Delay-dependent Stability Analysis for Uncertain Switched Neutral System

This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.

Analysis of Different Designed Landing Gears for a Light Aircraft

The design of a landing gear is one of the fundamental aspects of aircraft design. The need for a light weight, high strength, and stiffness characteristics coupled with techno economic feasibility are a key to the acceptability of any landing gear construction. In this paper, an approach for analyzing two different designed landing gears for an unmanned aircraft vehicle (UAV) using advanced CAE techniques will be applied. Different landing conditions have been considered for both models. The maximum principle stresses for each model along with the factor of safety are calculated for every loading condition. A conclusion is drawing about better geometry.

Higher Plants Ability to Assimilate Explosives

The ability of agricultural and decorative plants to absorb and detoxify TNT and RDX has been studied. All tested 8 plants, grown hydroponically, were able to absorb these explosives from water solutions: Alfalfa > Soybean > Chickpea> Chikling vetch >Ryegrass > Mung bean> China bean > Maize. Differently from TNT, RDX did not exhibit negative influence on seed germination and plant growth. Moreover, some plants, exposed to RDX containing solution were increased in their biomass by 20%. Study of the fate of absorbed [1-14ðí]-TNT revealed the label distribution in low and high-molecular mass compounds, both in roots and above ground parts of plants, prevailing in the later. Content of 14ðí in lowmolecular compounds in plant roots are much higher than in above ground parts. On the contrary, high-molecular compounds are more intensively labeled in aboveground parts of soybean. Most part (up to 70%) of metabolites of TNT, formed either by enzymatic reduction or oxidation, is found in high molecular insoluble conjugates. Activation of enzymes, responsible for reduction, oxidation and conjugation of TNT, such as nitroreductase, peroxidase, phenoloxidase and glutathione S-transferase has been demonstrated. Among these enzymes, only nitroreductase was shown to be induced in alfalfa, exposed to RDX. The increase in malate dehydrogenase activities in plants, exposed to both explosives, indicates intensification of Tricarboxylic Acid Cycle, that generates reduced equivalents of NAD(P)H, necessary for functioning of the nitroreductase. The hypothetic scheme of TNT metabolism in plants is proposed.

Modeling and Identification of Hammerstein System by using Triangular Basis Functions

This paper deals with modeling and parameter identification of nonlinear systems described by Hammerstein model having Piecewise nonlinear characteristics such as Dead-zone nonlinearity characteristic. The simultaneous use of both an easy decomposition technique and the triangular basis functions leads to a particular form of Hammerstein model. The approximation by using Triangular basis functions for the description of the static nonlinear block conducts to a linear regressor model, so that least squares techniques can be used for the parameter estimation. Singular Values Decomposition (SVD) technique has been applied to separate the coupled parameters. The proposed approach has been efficiently tested on academic examples of simulation.

An Implementation of Stipple Operations

Stipples are desired for pattern fillings and transparency effects. In contrast, some graphics standards, including OpenGL ES 1.1 and 2.0, omitted this feature. We represent details of providing line stipples and polygon stipples, through combining texture mapping and alpha blending functions. We start from the OpenGL-specified stipple-related API functions. The details of mathematical transformations are explained to get the correct texture coordinates. Then, the overall algorithm is represented, and its implementation results are followed. We accomplished both of line and polygon stipples, and verified its result with conformance test routines.

A Beacon Based Priority Routing Scheme for Solar Power Plants in WSNs

Solar power plants(SPPs) have shown a lot of good outcomes in providing a various functions depending on industrial expectations by deploying ad-hoc networking with helps of light loaded and battery powered sensor nodes. In particular, it is strongly requested to develop an algorithm to deriver the sensing data from the end node of solar power plants to the sink node on time. In this paper, based on the above observation we have proposed an IEEE802.15.4 based self routing scheme for solar power plants. The proposed beacon based priority routing Algorithm (BPRA) scheme utilizes beacon periods in sending message with embedding the high priority data and thus provides high quality of service(QoS) in the given criteria. The performance measures are the packet Throughput, delivery, latency, total energy consumption. Simulation results under TinyOS Simulator(TOSSIM) have shown the proposed scheme outcome the conventional Ad hoc On-Demand Distance Vector(AODV) Routing in solar power plants.

A Hybrid Fuzzy AGC in a Competitive Electricity Environment

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Digital Automatic Gain Control Integrated on WLAN Platform

In this work we present a solution for DAGC (Digital Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4 GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used enables gain control over Low Noise Amplifier (LNA) and a Variable Gain Amplifier (VGA). The control over those signals is performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the average power of the baseband signal close to the desired set point. DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and actual gain setting, adjusting a gain factor of the accumulation, and applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.

Elections Management Information Communication System Voter Ballot

Abovepresented work deals with the new scope of application of information and communication technologies for the improvement of the election process in the biased environment. We are introducing a new concept of construction of the information-communication system for the election participant. It consists of four main components: Software, Physical Infrastructure, Structured Information and the Trained Stuff. The Structured Information is the bases of the whole system and is the collection of all possible events (irregularities among them) at the polling stations, which are structured in special templates, forms and integrated in mobile devices.The software represents a package of analytic modules, which operates with the dynamic database. The application of modern communication technologies facilities the immediate exchange of information and of relevant documents between the polling stations and the Server of the participant. No less important is the training of the staff for the proper functioning of the system. The e-training system with various modules should be applied in this respect. The presented methodology is primarily focused on the election processes in the countries of emerging democracies.It can be regarded as the tool for the monitoring of elections process by the political organization(s) and as one of the instruments to foster the spread of democracy in these countries.

Design of Permanent Magnet Machines with Different Rotor Type

This paper presents design, analysis and comparison of the different rotor type permanent magnet machines. The presented machines are designed as having same geometrical dimensions and same materials for comparison. The main machine parameters of interior and exterior rotor type machines including eddy current effect, torque-speed characteristics and magnetic analysis are investigated using MAXWELL program. With this program, the components of the permanent magnet machines can be calculated with high accuracy. Six types of Permanent machines are compared with respect to their topology, size, magnetic field, air gap flux, voltage, torque, loss and efficiency. The analysis results demonstrate the effectiveness of the proposed machines design methodology. We believe that, this study will be a helpful resource in terms of examination and comparison of the basic structure and magnetic features of the PM (Permanent magnet) machines which have different rotor structure.

The Global Stability Using Lyapunov Function

An important technique in stability theory for differential equations is known as the direct method of Lyapunov. In this work we deal global stability properties of Leptospirosis transmission model by age group in Thailand. First we consider the data from Division of Epidemiology Ministry of Public Health, Thailand between 1997-2011. Then we construct the mathematical model for leptospirosis transmission by eight age groups. The Lyapunov functions are used for our model which takes the forms of an Ordinary Differential Equation system. The globally asymptotically for equilibrium states are analyzed.

Application of “Multiple Risk Communicator“ to the Personal Information Leakage Problem

Along with the progress of our information society, various risks are becoming increasingly common, causing multiple social problems. For this reason, risk communications for establishing consensus among stakeholders who have different priorities have become important. However, it is not always easy for the decision makers to agree on measures to reduce risks based on opposing concepts, such as security, privacy and cost. Therefore, we previously developed and proposed the “Multiple Risk Communicator" (MRC) with the following functions: (1) modeling the support role of the risk specialist, (2) an optimization engine, and (3) displaying the computed results. In this paper, MRC program version 1.0 is applied to the personal information leakage problem. The application process and validation of the results are discussed.

Hutchinson-Barnsley Operator in Intuitionistic Fuzzy Metric Spaces

The main purpose of this paper is to prove the intuitionistic fuzzy contraction properties of the Hutchinson-Barnsley operator on the intuitionistic fuzzy hyperspace with respect to the Hausdorff intuitionistic fuzzy metrics. Also we discuss about the relationships between the Hausdorff intuitionistic fuzzy metrics on the intuitionistic fuzzy hyperspaces. Our theorems generalize and extend some recent results related with Hutchinson-Barnsley operator in the metric spaces to the intuitionistic fuzzy metric spaces.

Fractal Shapes Description with Parametric L-systems and Turtle Algebra

In this paper, we propose a new method to describe fractal shapes using parametric l-systems. First we introduce scaling factors in the production rules of the parametric l-systems grammars. Then we decorticate these grammars with scaling factors using turtle algebra to show the mathematical relation between l-systems and iterated function systems (IFS). We demonstrate that with specific values of the scaling factors, we find the exact relationship established by Prusinkiewicz and Hammel between l-systems and IFS.

