Analysis and Preservation of Lime-Kilns in Corsica

The aim of this paper is the analysis and preservation of lime kilns, focusing on the structure, construction, and functionality of vertical shaft lime kilns of the Cap Corse in Corsica. Plans and sections of two lime kilns are presented in detail, providing an overall picture of this specific industrial heritage. The potential damage areas are identified performing structural analysis of a lime kiln using the finite element method. A restoration and strengthening technique that satisfies the directions of the Charter of Venice is presented using post-tensioning tendons. Recommendations are given to preserve and promote these important historical structures integrating them into the custom footpath.

Minimizing Fish-feed Loss due to Sea Currents: An Economic Methodology

Fish-feed is a major cost component of operating expenses for any aquaculture farm. Due to soaring prices of fish-feed ingredients, the need for better feeding schedule management has become imperative. On such factor that influences the utilization rate of fish-feed are sea currents. Up to now, practical monitoring of fishfeed loss due to sea currents is not exercised. This paper gives a description of an economic methodology that aims at quantifying the amount of fish-feed lost due to sea currents and draws on data from a Mediterranean aquaculture farm to formulate the associated model.

Generation of Sets of Synthetic Classifiers for the Evaluation of Abstract-Level Combination Methods

This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.

Unit Commitment Solution Methods

An effort to develop a unit commitment approach capable of handling large power systems consisting of both thermal and hydro generating units offers a large profitable return. In order to be feasible, the method to be developed must be flexible, efficient and reliable. In this paper, various proposed methods have been described along with their strengths and weaknesses. As all of these methods have some sort of weaknesses, a comprehensive algorithm that combines the strengths of different methods and overcomes each other-s weaknesses would be a suitable approach for solving industry-grade unit commitment problem.

Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

The Long Run Relationship between Exports and Imports in South Africa: Evidence from Cointegration Analysis

This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.

Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control

In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Vector Control of Multimotor Drive

Three-phase induction machines are today a standard for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are replacing dc drive systems. The development of power electronics and signal processing systems has eliminated one of the greatest disadvantages of such ac systems, which is the issue of control. With modern techniques of field oriented vector control, the task of variable speed control of induction machines is no longer a disadvantage. The need to increase system performance, particularly when facing limits on the power ratings of power supplies and semiconductors, motivates the use of phase number other than three, In this paper a novel scheme of connecting two, three phase induction motors in parallel fed by two inverters; viz. VSI and CSI and their vector control is presented.

Optimal Space Vector Control for Permanent Magnet Synchronous Motor based on Nonrecursive Riccati Equation

In this paper the optimal control strategy for Permanent Magnet Synchronous Motor (PMSM) based drive system is presented. The designed full optimal control is available for speed operating range up to base speed. The optimal voltage space-vector assures input energy reduction and stator loss minimization, maintaining the output energy in the same limits with the conventional PMSM electrical drive. The optimal control with three components is based on the energetically criteria and it is applicable in numerical version, being a nonrecursive solution. The simulation results confirm the increased efficiency of the optimal PMSM drive. The properties of the optimal voltage space vector are shown.

Simultaneously Reduction of NOx and Soot Emissions in a DI Heavy Duty diesel Engine Operating at High Cooled EGR Rates

One promising way to achieve low temperature combustion regime is the use of a large amount of cooled EGR. In this paper, the effect of injection timing on low temperature combustion process and emissions were investigated via three dimensional computational fluid dynamics (CFD) procedures in a DI diesel engine using high EGR rates. The results show when increasing EGR from low levels to levels corresponding to reduced temperature combustion, soot emission after first increasing, is decreased beyond 40% EGR and get the lowest value at 58% EGR rate. Soot and NOx emissions are simultaneously decreased at advanced injection timing before 20.5 ºCA BTDC in conjunction with 58% cooled EGR rate in compared to baseline case.

Optimal Sizing of SSSC Controllers to Minimize Transmission Loss and a Novel Model of SSSC to Study Transient Response

In this paper, based on steady-state models of Flexible AC Transmission System (FACTS) devices, the sizing of static synchronous series compensator (SSSC) controllers in transmission network is formed as an optimization problem. The objective of this problem is to reduce the transmission losses in the network. The optimization problem is solved using particle swarm optimization (PSO) technique. The Newton-Raphson load flow algorithm is modified to consider the insertion of the SSSC devices in the network. A numerical example, illustrating the effectiveness of the proposed algorithm, is introduced. In addition, a novel model of a 3- phase voltage source converter (VSC) that is suitable for series connected FACTS a controller is introduced. The model is verified by simulation using Power System Blockset (PSB) and Simulink software.

Spray Combustion Dynamics under Thermoacoustic Oscillations

Thermoacoustic instabilities in combustors have remained a topic of investigation for over a few decades due to the challenges it posses to the operation of low emission gas turbines. For combustors burning liquid fuel, understanding the cause-andeffect relationship between spray combustion dynamics and thermoacoustic oscillations is imperative for the successful development of any control methodology for its mitigation. The paper presents some very unique operating characteristics of a kerosene-fueled diffusion type combustor undergoing limit-cycle oscillations. Combustor stability limits were mapped using three different-sized injectors. The results show that combustor instability depends on the characteristics of the fuel spray. A simple analytic analysis is also reported in support of a plausible explanation for the unique combustor behavior. The study indicates that high amplitude acoustic pressure in the combustor may cause secondary breakdown of fuel droplets resulting in premixed pre-vaporized type burning of the diffusion type combustor.

