Search results for: Proportional gain prediction.

Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: Building energy management, machine learning, simulation-based optimization, operation planning.

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Authors: G.H. Farrahi, S.A. Faghidian, D.J. Smith

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A thin layer on the component surface can be found with high tensile residual stresses, due to turning operations, which can dangerously affect the fatigue performance of the component. In this paper an analytical approach is presented to reconstruct the residual stress field from a limited incomplete set of measurements. Airy stress function is used as the primary unknown to directly solve the equilibrium equations and satisfying the boundary conditions. In this new method there exists the flexibility to impose the physical conditions that govern the behavior of residual stress to achieve a meaningful complete stress field. The analysis is also coupled to a least squares approximation and a regularization method to provide stability of the inverse problem. The power of this new method is then demonstrated by analyzing some experimental measurements and achieving a good agreement between the model prediction and the results obtained from residual stress measurement.

Keywords: Residual stress, Limited measurements, Inverse problems, Turning process.

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Authors: Moaz H. Ali, M. N. M. Ansari, Pang Jing Shen

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In present work, prediction the effect of nose radius, rz (mm) on the equivalent strain (PEEQ) and surface finish during the machining of titanium alloy (Ti-6Al-4V) through orthogonal cutting process. The results were performed at several of the nose radiuses, rz (mm) while the cutting speed, vc (m/min), feed rate, f (mm/tooth) and depth of cut, d (mm) were remained constant. The equivalent plastic strain (PEEQ) was estimated by using finite element modeling (FEM) and applied through ABAQUS/EXPLICIT software. The simulation results led to conclude that the equivalent plastic strain (PEEQ) was increased and surface roughness (Ra) decreased when increasing nose radius, rz (mm) during the machining of titanium alloy (Ti–6Al–4V) in dry cutting conditions.

Keywords: Finite element modeling (FEM), nose radius, plastic strain (PEEQ), titanium alloy (Ti-6Al-4V).

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Authors: F. Rasi Maezabadi, M. Masdari, M. R. Soltani

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Series of experimental tests were conducted on a section of a 660 kW wind turbine blade to measure the pressure distribution of this model oscillating in plunging motion. In order to minimize the amount of data required to predict aerodynamic loads of the airfoil, a General Regression Neural Network, GRNN, was trained using the measured experimental data. The network once proved to be accurate enough, was used to predict the flow behavior of the airfoil for the desired conditions. Results showed that with using a few of the acquired data, the trained neural network was able to predict accurate results with minimal errors when compared with the corresponding measured values. Therefore with employing this trained network the aerodynamic coefficients of the plunging airfoil, are predicted accurately at different oscillation frequencies, amplitudes, and angles of attack; hence reducing the cost of tests while achieving acceptable accuracy.

Keywords: Airfoil, experimental, GRNN, Neural Network, Plunging.

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Authors: Suman B. Chakraborty, Samir Banerjee

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Stocking density is considered one of the important factors affecting fish growth. But, information related to impact of stocking density on growth performance of monosex tilapia population under the ecological conditions of Gangetic plains in West Bengal, India is limited. The aim of our study was to compare the growth potential of monosex tilapia at various stocking densities and to determine an ideal stocking density for culture of all-male monosex fish. The males were isolated by examination of genital papilla region and were stocked separately in 0.01 ha earthen ponds at different stocking densities (5000, 10000, 15000, 20000, 25000 and 30000 fingerlings/ha). It was found that the highest weight, length, daily weight gain, growth rate and protein content were observed for the 20000 fish/ha density class. Thus, culture of monosex tilapia at a density of 20000 fish/ha can be considered ideal for augmented production of the fish under Indian context.

Keywords: Growth potential, Nile tilapia, Pond culture, Stockingdensity.

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Authors: J. P. Dubois

Abstract:

Stochastic modeling of network traffic is an area of significant research activity for current and future broadband communication networks. Multimedia traffic is statistically characterized by a bursty variable bit rate (VBR) profile. In this paper, we develop an improved model for uniform activity level video sources in ATM using a doubly stochastic autoregressive model driven by an underlying spatial point process. We then examine a number of burstiness metrics such as the peak-to-average ratio (PAR), the temporal autocovariance function (ACF) and the traffic measurements histogram. We found that the former measure is most suitable for capturing the burstiness of single scene video traffic. In the last phase of this work, we analyse statistical multiplexing of several constant scene video sources. This proved, expectedly, to be advantageous with respect to reducing the burstiness of the traffic, as long as the sources are statistically independent. We observed that the burstiness was rapidly diminishing, with the largest gain occuring when only around 5 sources are multiplexed. The novel model used in this paper for characterizing uniform activity video was thus found to be an accurate model.

