A New Stability Analysis and Stabilization of Discrete-Time Switched Linear Systems Using Vector Norms Approach

In this paper, we aim to investigate a new stability analysis for discrete-time switched linear systems based on the comparison, the overvaluing principle, the application of Borne-Gentina criterion and the Kotelyanski conditions. This stability conditions issued from vector norms correspond to a vector Lyapunov function. In fact, the switched system to be controlled will be represented in the Companion form. A comparison system relative to a regular vector norm is used in order to get the simple arrow form of the state matrix that yields to a suitable use of Borne-Gentina criterion for the establishment of sufficient conditions for global asymptotic stability. This proposed approach could be a constructive solution to the state and static output feedback stabilization problems.

Semantic Modeling of Management Information: Enabling Automatic Reasoning on DMTF-CIM

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Evolutionary Techniques for Model Order Reduction of Large Scale Linear Systems

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Determining the Best Method of Stability Landslide by Using of DSS (Case Study: Landslide in Hasan Salaran, Kurdistan Province in Iran)

One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.

An Overview of Islanding Detection Methods in Photovoltaic Systems

The issue of unintentional islanding in PV grid interconnection still remains as a challenge in grid-connected photovoltaic (PV) systems. This paper discusses the overview of popularly used anti-islanding detection methods, practically applied in PV grid-connected systems. Anti-islanding methods generally can be classified into four major groups, which include passive methods, active methods, hybrid methods and communication base methods. Active methods have been the preferred detection technique over the years due to very small non-detected zone (NDZ) in small scale distribution generation. Passive method is comparatively simpler than active method in terms of circuitry and operations. However, it suffers from large NDZ that significantly reduces its performance. Communication base methods inherit the advantages of active and passive methods with reduced drawbacks. Hybrid method which evolved from the combination of both active and passive methods has been proven to achieve accurate anti-islanding detection by many researchers. For each of the studied anti-islanding methods, the operation analysis is described while the advantages and disadvantages are compared and discussed. It is difficult to pinpoint a generic method for a specific application, because most of the methods discussed are governed by the nature of application and system dependent elements. This study concludes that the setup and operation cost is the vital factor for anti-islanding method selection in order to achieve minimal compromising between cost and system quality.

Order Reduction of Linear Dynamic Systems using Stability Equation Method and GA

The authors present an algorithm for order reduction of linear dynamic systems using the combined advantages of stability equation method and the error minimization by Genetic algorithm. The denominator of the reduced order model is obtained by the stability equation method and the numerator terms of the lower order transfer function are determined by minimizing the integral square error between the transient responses of original and reduced order models using Genetic algorithm. The reduction procedure is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The proposed algorithm has also been extended for the order reduction of linear multivariable systems. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing ones including one example of multivariable system.

A Comparison of Adaline and MLP Neural Network based Predictors in SIR Estimation in Mobile DS/CDMA Systems

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

From Mother Tongue Education to Multilingual Higher Education

Through the time, the higher education has changed the learning system since mother tongue to bilingual, and in this new century has been coming develop a multilingual education. All as part of globalization process of the countries and the education. Nevertheless, this change only has been effectively in countries of the first world, the rest have been lagging. Therefore, these countries require strengthen their higher education systems through models that give way to multilingual and bilingual education. In this way, shows a new model adapted from a systemic form to allow a higher bilingual and multilingual education in Latin America. This systematization aims to increase the skills and competencies student’s, decrease the time learning of a second tongue, add to multilingualism in the American Latin Universities, also, contribute to position the region´s countries in a better global status, and stimulate the development of new research in this area.

Solar Energy for Water Conditioning

Shortening of natural resources will impose greater limitations of electric energy consumption in various fields including water treatment technologies. Small water treatment installations supplied with electric energy from solar sources are perfect example of zero-emission technology. Possibility of solar energy application, as one of the alternative energy resources for decontamination processes is strongly dependent on geographical location. Various examples of solar driven water purification systems are given and design of solar-water treatment installation based on ozone for the geographical conditions in Poland are presented.

