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jperc-908
Developing Undergraduate Students' Geography Learning Skills during Fieldwork and Their Attitude toward It: Developing Undergraduate Students' Geography Learning Skills during Fieldwork and Their Attitude toward It
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Abstract

This study identified the developing of a range of students' geography learning skills and the change in their attitudes toward fieldwork as a consequence of leaning experiences that occurred within a field trip. The sample of the study consisted of (27) students within a special topic course enrolled in Geography Department at Umm Al-Qura University in Saudi Arabia in semester 2, 2018. A range of students' geography learning skills were measured by the skills questionnaire that consisted of 12 geography skills after completing field work. Changes in students' attitudes towards fieldwork was measured through a modified version of Boyle et al.'s (2007) attitudes instrument at the beginning and at the end of the field trip. Interviews were used to enhance the studies' instruments as a data gathering technique. The findings of the study showed that students developed the all geography learning skills, where more than 95% of students felt that they developed their basic problem solving, sampling, measuring & recording, survey methods, information gathering, data analysis, safety and communication & transferable skills. While 92% of students developed observation and integration skill, 90% developed identification skills, 89% developed experimental design skill, and finally, 76% developed interpretation skill. The students increased their enjoyment (t=12.77, p<0.001) as a consequence of doing fieldwork. A similar result was produced for collaboration (t=14.44, p<0.001) over the field trip. The students' responses of interviews questions supported quantitative results.

Keywords: developing, undergraduate students, fieldwork, geography-learning skills, attitudes.

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Publication Date
Sat Jun 01 2024
Journal Name
Partial Differential Equations In Applied Mathematics
Improving the hepatitis viral transmission model’s dynamics by vaccination and contrasting it with the fractional-order model
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We investigate mathematical models of the Hepatitis B and C viruses in the study, considering vaccination effects into account. By utilising fractional and ordinary differential equations, we prove the existence of equilibrium and the well-posedness of the solution. We prove worldwide stability with respect to the fundamental reproduction number. Our numerical techniques highlight the biological relevance and highlight the effect of fractional derivatives on temporal behaviour. We illustrate the relationships among susceptible, immunised, and infected populations in our epidemiological model. Using comprehensive numerical simulations, we analyse the effects of fractional derivatives and highlight solution behaviours. Subsequent investigatio

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Publication Date
Sun Dec 01 2024
Journal Name
Iraqi Journal Of Physics
Study of the Sensitivity of Carbon Quantum Dots for NO2 Gas Sensor and improve it using Graphene
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Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Prevalence of gastrointestinal parasites in Iraq during 2015
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Publication Date
Fri Jun 04 2021
Journal Name
Journal Of Interdisciplinary Mathematics
Employ shrinkage technique during estimate normal distribution mean
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Survival of Different Fungal Spores During Tabletting
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The survival of dried spores of A.flavus, Penicillia Spp., and Cladosporia Spp.inoculated into multivitamins and folic acid tablets were examined at different compression pressures.Survival of fungal spores decreased with increasing compression pressure. The level of survival at particular pressures was shown to depend on the size of the contaminating fungal spores.The lethal effect of tabletting was attributed to shearing forces upon the contaminating spores generated by interparticulate movement. This hypothesis was supported by the dependence of survival upon spore size.

Key words: Fungal spores, microbial contamination.

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Coloproctology
The Value of Terminal Ileum Intubation During Colonoscopy
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Abstract<p>It is uncertain whether terminal ileum intubation should be performed routinely during colonoscopy, as there is uncertainty regarding its diagnostic value. The aim of the present study is to assess the diagnostic yield of terminal ileum intubation during colonoscopy according to indications for colonoscopy. This is a cross-sectional study in which the results of 294 total colonoscopy procedures were reviewed; ileal intubation was performed in 269 (91.49%) patients. The indications for colonoscopy, the results of ileoscopy, and the histopathological results of ileal biopsies were evaluated.</p><p>A total of 54 (20%) out of 269 patients who had successful intubation into the terminal ileum sh</p> ... Show More
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Publication Date
Sat Nov 01 2014
Journal Name
Patient Preference And Adherence
Antibiotic-prescribing patterns for Iraqi patients during Ramadan
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Background: During Ramadan, Muslims fast throughout daylight hours. There is a direct link between fasting and increasing incidence of infections. Antibiotic usage for treatment of infections should be based on accurate diagnosis, with the correct dose and dosing regimen for the shortest period to avoid bacterial resistance. This study aimed to evaluate the practices of physicians in prescribing suitable antibiotics for fasting patients and the compliance of the patients in using such antibiotics at regular intervals. Materials and methods: An observational study was carried out during the middle 10 days of Ramadan 2014 in two pharmacies at Baghdad. A total of 34 prescriptions (Rx) for adults who suffered from infections were examined. For

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Publication Date
Fri May 17 2013
Journal Name
Sensors
Evolution of Electroencephalogram Signal Analysis Techniques during Anesthesia
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Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG sig

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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