Relevant bibliographies by topics / Function approximation and processing control

Academic literature on the topic 'Function approximation and processing control'

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Published: 10 December 2022
Last updated: 19 February 2023

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Journal articles on the topic "Function approximation and processing control"

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Kuwahata, Yudai, Jun-ichi Kushida, and Satoshi Ono. "A Preliminary Study on Adaptive Evolution Control Using Rank Correlation for Surrogate-Assisted Evolutionary Computation." International Journal of Software Innovation 6, no. 4 (October 2018): 59–72. http://dx.doi.org/10.4018/ijsi.2018100105.

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This article describes how surrogate-assisted evolutionary computation (SAEC) has widely applied to approximate expensive optimization problems, which require much computational time such as hours for one solution evaluation. SAEC may potentially also reduce the processing time of inexpensive optimization problems wherein solutions are evaluated within a few seconds or minutes. To achieve this, the approximation model construction for an objective function should be iterated as few times as possible during optimization. Therefore, this article proposes an adaptive evolution control mechanism for SAEC using rank correlations between actually evaluated and approximately evaluated values of the objective function. These correlations are then used to adaptively switch the approximation and actual evaluation phases, reducing the number of runs required to learn the approximation model. Experiments show that the proposed method could successfully reduce the processing time in some benchmark functions even under inexpensive scenario.
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Kusaka, Takashi, and Takayuki Tanaka. "Fast and Accurate Approximation Methods for Trigonometric and Arctangent Calculations for Low-Performance Computers." Electronics 11, no. 15 (July 22, 2022): 2285. http://dx.doi.org/10.3390/electronics11152285.

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In modern computers, complicated signal processing is highly optimized with the use of compilers and high-speed processing using floating-point units (FPUs); therefore, programmers have little opportunity to care about each process. However, a highly accurate approximation can be processed in a small number of computation cycles, which may be useful when embedded in a field-programmable gate array (FPGA) or micro controller unit (MCU), or when performing many large-scale operations on a graphics processing unit (GPU). It is necessary to devise algorithms to obtain the desired calculated values without an accelerator or compiler assistance. The residual correction method (RCM) developed here can produce simple and accurate approximations of certain nonlinear functions with minimal multiply–add operations. In this study, we designed an algorithm for the approximate computation of trigonometric and inverse trigonometric functions, which are nonlinear elementary functions, to achieve their fast and accurate computation. A fast first approximation and a more accurate second approximation of each function were created using RCM with a less than 0.001 error using multiply–add operations only. This achievement is particularly useful for MCUs, which have a low power consumption but limited computational power, and the proposed approximations are candidate algorithms that can be used to stabilize the attitude control of robots and drones, which require real-time processing.
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Cybenko, G. "Approximation by superpositions of a sigmoidal function." Mathematics of Control, Signals, and Systems 2, no. 4 (December 1989): 303–14. http://dx.doi.org/10.1007/bf02551274.

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Cybenko, G. "Approximation by superpositions of a sigmoidal function." Mathematics of Control, Signals, and Systems 5, no. 4 (December 1992): 455. http://dx.doi.org/10.1007/bf02134016.

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Babenko, Mikhail, Andrei Tchernykh, Bernardo Pulido-Gaytan, Arutyun Avetisyan, Sergio Nesmachnow, Xinheng Wang, and Fabrizio Granelli. "Towards the Sign Function Best Approximation for Secure Outsourced Computations and Control." Mathematics 10, no. 12 (June 10, 2022): 2006. http://dx.doi.org/10.3390/math10122006.

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Homomorphic encryption with the ability to compute over encrypted data without access to the secret key provides benefits for the secure and powerful computation, storage, and communication of resources in the cloud. One of its important applications is fast-growing robot control systems for building lightweight, low-cost, smarter robots with intelligent brains consisting of data centers, knowledge bases, task planners, deep learning, information processing, environment models, communication support, synchronous map construction and positioning, etc. It enables robots to be endowed with secure, powerful capabilities while reducing sizes and costs. Processing encrypted information using homomorphic ciphers uses the sign function polynomial approximation, which is a widely studied research field with many practical results. State-of-the-art works are mainly focused on finding the polynomial of best approximation of the sign function (PBAS) with the improved errors on the union of the intervals [−1,−ϵ]∪[ϵ,1]. However, even though the existence of the single PBAS with the minimum deviation is well known, its construction method on the complete interval [−1,1] is still an open problem. In this paper, we provide the PBAS construction method on the interval [−1,1], using as a norm the area between the sign function and the polynomial and showing that for a polynomial degree n≥1, there is (1) unique PBAS of the odd sign function, (2) no PBAS of the general form sign function if n is odd, and (3) an uncountable set of PBAS, if n is even.
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Deeb, W., and R. Khalil. "Best approximation in function and operator spaces." Numerical Functional Analysis and Optimization 11, no. 9-10 (January 1990): 917–27. http://dx.doi.org/10.1080/01630569108816409.

