Elliptical Features Extraction Using Eigen Values of Covariance Matrices, Hough Transform and Raster Scan Algorithms

In this paper, we introduce a new method for elliptical object identification. The proposed method adopts a hybrid scheme which consists of Eigen values of covariance matrices, Circular Hough transform and Bresenham-s raster scan algorithms. In this approach we use the fact that the large Eigen values and small Eigen values of covariance matrices are associated with the major and minor axial lengths of the ellipse. The centre location of the ellipse can be identified using circular Hough transform (CHT). Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of circumference pixels is identified using raster scan algorithm which uses the geometrical symmetry property. This method does not require the evaluation of tangents or curvature of edge contours, which are generally very sensitive to noise working conditions. The proposed method has the advantages of small storage, high speed and accuracy in identifying the feature. The new method has been tested on both synthetic and real images. Several experiments have been conducted on various images with considerable background noise to reveal the efficacy and robustness. Experimental results about the accuracy of the proposed method, comparisons with Hough transform and its variants and other tangential based methods are reported.

Power Quality Improvement Using PI and Fuzzy Logic Controllers Based Shunt Active Filter

In recent years the large scale use of the power electronic equipment has led to an increase of harmonics in the power system. The harmonics results into a poor power quality and have great adverse economical impact on the utilities and customers. Current harmonics are one of the most common power quality problems and are usually resolved by using shunt active filter (SHAF). The main objective of this work is to develop PI and Fuzzy logic controllers (FLC) to analyze the performance of Shunt Active Filter for mitigating current harmonics under balanced and unbalanced sinusoidal source voltage conditions for normal load and increased load. When the supply voltages are ideal (balanced), both PI and FLC are converging to the same compensation characteristics. However, the supply voltages are non-ideal (unbalanced), FLC offers outstanding results. Simulation results validate the superiority of FLC with triangular membership function over the PI controller.

A Reconfigurable Distributed Multiagent System Optimized for Scalability

This paper proposes a novel solution for optimizing the size and communication overhead of a distributed multiagent system without compromising the performance. The proposed approach addresses the challenges of scalability especially when the multiagent system is large. A modified spectral clustering technique is used to partition a large network into logically related clusters. Agents are assigned to monitor dedicated clusters rather than monitor each device or node. The proposed scalable multiagent system is implemented using JADE (Java Agent Development Environment) for a large power system. The performance of the proposed topologyindependent decentralized multiagent system and the scalable multiagent system is compared by comprehensively simulating different fault scenarios. The time taken for reconfiguration, the overall computational complexity, and the communication overhead incurred are computed. The results of these simulations show that the proposed scalable multiagent system uses fewer agents efficiently, makes faster decisions to reconfigure when a fault occurs, and incurs significantly less communication overhead.

Investigating Sustainable Neighborhood Development in Jahanshahr

Nowadays, access to sustainable development in cities is assumed as one of the most important goals of urban managers. In the meanwhile, neighborhood as the smallest unit of urban spatial organization has a substantial effect on urban sustainability. Hence, attention to and focus on this subject is highly important in urban development plans. The objective of this study is evaluation of the status of Jahanshahr Neighborhood in Karaj city based on sustainable neighborhood development indicators. This research has been applied based on documentary method and field surveys. Also, evaluating of Jahanshahr Neighborhood of Karaj shows that it has a high level in sustainability in physical and economical dimension while a low level in cultural and social dimension. For this purpose, this neighborhood as a semi-sustainable neighborhood must take measures for development of collective spaces and efficiency of utilizing the public neighborhood spaces via collaboration of citizens and officials.

A Novel Stator Resistance Estimation Method and Control Design of Speed-Sensorless Induction Motor Drives

Speed sensorless systems are intensively studied during recent years; this is mainly due to their economical benefit and fragility of mechanical sensors and also the difficulty of installing this type of sensor in many applications. These systems suffer from instability problems and sensitivity to parameter mismatch at low speed operation. In this paper an analysis of adaptive observer stability with stator resistance estimation is given.

