Optimal Embedded Generation Allocation in Distribution System Employing Real Coded Genetic Algorithm Method

This paper proposes a new methodology for the optimal allocation and sizing of Embedded Generation (EG) employing Real Coded Genetic Algorithm (RCGA) to minimize the total power losses and to improve voltage profiles in the radial distribution networks. RCGA is a method that uses continuous floating numbers as representation which is different from conventional binary numbers. The RCGA is used as solution tool, which can determine the optimal location and size of EG in radial system simultaneously. This method is developed in MATLAB. The effect of EG units- installation and their sizing to the distribution networks are demonstrated using 24 bus system.

Improved Text-Independent Speaker Identification using Fused MFCC and IMFCC Feature Sets based on Gaussian Filter

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel- Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.

The Nonlinear Dynamic Elasto-Plastic Analysis for Evaluating the Controlling Effectiveness and Failure Mechanism of the MSCSS

This paper focuses on the Mega-Sub Controlled Structure Systems (MSCSS) performances and characteristics regarding the new control principle contained in MSCSS subjected to strong earthquake excitations. The adopted control scheme consists of modulated sub-structures where the control action is achieved by viscous dampers and sub-structure own configuration. The elastic-plastic time history analysis under severe earthquake excitation is analyzed base on the Finite Element Analysis Method (FEAM), and some comparison results are also given in this paper. The result shows that the MSCSS systems can remarkably reduce vibrations effects more than the mega-sub structure (MSS). The study illustrates that the improved MSCSS presents good seismic resistance ability even at 1.2g and can absorb seismic energy in the structure, thus imply that structural members cross section can be reduce and achieve to good economic characteristics. Furthermore, the elasto-plastic analysis demonstrates that the MSCSS is accurate enough regarding international building evaluation and design codes. This paper also shows that the elasto-plastic dynamic analysis method is a reasonable and reliable analysis method for structures subjected to strong earthquake excitations and that the computed results are more precise.

Visualized Characterization of Molecular Mobility for Water Species in Foods

Six parameters, the effective diffusivity (De), activation energy of De, pre-exponential factor of De, amount (ASOW) of self-organized water species, and amplitude (α) of the forced oscillation of the molecular mobility (1/tC) derived from the forced cyclic temperature change operation, were characterized by using six typical foods, squid, sardines, scallops, salmon, beef, and pork, as a function of the correlation time (tC) of the water molecule-s proton retained in the foods. Each of the six parameters was clearly divided into the water species A1 and A2 at a specified value of tC =10-8s (=CtC), indicating an anomalous change in the physicochemical nature of the water species at the CtC. The forced oscillation of 1/tC clearly demonstrated a characteristic mode depending on the food shown as a three dimensional map associated with 1/tC, the amount of self-organized water, and tC.

Pesticides Use in Rural Settings in Romania

The environment pollution with pesticides and heavy metals is a recognized problem nowadays, with extension to the global scale the tendency of amplification. Even with all the progress in the environmental field, both in the emphasize of the effect of the pollutants upon health, the linked studies environment-health are insufficient, not only in Romania but all over the world also. We aim to describe the particular situation in Romania regarding the uncontrolled use of pesticides, to identify and evaluate the risk zones for health and the environment in Romania, with the final goal of designing adequate programs for reduction and control of the risk sources. An exploratory study was conducted to determine the magnitude of the pesticide use problem in a population living in Saliste, a rural setting in Transylvania, Romania. The significant stakeholders in Saliste region were interviewed and a sample from the population living in Saliste area was selected to fill in a designed questionnaire. All the selected participants declared that they used pesticides in their activities for more than one purpose. They declared they annually applied pesticides for a period of time between 11 and 30 years, from 5 to 9 days per year on average, mainly on crops situated at some distance from the houses but high risk behavior was identified as the volunteers declared the use of pesticides in the backyard gardens, near their homes, where children were playing. The pesticide applicators did not have the necessary knowledge about safety and exposure. The health data must be correlated with exposure biomarkers in attempt to identify the possible health effects of the pesticides exposure. Future plans include educational campaigns to raise the awareness of the population on the danger of uncontrolled use of pesticides.

Detection, Tracking and Classification of Vehicles and Aircraft based on Magnetic Sensing Technology

Existing ground movement surveillance technologies at airports are subjected to limitations due to shadowing effects or multiple reflections. Therefore, there is a strong demand for a new sensing technology, which will be cost effective and will provide detection of non-cooperative targets under any weather conditions. This paper aims to present a new intelligent system, developed within the framework of the EC-funded ISMAEL project, which is based on a new magnetic sensing technology and provides detection, tracking and automatic classification of targets moving on the airport surface. The system is currently being installed at two European airports. Initial experimental results under real airport traffic demonstrate the great potential of the proposed system.

Remote Operation of CNC Milling Through Virtual Simulation and Remote Desktop Interface

Increasing the demand for effectively use of the production facility requires the tools for sharing the manufacturing facility through remote operation of the machining process. This research introduces the methodology of machining technology for direct remote operation of networked milling machine. The integrated tools with virtual simulation, remote desktop protocol and Setup Free Attachment for remote operation of milling process are proposed. Accessing and monitoring of machining operation is performed by remote desktop interface and 3D virtual simulations. Capability of remote operation is supported by an auto setup attachment with a reconfigurable pin type setup free technology installed on the table of CNC milling machine to perform unattended machining process. The system is designed using a computer server and connected to a PC based controlled CNC machine for real time monitoring. A client will access the server through internet communication and virtually simulate the machine activity. The result has been presented that combination between real time virtual simulation and remote desktop tool is enabling to operate all machine tool functions and as well as workpiece setup..

Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model

Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.

Plastic Flow through Taper Dies: A Threedimensional Analysis

The plastic flow of metal in the extrusion process is an important factor in controlling the mechanical properties of the extruded products. It is, however, difficult to predict the metal flow in three dimensional extrusions of sections due to the involvement of re-entrant corners. The present study is to find an upper bound solution for the extrusion of triangular sectioned through taper dies from round sectioned billet. A discontinuous kinematically admissible velocity field (KAVF) is proposed. From the proposed KAVF, the upper bound solution on non-dimensional extrusion pressure is determined with respect to the chosen process parameters. The theoretical results are compared with experimental results to check the validity of the proposed velocity field. An extrusion setup is designed and fabricated for the said purpose, and all extrusions are carried out using circular billets. Experiments are carried out with commercially available lead at room temperature.

Removal of Volatile Organic Compounds from Contaminated Surfactant Solution using Co-Curren Vacuum Stripping

There has been a growing interest in utilizing surfactants in remediation processes to separate the hydrophobic volatile organic compounds (HVOCs) from aqueous solution. One attractive process is cloud point extraction (CPE), which utilizes nonionic surfactants as a separating agent. Since the surfactant cost is a key determination of the economic viability of the process, it is important that the surfactants are recycled and reused. This work aims to study the performance of the co-current vacuum stripping using a packed column for HVOCs removal from contaminated surfactant solution. Six types HVOCs are selected as contaminants. The studied surfactant is the branched secondary alcohol ethoxylates (AEs), Tergitol TMN-6 (C14H30O2). The volatility and the solubility of HVOCs in surfactant system are determined in terms of an apparent Henry’s law constant and a solubilization constant, respectively. Moreover, the HVOCs removal efficiency of vacuum stripping column is assessed in terms of percentage of HVOCs removal and the overall liquid phase volumetric mass transfer coefficient. The apparent Henry’s law constant of benzenz , toluene, and ethyl benzene were 7.00×10-5, 5.38×10-5, 3.35× 10-5 respectively. The solubilization constant of benzene, toluene, and ethyl benzene were 1.71, 2.68, 7.54 respectively. The HVOCs removal for all solute were around 90 percent.

Ψ-Eventual Stability of Differential System with Impulses

In this paper, the criteria of Ψ-eventual stability have been established for generalized impulsive differential systems of multiple dependent variables. The sufficient conditions have been obtained using piecewise continuous Lyapunov function. An example is given to support our theoretical result.

Comparative Study of Virtual Sickness between a Single-screen and Three-screen from Parallax Affect

Virtual environment induces simulator sickness effect for some users. The purpose of this research is to compare the simulation sickness relative with parallax affect in one-screen and three-screen HoloStageTM system, measured by Simulation Sickness Questionnaire (SSQ). The results show the subjects tested in three-screen has less sickness than one-screen and effect from the Oculomotor (O) more than from the Disorientation (D) and more than from the Nausea (N) or represented in O>D>N.

Receding Horizon Filtering for Mobile Robot Systems with Cross-Correlated Sensor Noises

This paper reports on a receding horizon filtering for mobile robot systems with cross-correlated sensor noises and uncertainties. Also, the effect of uncertain parameters in the state of the tracking error model performance is considered. A distributed fusion receding horizon filter is proposed. The distributed fusion filtering algorithm represents the optimal linear combination of the local filters under the minimum mean square error criterion. The derivation of the error cross-covariances between the local receding horizon filters is the key of this paper. Simulation results of the tracking mobile robot-s motion demonstrate high accuracy and computational efficiency of the distributed fusion receding horizon filter.