Keywords: AR, ATM, burstiness, doubly stochastic, statisticalmultiplexing.

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Authors: Victoria S. Scarratt

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Couples involved in age-gap relationships generally evoke negative stereotypes, opinions, and social disapproval. This research seeks to examine whether financial disparities in age-discrepant relationships cause negative attitudes in study participants. It was hypothesized that an age-gap couple (29-year difference) would receive a greater degree of societal disapproval when the couple also had a large salary-gap compared to a similarly aged couple (1-year difference) with a salary-gap. Additionally, there would be no significant difference between age-gap couples without a salary-gap compared to a similarly aged couple without a salary gap. To test the hypothesis, participants were given one of four scenarios regarding a couple in a romantic relationship. Then they were asked to respond to nine Likert scale questions. Results indicated that participants perceived age-gap relationships with a salary disparity to be less equitable in regard to a power imbalance between the couple and the financial and general gain that one partner will receive. A significant interaction was also detected for evoking feelings of disgust in participants, and how morally correct it is for the couple to continue their relationship.

Keywords: Age-gap relationships, financial discrepancies, love, relationships, societal stigmas.

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Authors: Saurav Bhattacharjee, Syam Nair

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Lime stabilization is a sustainable and economically viable option to address strength deficiencies of subgrade soils. However, exposure of stabilized layers to environmental elements can lead to a reduction in post-stabilization strength gain expected in these layers. The current study investigates the impact of carbonation on the strength properties of lime-treated soils. Manufactured soils prepared using varying proportions of bentonite silica mixtures were used in the study. Lime-treated mixtures were exposed to different atmospheric conditions created by varying the concentrations of CO₂ in the testing chamber. The impact of CO₂ diffusion was identified based on changes in carbonate content and unconfined compressive strength (UCS) properties. Changes in soil morphology were also investigated as part of the study. The rate of carbonation was observed to vary polynomially (2nd order) with exposure time. The strength properties of the mixes were observed to decrease with exposure time.

Keywords: Manufactured soil, carbonation, morphology, unconfined compressive strength.

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Authors: Inamullah Bhatti, Ahsanullah Baloch, Khadija Qureshi

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The objective of this research is to examine the shear thinning behaviour of mixing flow of non-Newtonian fluid like toothpaste in the dissolution container with rotating stirrer. The problem under investigation is related to the chemical industry. Mixing of fluid is performed in a cylindrical container with rotating stirrer, where stirrer is eccentrically placed on the lid of the container. For the simulation purpose the associated motion of the fluid is considered as revolving of the container, with stick stirrer. For numerical prediction, a time-stepping finite element algorithm in a cylindrical polar coordinate system is adopted based on semi-implicit Taylor-Galerkin/pressure-correction scheme. Numerical solutions are obtained for non-Newtonian fluids employing power law model. Variations with power law index have been analysed, with respect to the flow structure and pressure drop.

Keywords: finite element simulation, mixing fluid, rheology, rotating flow, toothpaste

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Authors: Djarot B. Darmadi

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The wider growing Finite Element Method (FEM) application is caused by its benefits of cost saving and environment friendly. Also, by using FEM a deep understanding of certain phenomenon can be achieved. This paper observed the role of material properties and volumetric change when Solid State Phase Transformation (SSPT) takes place in residual stress formation due to a welding process of ferritic steels through coupled Thermo- Metallurgy-Mechanical (TMM) analysis. The correctness of FEM residual stress prediction was validated by experiment. From parametric study of the FEM model, it can be concluded that the material properties change tend to over-predicts residual stress in the weld center whilst volumetric change tend to underestimates it. The best final result is the compromise of both by incorporates them in the model which has a better result compared to a model without SSPT.

Keywords: Residual stress, ferritic steels, SSPT, coupled-TMM.

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Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

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Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.

Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.

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Authors: Zarita Zainuddin, Ong Pauline, C. Ardil

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Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Keywords: Diabetes Mellitus, principal component analysis, time-series, wavelet neural network.

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Authors: Supriya Pal, Kalyan Adhikari, Somnath Mukherjee, Sudipta Ghosh

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This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent concentration of phenol(mg/L) on the top end of the soil column, depth of the soil column (cm), elapsed time after phenol injection (hr), percentage of clay (%), percentage of silt (%) in soils. The output of the ANN was the effluent phenol concentration (mg/L) from the bottom end of the soil columns. The ANN predicted results were compared with the experimental results of the laboratory tests and the accuracy of the ANN model was evaluated.

