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 accurate solution for indoor robot navigation. The more accurate solution of the guide robotic system opens a new window of the self-localization system and solves the more complex problem of indoor robot navigation. It makes a reliable interface between humans and robots. This study successfully demonstrated how a robot finds its initial position inside a room. A deep learning system, such as a convolutional neural network, trains the self-localization system as an image classification problem. The robot was placed inside the room to collect images using a panoramic camera. Two datasets were created from the room images based on the height above and below the chest. The above-mentioned method achieved a localization accuracy of 98.98%.
A fluorescence microscopy considered as a powerful imaging tool in biology and medicine. In addition to useful signal obtained from fluorescence microscopy, there are some defects in its images such as random variation in brightness, noise that caused by photon detection and some background pixels in the acquired fluorescence microscopic images appear wrongly auto-fluorescence property. All these practical limitations have a negative impact on the correct vision and analysis of the fluorescent microscope users. Our research enters the field of automation of image processing and image analysis using image processing techniques and applying this processing and analysis on one of the very important experiments in biology science. This research
... Show MoreThe current research aims to identify the Vocational Self of the educational counselors as well as to identify the significant difference in the professional self according to the gender variable (male-female). The researcher adopted the scale of al-hasani (2015), which consisted of (34) items. It was applied to a sample of (300) school counselors (male-female) who were randomly selected from the six directorates in the Baghdad governorate for the academic year 2020/2021. The results showed that the research sample of educational counselors has a vocational self-concept. There are no statistically significant differences in the vocational self-concept between males and females among the educational counselors.
Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
... Show MoreA content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a
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This research aims at know the position of Al-Jassas Al- Hanafi (D. 370 AH) of "As-Sifat Al- Khbriya", through his interpretation: (the provisions of Qur'an), by studying his interpretation of the verses related to this issue.
The most significant results of this study that Al-Jassas did not consider the words that called: "As-Sifat Al- Khbriya" as adjectives to Allah almighty, but he consider them contained an inappropriate meaning to Allah almighty, thus it must be referred to the perfect arbitrator, so he was believe in opinion of interpretation. and interpretations of Al-Jassas for the related of the Qur'an verses relat
... Show MoreThe research aims to demonstrate the impact of TDABC as a strategic technology compatible with the rapid developments and changes in the contemporary business environment) on pricing decisions. As TDABC provides a new philosophy in the process of allocating indirect costs through time directives of resources and activities to the goal of cost, identifying unused energy and associated costs, which provides the management of economic units with financial and non-financial information that helps them in the complex and dangerous decision-making process. Of pricing decisions. To achieve better pricing decisions in light of the endeavor to maintain customers in a highly competitive environment and a variety of alternatives, the resear
... Show MoreThis research aims to identify the means and forms of interactive communication concerning Iraqi topics on the websites of global radio stations, namely Sawa and Monte Carlo. It also seeks to uncover the editorial and artistic interactions related to Iraqi topics on the selected websites chosen as the research sample, comparing them with the editorial interaction within the Iraqi context between the Radio Monte Carlo and Sawa websites.
The research yields several conclusions, including the following:
Iraqis focus their interaction with topics related to Iraq on Facebook for both Radio Monte Carlo and Sawa; Arabs show higher levels of interaction on Twitter with Radio Monte Carlo; Participants on the webs
In this paper normal self-injective hyperrings are introduced and studied. Some new relations between this concept and essential hyperideal, dense hyperideal, and divisible hyperring are studied.
The key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.
The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty