GA based Optimal Sizing and Placement of Distributed Generation for Loss Minimization

This paper addresses a novel technique for placement of distributed generation (DG) in electric power systems. A GA based approach for sizing and placement of DG keeping in view of system power loss minimization in different loading conditions is explained. Minimal system power loss is obtained under voltage and line loading constraints. Proposed strategy is applied to power distribution systems and its effectiveness is verified through simulation results on 16, 37-bus and 75-bus test systems.

Business Intelligence for N=1 Analytics using Hybrid Intelligent System Approach

The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.

Environmental Friendly Polyurethane Coatings Based On Hyperbranched Resin

Water borne polyurethane (PU) based on newly prepared hyperbranched poly (amine-ester) (HBPAE) was applied and evaluated as organic coating material. HBPAE was prepared through one-pot synthesis between trimethylol propane as a core and AB2 branched monomer which was obtained via Michal addition of methyl methacrylate (MMA) and diethanol amine (DEA). PU was prepared from HBPAE using different ratios of toluene diisocyanate (TDI) to form cured coating film. The prepared HBPAE was characterized using; GPC, FT-IR and 1H-NMR. The mechanical properties (impact, hardness, adhesion, and flexibility), thermal properties (DSC and TGA) and chemical resistance of the applied film were estimated. The results indicated 50% of TDI is the selected ratio. This formulation represents a promising candidate to be used as coating material.

The Effect of Slow Variation of Base Flow Profile on the Stability of Slightly Curved Mixing Layers

The effect of small non-parallelism of the base flow on the stability of slightly curved mixing layers is analyzed in the present paper. Assuming that the instability wavelength is much smaller than the length scale of the variation of the base flow we derive an amplitude evolution equation using the method of multiple scales. The proposed asymptotic model provides connection between parallel flow approximations and takes into account slow longitudinal variation of the base flow.

Uniform Distribution of Ductility Demand in Irregular Bridges using Shape Memory Alloy

Excessive ductility demand on shorter piers is a common problem for irregular bridges subjected to strong ground motion. Various techniques have been developed to reduce the likelihood of collapse of bridge due to failure of shorter piers. This paper presents the new approach to improve the seismic behavior of such bridges using Nitinol shape memory alloys (SMAs). Superelastic SMAs have the ability to remain elastic under very large deformation due to martensitic transformation. This unique property leads to enhanced performance of controlled bridge compared with the performance of the reference bridge. To evaluate the effectiveness of the devices, nonlinear time history analysis is performed on a RC single column bent highway bridge using a suite of representative ground motions. The results show that this method is very effective in limiting the ductility demand of shorter pier.

Model Inversion of a Two Degrees of Freedom Linearized PUMA from Bicausal Bond Graphs

A bond graph model of a two degrees of freedom PUMA is described. System inversion gives the system input required to generate a given system output. In order to get the system inversion of the PUMA manipulator, a linearization of the nonlinear bond graph is obtained. Hence, the bicausality of the linearized bond graph of the PUMA manipulator is applied. Thus, the bicausal bond graph provides a systematic way of generating the equations of the system inversion. Simulation results to verify the calculated input for a given output are shown.

Combinatorial Optimisation of Worm Propagationon an Unknown Network

Worm propagation profiles have significantly changed since 2003-2004: sudden world outbreaks like Blaster or Slammer have progressively disappeared and slower but stealthier worms appeared since, most of them for botnets dissemination. Decreased worm virulence results in more difficult detection. In this paper, we describe a stealth worm propagation model which has been extensively simulated and analysed on a huge virtual network. The main features of this model is its ability to infect any Internet-like network in a few seconds, whatever may be its size while greatly limiting the reinfection attempt overhead of already infected hosts. The main simulation results shows that the combinatorial topology of routing may have a huge impact on the worm propagation and thus some servers play a more essential and significant role than others. The real-time capability to identify them may be essential to greatly hinder worm propagation.

Fuzzy Scan Method to Detect Clusters

The classical temporal scan statistic is often used to identify disease clusters. In recent years, this method has become as a very popular technique and its field of application has been notably increased. Many bioinformatic problems have been solved with this technique. In this paper a new scan fuzzy method is proposed. The behaviors of classic and fuzzy scan techniques are studied with simulated data. ROC curves are calculated, being demonstrated the superiority of the fuzzy scan technique.

Design, Implementation and Analysis of Composite Material Dampers for Turning Operations

This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in the design phase was to enhance the damping capability minimizing the loss in static stiffness through implementation of composite material interfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machining system, as well as the surface roughness of the machined workpieces. The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take into consideration the interaction between the elastic structure of the machine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.

ANN Models for Microstrip Line Synthesis and Analysis

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Alertness States Classification By SOM and LVQ Neural Networks

Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.

Design of an SNMP Agent for OSGi Service Platforms

On one hand, SNMP (Simple Network Management Protocol) allows integrating different enterprise elements connected through Internet into a standardized remote management. On the other hand, as a consequence of the success of Intelligent Houses they can be connected through Internet now by means of a residential gateway according to a common standard called OSGi (Open Services Gateway initiative). Due to the specifics of OSGi Service Platforms and their dynamic nature, specific design criterions should be defined to implement SNMP Agents for OSGi in order to integrate them into the SNMP remote management. Based on the analysis of the relation between both standards (SNMP and OSGi), this paper shows how OSGi Service Platforms can be included into the SNMP management of a global enterprise, giving implementation details about an SNMP Agent solution and the definition of a new MIB (Management Information Base) for managing OSGi platforms that takes into account the specifics and dynamic nature of OSGi.

Development of a Catchment Water Quality Model for Continuous Simulations of Pollutants Build-up and Wash-off

Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.

A Retrospective of High-Lift Device Technology

The present paper deals with the most adopted technical solutions for the enhancement of the lift force of a wing. In fact, during several flight conditions (such as take off and landing), the lift force needs to be dramatically enhanced. Both trailing edge devices (such as flaps) and leading edge ones (such as slats) are described. Finally, the most advanced aerodynamic solutions to avoid the separation of the boundary layer from aircraft wings at high angles of attack are reviewed.

Highlighting Document's Structure

In this paper, we present symbolic recognition models to extract knowledge characterized by document structures. Focussing on the extraction and the meticulous exploitation of the semantic structure of documents, we obtain a meaningful contextual tagging corresponding to different unit types (title, chapter, section, enumeration, etc.).

Block Activity in Metric Neural Networks

The model of neural networks on the small-world topology, with metric (local and random connectivity) is investigated. The synaptic weights are random, driving the network towards a chaotic state for the neural activity. An ordered macroscopic neuron state is induced by a bias in the network connections. When the connections are mainly local, the network emulates a block-like structure. It is found that the topology and the bias compete to influence the network to evolve into a global or a block activity ordering, according to the initial conditions.

Dynamic Time Warping in Gait Classificationof Motion Capture Data

The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.

The Application of HLLC Numerical Solver to the Reduced Multiphase Model

The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis.

Propagation of Electron-Acoustic Solitary Waves in Weakly Relativistically Degenerate Fermi Plasma

Using one dimensional Quantum hydrodynamic (QHD) model Korteweg de Vries (KdV) solitary excitations of electron-acoustic waves (EAWs) have been examined in twoelectron- populated relativistically degenerate super dense plasma. It is found that relativistic degeneracy parameter influences the conditions of formation and properties of solitary structures.

Olive Leaves Extract Restored the antioxidant Perturbations in Red Blood Cells Hemolysate in Streptozotocin Induced Diabetic Rats

Oxidative stress and overwhelming free radicals associated with diabetes mellitus are likely to be linked with development of certain complication such as retinopathy, nephropathy and neuropathy. Treatment of diabetic subjects with antioxidant may be of advantage in attenuating these complications. Olive leaf (Oleaeuropaea), has been endowed with many beneficial and health promoting properties mostly linked to its antioxidant activity. This study aimed to evaluate the significance of supplementation of Olive leaves extract (OLE) in reducing oxidative stress, hyperglycemia and hyperlipidemia in Sterptozotocin (STZ)- induced diabetic rats. After induction of diabetes, a significant rise in plasma glucose, lipid profiles except High density lipoproteincholestrol (HDLc), malondialdehyde (MDA) and significant decrease of plasma insulin, HDLc and Plasma reduced glutathione GSH as well as alteration in enzymatic antioxidants was observed in all diabetic animals. During treatment of diabetic rats with 0.5g/kg body weight of Olive leaves extract (OLE) the levels of plasma (MDA) ,(GSH), insulin, lipid profiles along with blood glucose and erythrocyte enzymatic antioxidant enzymes were significantly restored to establish values that were not different from normal control rats. Untreated diabetic rats on the other hand demonstrated persistent alterations in the oxidative stress marker (MDA), blood glucose, insulin, lipid profiles and the antioxidant parameters. These results demonstrate that OLE may be of advantage in inhibiting hyperglycemia, hyperlipidemia and oxidative stress induced by diabetes and suggest that administration of OLE may be helpful in the prevention or at least reduced of diabetic complications associated with oxidative stress.