In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.

Most researchers concentrate their studies on the design, stress and pressure distributions of the prosthetic socket. A little attention is considered for the stiffness of the various materials of the prosthetic sockets. Prosthetic laminated sockets in Iraq are costly to be manufactured while polypropylene socket is relatively cheap in comparing with the laminates.

Experimental study is conducted to compare the stiffness of five prosthetic sockets made of different materials. Compression, three point flexural and tensile tests are implemented by the Testometric machine. The laminate sockets give better results in compression than polypropylene. Polypropylene gives good results in bending compared with the laminate sockets. When t

KE Sharquie, MM Al-Waiz, AA Al-Nuaimy, Saudi medical journal, 2005 - Cited by 8

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At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena

In the last years of the twentieth century, scholars solidly focused on paradiplomacy as a study subject, linking it to federalism and decentralised systems. In the Arab world, which has 22 countries, a few states have adopted federalism or decentralisation. Only five countries, i.e., 22.7%, have adopted federalism and decentralised experience. Therefore, limited research and academic work has been conducted regarding paradiplomacy. This paper aims to research the relationship between federalism and paradiplomacy conceptually and practically and then analyse the Arab experiences in federalism and whether they applied paradiplomacy and succeeded in doing so. To explore that, the paper studies and compares the related articles of constitution

In the last years of the twentieth century, scholars solidly focused on paradiplomacy as a study subject, linking it to federalism and decentralised systems. In the Arab world, which has 22 countries, a few states have adopted federalism or decentralisation. Only five countries, i.e., 22.7%, have adopted federalism and decentralised experience. Therefore, limited research and academic work has been conducted regarding paradiplomacy. This paper aims to research the relationship between federalism and paradiplomacy conceptually and practically and then analyse the Arab experiences in federalism and whether they applied paradiplomacy and succeeded in doing so. To explore that, the paper studies and compares the related articles of constitution

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we