Search results for: ambient ozone estimate

Authors: G. Zahedi, H. Yaghoobi

Abstract:

Modeling of a heterogeneous industrial fixed bed reactor for selective dehydrogenation of heavy paraffin with Pt-Sn- Al2O3 catalyst has been the subject of current study. By applying mass balance, momentum balance for appropriate element of reactor and using pressure drop, rate and deactivation equations, a detailed model of the reactor has been obtained. Mass balance equations have been written for five different components. In order to estimate reactor production by the passage of time, the reactor model which is a set of partial differential equations, ordinary differential equations and algebraic equations has been solved numerically. Paraffins, olefins, dienes, aromatics and hydrogen mole percent as a function of time and reactor radius have been found by numerical solution of the model. Results of model have been compared with industrial reactor data at different operation times. The comparison successfully confirms validity of proposed model.

Keywords: Dehydrogenation, fixed bed reactor, modeling, linear alkyl benzene.

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Authors: R. Sabre, W. Horrigue, J. C. Simon

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This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: Spectral density, stable processes, aliasing, periodogram.

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

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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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Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

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The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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Authors: P. Meesuk, T. Kulworawanichpong, P. Pao-la-or

Abstract:

This paper proposes a set of quasi-static mathematical model of magnetic fields caused by high voltage conductors of distribution transformer by using a set of second-order partial differential equation. The modification for complex magnetic field analysis and time-harmonic simulation are also utilized. In this research, transformers were study in both balanced and unbalanced loading conditions. Computer-based simulation utilizing the threedimensional finite element method (3-D FEM) is exploited as a tool for visualizing magnetic fields distribution volume a distribution transformer. Finite Element Method (FEM) is one among popular numerical methods that is able to handle problem complexity in various forms. At present, the FEM has been widely applied in most engineering fields. Even for problems of magnetic field distribution, the FEM is able to estimate solutions of Maxwell-s equations governing the power transmission systems. The computer simulation based on the use of the FEM has been developed in MATLAB programming environment.

Keywords: Distribution Transformer, Magnetic Field, Load Unbalance, 3-D Finite Element Method (3-D FEM)

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Authors: B.Singh, B.K.Nanda

Abstract:

Response surface methodology with Box–Benhken (BB) design of experiment approach has been utilized to study the mechanism of interface slip damping in layered and jointed tack welded beams with varying surface roughness. The design utilizes the initial amplitude of excitation, tack length and surface roughness at the interfaces to develop the model for the logarithmic damping decrement of the layered and jointed welded structures. Statistically designed experiments have been performed to estimate the coefficients in the mathematical model, predict the response, and check the adequacy of the model. Comparison of predicted and experimental response values outside the design conditions have shown good correspondence, implying that empirical model derived from response surface approach can be effectively used to describe the mechanism of interface slip damping in layered and jointed tack welded structures.

Keywords: Interface slip damping, welded joint, surface roughness, amplitude, tack length, response surface methodology.

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Authors: D. Vainauska, S. Kozireva, A. Karpovs, M. Chistyakovs, M. Baryshev

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Liposomal magnetofection is a simple, highly efficient technology for cell transfection, demonstrating better outcome than a number of other common gene delivery methods. However, aggregate complexes distribution over the cell surface is non-uniform due to the gradient of the permanent magnetic field. The aim of this study was to estimate the efficiency of liposomal magnetofection for prostate carcinoma PC3 cell line using newly designed device, “DynaFECTOR", ensuring magnetofection in a dynamic gradient magnetic field. Liposomal magnetofection in a dynamic gradient magnetic field demonstrated the highest transfection efficiency for PC3 cells – it increased for 21% in comparison with liposomal magnetofection and for 42% in comparison with lipofection alone. The optimal incubation time under dynamic magnetic field for PC3 cell line was 5 minutes and the optimal rotation frequency of magnets – 5 rpm. The new approach also revealed lower cytotoxic effect to cells than liposomal magnetofection.

Keywords: Dynamic gradient magnetic field, gene delivery, liposomal magnetofection, prostate cancer cell line

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Authors: Xinhua Zhang, Kelin Li

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In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.

Keywords: Exponential stability, stochastic fuzzy cellular neural networks, time-varying delays, impulses, reaction-diffusion terms.

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Authors: Sabah I. Wais, Raghad Y. Mohammed, Sedki O. Yousif

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The influence of axial magnetic field (B=0.48 T) on the variation of ionization efficiency coefficient h and secondary electron emission coefficient g with respect to reduced electric field E/P is studied at a new range of plane-parallel electrode spacing (0< d< 20 cm) and different nitrogen working pressure between 0.5-20 Pa. The axial magnetic field is produced from an inductive copper coil of radius 5.6 cm. The experimental data of breakdown voltage is adopted to estimate the mean Paschen curves at different working features. The secondary electron emission coefficient is calculated from the mean Paschen curve and used to determine the minimum breakdown voltage. A reduction of discharge voltage of about 25% is investigated by the applied of axial magnetic field. At high interelectrode spacing, the effect of axial magnetic field becomes more significant for the obtained values of h but it was less for the values of g.

Keywords: Paschen curve, Townsend coefficient, Secondaryelectron emission, Magnetic field, Minimum breakdown voltage.

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Authors: R. Mahjoub, K. Maghsoudi Mehraban

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In recent years, solid oxide fuel cells have been used as one of the main technologies for the production of electrical energy with high-efficiency ratio, which is used hydrogen and other hydrocarbons as fuels. The fuel cell technology can be used either alone or in hybrid gas turbines systems. In this study, thermodynamics analysis for GT-SOFC hybrid system is developed, and then mass balance and exergy equations have been applied not only on the process but also on the individual components of the hybrid system, which enable us to estimate the thermal efficiency of the hybrid systems. Furthermore, various sources of irreversibility in the solid oxide fuel cell system are discussed, and modeling and parametric analyses like heat and pressure are carried out. This study enables us to consider the irreversible effects of solid oxide fuel cells, and also it leads to the specification of efficiency of the system accurately. Next in the study, both methane and hydrogen as a fuel for SOFC are used and implemented, and finally, our results are compared with other references.

Keywords: hybrid system, gas turbine, entropy and exergy analysis, irreversibility analysis

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Authors: Seyed Hossein Iranmanesh, Mansoureh Zarezadeh

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This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

Keywords: Earned Value Management System (EVMS), Artificial Neural Network (ANN), Estimate At Completion, Forecasting Methods, Project Performance Measurement.

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Authors: N.R.N. Idris

Abstract:

This study uses simulated meta-analysis to assess the effects of publication bias on meta-analysis estimates and to evaluate the efficacy of the trim and fill method in adjusting for these biases. The estimated effect sizes and the standard error were evaluated in terms of the statistical bias and the coverage probability. The results demonstrate that if publication bias is not adjusted it could lead to up to 40% bias in the treatment effect estimates. Utilization of the trim and fill method could reduce the bias in the overall estimate by more than half. The method is optimum in presence of moderate underlying bias but has minimal effects in presence of low and severe publication bias. Additionally, the trim and fill method improves the coverage probability by more than half when subjected to the same level of publication bias as those of the unadjusted data. The method however tends to produce false positive results and will incorrectly adjust the data for publication bias up to 45 % of the time. Nonetheless, the bias introduced into the estimates due to this adjustment is minimal

Keywords: Publication bias, Trim and Fill method, percentage relative bias, coverage probability

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Authors: Dewi Fatmaningrum, Ade Wiradnyani

Abstract:

Optimal feeding, including optimal micronutrient intake, becomes one of the ways to overcome the long-term consequences of undernutrition. Macronutrient and micronutrient intake were important to a rapid growth and development of young children. The study objective was to assess macro and micronutrient intake and its adequacy in children aged 12-23 months. This survey was a cross-sectional study, involving 83 caregivers with children aged 12-23 months old in Senen Sub-district, Central Jakarta selected through simple random sampling. Data on nutrient intake was obtained through interview using single 24-hour recall. Repeated 24- hour recall to sub-sample was done to estimate the proportion of nutrient inadequacy. The highest prevalence of nutrient inadequacy was iron (52.4%), followed by vitamin C (30.9%) and zinc (28.8%). Almost 12% children had inadequate energy intake. More than half of children (62.6%) were anemic (25.3% were severely anemic). Micronutrient inadequacy, especially iron, was more problematic than macronutrient inadequacy in the study area.

Keywords: Micronutrient, macronutrient, children under five, urban setting.

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Authors: Ali A. Ahmed, Mohammed I. Hussein

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The amounts of radioactivity in the igneous rocks have been investigated; samples were collected from the total of eight basalt rock types in the northeastern of Kurdistan region/Iraq. The activity concentration of 226Ra (238U) series, 228Ac (232Th) series, 40K and 137Cs were measured using Planar HPGe and NaI(Tl) detectors. Along the study area the radium equivalent activities Raeq in Bq/Kg of samples under investigation were found in the range of 22.16 to 77.31 Bq/Kg with an average value of 44.8 Bq/Kg, this value is much below the internationally accepted value of 370 Bq/Kg. To estimate the health effects of this natural radioactive composition, the average values of absorbed gamma dose rate D (55 nGyh-1), Indoor and outdoor annual effective dose rates Eied (0.11 mSvy-1) . and Eoed (0.03 mSvy-1), External hazard index Hex (0.138) and internal hazard index Hin(0.154), and representative level index Iγr (0.386) have been calculated and found to be lower than the worldwide average values.

Keywords: Absorbed dose, activity concentration, igneousrocks, HPGe, NaI(TI), Natural Radioactivity.

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Authors: Tao Dai, Andy Adler, Behnam Shahrrava

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This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Keywords: Adaptive signal processing, affine projection algorithms, variable step-size adaptive algorithms, regularization.

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Authors: K. Khlifi, A. Haddouk, M. Hlaili, H. Mechergui

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The present paper provides a detailed analysis of prior methods and approaches for non-linear load identification in residential buildings. The main goal of this analysis is to decipher the distorted signals and to estimate the harmonics influence on power systems. We have performed an analytical study of non-linear loads behavior in the residential environment. Simulations have been performed in order to evaluate the distorted rate of the current and follow his behavior. To complete this work, an instrumental platform has been realized to carry out practical tests on single-phase non-linear loads which illustrate the current consumption of some domestic appliances supplied with single-phase sinusoidal voltage. These non-linear loads have been processed and tracked in order to limit their influence on the power grid and to reduce the Joule effect losses. As a result, the study has allowed to identify responsible circuits of harmonic pollution.

Keywords: Distortion rate, harmonic analysis, harmonic pollution, non-linear load, power factor.

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Authors: W. S. Hsu, Y. Chiang, Y. S. Tseng, J. R. Wang, C. Shih, S. W. Chen

Abstract:

Kuosheng nuclear power plant (NPP) is a BWR/6 plant in Taiwan. There is more concern for the safety of NPPs in Taiwan after Japan Fukushima NPP disaster occurred. Hence, in order to estimate the safety of Kuosheng NPP spent fuel pool (SFP), by using TRACE, MELCOR, and SNAP codes, the safety analysis of Kuosheng NPP SFP was performed. There were two main steps in this research. First, the Kuosheng NPP SFP models were established. Second, the transient analysis of Kuosheng SFP was done by TRACE and MELCOR under the cooling system failure condition (Fukushima-like condition). The results showed that the calculations of MELCOR and TRACE were very similar in this case, and the fuel uncover happened roughly at 4^th day after the failure of cooling system. The above results indicated that Kuosheng NPP SFP may be unsafe in the case of long-term SBO situation. In addition, future calculations were needed to be done by the other codes like FRAPTRAN for the cladding calculations.

Keywords: TRACE, MELCOR, SNAP, spent fuel pool.

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Authors: M. Malek Yarand, H. Saebi Monfared

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This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: Mechanical Force Gauge, Mold, Reshaped Fruit, Square Watermelon.