Experimental Investigation of a Novel Reaction in Reduction of Sulfates by Natural Gas as a Reducing Agent

In a pilot plant scale of a fluidized bed reactor, a reduction reaction of sodium sulfate by natural gas has been investigated. Natural gas is applied in this study as a reductant. Feed density, feed mass flow rate, natural gas and air flow rate (independent parameters)and temperature of bed and CO concentration in inlet and outlet of reactor (dependent parameters) were monitored and recorded at steady state. The residence time was adjusted close to value of traditional reaction [1]. An artificial neural network (ANN) was established to study dependency of yield and carbon gradient on operating parameters. Resultant 97% accuracy of applied ANN is a good prove that natural gas can be used as a reducing agent. Predicted ANN model for relation between other sources carbon gradient (accuracy 74%) indicates there is not a meaningful relation between other sources carbon variation and reduction process which means carbon in granule does not have significant effect on the reaction yield.

SDS-induced Serine Protease Activity of an Antiviral Red Fluorescent Protein

A rare phenomenon of SDS-induced activation of a latent protease activity associated with the purified silkworm excretory red fluorescent protein (SE-RFP) was noticed. SE-RFP aliquots incubated with SDS for different time intervals indicated that the protein undergoes an obligatory breakdown into a number of subunits which exhibit autoproteolytic (acting upon themselves) and/or heteroproteolytic (acting on other proteins) activities. A strong serine protease activity of SE-RFP subunits on Bombyx mori nucleopolyhedrovirus (BmNPV) polyhedral protein was detected by zymography technique. A complete inhibition of BmNPV infection to silkworms was observed by the oral administration assay of the SE-RFP. Here, it is proposed that the SE-RFP prevents the initial infection of BmNPV to silkworms by obliterating the polyhedral protein. This is the first report on a silkworm red fluorescent protein that exhibits a protease activity on exposure to SDS. The present studies would help in understanding the antiviral mechanism of silkworm red fluorescent proteins.

Design of High-speed Modified Booth Multipliers Operating at GHz Ranges

This paper describes the pipeline architecture of high-speed modified Booth multipliers. The proposed multiplier circuits are based on the modified Booth algorithm and the pipeline technique which are the most widely used to accelerate the multiplication speed. In order to implement the optimally pipelined multipliers, many kinds of experiments have been conducted. The speed of the multipliers is greatly improved by properly deciding the number of pipeline stages and the positions for the pipeline registers to be inserted. We described the proposed modified Booth multiplier circuits in Verilog HDL and synthesized the gate-level circuits using 0.13um standard cell library. The resultant multiplier circuits show better performance than others. Since the proposed multipliers operate at GHz ranges, they can be used in the systems requiring very high performance.

PPP in Light Rail Transit Systems in Spain

Light rail systems have proliferated in Spain in the last decade, following a tendency that is common not only in other European countries but also in other parts of the world. This paper reviews the benefits of light rail systems, both related to environmental issues and mobility issues. It analyses the evolution of light rail projects in Spain and shows that light rail systems in this country have evolved towards an extensive use of public-private partnerships. The analysis of the Spanish projects, however, does not contribute any conclusive evidence about whether public-private partnerships have been more efficient than publicly owned enterprises in building and operating light rail systems.

A Predictive Rehabilitation Software for Cerebral Palsy Patients

Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.

Dynamic Modeling of Underplateform Damper used in Turbomachinery

The present work deals with the structural analysis of turbine blades and modeling of turbine blades. A common failure mode for turbine machines is high cycle of fatigue of compressor and turbine blades due to high dynamic stresses caused by blade vibration and resonance within the operation range of the machinery. In this work, proper damping system will be analyzed to reduce the vibrating blade. The main focus of the work is the modeling of under platform damper to evaluate the dynamic analysis of turbine-blade vibrations. The system is analyzed using Bond graph technique. Bond graph is one of the most convenient ways to represent a system from the physical aspect in foreground. It has advantage of putting together multi-energy domains of a system in a single representation in a unified manner. The bond graph model of dry friction damper is simulated on SYMBOLS-shakti® software. In this work, the blades are modeled as Timoshenko beam. Blade Vibrations under different working conditions are being analyzed numerically.

Principal Component Analysis-Ranking as a Variable Selection Method for the Simultaneous Spectrophotometric Determination of Phenol, Resorcinol and Catechol in Real Samples

Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.

Worker Behavior Interpretation for Flexible Production

This paper addresses the problem of recognizing and interpreting the behavior of human workers in industrial environments for the purpose of integrating humans in software controlled manufacturing environments. In this work we propose a generic concept in order to derive solutions for task-related manual production applications. Thus, we are able to use a versatile concept providing flexible components and being less restricted to a specific problem or application. We instantiate our concept in a spot welding scenario in which the behavior of a human worker is interpreted when performing a welding task with a hand welding gun. We acquire signals from inertial sensors, video cameras and triggers and recognize atomic actions by using pose data from a marker based video tracking system and movement data from inertial sensors. Recognized atomic actions are analyzed on a higher evaluation level by a finite state machine.