In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

Background: Accurate measurement of a patient’s height and weight is an essential part of diagnosis and therapy, but there is some controversy as to how to calculate the height and weight of patients with disabilities. Objective: This study aims to use anthropometric measurements (arm span, length of leg, chest circumference, and waist circumference) to find a model (alternatives) that can allow the calculation of the height and the body weight of patients with disabilities. Additionally, a model for the prediction of weight and height measurements of patients with disabilities was established. Method: Four hander patients aged 20-80 years were enrolled in this study and divided into two groups, 210 (52.5%) male and 190 (47.5%) fe

Background: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.

Aim of the study:  Role of p110-beta as well as and CDK 1  in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.

Type of the study: is a retrospective study

Methods: This retr

One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

The bubbled slab, a type of reinforced concrete (RC) slab with plastic voids, is an innovative design that employs a biaxial distribution of voiding formers within the slab to reduce the slab’s self-weight while preserving a load-carrying capacity that is approximately comparable to that of solid slabs. This paper presents a new approach for figuring out the effective critical shear perimeter of voided slabs using the reduced-volume concept of concrete. This approach aims to reduce the coefficient of variation of the current design standards, namely the ACI 318-19 and Eurocode 2, for assessing the slabs’ resistance to punching shear. Our experimental program investigated the impact of voiding former patterns and the location of