of ASTER images can be used to map and characterize with limited fieldwork and geochemistr