Conveyor belt systems facilitate the movement of goods and materials, making them an essential part of various fields. Deep learning control methods are therefore indispensable to assure their energy efficiency and optimal motor speed. Here, training is conducted via a convolutional neural network with transfer learning using VGG16 base net. Feature extraction layers are fixed, whilst fully connected layers are replaced. Thirty-three appropriate object classes are considered for classification, and images are acquired using an overhead camera. The obtained weight values are transmitted to Arduino that uses these data to control the stepper motor speed for optimal performance and minimum energy consumption, achieving approximate esti

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

Objective: To determine the ability of uVDBP to discern SRNS from steroid-sensitive nephrotic syndrome (SSNS) in Iraqi children. Materials and Methods: This cross-sectional study enrolled children with SRNS (n=31) and SSNS (n=32) from the pediatric nephrology clinic of Babylon Hospital for Maternity and Pediatrics over three months. Patients' characteristics in terms of demographics, clinical data, and urinary investigations were collected. Quantitative analysis of uVDBP levels was undertaken via a commercially available ELISA kit. Results: The median uVDBP values were significantly higher (p-value<0.001) in the SRNS group (median=10.26, IQR=5.91 μg/mL) than in the SSNS group (median=0.953, IQR=4.12 μg/mL). A negative correlati

     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

 
      The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca

This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria’s value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded fro

Cerebral palsy "is one of the diseases that afflict children, and it is a term given to the condition of a child who is exposed to a normal brain injury by accident due to its inability to grow or damage to the cells of the areas responsible for movement and knowledge of strength and balance during the stage of normal development." (116: 1999: 10) Cerebral palsy causes disruption in movement and posture due to damage to brain cells in areas that control and coordinate muscle tone, reflexes, strength, and movement. The degree and location of brain damage varies greatly between people with paralysis, as well as the severity of disability and symptoms, as they fall into severe to very simple, and cerebral palsy is one of the diseases that caus