Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

ABSTRACT

The research aims to know the reality of a two examined variables at the organization studied identifying the relationship between managerial processes reengineering and organizational citizenship behavior. The research applied on the Electronic Manufacturing Company encompassing a sample of managers and employees consisted of (100) individuals. A questionnaire is the main instrument for data gathering, which has been included (45) questions as well as personal interviews to support the questionnaire's questions and to achieve greater realism for collecting information.

Answers were analyzed to reach the final results through the use of a number of statistical methods via

The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

In this paper we introduce a new type of functions called the generalized regular
continuous functions .These functions are weaker than regular continuous functions and
stronger than regular generalized continuous functions. Also, we study some
characterizations and basic properties of generalized regular continuous functions .Moreover
we study another types of generalized regular continuous functions and study the relation
among them

In Libya, there are multiple sources of pollution, one of which is animal waste. The anaerobic digestion (AD) of organic wastes to produce biogas has the advantage of producing valuable, renewable energy while reducing the environmental impact of these wastes. Cowmanure have the potential to produce biogas due to their high organic content. This study aimed to study different concentrations for the feedstock (1:1 and 2:1 cow manure: water v/v) to monitor which one gives higher biogas production. A plastic tank with a capacity of 72 liters and a feedstock volume of 60 liters was used to create a pilot scale. The biogas was analyzed using a GC device at the end of the experiment in the Zawiya Oil Refining Company. The result indicated that th

  The study was conducted to evaluate the effect of essential oil extracted from yellow peels of Citrus aurantium on the radial growth of all fungi.  Penicillium expansum, Aspergilus flavus and Fusarium oxysporum.              The results showed significant gradual reduction of the surface growth of fungi, P. expansum and A. flavus was more affected by the essential oil, while  F. oxysporum  showed less sensitivity towards the essential oil. The reaction of growth was inconcommitant with increasing concentrationsof oil, reaching concentration of (5)% which showed complete inhibition.

Due to its various resistance mechanisms, Pseudomonas aeruginosa is the most prevalent opportunistic infection that kills hospitalized patients. Thus, therapeutic options become limited. Objective: The study aimed to estimate the antibiofilm effectiveness of Conocarpus erectus leaf extracts against MDR P. aeruginosa isolates and examines pelA and algD gene expression. Subjects and Methods: One hundred-fifty clinical samples were collected from five Baghdad hospitals between September 2021 and January 2022. Samples were grown on different mediums. Despite cetrimide agar's ability to detect P. aeruginosa, only 83 isolates developed at 42°C. VITEK 2 compact system identification followed. This study examined 83 of P. aeruginosa isolates for r

This study was aimed to investigate the effect of essential oil extracted from the yellow peels of Citrus aurantium on the growth of four species of fungi: Penicillium expansum, Penicillium oxalicum, Fusarium oxysporum and Fusarium proliferatum and effect of one fungicide: Aliette (fosetyl-aluminum) against these fungi. The results showed that the essential oil of C. aurantium inhibited the radial growth of P. oxalicum at concentration 4.5% while P. expansum and F. oxysporum at concentrations 5% and F. proliferatum at concentrations 5.5% additionally the one fungicide tested showed inhibitory effect on radial growth of these fungi. So that there is a negative relationship between the increasing of concentration and radial growth of fungi.

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo