Investigations into Effect of Neural Network Predictive Control of UPFC for Improving Transient Stability Performance of Multimachine Power System

The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.

A Functional Beverage: Lemonade

Fruits and vegetables are the essentials of a healthy diet, mainly because of their antioxidant properties contributing to disease blockage especially for some certain types of cancer. Being a favourite fruit, citrus are produced for economic and commercial purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has an important place in export products of Turkey. Lemon has a great importance on human nutrition with regard to being a source of nutrients, flavonoids, vitamin C and minerals. It is used for food flavouring and pickling and also processed for lemonade. By processing citrus into fruit juices, consumption may increase and also become easier. Like many fruits and vegetables lemons are cheap and abundant during harvesting period, while they are quite expensive in other seasons. Lemon juice and concentrate production allows consumers to get benefits from lemon fruit in any time of the year. Lemonade is getting in to the focus of consumers’ attention preferring non-carbonated drinks. The demand of healthy, convenient functional foods affects consumer trends through innovative products. For this reason, lemonade could be enriched with different natural herb extracts such as ginger (Zingiber officinale), linden (Tilia cordata), and mint (Mentha piperita).

An Empirical Model to Calculate the Threads Stripping of a Bolt Installed in a Tapped Part

To determine the length of engagement threads of a bolt installed in a tapped part in order to avoid the threads stripping remains a very current problem in the design of the thread assemblies. It does not exist a calculation method formalized for the cases where the bolt is screwed directly in a ductile material. In this article, we study the behavior of the threads stripping of a loaded assembly by using a modelling by finite elements and a rupture criterion by damage. This modelling enables us to study the different parameters likely to influence the behavior of this bolted connection. We study in particular, the influence of couple of materials constituting the connection, of the bolt-s diameter and the geometrical characteristics of the tapped part, like the external diameter and the length of engagement threads. We established an experiments design to know the most significant parameters. That enables us to propose a simple expression making possible to calculate the resistance of the threads whatever the metallic materials of the bolt and the tapped part. We carried out stripping tests in order to validate our model. The estimated results are very close to those obtained by the tests.

A Comparison and Analysis of Name Matching Algorithms

Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.

Hybrid Association Control Scheme and Load Balancing in Wireless LANs

This paper presents a hybrid association control scheme that can maintain load balancing among access points in the wireless LANs and can satisfy the quality of service requirements of the multimedia traffic applications. The proposed model is mathematically described as a linear programming model. Simulation study and analysis were conducted in order to demonstrate the performance of the proposed hybrid load balancing and association control scheme. Simulation results shows that the proposed scheme outperforms the other schemes in term of the percentage of blocking and the quality of the data transfer rate providing to the multimedia and real-time applications.

Reliable One-Dimensional Model of Two-Dimensional Insulated Oval Duct Considering Heat Radiation

The reliable results of an insulated oval duct considering heat radiation are obtained basing on accurate oval perimeter obtained by integral method as well as one-dimensional Plane Wedge Thermal Resistance (PWTR) model. This is an extension study of former paper of insulated oval duct neglecting heat radiation. It is found that in the practical situations with long-short-axes ratio a/b 4.5% while t/R2

An Off-the-Shelf Scheme for Dependable Grid Systems Using Virtualization

Recently, grid computing has been widely focused on the science, industry, and business fields, which are required a vast amount of computing. Grid computing is to provide the environment that many nodes (i.e., many computers) are connected with each other through a local/global network and it is available for many users. In the environment, to achieve data processing among nodes for any applications, each node executes mutual authentication by using certificates which published from the Certificate Authority (for short, CA). However, if a failure or fault has occurred in the CA, any new certificates cannot be published from the CA. As a result, a new node cannot participate in the gird environment. In this paper, an off-the-shelf scheme for dependable grid systems using virtualization techniques is proposed and its implementation is verified. The proposed approach using the virtualization techniques is to restart an application, e.g., the CA, if it has failed. The system can tolerate a failure or fault if it has occurred in the CA. Since the proposed scheme is implemented at the application level easily, the cost of its implementation by the system builder hardly takes compared it with other methods. Simulation results show that the CA in the system can recover from its failure or fault.

