Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

Sustainable development (SD) is an improvement that meets present needs but jeopardizes the ability of new populations to do the same. It is vital to acquaint EFL students with the terminology and idiomatic expressions of this discipline. Nowadays, sustainable development and the environment have been prioritized in every aspect of life. Since culture and the teaching of Foreign language English cannot be separated, the English language becomes the mean of communication in health, economics, education, and politics. Thus, integrating sustainable development goals within language learning and teaching is very important. This descriptive quantitative study aims to investigate the perception of EFL pre-service teachers of sustainable develo

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

 Abstract

It considers training programs is an important process contributing to provide employees with the skills required to do their jobs efficiently and effectively, so it should be concerned with and the focus of all government our organizations, and perhaps the most important reasons that I was invited to select the subject (evaluation of training programs directed toward the diagnosis of the phenomenon of financial and administrative corruption) It is the importance of those programs working in the regulatory institutions General and the Office of Inspector General of Finance and the Ministry particularly for employees because of their role in the development of their skills and their experience and their beha

Purpose: The purpose of this study was to clarify the basic dimensions, which seeks to indestructible scenarios practices within the organization, as a final result from the use of this philosophy.

Methodology: The methodology that focuses adoption researchers to study survey of major literature that dealt with this subject in order to provide a conceptual theoretical conception of scenarios theory  .

The most prominent findings: The only successful formulation of scenarios, when you reach the decision-maker's mind wa takes aim to form a correct mental models, which appear in the expansion of Perception managers, and adopted as the basis of the decisions taken. The strength l

In this paper, the problem of scheduling jobs on one machine for a variety multicriteria
are considered to minimize total completion time and maximum late work. A set of n
independent jobs has to be scheduled on a single machine that is continuously available from
time zero onwards and that can handle no more than one job at a time. Job i,(i=1,…,n)
requires processing during a given positive uninterrupted time pi, and its due date d
i.
For the bicriteria problems, some algorithms are proposed to find efficient (Pareto)
solutions for simultaneous case. Also for the multicriteria problem we proposed general
algorithms which gives efficient solutions within the efficient range

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load applied on a footing resting on sandy soil at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into consideration include loading frequency, size of footing and different soil conditions. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used. The footings were tested by changing all parameters at the surface and at 50 mm depth below model surface. Meanwhile, the investigated paramete