Search results for: Nonlinear Systems

Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

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This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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Authors: Onder Yakut, Serdar Solak, Emine Dogru Bolat

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Measuring the Electrocardiogram (ECG) signal is an essential process for the diagnosis of the heart diseases. The ECG signal has the information of the degree of how much the heart performs its functions. In medical diagnosis and treatment systems, Decision Support Systems processing the ECG signal are being developed for the use of clinicians while medical examination. In this study, a modular wireless ECG (WECG) measuring and recording system using a single board computer and e-Health sensor platform is developed. In this designed modular system, after the ECG signal is taken from the body surface by the electrodes first, it is filtered and converted to digital form. Then, it is recorded to the health database using Wi-Fi communication technology. The real time access of the ECG data is provided through the internet utilizing the developed web interface.

Keywords: ECG, e-health sensor shield, raspberry Pi, wifi technology.

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Authors: HyunSu Seo, HoYoung Son, Sungjin Kim, WooYoung Jung

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In order to understand the seismic behavior of steel frame structure with infill FRP composite panel, simple models for simulation on the steel frame with the panel systems were developed in this study. To achieve the simple design method of the steel framed structure with the damping panel system, 2-D finite element analysis with the springs and dashpots models was conducted in ABAQUS. Under various applied spring stiffness and dashpot coefficient, the expected hysteretic energy responses of the steel frame with damping panel systems we investigated. Using the proposed simple design method which decides the stiffness and the damping, it is possible to decide the FRP and damping materials on a steel frame system.

Keywords: Interface damping layer, steel frame, seismic, FRP.

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events is important to improve safety and reliability of machine operations and reduce losses caused by failures. Improper set-ups or aligning of parts often leads to severe problems in many machines. The construction of prediction models for predicting faulty conditions is quite essential in making decisions on when to perform machine maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of machine measurement data. The calibration model is used to predict two faulty conditions from historical reference data. This approach utilizes genetic algorithms (GA) based variable selection, and we evaluate the predictive performance of several prediction methods using real data. The results shows that the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: Prediction, operation monitoring, on-line data, nonlinear statistical methods, empirical model.

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Authors: W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sathasivam

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This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, Modeling, Neural Networks, Preconditioned Conjugate Gradient.

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Authors: S. Montenegro, W. Hu

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The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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Authors: C. Kalamani, S. Sowmiya, S. Dheivambigai, G. Harihara Sudhan

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Radio Frequency Identification (RFID) is a blooming technology which uses radio frequency to track the objects. This technology transmits signals between tag and reader to fetch information from the tag with a unique serial identity. Generally, the drawbacks of RFID technology are high cost, high consumption of power and weak authentication systems between a reader and a tag. The proposed protocol utilizes less dynamic power using reversible truncated multipliers which are implemented in RFID tag-reader with mutual authentication protocol system to reduce both leakage and dynamic power consumption. The proposed system was simulated using Xilinx and Cadence tools.

Keywords: Mutual authentication, protocol, reversible gates, RFID.

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Authors: Adel A. Ghoneim

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In most existing buildings in hot climate, cooling loads lead to high primary energy consumption and consequently high CO2 emissions. These can be substantially decreased with integrated renewable energy systems. Kuwait is characterized by its dry hot long summer and short warm winter. Kuwait receives annual total radiation more than 5280 MJ/m2 with approximately 3347 h of sunshine. Solar energy systems consist of PV modules and parabolic trough collectors are considered to satisfy electricity consumption, domestic water heating, and cooling loads of an existing building. This paper presents the results of an extensive program of energy conservation and energy generation using integrated photovoltaic (PV) modules and Parabolic Trough Collectors (PTC). The program conducted on an existing institutional building intending to convert it into a Net-Zero Energy Building (NZEB) or near net Zero Energy Building (nNZEB). The program consists of two phases; the first phase is concerned with energy auditing and energy conservation measures at minimum cost and the second phase considers the installation of photovoltaic modules and parabolic trough collectors. The 2-storey building under consideration is the Applied Sciences Department at the College of Technological Studies, Kuwait. Single effect lithium bromide water absorption chillers are implemented to provide air conditioning load to the building. A numerical model is developed to evaluate the performance of parabolic trough collectors in Kuwait climate. Transient simulation program (TRNSYS) is adapted to simulate the performance of different solar system components. In addition, a numerical model is developed to assess the environmental impacts of building integrated renewable energy systems. Results indicate that efficient energy conservation can play an important role in converting the existing buildings into NZEBs as it saves a significant portion of annual energy consumption of the building. The first phase results in an energy conservation of about 28% of the building consumption. In the second phase, the integrated PV completely covers the lighting and equipment loads of the building. On the other hand, parabolic trough collectors of optimum area of 765 m2 can satisfy a significant portion of the cooling load, i.e about73% of the total building cooling load. The annual avoided CO2 emission is evaluated at the optimum conditions to assess the environmental impacts of renewable energy systems. The total annual avoided CO2 emission is about 680 metric ton/year which confirms the environmental impacts of these systems in Kuwait.