Keywords: Modeling, Neural Networks, Phenol, Soil media

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Authors: Mohammed Bilal

Abstract:

The precise prediction of aerodynamic behavior is necessary for the design and optimization of airfoils for a variety of applications. Turbulence, a phenomenon of complex and irregular flow, significantly affects the aerodynamic properties of airfoils. Therefore, turbulence modeling is essential for accurately predicting the behavior of airfoils in simulations. This study investigates five commonly employed turbulence models: Spalart-Allmaras (SA) model, k-epsilon model, k-omega model, Reynolds Stress Model (RSM), and Large Eddy Simulation (LES) model. The paper includes a comparison of the models' precision, computational expense, and applicability to various flow conditions. The strengths and weaknesses of each model are highlighted, allowing researchers and engineers to make informed decisions regarding simulations of specific airfoils. Unquestionably, the continuous development of turbulence modeling will contribute to further improvements in airfoil design and optimization, which will be advantageous to numerous industries.

Keywords: Computational fluid dynamics, airfoil, turbulence, aircraft.

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Authors: Nasim Ullah, Shaoping Wang

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ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.

Keywords: ELS, Observer, Transient Performance, SMC, Extra Torque, Fuzzy Logic.

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Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

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Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: Complex adaptive systems, X-events, risk management, antifragility, banking antifragility index, triangular fuzzy number.

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: Forecasting, ordinary differential equations, SARS-CoV-2 epidemic, SIR model.

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Authors: Sonia Alberti

Abstract:

The Regional Conference to Restructure Psychiatric Care in Latin America, convened by the Pan American Health Organization (PAHO) in 1990, oriented the Brazilian Federal Act in 2001 that stipulated the psychiatric reform which requires deinstitutionalization and community-based treatment. Since then, the 15 years’ experience of different working teams in mental health led an academic working group – supervisors from personal practices, professors and researchers – to discuss certain clinical issues, as well as supervisions, and to organize colloquia in different cities as a methodology. These colloquia count on the participation of different working teams from the cities in which they are held, with team members with different levels of educational degrees and prior experiences, in order to increase dialogue right where it does not always appear to be possible. The principal aim of these colloquia is to gain interlocution between practitioners and academics. Working with the theory of case constructions, this methodology revealed itself helpful in unfolding new solutions. The paper also observes that there is not always harmony between what the psychiatric reform demands and clinical ethics.

Keywords: Mental health, supervision, clinical cases, Brazilian experience.

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Authors: Mehdi Shami Zanjani, Shohreh Mehrasa, Mandana Modiri

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In the current economy of increasing global competition, many organizations are attempting to use knowledge as one of the means to gain sustainable competitive advantage. Besides large organizations, the success of SMEs can be linked to how well they manage their knowledge. Despite the profusion of research about knowledge management within large organizations, fewer studies tried to analyze KM in SMEs. This research proposes a new framework showing the determinant role of organizational dimensions onto KM approaches. The paper and its propositions are based on a literature review and analysis. In this research, personalization versus codification, individualization versus institutionalization and IT-based versus non IT-based are highlighted as three distinct dimensions of knowledge management approaches. The study contributes to research by providing a more nuanced classification of KM approaches and provides guidance to managers about the types of KM approaches that should be adopted based on the size, geographical dispersion and task nature of SMEs. To the author-s knowledge, the paper is the first of its kind to examine if there are suitable configurations of KM approaches for SMEs with different dimensions. It gives valuable information, which hopefully will help SME sector to accomplish KM.

Keywords: Knowledge Management, Knowledge Management Approach, SME, Organizational Dimension.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Victoria Wolf, Renata Dobrucka, Robert Prezkop, Stephan Haubold

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The COVID-19 causes a worldwide crisis and has an impact in every dimension of the economy. Organizations with the ability to adapt to new developments and which innovate solutions for the disrupted world during and after the Corona crises have the opportunity to not only survive the crisis but rather to use new trends to implement new business models and gain advantage. In this context, startups seem to have better opportunities to manage the Corona crisis through their innovation-based nature. The main result of this paper is the understanding that by applying a startup orientated innovation (SOCI) strategy, established companies can be motivated to meet the challenge of COVID-19 in a similar way like startups. This result can be achieved by describing the role of innovation and a SOCI strategy as helpful methods for organizations to meet the coming challenges during and after the COVID-19 epidemics. In addition to this, this paper presents a practical application of SOCI through the PANDA approach of the Fresenius University of Applied Sciences in Germany and discuss it in the context of COVID-19 as an exemplary successful real-world implementation of SOCI strategy.

