Search results for: interval estimation.

Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: Cascaded neural network, internal temperature, three-phase induction motor, inverter.

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.

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Authors: Md. Emaj Uddin

Abstract:

Age at first marriage is a basic temporal term that is culturally constructed for marriage relationship between an adult male and an adult female intended to have sex, to reproduce and to adapt to environment from one generation to another around the world. Cross-cultural evidences suggest that age at first marriage for both male and female not only varies across the cultures, but also varies among the subcultures of the same society. The purpose of the study was to compare age at first marriage for husband and wife including age differences between them between Muslim and Santal communities in rural Bangladesh. For this we hypothesized that (1) there were significant differences in age at first marriage and age interval between husband and wife between Muslim and Santal communities in rural Bangladesh. In so doing, 288 couples (145 pairs of couples for Muslim and 143 pairs of couples for Santal) were selected by cluster random sampling from the Kalna village situated in the Tanore Upazila of Rajshahi district, Bangladesh, whose current mean age range was 36.59 years for husband and 28.85 years for wife for the Muslim and 31.74 years for husband and 25.21 years for wife for the Santal respectively. The results of Independent Sample t test showed that mean age at first marriage for the Muslim samples was 23.05 years for husbands and 15.11 years for wives, while mean age at first marriage for the Santal samples was 20.71 years for husbands and 14.34 years for wives respectively that were significantly different at p<0.05 level. Although husbands compared to wives in both the communities were relatively older, there were significant similarities in mean age differences (7.71 for Muslim couples and 7.51 for Santal, p>0.05) among the selected husbands and wives between the two communities. This study recommends that further cross-cultural researches should be done on the causeeffect relationships between socio-cultural factors and age at marriage between the two communities in Bangladesh.

Keywords: Age at First Marriage, Age Difference at Marriage, Bangladesh, Cross-Cultural Comparison, Muslim, Santal.

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Authors: Alexander Schulz, Ingrid Rottensteiner, Manfred Neumann, Michael Wehse, Johann Wassermann

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Self-sensing estimates the air gap within an electro magnetic path by analyzing the bearing coil current and/or voltage waveform. The self-sensing concept presented in this paper has been developed within the research project “Active Magnetic Bearings with Supreme Reliability" and is used for position sensor fault detection. Within this new concept gap calculation is carried out by an alldigital analysis of the digitized coil current and voltage waveform. For analysis those time periods within the PWM period are used, which give the best results. Additionally, the concept allows the digital compensation of nonlinearities, for example magnetic saturation, without degrading signal quality. This increases the accuracy and robustness of the air gap estimation and additionally reduces phase delays. Beneath an overview about the developed concept first measurement results are presented which show the potential of this all-digital self-sensing concept.

Keywords: digital signal analysis, active magnetic bearing, reliability, fault detection.

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Authors: M. Debyeche, J.P Haton, A. Houacine

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The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.

Keywords: Hidden Markov Model, Vector Quantization, Neural Network, Speech Recognition, Arabic Language

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Authors: Kaige Shi, Chao Jiang, Xin Li

Abstract:

The swirl gripper is an electrically activated noncontact handling device that uses swirling airflow to generate a lifting force. This force can be used to pick up a workpiece placed underneath the swirl gripper without any contact. It is applicable, for example, in the semiconductor wafer production line, where contact must be avoided during the handling and moving of a workpiece to minimize damage. When a workpiece levitates underneath a swirl gripper, the gap height between them is crucial for safe handling. Therefore, in this paper, we propose a method to estimate the levitation gap height by detecting pressure at two points. The method is based on theoretical model of the swirl gripper, and has been experimentally verified. Furthermore, the force between the gripper and the workpiece can also be estimated using the detected pressure. As a result, the nonlinear relationship between the force and gap height can be linearized by adjusting the rotating speed of the fan in the swirl gripper according to the estimated force and gap height. The linearized relationship is expected to enhance handling stability of the workpiece.

Keywords: Swirl gripper, noncontact handling, levitation, gap height estimation.