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Authors: Zain M. Al-Houri, Oday K. Abu-Hadba, Khaled A. Hamdan

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Roof top rainwater harvesting (RWH) has been carried out worldwide to provide an inexpensive source of water for many people. This research aims at evaluating the potential of roof top rain water harvesting as a resource in Jordan. For the purpose of this work, two case studies at Al-Jubiha and Shafa-Badran districts in Amman city were selected. All existing rooftops in both districts were identified by digitizing 2012 satellite images of the two districts using Google earth and ArcGIS tools. Rational method was used to estimate the potential volume of rainwater that can be harvested from the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr can be harvested in Al-Jubiha and Shafa-Badran districts, respectively. This study should increase the attention to the importance of implementing RWH technique in Jordanian residences as a viable alternative for ensuring a continued source of non-potable water.

Keywords: Amman districts, ArcGIS, Rational method, Roof top rain water harvesting.

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Authors: Tijani Delleji, Mourad Zribi, Ahmed Ben Hamida

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This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Keywords: Satellite image fusion, Bayesian segmentation, Bootstrap approach, EM algorithm.

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Authors: Mahesh Chudasama, Harit Raval

Abstract:

Conical sections and shells made from metal plates are widely used in various industrial applications. 3-roller conical bending process is preferably used to produce such conical sections and shells. Bending mechanics involved in the process is complex and little work is done in this area. In the present paper an analytical model is developed to predict bending force which will be acting during 3-roller conical bending process. To verify the developed model, conical bending experiments are performed. Analytical results and experimental results were compared. Force predicted by analytical model is in close proximity of the experimental results. The error in the prediction is ±10%. Hence the model gives quite satisfactory results. Present model is also compared with the previously published bending force prediction model and it is found that the present model gives better results. The developed model can be used to estimate the bending force during 3-roller bending process and can be useful to the designers for designing the 3-roller conical bending machine.

Keywords: Bending-force, Experimental-verification, Internal-moment, Roll-bending.

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.

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Authors: Mei-Hsiu Chi, Jyh-Yang Wu, Sheng-Gwo Chen

Abstract:

The diffusion-reaction equations are important Partial Differential Equations in mathematical biology, material science, physics, and so on. However, finding efficient numerical methods for diffusion-reaction systems on curved surfaces is still an important and difficult problem. The purpose of this paper is to present a convergent geometric method for solving the reaction-diffusion equations on closed surfaces by an O(r)-LTL configuration method. The O(r)-LTL configuration method combining the local tangential lifting technique and configuration equations is an effective method to estimate differential quantities on curved surfaces. Since estimating the Laplace-Beltrami operator is an important task for solving the reaction-diffusion equations on surfaces, we use the local tangential lifting method and a generalized finite difference method to approximate the Laplace-Beltrami operators and we solve this reaction-diffusion system on closed surfaces. Our method is not only conceptually simple, but also easy to implement.

Keywords: Close surfaces, high-order approach, numerical solutions, reaction-diffusion systems.

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Authors: Hsiang-Wen Hsieh, Chin-Chia Wu, Hung-Hsiu Yu, Shu-Fan Liu

Abstract:

Localization is one of the critical issues in the field of robot navigation. With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, a hybrid Distributed Vision System (DVS) for robot localization is presented. The presented approach integrates odometry data from robot and images captured from overhead cameras installed in the environment to help reduce possibilities of fail localization due to effects of illumination, encoder accumulated errors, and low quality range data. An odometry-based motion model is applied to predict robot poses, and robot images captured by overhead cameras are then used to update pose estimates with HSV histogram-based measurement model. Experiment results show the presented approach could localize robots in a global world coordinate system with localization errors within 100mm.

Keywords: Distributed Vision System, Localization, Measurement model, Motion model

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Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho

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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.

Keywords: Ganoderma, oil palm, regression model, yield loss, economic loss.

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Authors: C. Kwan, X. Li, D. Lao, Y. Deng, Z. Ren, B. Raj, R. Singh, R. Stern

Abstract:

Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.

