Search results for: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7608

Search results for: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy

5748 Numerical Simulation of the Flow Field around a 30° Inclined Flat Plate

Authors: M. Raciti Castelli, P. Cioppa, E. Benini

Abstract:

This paper presents a CFD analysis of the flow around a 30° inclined flat plate of infinite span. Numerical predictions have been compared to experimental measurements, in order to assess the potential of the finite volume code of determining the aerodynamic forces acting on a flat plate invested by a fluid stream of infinite extent. Several turbulence models and spatial node distributions have been tested and flow field characteristics in the neighborhood of the flat plate have been numerically investigated, allowing the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and the corresponding turbulence model for the prediction of the flow field over a twodimensional inclined plate.

Keywords: CFD, lift, drag, flat plate

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5747 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model

Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

Abstract:

A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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5746 Navigation of Multiple Mobile Robots using Rule-based-Neuro-Fuzzy Technique

Authors: Saroj Kumar Pradhan, Dayal Ramakrushna Parhi, Anup Kumar Panda

Abstract:

This paper deals with motion planning of multiple mobile robots. Mobile robots working together to achieve several objectives have many advantages over single robot system. However, the planning and coordination between the mobile robots is extremely difficult. In the present investigation rule-based and rulebased- neuro-fuzzy techniques are analyzed for multiple mobile robots navigation in an unknown or partially known environment. The final aims of the robots are to reach some pre-defined goals. Based upon a reference motion, direction; distances between the robots and obstacles; and distances between the robots and targets; different types of rules are taken heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and with an attracting influence between the robots and targets. Then a hybrid rule-based-neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation results show that the proposed rulebased- neuro-fuzzy technique can improve navigation performance in complex and unknown environments compared to this simple rulebased technique.

Keywords: Mobile robots, Navigation, Neuro-fuzzy, Obstacle avoidance, Rule-based, Target seeking

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5745 Optimizing Dialogue Strategy Learning Using Learning Automata

Authors: G. Kumaravelan, R. Sivakumar

Abstract:

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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5744 Induction Motor Efficiency Estimation using Genetic Algorithm

Authors: Khalil Banan, Mohammad B.B. Sharifian, Jafar Mohammadi

Abstract:

Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.

Keywords: Genetic algorithm, induction motor, efficiency.

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5743 Fragility Assessment for Vertically Irregular Buildings with Soft Storey

Authors: N. Akhavan, Sh. Tavousi Tafreshi, A. Ghasemi

Abstract:

Seismic behavior of irregular structures through the past decades indicate that the stated buildings do not have appropriate performance. Among these subjects, the current paper has investigated the behavior of special steel moment frame with different configuration of soft storey vertically. The analyzing procedure has been evaluated with respect to incremental dynamic analysis (IDA), and numeric process was carried out by OpenSees finite element analysis package. To this end, nine 2D steel frames, with different numbers of stories and irregularity positions, which were subjected to seven pairs of ground motion records orthogonally with respect to Ibarra-Krawinkler deterioration model, have been investigated. This paper aims at evaluating the response of two-dimensional buildings incorporating soft storey which subjected to bi-directional seismic excitation. The IDAs were implemented for different stages of PGA with various ground motion records, in order to determine maximum inter-storey drift ratio. According to statistical elements and fracture range (standard deviation), the vulnerability or exceedance from above-mentioned cases has been examined. For this reason, fragility curves for different placement of soft storey in the first, middle and the last floor for 4, 8, and 16 storey buildings have been generated and compared properly.

Keywords: Special steel moment frame, soft storey, incremental dynamic analysis, fragility curve.

