Search results for: Gaussian Mixture Model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7919

Search results for: Gaussian Mixture Model

4169 Numerical Simulation of Liquid Nitrogen Spray Equipment for Space Environmental Simulation Facility

Authors: He Chao, Zhang Lei, Liu Ran, Li Ang

Abstract:

Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keeps the shrouds in the temperature range from -150°C to +150°C. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.

Keywords: Space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent.

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4168 Numerical Simulation of Investment Casting of Gold Jewelry: Experiments and Validations

Authors: Marco Actis Grande, Somlak Wannarumon

Abstract:

This paper proposes the numerical simulation of the investment casting of gold jewelry. It aims to study the behavior of fluid flow during mould filling and solidification and to optimize the process parameters, which lead to predict and control casting defects such as gas porosity and shrinkage porosity. A finite difference method, computer simulation software FLOW-3D was used to simulate the jewelry casting process. The simplified model was designed for both numerical simulation and real casting production. A set of sensor acquisitions were allocated on the different positions of the wax tree of the model to detect filling times, while a set of thermocouples were allocated to detect the temperature during casting and cooling. Those detected data were applied to validate the results of the numerical simulation to the results of the real casting. The resulting comparisons signify that the numerical simulation can be used as an effective tool in investment-casting-process optimization and casting-defect prediction.

Keywords: Computer fluid dynamic, Investment casting, Jewelry, Mould filling, Simulation.

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4167 Grating Scale Thermal Expansion Error Compensation for Large Machine Tools Based on Multiple Temperature Detection

Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

Abstract:

To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detection is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15μm/10m and the accuracy of the machine tool is significant improved.

Keywords: Thermal expansion error of grating scale, error compensation, machine tools, integral method.

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4166 A Method of Effective Planning and Control of Industrial Facility Energy Consumption

Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

Abstract:

A method of effective planning and control of industrial facility energy consumption is offered. The method allows optimally arranging the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: Energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics.

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4165 The Magnetized Quantum Breathing in Cylindrical Dusty Plasma

Authors: A. Abdikian

Abstract:

A quantum breathing mode has been theatrically studied in quantum dusty plasma. By using linear quantum hydrodynamic model, not only the quantum dispersion relation of rotation mode but also void structure has been derived in the presence of an external magnetic field. Although the phase velocity of the magnetized quantum breathing mode is greater than that of unmagnetized quantum breathing mode, attenuation of the magnetized quantum breathing mode along radial distance seems to be slower than that of unmagnetized quantum breathing mode. Clearly, drawing the quantum breathing mode in the presence and absence of a magnetic field, we found that the magnetic field alters the distribution of dust particles and changes the radial and azimuthal velocities around the axis. Because the magnetic field rotates the dust particles and collects them, it could compensate the void structure.

Keywords: The linear quantum hydrodynamic model, the magnetized quantum breathing mode, the quantum dispersion relation of rotation mode, void structure.

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4164 Effect of Different Diesel Fuels on Formation of the Cavitation Phenomena

Authors: Mohammadreza Nezamirad, Sepideh Amirahmadian, Nasim Sabetpour, Azadeh Yazdi, Amirmasoud Hamedi

Abstract:

Cavitation inside a diesel injector nozzle is investigated numerically in this study. The Reynolds Stress Navier Stokes set of equations (RANS) are utilized to investigate flow behavior inside the nozzle numerically. Moreover, K-ε turbulent model is found to be a better approach comparing to K-ω turbulent model. The Winklhofer rectangular shape nozzle is also simulated in order to verify the current numerical scheme, and with the mass flow rate approach, the current solution is verified. Afterward, a six-hole real size nozzle was simulated and it was found that among the different fuels used in this study with the same condition, diesel fuel provides the largest length of cavitation. Also, it was found that at the same boundary condition, rapeseed methyl ester (RME) fuel leads to the highest value of discharge coefficient and mass flow rate.

Keywords: cavitation, diesel fuel, CFD, real size nozzle, discharge coefficient

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4163 Local Linear Model Tree (LOLIMOT) Reconfigurable Parallel Hardware

Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas

Abstract:

Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.

Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.

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4162 A Simplified, Fabrication-Friendly Acoustophoretic Model for Size Sensitive Particle Sorting

Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

Abstract:

In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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4161 A Comparison of Artificial Neural Networks for Prediction of Suspended Sediment Discharge in River- A Case Study in Malaysia

Authors: M.R. Mustafa, M.H. Isa, R.B. Rezaur

Abstract:

Prediction of highly non linear behavior of suspended sediment flow in rivers has prime importance in the field of water resources engineering. In this study the predictive performance of two Artificial Neural Networks (ANNs) namely, the Radial Basis Function (RBF) Network and the Multi Layer Feed Forward (MLFF) Network have been compared. Time series data of daily suspended sediment discharge and water discharge at Pari River was used for training and testing the networks. A number of statistical parameters i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the models. Both the models produced satisfactory results and showed a good agreement between the predicted and observed data. The RBF network model provided slightly better results than the MLFF network model in predicting suspended sediment discharge.

Keywords: ANN, discharge, modeling, prediction, suspendedsediment,

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4160 Gain Tuning Fuzzy Controller for an Optical Disk Drive

Authors: Shiuh-Jer Huang, Ming-Tien Su

Abstract:

Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.

Keywords: Fuzzy control, gain tuning and optical disk drive.

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4159 Speed Sensorless IFOC of PMSM Based On Adaptive Luenberger Observer

Authors: Grouz Faten, Sbita Lassaâd

Abstract:

In this paper, Speed Sensorless Indirect Field Oriented Control (IFOC) of a Permanent Magnet Synchronous machine (PMSM) is studied. The closed loop scheme of the drive system utilizes fuzzy speed and current controllers. Due to the well known drawbacks of the speed sensor, an algorithm is proposed in this paper to eliminate it. In fact, based on the model of the PMSM, the stator currents and rotor speed are estimated simultaneously using adaptive Luenberger observer for currents and MRAS (Model Reference Adaptive System) observer for rotor speed. To overcome the sensivity of this algorithm against parameter variation, adaptive for on line stator resistance tuning is proposed. The validity of the proposed method is verified by an extensive simulation work.

Keywords: PMSM, Indirect Field Oriented Control, fuzzy speed and currents controllers, Adaptive Luenberger observer, MRAS.

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4158 Robust H∞ Filter Design for Uncertain Fuzzy Descriptor Systems: LMI-Based Design

Authors: Wudhichai Assawinchaichote, Sing Kiong Nguang

Abstract:

This paper examines the problem of designing a robust H∞ filter for a class of uncertain fuzzy descriptor systems described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain nonlinear descriptor systems to have an H∞ performance are derived. To alleviate the ill-conditioning resulting from the interaction of slow and fast dynamic modes, solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation ε, when ε is sufficiently small. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard uncertain nonlinear descriptor systems. A numerical example is provided to illustrate the design developed in this paper.

Keywords: H∞ control, Takagi-Sugeno (TS) fuzzy model, Linear Matrix Inequalities (LMIs), Descriptor systems.

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4157 A Study of Islamic Stock Indices and Macroeconomic Variables

Authors: Mohammad Irfan

Abstract:

The purpose of this paper is to investigate the relationship among the key macroeconomic variables and Islamic stock market in India. This study is based on the time series data of financial years 2009-2015 to explore the consistency of relationship between macroeconomic variables and Shariah Indices. The ADF (Augmented Dickey–Fuller Test Statistic) and PP (Phillips–Perron Test Statistic) tests are employed to check stationarity of the data. The study depicts the long run relationship between Shariah indices and macroeconomic variables by using the Johansen Co-integration test. BSE Shariah and Nifty Shariah have uni-direct Granger causality. The outcome of VECM is significantly confirming the applicability of best fitted model. Thus, Islamic stock indices are proficiently working for the development of Indian economy. It suggests that by keeping eyes on Islamic stock market which will be more interactive in the future with other macroeconomic variables.

Keywords: Indian shariah indices, macroeconomic variables, co-integration, Granger causality, Vector error correction model.

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4156 Multidimensional and Data Mining Analysis for Property Investment Risk Analysis

Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

Abstract:

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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4155 Adsorptive Removal of Vapors of Toxic Sulfur Compounds using Activated Carbons

Authors: Meenakshi Goyal, Rashmi Dhawan

Abstract:

Adsorption of CS2 vapors has been studied on different types of activated carbons obtained from different source raw materials. The activated carbons have different surface areas and are associated with varying amounts of the carbon-oxygen surface groups. The adsorption of CS2 vapors is not directly related to surface area, but is considerably influenced by the presence of carbonoxygen surface groups. The adsorption decreases on increasing the amount of carbon-oxygen surface groups on oxidation and increases when these surface groups are eliminated on degassing. The adsorption is maximum in case of the 950°-degassed carbon sample which is almost completely free of any associated oxygen. The kinetic data as analysed by Empirical diffusion model and Linear driving force mass transfer model indicate that the adsorption does not involve Fickian diffusion but may be considered as a pseudo first order mass transfer process. The activation energy of adsorption and isosteric enthalpies of adsorption indicate that the adsorption does not involve interaction between CS2 and carbon-oxygen surface groups, but hydrophobic interactions between CS2 and C-C atoms in the carbon lattice.

Keywords: Adsorption, surface groups, adsorption kinetics, isosteric enthalpy of adsorption.

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4154 Development of a Non-invasive System to Measure the Thickness of the Subcutaneous Adipose Tissue Layer for Human

Authors: Hyuck Ki Hong, Young Chang Jo, Yeon Shik Choi, Beom Joon Kim, Hyo Derk Park

Abstract:

To measure the thickness of the subcutaneous adipose tissue layer, a non-invasive optical measurement system (λ=1300 nm) is introduced. Animal and human subjects are used for the experiments. The results of human subjects are compared with the data of ultrasound device measurements, and a high correlation (r=0.94 for n=11) is observed. There are two modes in the corresponding signals measured by the optical system, which can be explained by two-layered and three-layered tissue models. If the target tissue is thinner than the critical thickness, detected data using diffuse reflectance method follow the three-layered tissue model, so the data increase as the thickness increases. On the other hand, if the target tissue is thicker than the critical thickness, the data follow the two-layered tissue model, so they decrease as the thickness increases.

Keywords: Subcutaneous adipose tissue layer, non-invasive measurement system, two-layered and three-layered tissue models.

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4153 Determination of Water Pollution and Water Quality with Decision Trees

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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4152 Students’ Willingness to Accept Virtual Lecturing Systems: An Empirical Study by Extending the UTAUT Model

Authors: Ahmed Shuhaiber

Abstract:

The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centered, which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence students’ willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed, by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences, and self-efficacy could significantly influence students’ attitudes towards virtual lectures. Additionally, Facilitating conditions and attitudes towards virtual lectures were found with significant influence on students’ intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-Learning, Student willingness, UTAUT, Virtual Lectures, Web-based learning systems.

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4151 Energy Communities from Municipality Level to Province Level: A Comparison Using Autoregressive Integrated Moving Average Model

Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

Abstract:

Considering the energy crisis that is hitting Europe, it becomes increasingly necessary to change energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy, not only to satisfy energy needs and fulfill the required consumption, but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energy communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next 10 years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series.

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4150 Energy Supply, Demand and Environmental Analysis – A Case Study of Indian Energy Scenario

Authors: I.V. Saradhi, G.G. Pandit, V.D. Puranik

Abstract:

Increasing concerns over climate change have limited the liberal usage of available energy technology options. India faces a formidable challenge to meet its energy needs and provide adequate energy of desired quality in various forms to users in sustainable manner at reasonable costs. In this paper, work carried out with an objective to study the role of various energy technology options under different scenarios namely base line scenario, high nuclear scenario, high renewable scenario, low growth and high growth rate scenario. The study has been carried out using Model for Energy Supply Strategy Alternatives and their General Environmental Impacts (MESSAGE) model which evaluates the alternative energy supply strategies with user defined constraints on fuel availability, environmental regulations etc. The projected electricity demand, at the end of study period i.e. 2035 is 500490 MWYr. The model predicted the share of the demand by Thermal: 428170 MWYr, Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr in the base line scenario. Coal remains the dominant fuel for production of electricity during the study period. However, the import dependency of coal increased during the study period. In baseline scenario the cumulative carbon dioxide emissions upto 2035 are about 11,000 million tones of CO2. In the scenario of high nuclear capacity the carbon dioxide emissions reduced by 10 % when nuclear energy share increased to 9 % compared to 3 % in baseline scenario. Similarly aggressive use of renewables reduces 4 % of carbon dioxide emissions.

Keywords: Carbon dioxide, energy, electricity, message.