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Zatylkin, А. V., D. A. Goluschko, Y. A. Varenik, E. S. Dementeva, and B. L. Svistunov. "METHOD OF PROCESSING EXPERIMENTAL DATA BY LINEAR FUNCTIONS OF VARIABLE LENGTH." Issues of radio electronics, no. 12 (December 20, 2018): 74–82. http://dx.doi.org/10.21778/2218-5453-2018-12-74-82.

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The purpose of the research is to increase the effectiveness of information and measurement and control systems of vibration testing equipment by introducing automated processing of experimental data allowing to extract with the required accuracy resonant bursts in the investigated amplitude-frequency characteristic section of the developed sample of a technical tool. To achieve this goal, a new method for processing experimental data by linear functions of variable length has been developed. The proposed method is based on the elements of the classical least squares method used to construct single approximating linear functions. The proposed method for processing experimental data differs from the known ones in that the number of linear approximating functions and their lengths vary depending on the required accuracy of approximation. The authors developed a mechanism for the formation of a sequence of linear functions on the considered segment, taking into account the given accuracy of approximation. The proposed mechanism is implemented in the form of algorithms, the description of which is presented in the work. Practical significance of the application of the developed method consists in reducing the processing time of the experimental data and obtaining the information necessary for the development engineers to provide a given level of strength and stability to external vibrational influences of the developed technical tools.
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Goubet, Olivier. "Finite element multilevel approximation of a function and applications." Numerical Functional Analysis and Optimization 15, no. 3-4 (January 1994): 279–99. http://dx.doi.org/10.1080/01630569408816566.

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Mayorga-Macías, Walter A., Luis E. González-Jiménez, Marco A. Meza-Aguilar, and Luis F. Luque-Vega. "Low-Cost Experimental Methodology for the Dynamic Model Approximation of Multirotor Actuators." International Journal of Aerospace Engineering 2020 (July 11, 2020): 1–9. http://dx.doi.org/10.1155/2020/9263961.

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A methodology for the experimental modelling of the electric actuators of a multirotor is presented in this work. These actuators are usually brushless DC motors which are driven by electronic speed controllers in an open loop. The duty cycle of a PWM signal, generated by the electronic control unit, is the input of the electronic controller. However, during the control design procedure for the multirotor, it is important to account with a model of the actuators as its dynamical features define the closed-loop performance of the overall aircraft. Hence, a procedure, based on low-cost electronic components, to obtain approximated transfer functions of the actuators of a multirotor is presented. Moreover, as the proposed signal processing algorithms are simple, the computational capabilities of the required embedded system are also low. Given that different control schemes require different information from the actuator, two models were obtained: a duty cycle vs. angular velocity transfer function and a duty cycle vs. consumed current transfer function. The effectivity of the proposal is validated with experimental results on common electric actuators of a multirotor.
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Žaimis, Uldis, Dzintars Tomsons, and Valdis Priedols. "SIMPLE DATA APPROXIMATION FOR COMPUTER AND CONTROLLER-AIDED DEVICES." SOCIETY. TECHNOLOGY. SOLUTIONS. Proceedings of the International Scientific Conference 1 (April 17, 2019): 14. http://dx.doi.org/10.35363/via.sts.2019.10.

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INTRODUCTION Development of mechatronic systems involves finding an optimal balance between the basic mechanical structure, sensor and actuator implementation, automatic information processing and overall control. Mechatronic systems are characterized by a combination of basic mechanical devices with a processing unit monitoring and controlling it via number of actuators and sensors. Therefore sensors are significant in the process of providing usable output to microcontrollers. Wide range of sensors are available for constructing mechatronic systems. Sensors can be divided into two big groups: Active and Passive. Other type of classification is by the means of detection used in the sensor. Some of the means are electric, chemical, radioactive etc. Various types of sensors are classified by their measuring objectives for example light sensors, temperature sensors, flow sensors etc. MATERIALS AND METHODS In the process of constructing a mechatronic system a proper setup and signal processing must be provided. There exist certain problems with several sensors, therefore sometimes additional circuits for signal conditioning are made to linearize the output with hardware, but some researchers and developers try to linearize the signal using software. In modern manufacturing equipment very complex systems of devices and sensors are made therefore, they must function correctly because they are the main control parameters. It is particularly important that such control parameters that bring about a correct actual behavior in relation to the reference behavior of such a system are available as a function of time. This means that the parameters must be such that the actual behavior of the system corresponds as closely as possible to the reference behavior. Some examples of such systems are: Robot arms, which move a tool, such as a laser or burr removing tool, for example, which is to be guided along a particulary contour line of a workpiece. Heating systems which are intended to impart a particulary temperature profile to a workpiece. The input data of sensors is crucial for mechatronic systems. A large part of the system is equipped with sensors that read the most important parameters – location coordinates, altitude, compass readings, distance to the barrier (for robots and unmanned aerial vehicles), temperature (heaters and coolers), lighting, etc. Often, some types of sensors give floating data, processing which, a computer or controller acting under an algorithm develops non-physical, inexecutable commands for the final control elements. This results in an increasing load of engines, heating elements, and other actuators, as well as inappropriately increasing energy consumption. The well-known PID algorithm and numerical approximation with built-in MatLab or MATCAD functions does not provide a solution for autonomous systems with controllers that have limited memory and speed of operation. RESULTS New methods that approximate sensor data and are applicable to both analogue and PWM (Pulse-Width-Modulation)-controlled devices have been developed in the paper. The first proposed – derivative - method relates to the restriction of the function direction coefficient module. The second method – the growth bisection method enables smooth sensor data to be obtained. The derivation method is based on limitation of the maximum function increment to a specified level. The growth bisection (proportional) method is based on comparison of the increment module with the increment in the previous step and its proportional decrease by multiplying by a predefined constant. Both methods take up some lines in the control program code, and most mechatronic equipment is capable of real-time operation. CONCLUSIO Dynamic data background connection allows to obtain a self-learning system adapting to the nature of incoming data – a higher number of data will be used in case of minor changes; in contrast, only the last data saved will be used for a rapid change. A system response delay is negligible.
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Dissertations / Theses on the topic "Function approximation and processing control"

