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New Trends in Teaching and Learning Theory Dr. Jasim Muhammad Abdul- Slamy
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New trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teaching is an intended activity. Education is the
process of acquiring knowledge, skills and trends by the person who wants to learn
himself / herself. Accordingly, learning is a principal branch of teaching, because it is
considered one of the varied methods in carrying out the teaching process. From this
fact did the need to use a good theory as a guide to the later researches come. Its value
depends highly on the studies and researches it produces to help the researcher find a
way that direct him to discover new aspects.
* The Research purpose:
This research aims at knowing the new trends and methods in the theory of
teaching and learning.
* The Research Boundary:
This research is limited to: finding out the theory of teaching and learning and
putting a balance between them. In addition to discovering the features and methods
of building the teaching theory. Moreover, it aims at putting a limit to the role played
by the theory in the teaching and learning process.
Specifying terminology:
Terms concerning teaching and learning are specified in the research itself.

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Publication Date
Wed Dec 30 2020
Journal Name
Journal Of Planner And Development
"2030 City Tour". New paradigm for intervention in the XXI century cities
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THE ACTUAL SOCIETY MODEL

Our society model has been showing signs of exhaustion since the end of the XX century. The recent appearance of the Covid-19 virus is another consequence of humanity's distance from Nature and the environment it inhabits. Also, climate change, environmental deterioration, loss of biodiversity, overexploitation of natural resources, and social inequality are some of the consequences derived from this separation between society and Nature. We must change our operating habits. Inevitably from a society based on the market, hyper consumption, fossil energy and individual enrichment at all costs, we will have to change to another

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Publication Date
Thu Nov 23 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
New Record of the Species Amegilla niveocincta (Smith, 1854)(Hymenoptera:Apidae) in Iraq
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Publication Date
Sun Jul 01 2012
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NEW RECORD OF PREDATOR MELANTHRIPS PALLIDIOR PRIESNER (THYSANOPTERA: MELANTHRIPIDAE) IN BAGHDAD - IRAQ
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The predator Melanthrips pallidior Priesner regarded as a new record in Baghdad. The specimens were collected from alfalfa field during April 2010 to April 2011 in Abu-Gharib. Morphological characters of different body parts were studied and compared with other specimens by using taxonomic keys.

 

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Publication Date
Sat Aug 01 2015
Journal Name
Modern Applied Science
A New Method for Detecting Cerebral Tissues Abnormality in Magnetic Resonance Images
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We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

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Publication Date
Thu Dec 01 2022
Journal Name
Wiadomości Lekarskie
EVALUATION OF TWO CRYOPROTECTANTS USED IN A NEW HUMAN SPERM CRYOPRESERVATION TECHNIQUE
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The aim: To examine the efficiency of different concentrations of Dimethyl sulfoxide (DMSO) and glycerol as a cytoprotectants in protection of human sperms during cryopres¬ervation in this technique. Materials and methods: Thirty oligozoospermic semen samples were used in this study. Samples diagnosed according to WHO 2010 criteria. Sheep’s ovarian follicles obtained from local slaughterhouse and prepared by slicing the ovaries and evacuating the follicular fluid and oocyte. Each semen sample divided into six equal parts, and diluted 1:1 with cryosolution contains 5%, 10%, 15% DMSO or glycerol and injected within the emptied follicles. After freezing and thawing, the semen mixture aspired outside the follicles and sperm concentr

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Publication Date
Tue May 10 2016
Journal Name
International Journal Of Current Microbiology And Applied Sciences
New Record of Liriomyza trifolii (Burgess, 1880) (Diptera; Agromyzidae) in Baghdad, Iraq
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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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

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Crossref (1)
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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