Balanced and Unbalanced Voltage Sag Mitigation Using DSTATCOM with Linear and Nonlinear Loads

DSTATCOM is one of the equipments for voltage sag mitigation in power systems. In this paper a new control method for balanced and unbalanced voltage sag mitigation using DSTATCOM is proposed. The control system has two loops in order to regulate compensator current and load voltage. Delayed signal cancellation has been used for sequence separation. The compensator should protect sensitive loads against different types of voltage sag. Performance of the proposed method is investigated under different types of voltage sags for linear and nonlinear loads. Simulation results show appropriate operation of the proposed control system.

Review Risk and Threats Due to Dam Break

The one of most important objects in implementation of damage analysis observations is manner of dam break wave propagation. In this paper velocity and wave height due dam break in with and without tailwater states for appointment hazardous lands and flood radius are investigate. In order to modeling above phenomenon finite volume method of Roe type for solving shallow water equations is used. Results indicated that in the dry bed state risk radius due to dam break is too high. While in the wet bed risk radius has a less wide. Therefore in the first state constructions and storage facilities are encountered with destruction risk. Further velocity due to dam break in the second state is more comparing to the first state. Hence erosion and scour the river bed in the dry bed is too more compare to the wet bed.

Difference in Psychological Well-Being Based On Comparison of Religions: A Case Study in Pekan District, Pahang, Malaysia

The psychological well-being of a family is a subjective matter for evaluation, all the more when it involves the element of religions, whether Islam, Christianity, Buddhism or Hinduism. Each of these religions emphasises similar values and morals on family psychological well-being. This comparative study is specifically to determine the role of religion on family psychological well-being in Pekan district, Pahang, Malaysia. The study adopts a quantitative and qualitative mixed method design and considers a total of 412 samples of parents and children for the quantitative study, and 21 samples for the qualitative study. The quantitative study uses simple random sampling, whereas the qualitative sampling is purposive. The instrument for quantitative study is Ryff’s Psychological Well-being Scale and the qualitative study involves the construction of a guidelines protocol for in-depth interviews of respondents. The quantitative study uses the SPSS version .19 with One Way Anova, and the qualitative analysis is manual based on transcripts with specific codes and themes. The results show nonsignificance, that is, no significant difference among religions in all family psychological well-being constructs in the comparison of Islam, Christianity, Buddhism and Hinduism, thereby accepting a null hypothesis and rejecting an alternative hypothesis. The qualitative study supports the quantitative study, that is, all 21 respondents explain that no difference exists in psychological wellbeing in the comparison of teachings in all the religious mentioned. These implications may be used as guidelines for government and non-government bodies in considering religion as an important element in family psychological well-being in the long run. 

Molecular Evolutionary Analysis of Yeast Protein Interaction Network

To understand life as biological system, evolutionary understanding is indispensable. Protein interactions data are rapidly accumulating and are suitable for system-level evolutionary analysis. We have analyzed yeast protein interaction network by both mathematical and biological approaches. In this poster presentation, we inferred the evolutionary birth periods of yeast proteins by reconstructing phylogenetic profile. It has been thought that hub proteins that have high connection degree are evolutionary old. But our analysis showed that hub proteins are entirely evolutionary new. We also examined evolutionary processes of protein complexes. It showed that member proteins of complexes were tend to have appeared in the same evolutionary period. Our results suggested that protein interaction network evolved by modules that form the functional unit. We also reconstructed standardized phylogenetic trees and calculated evolutionary rates of yeast proteins. It showed that there is no obvious correlation between evolutionary rates and connection degrees of yeast proteins.

Long- term Irrigation with Dairy Factory Wastewater Influences Soil Quality

The effects of irrigation with dairy factory wastewater on soil properties were investigated at two sites that had received irrigation for > 60 years. Two adjoining paired sites that had never received DFE were also sampled as well as another seven fields from a wider area around the factory. In comparison with paired sites that had not received effluent, long-term wastewater irrigation resulted in an increase in pH, EC, extractable P, exchangeable Na and K and ESP. These changes were related to the use of phosphoric acid, NaOH and KOH as cleaning agents in the factory. Soil organic C content was unaffected by DFE irrigation but the size (microbial biomass C and N) and activity (basal respiration) of the soil microbial community were increased. These increases were attributed to regular inputs of soluble C (e.g. lactose) present as milk residues in the wastewater. Principal component analysis (PCA) of the soils data from all 11sites confirmed that the main effects of DFE irrigation were an increase in exchangeable Na, extractable P and microbial biomass C, an accumulation of soluble salts and a liming effect. PCA analysis of soil bacterial community structure, using PCR-DGGE of 16S rDNA fragments, generally separated individual sites from one another but did not group them according to irrigation history. Thus, whilst the size and activity of the soil microbial community were increased, the structure and diversity of the bacterial community remained unaffected.

A Comparison Study of a Symmetry Solution of Magneto-Elastico-Viscous Fluid along a Semi- Infinite Plate with Homotopy Perturbation Method and4th Order Runge–Kutta Method

The equations governing the flow of an electrically conducting, incompressible viscous fluid over an infinite flat plate in the presence of a magnetic field are investigated using the homotopy perturbation method (HPM) with Padé approximants (PA) and 4th order Runge–Kutta method (4RKM). Approximate analytical and numerical solutions for the velocity field and heat transfer are obtained and compared with each other, showing excellent agreement. The effects of the magnetic parameter and Prandtl number on velocity field, shear stress, temperature and heat transfer are discussed as well.

Hexagonal Honeycomb Sandwich Plate Optimization Using Gravitational Search Algorithm

Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.

Design of Smith-like Predictive Controller with Communication Delay Adaptation

This paper addresses the design of predictive networked controller with adaptation of a communication delay. The networked control system contains random delays from sensor to controller and from controller to actuator. The proposed predictive controller includes an adaptation loop which decreases the influence of communication delay on the control performance. Also, the predictive controller contains a filter which improves the robustness of the control system. The performance of the proposed adaptive predictive controller is demonstrated by simulation results in comparison with PI controller and predictive controller with constant delay.

Strategic Management via System Dynamics Simulation Models

This paper examines the problem of strategic management in highly turbulent dynamic business environmental conditions. As shown the high complexity of the problem can be managed with the use of System Dynamics Models and Computer Simulation in obtaining insights, and thorough understanding of the interdependencies between the organizational structure and the business environmental elements, so that effective product –market strategies can be designed. Simulation reveals the underlying forces that hold together the structure of an organizational system in relation to its environment. Such knowledge will contribute to the avoidance of fundamental planning errors and enable appropriate proactive well focused action.

Application of Central Composite Design Based Response Surface Methodology in Parameter Optimization and on Cellulase Production Using Agricultural Waste

Response Surface Methodology (RSM) is a powerful and efficient mathematical approach widely applied in the optimization of cultivation process. Cellulase enzyme production by Trichoderma reesei RutC30 using agricultural waste rice straw and banana fiber as carbon source were investigated. In this work, sequential optimization strategy based statistical design was employed to enhance the production of cellulase enzyme through submerged cultivation. A fractional factorial design (26-2) was applied to elucidate the process parameters that significantly affect cellulase production. Temperature, Substrate concentration, Inducer concentration, pH, inoculum age and agitation speed were identified as important process parameters effecting cellulase enzyme synthesis. The concentration of lignocelluloses and lactose (inducer) in the cultivation medium were found to be most significant factors. The steepest ascent method was used to locate the optimal domain and a Central Composite Design (CCD) was used to estimate the quadratic response surface from which the factor levels for maximum production of cellulase were determined.

Mining Correlated Bicluster from Web Usage Data Using Discrete Firefly Algorithm Based Biclustering Approach

For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a dataset. It retrieves subgroups of objects that are similar in one subgroup of variables and different in the remaining variables. Firefly Algorithm (FA) is a recently-proposed metaheuristic inspired by the collective behavior of fireflies. This paper provides a preliminary assessment of discrete version of FA (DFA) while coping with the task of mining coherent and large volume bicluster from web usage dataset. The experiments were conducted on two web usage datasets from public dataset repository whereby the performance of FA was compared with that exhibited by other population-based metaheuristic called binary Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of DFA while tackling the biclustering problem.