Keywords: COVID-19, innovation, open innovation, startup, SOCI framework.

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Authors: M. Fems Kurotimi, Agada Franklin, Godsave Aladei, Opigo Helen

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Within the last 30 years, entrepreneurship education (EE) has continued to gain massive interest both in the field of research and among policy makers. This surge in interest can be attributed to the perceived importance EE plays in the equipping of potential entrepreneurs and as a 21^st century strategy to foster economic growth and development. This paper sets out to ascertain the correlation between EE and economic growth and development. A desk research approach was adopted where a multiplicity of literatures in the field were studied intensely. The findings reveal that indeed EE has a positive effect on entrepreneurship engagement thereby fostering economic growth and development. However, some research studies reported the contrary. That although EE may be able to equip potential entrepreneurs with requisite entrepreneurial skills and competencies, it will only be successful in producing entrepreneurs if they are internally driven to become entrepreneurs, because we cannot make people what they are not. The findings also reveal that countries that adopted EE early have more innovations inspired by entrepreneurs and are more developed than those that only recently adopted EE as a viable tool for entrepreneurship and economic development.

Keywords: Entrepreneurship, entrepreneurship education, economic development, economic growth, sustainable development.

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Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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Authors: Chit Su Htwe, Win Htay

Abstract:

The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

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Authors: Dalvir Singh, Somnath Chattopadhyaya

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During welding or flame cutting of metals, the prediction of heat affected zone (HAZ) is critical. There is need to develop a simple mathematical model to calculate the temperature variation in HAZ and derivative analysis can be used for this purpose. This study presents analytical solution for heat transfer through conduction in mild steel plate. The homogeneous and nonhomogeneous boundary conditions are single variables. The full field analytical solutions of temperature measurement, subjected to local heating source, are derived first by method of separation of variables followed with the experimental visualization using infrared imaging. Based on the present work, it is suggested that appropriate heat input characteristics controls the temperature distribution in and around HAZ.

Keywords: Conduction Heat Transfer, Heat Affected Zone (HAZ), Infra-Red Imaging, Numerical Method, Orthogonal Function, Plasma Arc Cutting, Separation of Variables, Temperature Measurement.

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

Abstract:

In this study, an Artificial Neural Network (ANN) analytical method has been developed for analyzing earthquake performances of the Reinforced Concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: Artificial neural network, earthquake, performance, reinforced concrete.

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Authors: Rawad Asfour, Salam Khamas, Edward A. Ball

Abstract:

This paper is focused on the design of an mm-wave phased array. To date, linear polarization is adapted in the reported designs of phased arrays. However, linear polarization faces several well-known challenges. As such, an advanced design for phased array antennas is required that offers circularly polarized (CP) radiation. A feasible solution for achieving CP phased array antennas is proposed using open-circular loop antennas. To this end, a 3-element circular loop phased array antenna is designed to operate at 28 GHz. In addition, the array ability to control the direction of the main lobe is investigated. The results show that the highest achievable field of view (FOV) is 100°, i.e. 50° to the left and 50° to the right-hand side directions. The results are achieved with a CP bandwidth of 15%. Furthermore, the results demonstrate that a high broadside gain of circa 11 dBi can be achieved for the steered beam. Besides, radiation efficiency of 97% can also be achieved based on the proposed design.

Keywords: loop antenna, phased array, beam steering, wide bandwidth, circular polarization, CST

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Authors: D. Uma Devi, P. Seetha Ramaiah

Abstract:

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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Authors: Surinder Deswal, D. V. S. Verma

Abstract:

Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.

Keywords: Conical plunging jet, oxygen-transfer efficiency, support vector machines, volumetric oxygen-transfer coefficient.

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Authors: P.Varzakas

Abstract:

In this paper, an accurate theoretical analysis for the achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct-sequence/fast frequency hopping code-division multiple-access (DS/FFH-CDMA) system operating in a Rayleigh fading environment is presented. The analysis covers the downlink operation and leads to the derivation of an exact mathematical expression between the normalized average channel capacity available to each system-s user, under simultaneous optimal power and rate adaptation and the system-s parameters, as the number of hops per bit, the processing gain applied, the number of users per cell and the received signal-tonoise power ratio over the signal bandwidth. Finally, numerical results are presented to illustrate the proposed mathematical analysis.

Keywords: Shannon capacity, adaptive systems, code-division multiple access, fading channels.

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