The feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, object holes, noise removal, scanning 2D objects.
In the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl
... Show MoreThe research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement
... Show MoreThis paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
... Show MoreThe important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was
... Show MoreThe influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
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