Search results for: nonlinear statistical methods

Authors: Faranak Rabiei, Fudziah Ismail, S. Norazak, Saeid Emadi

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In this paper we developed the Improved Runge-Kutta Nystrom (IRKN) method for solving second order ordinary differential equations. The methods are two step in nature and require lower number of function evaluations per step compared with the existing Runge-Kutta Nystrom (RKN) methods. Therefore, the methods are computationally more efficient at achieving the higher order of local accuracy. Algebraic order conditions of the method are obtained and the third and fourth order method are derived with two and three stages respectively. The numerical results are given to illustrate the efficiency of the proposed method compared to the existing RKN methods.

Keywords: Improved Runge-Kutta Nystrom method, Two step method, Second-order ordinary differential equations, Order conditions

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Authors: Li Xiguang

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In this paper, by constructing a special non-empty closed convex set and utilizing M¨onch fixed point theory, we investigate the existence of solution for a class of fourth-order singular differential equation in Banach space, which improved and generalized the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation.

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Authors: M. R. Yadav, A. K. Sharma, B. S. Thakur

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The purpose of this paper is to present a best proximity point theorems through rational expression for a combination of contraction condition, Kannan and Chatterjea nonlinear cyclic contraction in what we call MT-K and MT-C rational cyclic contraction. Some best proximity point theorems for a mapping satisfy these conditions have been established in metric spaces. We also give some examples to support our work.

Keywords: Cyclic contraction, rational cyclic contraction, best proximity point and complete metric space.

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Authors: Ahmed Kadry, Gwyn Dodd

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There has been a growing call globally for police forces to embed evidence-based policing research methods into police interventions in order to better understand and evaluate their impact. This research study highlights the success and challenges that police forces may encounter when trying to embed evidence-based research methods within their organisation. Ten in-depth qualitative interviews were conducted with police officers and staff at Greater Manchester Police (GMP) who were tasked with integrating evidence-based research methods into their operational interventions. The findings of the study indicate that with adequate resources and individual expertise, evidence-based research methods can be applied to operational work, including the testing of initiatives with strict controls in order to fully evaluate the impact of an intervention. However, the findings also indicate that this may only be possible where an operational intervention is heavily resourced with police officers and staff who have a strong understanding of evidence-based policing research methods, attained for example through their own graduate studies. In addition, the findings reveal that ample planning time was needed to trial operational interventions that would require strict parameters for what would be tested and how it would be evaluated. In contrast, interviewees underscored that operational interventions with the need for a speedy implementation were less likely to have evidence-based research methods applied. The study contributes to the wider literature on evidence-based policing by providing considerations for police forces globally wishing to apply evidence-based research methods to more of their operational work in order to understand their impact. The study also provides considerations for academics who work closely with police forces in assisting them to embed evidence-based policing. This includes how academics can provide their expertise to police decision makers wanting to underpin their work through evidence-based research methods, such as providing guidance on how to evaluate the impact of their work with varying research methods that they may otherwise be unaware of.

Keywords: evidence based policing, evidence-based practice, operational policing, organisational change

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Authors: Kuntida Thamwipat, Sorakrich Maneewan, Thanarat Pumjaroen

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The purposes of this research were 1) to investigate behavior of media exposure and participation in environmental activities of King Mongkut-s University of Technology Thonburi (KMUTT) dormitory students, 2) to compare the correlation between faculties and participation in environmental activities of KMUTT dormitory students, and 3) to compare the correlation between media exposure and participation in environmental activities of KMUTT dormitory students. The tool used for collecting data was questionnaire. The research findings revealed that dormitory students were mostly exposed to the environmental media via public relations boards for general media and KMUTT dormitory media. Dormitory students were daily exposed to media via websites on the internet and weekly for other media. Dormitory students participation in the environmental activities was at high level (x = 3.65) on an individual basis and was at medium level (x = 2.76) on a collective basis. Faculties did not correlate with the participation in environmental activities of dormitory students at the .01 statistical level and media exposure via various media correlated with participation in environmental activities of dormitory students at the .01 statistical level.

Keywords: Dormitary Students, Environmental Activities Media Exposure, Participation.

