Correlation-based tuning of decoupling multivariable controllers

The iterative method labelled correlation-based tuning (CbT) is considered in this paper for tuning linear time-invariant multivariable controllers. The approach allows one to tune some elements of the controller transfer function matrix to satisfy the desired closed-loop performance, while the other elements are tuned to mutually decouple the closed-loop outputs. Decoupling is achieved by decorrelating a given reference with the non-corresponding outputs. The controller parameters are calculated either by solving a correlation equation (decorrelation procedure) or by minimizing a cross-correlation function (correlation reduction). In addition, the preferred way of exciting a 2×2 system for CbT is investigated via the accuracy of the estimated controller parameters. It is shown that simultaneous excitation of both reference signals does not improve the accuracy of the estimated controller parameters compared to the case of sequential excitation. In fact, one must choose between low experimental cost (simultaneous excitation) and better accuracy of the estimated parameters (sequential excitation). The theoretical results are illustrated via three simulation studies.     

Classroom furniture and anthropometric characteristics of Iranian high school students: Proposed dimensions based on anthropometric data

The study evaluated the potential mismatch between classroom furniture dimensions and anthropometric characteristics of 978 Iranian high school students (498 girls, 480 boys), aged 15-18 years. Nine anthropometric measurements (stature, sitting height, sitting shoulder height, popliteal height, hip breadth, elbow-seat height, buttock-popliteal length, buttock-knee length and thigh clearance) and five dimensions from the existing classroom furniture were measured and then compared together (using match criterion equations) to identify any potential mismatch between them. The results indicated a considerable mismatch between body dimensions of the students and the existing classroom furniture, with seat height (60.9%), seat width (54.7%) and desktop height (51.7%) being the furniture dimensions with a higher level of mismatch. The levels of mismatch varied between the high-school grade levels and between genders, indicating their special requirements and possible problems. The proposed dimensions of the classroom furniture more appropriate for the students were given. This additional information on students' anthropometry can be used by local furniture industries as a starting point for designing more appropriate furniture for school children, or used by schools to aid in furniture selection.     

Assessing mobile phone communication utility preferences in a social support network

While it is generally accepted that the mobile cell phone has become ubiquitous within society for communicating, the actual use of the utilities on a phone have not been reported. Understanding how communication patterns are changing in society as a result of the mobile cell phone will enable the development and/or modification of existing cell phone utilities, the concept of privacy, and a mobile literacy research domain. To explore mobile cell phone utility use, 99 people completed a mobile phone usage questionnaire. Key results from the questionnaire are physical location when using a mobile cell phone, the length of communication episodes, the usage of phone utilities and existing privacy concerns related to mobile cell phones.     

Feature Extraction Method Based on Social Network Analysis

Due to rapid development of Internet technology and electronic business, fraudulent activities have increased. One of the ways to cope with damages of them is fraud detection. In this field, there is a need for methods accurate and fast. Therefore, a novel and efficient feature extraction method based on social network analysis called FEMBSNA is proposed for fraud detection in banking accounts. In this method, in order to increase accuracy and control runtime in the first step, features based on network level are considered using social network analysis and extracted feature is combined with other features based on user level in the next phase. To evaluate our feature extraction method, we use PCK-means method as a basic method to learn. The results show using the proposed feature extraction as a pre-processing step in fraud detection improves the accuracy remarkably while it controls runtime in comparison with other methods.     

A segmentation approach for file broadcast scheduling

We study the broadcast scheduling problem in which clients send their requests to a server in order to receive some files available on the server. The server may be scheduled in a way that several requests are satisfied in one broadcast. When files are transmitted over computer networks, broadcasting the files by fragmenting them provides flexibility in broadcast scheduling that allows the optimization of per user response time. The broadcast scheduling algorithm, then, is in charge of determining the number of segments of each file and their order of transmission in each round of transmission. In this paper, we obtain a closed form approximation formula which approximates the optimal number of segments for each file, aiming at minimizing the total response time of requests. The obtained formula is a function of different parameters including those of underlying network as well as those of requests arrived at the server. Based on the obtained approximation formula we propose an algorithm for file broadcast scheduling which leads to total response time which closely conforms to the optimum one. We use extensive simulation and numerical study in order to evaluate the proposed algorithm which reveals high accuracy of obtained analytical approximation. We also investigate the impact of various headers that different network protocols add to each file segment. Our segmentation approach is examined for scenarios with different file sizes at the range of 100 KB to 1 GB. Our results show that for this range of file sizes the segmentation approach shows on average 13% tolerance from that of optimum in terms of total response time and the accuracy of the proposed approach is growing by increasing file size. Besides, using proposed segmentation in this work leads to a high Goodput of the scheduling algorithm.     