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5742 Efficacy of Recovery Tech Virtual Reality Rehabilitation System for Shoulder Impingement Syndrome

Authors: Kasra Afsahi, Maryam Soheilifar, Nazanin Vahed, Omid Seyed Esmaeili, S. Hossein Hosseini

Abstract:

The most common cause of shoulder pain occurs when rotator cuff tendons become trapped under the bony area in the shoulder. This pilot study was performed to evaluate the feasibility of Virtual Reality based rehabilitation of shoulder impingement syndrome in athletes. Three consecutive patients with subacromial impingement syndrome were enrolled. The participants were rehabilitated for 5 times a week for 4 weeks, 20 sessions in total (with duration of each session being 60 minutes). In addition to the conventional rehabilitation program, a 10-minute game-based virtual reality exercise was administered. Primary outcome measures were range of motion evaluated with goniometer, pain sensation, disability intensity using ‘The Disabilities of the Arm, Shoulder and Hand Questionnaire’, muscle strength using ‘dynamometer’; pain threshold with 'algometer' and level of satisfaction. There were significant improvements in the range of motion, pain sensation, disability, pain threshold and muscle strength compared to basis (P < 0.05). There were no major adverse effects. This study showed the usefulness of VR therapy as an adjunct to conventional physiotherapy in improving function in patients with shoulder impingement syndrome.

Keywords: Shoulder impingement syndrome, VR therapy, feasibility, rehabilitation.

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5741 Mechanism of Alcohol Related Disruption of the Error Monitoring and Processing System

Authors: M. O. Welcome, Y. E. Razvodovsky, E. V. Pereverzeva, V. A. Pereverzev

Abstract:

The error monitoring and processing system, EMPS is the system located in the substantia nigra of the midbrain, basal ganglia and cortex of the forebrain, and plays a leading role in error detection and correction. The main components of EMPS are the dopaminergic system and anterior cingulate cortex. Although, recent studies show that alcohol disrupts the EMPS, the ways in which alcohol affects this system are poorly understood. Based on current literature data, here we suggest a hypothesis of alcohol-related glucose-dependent system of error monitoring and processing, which holds that the disruption of the EMPS is related to the competency of glucose homeostasis regulation, which in turn may determine the dopamine level as a major component of EMPS. Alcohol may indirectly disrupt the EMPS by affecting dopamine level through disorders in blood glucose homeostasis regulation.

Keywords: Alcohol related disruption, Error monitoring andprocessing system, Mechanism.

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5740 Exploiting Non Circularity for Angle Estimation in Bistatic MIMO Radar Systems

Authors: Ebregbe David, Deng Weibo

Abstract:

The traditional second order statistics approach of using only the hermitian covariance for non circular signals, does not take advantage of the information contained in the complementary covariance of these signals. Radar systems often use non circular signals such as Binary Phase Shift Keying (BPSK) signals. Their noncicular property can be exploited together with the dual centrosymmetry of the bistatic MIMO radar system to improve angle estimation performance. We construct an augmented matrix from the received data vectors using both the positive definite hermitian covariance matrix and the complementary covariance matrix. The Unitary ESPRIT technique is then applied to the signal subspace of the augmented covariance matrix for automatically paired Direction-of-arrival (DOA) and Direction-of-Departure (DOD) angle estimates. The number of targets that can be detected is twice that obtainable with the conventional ESPRIT approach. Simulation results show the effectiveness of this method in terms of increase in resolution and the number of targets that can be detected.

Keywords: Bistatic MIMO Radar, Unitary Esprit, Non circular signals.

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5739 Estimation of the Temperatures in an Asynchronous Machine Using Extended Kalman Filter

Authors: Yi Huang, Clemens Guehmann

Abstract:

In order to monitor the thermal behavior of an asynchronous machine with squirrel cage rotor, a 9th-order extended Kalman filter (EKF) algorithm is implemented to estimate the temperatures of the stator windings, the rotor cage and the stator core. The state-space equations of EKF are established based on the electrical, mechanical and the simplified thermal models of an asynchronous machine. The asynchronous machine with simplified thermal model in Dymola is compiled as DymolaBlock, a physical model in MATLAB/Simulink. The coolant air temperature, three-phase voltages and currents are exported from the physical model and are processed by EKF estimator as inputs. Compared to the temperatures exported from the physical model of the machine, three parts of temperatures can be estimated quite accurately by the EKF estimator. The online EKF estimator is independent from the machine control algorithm and can work under any speed and load condition if the stator current is nonzero current system.

