Dynamic Fuzzy-Neural Network Controller for Induction Motor Drive

In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.

Fractal Patterns for Power Quality Detection Using Color Relational Analysis Based Classifier

This paper proposes fractal patterns for power quality (PQ) detection using color relational analysis (CRA) based classifier. Iterated function system (IFS) uses the non-linear interpolation in the map and uses similarity maps to construct various fractal patterns of power quality disturbances, including harmonics, voltage sag, voltage swell, voltage sag involving harmonics, voltage swell involving harmonics, and voltage interruption. The non-linear interpolation functions (NIFs) with fractal dimension (FD) make fractal patterns more distinguishing between normal and abnormal voltage signals. The classifier based on CRA discriminates the disturbance events in a power system. Compared with the wavelet neural networks, the test results will show accurate discrimination, good robustness, and faster processing time for detecting disturbing events.

A Tool for Audio Quality Evaluation Under Hostile Environment

In this paper is to evaluate audio and speech quality with the help of Digital Audio Watermarking Technique under the different types of attacks (signal impairments) like Gaussian Noise, Compression Error and Jittering Effect. Further attacks are considered as Hostile Environment. Audio and Speech Quality Evaluation is an important research topic. The traditional way for speech quality evaluation is using subjective tests. They are reliable, but very expensive, time consuming, and cannot be used in certain applications such as online monitoring. Objective models, based on human perception, were developed to predict the results of subjective tests. The existing objective methods require either the original speech or complicated computation model, which makes some applications of quality evaluation impossible.

Enhanced Conference Organization Based On Correlation of Web Information and Ontology Based Expertise Search

From the importance of the conference and its constructive role in the studies discussion, there must be a strong organization that allows the exploitation of the discussions in opening new horizons. The vast amount of information scattered across the web, make it difficult to find experts, who can play a prominent role in organizing conferences. In this paper we proposed a new approach of extracting researchers- information from various Web resources and correlating them in order to confirm their correctness. As a validator of this approach, we propose a service that will be useful to set up a conference. Its main objective is to find appropriate experts, as well as the social events for a conference. For this application we us Semantic Web technologies like RDF and ontology to represent the confirmed information, which are linked to another ontology (skills ontology) that are used to present and compute the expertise.

Design of a Fuzzy Feed-forward Controller for Monitor HAGC System of Cold Rolling Mill

In this study we propose a novel monitor hydraulic automatic gauge control (HAGC) system based on fuzzy feedforward controller. This is used in the development of cold rolling mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in the entry steel strip. The proposed method uses a mathematical model of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In order to improve the speed of the controller in rejecting disturbances introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.

The Role of Ga(Gallium)-flux and AlN(Aluminum Nitride) as the Interface Materials, between (Ga-face)GaN and (Siface)4H-SiC, through Molecular Dynamics Simulation

We report here, the results of molecular dynamics simulation of p-doped (Ga-face)GaN over n-doped (Siface)( 0001)4H-SiC hetero-epitaxial material system with one-layer each of Ga-flux and (Al-face)AlN, as the interface materials, in the form of, the total Density of States (DOS). It is found that the total DOS at the Fermi-level for the heavily p-doped (Ga-face)GaN and ndoped (Si-face)4H-SiC hetero-epitaxial system, with one layer of (Al-face)AlN as the interface material, is comparatively higher than that of the various cases studied, indicating that there could be good vertical conduction across the (Ga-face)GaN over (Si-face)(0001)4HSiC hetero-epitaxial material system.

Deep Learning and Virtual Environment

While computers are known to facilitate lower levels of learning, such as rote memorization of facts, measurable through electronically administered and graded multiple-choice questions, yes/no, and true/false answers, the imparting and measurement of higher-level cognitive skills is more vexing. These require more open-ended delivery and answers, and may be more problematic in an entirely virtual environment, notwithstanding the advances in technologies such as wikis, blogs, discussion boards, etc. As with the integration of all technology, merit is based more on the instructional design of the course than on the technology employed in, and of, itself. With this in mind, this study examined the perceptions of online students in an introductory Computer Information Systems course regarding the fostering of various higher-order thinking and team-building skills as a result of the activities, resources and technologies (ART) used in the course.

