Volume 12 | Issue 3 |

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Preferences for Readymade and Tailored Garments amongst Sharda Exports Professionals

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This research project is made to make easier for professional to create invoicing, filing and managing client with one click.

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CRM , My Sql,Laravel,

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The study's goal was to find out how well the cardiac rehabilitation plan worked on activity tolerance, certain physiological parameters (heart rate (HR) and electrocardiogram (ECG)), and quality of life in Dr. Prem Hospital Panipat patients who had recently undergone CABG surgery. This study's main ideas come from Sister Calista Roy's Adaptation Model, which is made up of four ideas: the person, nursing, health, and surroundings. Methodology: To test a goal, a quantitative research method is used. This study uses a quasi-experimental research design to find out how well a cardiac rehabilitation plan works. It does this by using a quasi-experimental nonequivalent Pretest Post Test control group design. The study took place at Dr. Prem Hospital. For the study, 60 people who had CABG surgery were chosen: 30 were in the experimental group and 30 were in the control group. They were all brought to the cardiothoracic surgery department. The study used a method called "total enumerative sampling." Demographic and clinical variables, the Duke Activity Status Index, heart rate, an ECG, and the SF 36 questionnaire are all used to gather data. Also, written permission was asked for. The method used was total enumerative selection. This cardiac rehabilitation scheme checked in on people who had CABG surgery once a week. On the fifth day after surgery, both the experimental group and the control group took a pre-test in the post-operative room of the cardiothoracic department. Thirty of them were put in the training group and thirty were put in the control group. The intervention group got cardiac rehabilitation for three days in a row through a planned training programme and demonstration. They were told what to do and were urged to do it over the phone. Before 30 and 60 days, changes were measured in both groups' exercise tolerance, physiological parameters (heart rate ECG), and quality of life. The standardised tools were used, and the material was approved by experts. The Cronbach alpha method was used to check the reliability of the tools. Before the samples were used to collect data, the Duke activity status index was used to measure activity tolerance and the SF-36 questionnaire was used to measure quality of life. For heart rate.9, the inter rater method ECG-.75 was used. The control group had an activity tolerance score of 45.47 + 4.883 on the post-test, which is the mean and standard deviation. The average and range of exercise tolerance levels in the control group during the post-test were 25.23 + 8.169, and the score for the independent 't' test was 12.045 for 58 degrees of freedom. The 'p' number was less than 0.001, which means it was probably real. To compare the experimental group and the control group, the quality of life score after the test was 50.4 + 9.676 for the experimental group and 30.8 + 5.372 for the control group. The independent 't' test score was 9.700 for the degree of freedom 58. At a 'p' value of less than 0.001, it was statistically significant(p value less than 0.001). Based on the study, it can be said that a mix of interventions, such as teaching, showing exercises, giving out pamphlets about cardiac rehabilitation, and phone calls to encourage people to stick with it can increase adherence to cardiac rehabilitation, which in turn improves activity tolerance and quality of life.People who went through a cardiac rehabilitation course will not get sick again or have to go back to the hospital.It makes people more likely to follow through with their therapy treatment.

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Effectiveness, cardiac rehabilitation programme, activity tolerance, selected physiological parameters, Heart rate, Electro cardio gram and quality of life CABG surgery patients

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This innovative project addresses the growing need for efficient healthcare solutions by introducing a Human Sound-Based Diseases Detection System. Leveraging advanced machine learning techniques and signal processing, the system aims to diagnose respiratory conditions like asthma, COVID-19, tuberculosis, and obstructive diseases through the analysis of audio data converted into spectrogram images. The methodology involves utilizing the Librosa library for audio preprocessing, employing the Dense Net architecture for model training, and discussing the selected database's pivotal role. Results indicate the CNN's impressive accuracy improvement from 0.3 to 0.99 during 20 epochs, highlighting the system's ability to make accurate predictions. The discussion emphasizes the need for further validation, consideration of potential biases, and exploration of additional metrics to enhance the system's applicability in non-invasive disease detection

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Asthma, Tuberculosis, obstructive, covid-19, Librosa library, CNN.

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In this study an attempt has been made to establish the differential action of high temperature on photosynthetic electron transport mediated by either PS-II or PS- I or both in Maize thylakoids after giving high temperature treatment to primary leaves. The increase in the temperature from 250C-450C cause inhibition in PS-II catalysed electron transport. The possible reason for the loss of PS-II catalysed electron transport could be depletion of manganeese from water oxidation complex. In contrary high temperature induced enhancement in PS-I catalysed electron transport due to opening of new site to donate electrons before plastocyanin by reduced DCPIP. Thus high temperature exerts differential effect on PS-II as well as PS-I in Maize plants.