Keywords: Asynchronous machine, extended Kalman filter, resistance, simulation, temperature estimation, thermal model.

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5738 On the Dynamic Model of Service Innovation in Manufacturing Industry

Authors: Yongyoon Suh, Chulhyun Kim, Moon-soo Kim

Abstract:

As the trend of manufacturing is being dominated depending on services, products and processes are more and more related with sophisticated services. Thus, this research starts with the discussion about integration of the product, process, and service in the innovation process. In particular, this paper sets out some foundations for a theory of service innovation in the field of manufacturing, and proposes the dynamic model of service innovation related to product and process. Two dynamic models of service innovation are suggested to investigate major tendencies and dynamic variations during the innovation cycle: co-innovation and sequential innovation. To structure dynamic models of product, process, and service innovation, the innovation stages in which two models are mainly achieved are identified. The research would encourage manufacturers to formulate strategy and planning for service development with product and process.

Keywords: dynamic model, service innovation, service innovation models, innovation cycle, manufacturing industry.

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5737 A Method for Iris Recognition Based on 1D Coiflet Wavelet

Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa

Abstract:

There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Keywords: Biometric, iris recognition, wavelet transform.

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5736 Estimation of Uncertainty of Thermal Conductivity Measurement with Single Laboratory Validation Approach

Authors: Saowaluck Ukrisdawithid

Abstract:

The thermal conductivity of thermal insulation materials are measured by Heat Flow Meter (HFM) apparatus. The components of uncertainty are complex and difficult on routine measurement by modelling approach. In this study, uncertainty of thermal conductivity measurement was estimated by single laboratory validation approach. The within-laboratory reproducibility was 1.1%. The standard uncertainty of method and laboratory bias by using SRM1453 expanded polystyrene board was dominant at 1.4%. However, it was assessed that there was no significant bias. For sample measurement, the sources of uncertainty were repeatability, density of sample and thermal conductivity resolution of HFM. From this approach to sample measurements, the combined uncertainty was calculated. In summary, the thermal conductivity of sample, polystyrene foam, was reported as 0.03367 W/m·K ± 3.5% (k = 2) at mean temperature 23.5 °C. The single laboratory validation approach is simple key of routine testing laboratory for estimation uncertainty of thermal conductivity measurement by using HFM, according to ISO/IEC 17025-2017 requirements. These are meaningful for laboratory competent improvement, quality control on products, and conformity assessment.

Keywords: Single laboratory validation approach, within-laboratory reproducibility, method and laboratory bias, certified reference material.

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5735 Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering

Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

Abstract:

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.

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5734 Non-Isothermal Kinetics of Crystallization and Phase Transformation of SiO2-Al2O3-P2O5-CaO-CaF Glass

Authors: Bogdan Il. Bogdanov, Plamen S. Pashev, Yancho H. Hristov, Dimitar P.Georgiev, Irena G. Markovska

Abstract:

The crystallization kinetics and phase transformation of SiO2.Al2O3.0,56P2O5.1,8CaO.0,56CaF2 glass have been investigated using differential thermal analysis (DTA), x-ray diffraction (XRD), and scanning electron microscopy (SEM). Glass samples were obtained by melting the glass mixture at 14500С/120 min. in platinum crucibles. The mixture were prepared from chemically pure reagents: SiO2, Al(OH)3, H3PO4, CaCO3 and CaF2. The non-isothermal kinetics of crystallization was studied by applying the DTA measurements carried out at various heating rates. The activation energies of crystallization and viscous flow were measured as 348,4 kJ.mol–1 and 479,7 kJ.mol–1 respectively. Value of Avrami parameter n ≈ 3 correspond to a three dimensional of crystal growth mechanism. The major crystalline phase determined by XRD analysis was fluorapatite (Ca(PO4)3F) and as the minor phases – fluormargarite (CaAl2(Al2SiO2)10F2) and vitlokite (Ca9P6O24). The resulting glass-ceramic has a homogeneous microstructure, composed of prismatic crystals, evenly distributed in glass phase.

