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Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Mon Apr 03 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
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Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless 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

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Publication Date
Sun Dec 31 2023
Journal Name
Biomedical And Pharmacology Journal
Extraction, Isolation and Structure Elucidation of Two Phenolic Acids from Aerial Parts of Celery and Coriander
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Celery and coriander are vastly applied in modern medicine and traditionally because various medicinal and nutritional benefits depend on their medicinal characteristics. The study aimed to detect, isolate and compare extracts contents of phenolic acids (caffeic and p-coumaric acids) in ethyl acetate fraction of fresh and dry aerial parts of coriander (Coriandrum sativum L.) and celery (Apium graveolens L.) of the Apiaceae family. The extraction of these constituents was carried out by maceration method using 70% ethanol and fractionation was done by using petroleum ether, and ethyl acetate. The existence of caffeic and p-coumaric acids in aerial part extracts of two plants was identified by thin-layer chromatography (TLC) and high-

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Ecological Engineering
Calibration and evaluation of aquacrop for maize (Zea Mays L.) under different irrigation and cultivation methods
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rop simulation models play a pivotal role in evaluating irrigation management strategies to improve water use in agriculture. The aim of this study is to verify the validity of the Aquacrop model of maize under the surface and sprinkler irrigation systems, and a cultivation system, borders and furrows, and for two varieties of Maze (Fajr and Drakma) At two different sites in Iraq, Babylon and Al-Qadisiyah governorates. An experiment was conducted to evaluate the performance of the Aquacrop model in simulating canopy cover (CC), biomass (B), dry yield, harvest index (HI), and water productivity (WP). The results of RMSE, R2, MAE, d, NSE, CC, Pe indicated good results and high compatibility between measured and simulated values. The highest a

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Comparison of Single and Group Jet Grout Columns Settlement Based on Field Test and Theoretical Methods
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Abstract<p>The settlement evaluation for the jet grouted columns (JGC) in soft soils is a problematic matter, because it is influenced by the number of aspects such as soil type, effect mixture between soil and grouting materials, nozzle energy, jet grouting, water flow rate, rotation and lifting speed. Most methods of design the jet-grouting column based on experience. In this study, a prototype single and group jet grouting models (single, 1*2, and 2*2) with the total length and diameter were (2000 and 150 mm) respectively and clear spacing (3D) has been constructed in soft clay and subjected to vertical axial loads. Furthermore, different theoretical methods have been used for the estimation </p> ... Show More
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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Educational And Psychological Researches
Teaching methods approved in the university and its relationship to classroom discipline and management proposals treated
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The study aims detection teaching modalities adopted relationship in Jerash University exactly the classroom, and to achieve the goal of the study was to develop a questionnaire consisting of (39) items, and was achieving validity and reliability have, then sent to a sample of professors made up the university from (122) university professor of the total (172) professor, and they study population.

     Study found a relationship between the teaching methods of the four their strategies with classroom management, and as a result the overall average level, while Hspt critical thinking at the highest correlation with classroom discipline management relationship strategy, while the relatio

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
MATERNAL AND FETAL OUTCOMES IN EMERGENCY VERSUS ELECTIVE TWO OR MORE PREVIOUS CAESAREAN DELIVERIES
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Background: Women with previous two or
more caesarean deliveries are usually
managed by elective cesarean section to avoid
the possible risks of labor.
Objective: To compare the relative risks of
maternal and fetal outcomes in emergency
versus elective previous two or more
caesarean deliveries
Design: Randomized prospective clinical
study
Setting: Al-Elweya Maternity Teaching
Hospital, from 1st of March to 31st of
September 2008.
Methods: The study groups, those who had
previous two or more caesarean deliveries,
were included from the hospital admissions.
The 1st group (102 women) presented in labor
and was managed by caesarean delivery as
soon as it was possible. The second group (7

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