Keywords: Building integrated renewable systems, Net-Zero Energy Building, solar fraction, avoided CO2 emission.

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Authors: A. Sharahi, R. Tehrani, A. Mollajan

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The final step to complete the “Analytical Systems Engineering Process” is the “Allocated Architecture” in which all Functional Requirements (FRs) of an engineering system must be allocated into their corresponding Physical Components (PCs). At this step, any design for developing the system’s allocated architecture in which no clear pattern of assigning the exclusive “responsibility” of each PC for fulfilling the allocated FR(s) can be found is considered a poor design that may cause difficulties in determining the specific PC(s) which has (have) failed to satisfy a given FR successfully. The present study utilizes the Axiomatic Design method principles to mathematically address this problem and establishes an “Axiomatic Model” as a solution for reaching good alternatives for developing the allocated architecture. This study proposes a “loss Function”, as a quantitative criterion to monetarily compare non-ideal designs for developing the allocated architecture and choose the one which imposes relatively lower cost to the system’s stakeholders. For the case-study, we use the existing design of U. S. electricity marketing subsystem, based on data provided by the U.S. Energy Information Administration (EIA). The result for 2012 shows the symptoms of a poor design and ineffectiveness due to coupling among the FRs of this subsystem.

Keywords: Allocated Architecture, Analytical Systems Engineering Process, Functional Requirements (FRs), Physical Components (PCs), Responsibility of a Physical Component, System’s Stakeholders.

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Authors: S. Panda, N. P. Patidar, R. Singh

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Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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Authors: Tawiwat V., Phermsak S., Noppasit C.

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This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.

Keywords: Under actuator, Dynamic optimal control, Minimumjerk, Minimum energy.

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Authors: Kassem Saleh

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Decision Support System (DSS) are interactive software systems that are built to assist the management of an organization in the decision making process when faced with nonroutine problems in a specific application domain. Non-functional requirements (NFRs) for a DSS deal with the desirable qualities and restrictions that the DSS functionalities must satisfy. Unlike the functional requirements, which are tangible functionalities provided by the DSS, NFRs are often hidden and transparent to DSS users but affect the quality of the provided functionalities. NFRs are often overlooked or added later to the system in an ad hoc manner, leading to a poor overall quality of the system. In this paper, we discuss the development of NFRs as part of the requirements engineering phase of the system development life cycle of DSSs. To help eliciting NFRs, we provide a comprehensive taxonomy of NFRs for DSSs.

Keywords: Decision support system, Development, Elicitation, Non-functional requirements, Taxonomy

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Authors: J. Chakwizira, P. Bikam, T. A. Adeboyejo

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This paper seeks to illustrate the impact of rapid urbanization (in terms of both increase in people and vehicles) in the Gauteng region (which includes Johannesburg, Pretoria and Ekurhuleni). The impact that existing transport systems and options place on the capacity of residents from low income areas to travel and conduct various socio-economic activities is discussed. The findings are drawn from a 2013 analysis of a random transport household survey of 1550 households carried out in Gauteng province. 91.4% of the study respondents had access to public transport, while 8.6% had no access to public transport. Of the 91.4% who used public transport, the main reason used to explain this state of affairs was that it was affordable (54.3%), convenient (15.9%), Accessible (11.9%), lack of alternatives (6.4%) and reliable at 4.1%. Recommendations advanced revolve around the need to reverse land use and transportation effects of apartheid planning, growing and developing a sustainable critical mass of public transport interventions supported by appropriate transport systems that are environmentally sustainable through proper governance. 38.5% of the respondents indicated that developing compact, smart and integrated urban land spaces was key to reducing travel challenges in the study area. 23.4% indicated that the introduction and upgrading of BRT buses to cover all areas in the study area was a step in the right direction because it has great potential in shifting travel patterns to favor public modes of transport. 15.1% indicated that all open spaces should be developed so that fragmentation of land uses can be addressed. This would help to fight disconnected and fragmented space and trip making challenges in Gauteng. 13.4% indicated that improving the metro rail services was critical since this is a mass mover of commuters. 9.6% of the respondents highlighted that the bus subsidy policy has to be retained in the short to medium term since the spatial mismatches and challenges created by apartheid are yet to be fully reversed.

Keywords: Urbanisation, population, public, transport systems, Gauteng.