Keywords: glass-ceramic, crystallization, non-isothermalkinetics, Avrami parameter

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5733 Development of Multimedia Learning Application for Mastery Learning Style: A Graduated Difficulty Strategy

Authors: Nur Azlina Mohamed Mokmin, Mona Masood

Abstract:

Guided by the theory of learning styles, this study is based on the development of a multimedia learning application for students with mastery learning style. The learning material was developed by applying a graduated difficulty learning strategy. Algebra was chosen as the learning topic for this application. The effectiveness of this application in helping students learn is measured by giving a pre- and post-test. The result shows that students who learn using the learning material that matches their preferred learning style perform better than the students with a non-personalized learning material.

Keywords: Algebraic Fractions, Graduated Difficulty, Mastery Learning Style, Multimedia.

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5732 Characterization of Aluminium Alloy 6063 Hybrid Metal Matrix Composite by Using Stir Casting Method

Authors: Balwinder Singh

Abstract:

The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.

Keywords: Reinforcement, silicon carbide, fly ash, red mud.

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5731 Modelling Conditional Volatility of Saving Rate by a Time-Varying Parameter Model

Authors: Katleho D. Makatjane, Kalebe M. Kalebe

Abstract:

The present paper used time-varying parameters which are based on the score function of a probability density at time t to model volatility of saving rate. We used a scaled likelihood function to update the parameters of the model overtime. Our results revealed high diligence of time-varying since the location parameter is greater than zero. Furthermore, we discovered a leptokurtic condition on saving rate’s distribution. Kapetanios, Shin-Shell Nonlinear Augmented Dickey-Fuller (KSS-NADF) test showed that the saving rate has a nonlinear unit root; therefore, it can be modeled by a generalised autoregressive score (GAS) model. Additionally, value at risk (VaR) and conditional tail expectation (CTE) indicate that 99% of the time people in Lesotho are saving more than spending. This puts the economy in high risk of not expanding. Therefore, the monetary policy committee (MPC) of Lesotho should revise their monetary policies towards this high saving rates risk.

Keywords: Generalized autoregressive score, time-varying, saving rate, Lesotho.

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5730 Mixed Integer Programing for Multi-Tier Rebate with Discontinuous Cost Function

Authors: Y. Long, L. Liu, K. V. Branin

Abstract:

One challenge faced by procurement decision-maker during the acquisition process is how to compare similar products from different suppliers and allocate orders among different products or services. This work focuses on allocating orders among multiple suppliers considering rebate. The objective function is to minimize the total acquisition cost including purchasing cost and rebate benefit. Rebate benefit is complex and difficult to estimate at the ordering step. Rebate rules vary for different suppliers and usually change over time. In this work, we developed a system to collect the rebate policies, standardized the rebate policies and developed two-stage optimization models for ordering allocation. Rebate policy with multi-tiers is considered in modeling. The discontinuous cost function of rebate benefit is formulated for different scenarios. A piecewise linear function is used to approximate the discontinuous cost function of rebate benefit. And a Mixed Integer Programing (MIP) model is built for order allocation problem with multi-tier rebate. A case study is presented and it shows that our optimization model can reduce the total acquisition cost by considering rebate rules.

Keywords: Discontinuous cost function, mixed integer programming, optimization, procurement, rebate.

