The current research dealt with the rapid development of industrial product design in recent times, and this development in the field of design led to the emergence of modern trends in many terms and theories to direct greater interest in the cognitive foundations of design and its relationship with the components of other natural sciences, and despite the impressive technological development, nature remains With its content of formative values and structural dimensions, it is the first source of inspiration and the source of all modern mathematical sciences and theories, as God made them tend towards organization to continue to provide us with endless inspiration. Hence, the fractional one, which is an important part of dedicating the d

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Nowadays, due to our everyday stress and current stressful lifestyle, the loss of items appears a frequent issue and may be very inconvenient. In this regard, until the IoT becomes part of everyday life, we can use the software as an efficient tool to assist a person's searching, verifying, and finding lost belongings. This paper presents an Android-based application that we proposed and implemented to help users find lost items. Utilizing this software will enable the subscriber to record his request to the relevant authority. In addition, a special section offers to insert a contact telephone number or email to communicate between the person who found the item and the person who lost it. During testing, among other services, the p

Students in the twenty-first century need to find innovative ways to satisfy and respond to these learning requirements since they live in a visible world that is continuously surrounded by visual, technological stimuli. This is especially true of higher education. In order promote advancements in sustainable awareness, the project aims to include visual understanding in education (VUE) in higher education communication skills. An interview has been employed as a tool to accomplish the study's goal. The idea of Visual Understanding in Education (VUE) is one of the many novel or modern ways that has produced remarkable outcomes in a wide range of specialized sectors. Teachers may spread lessons of responsibility and consciousness by being aw

This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

This research has discussed the origins of ESP, addressed key notions about ESP and examined issues in ESP syllabus design. The content of the paper was determined by a need identified based on my  experience as an ESL instructor designing and delivering the content-based language program - Language Preparation for the Cadets and Employment in the Iraqi  College of Police . These issues, where possible, have been supported by current and pertinent academic literature. It is my sincerest hope that these observations will lend insight into the challenges facing the ESL instructor acting as ESP syllabus developer.

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m