This field experiment was conducted at Research Station B, Department of Horticulture and Landscape Engineering, College of Agricultural Engineering Sciences, University of Baghdad, Jadiriyah during the fall season of 2019-2020 to evaluate the effect of cultivation dates and soil fertilization source on the growth, yield and quality of broccoli. A split plot design within the RCBD design with three replicates was applied as the Max F1 hybrid broccoli seedlings were transferred to the field at two dates 25, Sep. 2019 and 15, Oct. 2019, which were symbolized as A and B, respectively, and occupied at the main plot. After two weeks of cultivation, the soil fertilizers were applied three times during the season in 20 days between each applicati

Diese Forschungsarbeit versteht sich als ein Versuch zur Bestimmung einer der neuen Unterrichtsmethoden, die den Lernenden im Fach Deutsch besonders interessant vorkommen.Der Unterricht soll in einer Atmosphäre, die frei von Zeitdruck, Angst und Zensurdruck ablaufen lassen, damit werden die Studenten ermutigt, die Nutzung von Spiel zu ihrer eigenen Sache machen, um die Spielziele Spaß, Empathie, Zusammenarbeit und Kommunikation zu realisieren. Das Hauptlernziel des Fremdsprachenunterrichts ist es, Lernenden zu ermöglichen, in der Zielsprache zu kommunizieren.

Wir konzentrieren uns in diesem Beitrag auf eine wichtige sprachliche Fertigkeit, die den rezeptiven Fertigkeiten gehört, die ist das Hörverstehen.

Das Hörvers

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distri

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an