Search results for: recursive model

Authors: Ju-Hong Lee, Chong-Jia Ciou, Yuan-Hau Yang

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This paper deals with the problem of two-dimensional (2-D) recursive doubly complementary (DC) digital filter design. We present a structure of 2-D recursive DC filters by using 2-D symmetric half-plane (SHP) recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive DC digital lattice filter is that the resulting 2-D SHP recursive DC digital lattice filter provides better performance than the existing 2-D SHP recursive DC digital filter. Moreover, the proposed structure possesses a favorable 2-D DC half-band (DC-HB) property that allows about half of the 2-D SHP recursive DALF’s coefficients to be zero. This leads to considerable savings in computational burden for implementation. To ensure the stability of a designed 2-D SHP recursive DC digital lattice filter, some necessary constraints on the phase of the 2-D SHP recursive DALF during the design process are presented. Design of a 2-D diamond-shape decimation/interpolation filter is presented for illustration and comparison.

Keywords: all-pass digital filter, doubly complementary, lattice structure, symmetric half-plane digital filter, sampling rate conversion

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Authors: Ju-Hong Lee, Chong-Jia Ciou

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This paper deals with the problem of two-dimensional (2-D) recursive two-channel quincunx quadrature mirror filter (QQMF) banks design. The analysis and synthesis filters of the 2-D recursive QQMF bank are composed of 2-D recursive digital allpass lattice filters (DALFs) with symmetric half-plane (SHP) support regions. Using the 2-D doubly complementary half-band (DC-HB) property possessed by the analysis and synthesis filters, we facilitate the design of the proposed QQMF bank. For finding the coefficients of the 2-D recursive SHP DALFs, we present a structure of 2-D recursive digital allpass filters by using 2-D SHP recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive QQMF bank is that the resulting 2-D recursive QQMF bank provides better performance than the existing 2-D recursive QQMF banks. Simulation results are also presented for illustration and comparison.

Keywords: all-pass digital filter, lattice structure, quincunx QMF bank, symmetric half-plane digital filter

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Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

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This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

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Authors: Vaclav Sadilek, Miroslav Vorechovsky

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The paper deals with the classical fiber bundle model of equal load sharing, sometimes referred to as the Daniels' bundle or the democratic bundle. Daniels formulated a multidimensional integral and also a recursive formula for evaluation of the strength cumulative distribution function. This paper describes three algorithms for evaluation of the recursive formula and also their implementations with source codes in high-level programming language Python. A comparison of the algorithms are provided with respect to execution time. Analysis of orders of magnitudes of addends in the recursion is also provided.

Keywords: equal load sharing, mpmath, python, strength of Daniels' bundle

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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Authors: Ju-Hong Lee, Ding-Chen Chung

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This paper deals with the optimal design of recursive doubly complementary (DC) digital filter design using a metaheuristic based optimization technique. Based on the theory of DC digital filters using two recursive digital all-pass filters (DAFs), the design problem is appropriately formulated to result in an objective function which is a weighted sum of the phase response errors of the designed DAFs. To deal with the stability of the recursive DC filters during the design process, we can either impose some necessary constraints on the phases of the recursive DAFs. Through a frequency sampling and a weighted least squares approach, the optimization problem of the objective function can be solved by utilizing a population based stochastic optimization approach. The resulting DC digital filters can possess satisfactory frequency response. Simulation results are presented for illustration and comparison.

Keywords: doubly complementary, digital all-pass filter, weighted least squares algorithm, particle swarm optimization

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Authors: Flavio O. Torres, Maria J. Castilla, Rodrigo A. Augsburger, Pedro I. Cachana, Katherine S. Reyes

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In this paper, we present a scene-based nonuniformity correction method using a modified recursive least square algorithm with a feedback system on the updates. The feedback is designed to remove impulsive noise contamination images produced by a recursive least square algorithm by measuring the output of the proposed algorithm. The key advantage of the method is based on its capacity to estimate detectors parameters and then compensate for impulsive noise contamination image in a frame by frame basics. We define the algorithm and present several experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published recursive least square-based methods. We show that the proposed method removes impulsive noise contamination image.

