Search results for: Maximum Likelihood estimation

Authors: Taiyo Matsumura, Kuninori Takahashi, Takashi Ono

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The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.

Keywords: Exponential smoothing method, open data, operation estimation, train schedule.

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Authors: M. Pourgholi, V.J.Majd

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This paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method.

Keywords: Adaptive observer, linear matrix inequality, nonlinear systems, nonlinear observer, resilient observer, robust estimation.

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

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Let max_ζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: Interconnection network, Augmented cube, Induced subgraph, Bisection width.

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Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: Pose estimation, deep learning, point cloud, bin-picking, 3D computer vision.

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Authors: Ishapathik Das

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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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Authors: Ratanaporn Leesing, Supaporn Kookkhunthod, Ngarmnit Nontaso

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The objective of this work is to produce heterotrophic microalgal lipid in flask-batch fermentation. Chlorella sp. KKU-S2 supported maximum values of 0.374 g/L/d, 0.478 g lipid/g cells, and 0.112 g/L/d for volumetric lipid production rate, and specific yield of lipid, and specific rate of lipid production, respectively when culture was performed on BG-11 medium supplemented with 50g/L glucose. Among the carbon sources tested, maximum cell yield coefficient (YX/S, g/L), maximum specific yield of lipid (YP/X, g lipid/g cells) and volumetric lipid production rate (QP, g/L/d) were found of 0.728, 0.237, and 0.619, respectively, using sugarcane molasses as carbon source. The main components of fatty acid from extracted lipid were palmitic acid, stearic acid, oleic acid and linoleic acid which similar to vegetable oils and suitable for biodiesel production.

Keywords: Microalgal lipid, Chlorella sp. KKU-S2, kineticparameters, biodiesel.

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Authors: Susmita Das, Kala Praveen Bagadi

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SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.

Keywords: Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate

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Authors: Hadi Farhadian, Homayoon Katibeh

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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occured in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: Water Seepage, Amirkabir Tunnel, Analytical Method, DEM, SGR.

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Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

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This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: Analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges.

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Authors: Michela Lecca

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System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a self configuring and highly user-friendly tool.

Keywords: Automatic Object Recognition, Clustering, Contentbased Image Retrieval System, Image Segmentation, Region Adjacency Graph, Region Grouping.

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Authors: Meiling Yang, Shuguo Xie, Yilong Zhu

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Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.

Keywords: Virtual antenna array, DOA, localization, far field.

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Authors: Said Ali Al-Hadhrami

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Ranked set sampling (RSS) was first suggested to increase the efficiency of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this method. When a concomitant variable is available, ratio estimation based on ranked set sampling was proposed. This ratio estimator is more efficient than that based on SRS. In this paper some ratio type estimators of the population mean based on RSS are suggested. These estimators are found to be more efficient than the estimators of similar form using simple random sample.

Keywords: Bias, Efficiency, Ranked Set Sampling, Ratio Type Estimator

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: Co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection.

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Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern

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The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation.

Keywords: speaker adaptation; environment adaptation; robust speech recognition; SVD; non-native speech recognition

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Authors: B. O. Ayinmode, I. P. Farai

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The levels of maximum power density of GSM signals in the cities of Lagos, Ibadan and Abuja were studied. Measurements were made with a calibrated hand held spectrum analyzer 200m away from 271 base stations, at 1.2m to the ground level. The maximum GSM 900 signal power density was 139.63μW/m2 in Lagos, 162.49μW/m2 in Ibadan and 5411.26μW/m2 in Abuja. Also, the maximum GSM 1800 signal power density was 296.82μW/m2 in Lagos, 116.82μW/m2 in Ibadan and 1263.00μW/m2 in Abuja. The level of power density of GSM 900 and GSM 1800 signals in the cities of Lagos, Ibadan and Abuja are far less than the recommended value of 4.5W/m2 for GSM 900 and 9.0 W/m2 for GSM 1800 by the ICNRP guideline. It can be concluded that exposure to GSM signals in these cities cannot contribute to the health detriments caused by thermal effects of radiofrequency radiation.

Keywords: Radiofrequency, power density, radiation exposure, base stations (BTS).

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Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

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The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use Microsoft^TM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: Aircraft aerodynamic model, Microsoft flight simulator, MQ-1 Predator, total least squares estimation, piloting the aircraft.

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Authors: S. A. Naeini, M. Ghorbani Tochaee

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The aim of this study is to assess the influence of plastic fines content on sand-clay mixtures on maximum shear modulus and liquefaction resistance using a series of resonant column tests. A high plasticity clay called bentonite was added to 161 Firoozkooh sand at the percentages of 10, 15, 20, 25, 30 and 35 by dry weight. The resonant column tests were performed on the remolded specimens at constant confining pressure of 100 KPa and then the values of G_max and liquefaction resistance were investigated. The maximum shear modulus and cyclic resistance ratio (CRR) are examined in terms of fines content. Based on the results, the maximum shear modulus and liquefaction resistance tend to decrease within the increment of fine contents.

Keywords: Gmax, liquefaction, plastic fines, resonant column, sand-clay mixtures, bentonite.

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Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: Artificial neural network, low series manufacturing, polymer cutting, setup period estimation.

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Authors: Youssef Khmou, Said Safi

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In this paper, we investigated the effect of real valued transformation of the spectral matrix of the received data for Angles Of Arrival estimation problem.  Indeed, the unitary transformation of Partial Propagator (UPP) for narrowband sources is proposed and applied on Uniform Linear Array (ULA).

Monte Carlo simulations proved the performance of the UPP spectrum comparatively with Forward Backward Partial Propagator (FBPP) and Unitary Propagator (UP). The results demonstrates that when some of the sources are fully correlated and closer than the Rayleigh angular limit resolution of the broadside array, the UPP method outperforms the FBPP in both of spatial resolution and complexity.

Keywords: DOA, Uniform Linear Array, Narrowband, Propagator, Real valued transformation, Subspace, Unitary Operator.

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Authors: Marcus Walter, Norbert Nitzsche, Dirk Odenthal, Steffen M¨uller

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This contribution presents a friction estimator for industrial purposes which identifies Coulomb friction in a steering system. The estimator only needs a few, usually known, steering system parameters. Friction occurs on almost every mechanical system and has a negative influence on high-precision position control. This is demonstrated on a steering angle controller for highly automated driving. In this steering system the friction induces limit cycles which cause oscillating vehicle movement when the vehicle follows a given reference trajectory. When compensating the friction with the introduced estimator, limit cycles can be suppressed. This is demonstrated by measurements in a series vehicle.

Keywords: Friction estimation, friction compensation, steering system, lateral vehicle guidance.

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Authors: Marius Gheju, Rodica Pode

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Hexavalent chromium is highly toxic to most living organisms and a known human carcinogen by the inhalation route of exposure. Therefore, treatment of Cr(VI) contaminated wastewater is essential before their discharge to the natural water bodies. Cr(VI) reduction to Cr(III) can be beneficial because a more mobile and more toxic chromium species is converted to a less mobile and less toxic form. Zero-valence-state metals, such as scrap iron, can serve as electron donors for reducing Cr(VI) to Cr(III). The influence of pH on scrap iron capacity to reduce Cr(VI) was investigated in this study. Maximum reduction capacity of scrap iron was observed at the beginning of the column experiments; the lower the pH, the greater the experiment duration with maximum scrap iron reduction capacity. The experimental results showed that highest maximum reduction capacity of scrap iron was 12.5 mg Cr(VI)/g scrap iron, at pH 2.0, and decreased with increasing pH up to 1.9 mg Cr(VI)/g scrap iron at pH = 7.3.

Keywords: hexavalent chromium, heavy metals, scrap iron, reduction capacity, wastewater treatment.

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Authors: Iqbal Hossain, Monzur Alam Imteaz, Mohammed Iqbal Hossain

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Estimation of stormwater pollutants is a pre-requisite for the protection and improvement of the aquatic environment and for appropriate management options. The usual practice for the stormwater quality prediction is performed through water quality modeling. However, the accuracy of the prediction by the models depends on the proper estimation of model parameters. This paper presents the estimation of model parameters for a catchment water quality model developed for the continuous simulation of stormwater pollutants from a catchment to the catchment outlet. The model is capable of simulating the accumulation and transportation of the stormwater pollutants; suspended solids (SS), total nitrogen (TN) and total phosphorus (TP) from a particular catchment. Rainfall and water quality data were collected for the Hotham Creek Catchment (HTCC), Gold Coast, Australia. Runoff calculations from the developed model were compared with the calculated discharges from the widely used hydrological models, WBNM and DRAINS. Based on the measured water quality data, model water quality parameters were calibrated for the above-mentioned catchment. The calibrated parameters are expected to be helpful for the best management practices (BMPs) of the region. Sensitivity analyses of the estimated parameters were performed to assess the impacts of the model parameters on overall model estimations of runoff water quality.

Keywords: Calibration, Model Parameters, Suspended Solids, TotalNitrogen, Total Phosphorus.

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Authors: S. Phanyaem

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Exponentially weighted moving average control chart (EWMA) is a popular chart used for detecting shift in the mean of parameter of distributions in quality control. The objective of this paper is to compare the efficiency of control chart to detect an increases in the mean of a process. In particular, we compared the Maximum Exponentially Weighted Moving Average (MaxEWMA) and Maximum Generally Weighted Moving Average (MaxGWMA) control charts when the observations are Exponential distribution. The criteria for evaluate the performance of control chart is called, the Average Run Length (ARL). The result of comparison show that in the case of process is small sample size, the MaxEWMA control chart is more efficiency to detect shift in the process mean than MaxGWMA control chart. For the case of large sample size, the MaxEWMA control chart is more sensitive to detect small shift in the process mean than MaxGWMA control chart, and when the process is a large shift in mean, the MaxGWMA control chart is more sensitive to detect mean shift than MaxEWMA control chart.