Predicting performance in ASEAN banks: an integrated fuzzy MCDM–neural network approach

This paper presents a performance assessment of 88 Association of Southeast Asian Nations banks from 2010 to 2013, using an integrated three‐stage approach on financial criteria that emulates the CAMELS rating system. More precisely, fuzzy analytic hierarchy process is used first to assess the relative weights of a number of criteria related to capital adequacy (C), asset quality (A), management quality (M), earnings (E), liquidity (L), and sensitivity to market risk (S) based on the opinion of 88 Association of Southeast Asian Nations experts. Then, these weights are used as technique for order of preference by similarity to ideal solution inputs to assess their relative efficiency. Lastly, neural networks are combined with technique for order of preference by similarity to ideal solution results to produce a model for banking performance with effective predictive ability. The results reveal that contextual variables have a prominent impact on efficiency. Specifically, parsimony in equity leveraging derived from Islamic finance principles may be the underlying cause in explaining higher efficiency levels.     

A comprehensive review of renewable energy resources for electricity generation in Australia

Recently, renewable energy resources and their impacts have sparked a heated debate to resolve the Australian energy crisis. There are many projects launched throughout the country to improve network security and reliability. This paper aims to review the current status of different renewable energy resources along with their impacts on society and the environment. Besides, it provides for the first time the statistics of the documents published in the field of renewable energy in Australia. The statistics include information such as the rate of papers published, possible journals for finding relative paper, types of documents published, top authors, and the most prevalent keywords in the field of renewable energy in Australia. It will focus on solar, wind, biomass, geothermal and hydropower technologies and will investigate the social and environmental impacts of these technologies.     

A numerical study on heat transfer enhancement and design of a heat exchanger with porous media in continuous hydrothermal flow synthesis system

The aim of this study is to use a new configuration of porous media in a heat exchanger in continuous hydrothermal flow synthesis (CHFS) system to enhance the heat transfer and minimize the required length of the heat exchanger.For this purpose,numerous numerical simulations are performed to investigate performance of the system with porons media.First,the numerical simulation for the heat exchanger in CHFS system is validated by experimental data.Then,porous media is added to the system and six different thicknesses for the porous media are examined to obtain the optimum thickness,based on the minimum required length of the heat exchanger.Finally,by changing the flow rate and inlet temperature of the product as well as the cooling water flow rate,the minimum required length of the heat exchanger with porous media for various inlet conditions is assessed.The investigations indicate that using porous media with the proper thickness in the heat exchanger increases the cooling rate of the product by almost 40％and reduces the required length of the heat exchanger by approximately 35％.The results also illustrate that the most proper thickness of the porous media is approximately equal to 90％ of the product tube's thickness.Results of this study lead to design a porous heat exchanger in CHFS system for various inlet conditions.     

Adaptive synchronization of master–slave systems with mixed neutral and discrete time‐delays and nonlinear perturbations

This paper investigates the delay‐dependent adaptive synchronization problem of the master and slave structure of linear systems with both constant neutral and time‐varying discrete time‐delays and nonlinear perturbations based on the Barbalat lemma and matching conditions. An adaption law which includes the master‐slave parameters is obtained by using the Lyapunov functional method and inequality techniques to synchronize the master‐slave systems without the knowledge of upper bounds of perturbation terms. Particularly, it is shown that the synchronization speed can be controlled by adjusting the update gain of the synchronization signal. A numerical example has been given to show the effectiveness of the method. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society