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5729 Optimal Estimation of Supporting-Ground Orientation for Multi-Segment Body Based on Otolith-Canal Fusion

Authors: Karim A. Tahboub

Abstract:

This article discusses the problem of estimating the orientation of inclined ground on which a human subject stands based on information provided by the vestibular system consisting of the otolith and semicircular canals. It is assumed that body segments are not necessarily aligned and thus forming an open kinematic chain. The semicircular canals analogues to a technical gyrometer provide a measure of the angular velocity whereas the otolith analogues to a technical accelerometer provide a measure of the translational acceleration. Two solutions are proposed and discussed. The first is based on a stand-alone Kalman filter that optimally fuses the two measurements based on their dynamic characteristics and their noise properties. In this case, no body dynamic model is needed. In the second solution, a central extended disturbance observer that incorporates a body dynamic model (internal model) is employed. The merits of both solutions are discussed and demonstrated by experimental and simulation results.

Keywords: Kalman filter, orientation estimation, otolith-canalfusion, vestibular system.

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5728 Design for Reliability and Manufacturing Yield (Study and Modeling of Defects in Integrated Circuits for their Reliability Analysis)

Authors: G. Ait Abdelmalek, R. Ziani

Abstract:

In this document, we have proposed a robust conceptual strategy, in order to improve the robustness against the manufacturing defects and thus the reliability of logic CMOS circuits. However, in order to enable the use of future CMOS technology nodes this strategy combines various types of design: DFR (Design for Reliability), techniques of tolerance: hardware redundancy TMR (Triple Modular Redundancy) for hard error tolerance, the DFT (Design for Testability. The Results on largest ISCAS and ITC benchmark circuits show that our approach improves considerably the reliability, by reducing the key factors, the area costs and fault tolerance probability.

Keywords: Design for reliability, design for testability, fault tolerance, manufacturing yield.

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5727 Monte Carlo and Biophysics Analysis in a Criminal Trial

Authors: Luca Indovina, Carmela Coppola, Carlo Altucci, Riccardo Barberi, Rocco Romano

Abstract:

In this paper a real court case, held in Italy at the Court of Nola, in which a correct physical description, conducted with both a Monte Carlo and biophysical analysis, would have been sufficient to arrive at conclusions confirmed by documentary evidence, is considered. This will be an example of how forensic physics can be useful in confirming documentary evidence in order to reach hardly questionable conclusions. This was a libel trial in which the defendant, Mr. DS (Defendant for Slander), had falsely accused one of his neighbors, Mr. OP (Offended Person), of having caused him some damages. The damages would have been caused by an external plaster piece that would have detached from the neighbor’s property and would have hit Mr DS while he was in his garden, much more than a meter far away from the facade of the building from which the plaster piece would have detached. In the trial, Mr. DS claimed to have suffered a scratch on his forehead, but he never showed the plaster that had hit him, nor was able to tell from where the plaster would have arrived. Furthermore, Mr. DS presented a medical certificate with a diagnosis of contusion of the cerebral cortex. On the contrary, the images of Mr. OP’s security cameras do not show any movement in the garden of Mr. DS in a long interval of time (about 2 hours) around the time of the alleged accident, nor do they show any people entering or coming out from the house of Mr. DS in the same interval of time. Biophysical analysis shows that both the diagnosis of the medical certificate and the wound declared by the defendant, already in conflict with each other, are not compatible with the fall of external plaster pieces too small to be found. The wind was at a level 1 of the Beaufort scale, that is, unable to raise even dust (level 4 of the Beaufort scale). Therefore, the motion of the plaster pieces can be described as a projectile motion, whereas collisions with the building cornice can be treated using Newtons law of coefficients of restitution. Numerous numerical Monte Carlo simulations show that the pieces of plaster would not have been able to reach even the garden of Mr. DS, let alone a distance over 1.30 meters. Results agree with the documentary evidence (images of Mr. OP’s security cameras) that Mr. DS could not have been hit by plaster pieces coming from Mr. OP’s property.