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Skelly, Margaret Mary. "Hierarchical Reinforcement Learning with Function Approximation for Adaptive Control." Case Western Reserve University School of Graduate Studies / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=case1081357818.

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Swingler, Kevin. "Mixed order hyper-networks for function approximation and optimisation." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/25349.

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Many systems take inputs, which can be measured and sometimes controlled, and outputs, which can also be measured and which depend on the inputs. Taking numerous measurements from such systems produces data, which may be used to either model the system with the goal of predicting the output associated with a given input (function approximation, or regression) or of finding the input settings required to produce a desired output (optimisation, or search). Approximating or optimising a function is central to the field of computational intelligence. There are many existing methods for performing regression and optimisation based on samples of data but they all have limitations. Multi layer perceptrons (MLPs) are universal approximators, but they suffer from the black box problem, which means their structure and the function they implement is opaque to the user. They also suffer from a propensity to become trapped in local minima or large plateaux in the error function during learning. A regression method with a structure that allows models to be compared, human knowledge to be extracted, optimisation searches to be guided and model complexity to be controlled is desirable. This thesis presents such as method. This thesis presents a single framework for both regression and optimisation: the mixed order hyper network (MOHN). A MOHN implements a function f:{-1,1}^n →R to arbitrary precision. The structure of a MOHN makes the ways in which input variables interact to determine the function output explicit, which allows human insights and complexity control that are very difficult in neural networks with hidden units. The explicit structure representation also allows efficient algorithms for searching for an input pattern that leads to a desired output. A number of learning rules for estimating the weights based on a sample of data are presented along with a heuristic method for choosing which connections to include in a model. Several methods for searching a MOHN for inputs that lead to a desired output are compared. Experiments compare a MOHN to an MLP on regression tasks. The MOHN is found to achieve a comparable level of accuracy to an MLP but suffers less from local minima in the error function and shows less variance across multiple training trials. It is also easier to interpret and combine from an ensemble. The trade-off between the fit of a model to its training data and that to an independent set of test data is shown to be easier to control in a MOHN than an MLP. A MOHN is also compared to a number of existing optimisation methods including those using estimation of distribution algorithms, genetic algorithms and simulated annealing. The MOHN is able to find optimal solutions in far fewer function evaluations than these methods on tasks selected from the literature.
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Haro, Antonio. "Example Based Processing For Image And Video Synthesis." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/5283.

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The example based processing problem can be expressed as: "Given an example of an image or video before and after processing, apply a similar processing to a new image or video". Our thesis is that there are some problems where a single general algorithm can be used to create varieties of outputs, solely by presenting examples of what is desired to the algorithm. This is valuable if the algorithm to produce the output is non-obvious, e.g. an algorithm to emulate an example painting's style. We limit our investigations to example based processing of images, video, and 3D models as these data types are easy to acquire and experiment with. We represent this problem first as a texture synthesis influenced sampling problem, where the idea is to form feature vectors representative of the data and then sample them coherently to synthesize a plausible output for the new image or video. Grounding the problem in this manner is useful as both problems involve learning the structure of training data under some assumptions to sample it properly. We then reduce the problem to a labeling problem to perform example based processing in a more generalized and principled manner than earlier techniques. This allows us to perform a different estimation of what the output should be by approximating the optimal (and possibly not known) solution through a different approach.
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Ebeigbe, Donald Ehima. "CONTROL OF RIGID ROBOTS WITH LARGE UNCERTAINTIES USING THE FUNCTION APPROXIMATION TECHNIQUE." Cleveland State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=csu1568034334694515.

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Lee, Jong Min. "A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5048.