Laminar Free Convection of Nanofluid Flow in Horizontal Porous Annulus

A numerical study has been carried out to investigate the heat transfer by natural convection of nanofluid taking Cu as nanoparticles and the water as based fluid in a three dimensional annulus enclosure filled with porous media (silica sand) between two horizontal concentric cylinders with 12 annular fins of 2.4mm thickness attached to the inner cylinder under steady state conditions. The governing equations which used are continuity, momentum and energy equations under an assumptions used Darcy law and Boussinesq-s approximation which are transformed to dimensionless equations. The finite difference approach is used to obtain all the computational results using the MATLAB-7. The parameters affected on the system are modified Rayleigh number (10 ≤Ra*≤ 1000), fin length Hf (3, 7 and 11mm), radius ratio Rr (0.293, 0.365 and 0.435) and the volume fraction(0 ≤ ¤ò ≤ 0 .35). It was found that the average Nusselt number depends on (Ra*, Hf, Rr and φ). The results show that, increasing of fin length decreases the heat transfer rate and for low values of Ra*, decreasing Rr cause to decrease Nu while for Ra* greater than 100, decreasing Rr cause to increase Nu and adding Cu nanoparticles with 0.35 volume fraction cause 27.9% enhancement in heat transfer. A correlation for Nu in terms of Ra*, Hf and φ, has been developed for inner hot cylinder.

Seismic Behavior and Capacity/Demand Analyses of a Simply-Supported Multi-Span Precast Bridge

This paper presents the results of an analytical study on the seismic response of a Multi-Span-Simply-Supported precast bridge in Washington State. The bridge was built in the early 1960's along Interstate 5 and was widened the first time in 1979 and the second time in 2001. The primary objective of this research project is to determine the seismic vulnerability of the bridge in order to develop the required retrofit measure. The seismic vulnerability of the bridge is evaluated using two seismic evaluation methods presented in the FHWA Seismic Retrofitting Manual for Highway Bridges, Method C and Method D2. The results of the seismic analyses demonstrate that Method C and Method D2 vary markedly in terms of the information they provide to the bridge designer regarding the vulnerability of the bridge columns.

A Scenario Oriented Supplier Selection by Considering a Multi Tier Supplier Network

One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article model developed based on the features of second tiers suppliers and four scenarios are predicted in order to help the decision maker (DM) in making up his/her mind. In addition two tiers of suppliers have been considered as a chain of suppliers. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second tier suppliers features as criteria for selecting the best supplier.

Business Rules for Data Warehouse

Business rules and data warehouse are concepts and technologies that impact a wide variety of organizational tasks. In general, each area has evolved independently, impacting application development and decision-making. Generating knowledge from data warehouse is a complex process. This paper outlines an approach to ease import of information and knowledge from a data warehouse star schema through an inference class of business rules. The paper utilizes the Oracle database for illustrating the working of the concepts. The star schema structure and the business rules are stored within a relational database. The approach is explained through a prototype in Oracle-s PL/SQL Server Pages.

Visualization of Code Clone Detection Results and the Implementation with Structured Data

This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.

Analytical Solution for Free Vibration of Rectangular Kirchhoff Plate from Wave Approach

In this paper, an analytical approach for free vibration analysis of four edges simply supported rectangular Kirchhoff plates is presented. The method is based on wave approach. From wave standpoint vibration propagate, reflect and transmit in a structure. Firstly, the propagation and reflection matrices for plate with simply supported boundary condition are derived. Then, these matrices are combined to provide a concise and systematic approach to free vibration analysis of a simply supported rectangular Kirchhoff plate. Subsequently, the eigenvalue problem for free vibration of plates is formulated and the equation of plate natural frequencies is constructed. Finally, the effectiveness of the approach is shown by comparison of the results with existing classical solution.

Assessment of Cadmium Level in Water from Watershed of the Kowsar Dam

The Kowsar dam supply water for different usages such as drinking, industrial, agricultural and aquaculture farms usages and located next to the city of Dehdashat in Kohgiluye and Boyerahmad province in southern Iran. There are some towns and villages on the Kowsar dam watersheds, which Dehdasht and Choram are the most important and populated cities in this area. The study was undertaken to assess the status of water quality in the urban areas of the Kowsar dam. A total of 28 water samples were collected from 6 stations on surface water and 1 station from groundwater on the watershed of the Kowsar dam. All the samples were analyzed for Cd concentration using standard procedures. The results were compared with other national and international standards. Among the analyzed samples, as the maximum value of cadmium (1.131 μg/L) was observed on the station 2 at the winter 2009, all the samples analyzed were within the maximum admissible limits by the United States Environmental Protection Agency, EU, WHO, New Zealand , Australian, Iranian, and the Indian standards. In general results of the present study have shown that Cd mean values of stations No. 4, 1 and 2 with 0.5135, 0.0.4733 and 0.4573 μg/L respectively are higher than the other stations . Although Cd level of all samples and stations have had normal values but this is an indication of pollution potential and hazards because of human activity and waste water of towns in the areas, which can effect on human health implications in future. This research, therefore, recommends the government and other responsible authorities to take suitable improving measures in the Kowsar dam watershed-s.

Fuzzy Control of the Air Conditioning System at Different Operating Pressures

The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.