Influence of Drought on Yield and Yield Components in White Bean

In order to study seed yield and seed yield components in bean under reduced irrigation condition and assessment drought tolerance of genotypes, 15 lines of White beans were evaluated in two separate RCB design with 3 replications under stress and non stress conditions. Analysis of variance showed that there were significant differences among varieties in terms of traits under study, indicating the existence of genetic variation among varieties. The results indicate that drought stress reduced seed yield, number of seed per plant, biological yield and number of pod in White been. In non stress condition, yield was highly correlated with the biological yield, whereas in stress condition it was highly correlated with harvest index. Results of stepwise regression showed that, selection can we done based on, biological yield, harvest index, number of seed per pod, seed length, 100 seed weight. Result of path analysis showed that the highest direct effect, being positive, was related to biological yield in non stress and to harvest index in stress conditions. Factor analysis were accomplished in stress and nonstress condition a, there were 4 factors that explained more than 76 percent of total variations. We used several selection indices such as Stress Susceptibility Index ( SSI ), Geometric Mean Productivity ( GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and Tolerance Index ( TOL ) to study drought tolerance of genotypes, we found that the best Stress Index for selection tolerance genotypes were STI, GMP and MP were the greatest correlations between these Indices and seed yield under stress and non stress conditions. In classification of genotypes base on phenotypic characteristics, using cluster analysis ( UPGMA ), all allels classified in 5 separate groups in stress and non stress conditions.

The Identification of Selected Dysfunctions and Paradoxes in Corporate Social Responsibility Management in Small Enterprise

The study presents a brief and synthetic discussion of selected conclusions resulting from multidimensional and in-depth empirical studies. Its theoretical part presents the assumptions referring to social responsibility management from the perspective of the specific nature of small enterprise functioning, while the empirical part presents the selected dysfunctions and paradoxes in social responsibility management referring to this group of enterprises. The paper is summarized by a short list of the resulting recommendations.

A Self-stabilizing Algorithm for Maximum Popular Matching of Strictly Ordered Preference Lists

In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).

Two Individual Genetic Algorithm

The particular interests of this paper is to explore if the simple Genetic Algorithms (GA) starts with population of only two individuals and applying different crossover technique over these parents to produced 104 children, each one has different attributes inherited from their parents; is better than starting with population of 100 individuals; and using only one type crossover (order crossover OX). For this reason we implement GA with 52 different crossover techniques; each one produce two children; which means 104 different children will be produced and this may discover more search space, also we implement classic GA with order crossover and many experiments were done over 3 Travel Salesman Problem (TSP) to find out which method is better, and according to the results we can say that GA with Multi-crossovers is much better.

Multi-Walled Carbon Nanotubes/Polyacrylonitrile Composite as Novel Semi-Permeable Mixed Matrix Membrane in Reverse Osmosis Water Treatment Process

novel and simple method is introduced for rapid and highly efficient water treatment by reverse osmosis (RO) method using multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN) polymer as a flexible, highly efficient, reusable and semi-permeable mixed matrix membrane (MMM). For this purpose, MWCNTs were directly synthesized and on-line purified by chemical vapor deposition (CVD) process, followed by directing the MWCNT bundles towards an ultrasonic bath, in which PAN polymer was simultaneously suspended inside a solid porous silica support in water at temperature to ~70 οC. Fabrication process of MMM was finally completed by hot isostatic pressing (HIP) process. In accordance with the analytical figures of merit, the efficiency of fabricated MMM was ~97%. The rate of water treatment process was also evaluated to 6.35 L min-1. The results reveal that, the CNT-based MMM is suitable for rapid treatment of different forms of industrial, sea, drinking and well water samples.

Finite Element Prediction and Experimental Verification of the Failure Pattern of Proximal Femur using Quantitative Computed Tomography Images

This paper presents a novel method for prediction of the mechanical behavior of proximal femur using the general framework of the quantitative computed tomography (QCT)-based finite element Analysis (FEA). A systematic imaging and modeling procedure was developed for reliable correspondence between the QCT-based FEA and the in-vitro mechanical testing. A speciallydesigned holding frame was used to define and maintain a unique geometrical reference system during the analysis and testing. The QCT images were directly converted into voxel-based 3D finite element models for linear and nonlinear analyses. The equivalent plastic strain and the strain energy density measures were used to identify the critical elements and predict the failure patterns. The samples were destructively tested using a specially-designed gripping fixture (with five degrees of freedom) mounted within a universal mechanical testing machine. Very good agreements were found between the experimental and the predicted failure patterns and the associated load levels.