Keywords: Maximum Exponentially Weighted Moving Average, Maximum General Weighted Moving Average, Average Run Length.

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Authors: Salem Belhaj, Moncef Tagina

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This paper is aimed at describing a delay-based endto- end (e2e) congestion control algorithm, called Very FAST TCP (VFAST), which is an enhanced version of FAST TCP. The main idea behind this enhancement is to smoothly estimate the Round-Trip Time (RTT) based on a nonlinear filter, which eliminates throughput and queue oscillation when RTT fluctuates. In this context, an evaluation of the suggested scheme through simulation is introduced, by comparing our VFAST prototype with FAST in terms of throughput, queue behavior, fairness, stability, RTT and adaptivity to changes in network. The achieved simulation results indicate that the suggested protocol offer better performance than FAST TCP in terms of RTT estimation and throughput.

Keywords: Fast tcp, RTT, delay estimation, delay-based congestion control, high speed TCP, large bandwidth delay product.

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Authors: Z. Masoumi, B. Moaveni

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This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Structural health monitoring, Kalman filter, Least square estimation, structural system identification.

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Authors: Zviad Ghadua, Biswa Bhattacharya

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The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano

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The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.

Keywords: Crack, critical flow, leak, roughness.

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Authors: Sunthari Tharapan, Chockpisit Thepsithar, Kullanart Obsuwan

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This study was aimed to investigate the effect of various organic supplements on growth and development of Dendrobium discolor’s protocorms and seedlings growth of Dendrobium Judy Rutz. Protocorms of Dendrobium discolor with 2.0 cm. in diameter and seedlings of Dendrobium Judy Rutz at the same size (0.5 cm. height) were sub-cultured on Hyponex medium supplemented with cow milk (CM), soy milk (SM), potato extract (PE) and peptone (P) for 2 months. The protocorms were developed to seedlings in all treatments after cultured for 2 months. However, the best results were found on Hyponex medium supplemented with P was the best in which the maximum fresh and dry weight and maximum shoot height were obtained in this treatment statistically different (p ≤ 0.05) to other treatments. Moreover, Hyponex medium supplemented with P also stimulated the maximum mean number of 5.7 shoots per explant which also showed statistically different (p ≤ 0.05) when compared to other treatments. The results of growth of Dendrobium Judy Rutz seedlings indicated the medium supplemented with 100 mL/L PE enhanced the maximum fresh and dry weigh per explants with significantly different (p ≤ 0.05) in fresh weight from other treatments including the control medium without any organic supplementation. However, the dry weight was not significantly different (p ≤ 0.05) from medium supplemented with SM and P. There was multiple shoots induction in all media with or without organic supplementation ranging from 2.6 to 3 shoots per explants. The maximum shoot height was also obtained in the seedlings cultured on medium supplemented with PE while the longest root length was found in medium supplemented with SM.

Keywords: Fresh weight, in vitro propagation, orchid, plant height.

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Authors: Chun-Yao Lee , Yi-Xing Shen , Jung-Cheng Cheng , Chih-Wen Chang, Yi-Yin Li

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This paper proposes the method combining artificial neural network with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. With the measurements of wind speed, rotor speed of wind generator and output power, the artificial neural network can be trained and the wind speed can be estimated. The proposed control system in this paper provides a manner for searching the maximum output power of wind generator even under the conditions of varying wind speed and load impedance.

Keywords: maximum power point tracking, artificial neural network, particle swarm optimization.

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Authors: E. Movahednejad, F. Ommi

Abstract:

Droplet size distributions in the cold spray of a fuel are important in observed combustion behavior. Specification of droplet size and velocity distributions in the immediate downstream of injectors is also essential as boundary conditions for advanced computational fluid dynamics (CFD) and two-phase spray transport calculations. This paper describes the development of a new model to be incorporated into maximum entropy principle (MEP) formalism for prediction of droplet size distribution in droplet formation region. The MEP approach can predict the most likely droplet size and velocity distributions under a set of constraints expressing the available information related to the distribution. In this article, by considering the mechanisms of turbulence generation inside the nozzle and wave growth on jet surface, it is attempted to provide a logical framework coupling the flow inside the nozzle to the resulting atomization process. The purpose of this paper is to describe the formulation of this new model and to incorporate it into the maximum entropy principle (MEP) by coupling sub-models together using source terms of momentum and energy. Comparison between the model prediction and experimental data for a gas turbine swirling nozzle and an annular spray indicate good agreement between model and experiment.

Keywords: Droplet, instability, Size Distribution, Turbulence, Maximum Entropy

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