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Authors: Kiurski S. Jelena, Oros B. Ivana, Kecić S. Vesna, Kovačević M. Ilija, Aksentijević M. Snežana

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The adsorption efficiency of various adsorbents for the removal of Zn(II) ions from the waste printing developer was studied in laboratory batch mode. The maximum adsorption efficiency of 94.1% was achieved with unfired clay pellets size (d ≈ 15 mm). The obtained values of adsorption efficiency was subjected to the independent-samples t test in order to investigate the statistically significant differences of the investigated adsorbents for the effective removal of Zn(II) ions from the waste printing developer. The most statistically significant differences of adsorption efficiencies for Zn(II) ions removal were obtained between unfired clay pellets (size d ≈ 15 mm) and activated carbon (½t½=6.909), natural zeolite (½t½=10.380), mixture of activated carbon and natural zeolite (½t½=9.865), bentonite (½t½=6.159), fired clay (½t½=6.641), fired clay pellets (size d ≈ 5 mm) (½t½=6.678), fired clay pellets (size d ≈ 8 mm) (½t½=3.422), respectively.

Keywords: Adsorbent, adsorption efficiency, statistical analysis, zinc ion.

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: Corporate credit rating prediction, feature selection, genetic algorithms, instance selection, multiclass support vector machines.

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Authors: Ramandeep Behl, Prashanth Maroju, S. S. Motsa

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In this paper, we study the semilocal convergence of a fifth order iterative method using recurrence relation under the assumption that first order Fréchet derivative satisfies the Hölder condition. Also, we calculate the R-order of convergence and provide some a priori error bounds. Based on this, we give existence and uniqueness region of the solution for a nonlinear Hammerstein integral equation of the second kind.

Keywords: Hölder continuity condition, Fréchet derivative, fifth order convergence, recurrence relations.

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

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Authors: Ayub V. O. Ofulla, Jackson H. O. Onyuka, Samuel Wagai, Douglas Anyona, Gabriel O. Dida, John Gichuki

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This study was set to determine the antimicrobial activities of brine salting, chlorinated solution, and oil frying treatments on enteric bacteria and fungi in Rastrineobola argentea fish from fish landing beaches within L. Victoria basin of western Kenya. Statistical differences in effectiveness of the different treatment methods was determined by single factor ANOVA, and paired two-tail t-Test was performed to compare the differences in moisture contents before and after storage. Oil fried fish recorded the lowest microbial loads, sodium chloride at 10% concentration was the second most effective and chlorinated solution even at 150ppm was the least effective against the bacteria and fungi in fish. Moisture contents of the control and treated fish were significantly lower after storage. These results show that oil frying of fish should be adopted for processing and preserving Rastrineobola argentea which is the most abundant and affordable fish species from Lake Victoria.

Keywords: Fish landing beaches, Lake Victoria, oil frying, preservatives.

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

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In this paper, there is an implementation, verification, and graphical demonstration of a software application, which can be used swiftly over different preliminary orbit determination methods. A passive orbit determination method is used in this study to determine the location of a satellite or a flying body. It is named a passive orbit determination because it depends on observation without the use of any aids (radio and laser) installed on satellite. In order to understand how these methods work and how their output is accurate when compared with available verification data, the built models help in knowing the different inputs used with each method. Output from the different orbit determination methods (Gibbs, Lambert, and Gauss) will be compared with each other and verified by the data obtained from Satellite Tool Kit (STK) application. A modified model including all of the orbit determination methods using the same input will be introduced to investigate different models output (orbital parameters) for the same input (azimuth, elevation, and time). Simulation software is implemented using MATLAB. A Graphical User Interface (GUI) application named OrDet is produced using the GUI of MATLAB. It includes all the available used inputs and it outputs the current Classical Orbital Elements (COE) of satellite under observation. Produced COE are then used to propagate for a complete revolution and plotted on a 3-D view. Modified model which uses an adapter to allow same input parameters, passes these parameters to the preliminary orbit determination methods under study. Result from all orbit determination methods yield exactly the same COE output, which shows the equality of concept in determination of satellite’s location, but with different numerical methods.

Keywords: Orbit determination, STK, MATLAB-GUI, satellite tracking.

