Search results for: quadratic loss function.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3154

Search results for: quadratic loss function.

2764 Measurement of CES Production Functions Considering Energy as an Input

Authors: Donglan Zha, Jiansong Si

Abstract:

Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: Bias of technical change, CES production function, elasticity of substitution, energy input.

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2763 Zigbee Based Wireless Energy Surveillance System for Energy Savings

Authors: Won-Ho Kim, Chang-Ho Hyun, Moon-Jung Kim

Abstract:

In this paper, zigbee communication based wireless energy surveillance system is presented. The proposed system consists of multiple energy surveillance devices and an energy surveillance monitor. Each different standby power-off value of electric device is set automatically by using learning function of energy surveillance device. Thus adaptive standby power-off function provides user convenience and it maximizes the energy savings. Also, power consumption monitoring function is helpful to reduce inefficient energy consumption in home. The zigbee throughput simulator is designed to evaluate minimum transmission power and maximum allowable information quantity in the proposed system. The test result of prototype has been satisfied all the requirements. The proposed system has confirmed that can be used as an intelligent energy surveillance system for energy savings in home or office.

Keywords: Energy monitoring system, Energy surveillance system, Energy sensor network, Energy savings.

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2762 Optimal Aggregate Production Planning with Fuzzy Data

Authors: Wen-Lung Huang, Shih-Pin Chen

Abstract:

This paper investigates the optimization problem of multi-product aggregate production planning (APP) with fuzzy data. From a comprehensive viewpoint of conserving the fuzziness of input information, this paper proposes a method that can completely describe the membership function of the performance measure. The idea is based on the well-known Zadeh-s extension principle which plays an important role in fuzzy theory. In the proposed solution procedure, a pair of mathematical programs parameterized by possibility level a is formulated to calculate the bounds of the optimal performance measure at a . Then the membership function of the optimal performance measure is constructed by enumerating different values of a . Solutions obtained from the proposed method contain more information, and can offer more chance to achieve the feasible disaggregate plan. This is helpful to the decision-maker in practical applications.

Keywords: fuzzy data, aggregate production planning, membership function, parametric programming

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2761 Determination of Optimal Stress Locations in 2D–9 Noded Element in Finite Element Technique

Authors: Nishant Shrivastava, D. K. Sehgal

Abstract:

In Finite Element Technique nodal stresses are calculated through displacement as nodes. In this process, the displacement calculated at nodes is sufficiently good enough but stresses calculated at nodes are not sufficiently accurate. Therefore, the accuracy in the stress computation in FEM models based on the displacement technique is obviously matter of concern for computational time in shape optimization of engineering problems. In the present work same is focused to find out unique points within the element as well as the boundary of the element so, that good accuracy in stress computation can be achieved. Generally, major optimal stress points are located in domain of the element some points have been also located at boundary of the element where stresses are fairly accurate as compared to nodal values. Then, it is subsequently concluded that there is an existence of unique points within the element, where stresses have higher accuracy than other points in the elements. Therefore, it is main aim is to evolve a generalized procedure for the determination of the optimal stress location inside the element as well as at the boundaries of the element and verify the same with results from numerical experimentation. The results of quadratic 9 noded serendipity elements are presented and the location of distinct optimal stress points is determined inside the element, as well as at the boundaries. The theoretical results indicate various optimal stress locations are in local coordinates at origin and at a distance of 0.577 in both directions from origin. Also, at the boundaries optimal stress locations are at the midpoints of the element boundary and the locations are at a distance of 0.577 from the origin in both directions. The above findings were verified through experimentation and findings were authenticated. For numerical experimentation five engineering problems were identified and the numerical results of 9-noded element were compared to those obtained by using the same order of 25-noded quadratic Lagrangian elements, which are considered as standard. Then root mean square errors are plotted with respect to various locations within the elements as well as the boundaries and conclusions were drawn. After numerical verification it is noted that in a 9-noded element, origin and locations at a distance of 0.577 from origin in both directions are the best sampling points for the stresses. It was also noted that stresses calculated within line at boundary enclosed by 0.577 midpoints are also very good and the error found is very less. When sampling points move away from these points, then it causes line zone error to increase rapidly. Thus, it is established that there are unique points at boundary of element where stresses are accurate, which can be utilized in solving various engineering problems and are also useful in shape optimizations.