Intelligent Off-Grid Photovoltaic Supply Systems

Off-grid Photovoltaic (PV) systems are empowering technology in underdeveloped countries like Ethiopia where many people live far away from the modern world. Where there is relatively low energy consumption, providing energy from grid systems is not commercially cost-effective. As a result, significant people groups worldwide stay without access to electricity. One remote village in northern Ethiopia was selected by the United Nations for a pilot project to improve its living conditions. As part of this comprehensive project, an intelligent charge controller circuit for Off-grid PV systems was designed for the clinic in that village. In this paper, design aspects of an intelligent charge controller unit and its load driver circuits are discussed for an efficient utilization of PVbased supply systems.

Automation of the Maritime UAV Command, Control, Navigation Operations, Simulated in Real-Time Using Kinect Sensor: A Feasibility Study

This paper describes the process used in the automation of the Maritime UAV commands using the Kinect sensor. The AR Drone is a Quadrocopter manufactured by Parrot [1] to be controlled using the Apple operating systems such as iPhones and Ipads. However, this project uses the Microsoft Kinect SDK and Microsoft Visual Studio C# (C sharp) software, which are compatible with Windows Operating System for the automation of the navigation and control of the AR drone. The navigation and control software for the Quadrocopter runs on a windows 7 computer. The project is divided into two sections; the Quadrocopter control system and the Kinect sensor control system. The Kinect sensor is connected to the computer using a USB cable from which commands can be sent to and from the Kinect sensors. The AR drone has Wi-Fi capabilities from which it can be connected to the computer to enable transfer of commands to and from the Quadrocopter. The project was implemented in C#, a programming language that is commonly used in the automation systems. The language was chosen because there are more libraries already established in C# for both the AR drone and the Kinect sensor. The study will contribute toward research in automation of systems using the Quadrocopter and the Kinect sensor for navigation involving a human operator in the loop. The prototype created has numerous applications among which include the inspection of vessels such as ship, airplanes and areas that are not accessible by human operators.

The Effect of Simulated Acid Rain on Glycine max

Acid rain occurs when sulphur dioxide (SO2) and nitrogen oxides (Nox) gases react in the atmosphere with water, oxygen, and other chemicals to form various acidic compounds. The result is a mild solution of sulfuric acid and nitric acid. Soil has a greater buffering capacity than aquatic systems. However excessive amount of acids introduced by acid rains may disturb the entire soil chemistry. Acidity and harmful action of toxic elements damage vegetation while susceptible microbial species are eliminated. In present study, the effects of simulated sulphuric acid and nitric acid rains were investigated on crop Glycine max. The effect of acid rain on change in soil fertility was detected in which pH of control sample was 6.5 and pH of 1%H2SO4 and 1%HNO3 were 3.5. Nitrogen nitrate in soil was high in 1% HNO3 treated soil & Control sample. Ammonium nitrogen in soil was low in 1% HNO3 & H2SO4 treated soil. Ammonium nitrogen was medium in control and other samples. The effect of acid rain on seed germination on 3rd day of germination control sample growth was 7 cm, 0.1% HNO3 was 8cm, and 0.001% HNO3 & 0.001% H2SO4 was 6cm each. On 10th day fungal growth was observed in 1% and 0.1%H2SO4 concentrations, when all plants were dead. The effect of acid rain on crop productivity was investigated on 3rd day roots were developed in plants. On12th day Glycine max showed more growth in 0.1% HNO3, 0.001% HNO3 and 0.001% H2SO4 treated plants growth were same as compare to control plants. On 20th day development of discoloration of plant pigments were observed on acid treated plants leaves. On 38th day, 0.1, 0.001% HNO3 and 0.1, 0.001% H2SO4 treated plants and control plants were showing flower growth. On 42th day, acid treated Glycine max variety and control plants were showed seeds on plants. In Glycine max variety 0.1, 0.001% H2SO4, 0.1, 0.001% HNO3 treated plants were dead on 46th day and fungal growth was observed. The toxicological study was carried out on Glycine max plants exposed to 1% HNO3 cells were damaged more than 1% H2SO4. Leaf sections exposed to 0.001% HNO3 & H2SO4 showed less damaged of cells and pigmentation observed in entire slide when compare with control plant. The soil analysis was done to find microorganisms in HNO3 & H2SO4 treated Glycine max and control plants. No microorganism growth was observed in 1% HNO3 & H2SO4 but control plant showed microbial growth.