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Authors: Saheed A. Gbadegeshin

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Commercialization method is a means to make inventions available at the market for final consumption. It is described as an important tool for keeping business enterprises sustainable and improving national economic growth. Thus, there are several scholarly publications on it, either presenting or testing different methods for commercialization. However, young entrepreneurs, technologists and scientists would like to know the best method to commercialize their innovations. Then, this question arises: What is the best commercialization method? To answer the question, a systematic literature review was conducted, and practitioners were interviewed. The literary results revealed that there are many methods but new methods are needed to improve commercialization especially during these times of economic crisis and political uncertainty. Similarly, the empirical results showed there are several methods, but the best method is the one that reduces costs, reduces the risks associated with uncertainty, and improves customer participation and acceptability. Therefore, it was concluded that new commercialization method is essential for today's high technologies and a method was presented.

Keywords: Commercialization method, high technology, lean start-up methodology, technology, knowledge.

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Authors: Xin Luo, Jin Huang, Pan Cheng

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By means of Sidi-Israeli’s quadrature rules, mechanical quadrature methods (MQMs) for solving the first kind boundary integral equations (BIEs) of steady state Stokes problem are presented. The convergence of numerical solutions by MQMs is proved based on Anselone’s collective compact and asymptotical compact theory, and the asymptotic expansions with the odd powers of the errors are provided, which implies that the accuracy of the approximations by MQMs possesses high accuracy order O (h3). Finally, the numerical examples show the efficiency of our methods.

Keywords: Stokes problem, boundary integral equation, mechanical quadrature methods, asymptotic expansions.

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Authors: Sumachaya Harnsukworapanich, Tetsuo Ichimori

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The apportionment method is used by many countries, to calculate the distribution of seats in political bodies. For example, this method is used in the United States (U.S.) to distribute house seats proportionally based on the population of the electoral district. Famous apportionment methods include the divisor methods called the Adams Method, Dean Method, Hill Method, Jefferson Method and Webster Method. Sometimes the results from the implementation of these divisor methods are unfair and include errors. Therefore, it is important to examine the optimization of this method by using a bias measurement to figure out precise and fair results. In this research we investigate the bias of divisor methods in the U.S. Houses of Representatives toward large and small states by applying the Stolarsky Mean Method. We compare the bias of the apportionment method by using two famous bias measurements: the Balinski and Young measurement and the Ernst measurement. Both measurements have a formula for large and small states. The Third measurement however, which was created by the researchers, did not factor in the element of large and small states into the formula. All three measurements are compared and the results show that our measurement produces similar results to the other two famous measurements.

Keywords: Apportionment, Bias, Divisor, Fair, Simulation

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Large Neural Network, Short-Term Load Forecasting, Particle Swarm Optimization.

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Authors: Ali Gholami, M.Esfadiari, M.H.Masihabadi

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In this research three methods of Maximum Likelihood, Mahalanobis Distance and Minimum Distance were analyzed in the Western part of Isfahan province in the Iran country. For this purpose, the IRS satellite images and various land preparation uses in region including rangelands, irrigation farming, dry farming, gardens and urban areas were separated and identified. In these methods, matrix error and Kappa index were calculated and accuracy of each method, based on percentages: 53.13, 56.64 and 48.44, were obtained respectively. Considering the low accuracy of these methods to separate land uses due to spread of the land uses, it-s suggested the visual interpretation of the map, to preparing the land use map in this region. The map prepared by visual interpretation is in high accuracy if it will be accompany with the visit of the region.

Keywords: Aghche Region, land use map, MaximumLikelihood, Mahalanobis Distance and Minimum Distance.

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Authors: Ka-Yan Yim, Chi-Wai Kan

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This paper conducts a comparison study using KES-FB and PhabrOmeter to measure 58 selected warp knitted fabric hand properties. Fabric samples were selected and measured by both KES-FB and PhabrOmeter. Results show differences between these two measurement methods. Smoothness and stiffness values obtained by KES-FB were found significant correlated (p value = 0.003 and 0.022) to the PhabrOmeter results while softness values between two measurement methods did not show significant correlation (p value = 0.828). Disagreements among these two measurement methods imply limitations on different mechanism principles when facing warp knitted fabrics. Subjective measurement methods and further studies are suggested in order to ascertain deeper investigation on the mechanisms of fabric hand perceptions.

Keywords: Fabric hand, fabric objective measurement, KES-FB, PhabrOmeter.

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Authors: Michal Polanský, C. Ardil

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This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.