Decision Support for the Selection of Electric Power Plants Generated from Renewable Sources

Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

A Hybrid Approach for Selection of Relevant Features for Microarray Datasets

Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.

A GA-Based Role Assignment Approach for Web-based Cooperative Learning Environments

Web-based cooperative learning focuses on (1) the interaction and the collaboration of community members, and (2) the sharing and the distribution of knowledge and expertise by network technology to enhance learning performance. Numerous research literatures related to web-based cooperative learning have demonstrated that cooperative scripts have a positive impact to specify, sequence, and assign cooperative learning activities. Besides, literatures have indicated that role-play in web-based cooperative learning environments enhances two or more students to work together toward the completion of a common goal. Since students generally do not know each other and they lack the face-to-face contact that is necessary for the negotiation of assigning group roles in web-based cooperative learning environments, this paper intends to further extend the application of genetic algorithm (GA) and propose a GA-based algorithm to tackle the problem of role assignment in web-based cooperative learning environments, which not only saves communication costs but also reduces conflict between group members in negotiating role assignments.

Resource Leveling in Construction Projects using Re- Modified Minimum Moment Approach

An attempt in this paper proposes a re-modification to the minimum moment approach of resource leveling which is a modified minimum moment approach to the traditional method by Harris. The method is based on critical path method. The new approach suggests the difference between the methods in the selection criteria of activity which needs to be shifted for leveling resource histogram. In traditional method, the improvement factor found first to select the activity for each possible day of shifting. In modified method maximum value of the product of Resources Rate and Free Float was found first and improvement factor is then calculated for that activity which needs to be shifted. In the proposed method the activity to be selected first for shifting is based on the largest value of resource rate. The process is repeated for all the remaining activities for possible shifting to get updated histogram. The proposed method significantly reduces the number of iterations and is easier for manual computations.

Levenberg-Marquardt Algorithm for Karachi Stock Exchange Share Rates Forecasting

Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.

Investigation of Water Vapour Transport Properties of Gypsum Using Genetic Algorithm

Water vapour transport properties of gypsum block are studied in dependence on relative humidity using inverse analysis based on genetic algorithm. The computational inverse analysis is performed for the relative humidity profiles measured along the longitudinal axis of a rod sample. Within the performed transient experiment, the studied sample is exposed to two environments with different relative humidity, whereas the temperature is kept constant. For the basic gypsum characterisation and for the assessment of input material parameters necessary for computational application of genetic algorithm, the basic material properties of gypsum are measured as well as its thermal and water vapour storage parameters. On the basis of application of genetic algorithm, the relative humidity dependent water vapour diffusion coefficient and water vapour diffusion resistance factor are calculated.

Using Partnerships to Achieve National Goals

Ireland developed a National Strategy 2030 that argued for the creation of a new form of higher education institution, a Technological University. The research reported here reviews the first stage of this partnership development. The study found that national policy can create system capacity and change, but that individual partners may have more to gain or lose in collaborating. When presented as a zero-sum activity, fear among partners is high. The level of knowledge and networking within the higher education system possessed by each partner contributed to decisions to participate or not in a joint proposal for collaboration. Greater success resulted when there were gains for all partners. This research concludes that policy mandates can provide motivation to collaborate, but that the partnership needs to be built more on shared values versus coercion by mandates.

Analysis of Dynamic Loads Induced by Spectator Movements in Stadium

In the stadium structure, the significant dynamic responses such as resonance or similar behavior can be occurred by spectator rhythmical activities. Thus, accurate analysis and precise investigation of stadium structure that is subjected to dynamic loads are required for practical design and serviceability check of stadium structures. Moreover, it is desirable to measure and analyze the dynamic loads of spectator activities because these dynamic loads can not be easily expressed in numerical formula. In this study, various dynamic loads induced by spectator movements are measured and analyzed. These dynamic loads induced by spectators movement of stadium structure can be classified into the impact load and the periodic load. These dynamic loads can be expressed as Fourier harmonic load. And, these dynamic loads could be applied for the accurate vibration analysis of a stadium structure.

