The Impact of Transfer Learning and Pre-trained Models on Model Performance
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Coronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.
The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.
COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.
COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019. Since then it spreads leading to a pandemic.
... Show MoreThere is a need to make serious efforts For Iraqi universities to be in the ranks of advanced universities in the world. This requires attracting teaching talents and providing an incubating environment for them. Therefore, the objective of the research was to explore the influence of (the environment, the development of talents) on sustainable competitive advantages. The research followed the descriptive approach and used the quantitative analysis method. Almaqaal university is the field of study. The study sample size (of 76 people), from almaaqal university teachers, and the sample comprised the available staff specialized in the field of Teaching and research. The questionnaire was utilised as a data collection tool and (spss) program w
... Show MoreReliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a
... Show MoreThere is a growing need for up-to-date data for rapid decision making in the modern digital age. Recently, the need for high-resolution topographic maps is highly demanding by most mapping clients. With the maturing automatic structure from mobile and multi-view stereoscopy software, small organizations and individuals now have the ability to make their own surveys based on mobile mapping devices. This study looks at how feasible using low-cost Unmanned Aerial Vehicle (UAV) as a mobile mapping device for photogrammetric topographical surveys. It is showing the impact of different UAV flight settings and parameters on the accuracy of mapping products. An automatic scenario for photogra
This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b
... Show MoreThe Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr
... Show MoreThis research investigates the type and the significant relationship between roaming management and self-efficacy and its impact on excellence in providing hotel service. To achieve this, the applied approach was adopted through A questionnaire was designed and developed for the collected data. It has consisted of three parts. The firsts section included nine questions to measure the dimensions of management by roaming. The second section includes nine questions to measure the effectiveness of the two employees. The last section includes 12 questions to measure the excellence of the hotel service. The research sample included 43 employees' responding to this
... Show MoreThe current research aims to identify the effect of Daniel's model on the fifth grade scientific students’ achievement of chemistry in high government day preparatory schools. The Loyal Preparatory School for Boys was chosen by the deliberate appointment of its students to be the research sample, affiliated with the Directorate of Education in Anbar Department of Education Fallujah for the academic year (2022-2023). Two divisions of the fifth grade scientific people were randomly selected out of five divisions to represent one of the experimental group that is studying according to Daniel's model and the other is the control group that is studying according to the usual method. The equivalence of the two research groups was verified by a
... Show MoreCrime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o
The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
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