Keywords: Finite element, Lagrangian, optimal stress location, serendipity.

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2760 Overview of Operational Risk Management Methods

Authors: Milan Rippel, Pert Teplý

Abstract:

Operational risk has become one of the most discussed topics in the financial industry in the recent years. The reasons for this attention can be attributed to higher investments in information systems and technology, the increasing wave of mergers and acquisitions and emergence of new financial instruments. In addition, the New Basel Capital Accord (known as Basel II) demands a capital requirement for operational risk and further motivates financial institutions to more precisely measure and manage this type of risk. The aim of this paper is to shed light on main characteristics of operational risk management and common applied methods: scenario analysis, key risk indicators, risk control self assessment and loss distribution approach.

Keywords: Operational risk, economic capital, key risk indicators, loss distribution approach.

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2759 Electrical Analysis of Corn Oil as an Alternative to Mineral Oil in Power Transformers

Authors: E. Taslak, C. Kocatepe, O. Arıkan, C. F. Kumru

Abstract:

In insulation and cooling of power transformers various liquids are used. Mineral oils have wide availability and low cost. However, they have a poor biodegradability potential and lower fire point in comparison with other insulating liquids. Use of a liquid having high biodegradability is important due to environmental consideration. This paper investigates edible corn oil as an alternative to mineral oil. Various properties of mineral and corn oil like breakdown voltage, dissipation factor, relative dielectric constant, power loss and resistivity were measured according to different standards.

Keywords: Breakdown voltage, corn oil, dissipation factor, mineral oil, power loss, relative dielectric constant, resistivity.

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2758 Roles of Aquatic Plants on Erosion Relief of Stream Bed

Authors: Jin-Hong Kim

Abstract:

Roles of the vegetation to mitigate the erosion of the stream bed or to facilitate the deposition of the fine sediments by the species of the aquatic plants were presented. Field investigation on the estimation of the change of the bed level and the estimation of the flow characteristics were performed. The results showed that Phragmites japonica has the mitigation function of 0.3m-0.4m of the erosion in the range of higher than 1.0m/s of flow velocity at the vegetated region. Phragmites communis has the mitigation function of 0.2m-0.3m of the erosion in the range of higher than 0.7m/s of flow velocity at the vegetated region. Salix gracilistyla has greater role than Phragmites japonica and Phragmites communis to sustain the stable channel. It has the mitigation function of 0.4m-0.5m of the erosion in the range of higher than 1.4m/s of flow velocity. Miscanthus sacchariflorus has a weak role compared with that of Phragmites japonica and Salix gracilistyla, but it has still function for sustaining the stable bed. From these results, the vegetation has effective roles to mitigate the erosion or to facilitate the deposition of the stream bed.

Keywords: Aquatic plants, Phragmites japonica, Phragmites communis, Miscanthus sacchariflorus, Salix gracilistyla.

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2757 Effect of Windrow Management on Ammonia and Nitrous Oxide Emissions from Swine Manure Composting

Authors: Nanh Lovanh, John Loughrin, Kimberly Cook, Phil Silva, Byung-Taek Oh

Abstract:

In the era of sustainability, utilization of livestock wastes as soil amendment to provide micronutrients for crops is very economical and sustainable. It is well understood that livestock wastes are comparable, if not better, nutrient sources for crops as chemical fertilizers. However, the large concentrated volumes of animal manure produced from livestock operations and the limited amount of available nearby agricultural land areas necessitated the need for volume reduction of these animal wastes. Composting of these animal manures is a viable option for biomass and pathogenic reduction in the environment. Nevertheless, composting also increases the potential loss of available nutrients for crop production as well as unwanted emission of anthropogenic air pollutants due to the loss of ammonia and other compounds via volatilization. In this study, we examine the emission of ammonia and nitrous oxide from swine manure windrows to evaluate the benefit of biomass reduction in conjunction with the potential loss of available nutrients. The feedstock for the windrows was obtained from swine farm in Kentucky where swine manure was mixed with wood shaving as absorbent material. Static flux chambers along with photoacoustic gas analyzer were used to monitor ammonia and nitrous oxide concentrations during the composting process. The results show that ammonia and nitrous oxide fluxes were quite high during the initial composting process and after the turning of each compost pile. Over the period of roughly three months of composting, the biochemical oxygen demand (BOD) decreased by about 90%. Although composting of animal waste is quite beneficial for biomass reduction, composting may not be economically feasible from an agronomical point of view due to time, nutrient loss (N loss), and potential environmental pollution (ammonia and greenhouse gas emissions). Therefore, additional studies are needed to assess and validate the economics and environmental impact of animal (swine) manure composting (e.g., crop yield or impact on climate change).

Keywords: Windrow, swine manure, ammonia, nitrous oxide, fluxes, management.

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2756 Hybrid Algorithm for Hammerstein System Identification Using Genetic Algorithm and Particle Swarm Optimization

Authors: Tomohiro Hachino, Kenji Shimoda, Hitoshi Takata

Abstract:

This paper presents a method of model selection and identification of Hammerstein systems by hybridization of the genetic algorithm (GA) and particle swarm optimization (PSO). An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The weighting parameters of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. On the other hand, the adjusting parameters of the ACF model structure are properly selected by the hybrid algorithm of the GA and PSO, where the Akaike information criterion is utilized as the evaluation value function. Simulation results are shown to demonstrate the effectiveness of the proposed hybrid algorithm.

Keywords: Hammerstein system, identification, automatic choosing function model, genetic algorithm, particle swarm optimization.

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2755 Cardiac Function and Morphological Adaptations in Endurance and Resistance Athletes: Evaluation using a new Method

Authors: K. Hosseini, MD., R. Mazaheri, MD., H.R. Khoddami Vishteh, MD., M.A. Mansournia, MD., H. Angoorani, MD

Abstract:

Background: Tissue Doppler Echocardiography (TDE) assesses diastolic function more accurately than routine pulse Doppler echo. Assessment of the effects of dynamic and static exercises on the heart by using TDE can provides new information about the athlete-s heart syndrome. Methods: This study was conducted on 20 elite wrestlers, 14 endurance runners at national level and 21 non-athletes as the control group. Participants underwent two-dimensional echocardiography, standard Doppler and TDE. Results: Wrestlers had the highest left ventricular mass index, enddiastolic inter-ventricular septum thickness and left ventricular Posterior wall thickness. Runners had the highest Left ventricular end-diastolic volume, LV ejection fraction, stroke volume and cardiac output. In TDE, the early diastolic velocity of mitral annulus to the late diastolic velocity ratio in athletic groups was greater than the controls with no significant difference. Conclusion: In spite of cardiac morphological changes in athletes, TDE shows that cardiac diastolic function won-t be adversely affected.

Keywords: Tissue Doppler Echocardiography, Diastolic function, Athlete's heart syndrome, Static exercise, Dynamic exercise

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2754 Grooved Linear Microstrip Patch Antenna Array

Authors: Ayesha Aslam, F A Bhatti

Abstract:

A simple impedance matching technique for inset feed grooved microstrip patch antenna based on the concept of coplanar waveguide feed line has been developed and investigated for a printed antenna at X-Band frequency of 10GHz. The proposed technique has been used in the design of Linear Grooved Microstrip patch antenna array. The characteristics of the antenna are determined in terms of Return loss, VSWR, gain, radiation pattern etc. The measured and simulated results presented are found to be in good agreement.

Keywords: Gain, Microstrip patch, return loss, VSWR, Radiation pattern, CPW Feed, Inset feed.

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2753 The Whale Optimization Algorithm and Its Implementation in MATLAB

Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

Abstract:

Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.