Screening Wheat Parents of Mapping Population for Heat and Drought Tolerance, Detection of Wheat Genetic Variation

To evaluate genetic variation of wheat (Triticum aestivum) affected by heat and drought stress on eight Australian wheat genotypes that are parents of Doubled Haploid (HD) mapping populations at the vegetative stage, the water stress experiment was conducted at 65% field capacity in growth room. Heat stress experiment was conducted in the research field under irrigation over summer. Result show that water stress decreased dry shoot weight and RWC but increased osmolarity and means of Fv/Fm values in all varieties except for Krichauff. Krichauff and Kukri had the maximum RWC under drought stress. Trident variety was shown maximum WUE, osmolarity (610 mM/Kg), dry mater, quantum yield and Fv/Fm 0.815 under water stress condition. However, the recovery of quantum yield was apparent between 4 to 7 days after stress in all varieties. Nevertheless, increase in water stress after that lead to strong decrease in quantum yield. There was a genetic variation for leaf pigments content among varieties under heat stress. Heat stress decreased significantly the total chlorophyll content that measured by SPAD. Krichauff had maximum value of Anthocyanin content (2.978 A/g FW), chlorophyll a+b (2.001 mg/g FW) and chlorophyll a (1.502 mg/g FW). Maximum value of chlorophyll b (0.515 mg/g FW) and Carotenoids (0.234 mg/g FW) content belonged to Kukri. The quantum yield of all varieties decreased significantly, when the weather temperature increased from 28 ÔùªC to 36 ÔùªC during the 6 days. However, the recovery of quantum yield was apparent after 8th day in all varieties. The maximum decrease and recovery in quantum yield was observed in Krichauff. Drought and heat tolerant and moderately tolerant wheat genotypes were included Trident, Krichauff, Kukri and RAC875. Molineux, Berkut and Excalibur were clustered into most sensitive and moderately sensitive genotypes. Finally, the results show that there was a significantly genetic variation among the eight varieties that were studied under heat and water stress.

Design of Genetic-Algorithm Based Robust Power System Stabilizer

This paper presents a systematic approach for the design of power system stabilizer using genetic algorithm and investigates the robustness of the GA based PSS. The proposed approach employs GA search for optimal setting of PSS parameters. The performance of the proposed GPSS under small and large disturbances, loading conditions and system parameters is tested. The eigenvalue analysis and nonlinear simulation results show the effectiveness of the GPSS to damp out the system oscillations. It is found tat the dynamic performance with the GPSS shows improved results, over conventionally tuned PSS over a wide range of operating conditions.

Effect of Adaptation Gain on system Performance for Model Reference Adaptive Control Scheme using MIT Rule

Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. This paper deals with application of model reference adaptive control scheme in first order system. The rule which is used for this application is MIT rule. This paper also shows the effect of adaptation gain on the system performance. Simulation is done in MATLAB and results are discussed in detail.

Embedded Singly Diagonally Implicit Runge-Kutta –Nystrom Method Order 5(4) for the Integration of Special Second Order ODEs

In this paper a new embedded Singly Diagonally Implicit Runge-Kutta Nystrom fourth order in fifth order method for solving special second order initial value problems is derived. A standard set of test problems are tested upon and comparisons on the numerical results are made when the same set of test problems are reduced to first order systems and solved using the existing embedded diagonally implicit Runge-Kutta method. The results suggests the superiority of the new method.

Development of a Semantic Wiki-based Feature Library for the Extraction of Manufacturing Feature and Manufacturing Information

A manufacturing feature can be defined simply as a geometric shape and its manufacturing information to create the shape. In a feature-based process planning system, feature library that consists of pre-defined manufacturing features and the manufacturing information to create the shape of the features, plays an important role in the extraction of manufacturing features with their proper manufacturing information. However, to manage the manufacturing information flexibly, it is important to build a feature library that can be easily modified. In this paper, the implementation of Semantic Wiki for the development of the feature library is proposed.

Diagnosis of Multivariate Process via Nonlinear Kernel Method Combined with Qualitative Representation of Fault Patterns

The fault detection and diagnosis of complicated production processes is one of essential tasks needed to run the process safely with good final product quality. Unexpected events occurred in the process may have a serious impact on the process. In this work, triangular representation of process measurement data obtained in an on-line basis is evaluated using simulation process. The effect of using linear and nonlinear reduced spaces is also tested. Their diagnosis performance was demonstrated using multivariate fault data. It has shown that the nonlinear technique based diagnosis method produced more reliable results and outperforms linear method. The use of appropriate reduced space yielded better diagnosis performance. The presented diagnosis framework is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. The use of reduced model space helps to mitigate the sensitivity of the fault pattern to noise.

A Comparison of the Sum of Squares in Linear and Partial Linear Regression Models

In this paper, estimation of the linear regression model is made by ordinary least squares method and the partially linear regression model is estimated by penalized least squares method using smoothing spline. Then, it is investigated that differences and similarity in the sum of squares related for linear regression and partial linear regression models (semi-parametric regression models). It is denoted that the sum of squares in linear regression is reduced to sum of squares in partial linear regression models. Furthermore, we indicated that various sums of squares in the linear regression are similar to different deviance statements in partial linear regression. In addition to, coefficient of the determination derived in linear regression model is easily generalized to coefficient of the determination of the partial linear regression model. For this aim, it is made two different applications. A simulated and a real data set are considered to prove the claim mentioned here. In this way, this study is supported with a simulation and a real data example.