Robust Control Synthesis for an Unmanned Underwater Vehicle

The control design for unmanned underwater vehicles (UUVs) is challenging due to the uncertainties in the complex dynamic modeling of the vehicle as well as its unstructured operational environment. To cope with these difficulties, a practical robust control is therefore desirable. The paper deals with the application of coefficient diagram method (CDM) for a robust control design of an autonomous underwater vehicle. The CDM is an algebraic approach in which the characteristic polynomial and the controller are synthesized simultaneously. Particularly, a coefficient diagram (comparable to Bode diagram) is used effectively to convey pertinent design information and as a measure of trade-off between stability, response speed and robustness. In the polynomial ring, Kharitonov polynomials are employed to analyze the robustness of the controller due to parametric uncertainties.

ARMrayan Multimedia Mobile CMS: a Simplified Approach towards Content-Oriented Mobile Application Designing

The ARMrayan Multimedia Mobile CMS (Content Management System) is the first mobile CMS that gives the opportunity to users for creating multimedia J2ME mobile applications with their desired content, design and logo; simply, without any need for writing even a line of code. The low-level programming and compatibility problems of the J2ME, along with UI designing difficulties, makes it hard for most people –even programmers- to broadcast their content to the widespread mobile phones used by nearly all people. This system provides user-friendly, PC-based tools for creating a tree index of pages and inserting multiple multimedia contents (e.g. sound, video and picture) in each page for creating a J2ME mobile application. The output is a standalone Java mobile application that has a user interface, shows texts and pictures and plays music and videos regardless of the type of devices used as long as the devices support the J2ME platform. Bitmap fonts have also been used thus Middle Eastern languages can be easily supported on all mobile phone devices. We omitted programming concepts for users in order to simplify multimedia content-oriented mobile applictaion designing for use in educational, cultural or marketing centers. Ordinary operators can now create a variety of multimedia mobile applications such as tutorials, catalogues, books, and guides in minutes rather than months. Simplicity and power has been the goal of this CMS. In this paper, we present the software engineered-designed concepts of the ARMrayan MCMS along with the implementation challenges faces and solutions adapted.

A New Scheduling Algorithm Based on Traffic Classification Using Imprecise Computation

Wireless channels are characterized by more serious bursty and location-dependent errors. Many packet scheduling algorithms have been proposed for wireless networks to guarantee fairness and delay bounds. However, most existing schemes do not consider the difference of traffic natures among packet flows. This will cause the delay-weight coupling problem. In particular, serious queuing delays may be incurred for real-time flows. In this paper, it is proposed a scheduling algorithm that takes traffic types of flows into consideration when scheduling packets and also it is provided scheduling flexibility by trading off video quality to meet the playback deadline.

Computer Generated Hologram for SemiFragile Watermarking with Encrypted Images

The protection of the contents of digital products is referred to as content authentication. In some applications, to be able to authenticate a digital product could be extremely essential. For example, if a digital product is used as a piece of evidence in the court, its integrity could mean life or death of the accused. Generally, the problem of content authentication can be solved using semifragile digital watermarking techniques. Recently many authors have proposed Computer Generated Hologram Watermarking (CGHWatermarking) techniques. Starting from these studies, in this paper a semi-fragile Computer Generated Hologram coding technique is proposed, which is able to detect malicious tampering while tolerating some incidental distortions. The proposed technique uses as watermark an encrypted image, and it is well suitable for digital image authentication.

Optimal Multilayer Perceptron Structure For Classification of HIV Sub-Type Viruses

The feature of HIV genome is in a wide range because of it is highly heterogeneous. Hence, the infection ability of the virus changes related with different chemokine receptors. From this point, R5 and X4 HIV viruses use CCR5 and CXCR5 coreceptors respectively while R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the coreceptors of HIV genome. The aim of this study is to develop the optimal Multilayer Perceptron (MLP) for high classification accuracy of HIV sub-type viruses. To accomplish this purpose, the unit number in hidden layer was incremented one by one, from one to a particular number. The statistical data of R5X4, R5 and X4 viruses was preprocessed by the signal processing methods. Accessible residues of these virus sequences were extracted and modeled by Auto-Regressive Model (AR) due to the dimension of residues is large and different from each other. Finally the pre-processed dataset was used to evolve MLP with various number of hidden units to determine R5X4 viruses. Furthermore, ROC analysis was used to figure out the optimal MLP structure.