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. The developed on-board DT offered a model where interaction with the unknown payload and aerial robot dynamics is informed. Beside this, the results showed the ability of the introduced DT to foretell the conditions of the forces acting on the payload which helped to predict the situation of aerial manipulation process. Additionally, the results showed that the DT model could detect real-time errors in the physical asset.
This study was conducted to test the effectiveness of Agaricus bisporus inoculums (spawn) in the ratio of (0.25, 0.5 and 1%) v/v to control Pythium aphanidermatum fungus the causal agent of damping- off disease of cucumber plant. results showed the ability of A. bisporus fungus to protect the seedlings from incidence by P. aphanidermatum . all treatments of edible fungus inoculums were significantly different from pathogen treatment after 15 day of planting and there was no significant difference found from control treatment (without pathogen) . the successful of A. bisporus was continued to protect the seedlings after 30 and 45 day after planting. The numbers of seedlings were (8, 7.25 & 7.25) respectively compared to 5.5 seedlings in con
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This study aims to identify the extent to which the criteria of the American Council for Teaching Foreign Languages (ACTFL) are included in the English language books for the fifth and sixth graders. To achieve the objective of the study, a content analysis card was prepared, where the classification of language proficiencies was divided into five main levels (beginner, intermediate, advanced, superior, and distinguished) of the four language skills (listening, speaking, reading, and writing), The content analysis card consisted of (89) indicators distributed at the four levels of language skills as follows: Listening (17), speaking (33), reading (15), and writing (26). The study sample consisted of Engl
... Show MoreBackground:Â Various fluids in the oral environment can affect the surface roughness of resin composites. This in vitro study was conducted to determine the influence of the mouth rinses on surface roughness of two methacrylate-based resin (nanofilled and packable composite) and siloraine-based resin composites.
Materials and methods: Disc-shaped specimens (12 mm in diameter and 2mm in height) were prepared from three types of composi
... Show MoreThe research aimed to study the job satisfaction of the staff of the Federal board of supreme Audit and its relation to the effectiveness of their performance, The questionnaire was adopted as a main tool in the collection of data and information from a random sample of (54) employees of the Federal board of supreme Audit. In light of this, the data were collected and analyzed and the hypotheses were tested using the statistical program (SPSS).
The researchers reached a number of conclusions, the most important of which were: (1) the respondents' response to the variables of job satisfaction and the effectiveness of the performance were medium; (2) there was a significant relationship between job satisfaction and performance effe
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreDust 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
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show MoreThe investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
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