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Prevalence of Respiratory Complications In Covid-19 Patients
No full textBackground & Objective: In 2019 COVID-19 virus was emerged from China which was then declared a pandemic by WHO. This virus affects different organs of the body and causes some serious complications mainly affecting the respiratory system. The main objective of this research was to find out the prevalence of respiratory complications in patients with COVID-19. Methodology: A cross-sectional survey was conducted on patients with COVID-19 to find out the prevalence of respiratory complications in people. A sample size of 200 participants was selected using the non-probability convenience technique. The duration of the study was 6 months i.e., April to September 2021. Data was collected from Public sector hospitals situated in Rawalpindi and Islamabad in the form of hard copies. The tools used for the data collection were the CAP scale, MMRC scale for dyspnea, and CAT scale. The collected data was analyzed using SPSS Statistics V23.0. Results: Out of 200 participants, 111(55.5%) were male and 89 (44.5%) were females. The mean values of Community-acquired pneumonia (CAP) scale, Modified Medical Research Council (MMRC) scale for dyspnea and COPD Assessment Test (CAT) scale are 48.3, 3.02 and 26.09. Out of 200 participants Dyspnea was prevalent in 77.5% of people, Pneumonia was prevalent in 68% of people and COPD was prevalent in 56% of people. The P value for the three groups including CAP, MMRC and CAT is less than 0.05 (P < 0.05) which indicates that results are statistically significant. Conclusion: The findings indicate that there is a prevalence of Respiratory complications in COVID-19 Patients. Results are statistically significant as P value is P < 0.0
The Influence of the Audio-Lingual Method in Improving the Students' Vocabulary at SMA Negeri 21 Makassar
No full textThis study aims to find out the influence of the audio-lingual method (AML) in learning student vocabulary. The study uses a quantitative methodology to assess students' proficiency with the audio-lingual method (AML) in vocabulary learning. The audio-lingual Method (AML) arose after the aural-oral approach was devised in 1939 at the first English language Institute at the University of Michigan, United States by Charles Fries. The population of this study is first-grade students of SMA Negeri 21 Makassar 2023 There were five classes consisted 33 students per class. Moreover, The collecting data in this research are vocabulary tests and questionnaires. A vocabulary test is the instrument to find out whether dialogue can improve their vocabulary, while a questionnaire is an instrument for knowing the students' responses. The result of this study is Using the audio-lingual Method (ALM), students' pre-test and post-test scores on their vocabulary tests increased. The quantity of data, where 40% of the data showed that the student's scores improved as a result of using the audio-lingual method (ALM) in their English learning. In particular, with the growing influence of technology, vocabulary learning should be easier to be creative with, as there are many learning models that teachers can be inspired by to make their classes suit students' learning preferences, especially in this era
Constructing A Scale Based on Dramatic Representation of The Sociological and Psychological Skills of Students with Autism Spectrum Disorders and Verifying Its Psychometric Properties
No full textThe current study aimed to construct a measure based on dramatization of the sociological and psychological skills of students with autism spectrum disorders, in light of the variables of gender and group (experimental and control), and to verify its psychometric characteristics. The sample of the study consisted of (50) male and female students with autism spectrum disorders who were selected in a simple random manner. The sample was distributed into two groups. The experimental group amounted to (25), and the control group amounted to (25). The results of the study showed that there were statistically significant differences at the significance level (? ? 0.05) in the students’ performance on the immediate post-measurement in favor of the experimental group, and there were no statistically significant differences at the significance level (? ? 0.05). ? ? 0.05) in the students' performance of the sociological and psychological skills between the two measurements; The immediate and post-deferred dimensions of the experimental group, which gives an indication of the effectiveness of the scale of the sociological skills of students with autism spectrum disorders, and the current study, based on several indicators extracted from the SPSS program, concluded that the scale of the current study was judged with honesty in data representation, as well as with a high level of stability
The Reality of Competitive Advantage in the Ministry of Education in the Sultanate of Oman in the Context of Oman Vision 2040
No full textThis study aimed to assess the level of competitive advantage in the Ministry of Education in the Sultanate of Oman, in the context of Oman Vision 2040. A total of 257 employees from the Ministry of Education in Oman participated in the study. The analytical descriptive approach was used, and a questionnaire comprising 31 items was distributed among the participants to assess the quality of educational services, distinguished human resources, material and financial resources, and the pursuit of institutional excellence. The study found that the level of competitive advantage in the Ministry of Education in Oman was "average", with the quality of educational services dimension having the highest level and the distinguished human resources dimension having the lowest level. The study also revealed statistically significant differences in the responses due to qualification and years of experience. However, there were no statistically significant differences due to gender and nature of work. Based on the results, the study recommends the enhancement of competitive advantage in the Ministry of Education in Oman by improving the quality of educational services, developing human resources, improving management and strategic planning, and focusing on developing and modernizing educational programs to meet the needs of the labor market and the requirements of the times in light of Oman Vision 2040
Analysis Benefit Costs, Number of Tourist Visits (Domestic & International) and Per Capita Income on Conservation Forest Management in Jambi Province
No full textThis study aims to analyze the effect of benefit costs (X1), the number of visits by domestic tourists or foreign tourists (X2) and per capita income (X3) on the management of Jambi Province's conservation forest (Y). The data in this study were analyzed using Benefit Cost Ratio (BCR) analysis and multiple linear regression tests. Benefit cost analysis is carried out to calculate the amount of benefits and costs required from a project, if BCR ? 1 then the project is considered feasible and vice versa if BCR ? 1 is considered not feasible. And multiple linear regression analysis is used to determine the effect between variables. The results of the BCR calculations all get results ? 1, then there is an influence given by the variables X1, X2, X3 on variable Y. So it can be concluded that the project was declared not feasible
The Future of Executive Education and Training in Government Institutions: A Study on a Group of Government Institutions in the United Arab Emirates
Get PDFThis study explores the prospective trajectory of executive education and training in government institutions, focusing on a selection of government entities within the United Arab Emirates. The research delves into the evolving landscape of executive education, taking into account the rapid technological advancements, shifting social dynamics, and global challenges that influence the field. Through a comprehensive analysis of data gathered from the selected group of government institutions, the study examines various aspects of executive education, including the integration of traditional face-to-face and remote training methods. The findings offer insights into the perceptions of stakeholders regarding the significance of innovative methodologies, the impact of the COVID-19 pandemic on educational approaches, and the extent to which collaboration and access to high-quality education play a pivotal role. The research underscores the need for a balanced approach to executive education that addresses both current demands and future trends, positioning government institutions in the United Arab Emirates to effectively navigate the evolving landscape of executive education and training
The Influence of Changing Heat Transfer Coefficient, Type of Fluid, and Pipe Material on the Efficiency of the Distillation Exchanger
Get PDFThe fundamental purpose of the petroleum refining industry is to convert crude oil into refined products comprising more than 2,500 substances. Among the refined products are liquefied petroleum gasoline, aviation fuel, kerosene, fuel oils, diesel fuel, lubricating oils, and feedstocks, which have a variety of uses in the petrochemical and other industries. The petroleum refinery process begins with crude oil storage and continues with handling and refining operations before concluding with the separation process and shipping the refined compounds to their final destinations. A variety of methods are used in the petroleum refinery. The analysis of key components of the oil refinery will have a significant impact on the quality of the distilled products. Several scenarios, such as transfer coefficient, fluid type, and pipe materials, have been simulated to determine the most powerful example for the updated oil refineries, and their consequences are described.  
Machine Learning Approaches for Detecting Driver Drowsiness: A Critical Review
Get PDFDriver drowsiness is a serious issue that poses a significant threat to road safety, as it can lead to accidents and injuries. In response to this problem, a thorough review of machine learning techniques for detecting driver drowsiness was conducted. The review examined a range of techniques, including more recent approaches that use machine learning and deep learning algorithms as well as different types of data sources driver behaviours, physiological signals, and vehicle behaviours. The primary objective of this paper was to critically analyse and provide a comprehensive overview of the current state-of-the-art in detecting driver drowsiness, evaluate the effectiveness of each technique in terms of accuracy and reliability, and identify potential areas for future research and improvement. In order to achieve this, a systematic review of relevant research studies was undertaken. The review determined that machine learning-based techniques can improve the accuracy and reliability of driver drowsiness detection systems. However, certain limitations, such as the need for large amounts of data, feature extraction, and model structure, must be addressed. By overcoming these limitations, machine learning-based systems have the potential to enhance road safety and prevent accidents. In conclusion, this paper provides a thorough review of machine learning techniques for driver drowsiness detection, evaluates their effectiveness, identifies potential research directions, and highlights their significance and contribution to road safety. The insights gained from this study can be used to guide the development of more effective driver drowsiness detection systems and improve road safety for the community
A Comparative Study of Convolutional Neural Networks and Recurrent Neural Networks for Chord Recognition
Get PDFUsing Mel-spectrograms, this study evaluates the effectiveness of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNNs). Mel-spectrograms are justified by their non- linearity and similarity to the human hearing system. This study uses over 200 tracks by The Beatles and Queen collected through the Music Information Retrieval Evaluation Exchange. Data augmentation approaches are used to increase accuracy on unusual chords. This paper presents a 3-layer 2D CNN model trained on major and minor chords and then expanded to different types of chords. The dataset demonstrates that both models can recognize musical chords across various genres. We compare the proposed results to the existing literature and demonstrate the effectiveness of the proposed methodology. As a result of our analysis, we found that the CNN and RNN models were 79% and 76% accurate, respectively. The presented findings suggest that CNNs and RNNs are suitable models for chord recognition using Mel-spectrograms. Data augmentation can be an effective technique for improving accuracy on rare chords
Optimizing Gaming Experiences with a Web-Based Marketplace Peripherals
No full textOver the past decade, the global gaming peripheral market has emerged as a major investment in world trade. Numerous brands, including Razer and Logitech Inc., strive to make a significant impact and set trends in the industry by offering a wide range of products. These products cater to users' preferences and game system requirements, ranging from off-the-shelf options to fully custom-made gaming peripherals. This paper presents an application blueprint study for a centralized marketplace that compares on-market products from different renowned gaming peripheral producers. By leveraging this research, users can benefit from personalized recommendations for the best products that align with their preferences and game system requirements, ultimately enhancing their gaming experiences