Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing items in images.This article, will be focusing on comparing the main differences among the YOLO version's Architecture, and will discuss its evolution from YOLO to YOLOv8, its network architecture, newfeatures, and applications. Itstarts by looking at the basic ideas and design of the first YOLO model, which laid the groundwork for the following improvements in the YOLO family. In additionally, this article will provide a step-by-step guide on how to use the YOLO version architecture, Understanding the primary drivers, feature development, constraints, and even relationships for the versions is crucial as the YOLO versions advance.Researchers interested in object detection, especially beginning researchers, would find this paper useful and enlightening
The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co
... Show MoreThe main factors that make it possible to get the corrosion of reinforcing steel in concrete are chloride ions and the absorption of carbon dioxide from the environment, and each of them works with a mechanism which destroys the stable immunity of rebar in the concrete. In this work the effect of carbon dioxide content in the artificial concrete solution on the corrosion behavior of carbon steel reinforcing bar (CSRB) was studied, potentiostatically using CO2 stream gas at 6 level of concentrations; 0.03 to 2.0 weight percent, and the effect of rising electrolyte temperature was also followed in the range 20 to 50ᴼ C. Tafel plots and cyclic polarization procedures were obeyed to investigate the c
... Show MoreThe research aims to shed light on the role of artificial intelligence in achieving Ambidexterity performance, as banks work to take advantage of modern technologies, artificial intelligence is an innovation that is expected to have a long-term impact, as well as banks can improve the quality of their services and analyze data to ensure that customers' future needs are understood. . The Bank of Baghdad and the Middle East Bank were chosen as a community for the study because they had a role in the economic development of the country as well as their active role in the banking market. A sample of department managers was highlighted in collecting data and extracting results based on the checklist, which is the main tool for the stu
... Show MoreBackground: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, an
... Show MoreBackground: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreThe aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette
... Show MoreEnergy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit
... Show MoreThis paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an
Fatty Acid Methyl Ester (FAME) produced from biomass offers several advantages such as renewability and sustainability. The typical production process of FAME is accompanied by various impurities such as alcohol, soap, glycerol, and the spent catalyst. Therefore, the most challenging part of the FAME production is the purification process. In this work, a novel application of bulk liquid membrane (BLM) developed from conventional solvent extraction methods was investigated for the removal of glycerol from FAME. The extraction and stripping processes are combined into a single system, allowing for simultaneous solvent recovery whereby low-cost quaternary ammonium salt-glycerol-based deep eutectic solvent (DES) is used as the membrane phase.
... Show More