Volume 12 | Issue 5 |

 Abstract

A physical disability is a limitation on a person's physical functioning, mobility, dexterity or stamina. Family relationships maybe weakened by the added and unexpected physical, emotional and financial stress. Many factors influence the reaction of family including the emotional stability of each member, religious values and beliefs, socio economic status and the severity and the type of child's disability. In this context, it is proposed to study the perspectives of the parents towards their physically disabled children and the problems encountered by them in their course of life. The present study had examined the social profile of the parents of the physically challenged children in the selected study area and it analyzed the psychological perception of the parents of the physically challenged children towards their child's disability. The study had further analyzed the financial problems faced by the parents of the physically challenged children and it measured the health problems faced by the parents of the physically challenged children. The present research study adopts Descriptive Research Design. Both primary and secondary data were utilized for drawing conclusions from the study. Interview Schedule method was employed to extract the primary data from the selected sample respondents. The sampling area selected for the study was Guntur District of Andhra Pradesh. The sample size comprises 120 sample respondents. The nature of the sample was that of the parents of the physically challenged children. The study concludes that the parents of the physically challenged children are facing with social, psychological, financial and health problems and most of them are in the state of depression making them to rely upon medicines on day to day basis. The study further concludes that their financial position is average and they intend to seek financial help from the banking institutions.

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 Keywords

Key Words: Parents of disabled children, Socio-economic, Psychological, Health Problems

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Cloud computing is emerging as a new paradigm of large-scale distributed computing. In order to utilize the power of cloud computing completely, we need an efficient task scheduling algorithm. The traditional Min-Min algorithm is a simple, efficient algorithm that produces a better schedule that minimizes the total completion time of tasks than other algorithms in the literature [7]. However the biggest drawback of it is load imbalanced, which is one of the central issues for cloud providers. In this paper, an improved load balanced algorithm is introduced on the ground of Min-Min algorithm in order to reduce the makespan and increase the resource utilization (LBIMM). At the same time, Cloud providers offer computer resources to users on a pay-per-use base. In order to accommodate the demands of different users, they may offer different levels of quality for services. Then the cost per resource unit depends on the services selected by the user. In return, the user receives guarantees regarding the provided resources. To observe the promised guarantees, user-priority was considered in our proposed PA-LBIMM so that user's demand could be satisfied more completely. At last, the introduced algorithm is simulated using Matlab toolbox. The simulation results show that the improved algorithm can lead to significant performance gain and achieve over 20% improvement on both VIP user satisfaction and resource utilization ratio.

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 Keywords

Cloud Computing; User-priority Aware; Load Balance; Makespan; Min-Min Algorithm; Cloud Task Scheduling

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This research paper aims to explore the correlations between Spotify usage habits, such as playlist curation, listening preferences, and music genres, and various aspects of student academic performance, study habits, and overall learning experiences. Despite Spotify's widespread popularity worldwide, little attention has been given to user behaviour within these platforms. Understanding the influence of digital platforms and streaming services on broader societal domains, particularly education, has become increasingly crucial as their usage grows. Our analysis sheds light on the peak times of day for Spotify usage among users, and we also investigate the duration and intervals between consecutive user sessions across different devices, offering insights into device-switching behaviour. Notably, this study marks the first comprehensive examination of such behaviour among a large user base. The empirical examination of how Spotify features impact student learning within higher education institutions in the Pune region forms a central focus of this paper. The findings provide valuable insights for educators, policymakers, and platform developers, enhancing our comprehension of the intricate relationship between technology, music consumption, and educational outcomes

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 Keywords

Keywords: Spotify, student learning, higher education, academic performance, music consumption, Pune region.

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Abstract: This research paper introduces a novel application for predicting plant diseases and curing the disease by using Convolutional Neural Networks (CNNs). Separate CNN models were trained on labeled datasets like cotton and potato leaves, each associated with their respective diseases. The primary goal is to employ of two standard CNN systems to detect various diseases in cotton and potato plants. Given India's heavy reliance on agriculture, this innovation is crucial to address challenges faced by the sector, including technological limitations, limited access to credit and markets, and the impact of climate change. this research paper are susceptible to various diseases that can impede their growth and result in substantial yield losses. The conventional disease detection methods involve manual inspection and disease prognosis, which are time consuming and less accurate. The research show- cases the effectiveness of the automated plant disease detection and curing system, with two best models achieving impressive accuracies of 97.10% and 96.94% . These results offer promising insights for potential applications in crop management, benefiting the agricultural sector and contributing to increased productivity and profitability.

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CNN, Deep learning, ResNet50, VGG16 , Image classification, Transfer learning.

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Fast dissolving tablets (FDTs) gained significant attention in the pharmaceutical industry due to their numerous advantage such as rapid disintegration, ease of administration, enhanced patient compliance, and suitability for pediatric and geriatric populations. This comprehensive review explores various aspects of FDTs including formulation strategies, manufacturing techniques, evaluation parameters, and recent advancement. Different methods employed for the preparation of FDTs, including direct compression, freeze-drying, and sublimation, are discussed along with their advantages and limitations. The key factors influencing the disintegration and dissolution of FDTs such as choice of excipients, superdisintegrants and disintegration agents are highlighted. Furthermore, recent innovations in the field such as orally disintegrating films and 3D printing for FDT manufacturing are also discussed. Additionally challenges associated with FDT formulation and regulatory considerations are addressed. This review aims to provide valuable insights for researchers and pharmaceutical professionals involved in the development of fast dissolving tablets.