Keywords: infrared focal plane arrays, infrared imaging, least mean square, nonuniformity correction

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Authors: Chang Lee Shu-Jung, Mei-Se Chien, Chien-Chiang Lee, Hui-Ting Hu

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This paper applies recursive cointegration analysis to examine the dynamic changes in Feldstein-Horioka saving-investment (S-I) coefficients across China and the ASEAN-5 countries over time. To the extent that the S-I coefficients measure international capital mobility, the main empirical results are as follows. The recursive trace statistics show that the investment- savings nexus varies in these six countries. There is no cointegration between investment and savings in three countries (China, Malaysia, and Singapore), which means that the mobility of the capital markets in the three is high and that domestic investment in them will be financed by the global pool of capital. As to the other three countries (Indonesia, Thailand, and Philippines), there is cointegration between investment and savings for part of the sample period in the three, including before 2002 for Thailand, before 2001 for Indonesia, and before 2002 for Philippines. This shows these three countries achieved highly mobile and open capital markets later.

Keywords: investment, savings, recursive cointegration test, ASEAN, China

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Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

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This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: clutch drag torque, wet DCT, dynamic viscosity, recursive least squares

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Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

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Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

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Authors: Alina Mirza, Sumrin M. Kabir, Shahzad A. Sheikh

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The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.

Keywords: OFDM, impulsive noise, SSRLS, BER

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Authors: Asiye Aydilek, Harun Aydilek

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We investigate the costs of various suboptimal allocations in housing, consumption, bond and stock holdings of a retiree in a setting with recursive utility, considering the extensive empirical evidence that investors make suboptimal decisions in different ways. We find that suboptimal stock holdings impose only modest costs on the retiree. This may have a merit in explaining the limited stock investment in the data. The cost of suboptimal bond holdings is higher than that of stocks, but still small. This may partially explain why many more people hold bonds compared to stocks. We find that positive deviations from the optimal level are less costly relative to the negative ones in suboptimal housing allocations. This may help us to clarify why the elderly are over consuming housing, as seen in the housing data. The cost of suboptimal consumption is quite high and the highest of all. Our paper suggests that, in terms of welfare, the decisions of how much of liquid wealth to use for consumption and for saving are more important than the decision about the composition of liquid savings. Suboptimal stock holdings are twice more costly in power utility and suboptimal bond holdings are twenty times more costly in recursive utility. Recursive utility is superior to power utility in terms of rationalizing many people's preference for bonds instead of stocks in investment.

Keywords: housing, recursive utility, retirement, suboptimal decisions, welfare cost

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Ese Urhie, Olabisi Popoola, Obindah Gershon

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Several policies and programs initiated to address the challenge of unemployment in Nigeria seem to be inadequate. The desired structural transformation which is expected to absorb the excess labour in the economy is yet to be achieved. The agricultural sector accounts for almost half of the labour force with very low productivity. This could partly explain why the much anticipated structural transformation has not been achieved. A major reason for the low productivity is the fact that the production process is predominantly based on the use of traditional tools. In view of the underdeveloped nature of the agricultural sector, Nigeria still has huge potentials for productivity enhancement through modern technology. Aside from productivity enhancement, modern agriculture also stimulates both backward and forward linkages that promote investment and thus generate employment. Contrary to the apprehension usually expressed by many stake-holders about the adoption of modern technology by labour-abundant less-developed countries, this study showed that though there will be job loss initially, the reverse will be the case in the long-run. The outcome of this study will enhance the understanding of all stakeholders in the sector and also encourage them to adopt modern techniques of farming. It will also aid policy formulation at both sectoral and national levels. The recursive model and analysis adopted in the study is useful because it exhibits a unilateral cause-and-effect relationship which most simultaneous equation models do not. It enables the structural equations to be ordered in such a way that the first equation includes only predetermined variables on the right-hand side, while the solution for the final endogenous variable is completely determined by all equations of the system. The study examines the transmission channels and effect of modern agriculture on agricultural productivity and employment growth in Nigeria, via its forward and backward linkages. Using time series data spanning 1980 to 2014, the result of the analyses shows that: (i) a significant and positive relationship between agricultural productivity growth and modern agriculture; (ii) a significant and negative relationship between export price index and agricultural productivity growth; (iii) a significant and positive relationship between export and investment; and (iv) a significant and positive relationship between investment and employment growth. The unbalanced growth theory will be a good strategy to adopt by developing countries such as Nigeria.

