Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

Receipt date:6/3/2021  acceptance date:4/5/2021 Publication date:31/31/2021

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The research in the role of variables contact for non-state actors have become more influential in the current of contemporary events, that related with the reality of seeking services and providing all of that in favor of maintaining the social peace, and ensuring its empowerment in order to make peace and stability outcomes as a real fa

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

  To identify the importance of the role of succession planning in developing human capital in organizations in light of the accelerating and dynamic events and changes in the work environment, and the research problem indicated the seriousness of employees retiring or leaving their positions for any reason and the extent of its impact on the organization in creating gaps in leadership and problems In managing the talent injection because there will be a shortage of talent, which in turn will affect the general performance of the business in the researched institute, so the importance of research appears in trying to present a set of solutions through which some of the problems facing the organization in quest

Polycystic ovary syndrome (PCOS) is the most endocrine problem in women of regenerative age. PCOS women typically belong to an age and sex group which is at higher risk for severe coronavirus disease (COVID-19). COVID-19 targets cells through angiotensin-converting enzyme 2 (ACE2) receptor presents on cells in veins, lungs, heart, digestion tracts, and kidneys. Renin-Angiotensin System (RAS) over activity has likewise been described in metabolic disorders; type 2 diabetes mellitus (T2DM), and conditions shared by women with polycystic ovary condition. The point of this study is to know the job of renin and ACE2 in PCOS and coronavirus and its relationship with hormones and other metabolic parameters related. The study groups consist of 1

The aim of this study is to look at  the potential of a  local sustainable energy network in  a pre-existing context to develop a novel design beneficial to the environment. Nowadays, the concept of smart cities is still in the developmental phase/stage   andwe are currently residing in a transitional period, therefore it is very important to discover new solutions that show direct benefits the people may get from  transforming their city from a traditional to a smart city. Using experience and knowledge of successful projects in various European and non-European smart cities, this study attempts to demonstrate the practical potential of gradually moving existing cities to t

 This paper aims to verify the existence of relationships between product innovation and the reputation of the organization. The study problem is that the State Organization for Marketing of Oil (SOMO) system is inflexible in terms of marketing procedures and needs innovative, unconventional methods in innovating its products and improving performance. The reputation of the organization. The importance of the study lies in that it is an attempt to raise the interest of SOMO in its approach to the research variables in order to enhance its competitive position in the future and improve the marketing business environment, which contributes to enhancing the reputation of the organization by product innovation. The study sample

Abstract As the United Nations approaches its 70th anniversary, the world is going through the most severe accumulation of serious international security failures in recent memory, challenging the UN Security Council’s ability to address them effectively. Over the past four years, crises in Libya, Syria and Ukraine have precipitated a worrisome erosion of great power relations that has complicated Security Council decision making on a number of trouble spots. Its inability to devise consensus responses to the escalating civil war in Syria has been particularly troubling, resulting in the regional spill over into Iraq and the emergence of Islamic State as a new threat to peace in the region and beyond. Meanwhile, the UN’s often under

This purpose of the research is to test liquidity ratios to assess bank liquidity risks represented by liquidity ratios (current assets / current liabilities, current assets / total deposits, current assets / total assets, cash credit / total deposits, liquidity coverage ratio LCR, net stable financing ratio NSFR). This research involves evaluating these risks in banks via these ratios, and reveal the most important means used to solve these risks, including the capital adequacy ratio under the Basel II decisions and for selected period (2017-2019).The research reached the most important conclusion, which is the bank sample did not fall into bank liquidity risks throughout the years of research. Tracking specific ratio with adequ

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F