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This thesis develops approximate dynamic programming (ADP) strategies suitable for process control problems aimed at overcoming the limitations of MPC, which are the potentially exorbitant on-line computational requirement and the inability to consider the future interplay between uncertainty and estimation in the optimal control calculation. The suggested approach solves the DP only for the state points visited by closed-loop simulations with judiciously chosen control policies. The approach helps us combat a well-known problem of the traditional DP called 'curse-of-dimensionality,' while it allows the user to derive an improved control policy from the initial ones. The critical issue of the suggested method is a proper choice and design of function approximator. A local averager with a penalty term is proposed to guarantee a stably learned control policy as well as acceptable on-line performance. The thesis also demonstrates versatility of the proposed ADP strategy with difficult process control problems. First, a stochastic adaptive control problem is presented. In this application an ADP-based control policy shows an "active" probing property to reduce uncertainties, leading to a better control performance. The second example is a dual-mode controller, which is a supervisory scheme that actively prevents the progression of abnormal situations under a local controller at their onset. Finally, two ADP strategies for controlling nonlinear processes based on input-output data are suggested. They are model-based and model-free approaches, and have the advantage of conveniently incorporating the knowledge of identification data distribution into the control calculation with performance improvement.
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Grönlund, Christer. "Spatio-temporal processing of surface electromyographic signals : information on neuromuscular function and control." Doctoral thesis, Umeå universitet, Institutionen för strålningsvetenskaper, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-958.

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During muscle contraction, electrical signals are generated by the muscle cells. The analysis of those signals is called electromyography (EMG). The EMG signal is mainly determined by physiological factors including so called central factors (central nervous system origin) and peripheral factors (muscle tissue origin). In addition, during the acquisition of EMG signals, technical factors are introduced (measurement equipment origin). The aim of this dissertation was to develop and evaluate methods to estimate physiological properties of the muscles using multichannel surface EMG (MCsEMG) signals. In order to obtain accurate physiological estimates, a method for automatic signal quality estimation was developed. The method’s performance was evaluated using visually classified signals, and the results demonstrated high classification accuracy. A method for estimation of the muscle fibre conduction velocity (MFCV) and the muscle fibre orientation (MFO) was developed. The method was evaluated with synthetic signals and demonstrated high estimation precision at low contraction levels. In order to discriminate between the estimates of MFCV and MFO belonging to single or populations of motor units (MUs), density regions of so called spatial distributions were examined. This method was applied in a study of the trapezius muscle and demonstrated spatial separation of MFCV (as well as MFO) even at high contraction levels. In addition, a method for quantification of MU synchronisation was developed. The performance on synthetic sEMG signals showed high sensitivity on MU synchronisation and robustness to changes in MFCV. The method was applied in a study of the biceps brachii muscle and the relation to force tremor during fatigue. The results showed that MU synchronisation accounted for about 40 % of the force tremor. In conclusion, new sEMG methods were developed to study muscle function and motor control in terms of muscle architecture, muscle fibre characteristics, and processes within the central nervous system.
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Grönlund, Christer. "Spatio-temporal processing of surface electromyographic signals : information on neuromuscular function and control /." Umeå : Umeå universitet, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-958.

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Dadashi, Shirin. "Modeling and Approximation of Nonlinear Dynamics of Flapping Flight." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78224.

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The first and most imperative step when designing a biologically inspired robot is to identify the underlying mechanics of the system or animal of interest. It is most common, perhaps, that this process generates a set of coupled nonlinear ordinary or partial differential equations. For this class of systems, the models derived from morphology of the skeleton are usually very high dimensional, nonlinear, and complex. This is particularly true if joint and link flexibility are included in the model. In addition to complexities that arise from morphology of the animal, some of the external forces that influence the dynamics of animal motion are very hard to model. A very well-established example of these forces is the unsteady aerodynamic forces applied to the wings and the body of insects, birds, and bats. These forces result from the interaction of the flapping motion of the wing and the surround- ing air. These forces generate lift and drag during flapping flight regime. As a result, they play a significant role in the description of the physics that underlies such systems. In this research we focus on dynamic and kinematic models that govern the motion of ground based robots that emulate flapping flight. The restriction to ground based biologically inspired robotic systems is predicated on two observations. First, it has become increasingly popular to design and fabricate bio-inspired robots for wind tunnel studies. Second, by restricting the robotic systems to be anchored in an inertial frame, the robotic equations of motion are well understood, and we can focus attention on flapping wing aerodynamics for such nonlinear systems. We study nonlinear modeling, identification, and control problems that feature the above complexities. This document summarizes research progress and plans that focuses on two key aspects of modeling, identification, and control of nonlinear dynamics associated with flapping flight.
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Kölling, Peter [Verfasser]. "Numerical studies on coherent control of semiconductor quantum dots based on k.p-calculations in envelope function approximation / Peter Kölling." Paderborn : Universitätsbibliothek, 2019. http://d-nb.info/1176019848/34.

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Herron, Robyn. "Connectivity analysis of brain function in children with foetal alcohol spectrum disorder and control children during number processing." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/3244.

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Maternal drinking during pregnancy is a significant problem in the Western Cape, South Africa, with an accompanying high incidence of children diagnosed with foetal alcohol spectrum disorder (FASD). Little is known about the neural correlates governing the disorder that manifest as behavioural abnormalities and cognitive impairments, particularly in arithmethic calculation, repeatedly reported in affected children. The effect of prenatal alcohol exposure on number processing in children was investigated in a functional magnetic resonance imaging (fMRI) study (Meintjes et al., 2007). The results indicate significant differences in activation between alcohol-exposed and non-exposed control children during Exact Addition and Proximity Judgement tasks. This raised the question of whether the groups of children differ in functional connectivity during the number processing tasks. Therefore, the objective of this study was to analyse connectivity between functionally specialised brain areas in the previously collected fMRI data. The fMRI data of 14 controls and 7 alcohol-exposed children for Exact Addition and 15 controls and 9 alcohol-exposed children for Proximity Judgement was available for analysis. A primary aim was to determine normal functional connectivity in control children during number processing and a secondary aim, to investigate any differences in functional connectivity in children with FASD.
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Books on the topic "Function approximation and processing control"

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Farrell, Jay. Adaptive Approximation Based Control. New York: John Wiley & Sons, Ltd., 2006.

