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%.
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreThis study investigates self-perception and self-branding on Instagram among young Arab women in the UAE, focusing on how they curate, negotiate and perform their digital identities and whether their digital self-presentation in any way compromises their sense of authenticity. The study is based on 11 interviews with young women in the UAE, between the ages of 20 and 30, in addition to online observation to follow the participants’ activities on Instagram. The study demonstrates that while social and digital media platforms may play a role in “empowering” Arab women, women tend to set their boundaries of authenticity shaped according to their audience’s expectations and their in-groups. This confirms the r
... Show MoreMetaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreA new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
... Show Moreمشكلة البحث وأهمية:-
أن بناء الشخصية القادرة على التفاعل والتأثير في معطيات الحضارة ، والتقدم في مسالكها المتطورة ، بات هدفا لكل مجتمع يريد الوصول إلى مصاف الدول المتقدمة
(رسول ، 1984، ص7) وبالأخص في مجتمعنا الذي يمتلك مقومات المجتمعات المتحضرة ، فظهر الاهتمام بالدوافع التي تدفع الأفراد نحو مزيد من العطاء والإنجاز وتساعد في بناء شخصية قوية قادرة على تحقيق ما تصبو أليه من أهداف وطموحات ، ومتمتعة
Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreThere are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
Programs directed to children through the media in general and in television in particular are among the main factors that help in forming the cultural and educational values of this important segment of society, and in light of this the study problem was identified in answering a major question: What are the cultural and educational values that Ajyal channel seeks Space planted in children through my program, Iftah Ya Simsim (in its new season) and Friends of Ajyal? , While the objectives of the study were evident in identifying the most prominent cultural and educational values that the Ajyal satellite channel worked to instill in children, and identifying the nature of the techniques used by Ajyal channel in providing the value conten
... Show MoreAl- belenoby , Andalusian obscure poet .I choose to study poetic rhythm in this poetic and the appropriateness of with what rhythm touring in his self to give beautiful meaning raise to receiver to put the hands of continental placements creativity in poetry .I divided my research into ideas are presented in a sequential manner , I started researching with poetic rhyme than rhyme they represent the form of the poem, they represent the external form of the poem and their music that farm the general concept then the rhetorical styles that represent the internal form of the poem and it music that the listener works and enjoying it part by part all this led to the put the hands of the receiver placement creativity in Belenoby Poet.&nbs
... Show More