Differentiation of Heart Rate Time Series from Electroencephalogram and Noise

Analysis of heart rate variability (HRV) has become a popular non-invasive tool for assessing the activities of autonomic nervous system. Most of the methods were hired from techniques used for time series analysis. Currently used methods are time domain, frequency domain, geometrical and fractal methods. A new technique, which searches for pattern repeatability in a time series, is proposed for quantifying heart rate (HR) time series. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are able to distinguish HR data clearly from noise and electroencephalogram (EEG). The results of analysis using these measures give an insight into the fundamental difference between the composition of HR time series with respect to EEG and noise.

Arc Length of Rational Bezier Curves and Use for CAD Reparametrization

The length  of a given rational B'ezier curve is efficiently estimated. Since a rational B'ezier function is nonlinear, it is usually impossible to evaluate its length exactly. The length is approximated by using subdivision and the accuracy of the approximation n is investigated. In order to improve the efficiency, adaptivity is used with some length estimator. A rigorous theoretical analysis of the rate of convergence of n to  is given. The required number of subdivisions to attain a prescribed accuracy is also analyzed. An application to CAD parametrization is briefly described. Numerical results are reported to supplement the theory.

Secure Data Aggregation Using Clusters in Sensor Networks

Wireless sensor network can be applied to both abominable and military environments. A primary goal in the design of wireless sensor networks is lifetime maximization, constrained by the energy capacity of batteries. One well-known method to reduce energy consumption in such networks is data aggregation. Providing efcient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present privacy-preserving data aggregation scheme for additive aggregation functions. The Cluster-based Private Data Aggregation (CPDA)leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes.

An Efficient Key Management Scheme for Secure SCADA Communication

A SCADA (Supervisory Control And Data Acquisition) system is an industrial control and monitoring system for national infrastructures. The SCADA systems were used in a closed environment without considering about security functionality in the past. As communication technology develops, they try to connect the SCADA systems to an open network. Therefore, the security of the SCADA systems has been an issue. The study of key management for SCADA system also has been performed. However, existing key management schemes for SCADA system such as SKE(Key establishment for SCADA systems) and SKMA(Key management scheme for SCADA systems) cannot support broadcasting communication. To solve this problem, an Advanced Key Management Architecture for Secure SCADA Communication has been proposed by Choi et al.. Choi et al.-s scheme also has a problem that it requires lots of computational cost for multicasting communication. In this paper, we propose an enhanced scheme which improving computational cost for multicasting communication with considering the number of keys to be stored in a low power communication device (RTU).

Intuitionistic Fuzzy Multisets And Its Application in Medical Diagnosis

In this paper a new concept named Intuitionistic Fuzzy Multiset is introduced. The basic operations on Intuitionistic Fuzzy Multisets such as union, intersection, addition, multiplication etc. are discussed. An application of Intuitionistic Fuzzy Multiset in Medical diagnosis problem using a distance function is discussed in detail.

Use of Multiple Linear Regressions to Evaluate the Influence of O3 and PM10 on Biological Pollutants

Exposure to ambient air pollution has been linked to a number of health outcomes, starting from modest transient changes in the respiratory tract and impaired pulmonary function, continuing to restrict activity/reduce performance and to the increase emergency rooms visits, hospital admissions or mortality. The increase of allergenic symptoms has been associated with air contaminants such as ozone, particulate matter, fungal spores and pollen. Considering the potential relevance of crossed effects of nonbiological pollutants and airborne pollens and fungal spores on allergy worsening, the aim of this work was to evaluate the influence of non-biological pollutants (O3 and PM10) and meteorological parameters on the concentrations of pollen and fungal spores using multiple linear regressions. The data considered in this study were collected in Oporto which is the second largest Portuguese city, located in the North. Daily mean of O3, PM10, pollen and fungal spore concentrations, temperature, relative humidity, precipitation, wind velocity, pollen and fungal spore concentrations, for 2003, 2004 and 2005 were considered. Results showed that the 90th percentile of the adjusted coefficient of determination, P90 (R2aj), of the multiple regressions varied from 0.613 to 0.916 for pollen and from 0.275 to 0.512 for fungal spores. O3 and PM10 showed to have some influence on the biological pollutants. Among the meteorological parameters analysed, temperature was the one that most influenced the pollen and fungal spores airborne concentrations. Relative humidity also showed to have some influence on the fungal spore dispersion. Nevertheless, the models for each pollen and fungal spore were different depending on the analysed period, which means that the correlations identified as statistically significant can not be, even so, consistent enough.