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Marios, Polycarpou, ed. Adaptive approximation based control: Unifying neural, fuzzy and traditional adaptive approximation approaches. Hoboken, NJ: Wiley, 2006.

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Herring, Charles E. Function requirements for combat engineer command and control in the Maneuver Control System. Champaign, Ill: US Army Corps of Engineers, Construction Engineering Research Laboratory, 1986.

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P, Saratchandran, and Li Yan 1972-, eds. Fully tuned radial basis function neural networks for flight control. Boston: Kluwer Academic, 2002.

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Lectures On Constructive Approximation Fourier Spline And Wavelet Methods On The Real Line The Sphere And The Ball. Birkhauser Boston Inc, 2012.

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Hami, Abdelkhalak El, and Bouchaib Radi. Advanced Numerical Methods with Matlab 1: Function Approximation and System Resolution. Wiley & Sons, Incorporated, John, 2018.

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Hami, Abdelkhalak El, and Bouchaib Radi. Advanced Numerical Methods with Matlab 1: Function Approximation and System Resolution. Wiley & Sons, Incorporated, John, 2018.

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Hami, Abdelkhalak El, and Bouchaib Radi. Advanced Numerical Methods with Matlab 1: Function Approximation and System Resolution. Wiley & Sons, Incorporated, John, 2018.

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Hami, Abdelkhalak El, and Bouchaib Radi. Advanced Numerical Methods with Matlab 1: Function Approximation and System Resolution. Wiley & Sons, Incorporated, John, 2018.

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Low Rank Approximation Algorithms Implementation Applications. Springer, 2011.

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Book chapters on the topic "Function approximation and processing control"

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Osman, Hassab Elgawi. "Architecture of Behavior-Based Function Approximator for Adaptive Control." In Advances in Neuro-Information Processing, 104–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03040-6_13.

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Ylöstalo, Jyri. "Function Approximation Using Polynomials." In Streamlining Digital Signal Processing, 251–63. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118316948.ch26.

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Hu, Chenyi, Ling T. He, and Shanying Xu. "Interval Function Approximation and Applications." In Advanced Information and Knowledge Processing, 119–34. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-326-2_5.

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Ge, Shuzhi S., Chang C. Hang, Tong H. Lee, and Tao Zhang. "Neural Networks and Function Approximation." In Stable Adaptive Neural Network Control, 27–46. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-6577-9_3.

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Li, Weihua, Tielin Shi, and Kang Ding. "Gear Crack Detection Using Kernel Function Approximation." In Neural Information Processing, 535–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11893295_59.

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Peng, Yiming, Gang Chen, Mengjie Zhang, and Shaoning Pang. "Generalized Compatible Function Approximation for Policy Gradient Search." In Neural Information Processing, 615–22. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46687-3_68.

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Docampo, D., D. R. Hush, and C. T. Abdallah. "Constructive Function Approximation: Theory and Practice." In Intelligent Methods in Signal Processing and Communications, 199–219. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-2018-3_9.

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Deb, Anish, and Srimanti Roychoudhury. "Function Approximation via Block Pulse Function and Related Functions." In Control System Analysis and Identification with MATLAB®, 35–54. First edition. | Boca Raton, FL : Taylor & Francis Group, 2018. | “A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc.”: CRC Press, 2018. http://dx.doi.org/10.1201/9780203731291-2.

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Nguyen, Nhan T. "Function Approximation and Adaptive Control with Unstructured Uncertainty." In Model-Reference Adaptive Control, 151–84. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-56393-0_7.

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Kushner, Harold J., and G. George Yin. "Applications in Signal Processing and Adaptive Control." In Stochastic Approximation Algorithms and Applications, 47–66. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4899-2696-8_3.

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Conference papers on the topic "Function approximation and processing control"

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Rodriguez, N., P. Julian, and E. Paolini. "Function Approximation Using Symmetric Simplicial Piecewise-Linear Functions." In 2019 XVIII Workshop on Information Processing and Control (RPIC). IEEE, 2019. http://dx.doi.org/10.1109/rpic.2019.8882186.

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Zhou, Suying, and Hui Lin. "Function approximation based on self-adaptive RBF neural network with combined clustering algorithm." In 2010 International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2010. http://dx.doi.org/10.1109/icicip.2010.5565283.

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Avargel, Yekutiel, and Israel Cohen. "Identification of linear systems with adaptive control of the cross-multiplicative transfer function approximation." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518478.

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Novikov, Anatoly Ivanovich, Evgeny Yurievich Kholopov, Aleksey Igorevich Efimov, and Mikhail Borisovich Nikiforov. "Palm Gesture Recognition Technology Based on Comparison of Contour Autocorrelation Functions." In 32nd International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/graphicon-2022-477-483.

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The technology of detecting static hand gestures is considered. The technology includes four main stages of image processing: detection of palm contours; piecewise linear approximation of the palm contour; construction of the autocorrelation function (ACF) of the contour of the observed gesture; comparison of the calculated ACF with the ACF of reference gestures. Examples of identification of the main gestures with the palm using the proposed technology, as well as the resulting quantitative estimates of the similarity measure of gestures, are given. The proposed technology is characterized by high speed and lack of learning process. The presented approaches may be of interest in the construction of non-contact control systems.
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Jumanov, I. I., R. A. Safarov, and O. I. Djumanov. "Error Control of Identification and Filtering of Micro-Object Images." In III All-Russian Scientific Conference with International Participation "Science, technology, society: Environmental engineering for sustainable development of territories". Krasnoyarsk Science and Technology City Hall, 2022. http://dx.doi.org/10.47813/nto.3.2022.6.109-124.

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Researched and developed scientifically and methodologically foundations for optimal identification of micro-objects using traditional and Gaussian filtering, median filter, filters based on fast Fourier transform, wavelet transforms, shift transforms, mechanisms using geometric, specific features, statistical, dynamic properties of image information. Mechanisms for optimizing the identification of micro-objects are proposed that have advantages in reducing the complexity and laboriousness of analyzing the structure and processing information, identifying and segmentation of the image contour, using the dynamics of growth, visual differentiation, extracting internal features and properties, approximation, smoothing, and interpretation of objects. A mechanism has been investigated and implemented that performs the following functions: aligns histology slices; finds contours of objects, a set of levels, thresholds, combines segmentation, conducts registrations, forms a search graph, performs approximations based on a wavelet, shear, and other transformations, determines parameters, performs color coding and color visualization of micro-objects. The implementations of algorithms and software modules of the software complex for identification, recognition and classification of micro-objects, in particular, cellular elements of the inflammatory series (fibroblasts, fibrocytes) of lung disease, have been tested. The signs of chronic inflammation were assessed - the presence of giant cells. A software package for visualization, recognition, classification of images of pollen grains has been developed, the implementations of which have been tested taking into account the conditions of a priori insufficiency, parametric uncertainty and nonstationarity of processes.
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Li, Dongqin, Philip A. Wilson, Yifeng Guan, and Xin Zhao. "An Effective Approximation Modeling Method for Ship Resistance in Multidisciplinary Ship Design Optimization." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-23407.

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Ship design is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional ship design process only involves independent design optimization with some regression formulas within each discipline and there is no guarantee to achieve the optimum design. At the same time, it is crucial to improve the efficiency of modern ship design. Nowadays, the methods of computational fluid dynamics (CFD) has been brought into the ship design optimization. However, there are still some problems such as calculation precision and time consumption especially when CFD software is inlaid into the optimization procedure. Modeling is a far-ranging and all-around subject, and its precision directly affects the scientific decision in future. How to establish an accurate approximation model instead of the CFD calculation will be the key problem. The Support Vector Machines (SVM), a new general machine learning method based on the frame of statistical learning theory, may solve the problems in sample space and be an effective method of processing the non-liner classification and regression. The classical SVR has two parameters to control the errors. A new algorithm of Support Vector Regression proposed in this article has only one parameter to control the errors, adds b2/2 to the item of confidence interval at the same time, and adopts the Laplace loss function. It is named Single-parameter Lagrangian Support Vector Regression (SPL-SVR). This effective algorithm can improve the operation speed of program to a certain extent, and has better fitting precision. In practical design of ship, Design of Experiment (DOE) and the proposed support vector regression algorithm are applied to ship design optimization to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. The result indicates that the SPL-SVR method to establish approximate models can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.
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Mitkus, Rytis, Ayat Taleb Alashkar, and Michael Sinapius. "An Attempt to Topology Optimize 3D Printed Piezoelectric Composite Sensors for Highest D31 Output." In ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/smasis2021-68029.

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Abstract By adopting topology optimization based on numerical solvers, the geometries of the piezoelectric sensors can be optimized to produce higher electrical output in a certain loading directions. 2D topology optimization and simulation studies are carried out with ANSYS using Piezo and MEMS extensions for coupled systems. Topology optimization is based on Solid isotropic material with the penalization method, where the design variables are the pseudo densities that control material distribution at each finite element. The optimization problem is solved using Sequential Convex Programming. The approximation of the objective function happens through a uniform convex function. The objective is to reduce the fundamental frequency of the piezoelectric sensor for given constraints and boundary conditions (maximum sensor size of 30 × 30 mm and reduction of sensor mass by 50%). Two optimized shapes are chosen for further analysis. All sensors are made of 10 vol% PZT piezoelectric ceramic in High-Temperature V2 photopolymer resin. Sensors are manufactured using a simulated Direct Light Processing (DLP) type 3D printing process by tape-casting them on glass and exposing them to UV light. The performance of sensors is measured on a 4-point bending setup. Experiments show the enhanced performance of the optimized sensors even when their mass is reduced by 50%.
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Spanakis, Constantinos, Emmanuel Mathioudakis, Manolis Tsiknakis, Nikos Kampanis, and Kostas Marias. "Function Approximation for Medical Image Registration." In 2018 41st International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2018. http://dx.doi.org/10.1109/tsp.2018.8441336.