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2752 Use of Radial Basis Function Neural Network for Bearing Pressure Prediction of Strip Footing on Reinforced Granular Bed Overlying Weak Soil

Authors: Srinath Shetty K., Shivashankar R., Rashmi P. Shetty

Abstract:

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

Keywords: Bearing pressure, granular bed, radial basis function neural network, strip footing.

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2751 LQR Control for a Multi-MW Wind Turbine

Authors: Trung-Kien Pham, Yoonsu Nam, Hyungun Kim, Jaehoon Son

Abstract:

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbine, a set of operating conditions is identified and then a LQR controller is designed for each operating point. The feedback controller gains are then interpolated linearly to get control law for the entire operating region. Besides, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of the method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with that when using PI controller.

Keywords: variable speed variable pitch wind turbine, multi-MW size wind turbine, wind energy conversion system, LQR control.

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2750 DWT Based Robust Watermarking Embed Using CRC-32 Techniques

Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi

Abstract:

As far as the latest technological improvements are concerned, digital systems more become popular than the past. Despite this growing demand to the digital systems, content copy and attack against the digital cinema contents becomes a serious problem. To solve the above security problem, we propose “traceable watermarking using Hash functions for digital cinema system. Digital Cinema is a great application for traceable watermarking since it uses watermarking technology during content play as well as content transmission. The watermark is embedded into the randomly selected movie frames using CRC-32 techniques. CRC-32 is a Hash function. Using it, the embedding position is distributed by Hash Function so that any party cannot break off the watermarking or will not be able to change. Finally, our experimental results show that proposed DWT watermarking method using CRC-32 is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.

Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip, traceable watermark, Hash Function, CRC-32.

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2749 Distortion Estimation in Digital Image Watermarking using Genetic Programming

Authors: Labiba Gilani, Asifullah Khan, Anwar M. Mirza

Abstract:

This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

Keywords: Blind Watermarking, Genetic Programming (GP), Fitness Function, Discrete Cosine Transform (DCT).

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2748 A Wavelet-Based Watermarking Method Exploiting the Contrast Sensitivity Function

Authors: John N. Ellinas, Panagiotis Kenterlis

Abstract:

The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The current paper presents an approach for still image digital watermarking in which the watermark embedding process employs the wavelet transform and incorporates Human Visual System (HVS) characteristics. The sensitivity of a human observer to contrast with respect to spatial frequency is described by the Contrast Sensitivity Function (CSF). The strength of the watermark within the decomposition subbands, which occupy an interval on the spatial frequencies, is adjusted according to this sensitivity. Moreover, the watermark embedding process is carried over the subband coefficients that lie on edges where distortions are less noticeable. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency.

Keywords: Image watermarking, wavelet transform, human visual system, contrast sensitivity function.

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2747 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

Abstract:

In this talk, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, Financial returns, predictive distribution, quantile function model.

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2746 The Design of Axisymmetric Ducts for Incompressible Flow with a Parabolic Axial Velocity Inlet Profile

Authors: V.Pavlika

Abstract:

In this paper a numerical algorithm is described for solving the boundary value problem associated with axisymmetric, inviscid, incompressible, rotational (and irrotational) flow in order to obtain duct wall shapes from prescribed wall velocity distributions. The governing equations are formulated in terms of the stream function ψ (x,y)and the function φ (x,y)as independent variables where for irrotational flow φ (x,y)can be recognized as the velocity potential function, for rotational flow φ (x,y)ceases being the velocity potential function but does remain orthogonal to the stream lines. A numerical method based on the finite difference scheme on a uniform mesh is employed. The technique described is capable of tackling the so-called inverse problem where the velocity wall distributions are prescribed from which the duct wall shape is calculated, as well as the direct problem where the velocity distribution on the duct walls are calculated from prescribed duct geometries. The two different cases as outlined in this paper are in fact boundary value problems with Neumann and Dirichlet boundary conditions respectively. Even though both approaches are discussed, only numerical results for the case of the Dirichlet boundary conditions are given. A downstream condition is prescribed such that cylindrical flow, that is flow which is independent of the axial coordinate, exists.

Keywords: Inverse problem, irrotational incompressible flow, Boundary value problem.

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2745 Meta Model Based EA for Complex Optimization

Authors: Maumita Bhattacharya

Abstract:

Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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2744 Experimental Analysis of Mechanical Behavior under the Effect of Temperature Frequency

Authors: A. Nedjar, S. Aguib, M. Meloussi, T. Djedid, A. Khebli, R. Harhout, L. Kobzili, N. Chikh, M. Tourab

Abstract:

Finding the mechanical properties of magnetorheological elastomers (MREs) is fundamental to create smart materials and devices with desired properties and functionalities. The MREs properties, in shear mode, have been extensively investigated, but these have been less exploited with frequency-temperature dependence. In this article, we studied the performance of MREs with frequency-temperature dependence. The elastic modulus, loss modulus and loss factor of MREs were studied under different temperature values; different values of the magnetic field and different values of the frequency. The results found showed the interest of these active materials in different industrial sectors.

Keywords: Magnetorheological elastomer, mechanical behavior, frequency, temperature.

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2743 Experimental Study on Smart Anchor Head

Authors: Young-Jun You, Ki-Tae Park, Kyu-Wan Lee

Abstract:

Since prestressed concrete members rely on the tensile strength of the prestressing strands to resist loads, loss of even few them could result catastrophic. Therefore, it is important to measure present residual prestress force. Although there are some techniques for obtaining present prestress force, some problems still remain. One method is to install load cell in front of anchor head but this may increase cost. Load cell is a transducer using the elastic material property. Anchor head is also an elastic material and this might result in monitoring monitor present prestress force. Features of fiber optic sensor such as small size, great sensitivity, high durability can assign sensing function to anchor head. This paper presents the concept of smart anchor head which acts as load cell and experiment for the applicability of it. Test results showed the smart anchor head worked good and strong linear relationship between load and response.

Keywords: SHM, prestress force, anchor head, fiber optic sensor

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2742 Intervention Targeting in Environmental Networks

Authors: Chukwudi Henry Dike

Abstract:

We explore targeted subsidy in a set-up for which manufacturing firms in a waste-spillover network make endogenous production decisions. Here, games of substitution in digraphs arises where waste-producing firms internalise negative externality in a quadratic fashion. We find neutrality in intervention policies that create or reduce spillover links. Most importantly, we observe centrality distinction in asymmetric digraphs so that the dependence and power of each firm play unique roles. Here we see that in targeted subsidy, a firm with greater centrality guarantees optimal welfare improvement. This centrality however measures the weakness of each firm’s Nash-based link to other neighbourhood firms i.e., lower negative externality.

Keywords: Centrality, externality, key-player, Nash-Equilibrium.

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2741 Multi-Hazard Risk Assessment and Management in Tourism Industry- A Case Study from the Island of Taiwan

Authors: Chung-Hung Tsai

Abstract:

Global environmental changes lead to increased frequency and scale of natural disaster, Taiwan is under the influence of global warming and extreme weather. Therefore, the vulnerability was increased and variability and complexity of disasters is relatively enhanced. The purpose of this study is to consider the source and magnitude of hazard characteristics on the tourism industry. Using modern risk management concepts, integration of related domestic and international basic research, this goes beyond the Taiwan typhoon disaster risk assessment model and evaluation of loss. This loss evaluation index system considers the impact of extreme weather, in particular heavy rain on the tourism industry in Taiwan. Consider the extreme climate of the compound impact of disaster for the tourism industry; we try to make multi-hazard risk assessment model, strategies and suggestions. Related risk analysis results are expected to provide government department, the tourism industry asset owners, insurance companies and banking include tourist disaster risk necessary information to help its tourism industry for effective natural disaster risk management.

Keywords: Tourism industry, extreme weather, multi-hazard, vulnerability analysis, loss exceeding probability, risk management.

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2740 Selection of Designs in Ordinal Regression Models under Linear Predictor Misspecification

Authors: Ishapathik Das

Abstract:

The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: Model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs.

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2739 A Quantum Algorithm of Constructing Image Histogram

Authors: Yi Zhang, Kai Lu, Ying-hui Gao, Mo Wang

Abstract:

Histogram plays an important statistical role in digital image processing. However, the existing quantum image models are deficient to do this kind of image statistical processing because different gray scales are not distinguishable. In this paper, a novel quantum image representation model is proposed firstly in which the pixels with different gray scales can be distinguished and operated simultaneously. Based on the new model, a fast quantum algorithm of constructing histogram for quantum image is designed. Performance comparison reveals that the new quantum algorithm could achieve an approximately quadratic speedup than the classical counterpart. The proposed quantum model and algorithm have significant meanings for the future researches of quantum image processing.

Keywords: Quantum Image Representation, Quantum Algorithm, Image Histogram.

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2738 Optimisation of a Dragonfly-Inspired Flapping Wing-Actuation System

Authors: Jia-Ming Kok, Javaan Chahl

Abstract:

An optimisation method using both global and local optimisation is implemented to determine the flapping profile which will produce the most lift for an experimental wing-actuation system. The optimisation method is tested using a numerical quasi-steady analysis. Results of an optimised flapping profile show a 20% increase in lift generated as compared to flapping profiles obtained by high speed cinematography of a Sympetrum frequens dragonfly. Initial optimisation procedures showed 3166 objective function evaluations. The global optimisation parameters - initial sample size and stage one sample size, were altered to reduce the number of function evaluations. Altering the stage one sample size had no significant effect. It was found that reducing the initial sample size to 400 would allow a reduction in computational effort to approximately 1500 function evaluations without compromising the global solvers ability to locate potential minima. To further reduce the optimisation effort required, we increase the local solver’s convergence tolerance criterion. An increase in the tolerance from 0.02N to 0.05N decreased the number of function evaluations by another 20%. However, this potentially reduces the maximum obtainable lift by up to 0.025N.

Keywords: Flapping wing, Optimisation, Quasi-steady model.

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2737 Epistemological Functions of Emotions and Their Relevance to the Formation of Citizens and Scientists

Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

Abstract:

Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional mechanisms. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the so-called content-bearing function: it argues that emotions provide the material reasoning that is subsequently transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. This paper argues that science education must start from the presence of certain emotions in the learner if we want to form citizens with a scientific or cultural future.

Keywords: Epistemic emotions, science education, formation of citizens and scientists, epistemic functions of emotions.

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2736 A Note on Negative Hypergeometric Distribution and Its Approximation

Authors: S. B. Mansuri

Abstract:

In this paper, at first we explain about negative hypergeometric distribution and its properties. Then we use the w-function and the Stein identity to give a result on the poisson approximation to the negative hypergeometric distribution in terms of the total variation distance between the negative hypergeometric and poisson distributions and its upper bound.

Keywords: Negative hypergeometric distribution, Poisson distribution, Poisson approximation, Stein-Chen identity, w-function.

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2735 Reflection Performance of Truncated Pyramidal and Truncated Wedge Microwave Absorber Using Sugarcane Bagasse (SCB)

Authors: Liyana Zahid, Mohd Fareq Abd Malek, Ee Meng Cheng, Wei Wen Liu, Yeng Seng Lee, Muhammad Nadeem Iqbal, Fwen Hoon Wee, Farrah Salwani Abdullah

Abstract:

One of the parameters that affect the performance of microwave absorbers is the shape of the absorbers. This paper shows the performance (reflection loss) of truncated pyramidal and truncated wedge microwave absorbers in the range frequency between 8.2 to 12.4 GHz (X-Band) in simulation. The material used is sugarcane bagasse (SCB) which is one of the new materials that used to fabricate the microwave absorber. The complex permittivity was measured using Agilent dielectric probe technique. The designs were simulated using CST Microwave Studio Software. The reflection losses between these two shapes were compared.

Keywords: Microwave Absorber, Reflection Loss, Sugarcane Bagasse (SCB), X- Band.

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