<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in undesirable places to transmit live video with a moving camera and process it by the YOLOv5 model. Also, the robot system can receive images, videos, or YouTube links and process them with YOLOv5. Raspberry Pi is controlled remotely by connecting to the network through Wi-Fi locally or publicly using the internet with a remote desktop connection application. The results were very satisfactory and proved the high-performance efficiency of the robot.</span>
Green buildings are considered more efficient than traditional buildings due to the incorporated techniques and the multidisciplinary specializations required to comply with their specifications, in addition to the advanced commissioning, which undergoes before handing over the buildings to the owners to ensure requirements conformance. As a result, the appropriate selection of a project delivery system acts as the essential factor that affects the performance of the project. This research aims at building a system that helps to select the best method to implement green buildings. Through studying the recent research approaches in project delivery systems, the factors that affect the selection of the optimal implementation method fo
... Show MoreThis work represents implementation and investigation of optical coherent communication system between two computers. A single mode optical fiber is selected as transmission medium. The data are sent via the RS-232 standard interface with a bit rate of 9.6 kbps from personal computer (PC1) by line receive to convert the data from electrical levels (-12/+12 V) into TTL level (0/5 V). The modulation of this data was accomplished by internal modulation using laser diode type (HFCT-5208M) 1310 nm wavelength. The optical D-coupler was used to combine the optical signal that come from laser source with optical signal of laser local oscillator (OTS-304XI) at 1310/1550 nm wavelength to obtain coherent (homodyne and heterodyne) detection respective
... Show MoreFinding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over
... Show MoreThis paper describes the digital chaotic signal with ship map design. The robust digital implementation eliminates the variation tolerance and electronics noise problems common in analog chaotic circuits. Generation of good non-repeatable and nonpredictable random sequences is of increasing importance in security applications. The use of 1-D chaotic signal to mask useful information and to mask it unrecognizable by the receiver is a field of research in full expansion. The piece-wise 1-D map such as ship map is used for this paper. The main advantages of chaos are the increased security of the transmission and ease of generation of a great number of distinct sequences. As consequence, the number of users in the systems can be increased. Rec
... Show MoreIn this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa
... Show MoreIn this research design was treated gap laser mathematically and practically Bashaddam model Raasi simple and new and we have found that there is a good match in the practical and theoretical results
Abstract
The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one
... Show MoreThe aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth. Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment. Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return
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