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Zhong, Mingyuan, Mikala Johnson, Yuval Tassa, Tom Erez, and Emanuel Todorov. "Value function approximation and model predictive control." In 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). IEEE, 2013. http://dx.doi.org/10.1109/adprl.2013.6614995.

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Rozada, Sergio, Victor Tenorio, and Antonio G. Marques. "Low-rank State-action Value-function Approximation." In 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9616008.

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Reports on the topic "Function approximation and processing control"

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Montville, Thomas J., and Roni Shapira. Molecular Engineering of Pediocin A to Establish Structure/Function Relationships for Mechanistic Control of Foodborne Pathogens. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568088.bard.

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This project relates the structure of the bacteriocin molecule (which is genetically determined) to its antimicrobial function. We have sequenced the 19,542 bp pediocin plasmid pMD136 and developed a genetic transfer system for pediococci. The pediocin A operon is complex, containing putative structural, immunity, processing, and transport genes. The deduced sequence of the pediocin A molecule contains 44 amino acids and has a predicted PI of 9.45. Mechanistic studies compared the interaction of pediocin PA-1 and nisin with Listeria monocytgenes cells and model lipid systems. While significant nisin-induced intracellular ATP depletion is caused by efflux, pediocin-induced depletion is caused exclusively by hydrolysis. Liposomes derived from L. monocytogenes phospholipids were used to study the physical chemistry of pediocin and nisin interactions with lipids. Their different pH optima are the results of different specific ionizable amino acids. We generated a predicted 3-D structural model for pediocin PA-1 and used a variety of mutant pediocins to demonstrate that the "positive patch" at residues 11 and 12 (and not the YGNGV consensus sequence) is responsible for the binding step of pediocin action. This structure/function understanding gained here provides necessary prerequisites to the more efficacious use of bacteriocins to control foodborne pathogens.
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Steffens, John, Eithan Harel, and Alfred Mayer. Coding, Expression, Targeting, Import and Processing of Distinct Polyphenoloxidases in Tissues of Higher Plants. United States Department of Agriculture, November 1994. http://dx.doi.org/10.32747/1994.7613008.bard.

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Polyphenol oxidase (PPO) catalyzes the oxidation of phenols to quinones at the expense of O2. PPOs are ubiquitous in higer plants, and their role in oxidative browning of plant tissues causes large annual losses to food production. Despite the importance of PPOs to agriculture, the function(s) of PPOs in higher plants are not understood. Among other roles, PPOs have been proposed to participate in aspects of chloroplast metabolism, based on their occurrence in plastids and high Km for O2. Due to the ability of PPO to catalyze formation of highly reactive quinones, PPOs have also been proposed to be involved in a wide array of defensive interactions with insect, bacterial, and fungal pests. Physiological and biochemical studies of PPO have provided few answers to the major problems of PPO function, subcellular localization, and biochemical properties. This proposal achieved the following major objectives: cloning of PPO cDNAs in potato and tomato; characterization of the tomato PPO gene family; antisense downregulation of the tomato PPO gene family; and reduction in post-harvest enzymic browning of potato through expression of antisense PPO genes under the control of tuber-specific promoters. In addition, we established the lumenal localization of PPO, characterized and clarified the means by which PPOs are imported and processed by chloroplasts, and provided insight into the factors which control localization of PPOs. This proposal has thereby provided fundamental advances in the understanding of this enzyme and the control of its expression.
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Yang, Xinwei, Huan Tu, and Xiali Xue. The improvement of the Lower Limb exoskeletons on the gait of patients with spinal cord injury: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2021. http://dx.doi.org/10.37766/inplasy2021.8.0095.

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Review question / Objective: The purpose of this systematic review and meta-analysis was to determine the efficacy of lower extremity exoskeletons in improving gait function in patients with spinal cord injury, compared with placebo or other treatments. Condition being studied: Spinal Cord Injury (SCI) is a severely disabling disease. In the process of SCI rehabilitation treatment, improving patients' walking ability, improving their self-care ability, and enhancing patients' self-esteem is an important aspect of their return to society, which can also reduce the cost of patients, so the rehabilitation of lower limbs is very important. The lower extremity exoskeleton robot is a bionic robot designed according to the principles of robotics, mechanism, bionics, control theory, communication technology, and information processing technology, which can be worn on the lower extremity of the human body and complete specific tasks under the user's control. The purpose of this study was to evaluate the effect of the lower extremity exoskeleton on the improvement of gait function in patients with spinal cord injury.
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Dale, Naomi, Aneesa Khan, and Sophie Dale. Early intervention for vision and neurodevelopment in infants and very young children with visual impairment: a systematicreview. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0080.