Keywords: employment, modern agriculture, productivity, recursive model

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Authors: J. Ritonja

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Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

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Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

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Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: digital twin, distributed energy resources, remote terminal units, supervisory control and data acquisition system, smart recursive load flow

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Authors: Wen-Tsung Ho, Ku-Kuang Chang, Hsin-Yuan Chang

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In this study, we consider an economic lot-size batch-shipment scheduling problem (ELBSP) with extended basic period (EBP) and power-of-two (PoT) policies. In this problem, the supplier using a single facility to manufacture multiple products and equally sized batches are then delivered by the supplier to buyers over an infinite planning horizon. Further, the extended basic period (EBP) and power-of-two (PoT) policy are utilized. Relaxing the production schedule converts the ELBSP to an economic lot-size batch-shipment problem (ELBP) with EBP and PoT policies, and a nonlinear integer programming model of the ELBP is constructed. Using the replenishment cycle division and recursive tightening methods, optimal solutions are then solved separately for each product. The sum of these optimal solutions is the lower bound of the ELBSP. A proposed heuristic method with polynomial complexity is then applied to figure out the near-optimal solutions of the ELBSP. Numerical example is presented to confirm the efficacy of the proposed method.

Keywords: economic lot-size scheduling problem, extended basic period, replenishment cycle division, recursive tightening, power-of-two

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Authors: Marsden Jacques, Dennis Wong

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A weak order is a way to rank n objects where ties are allowed. In this talk, we present a recursive framework to generate Gray codes for weak orders. We then describe a simple algorithm based on the framework that generates 2-Gray codes for weak orders in constant amortized time per string. This framework can easily be modified to generate other Gray codes for weak orders. We provide an example on using the framework to generate the first Shift Gray code for weak orders, also in constant amortized time, where consecutive strings differ by a shift or a symbol change.

Keywords: weak order, Cayley permutation, Gray code, shift Gray code

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Authors: Paola Cattabriga

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According to Gödel’s first incompleteness argument it is possible to construct a formally undecidable proposition in Principia mathematica, a statement that, although true, turns out to be neither provable nor refutable for the system, making therefore incomplete any formal system suitable for the arithmetic of integers. Its features and limitation effects are today widespread basics throughout whole scientific thought. This article brings Gödel’s achievement into question by the definition of the refutability predicate as a number-theoretical statement. We develop proof of invalidity of Theorem VI in Gödel’s 1931, the so-called Gödel’s first incompleteness theorem, in two steps: defining refutability within the same recursive status as provability and showing that as a consequence propositions (15) and (16), derived from definition 8.1 in Gödel’s 1931, are false and unacceptable for the system. The achievement of their falsity blocks the derivation of Theorem VI, which turns out to be therefore invalid, together with all the depending theorems. This article opens up thus new perspectives for mathematical research and for the overall scientific reasoning.

Keywords: Gödel numbering, incompleteness, provability predicate, refutability predicate

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Authors: A. Mansouri, F. Krim

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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.

Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

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Authors: Jac J. W. Andrews, James B. Hale

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Effective practicing psychologists require ongoing skill development that is constructivist and recursive in nature, with mentor, colleague, co-worker, and patient feedback critical to successful acquisition and maintenance of professional competencies. This paper will provide an overview of the nature and scope of psychologist skill development through multisource feedback (MSF) or 360 degree evaluation, present a rationale for its use for assessing practicing psychologist performance, and advocate its use in psychology given the demonstrated model utility in other health professions. The paper will conclude that an international research design is needed to assess the feasibility, reliability, and validity of MSF system ratings intended to solicit feedback from mentors, colleagues, coworkers, and patients about psychologist competencies. If adopted, the MSF model could lead to enhanced skill development that fosters patient satisfaction within and across countries.

Keywords: psychologist, multisource feedback, psychologist competency, professionalism

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Owing to close antenna spacing between antenna sensors within a compact space, a part of data in one antenna sensor would outflow to other antenna sensors when the antenna sensors in an antenna array operate simultaneously. This phenomenon is called mutual coupling effect (MCE). It has been shown that the performance of antenna array systems can be degraded when the antenna sensors are in close proximity. Especially, in a systems equipped with massive antenna sensors, the degradation of beamforming performance due to the MCE is significantly inevitable. Moreover, it has been shown that even a small angle error between the true direction angle of the desired signal and the steering angle deteriorates the effectiveness of an array beamforming system. However, the true direction vector of the desired signal may not be exactly known in some applications, e.g., the application in land mobile-cellular wireless systems. Therefore, it is worth developing robust techniques to deal with the problem due to the MCE and steering angle error for array beamforming systems. In this paper, we present an efficient technique for performing adaptive beamforming with robust capabilities against the MCE and the steering angle error. Only the data vector received by an antenna array is required by the proposed technique. By using the received array data vector, a correlation matrix is constructed to replace the original correlation matrix associated with the received array data vector. Then, the mutual coupling matrix due to the MCE on the antenna array is estimated through a recursive algorithm. An appropriate estimate of the direction angle of the desired signal can also be obtained during the recursive process. Based on the estimated mutual coupling matrix, the estimated direction angle, and the reconstructed correlation matrix, the proposed technique can effectively cure the performance degradation due to steering angle error and MCE. The novelty of the proposed technique is that the implementation procedure is very simple and the resulting adaptive beamforming performance is satisfactory. Simulation results show that the proposed technique provides much better beamforming performance without requiring complicated complexity as compared with the existing robust techniques.

Keywords: adaptive beamforming, mutual coupling effect, recursive algorithm, steering angle error

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Authors: J. Ritonja

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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification

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Authors: M. Bartal

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A large empirical evidence points to sizable lifetime earnings losses associated with the displacement of tenured workers. The causes of these losses are still not well-understood. Existing explanations are heavily based on human capital depreciation during non-employment spells. In this paper, a new avenue is explored. Evidence on the role of household liquidity constraints in accounting for the persistence of post-displacement earning losses is provided based on SIPP data. Then, a directed search and matching model with endogenous human capital and wealth accumulation is introduced. The model is computationally tractable thanks to its block-recursive structure and highlights a non-trivial, yet intuitive, interaction between wealth and human capital. Constrained workers tend to accept jobs with low firm-sponsored training because the latter are (endogenously) easier to find. This new channel provides a plausible explanation for why young (highly constrained) workers suffer persistent scars after displacement. Finally, the model is calibrated on US data to show that the interplay between wealth and human capital is crucial to replicate the observed lifecycle pattern of earning losses. JEL— E21, E24, J24, J63.

Keywords: directed search, human capital accumulation, job displacement, wealth accumulation

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

Abstract:

Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: monomial forms, rectangular surfaces, CAGD curves, monomial matrix applications

Procedia PDF Downloads 146

Authors: Kim Hyekyoung, Au Yunkyung

Abstract:

As media plays an increasingly important role in our lives, the age at which media usage begins is getting younger worldwide. Particularly, young children are exposed to media at an early age, making early childhood media literacy education an essential task. However, most existing early childhood media literacy education programs focus solely on teaching children how to use media, and practical implementation and application are challenging. Therefore, this study aims to develop a play-based early childhood media literacy education program utilizing topic-based media content and explore the potential application and impact of this program on young children's media literacy learning. Based on theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perceptions of media literacy education for preschool children, this study developed a media literacy education program for preschool children, considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication). To verify the effectiveness of the program, 20 preschool children aged 5 from C City M Kindergarten were chosen as participants, and the program was implemented from March 28th to July 4th, 2022, once a week for a total of 7 sessions. The program was developed based on Gallenstain's (2003) iterative learning model (participation-exploration-explanation-extension-evaluation). To explore the quantitative changes before and after the program, a repeated measures analysis of variance was conducted, and qualitative analysis was employed to examine the observed process changes. It was found that after the application of the education program, media literacy levels such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication significantly improved. The recursive learning-based early childhood media literacy education program developed in this study can be effectively applied to young children's media literacy education and help enhance their media literacy levels. In terms of observed process changes, it was confirmed that children learned about various topics, expressed their thoughts, and improved their ability to communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can contribute to empowering young children to safely and effectively utilize media in their media environment. The results of this study, exploring the potential application and impact of the recursive learning-based early childhood media literacy education program on young children's media literacy learning, demonstrated positive changes in young children's media literacy levels. These results go beyond teaching children how to use media and can help foster their ability to safely and effectively utilize media in their media environment. Additionally, to enhance young children's media literacy levels and create a safe media environment, diverse content and methodologies are needed, and the continuous development and evaluation of education programs should be conducted.

Keywords: young children, media literacy, recursive learning, education program

Procedia PDF Downloads 75