Keywords: Non-stationary, speech recognition, voice commands.

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Authors: Nour Aljafari, Mariam, S. Maani, Serter Atabay, Tarig Ali, Said Daker, Lara Daher, Hamad Bukhammas, Mohammed Abou Shakra

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This paper aims at determining the soil characteristics that influence the irrigation process of green landscapes and deciding on the optimum amount of water needed for irrigation. The laboratory experiments were conducted using the constant head methodology to determine the soil infiltration rates. The steady state infiltration rate was reached after 10 minutes of infiltration at a rate of 200 mm/hr. The effects of different water heads on infiltration rates were also investigated, and the head of 11 cm was found to be the optimum head for the test. The experimental results showed consistent infiltration results for the range between 11 cm and 15 cm. The study also involved finding the initial moisture content, which ranged between 5% and 25%, and finding the organic content, which occupied 1% to 2% of the soil. These results will be later utilized, using the water balance approach, to estimate the optimum amount of water needed for irrigation for changing weather conditions.

Keywords: Infiltration rate, moisture content, grass type, organic content.

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Authors: Bin Su

Abstract:

The draft Auckland Unitary Plan outlines the future land used for new housing and businesses with Auckland population growth over the next thirty years. According to Auckland Unitary Plan, over the next 30 years, the population of Auckland is projected to increase by one million, and up to 70% of total new dwellings occur within the existing urban area. Intensification will not only increase the number of median or higher density houses such as terrace house, apartment building, etc. within the existing urban area but also change mean housing design data that can impact building thermal performance under the local climate. Based on mean energy consumption and building design data, and their relationships of a number of Auckland sample houses, this study is to estimate the future mean housing energy consumption associated with the change of mean housing design data and evaluate housing energy efficiency with the Auckland Unitary Plan.

Keywords: Auckland Unitary Plan, Building thermal design, Housing design, Housing energy efficiency.

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Authors: Y. T. Tsai, Jin H. Huang

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The sound pressure level (SPL) of the moving-coil loudspeaker (MCL) is often simulated and analyzed using the lumped parameter model. However, the SPL of a MCL cannot be simulated precisely in the high frequency region, because the value of cone effective area is changed due to the geometry variation in different mode shapes, it is also related to affect the acoustic radiation mass and resistance. Herein, the paper presents the inverse method which has a high ability to measure the value of cone effective area in various frequency points, also can estimate the MCL electroacoustic parameters simultaneously. The proposed inverse method comprises the direct problem, adjoint problem, and sensitivity problem in collaboration with nonlinear conjugate gradient method. Estimated values from the inverse method are validated experimentally which compared with the measured SPL curve result. Results presented in this paper not only improve the accuracy of lumped parameter model but also provide the valuable information on loudspeaker cone design.

Keywords: Inverse problem, cone effective area, loudspeaker, nonlinear conjugate gradient method.

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Authors: M. Seifi, S. Fallah, M. Firoozrai

Abstract:

Matrix metalloproteinase-3 (MMP3) is key member of the MMP family, and is known to be present in coronary atherosclerotic. Several studies have demonstrated that MMP-3 5A/6A polymorphism modify each transcriptional activity in allele specific manner. We hypothesized that this polymorphism may play a role as risk factor for development of coronary stenosis. The aim of our study was to estimate MMP-3 (5A/6A) gene polymorphism on interindividual variability in risk for coronary stenosis in an Iranian population.DNA was extracted from white blood cells and genotypes were obtained from coronary stenosis cases (n=95) and controls (n=100) by PCR (polymerase chain reaction) and restriction fragment length polymorphism techniques. Significant differences between cases and controls were observed for MMP3 genotype frequencies (X2=199.305, p< 0.001); the 6A allele was less frequently seen in the control group, compared to the disease group (85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data imply the involvement of -1612 5A/6A polymorphism in coronary stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a genetic susceptibility factor for coronary stenosis.

Keywords: Coronary artery stenosis, matrixmetalloproteinase-3, polymorphism, polymerase chain reaction.

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