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Authors: Ioan Popa, Radu Lupu, Cristiana Tudor

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In this paper, we apply the FM methodology to the cross-section of Romanian-listed common stocks and investigate the explanatory power of market beta on the cross-section of commons stock returns from Bucharest Stock Exchange. Various assumptions are empirically tested, such us linearity, market efficiency, the “no systematic effect of non-beta risk" hypothesis or the positive expected risk-return trade-off hypothesis. We find that the Romanian stock market shows the same properties as the other emerging markets in terms of efficiency and significance of the linear riskreturn models. Our analysis included weekly returns from January 2002 until May 2010 and the portfolio formation, estimation and testing was performed in a rolling manner using 51 observations (one year) for each stage of the analysis.

Keywords: Bucharest Stock Exchange, Fama-Macbeth methodology, systematic risk, non-linear risk-return dependence.

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Authors: Panudet Saengseedam, Nanthachai Kantanantha

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This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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Authors: Marios M. Hadjiandreou, Raul Conejeros, Ian Wilson

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This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.

Keywords: AIDS, chemotherapy, mathematical modeling, optimal control, progression.

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Authors: Alexey V. Klyuev, Arkady V. Yakimov, Mikhail I. Ryzhkin, Andrey V. Klyuev

Abstract:

Fluctuations of Schottky diode parameters in a structure of the mixer are investigated. These fluctuations are manifested in two ways. At the first, they lead to fluctuations in the transfer factor that is lead to the amplitude fluctuations in the signal of intermediate frequency. On the basis of the measurement data of 1/f noise of the diode at forward current, the estimation of a spectrum of relative fluctuations in transfer factor of the mixer is executed. Current dependence of the spectrum of relative fluctuations in transfer factor of the mixer and dependence of the spectrum of relative fluctuations in transfer factor of the mixer on the amplitude of the heterodyne signal are investigated. At the second, fluctuations in parameters of the diode lead to occurrence of 1/f noise in the output signal of the mixer. This noise limits the sensitivity of the mixer to the value of received signal.

Keywords: Current-voltage characteristic, fluctuations, mixer, Schottky diode, 1/f noise.

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Authors: Sangeeta Singh, Pankaj Kumar, P. N. Kondekar

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In this paper, the transient device performance analysis of n-type Gate Inside JunctionLess Transistor (GI-JLT) has been evaluated. 3-D Bohm Quantum Potential (BQP) transport device simulation has been used to evaluate the delay and power dissipation performance. GI-JLT has a number of desirable device parameters such as reduced propagation delay, dynamic power dissipation, power and delay product, intrinsic gate delay and energy delay product as compared to Gate-all-around transistors GAA-JLT. In addition to this, various other device performance parameters namely, on/off current ratio, short channel effects (SCE), transconductance Generation Factor (TGF) and unity gain cut-off frequency (fT ) and subthreshold slope (SS) of the GI-JLT and GAA-JLT have been analyzed and compared. GI-JLT shows better device performance characteristics than GAA-JLT for low power and high frequency applications, because of its larger gate electrostatic control on the device operation.

Keywords: Gate-inside junctionless transistor GI-JLT, Gate-all-around junctionless transistor GAA-JLT, propagation delay, power delay product.

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Authors: A. Alirezaei, S. Vahdani

Abstract:

This study estimates the seismic demands of tall buildings with central symmetric setbacks by using nonlinear time history analysis. Three setback structures, all 60-story high with setback in three levels, are used for evaluation. The effects of irregularities occurred by setback are evaluated by determination of global-drift, story-displacement and story drift. Story-displacement is modified by roof displacement and first story displacement and story drift is modified by global drift. All results are calculated at the center of mass and in x and y direction. Also the absolute values of these quantities are determined. The results show that increasing of vertical irregularities increases the global drift of the structure and enlarges the deformations in the height of the structure. It is also observed that the effects of geometry irregularity in the seismic deformations of setback structures are higher than those of mass irregularity.

Keywords: Deformation demand, drift, setback, tall building.

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

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Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: Remote sensing and GIS, permanent residence, decision tree, Lebanon.

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Authors: Chengli Liu, C. K. M. Lee

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The tradition competitive newsvendor game assumes decision makers are rational. However, there are behavioral biases when people make decisions, such as loss aversion, mental accounting and overconfidence. Overestimation of a subject’s own performance is one type of overconfidence. The objective of this research is to analyze the impact of the overestimated demand in the newsvendor competitive game with two players. This study builds a competitive newsvendor game model where newsvendors have private information of their demands, which is overestimated. At the same time, demands of each newsvendor forecasted by a third party institution are available. This research shows that the overestimation leads to demand steal effect, which reduces the competitor’s order quantity. However, the overall supply of the product increases due to overestimation. This study illustrates the boundary condition for the overestimated newsvendor to have the equilibrium order drop due to the demand steal effect from the other newsvendor. A newsvendor who has higher critical fractile will see its equilibrium order decrease with the drop of estimation level from the other newsvendor.

Keywords: Bias, competitive newsvendor, Nash equilibrium, overestimation.

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Authors: Asep Bayu Dani Nandiyanto, Asep Suhendi, Yutaka Kisakibaru, Takashi Ogi, Kikuo Okuyama

Abstract:

An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.

Keywords: Porous structure film; ATO particle; Ultra-low refractive index; vertical drop method; Low-density material;

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Authors: Naci Büyükkaracığan

Abstract:

Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, Minimum flows, probability distribution.

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Authors: Cornelia-Eugenia Munteanu

Abstract:

The goal of this paper is to present the diagnostic contribution that the screening instrument, Mini-Mental State Examination-2: Expanded Version (MMSE-2:EV), brings in detecting the cognitive impairment or in monitoring the progress of degenerative disorders. The diagnostic signification is underlined by the interpretation of the MMSE-2:EV scores, resulted from the test application to patients with mild and major neurocognitive disorders. The cases were selected from current practice, in order to cover vast and significant neurocognitive pathology: mild cognitive impairment, Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s disease, conversion of the mild cognitive impairment into Alzheimer’s disease. The MMSE-2:EV version was used: it was applied one month after the initial assessment, three months after the first reevaluation and then every six months, alternating the blue and red forms. Correlated with age and educational level, the raw scores were converted in T scores and then, with the mean and the standard deviation, the z scores were calculated. The differences of raw scores between the evaluations were analyzed from the point of view of statistic signification, in order to establish the progression in time of the disease. The results indicated that the psycho-diagnostic approach for the evaluation of the cognitive impairment with MMSE-2:EV is safe and the application interval is optimal. In clinical settings with a large flux of patients, the application of the MMSE-2:EV is a safe and fast psychodiagnostic solution. The clinicians can draw objective decisions and for the patients: it does not take too much time and energy, it does not bother them and it doesn’t force them to travel frequently.

Keywords: MMSE-2, dementia, cognitive impairment, neuropsychology.

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Authors: A. R. Salimi, M. Esmaeili, B. Salehi

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The development and extension of large cities induced a need for shallow tunnel in soft ground of building areas. Estimation of ground settlement caused by the tunnel excavation is important engineering point. In this paper, prediction of surface subsidence caused by tunneling in one section of seventh line of Tehran subway is considered. On the basis of studied geotechnical conditions of the region, tunnel with the length of 26.9km has been excavated applying a mechanized method using an EPB-TBM with a diameter of 9.14m. In this regard, settlement is estimated utilizing both analytical and numerical finite element method. The numerical method shows that the value of settlement in this section is 5cm. Besides, the analytical consequences (Bobet and Loganathan-Polous) are 5.29 and 12.36cm, respectively. According to results of this study, due tosaturation of this section, there are good agreement between Bobet and numerical methods. Therefore, tunneling processes in this section needs a special consolidation measurement and support system before the passage of tunnel boring machine.

Keywords: TBM, Subsidence, Numerical Method, Analytical Method.

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Authors: Kenji Suyama, Masahiro Oshida, Noboru Owada

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In this paper, an estimation accuracy of multiple moving talker tracking using a microphone array is improved. The tracking can be achieved by the adaptive method in which two algorithms are integrated, namely, the PAST (Projection Approximation Subspace Tracking) algorithm and the IPLS (Interior Point Least Square) algorithm. When either talker begins to speak again after a silent period, an appropriate feasible region for an evaluation function of the IPLS algorithm might not be set. Then, the tracking fails due to the incorrect updating. Therefore, if an increment of the number of active talkers is detected, the feasible region must be reset. Then, a low cost realization is required for the high speed tracking and a high accuracy realization is desired for the precise tracking. In this paper, the directions roughly estimated using the delayed-sum-array method are used for the resetting. Several results of experiments performed in an actual room environment show the effectiveness of the proposed method.