Keywords: H norm, Linear Matrix Inequalities, Observers, Takagi-Sugeno Systems, Parallel Distributed Compensation

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Authors: Mohammad Taghi Darvishi, Maliheh Najafi, Mohammad Najafi

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In this paper, the generalized (2+1)-dimensional Calogero-Bogoyavlenskii-Schiff (shortly CBS) equations are investigated. We employ the Hirota-s bilinear method to obtain the bilinear form of CBS equations. Then by the idea of extended homoclinic test approach (shortly EHTA), some exact soliton solutions including breather type solutions are presented.

Keywords: EHTA, (2+1)-dimensional CBS equations, (2+1)-dimensional breaking solution equation, Hirota's bilinear form.

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Authors: Yu Yuan, David Feng, Yu-Zhuo Zhong

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Ringing effect is one of the most annoying visual artifacts in digital video. It is a significant factor of subjective quality deterioration. However, there is a widely-accepted misunderstanding of its cause. In this paper, we propose a reasonable interpretation of the cause of ringing effect. Based on the interpretation, we suggest further two methods to reduce ringing effect in DCT-based video coding. The methods adaptively adjust quantizers according to video features. Our experiments proved that the methods could efficiently improve subjective quality with acceptable additional computing costs.

Keywords: ringing effect, video coding, subjective quality, DCT.

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Authors: Parvinder S. Sandhu, Sunil Khullar, Satpreet Singh, Simranjit K. Bains, Manpreet Kaur, Gurvinder Singh

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Fault-proneness of a software module is the probability that the module contains faults. To predict faultproneness of modules different techniques have been proposed which includes statistical methods, machine learning techniques, neural network techniques and clustering techniques. The aim of proposed study is to explore whether metrics available in the early lifecycle (i.e. requirement metrics), metrics available in the late lifecycle (i.e. code metrics) and metrics available in the early lifecycle (i.e. requirement metrics) combined with metrics available in the late lifecycle (i.e. code metrics) can be used to identify fault prone modules using Genetic Algorithm technique. This approach has been tested with real time defect C Programming language datasets of NASA software projects. The results show that the fusion of requirement and code metric is the best prediction model for detecting the faults as compared with commonly used code based model.

Keywords: Genetic Algorithm, Fault Proneness, Software Faultand Software Quality.

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Authors: Damith Senanayake, Lakmal Muthugama, Laksheen Mendis, Tiroshan Madushanka

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Customer churn prediction is one of the most useful areas of study in customer analytics. Due to the enormous amount of data available for such predictions, machine learning and data mining have been heavily used in this domain. There exist many machine learning algorithms directly applicable for the problem of customer churn prediction, and here, we attempt to experiment on a novel approach by using a cognitive learning based technique in an attempt to improve the results obtained by using a combination of supervised learning methods, with cognitive unsupervised learning methods.

Keywords: Growing Self Organizing Maps, Kernel Methods, Churn Prediction.

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Authors: H. D. Ibrahim, H. C. Chinwenyi, H. N. Ude

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In this paper, efforts were made to examine and compare the algorithmic iterative solutions of conjugate gradient method as against other methods such as Gauss-Seidel and Jacobi approaches for solving systems of linear equations of the form Ax = b, where A is a real n x n symmetric and positive definite matrix. We performed algorithmic iterative steps and obtained analytical solutions of a typical 3 x 3 symmetric and positive definite matrix using the three methods described in this paper (Gauss-Seidel, Jacobi and Conjugate Gradient methods) respectively. From the results obtained, we discovered that the Conjugate Gradient method converges faster to exact solutions in fewer iterative steps than the two other methods which took much iteration, much time and kept tending to the exact solutions.

Keywords: conjugate gradient, linear equations, symmetric and positive definite matrix, Gauss-Seidel, Jacobi, algorithm

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Authors: Oleksandr Poliakov, Yevgen Pashkov, Marina Kolesova, Olena Chepenyuk, Mykhaylo Kalinin, Vadym Kramar

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In this paper we present a substantiation of a new Laguerre-s type iterative method for solving of a nonlinear polynomial equations systems with real coefficients. The problems of its implementation, including relating to the structural choice of initial approximations, were considered. Test examples demonstrate the effectiveness of the method at the solving of many practical problems solving.