Keywords: Biophysical analysis, Monte Carlo simulations, Newton’s law of restitution, projectile motion.

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5726 New Scheme in Determining nth Order Diagrams for Cross Multiplication Method via Combinatorial Approach

Authors: Sharmila Karim, Haslinda Ibrahim, Zurni Omar

Abstract:

In this paper, a new recursive strategy is proposed for determining $\frac{(n-1)!}{2}$ of $n$th order diagrams. The generalization of $n$th diagram for cross multiplication method were proposed by Pavlovic and Bankier but the specific rule of determining $\frac{(n-1)!}{2}$ of the $n$th order diagrams for square matrix is yet to be discovered. Thus using combinatorial approach, $\frac{(n-1)!}{2}$ of the $n$th order diagrams will be presented as $\frac{(n-1)!}{2}$ starter sets. These starter sets will be generated based on exchanging one element. The advantages of this new strategy are the discarding process was eliminated and the sign of starter set is alternated to each others.

Keywords: starter sets, permutation, exchanging one element, determinant

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5725 Levenberg-Marquardt Algorithm for Karachi Stock Exchange Share Rates Forecasting

Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

Abstract:

Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.

Keywords: Gradient descent method, jacobian matrix.Levenberg-Marquardt algorithm, quadratic error surfaces,

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5724 Pupils´ Questions at School Attendance Beginning and Teachers´ Teaching Strategy

Authors: Marie Pavelková, Hana Lukášová

Abstract:

Pupils´ inquisitiveness at the beginning of their school attendance is reflected by characteristics of the questions they ask. Clearly most of the classroom communication sequences are initiated by the teacher. But the teaching process also includes questions initiated by pupils in the need to satisfy their need for knowledge. The purpose of our research is to present the results of our pre-research strategy of occurrence of pupil-initiated questions in math lessons at the lower elementary school level, and to reveal the extent to which they are influenced by the teacher´s teaching strategy. We used the research methods of direct and indirect observations of fifth year classes in primary school. We focused on questions asked by the pupils in their math lessons. Our research sample for the pre-research observation method was a collection of video recordings available online. We used them for analysing the nature of pupils´ questions identified there. On the basis of the analysis, we hereby present the results concerning the nature of pupils´ questions asked in math lessons on the lower elementary school level. The interpretation of the collected results will be the starting point for the selection of research strategies in the next research stages concerning pupils’ questions in the future.

Keywords: Alternative strategies, 1ower elementary school level, pupil´s question, teaching strategies.

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5723 Research on Building Urban Sustainability along the Coastal Area in China

Authors: Sun Jiaojiao, Fu Jiayan

Abstract:

At present, in China, the research about the urban sustainability construction is still in the exploratory stage. The ecological problems of the coastal area are more sensitive and complicated. In the background of global warming with serious ecological damage, this paper deeply researches on the main characteristics of urban sustainability and measures how to build urban sustainability. Through combining regional environmental with economic ability along the coastal area, then authors put forward the system planning framework, construction strategy and the evaluation index system, in order to seek the way of building urban sustainability along coastal area in China.

Keywords: Urban sustainability, coastal areas, construction strategy, evaluation index system.

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5722 A Review on Cloud Computing and Internet of Things

Authors: Sahar S. Tabrizi, Dogan Ibrahim

Abstract:

Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.

Keywords: Cloud computing, cloud services, IaaS, PaaS, SaaS, IoT.

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5721 Segmentation of Gray Scale Images of Dropwise Condensation on Textured Surfaces

Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

Abstract:

In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: Dropwise condensation, textured surface, image processing, watershed.

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5720 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: Currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features.

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5719 Image Processing on Geosynthetic Reinforced Layers to Evaluate Shear Strength and Variations of the Strain Profiles

Authors: S. K. Khosrowshahi, E. Güler

Abstract:

This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.

Keywords: Image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile.

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