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Fast dissolving tablet, oral route, superdisintegrants

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Real-time body pose estimation stands as a pivotal component in computer vision, finding applications across an array of domains. This study delves into the amalgamation of OpenCV and MediaPipe, two robust libraries, to accomplish precise and efficient human body pose estimation in real-time. OpenCV, renowned for its computer vision functionalities, joins forces with MediaPipe, which furnishes pre-trained machine learning models explicitly crafted for keypoint estimation. This collaboration enables the accurate detection and continual tracking of human body landmarks.The methodology of this study centers on harnessing OpenCV's capabilities for managing video input and employing MediaPipe's pose estimation models for the identification of anatomical keypoints. OpenCV takes charge of vital video stream manipulations such as frame resizing, color space conversions, and noise reduction, optimizing the input data for MediaPipe's specialized models. Subsequently, MediaPipe adeptly pinpoints and tracks key body joints, empowering the real-time estimation of intricate human poses within live video streams or camera feeds. A comprehensive evaluation of this system encompasses scrutiny of its accuracy, real-time performance, and robustness under diverse conditions, encompassing scenarios of occlusion and varying environmental settings. The system's efficacy in detecting and persistently tracking keypoints, coupled with its real-time capabilities, unveils its potential in multifaceted applications such as sports analytics, healthcare, human-computer interaction, and beyond. The fusion of OpenCV and MediaPipe encapsulates a promising trajectory for real-time body pose estimation, laying a sturdy framework for precise human pose analysis. The study's findings contribute to propelling advancements in the realm of computer vision by furnishing a dependable and efficient solution for real-time pose estimation. These advancements hold the promise of impacting various industries and domains, hinting at significant strides in real-time pose estimation technology.

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 Keywords

OpenCV, Computer Vision, Pose Estimation, Mediapipe

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This study investigates the correlation between green marketing strategies employed by companies and their influence on customers' purchasing decisions, as well as examines the underlying motivations behind the use of sustainable packaging. The research employs a quantitative approach, utilizing both primary and secondary data sources. A structured questionnaire is administered to 105 respondents, selected through convenience sampling. The questionnaire gathers insights on respondents' perceptions of green marketing strategies, sustainable packaging practices, and their purchasing behavior. Additionally, secondary data from relevant journals and research papers are utilized to enrich the analysis. Data analysis is conducted using Microsoft Excel, encompassing descriptive statistics, correlation analysis, and potentially regression analysis. Ethical considerations, including respondent confidentiality and informed consent, are upheld throughout the research process. The findings of this study contribute to understanding the relationship between green marketing strategies, sustainable packaging, and consumer behavior, with implications for businesses aiming to adopt environmentally conscious practices.

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Green Marketing and Sustainable Packaging - Can it Lead to Consumer Consciousness

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In today's fast-paced financial markets, timely access to relevant news is crucial for informed decision-making. As people invest time and effort in buying real estate, mutual funds, bonds, and more. Before investing, we search for a suitable banking partner. For long-term investments, we research which banks are performing well minus scams or frauds, and offer reasonable interest rates and returns. So we need to stay updated with financial and the current market .To address these challenges, we propose a chatbot that could provide you with all the information and news related to finance and the current market.

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LLM, LLAMA, Qdrant Vector Storage

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Unused disposal is a hard work for Economically developing countries alike. Biggest problem is that the public garbage cans often overflow well before they are due to be emptied again. This results in elevated levels of smokes, beetles, and houseflies produced by waste management which can cause some serious health disease. A comprehensive analysis is conducted in the latest research, focusing on the integration of machine learning techniques in enhancing smart waste management practices. With this technology, the system may optimize waste disposal by selecting the most efficient route using machine learning. ML-IoT-based design includes equipment that measures weight of rubbish adjusted to network environment as well as containing information about waste management Comparing these studies should give readers a complete understanding of the smart waste management domain

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Smart Waste Management, Intelligent Waste Management, IoT, Smart Bin

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Lock down is an emergency situation imposed by Government authorities where people are temporarily prevented from entering or leaving a restricted area. Generally the condition is imposed by the Government during the outbreak of epidemic diseases in which people are required to stay in their homes and limit their entry from homes. But an individual employed in various occupational fields such as health care, public works, law and enforcement , food supply are continue to work outside the home during lockdown. This situation is faced by the whole world for a period of 2 months. Lockdown is a difficult period for children with special needs as most of them cannot communicate even with their parents, leading to conflict within the family. The lockdown is a tricky time for parents of children with special needs as they are with various responsibilities while working from home. The parents should use emotional intelligence skills to understand and manage their children. They should try to involve their kids in various daily tasks which are easy to do and kids can easily understand them through visual prompts, like dusting, vegetable washing, filling water bottles, vegetable segregation, and various small role-playing games. Doctors said that Parents should ensure that children with special needs should avoid excessive use of the phone and television as it is associated with a decrease in a neurotransmitter which leads to abnormal behaviour. Sometimes the Parents can use video calls with children for short consultations with their special educators and therapists. So the present paper attempt to analyse the difficulties faced by the children with special needs during the lock down and to find out the emotional intelligence skills used by the parents to engage them.

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 Keywords

Lockdown, children with special needs, Emotional Intelligence

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Creative Commons Attribution 4.0 and The Open Definition