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Effect Of Technology Based Learning As A Supplement To Traditional Technology On Student's Achievement
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This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures. This paper studies the effect of using relatively new technology appearing in classroom today which is real time response system (voting system), that serves as real – time windows into each students understand of concepts. These devices can provide a foundation decision making based on data at scale never before possible as well as increasing students learning and engagement with each other as well with the lecturer, also, another new technology the "Bluetooth broadcasting system" is applied which is one of the moderate technique towards M- learning, this tool is used to transfer audio, video, text, notes, etc to the mobile of the students as well as laptop. The computer based examination, interactive board, and notepad as well as free wire and wireless internet access are used to close the digital divide and increasing technology literacy in all students which was one of the challenges, additional challenges include “social loafing,” characterized by
students who work less diligently than they otherwise might, or who become frustrated by course material or technology and thus less engaged. Finally the other colleague's resistance to the use of technology in learning and its effect on students learning is discussed based on practical situations.

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Mon Apr 08 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Bifurcation analysis of the role of good and bad bacteria in the decomposing toxins in the intestine with the impact of antibiotic and probiotics supplement
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This study presents a mathematical model describing the interaction of gut bacteria in the participation of probiotics and antibiotics, assuming that some good bacteria become harmful through mutations due to antibiotic exposure. The qualitative analysis exposes twelve equilibrium points, such as a good-bacteria equilibrium, a bad-bacteria equilibrium, and a coexisting endemic equilibrium in which both bacteria exist while being exposed to antibiotics. The theory of the Sotomayor theorem is applied to study the local bifurcation around all possible equilibrium points. It’s noticed that the transcritical and saddle-node bifurcation could occur near some of the system’s equilibrium points, while pitchfork bifurcation cannot be accrued at

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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Publication Date
Thu Jun 27 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Impact of Gliclazide Modified Release or Glimepiride as Add-on Therapy to Metformin on Glycemic and Oxidative Stress Parameters in Type 2 Diabetic Patients
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Background: Type 2 diabetes mellitus is a condition characterized by an elevation of oxidative stress, which has been implicated in diabetic progression and its vascular complications. Aim: Assessing the impact of gliclazide modified release (MR) versus glimepiride on oxidative stress markers, glycemic indices, lipid profile, and estimated glomerular filtration rate in uncontrolled type 2 diabetic patients on metformin monotherapy. Methods: This was an observational comparative study conducted in Thi-Qar specialized diabetic, endocrine, and metabolism center. Sixty-six patients were randomized into two groups based on the addition of the sulfonylureas (SUs). Group 1 (33 patients) was on gliclazide MR, whereas Group 2 (33 patients)

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Publication Date
Fri Apr 01 2016
Journal Name
Al–bahith Al–a'alami
Indicators of Mental image among Students of the University of Baghdad about Iraqi Political Parties-(a research based on a master thesis)
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Media studies have focused mostly on the issue of the mental image because the image that is formed in the mind has become not only a photo of a human being and having kept for himself. This image has an outside influence which may sometimes up to the formation of the fate of others and it sometimes includes individuals and groups together.
This study comes in the context of identifying the image of Iraqi political parties among Iraqi university students and the nature of the view that students have in their minds about these parties.
Chapter one includes the problem of the research, the importance of the study, the goals and method used. Chapter two is divided into two sections: section one deals with the concept of the mental i

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Publication Date
Wed Feb 14 2018
Journal Name
International Journal Of Science And Research (ijsr)
Effect of the Active Thinking Model in the Achievement of Students of the Fifth Grade Applied Science of Physics and Their Pivotal Thinking
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The aim of the current research is to identify the effect of the active thinking model in the achievement of students of the fifth grade applied science of physics, and their pivotal thinking by verifying the two zero hypotheses, where there is no significant difference at the level of significance (0.05) between the average scores of the experimental group who studied physics using the active thinking model and the average scores of the control group students who studied the same material in the usual way in the achievement test, as well as in the pivotal thinking test. The research sample consisted of (77) students of the applied fifth grade students in two divisions (a) and (b), randomly selected (a) to be the experimental group, and (b)

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
Aesthetics Contents of Data Visualization as an Input to its humanization
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The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

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Publication Date
Wed Mar 01 2000
Journal Name
Al-rafidain Collage Conference
The Modification of Median Filter to use as noise reduction procedure
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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Responding Wheat and Weeds for Seeding Rates and Herbicide as Well Its Effect on Yield and Yield Components
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Abstract<p>A field experiment was carried out during the seasons 2016 and 2017 in the farm of the Department of Field Crops Science, College of Agricultural Engineering Sciences-University of Baghdad to evaluate the effect of(Aminopyralid + Flurasulam, Coldinafop-propargyl and Flucarbazone-sodium) herbicides and seeding rate (100, 125 and 150) Kg.ha<sup>-1</sup> and the interaction between them in growth characteristics, grain and yield components in wheat (Var. IPA99). The results showed that herbicides used were significantly efficient in studied characteristics compared to weedy treatment. Herbicide Flucarbazone-sodium gave higher weed control after 60 and 90 days of spraying the he</p> ... Show More
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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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