A Neural Network Approach in Predicting the Blood Glucose Level for Diabetic Patients

Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Classification of Non Stationary Signals Using Ben Wavelet and Artificial Neural Networks

The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Angular-Coordinate Driven Radial Tree Drawing

We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment

The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.

T-Wave Detection Based on an Adjusted Wavelet Transform Modulus Maxima

The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.

Comparative Studies on Vertical Stratification,Floristic Composition, and Woody Species Diversity of Subtropical Evergreen Broadleaf Forests Between the Ryukyu Archipelago, Japan, and South China

In order to compare vertical stratification, floristic composition, and woody species diversity of subtropical evergreen broadleaf forests between the Ryukyu Archipelago, Japan, and South China, tree censuses in a 400 m2 plot in Ishigaki Island and a 1225 m2 plot in Dinghushan Nature Reserve were performed. Both of the subtropical forests consisted of five vertical strata. The floristic composition of the Ishigaki forest was quite different from that of the Dinghushan forest in terms of similarity on a species level (Kuno-s similarity index r0 = 0.05). The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom stratum upward in both forests, except H' for the top stratum in the Ishigaki forest and the upper two strata in the Dinghushan forest. The woody species diversity in the Dinghushan forest (H'= 3.01 bit) was much lower than that in the Ishigaki forest (H'= 4.36 bit).

Evaluation on the Viability of Combined Heat and Power with Different Distributed Generation Technologies for Various Bindings in Japan

This paper has examined the energy consumption characteristics in six different buildings including apartments, offices, commercial buildings, hospitals, hotels and educational facilities. Then 5-hectare (50000m2) development site for respective building-s type has been assumed as case study to evaluate the introduction effect of Combined Heat and Power (CHP). All kinds of CHP systems with different distributed generation technologies including Gas Turbine (GT), Gas Engine (GE), Diesel Engine (DE), Solid Oxide Fuel Cell (SOFC) and Polymer Electrolyte Fuel Cell (PEFC), have been simulated by using HEATMAP, CHP system analysis software. And their primary energy utilization efficiency, energy saving ratio and CO2 reduction ratio have evaluated and compared respectively. The results can be summarized as follows: Various buildings have their special heat to power ratio characteristics. Matching the heat to power ratio demanded from an individual building with that supplied from a CHP system is very important. It is necessary to select a reasonable distributed generation technologies according to the load characteristics of various buildings. Distributed generation technologies with high energy generating efficiency and low heat to power ratio, like SOFC and PEFC is more reasonable selection for Building Combined Heat and Power (BCHP). CHP system is an attractive option for hotels, hospitals and apartments in Japan. The users can achieve high energy saving and environmental benefit by introducing a CHP systems. In others buildings, especially like commercial buildings and offices, the introduction of CHP system is unreasonable.

Effect of Surface Stress on the Deformation around a Nanosized Elliptical Hole: a Finite Element Study

When the characteristic length of an elastic solid is down to the nanometer level, its deformation behavior becomes size dependent. Surface energy /surface stress have recently been applied to explain such dependency. In this paper, the effect of strain-independent surface stress on the deformation of an isotropic elastic solid containing a nanosized elliptical hole is studied by the finite element method. Two loading cases are considered, in the first case, hoop stress along the rim of the elliptical hole induced by pure surface stress is studied, in the second case, hoop stress around the elliptical opening under combined remote tension and surface stress is investigated. It has been shown that positive surface stress induces compressive hoop stress along the hole, and negative surface stress has opposite effect, maximum hoop stress occurs near the major semi-axes of the ellipse. Under combined loading of remote tension and surface stress, stress concentration around the hole can be either intensified or weakened depending on the sign of the surface stress.

Human Facial Expression Recognition using MANFIS Model

Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.