Application of Mutual Information based Least dependent Component Analysis (MILCA) for Removal of Ocular Artifacts from Electroencephalogram

The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Adaptive Early Packet Discarding Policy Based on Two Traffic Classes

Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.

Study of the Sorption of Biosurfactants from l. Pentosus on Sediments

Losses of surfactant due to sorption need to be considered when selecting surfactant doses for soil bioremediation. The degree of surfactant sorption onto soil depends primarily on the organic carbon fraction of soil and the chemical nature of the surfactant. The use of biosurfactants in the control of the bioavailability of toxicants in soils is an attractive option because of their biodegradability. In this work biosurfactants were produced from a cheap raw material, trimming vine shoots, employing Lactobacillus pentosus. When biosurfactants from L. pentosus was added to sediments the surface tensión of the water containing the sediments rapidly increase, the same behaviour was observed with the chemical surfactant Tween 20; whereas sodyum dodecyl sulphate (SDS) kept the surface tension of the water around 36 mN/m. It means, that the behaviour of biosurfactants from L. pentosus is more similar to non-ionic surfactatns than to anionic surfactants.

Pre-Clinical Studying of Antitumor Ramon Preparation: Chronic Toxicity

In article the data of chronic toxicity for pre-clinical researches of Ramon preparation is described. Ramon effects to hormone system and gastrointestinal tract; local irritative effect, allergic, pyrogenic properties and reaction to the immune system were studied.

Data and Control Flow Analysis of VDMµ Specifications

Formal Specification languages are being widely used for system specification and testing. Highly critical systems such as real time systems, avionics, and medical systems are represented using Formal specification languages. Formal specifications based testing is mostly performed using black box testing approaches thus testing only the set of inputs and outputs of the system. The formal specification language such as VDMµ can be used for white box testing as they provide enough constructs as any other high level programming language. In this work, we perform data and control flow analysis of VDMµ class specifications. The proposed work is discussed with an example of SavingAccount.

Dynamics and Driving Forces of the Alpine Wetlands in the Yarlung Zangbo River Basin of Tibet, China

Based on the field investigation and long term remote sensing data, the dynamics of the alpine wetland in the river basin and their response to climate change were studied. Results showed the alpine wetlands accounted for 3.73% of total basin in 2010. Lake and river appeared an increasing trend in the past 30 years, with an increase of 34.36 % and 24.57%. However, swamp exhibited a tendency of decreasing with 233.74 km2. Annual average temperature, maximum temperature, minimum temperature and precipitation in the river basin all exhibited an increasing trend, whereas relative humidity exhibited a decreasing trend. Ice and snow melting are main reasons of lake and river area enhancement and swamp area descend. There existed 91.78%-97.86% of reduced swamp converted into lakes on the basis of remote sensing image interpretation. China-s government policy of implementing development in the river basin is the major driving force of artificial wetland growth.

An Efficient Protocol for Cyclic Somatic Embryogenesis in Neem (Azadirachta indica A Juss.)

Neem is a highly heterozygous and commercially important perennial plant. Conventionally, it is propagated by seeds which loose viability within two weeks. Strictly cross pollinating nature of the plant causes serious barrier to the genetic improvement by conventional methods. Alternative methods of tree improvement such as somatic hybridization, mutagenesis and genetic transformation require an efficient in vitro plant regeneration system. In this regard, somatic embryogenesis particularly secondary somatic embryogenesis may offer an effective system for large scale plant propagation without affecting the clonal fidelity of the regenerants. It can be used for synthetic seed production, which further bolsters conservation of this tree species which is otherwise very difficult The present report describes the culture conditions necessary to induce and maintain repetitive somatic embryogenesis, for the first time, in neem. Out of various treatments tested, the somatic embryos were induced directly from immature zygotic embryos of neem on MS + TDZ (0.1 μM) + ABA (4 μM), in more than 76 % cultures. Direct secondary somatic embryogenesis occurred from primary somatic embryos on MS + IAA (5 μM) + GA3 (5 μM) in 12.5 % cultures. Embryogenic competence of the explant as well as of the primary embryos was maintained for a long period by repeated subcultures at frequent intervals. A maximum of 10 % of these somatic embryos were converted into plantlets.