Robust H8 Fuzzy Control Design for Nonlinear Two-Time Scale System with Markovian Jumps based on LMI Approach

This paper examines the problem of designing a robust H8 state-feedback controller for a class of nonlinear two-time scale systems with Markovian Jumps described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain Markovian jump nonlinear two-time scale systems to have an H8 performance are derived. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard nonlinear two-time scale systems. A numerical example is provided to illustrate the design developed in this paper.

Fuzzy Logic Controlled Shunt Active Power Filter for Three-phase Four-wire Systems with Balanced and Unbalanced Loads

This paper presents a fuzzy logic controlled shunt active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able to operate in both balanced and unbalanced load conditions. A fuzzy logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity of the presented approach in harmonic mitigation is verified via simulation results of the proposed test system under different loading conditions.

Feature-Driven Classification of Musical Styles

In this paper we address the problem of musical style classification, which has a number of applications like indexing in musical databases or automatic composition systems. Starting from MIDI files of real-world improvisations, we extract the melody track and cut it into overlapping segments of equal length. From these fragments, some numerical features are extracted as descriptors of style samples. We show that a standard Bayesian classifier can be conveniently employed to build an effective musical style classifier, once this set of features has been extracted from musical data. Preliminary experimental results show the effectiveness of the developed classifier that represents the first component of a musical audio retrieval system

Attacks Classification in Adaptive Intrusion Detection using Decision Tree

Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today's commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98% detection rate (DR) in comparison with other existing methods.

Designing a Football Team of Robots from Beginning to End

The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.

Remote-Sensing Sunspot Images to Obtain the Sunspot Roads

A combination of image fusion and quad tree decomposition method is used for detecting the sunspot trajectories in each month and computation of the latitudes of these trajectories in each solar hemisphere. Daily solar images taken with SOHO satellite are fused for each month and the result of fused image is decomposed with Quad Tree decomposition method in order to classifying the sunspot trajectories and then to achieve the precise information about latitudes of sunspot trajectories. Also with fusion we deduce some physical remarkable conclusions about sun magnetic fields behavior. Using quad tree decomposition we give information about the region on sun surface and the space angle that tremendous flares and hot plasma gases permeate interplanetary space and attack to satellites and human technical systems. Here sunspot images in June, July and August 2001 are used for studying and give a method to compute the latitude of sunspot trajectories in each month with sunspot images.

FHOJ: A New Java Benchmark Framework

There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.

Evaluation Process for the Hardware Safety Integrity Level

Safety instrumented systems (SISs) are becoming increasingly complex and the proportion of programmable electronic parts is growing. The IEC 61508 global standard was established to ensure the functional safety of SISs, but it was expressed in highly macroscopic terms. This study introduces an evaluation process for hardware safety integrity levels through failure modes, effects, and diagnostic analysis (FMEDA).FMEDA is widely used to evaluate safety levels, and it provides the information on failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a given component. In our evaluation process, the components of the SIS subsystem are first defined in terms of failure modes and effects. Then, the failure rate and failure mechanism distribution are assigned to each component. The safety mode and detectability of each failure mode are determined for each component. Finally, the hardware safety integrity level is evaluated based on the calculated results.