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Authors: S. Elnobi, Iman El-Zahaby, Amr M. Mahros

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In mobile communication systems, performance and capacity are affected by multi-path fading, delay spread and Co-Channel Interference (CCI). For this reason Orthogonal Frequency Division Multiplexing (OFDM) and adaptive antenna array are used is required. The goal of the OFDM is to improve the system performance against Inter-Symbol Interference (ISI). An array of adaptive antennas has been employed to suppress CCI by spatial technique. To suppress CCI in OFDM systems two main schemes the pre-FFT and the post-FFT have been proposed. In this paper, through a system level simulation, the behavior of the pre-FFT and post-FFT beamformers for OFDM system has been investigated based on two algorithms namely, Least Mean Squares (LMS) and Recursive Least Squares (RLS). The performance of the system is also discussed in multipath fading channel system specified by 3GPP Long Term Evolution (LTE).

Keywords: OFDM, Beamforming, Adaptive Antennas Array.

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Authors: R. Haoui

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The purpose of this work is to simulate the flow at the exit of Vulcan 1 engine of European launcher Ariane 5. The geometry of the propellant nozzle is already determined using the characteristics method. The pressure in the outlet section of the nozzle is less than atmospheric pressure on the ground, causing the existence of oblique and normal shock waves at the exit. During the rise of the launcher, the atmospheric pressure decreases and the shock wave disappears. The code allows the capture of shock wave at exit of nozzle. The numerical technique uses the Flux Vector Splitting method of Van Leer to ensure convergence and avoid the calculation instabilities. The Courant, Friedrichs and Lewy coefficient (CFL) and mesh size level are selected to ensure the numerical convergence. The nonlinear partial derivative equations system which governs this flow is solved by an explicit unsteady numerical scheme by the finite volume method. The accuracy of the solution depends on the size of the mesh and also the step of time used in the discretized equations. We have chosen in this study the mesh that gives us a stationary solution with good accuracy.

Keywords: Launchers, supersonic flow, finite volume, nozzles, shock wave.

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Authors: Nadjah Chergui, Narhimene Boustia

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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: Context, exception, default, IDS, Non-monotonic Description Logic JClassicδє, vulnerability.

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Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, S. K. Nayak, C. Ardil

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Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.

Keywords: Filtering, Decision Based Algorithm, noise, imagerestoration.

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Authors: R. N. Patel, S. K. Sinha, R. Prasad

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In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.

Keywords: Artificial intelligence, Automatic generation control, Fuzzy control, Genetic Algorithm, Particle swarm optimization, Power systems.

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Authors: T. Kosáros, D. Gál, F. Pekár, Gy. Lakatos

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Periphyton development and composition were studied in three different treatments: (i) two fishpond units of wetland-type wastewater treatment pond systems, (ii) two fishponds in combined intensive-extensive fish farming systems and (iii) three traditional polyculture fishponds. Results showed that amounts of periphyton developed in traditional polyculture fishponds (iii) were different compared to the other treatments (i and ii), where the main function of ponds was stated wastewater treatment. Negative correlation was also observable between water quality parameters and periphyton production. The lower trophity, halobity and saprobity level of ponds indicated higher amount of periphyton. The dry matter content of periphyton was significantly higher in the samples, which were developed in traditional polyculture fishponds (2.84±3.02 g m-2 day-1, whereby the ash content in dry matter 74%), than samples taken from (i) (1.60±2.32 g m-2 day-1, 61%) and (ii) fishponds (0.65±0.45 g m-2 day-1, 81%).

Keywords: Artificial substrate, fishpond, periphyton, waterquality

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Authors: Paul B. Stone, Subhashini Ganapathy, Mary E. Fendley, Layla Akilan

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As notifications become more common through mobile devices, it is important to understand the impact of wearable devices for improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer simulated petrochemical system. The key research question was to determine how using information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.

Keywords: computer applications, haptic feedback, petrochemical systems, situational awareness, wearable technology

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Authors: M. Salehi, A. A. Motie Birjandi, F. Namdari

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Weak damping of low frequency oscillations is a frequent phenomenon in electrical power systems. These frequencies can be damped by power system stabilizers. Unified power flow controller (UPFC), as one of the most important FACTS devices, can be applied to increase the damping of power system oscillations and the more effect of this controller on increasing the damping of oscillations depends on its proper placement in power systems. In this paper, a technique based on controllability is proposed to select proper location of UPFC and the best input control signal in order to enhance damping of power oscillations. The effectiveness of the proposed technique is demonstrated in IEEE 9 bus power system.

Keywords: Unified power flow controller (UPFC), controllability, small signal analysis, eigenvalues.

