Search results for: performance domain.

Authors: Vilas P. Mahatme, K. K. Bhoyar

Abstract:

Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.

Keywords: Data mining, e-examination, e-learning, moodle.

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Authors: Abd Latif Abdul Rahman, Adnan Jamaludin, Zamalia Mahmud

Abstract:

Unified Theory of Acceptance and Use of Technology (UTAUT) model has demonstrated the influencing factors for generic information systems use such as tablet personal computer (TPC) and mobile communication. However, in the context of digital library system, there has been very little effort to determine factors affecting the intention to use digital library based on the UTAUT model. This paper investigates factors that are expected to influence the intention of postgraduate students to use digital library based on modified UTAUT model. The modified model comprises of constructs represented by several latent variables, namely performance expectancy (PE), effort expectancy (EE), information quality (IQ) and service quality (SQ) and moderated by age, gender and experience in using digital library. Results show that performance expectancy, effort expectancy and information quality are positively related to the intention to use digital library, while service quality is negatively related to the intention to use digital library. Age and gender have shown no evidence of any significant interactions, while experience in using digital library significantly interacts with effort expectancy and intention to use digital library. This has provided the evidence of a moderating effect of experience in the intention to use digital library. It is expected that this research will shed new lights into research of acceptance and intention to use the library in a digital environment.

Keywords: Intention to use digital library, UTAUT model, performance expectancy, effort expectancy, information quality, service quality.

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Authors: Beata Ślusarczyk, Sebastian Kot

Abstract:

In subjective terms, Polish SME sector occupies a prominent position in the national economic development, in which planning of the management strategies should be primarily based on identifying and meeting the innovation needs. As a research sample, there is chosen a printing sector of industry. SMEs share in printing sector in Poland is estimated at the level of 81% of all enterprises. In recent years, the printing industry achieved one of the highest levels of EU support in Poland. There is a relatively high increase in the development of technological innovations in equipment and the associated significant increase in production capacity. It can be also noticed that on average, every third enterprise belonging to the printing industry has implemented innovations, but not all of them effected in better economic results. Therefore, the aim of this article is to evaluate the impact of the implementation of innovation projects financed from the EU funds for performance of SMEs in the printing industry. As the results of research of EU funds co-financing effects on the development of innovation in the printing industry, it was specified that examined SMEs prefer to implement product innovation to receive a grant to the project at a level between 40% to 60%, the remaining part of the investment is usually covered with equity. The most common type of innovation had indicated a single implementation, related only to the change in process, technology, or organization. The relationship between variables of the EU funds and management of innovative activities was verified. It has been observed that the identified variables arising from the support in a form of the EU funds had a positive effect on the level of earned revenue, the increase in margin and in increase in employment as well. It was confirmed that the implemented innovations supported by the European funds have a positive impact on the performance of the printing companies. Although there is a risk that due to the decreasing demand for printing services such a high level of funding the companies in this sector will significantly increase competition in the long term, that may also contribute to the economic problems of the enterprises belonging to the analyzed branch.

Keywords: Innovations, SMEs, performance, results.

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Authors: Eiad Yafi, Ahmed Sultan Al-Hegami, M. A. Alam, Ranjit Biswas

Abstract:

Association rules are an important problem in data mining. Massively increasing volume of data in real life databases has motivated researchers to design novel and incremental algorithms for association rules mining. In this paper, we propose an incremental association rules mining algorithm that integrates shocking interestingness criterion during the process of building the model. A new interesting measure called shocking measure is introduced. One of the main features of the proposed approach is to capture the user background knowledge, which is monotonically augmented. The incremental model that reflects the changing data and the user beliefs is attractive in order to make the over all KDD process more effective and efficient. We implemented the proposed approach and experiment it with some public datasets and found the results quite promising.

Keywords: Knowledge discovery in databases (KDD), Data mining, Incremental Association rules, Domain knowledge, Interestingness, Shocking rules (SHR).

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Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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Authors: V. Geetha, K. S. Aprameya

Abstract:

Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: Subrato Saha, Yun-Hyun Cho

Abstract:

This paper presents the design process of a high performance 3-phase 3.7 kW 2-pole line start permanent magnet synchronous motor for pumping system. A method was proposed to study the starting torque characteristics considering line start with high inertia load. A d-q model including cage was built to study the synchronization capability. Time-stepping finite element method analysis was utilized to accurately predict the dynamic and transient performance, efficiency, starting current, speed curve and etc. Considering the load torque of pumps during starting stage, the rotor bar was designed with minimum demagnetization of permanent magnet caused by huge starting current.

Keywords: LSPM, starting analysis, demagnetization, FEA, pumping system.

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Authors: N. C. Shahi, Anupama Singh, A. E. Kate

Abstract:

There was a scenario present day that drying of fresh fruits and vegetables by indirect solar drying by using mechanical device; hence, an effort was made to develop a small scale solar tunnel dryer (STD). Drying of spinach is carried out to analyze the performance of the dryer and to study its drying characteristics. To evaluate the performance of dryer the independent variables were selected as air flow rate, loading density and shade net while collector efficiency, drying efficiency, overall efficiency and specific energy consumption were selected as responses during performing the experiments. The spinach was dried from initial moisture content 88.21-94.04% (w.b.) to final moisture content 3.50-5.13% (w.b.). The drying time considerably reduced as compared to open sun drying of spinach as sun drying took 15 h for drying. The average collector efficiency, drying efficiency and overall efficiency were in the range 28.73-61.15%, 11.63% to 22.13%, and 7.61-14.66%, respectively.

Keywords: Solar dryer, collector efficiency, drying efficiency, spinach.

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Authors: Dong-Hyun Kim, Yoo-Han Kim

Abstract:

In this study, aeroelastic response and performance analyses have been conducted for a 5MW-Class composite wind turbine blade model. Advanced coupled numerical method based on computational fluid dynamics (CFD) and computational flexible multi-body dynamics (CFMBD) has been developed in order to investigate aeroelastic responses and performance characteristics of the rotating composite blade. Reynolds-Averaged Navier-Stokes (RANS) equations with k-ω SST turbulence model were solved for unsteady flow problems on the rotating turbine blade model. Also, structural analyses considering rotating effect have been conducted using the general nonlinear finite element method. A fully implicit time marching scheme based on the Newmark direct integration method is applied to solve the coupled aeroelastic governing equations of the 3D turbine blade for fluid-structure interaction (FSI) problems. Detailed dynamic responses and instantaneous velocity contour on the blade surfaces which considering flow-separation effects were presented to show the multi-physical phenomenon of the huge rotating wind- turbine blade model.

Keywords: Computational Fluid Dynamics (CFD), Computational Multi-Body Dynamics (CMBD), Reynolds-averageNavier-Stokes (RANS), Fluid Structure Interaction (FSI), FiniteElement Method (FEM)

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Authors: Ahmed Mohammed K. Alsalama

Abstract:

Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose1 a hybrid framework recommendation system to be applied on two dimensional spaces (User × Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: Data Mining, Association Rules, Recommendation Systems, Hybrid Systems.

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Authors: A.R. Ismail, M. R. A. Rani, Z. K. M. Makhbul, M. J. M. Nor, M. N. A. Rahman

Abstract:

The environmental factors such as temperature and relative humidity are very contribute to the effect of comfort, health, performance and worker productivity. To ensure an ergonomics work environment, it is possible to require a specific attention especially in industries. The aim of this study is to show the effect of temperature and relative humidity on worker productivity in automotive industry by taking a workstation in an automotive plant as the location to conduct the study. From the analysis of the data, there were relationship between temperature and relative humidity on worker productivity. Mathematical equation to represent the relationship between temperatures and relative humidity on the production rate is modelled. From the equation model, the production rate for the workstation can be predicted base on the value of temperature and relative humidity.

Keywords: WBGT, Relative Humidity, Comfort, Productivity.

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Authors: Van Nhan Nguyen, Harald Holone

Abstract:

Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: Automatic Speech Recognition, ASR, Air Traffic Control, ATC.

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Authors: K. Derradji Belloum, A. Moussi

Abstract:

Most high-performance ac drives utilize a current controller. The controller switches a voltage source inverter (VSI) such that the motor current follows a set of reference current waveforms. Fixed-band hysteresis (FBH) current control has been widely used for the PWM inverter. We want to apply the same controller for the PWM AC chopper. The aims of the controller is to optimize the harmonic content at both input and output sides, while maintaining acceptable losses in the ac chopper and to control in wide range the fundamental output voltage. Fixed band controller has been simulated and analyzed for a single-phase AC chopper and are easily extended to three-phase systems. Simulation confirmed the advantages and the excellent performance of the modulation method applied for the AC chopper.

Keywords: AC chopper, Current controller, Distortion factor, Hysteresis, Input Power Factor, PWM.

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Authors: Khalid Alnafjan, Tazar Hussain, Hanif Ullah, Zia ul haq Paracha

Abstract:

Software and applications are subjected to serious and damaging security threats, these threats are increasing as a result of increased number of potential vulnerabilities. Security testing is an indispensable process to validate software security requirements and to identify security related vulnerabilities. In this paper we analyze and compare different available vulnerabilities testing techniques based on a pre defined criteria using analytical hierarchy process (AHP). We have selected five testing techniques which includes Source code analysis, Fault code injection, Robustness, Stress and Penetration testing techniques. These testing techniques have been evaluated against five criteria which include cost, thoroughness, Ease of use, effectiveness and efficiency. The outcome of the study is helpful for researchers, testers and developers to understand effectiveness of each technique in its respective domain. Also the study helps to compare the inner working of testing techniques against a selected criterion to achieve optimum testing results.

Keywords: Software Security, Security Testing, Testing techniques, vulnerability, AHP.

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Authors: Hadi Sadoghi Yazdi, Mehri Sadoghi Yazdi, Mohammad Reza Mohammadi

Abstract:

This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.

Keywords: Forgetting factor, RLS, Inverse correlation matrix, human motion analysis.

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Authors: Javed Parvez, Mushtaq Ahmad Peer

Abstract:

Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Keywords: Bandwidth Reservation, Congestion, DynamicNetwork Topology, End-to-End Delay, Flexible QoS Model forMANET(FQMM), Hidden Terminal, Mobile AdhocNetwork(MANET), Packet Jitter, Queuing, Quality-of-Service(QoS), Relative Bandwidth Service Differentiation(RBSD), Resource ReSerVation Protocol (RSVP).

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Authors: S. Sfarni, E. Bellenger, J. Fortin, M. Guessasma

Abstract:

The use of the mechanical simulation (in particular the finite element analysis) requires the management of assumptions in order to analyse a real complex system. In finite element analysis (FEA), two modeling steps require assumptions to be able to carry out the computations and to obtain some results: the building of the physical model and the building of the simulation model. The simplification assumptions made on the analysed system in these two steps can generate two kinds of errors: the physical modeling errors (mathematical model, domain simplifications, materials properties, boundary conditions and loads) and the mesh discretization errors. This paper proposes a mesh adaptive method based on the use of an h-adaptive scheme in combination with an error estimator in order to choose the mesh of the simulation model. This method allows us to choose the mesh of the simulation model in order to control the cost and the quality of the finite element analysis.

Keywords: Finite element, discretization errors, adaptivity.

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Authors: M. Wendeker, K. Siadkowska, P. Magryta, Z. Czyz, K. Skiba

Abstract:

In the paper environmental impact analysis the optimal Diesel engine for a light helicopter was performed. The paper consist an answer to the question of what the optimal Diesel engine for a light helicopter is, taking into consideration its expected performance and design capacity. The use of turbocharged engine with self-ignition and an electronic control system can substantially reduce the negative impact on the environment by decreasing toxic substance emission, fuel consumption and therefore carbon dioxide emission. In order to establish the environmental benefits of the diesel engine technologies, mathematical models were created, providing additional insight on the environmental impact and performance of a classic turboshaft and an advanced diesel engine light helicopter, incorporating technology developments.

Keywords: Diesel engine, helicopter, simulation, environmental impact.

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Authors: Andrey V. Timofeev, Dmitry Egorov

Abstract:

This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: Bimodal processing, C-OTDR monitoring system, LPboost, SVM.

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Authors: Omid A. Zargar

Abstract:

Material damages dynamic analysis is difficult to deal with different material geometry and mechanism. In addition, it is difficult to measure the dynamic behavior of cracks, debond and delamination inside the material. Different simulation methods are developed in recent years for different physical features of mechanical systems like vibration and acoustic. Nonlinear fractures are analyzed and identified for different locations in this paper. The main idea of this work is to perform dynamic analysis on different types of materials (from normal homogeneous material to complex composite laminates). Technical factors like cracks, voids, interfaces and the damages’ locations are evaluated. In this project the modal analysis is performed on different types of materials. The results could be helpful in finding modal frequencies, natural frequencies, Time domain and fast Fourier transform (FFT) in industrial applications.

Keywords: Finite element method, dynamic analysis, vibration and acoustic, composite, crack, delamination.

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

Abstract:

A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: Backstepping control, iterative control, rehabilitation, ETS-MARSE.

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

Abstract:

The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: Clustering analysis, community of practice, data mining, higher education, new faculty challenges, social networks, social influence, professional development.