A Monte Carlo Method to Data Stream Analysis

Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte Carlo method in the approximation step. The data reduction has been performed horizontally and vertically through our EMR sampling method. The proposed method is analyzed by a series of experiments. We apply our algorithm on clustering and classification tasks to evaluate the utility of our approach.

Performance Comparison of Parallel Sorting Algorithms on the Cluster of Workstations

Sorting appears the most attention among all computational tasks over the past years because sorted data is at the heart of many computations. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. Many parallel sorting algorithms have been investigated for a variety of parallel computer architectures. In this paper, three parallel sorting algorithms have been implemented and compared in terms of their overall execution time. The algorithms implemented are the odd-even transposition sort, parallel merge sort and parallel rank sort. Cluster of Workstations or Windows Compute Cluster has been used to compare the algorithms implemented. The C# programming language is used to develop the sorting algorithms. The MPI (Message Passing Interface) library has been selected to establish the communication and synchronization between processors. The time complexity for each parallel sorting algorithm will also be mentioned and analyzed.

Ezilla Cloud Service with Cassandra Database for Sensor Observation System

The main mission of Ezilla is to provide a friendly interface to access the virtual machine and quickly deploy the high performance computing environment. Ezilla has been developed by Pervasive Computing Team at National Center for High-performance Computing (NCHC). Ezilla integrates the Cloud middleware, virtualization technology, and Web-based Operating System (WebOS) to form a virtual computer in distributed computing environment. In order to upgrade the dataset and speedup, we proposed the sensor observation system to deal with a huge amount of data in the Cassandra database. The sensor observation system is based on the Ezilla to store sensor raw data into distributed database. We adopt the Ezilla Cloud service to create virtual machines and login into virtual machine to deploy the sensor observation system. Integrating the sensor observation system with Ezilla is to quickly deploy experiment environment and access a huge amount of data with distributed database that support the replication mechanism to protect the data security.

Signal-to-Noise Ratio Improvement of EMCCD Cameras

Over the past years, the EMCCD has had a profound influence on photon starved imaging applications relying on its unique multiplication register based on the impact ionization effect in the silicon. High signal-to-noise ratio (SNR) means high image quality. Thus, SNR improvement is important for the EMCCD. This work analyzes the SNR performance of an EMCCD with gain off and on. In each mode, simplified SNR models are established for different integration times. The SNR curves are divided into readout noise (or CIC) region and shot noise region by integration time. Theoretical SNR values comparing long frame integration and frame adding in each region are presented and discussed to figure out which method is more effective. In order to further improve the SNR performance, pixel binning is introduced into the EMCCD. The results show that pixel binning does obviously improve the SNR performance, but at the expensive of the spatial resolution.

Faults Forecasting System

This paper presents Faults Forecasting System (FFS) that utilizes statistical forecasting techniques in analyzing process variables data in order to forecast faults occurrences. FFS is proposing new idea in detecting faults. Current techniques used in faults detection are based on analyzing the current status of the system variables in order to check if the current status is fault or not. FFS is using forecasting techniques to predict future timing for faults before it happens. Proposed model is applying subset modeling strategy and Bayesian approach in order to decrease dimensionality of the process variables and improve faults forecasting accuracy. A practical experiment, designed and implemented in Okayama University, Japan, is implemented, and the comparison shows that our proposed model is showing high forecasting accuracy and BEFORE-TIME.

Evaluation of Protein Digestibility in Canola Meals between Caecectomised and Intact Adult Cockerels

The experiment was conducted to evaluate digestibility quantities of protein in Canola Meals (CMs) between caecectomised and intact adult Rhode Island Red (RIR) cockerels with using conventional addition method (CAM) for 7 d: a 4-d adaptation and a 3-d experiment period on the basis of a completely randomized design with 4 replicates. Results indicated that caecectomy decreased (P

The Role of Faith-based Organizations in Building Democratic Process: Achieving Universal Primary Education in Sierra Leone

This paper aims to argue that religion and Faith-based Organizations (FBOs) contribute to building democratic process through the provision of education in Sierra Leone. Sierra Leone experienced a civil war from 1991 to 2002 and about 70 percent of the population lives in poverty. While the government has been in the process of rebuilding the nation, many forms of Civil Society Organizations (CSOs), including FBOs, have played a significant role in promoting social development. Education plays an important role in supporting people-s democratic movements through knowledge acquisition, spiritual enlightenment and empowerment. This paper discusses religious tolerance in Sierra Leone and how FBOs have contributed to the provision of primary education in Sierra Leone. This study is based on the author-s field research, which involved interviews with teachers and development stakeholders, notably government officials, Non-governmental Organizations (NGOs) and FBOs, as well as questionnaires completed by pupils, parents and teachers.