The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conversely, when using the maximum-likelihood classifier, the highest accuracy (83.06%) was achieved with FLAASH. The results demonstrate significant variations in accuracies for different land cover classes, which emphasizes the importance of per-class accuracy. The results highlight the critical role of preprocessing techniques and classifier selection in optimizing the classification processes and land cover mapping accuracy for remote sensing geospatial applications. Finally, the actual differences in classification accuracy between processing levels are larger than those given by the confusion matrix. So, the consideration of alternative evaluation methods with the absence of reference images is critical.
Toxoplasmosis is a widespread infection usually caused by Toxoplasma gondii (T. gondii) parasite. It occurs in humans and other warm blooded animals, causing severe problems. It was found that there is an alteration in the trace elements concentrations levels associated with some human diseases. This study aimed to investigate the changes in the concentrations of some trace elements (Mg, Fe , Zn, and Cu) in the sera of 60 immunocompetent patients with chronic toxoplasmosis and 82 healthy individuals as a control group. Measuring the serum level of seropositivity rate of anti-T. gondii antibodies was done by Enzyme Linked Immunosorbent Assay (ELISA) Kit, while the concentrations of trace elements were measured by absorption spectrophotometry
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Background: The estimation of ferritin and related variables by complete serum iron profile, for Iraqi hashimoto’s patients to see the effect of thyroid hormone insufficiency, which may lead to deficiency of ferritin iron stores, this may be quite useful during the diagnosis and treatment of hashimoto’s patients. Patients and Method: The study was performed at National Center of Teaching laboratories of Medical city institute in Baghdad. Fifty newly diagnosed patients with hashimoto’s and forty apparently healthy controls. Diagnosis based on thyroid profile analysis including:Thyroid Stimulating Hormone (TSH), Thyroxine (totalT4) and Triiodothyronine (total T3), estimation of antibodies against thyroperoxidase, iron profile including:
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MB Mahmood, BN Dhannoon
The importance of the research is evident in the use of exercises with the training device, which is one of the modern techniques in teaching the abilities of players, especially in teaching the skill of the backhand, and in improving the accuracy of the performance of players and increasing the contribution to the formation of a base for the game for players who have a good level of learning and upgrading the game to reach a certain achievement, and the research issue was represented in the lack of accuracy in sending balls to the required areas to achieve points, especially in the performance of the skill of the backhand due to the speed of play during the course of the match, and the study aimed to introduce modern technology usi
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The study aimed to identify the social support and its relation with death anxiety for
olds who are listed at the Palestinian ministry of social affairs in the Jerusalem governorate,
the researcher uses the descriptive method and she bases her research on two types of
criterion: the social support and the criterion of death anxiety, these two criterion are applied
on a stratified random sample, amounted to (184) of the elderly.
The results show no statistical differences in the level of social support for olds who
are listed at the Palestinian ministry of social affairs according to the variables of sex.
Whereas there are statistical differences in the level of social support for those olds according
to the variab
Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MorePlane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
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