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Authors: Ntokozo C. Mthembu

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The notion of sustainable chemistry has become significant in the discourse for a global post-colonial era, including South Africa, especially when it comes to access to the general health system and related policies in relation to disease or ease of human life. In view of the stubborn vestiges of coloniality in the daily lives of indigenous African people in general, the fundamentals of present Western medical and traditional medicine systems and related policies in the democratic era were examined in this study. The situation of traditional healers in relation to current policy was also reviewed. The advent of democracy in South Africa brought about a variety of development opportunities and limitations, particularly with respect to indigenous African knowledge systems such as traditional medicine. There were high hopes that the limitations of previous narrow cultural perspectives would be rectified in the democratic era through development interventions, but some sections of society, such as traditional healers, remain marginalised. The Afrocentric perspective was explored in dissecting government interventions related to traditional medicine. This article highlights that multiple medical systems should be adopted and that health policies should be aligned in order to guarantee mutual respect and to address the remnants of colonialism in South Africa, Africa and the broader global community.

Keywords: Traditional healing system, healers, pluralist healthcare system, post-colonial era.

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Authors: K. G. Firouzjah, A. Sheikholeslami

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The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.

Keywords: Active filter, predictive current control, low pass filter, harmonic omitting, o–d–q reference frame.

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Authors: M. Kowalski, M. Kastek, M. Szustakowski

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Multispectral screening systems are becoming more popular because of their very interesting properties and applications. One of the most significant applications of multispectral screening systems is prevention of terrorist attacks. There are many kinds of threats and many methods of detection. Visual detection of objects hidden under clothing of a person is one of the most challenging problems of threats detection. There are various solutions of the problem; however, the most effective utilize multispectral surveillance imagers. The development of imaging devices and exploration of new spectral bands is a chance to introduce new equipment for assuring public safety. We investigate the possibility of long lasting detection of potentially dangerous objects covered with various types of clothing. In the article we present the results of comparative studies of passive imaging in three spectrums – visible, infrared and terahertz.

Keywords: Infrared, image processing, object detection, screening camera, terahertz.

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Authors: Irina Pyrlina

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Author presents the results of a study conducted to identify criteria of efficient information system (IS) with serviceoriented architecture (SOA) realization and proposes a ranking method to evaluate SOA information systems using a set of architecture quality criteria before the systems are implemented. The method is used to compare 7 SOA projects and ranking result for SOA efficiency of the projects is provided. The choice of SOA realization project depends on following criteria categories: IS internal work and organization, SOA policies, guidelines and change management, processes and business services readiness, risk management and mitigation. The last criteria category was analyzed on the basis of projects statistics.

Keywords: multiple criteria threshold algorithm, serviceoriented architecture, SOA operational risks, efficiency criteria for IS architecture, projects ranking.

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Authors: Kyoung Hoon Kim, Giman Kim

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The cycles of the steam-injection gas-turbine systems are studied. The analyses of the parametric effects and the optimal operating conditions for the steam-injection gas-turbine (STIG) system and the regenerative steam-injection gas-turbine (RSTIG) system are investigated to ensure the maximum performance. Using the analytic model, the performance parameters of the system such as thermal efficiency, fuel consumption and specific power, and also the optimal operating conditions are evaluated in terms of pressure ratio, steam injection ratio, ambient temperature and turbine inlet temperature (TIT). It is shown that the computational results are presented to have a notable enhancement of thermal efficiency and specific power.

Keywords: gas turbine, RSTIG, steam injection, STIG, thermal efficiency.

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Authors: Ahed Abugabah, Louis Sanzogni

Abstract:

ERP systems are the largest software applications adopted by universities, along with quite significant investments in their implementation. However, unlike other applications little research has been conducted regarding these systems in a university environment. This paper aims at providing a critical review of previous research in ERP system in higher education with a special focus on higher education in Australia. The research not only forms the basis of an evaluation of previous research and research needs, it also makes inroads in identifying the payoff of ERPs in the sector from different perspectives with particular reference to the user. The paper is divided into two parts, the first part focuses on ERP literature in higher education at large, while the second focuses on ERP literature in higher education in Australia.

Keywords: Enterprise resource planning system, higher education, implementation, user level.

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Authors: Kyoung-jae Kim

Abstract:

Recommender systems are usually regarded as an important marketing tool in the e-commerce. They use important information about users to facilitate accurate recommendation. The information includes user context such as location, time and interest for personalization of mobile users. We can easily collect information about location and time because mobile devices communicate with the base station of the service provider. However, information about user interest can-t be easily collected because user interest can not be captured automatically without user-s approval process. User interest usually represented as a need. In this study, we classify needs into two types according to prior research. This study investigates the usefulness of data mining techniques for classifying user need type for recommendation systems. We employ several data mining techniques including artificial neural networks, decision trees, case-based reasoning, and multivariate discriminant analysis. Experimental results show that CHAID algorithm outperforms other models for classifying user need type. This study performs McNemar test to examine the statistical significance of the differences of classification results. The results of McNemar test also show that CHAID performs better than the other models with statistical significance.

Keywords: Customer need type, Data mining techniques, Recommender system, Personalization, Mobile user.

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