The impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills, Ayad Ali Hussein*, Israa Fouad Salih
The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
... Show MoreGlobal virtual teams (GVTs) are a recent organizational adaptation created to meet the needs of globalizatized marketplace. GVTs are essentially teams that are distributed across national boundaries and concerned through advanced information and communication technology (ICT) such as email, instant messaging, and video conferencing. The research on GVTs is important in the information system (IS) field because GVTs are dependent on information communication technology and the use of other technologies; GVTs also consists of people from different cultures. This paper tried to answer two research questions. The first one is: what are the GVTs problems facing the project manager (PM). A literature review was conducted to answer the fir
... Show MoreThe research studies the sculptural formation in the third millennium: styles and trends, by taking the most important results of sculpture in the third millennium. The problem of the research is to search for the new sculptural formation in what it constitutes of social and human importance, and what are the important factors in forming the contemporary sculptural structure, and what is the mechanism of showing and producing the new formation. The research requires the study of the most important thing that the (sculptural formation in the third millennium styles and trends) represents. The importance of research depends on the importance of the sculptural formation after the twentieth century and the importance that the for
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preparation process of performance evaluation in organizations is of extreme importance, and under development in organizations and the opening of markets and technological developments in the industry and heightened competition among industrial organizations imposed systems are built for performance give a clear picture about performance and competition, And centered research problem in answering the following questions: Is performance evaluation system is available in Wasit State Company for Textile Industries(Research sample ), This research aims to assess the performance of policies and programs in the company, according to guide performance evaluation of programs and policies prepared by the Dutch Cou
... Show MoreThe futuristic age requires progress in handwork or even sub-machine dependency and Brain-Computer Interface (BCI) provides the necessary BCI procession. As the article suggests, it is a pathway between the signals created by a human brain thinking and the computer, which can translate the signal transmitted into action. BCI-processed brain activity is typically measured using EEG. Throughout this article, further intend to provide an available and up-to-date review of EEG-based BCI, concentrating on its technical aspects. In specific, we present several essential neuroscience backgrounds that describe well how to build an EEG-based BCI, including evaluating which signal processing, software, and hardware techniques to use. Individu
... Show MoreMonaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
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