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Review question / Objective: Research question - What is the effectiveness of Early Childhood Intervention (ECI) in the first 3 years of life? Population (P) Infants and very young children with diagnosed visual impairment. Intervention (I) ECI programmes that includes vision and developmental stimulation, play, learning and responsive parenting Comparison (C) Standard care or control Outcomes (O) Primary: Vision function or and/or neurodevelopment and/or parent-child interaction outcomes Secondary: Parental context factors eg parental wellbeing and mental health, parental satisfaction with service provision. Condition being studied: Childhood congenital or very early visual impairment arising from congenital disorders of the peripheral or anterior visual system or cerebral-based vision disorders. This includes all vision disorders of the globe, retina and anterior optic nerve and all vision disorders that are considered cerebral based along visual pathways that are retro-chiasmatic and include central brain regions and networks involved in vision processing.
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Mevarech, Moshe, Jeremy Bruenn, and Yigal Koltin. Virus Encoded Toxin of the Corn Smut Ustilago Maydis - Isolation of Receptors and Mapping Functional Domains. United States Department of Agriculture, September 1995. http://dx.doi.org/10.32747/1995.7613022.bard.

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Ustilago maydis is a fungal pathogen of maize. Some strains of U. maydis encode secreted polypeptide toxins capable of killing other susceptible strains of U. maydis. Resistance to the toxins is conferred by recessive nuclear genes. The toxins are encoded by genomic segments of resident double-strande RNA viruses. The best characterized toxin, KP6, is composed of two polypeptides, a and b, which are not covalently linked. It is encoded by P6M2 dsRNA, which has been cloned, sequenced and expressed in a variety of systems. In this study we have shown that the toxin acts on the membranes of sensitive cells and that both polypeptides are required for toxin activity. The toxin has been shown to function by creating new pores in the cell membrane and disrupting ion fluxes. The experiments performed on artificial phospholipid bilayers indicated that KP6 forms large voltage-independent, cation-selective channels. Experiments leading to the resolution of structure-function relationship of the toxin by in vitro analysis have been initiated. During the course of this research the collaboration also yielded X-ray diffracion data of the crystallized a polypeptide. The effect of the toxin on the pathogen has been shown to be receptor-mediated. A potential receptor protein, identified in membrane fractions of sensitive cells, was subjected to tryptic hydrolysis followed by amino-acid analysis. The peptides obtained were used to isolate a cDNA fragment by reverse PCR, which showed 30% sequence homology to the human HLA protein. Analysis of other toxins secreted by U. maydis, KP1 and KP4, have demonstrated that, unlike KP6, they are composed of a single polypeptide. Finally, KP6 has been expressed in transgenic tobacco plants, indicating that accurate processing by Kex2p-like activity occurs in plants as well. Using tobacco as a model system, we determined that active antifungal toxins can be synthesized and targeted to the outside of transgenic plant cells. If this methodology can be applied to other agronomically crop species, then U. maydis toxins may provide a novel means for biological control of pathogenic fungi.
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Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transport techniques for different crops and structure types. All the objectives have been successfully addressed. The study was focused on both screenhouses and naturally ventilated greenhouses, and all proposed methods were examined. Background to the topic Our previous BARD project established that the eddy covariance (EC) technique is suitable for whole canopy evapotranspiration measurements in large agricultural screenhouses. Nevertheless, the eddy covariance technique remains difficult to apply in the farm due to costs, operational complexity, and post-processing of data – thereby inviting alternative techniques to be developed. The subject of this project was: 1) the evaluation of four turbulent transport (TT) techniques, namely, Surface Renewal (SR), Flux-Variance (FV), Half-order Time Derivative (HTD) and Bowen Ratio (BR), whose instrumentation needs and operational demands are not as elaborate as the EC, to estimate evapotranspiration within large agricultural structures; and 2) the development of mathematical models able to predict water savings and account for the external environmental conditions, physiological properties of the plant, and structure properties as well as to evaluate the necessary micrometeorological conditions for utilizing the above turbulent transfer methods in such protected environments. Major conclusions and achievements The major conclusions are: (i) the SR and FV techniques were suitable for reliable estimates of ET in shading and insect-proof screenhouses; (ii) The BR technique was reliable in shading screenhouses; (iii) HTD provided reasonable results in the shading and insect proof screenhouses; (iv) Quality control analysis of the EC method showed that conditions in the shading and insect proof screenhouses were reasonable for flux measurements. However, in the plastic covered greenhouse energy balance closure was poor. Therefore, the alternative methods could not be analyzed in the greenhouse; (v) A multi-layered flux footprint model was developed for a ‘generic’ crop canopy situated within a protected environment such as a large screenhouse. The new model accounts for the vertically distributed sources and sinks within the canopy volume as well as for modifications introduced by the screen on the flow field and microenvironment. The effect of the screen on fetch as a function of its relative height above the canopy is then studied for the first time and compared to the case where the screen is absent. The model calculations agreed with field experiments based on EC measurements from two screenhouse experiments. Implications, both scientific and agricultural The study established for the first time, both experimentally and theoretically, the use of four simple TT techniques for ET estimates within large agricultural screenhouses. Such measurements, along with reliable theoretical models, will enable the future development of lowcost ET monitoring system which will be attainable for day-to-day use by growers in improving irrigation management.
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.

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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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