Keywords: moving talkers tracking, microphone array, signal subspace

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Authors: T. C. B. N. Assunção, J. L. Silvino, P. Resende

Abstract:

The winding hot-spot temperature is one of the most critical parameters that affect the useful life of the power transformers. The winding hot-spot temperature can be calculated as function of the top-oil temperature that can estimated by using the ambient temperature and transformer loading measured data. This paper proposes the estimation of the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. The estimated top-oil temperature is compared with measured data of a power transformer in operation. The results are also compared with methods based on the IEEE Standard C57.91-1995/2000 and Artificial Neural Networks. It is shown that the Least Squares Support Vector Machines approach presents better performance than the methods based in the IEEE Standard C57.91-1995/2000 and artificial neural networks.

Keywords: Artificial Neural Networks, Hot-spot Temperature, Least Squares Support Vector, Top-oil Temperature.

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Authors: H. Barati, M. Wu, A. Kharicha, A. Ludwig

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A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Keywords: Clogging, nozzle, numerical model, simulation.

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Authors: Zohreh Sheikh Khozani, Wan Hanna Melini Wan Mohtar, Mojtaba Porhemmat

Abstract:

Prediction of wall shear stress in a rectangular channel, with non-homogeneous roughness distribution, was studied. Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, the Genetic Algorithm Artificial (GAA) neural network is introduced as a hybrid methodology of the Artificial Neural Network (ANN) and modified Genetic Algorithm (GA) combination. This GAA method was employed to predict the wall shear stress. Various input combinations and transfer functions were considered to find the most appropriate GAA model. The results show that the proposed GAA method could predict the wall shear stress of open channels with high accuracy, by Root Mean Square Error (RMSE) of 0.064 in the test dataset. Thus, using GAA provides an accurate and practical simple-to-use equation.

Keywords: Artificial neural network, genetic algorithm, genetic programming, rectangular channel, shear stress.

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Authors: Chatchai Pesee

Abstract:

This paper examines long-range dependence or longmemory of financial time series on the exchange rate data by the fractional Brownian motion (fBm). The principle of spectral density function in Section 2 is used to find the range of Hurst parameter (H) of the fBm. If 0< H <1/2, then it has a short-range dependence (SRD). It simulates long-memory or long-range dependence (LRD) if 1/2< H <1. The curve of exchange rate data is fBm because of the specific appearance of the Hurst parameter (H). Furthermore, some of the definitions of the fBm, long-range dependence and selfsimilarity are reviewed in Section II as well. Our results indicate that there exists a long-memory or a long-range dependence (LRD) for the exchange rate data in section III. Long-range dependence of the exchange rate data and estimation of the Hurst parameter (H) are discussed in Section IV, while a conclusion is discussed in Section V.

Keywords: Fractional Brownian motion, long-rangedependence, memory, short-range dependence.

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Authors: M. D. Kokate, T. R. Sontakke, P. W. Wani

Abstract:

This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.

Keywords: LMMSE, MOE, MUD.

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Authors: A. Benarous, D. Karmed, R. Haoui, A. Liazid

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The process for predicting the ballistic properties of a liquid rocket engine is based on the quantitative estimation of idealized performance deviations. In this aim, an equilibrium chemistry procedure is firstly developed and implemented in a Fortran routine. The thermodynamic formulation allows for the calculation of the theoretical performances of a rocket thrust chamber. In a second step, a computational fluid dynamic analysis of the turbulent reactive flow within the chamber is performed using a finite volume approach. The obtained values for the “quasi-real" performances account for both turbulent mixing and chemistryturbulence coupling. In the present work, emphasis is made on the combustion efficiency performance for which deviation is mainly due to radial gradients of static temperature and mixture ratio. Numerical values of the characteristic velocity are successfully compared with results from an industry-used code. The results are also confronted with the experimental data of a laboratory-scale rocket engine.

Keywords: JANAF methodology, Liquid rocket engine, Mascotte test-rig, Theoretical performances.

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Authors: Laleh Yerushalmi, Fariborz Haghighat, Maziar Bani Shahabadi

Abstract:

The estimation of overall on-site and off-site greenhouse gas (GHG) emissions by wastewater treatment plants revealed that in anaerobic and hybrid treatment systems greater emissions result from off-site processes compared to on-site processes. However, in aerobic treatment systems, onsite processes make a higher contribution to the overall GHG emissions. The total GHG emissions were estimated to be 1.6, 3.3 and 3.8 kg CO2-e/kg BOD in the aerobic, anaerobic and hybrid treatment systems, respectively. In the aerobic treatment system without the recovery and use of the generated biogas, the off-site GHG emissions were 0.65 kg CO2-e/kg BOD, accounting for 40.2% of the overall GHG emissions. This value changed to 2.3 and 2.6 kg CO2-e/kg BOD, and accounted for 69.9% and 68.1% of the overall GHG emissions in the anaerobic and hybrid treatment systems, respectively. The increased off-site GHG emissions in the anaerobic and hybrid treatment systems are mainly due to material usage and energy demand in these systems. The anaerobic digester can contribute up to 100%, 55% and 60% of the overall energy needs of plants in the aerobic, anaerobic and hybrid treatment systems, respectively.

Keywords: On-site and off-site greenhouse gas (GHG)emissions, wastewater treatment plants, biogas recovery

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Authors: Michal Natora, Felix Franke, Klaus Obermayer

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Linear convolutive filters are fast in calculation and in application, and thus, often used for real-time processing of continuous data streams. In the case of transient signals, a filter has not only to detect the presence of a specific waveform, but to estimate its arrival time as well. In this study, a measure is presented which indicates the performance of detectors in achieving both of these tasks simultaneously. Furthermore, a new sub-class of linear filters within the class of filters which minimize the quadratic response is proposed. The proposed filters are more flexible than the existing ones, like the adaptive matched filter or the minimum power distortionless response beamformer, and prove to be superior with respect to that measure in certain settings. Simulations of a real-time scenario confirm the advantage of these filters as well as the usefulness of the performance measure.

Keywords: Adaptive matched filter, minimum variance distortionless response, beam forming, Capon beam former, linear filters, performance measure.

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Authors: Alessandro Bevilacqua, Alessandro Gherardi, Ludovico Carozza, Filippo Piccinini

Abstract:

The last years have seen an increasing use of image analysis techniques in the field of biomedical imaging, in particular in microscopic imaging. The basic step for most of the image analysis techniques relies on a background image free of objects of interest, whether they are cells or histological samples, to perform further analysis, such as segmentation or mosaicing. Commonly, this image consists of an empty field acquired in advance. However, many times achieving an empty field could not be feasible. Or else, this could be different from the background region of the sample really being studied, because of the interaction with the organic matter. At last, it could be expensive, for instance in case of live cell analyses. We propose a non parametric and general purpose approach where the background is built automatically stemming from a sequence of images containing even objects of interest. The amount of area, in each image, free of objects just affects the overall speed to obtain the background. Experiments with different kinds of microscopic images prove the effectiveness of our approach.

Keywords: Microscopy, flat field correction, background estimation, image segmentation.

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.

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Authors: Ajab G. Majidi, Bilal Bingölbali, Adem Akpınar

Abstract:

This study aims to investigate the amount of energy (economic wave energy potential) that can be obtained from the existing wave energy converters in the high wave energy potential region of the Black Sea in terms of wave energy potential and their performance at different depths in the region. The data needed for this purpose were obtained using the calibrated nested layered SWAN wave modeling program version 41.01AB, which was forced with Climate Forecast System Reanalysis (CFSR) winds from 1979 to 2009. The wave dataset at a time interval of 2 hours was accumulated for a sub-grid domain for around Karaburun beach in Arnavutkoy, a district of Istanbul city. The annual sea state characteristic matrices for the five different depths along with a vertical line to the coastline were calculated for 31 years. According to the power matrices of different wave energy converter systems and characteristic matrices for each possible installation depth, the probability distribution tables of the specified mean wave period or wave energy period and significant wave height were calculated. Then, by using the relationship between these distribution tables, according to the present wave climate, the energy that the wave energy converter systems at each depth can produce was determined. Thus, the economically feasible potential of the relevant coastal zone was revealed, and the effect of different depths on energy converter systems is presented. The Oceantic at 50, 75 and 100 m depths and Oyster at 5 and 25 m depths presents the best performance. In the 31-year long period 1998 the most and 1989 is the least dynamic year.

Keywords: Annual power production, Black Sea, efficiency, power production performance, wave energy converter.

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