Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that the proposed MLFFNN has high performance and is efficient for solving the forward kinematics, with a Mean Squared Error (MSE) between the desired and estimated position of 4.3881×10-11. This performance clearly demonstrates that, despite the large size of the dataset, it can be effectively mastered with only a small number of neurons. The simplicity of the network allows it to learn a compact and efficient representation of the data. This improves the reliability of using the proposed network for similar applications in other robotic systems.
Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua
... Show MoreA new ligand 3-hydroxy-2-(3-(4-nitrobenzoyl) thiouriedo) propanoic acid (NTP) where synthesized by reaction of 4-nitro benzoyl isothiocyanate with serine amino acid. The ligand was characterized by FT-IR, NMR spectra and the elemental analysis. The transition metal complexes of this ligand where synthesize and characterized by UV-Visible spectra, FT-IR, magnetic suscpility, conductively measurement, The general formula [M (NTP) 2] where M+2= (Mn, Co, Ni, Cu, Zn, Cd, Hg,), the form of molecular for these complexes as tetrahedral except Cu has square planer.
N-Benzylidene m-nitrobenzeneamines (Schiff bases) were prepared by condensation of m-nitroaniline with aromatic aldehydes. These Schiff bases were found to react with maleic anhydride to give 2-Aryl-3-(m-nitrophenyl)-2, 3-dihydro [1, 3] oxazepine–4, 7–diones and with phthalic anhydride to give 2-Aryl-3–(m-nitrophenyl)–2, 3–dihydrobenz|| 1, 2-e|||| 1, 3] oxazepine–4, 7-diones which were reacted with pyrrolidine to give the anilide–pyrrolidides of maleic acid and phthalic acid.
The study of homomorphisms in cubic sets is considered one of the important concepts that transfer algebraic properties between different structures, so we study a homomorphism of a cubic set of a semigroup in a KU-algebra and defined the product of two cubic sets in this structure. Firstly, we define the image and the inverse image of a cubic set in a KU-semigroup and achieve some results in this notion. Secondly, the Cartesian product of cubic subsets in a KU-semigroup is discussed and some important characteristics are proved.
The aim of study was making comparison in some kinematics variables in (100) meter butterfly swimming to first and second ranking in championship 2003 Espana, so noticed there is no such like this study in our country in comparison study for international champions therefore not specific and scientific discovering to these advanced levels, also the researchers depend on group of kinematics variables when the comparison making and it was included (50 meter the first, 50 meter the second, the differences between the first (50) meter and the second , more over basic variables in (100) meter butterfly , after having the results and treat it statistically the researchers reaches to two conclusions which was: • Success the first rank in startin
... Show More1.
Embryonic Origin of Neural Tube Defects.
Insaf Jasim Mahmoud
2.
Etiology of Neural Tube Defectss.
Ali Abdul Razzak Obed
3.
Epidemiology of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi
4.
Surgical Management of Neural Tube Defects.
Laith Thamer Al-Ameri
5.
Prevention of Neural Tube Defects in Iraq.
Mahmood Dhahir Al-Mendalawi
This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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