Keywords: Iterative method, Laguerre's method, Newton's method, polynomial equation, system of equations

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Authors: Ademola K. Aremu, Joseph. C. Igbeka

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The performance of box-type solar cookers has been reported by several researchers but little attention was paid to the effect of the type of insulation material on the energy and exergy efficiency of these cookers. This research aimed at evaluating the energy and exergy efficiencies of the box-type cookers containing different insulation materials. Energy and exergy efficiencies of five box-type solar cookers insulated with maize cob, air (control), maize husk, coconut coir and polyurethane foam respectively were obtained over a period of three years. The cookers were evaluated using water heating test procedures in determining the energy and exergy analysis. The results were subjected to statistical analysis using ANOVA. The result shows that the average energy input for the five solar cookers were: 245.5, 252.2, 248.7, 241.5 and 245.5J respectively while their respective average energy losses were: 201.2, 212.7, 208.4, 189.1 and 199.8J. The average exergy input for five cookers were: 228.2, 234.4, 231.1, 224.4 and 228.2J respectively while their respective average exergy losses were: 223.4, 230.6, 226.9, 218.9 and 223.0J. The energy and exergy efficiency was highest in the cooker with coconut coir (37.35 and 3.90% respectively) in the first year but was lowest for air (11 and 1.07% respectively) in the third year. Statistical analysis showed significant difference between the energy and exergy efficiencies over the years. These results reiterate the importance of a good insulating material for a box-type solar cooker.

Keywords: Efficiency, energy, exergy, heating, insolation.

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Authors: Mohamed Shahin, Ahmed Badawi, Mohamed Kamel

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This paper presents a hand vein authentication system using fast spatial correlation of hand vein patterns. In order to evaluate the system performance, a prototype was designed and a dataset of 50 persons of different ages above 16 and of different gender, each has 10 images per person was acquired at different intervals, 5 images for left hand and 5 images for right hand. In verification testing analysis, we used 3 images to represent the templates and 2 images for testing. Each of the 2 images is matched with the existing 3 templates. FAR of 0.02% and FRR of 3.00 % were reported at threshold 80. The system efficiency at this threshold was found to be 99.95%. The system can operate at a 97% genuine acceptance rate and 99.98 % genuine reject rate, at corresponding threshold of 80. The EER was reported as 0.25 % at threshold 77. We verified that no similarity exists between right and left hand vein patterns for the same person over the acquired dataset sample. Finally, this distinct 100 hand vein patterns dataset sample can be accessed by researchers and students upon request for testing other methods of hand veins matching.

Keywords: Biometrics, Verification, Hand Veins, PatternsSimilarity, Statistical Performance.

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Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

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A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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Authors: Ritvik Chauhan, Vijay Kumar Baraik

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Women are most vulnerable to crime despite occupying central position in shaping a society as the first teacher of children. In India too, having equal rights and constitutional safeguards, the incidences of crime against them are large and grave. In this context of crime against women, especially rape has been increasing over time. This paper explores the spatial and temporal aspects of crime against women in India with special reference to rape. It also examines the crime against women with its spatial, socio-economic and demographic associates using related data obtained from the National Crime Records Bureau India, Indian Census and other government sources of the Government of India. The simple statistical, choropleth mapping and other cartographic representation methods have been used to see the crime rates, spatio-temporal patterns of crime, and association of crime with its correlates.  The major findings are visible spatial variations across the country and are also in the rising trends in terms of incidence and rates over the reference period. The study also indicates that the geographical associations are somewhat observed. However, selected indicators of socio-economic factors seem to have no significant bearing on crime against women at this level.

Keywords: Crime against women, crime mapping, trend analysis.

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Authors: Milan Rippel, Petr Teply

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This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Loss Distribution Approach and scenario analysis method are considered. Custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution is evaluated. Two main questions are assessed – What is the most appropriate statistical method to measure and model operational loss data distribution? and What is the impact of hypothetical plausible events on the financial institution? The g&h distribution was evaluated to be the most suitable one for operational risk modeling. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates and allows for the measurement of the impact of extreme events on banking operations.

Keywords: operational risk, scenario analysis, economic capital, loss distribution approach, extreme value theory, stress testing

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: Blood pressure, noninvasive optical system, PCA, continuous monitoring.

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