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4149 Control of Staphylococcus aureus in Meat System by in situ and ex situ Bacteriocins from Lactobacillus sakei and Pediococcus spp.

Authors: M. Naimi, M. B. Khaled

Abstract:

The present study consisted of an applied test in meat system to assess the effectiveness of three bio agents bacteriocinproducing strains: Lm24: Lactobacillus sakei, Lm14and Lm25: Pediococcus spp. Two tests were carried out: The ex situ test was intended for three batches added with crude bacteriocin solutions at 12.48 AU/ml for Lm25 and 8.4 AU/ml for Lm14 and Lm24. However, the in situ one consisted of four batches; three of them inoculated with one bacteriocinogenic Lm25, Lm14, Lm24, respectively. The fourth one was used in mixture: Lm14+m24 at approximately of 107 CFU/ml. The two used tests were done in the presence of the pathogen St. aureus ATCC 6538, as a test strain at 103 CFU/ml. Another batch served as a positive or a negative control was used too. The incubation was performed at 7°C. Total viable counts, staphylococci and lactic acid bacteria, at the beginning and at selected times with interval of three days were enumerated. Physico-chemical determinations (except for in situ test): pH, dry mater, sugars, fat and total protein, at the beginning and at end of the experiment, were done, according to the international norms. Our results confirmed the ex situ effectiveness. Furthermore, the batches affected negatively the total microbial load over the incubation days, and showed a significant regression in staphylococcal load at day seven, for Lm14, Lm24, and Lm25 of 0.73, 2.11, and 2.4 log units. It should be noticed that, at the last day of culture, staphylococcal load was nil for the three batches. In the in situ test, the cultures displayed less inhibitory attitude and recorded a decrease in staphylococcal load, for Lm14, Lm24, Lm25, Lm14+m24 of 0.73, 0.20, 0.86, 0.032 log units. Therefore, physicochemical analysis for Lm14, Lm24, Lm25, Lm14+m24 showed an increase in pH from 5.50 to 5.77, 6.18, 5.96, 7.22, a decrease in dry mater from 7.30% to 7.05%, 6.87%, 6.32%, 6.00%.This result reflects the decrease in fat ranging from 1.53% to 1.49%, 1.07%, 0.99%, 0.87%; and total protein from 6.18% to 5.25%, 5.56%, 5.37%, 5.5%. This study suggests that the use of selected strains as Lm25 could lead to the best results and would help in preserving and extending the shelf life of lamb meat.

Keywords: Biocontrol, in situ and ex situ, meat system, St. aureus, Lactobacillus sakei, Pediococcus spp.

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4148 Bayesian Online Learning of Corresponding Points of Objects with Sequential Monte Carlo

Authors: Miika Toivanen, Jouko Lampinen

Abstract:

This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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4147 A Detection Method of Faults in Railway Pantographs Based on Dynamic Phase Plots

Authors: G. Santamato, M. Solazzi, A. Frisoli

Abstract:

Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: Pantograph models, phase-plots, structural health monitoring, vibration-based condition monitoring.

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4146 Impact Analysis of Transportation Modal Shift on Regional Energy Consumption and Environmental Level: Focused on Electric Automobiles

Authors: Hong Bae Kim, Chang Ho Hur

Abstract:

Many governments have tried to reduce CO2 emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO2 emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO2 emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.

Keywords: Electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model.

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4145 Dynamic Performances of Tubular Linear Induction Motor for Pneumatic Capsule Pipeline System

Authors: Wisuwat Plodpradista

Abstract:

Tubular linear induction motor (TLIM) can be used as a capsule pump in a large pneumatic capsule pipeline (PCP) system. Parametric performance evaluation of the designed 1-meter diameter PCP-TLIM system yields encouraging results for practical implementation. The capsule thrust and speed inside the TLIM pump can be calculated from the combination of the PCP fluid mechanics and the TLIM equations. The TLIM equivalent circuits derived from those of the conventional three-phase induction motor are used as a model to predict the static test results of a small-scale PCP-TLIM system. In this paper, additional dynamic tests are performed on the same small-scale PCP-TLIM system with two capsules of different diameters. The behaviors of the capsule inside the pump are observed and analyzed. The dynamic performances from the dynamic tests are compared with the theoretical predictions based on the TLIM equivalent circuit model.