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Chlorophyll, Electron transport, Photo system, Maize plants.

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Pedagogical practices are the practices that teachers need to be well-aware of in promoting student learning. The major factors that need to be put into practice in shaping pedagogical practices are, reflections, documentation , learning and research. The current empirical study delves into the pedagogical practices of Social Science teachers with special reference to their pedagogy, Teaching Learning Practices (TLPs) and digitalization in the State of Telangana. The research employs an empirical approach which is qualitative and the study cohort comprised 350 Social Science teachers from Mahbubnagar district of Telangana State. The instrument is a self-developed questionnaire based on Likert five point scale. The data was analyzed using t-test. The main findings of the study indicate that there exists a significant difference in the pedagogical practices of Social Science teachers with regard to their pedagogy, Teaching Learning Practices (TLPs) and digitalization. The study reflects certain educational implications for teachers, Heads of Institutions and also for implementing authorities. Directions for further research were also portrayed succinctly.

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Pedagogical Practices, Social Science teachers, Empirical study, Teaching Leanring Material (TLM) , digitalization.

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In recent years, machine learning techniques have revolutionized the field of computer vision, particularly in the detection of gender and age from visual data. This paper presents a comprehensive analysis of two popular machine learning models, Support Vector Machines (SVM) and Convolutional Neural Networks (CNN), for gender and age detection tasks. The study evaluates the performance of SVM and CNN algorithms on diverse datasets and assesses their effectiveness in real-world applications such as advertising, security, healthcare, and surveillance. Results indicate that CNN-based approaches generally outperform SVM in terms of accuracy and robustness, owing to their ability to automatically learn hierarchical features from raw image data. However, SVM models exhibit advantages in computational efficiency and interpretability. The findings underscore the significance of gender and age detection in various domains, including personalized advertising, enhanced security measures, and improved healthcare diagnostics and treatments. This research contributes to the ongoing discourse on leveraging machine learning advancements for societal benefit and underscores the importance of choosing appropriate algorithms for specific applications in gender and age detection.

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Machine Learning, Convolutional Neural Network, Gender Classification, Age Classification, Support Vector Machine

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Deepfake detection is based on a deep learning model. Deepfake content is created with the help of artificial intelligence and machine learning to replace one person's face with another person's face in pictures. These manipulated pictures will undoubtedly have an enormous societal impact. Deepfake uses the latest technology like Machine Learning (ML), and Deep Learning (DL) to construct automated methods for creating fake content. We use the DFDC dataset for training the model, it contains 100,000 videos of more real and fake videos. To identify real and fake images using various Convolutional Neural Network (CNN) models, namely EfficientNetB0, VGG-16, and Xception. Our primary objective is to determine the model that yields the highest accuracy in identifying deepfake images. Initially, we preprocess videos from the DFDC dataset, extracting frames and preparing them for input into CNN models. Subsequently, we construct and train each CNN architecture on the preprocessed data, integrating techniques like data augmentation to enhance model generalization and resilience. Performance evaluation utilizes metrics such as accuracy, precision, recall, and F1 score.

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Deepfake Detection, Deepfake Image, Convolution Neural Network, DFDC Dataset

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Purpose: The purpose of this study is to identify ways by which classification and cataloguing services in the university libraries can be made more effective through the application of TQM techniques. Methodology: A total of five renowned universities of Assam are purposely sampled. The study assesses the current culture for quality management systems and also focuses on the cataloguing and classification skills of the staff. The user satisfaction level is also studied and the challenges they face in retrieving information. It investigates the idea of how timeliness is maintained, what schemes and rules are followed by those libraries and through what mode based on the principles of TQM. Findings: Study revealed that shortage of professional staff acts as the main barrier to process TQM. Recommendations are made to prioritize the needs of the users by providing excellent training to the staff. Value: The study has proven the users' requirements and the necessary actions that have to be implied to improve the efficiency of the staff. Moreover, it also focused on the proper utilization of time.

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TQM; University Libraries; Library Cataloguing; Library Classification

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Recommendation System are software application that provide or suggest item to user these System use filtering techniques to provide recommendation. The Purpose of this recommendation System provide services to small or part time Workers. It has been observed by the team that Recommendation System that are studied have not focused on small wokers like electrician and carpenters, plumber, mechanics but the corporate people.The recommendation system has been implemented in the android programming language.The results obtained were quite accurate which helps to recommend jobs to workers and workers to customers in the required work field.Where a job seeker applies to a job by creating a profile on a job portal by providing all his/her work preferences.These work preferences of each user can be collected from each user and provide worker recommendation based on their preference.

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Worker Recommendation System

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Creative Commons Attribution 4.0 and The Open Definition