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

Abstract:

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: Pradeep Singh, Sukhwinder Singh, Gurjinder Kaur

Abstract:

In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.

Keywords: Classification, clustering, content-based image retrieval (CBIR), relevance feedback (RF), statistical similarity matching, support vector machine (SVM).

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Authors: N. Jinesh, K. Shankar

Abstract:

This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.

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Authors: Ali Emad

Abstract:

Enhancement of the performance of a reverse osmosis (RO) unit through periodic control is studied. The periodic control manipulates the feed pressure and flow rate of the RO unit. To ensure the periodic behavior of the inputs, the manipulated variables (MV) are transformed into the form of sinusoidal functions. In this case, the amplitude and period of the sinusoidal functions become the surrogate MV and are thus regulated via nonlinear model predictive control algorithm. The simulation results indicated that the control system can generate cyclic inputs necessary to enhance the closedloop performance in the sense of increasing the permeate production and lowering the salt concentration. The proposed control system can attain its objective with arbitrary set point for the controlled outputs. Successful results were also obtained in the presence of modeling errors.

Keywords: Reverse osmosis, water desalination, periodic control, model predictive control.

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Authors: Do-Jin Jang, Sung-Ah Kim

Abstract:

A kinetic façade responds to user requirements and environmental conditions.  In designing a kinetic façade, kinetic patterns play a key role in determining its performance. This paper proposes a biomimetic method for the multi-objective optimization for kinetic façade design. The autonomous decentralized control system is combined with flocking algorithm. The flocking agents are autonomously reacting to sensor values and bring about kinetic patterns changing over time. A series of experiments were conducted to verify the potential and limitations of the flocking based decentralized control. As a result, it could show the highest performance balancing multiple objectives such as solar radiation and openness among the comparison group.

Keywords: Biomimicry, flocking algorithm, autonomous decentralized control, multi-objective optimization.

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Authors: Nopparat Pochai

Abstract:

Smoke discharging is a main reason of air pollution problem from industrial plants. The obstacle of a building has an affect with the air pollutant discharge. In this research, a mathematical model of the smoke dispersion from two sources and one source with a structural obstacle is considered. The governing equation of the model is an isothermal mass transfer model in a viscous fluid. The finite element method is used to approximate the solutions of the model. The triangular linear elements have been used for discretising the domain, and time integration has been carried out by semi-implicit finite difference method. The simulations of smoke dispersion in cases of one chimney and two chimneys are presented. The maximum calculated smoke concentration of both cases are compared. It is then used to make the decision for smoke discharging and air pollutant control problems on industrial area.

Keywords: Air pollution, Smoke dispersion, Finite element method, Stream function, Vorticity equation, Convection-diffusion equation, Semi-implicit method

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Authors: Hamid A. Jalab, Rabha W. Ibrahim

Abstract:

This paper introduces an image denoising algorithm based on generalized Srivastava-Owa fractional differential operator for removing Gaussian noise in digital images. The structures of nxn fractional masks are constructed by this algorithm. Experiments show that, the capability of the denoising algorithm by fractional differential-based approach appears efficient to smooth the Gaussian noisy images for different noisy levels. The denoising performance is measured by using peak signal to noise ratio (PSNR) for the denoising images. The results showed an improved performance (higher PSNR values) when compared with standard Gaussian smoothing filter.

Keywords: Fractional calculus, fractional differential operator, fractional mask, fractional filter.

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Authors: K. A. Sumithradevi, Vijayalakshmi. M. N., Annamma Abraham., Dr. Vasanta

Abstract:

The various applications of VLSI circuits in highperformance computing, telecommunications, and consumer electronics has been expanding progressively, and at a very hasty pace. This paper describes a new model for partitioning a circuit using DBSCAN and fuzzy ARTMAP neural network. The first step is concerned with feature extraction, where we had make use DBSCAN algorithm. The second step is the classification and is composed of a fuzzy ARTMAP neural network. The performance of both approaches is compared using benchmark data provided by MCNC standard cell placement benchmark netlists. Analysis of the investigational results proved that the fuzzy ARTMAP with DBSCAN model achieves greater performance then only fuzzy ARTMAP in recognizing sub-circuits with lowest amount of interconnections between them The recognition rate using fuzzy ARTMAP with DBSCAN is 97.7% compared to only fuzzy ARTMAP.

Keywords: VLSI, Circuit partitioning, DBSCAN, fuzzyARTMAP.

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