Keywords: Pneumatic capsule pipeline, Tubular linear induction motor

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4144 IoT Device Cost Effective Storage Architecture and Real-Time Data Analysis/Data Privacy Framework

Authors: Femi Elegbeleye, Seani Rananga

Abstract:

This paper focused on cost effective storage architecture using fog and cloud data storage gateway, and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. Several results obtained from this study on data privacy models show that when two or more data privacy models are integrated via a fog storage gateway, we often have more secure data. Our main focus in the study is to design a framework for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, including its structure, and its interrelationships.

Keywords: IoT, fog storage, cloud storage, data analysis, data privacy.

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4143 A Lagrangian Hamiltonian Computational Method for Hyper-Elastic Structural Dynamics

Authors: Hosein Falahaty, Hitoshi Gotoh, Abbas Khayyer

Abstract:

Performance of a Hamiltonian based particle method in simulation of nonlinear structural dynamics is subjected to investigation in terms of stability and accuracy. The governing equation of motion is derived based on Hamilton's principle of least action, while the deformation gradient is obtained according to Weighted Least Square method. The hyper-elasticity models of Saint Venant-Kirchhoff and a compressible version similar to Mooney- Rivlin are engaged for the calculation of second Piola-Kirchhoff stress tensor, respectively. Stability along with accuracy of numerical model is verified by reproducing critical stress fields in static and dynamic responses. As the results, although performance of Hamiltonian based model is evaluated as being acceptable in dealing with intense extensional stress fields, however kinds of instabilities reveal in the case of violent collision which can be most likely attributed to zero energy singular modes.

Keywords: Hamilton's principle of least action, particle based method, hyper-elasticity, analysis of stability.

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4142 Estimating European Tourism Demand for Malaysia

Authors: Zainudin Arsad, Norul Baine Mat Johor

Abstract:

Tourism industry is an important sector in Malaysia economy and this motivates the examination of long-run relationships between tourist arrivals from three selected European countries in Malaysia and four possible determinants; relative prices, exchange rates, transportation cost and relative prices of substitute destination. The study utilizes data from January 1999 to September 2008 and employs standard econometric techniques that include unit root test and cointegration test. The estimated demand model indicates that depreciation of local currency and increases in prices at substitute destination have positive impact on tourist arrivals while increase in transportation cost has negative impact on tourist arrivals. In addition, the model suggests that higher rate of increase in local prices relative to prices at tourist country of origin may not deter tourists from coming to Malaysia

Keywords: origin country, unit root test, cointegration test

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4141 The Model to Calculate the Cost of Money to the Breakdown of Deposits and Banking Service

Authors: Javad Elkaie Behjati, Mehrzad Minouei

Abstract:

The present study aimed to assess the cost of money based on separating deposits and identifying actions and costs affecting in the process of cost of money in EN Bank of Iran (also known as Eghtesad Novin Bank). The method to calculate the cost of money is based on Activity-Based Costing (ABC). To conduct the study, the required data including deposits in banks and absorbed costs related to the same deposits were extracted from the financial statements of the bank. In order to cost the bank services properly as well as determining the commercial strategies required by commercial units, the data are precisely studied and the cost of each deposit is calculated according to the ABC. Eventually, the factors helping to improve the cost management and also a new model to calculate the cost of money in the bank are presented by some applicable formulas. Furthermore, some offers have been provided for users of both sections, in the practical section in commercial units and the theoretical one in universities.

Keywords: The cost of money, activity-based costing, banking, bank deposits, bank fees, services bank.

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4140 Determining Optimal Production Plan by Revised Surrogate Worth Trade-off Method

Authors: Tunjo Peric, Zoran Babic

Abstract:

The authors of this work indicate by means of a concrete example that it is possible to apply efficaciously the method of multiple criteria programming in dealing with the problem of determining the optimal production plan for a certain period of time. The work presents: (1) the selection of optimization criteria, (2) the setting of the problem of determining an optimal production plan, (3) the setting of the model of multiple criteria programming in finding a solution to a given problem, (4) the revised surrogate trade-off method, (5) generalized multicriteria model for solving production planning problem and problem of choosing technological variants in the metal manufacturing industry. In the final part of this work the authors reflect on the application of the method of multiple criteria programming while determining the optimal production plan in manufacturing enterprises.

Keywords: multi-criteria programming, production planning, technological variant, Surrogate Worth Trade-off Method.

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