Volume 12 | Issue 6 |

 Abstract

Abstract:- We all know that Plastic is the biggest threat to this planet Earth. Yet this grave issue is not taken seriously by the public. In India alone, 3.5 million tons of plastic wastes are getting generated every year.4 According to a report of 2021, in India, plastic waste generation has increased almost more than double in the last 5 years.1 Waste production of plastic is increasing every year at the rate of 21.8%. Not only in India, the conditions have become severe all around the world. According to IUCN Report, the whole world is producing 300 million tons of plastic waste, of which above 14 million tons of plastic waste is going in the ocean.3 So, there is a very strict need to control the use of plastic and to minimize its use until it is utmost necessary. The present paper deals with this menace in brief and also sheds light on the efforts going on in National, International, Individual and community level to fight this menace.

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 Keywords

keywords Plastic, Non-biodegradable, Bio-friendly alternative, Incineration, climate change

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Creative Commons Attribution 4.0 and The Open Definition

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Cloud computing has become integral to modern business operations, offering scalability, flexibility, and cost-effectiveness. However, with the increasing reliance on cloud services comes the heightened risk of security breaches and data vulnerabilities. This paper explores next-generation approaches to cloud security, focusing on the integration of big data analytics and advanced data management techniques. The utilization of big data analytics enables the proactive detection of anomalies and potential threats within cloud environments. By harnessing vast amounts of data generated by cloud systems, machine learning algorithms can identify patterns indicative of security breaches, allowing for timely intervention and mitigation strategies. Additionally, advanced data management techniques, such as encryption, tokenization, and access control mechanisms, play a crucial role in safeguarding sensitive information stored in the cloud. This paper evaluates the effectiveness of these next-gen cloud security measures in mitigating risks associated with data breaches, unauthorized access, and insider threats. Furthermore, it discusses the challenges and considerations involved in implementing these technologies, including scalability, interoperability, and regulatory compliance. In conclusion, the integration of big data analytics and advanced data management techniques represents a promising paradigm shift in cloud security, offering enhanced protection against evolving cyber threats while enabling organizations to leverage the full potential of cloud computing resources.

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Cloud computing, cloud security, data management, cyber threats, Big Data

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Creative Commons Attribution 4.0 and The Open Definition

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The current study's goal is to create and assess a cosmetic herbal face pack using natural components to promote radiant skin and prevent wrinkles, aging, redness, acne, and scars. The fact that herbal cosmetics are non-toxic is their primary advantage. Herbal face masks aid in clearing debris from skin pores and enhancing blood circulation. The primary constituents in this composition are Fuller's Earth, coffee powder, powdered sandal wood, powdered lemon peel, Turmeric powder, and Rice flour. Using sieve no. 120, the precise amount of components was weighed and processed into a fine powder. Subsequently, the components were uniformly blended using the serial dilution procedure in a geometric manner. The composition of the face pack was assessed based on a number of factors, including physicochemical, parameters, an analysis of stability, and an irritation test.

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Face pack, Natural, Formulation, Characterization

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Creative Commons Attribution 4.0 and The Open Definition

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This abstract examines the potential of redesigning NGO websites through the perspective of knowledge management to enhance their effectiveness and reach. In the digital age, NGOs must transition from static online presences to dynamic knowledge hubs that facilitate the creation, sharing, and utilization of information. This study proposes a framework for NGO websites that integrates knowledge management principles, promoting efficient information flow, collaboration, and continuous learning. By implementing interactive features, comprehensive data repositories, and collaborative tools, NGOs can improve stakeholder engagement, support informed decision-making, and amplify their mission. This approach transforms NGO websites into essential platforms for knowledge exchange, thereby enhancing their operational impact and strategic outcomes.

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Keywords:NGO website design, Knowledge management (KM) for NGOs, Content management for NGOs, User-centered design for NGOs

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Thyroid disorders are prevalent endocrine diseases affecting millions of people worldwide. The accurate and timely classification of thyroid stages is crucial for effective diagnosis and treatment. In recent years, convolutional neural networks (CNNs) have emerged as a powerful tool for image recognition and classification tasks. The proposed methodology involves a multi-step process. First, a comprehensive dataset of thyroid images representing different stages is compiled and pre-processed for training and validation purposes. Next, a CNN architecture is designed, comprising multiple layers of convolutions, pooling, and fully connected layers. The model leverages the capability of CNNs to automatically learn and extract relevant features from the input images, making it well-suited for medical image analysis tasks. The training of the CNN is conducted using a large-scale dataset to optimize its performance and generalization ability. The model is fine-tuned through an iterative process to achieve the highest possible accuracy and precision for thyroid stage classification.

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Detection Of Thyroid Stages Classification By Using Convolution Neural Network Techniques

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Agriculture is vital to India's economy but is currently hindered by major challenges such as deteriorating soil fertility, inefficient resource utilization, and limited technology adoption. Intensive agricultural practices, excessive use of chemical fertilizers, and inadequate soil management have led to significant soil degradation and nutrient loss. Water scarcity and unpredictable rainfall further compound these problems, with traditional farming methods often resulting in wasted resources and reduced crop yields. The integration of Internet of Things (IoT) technology in soil fertility monitoring provides a promising solution. IoT systems use smart sensors to continuously monitor crucial soil parameters like nutrient levels, moisture, temperature, and pH in real-time. This data-centric approach improves soil health monitoring, optimizes the use of fertilizers and water, and promotes sustainable farming practices. Additionally, advanced analytics and machine learning can forecast soil health trends, allowing for proactive soil management. By adopting IoT technology, Indian agriculture can enhance soil management, increase resource efficiency, and boost productivity, ensuring food security and economic stability for millions of farmers.

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 Keywords

Internet of Things, Sensors, Machine Learning, Agriculture

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Creative Commons Attribution 4.0 and The Open Definition

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Glaucoma is a chronic eye disease that is the second leading cause of blindness all over the world, and a great number of people have been experiencing it. Glaucoma is a group of diseases that cause damage to the optic nerves,which leads to irreversible partial or fullvision loss. Early detection of glaucoma is critical and highly beneficial in preventing further deterioration. Glaucoma can occur at any age and shows no early signs or symptoms, which makes it hard to detect. The final stage leads to complete blindness, and a cure has not been found as of now. So, the only way is to slow down the effects by detecting them at an early stage. And another major drawback is the limited number of glaucoma specialists in our country, which makes it even more difficult to diagnose. Due to these reasons, the project focuses on developing an Android application that takes the fund us image as an input and then predicts whether it is glaucomatous or non- glaucomatous. This system is developed using the CNN algorithm in deep learning, which includes dataset collection, sequential model development,training,testing,model conversion,and application UIdevelopment.The accuracy of this model is found to be around 97%, and there are fewer false positives compared to the previous models. This project can be extended so that it can be used on multiple operating systems and be accessible through a web version. In the future, the fund us image can be extracted from the general eye image itself.

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Early Stage Detection Of Glaucoma Illness By Deep Learning Approach Forecasting

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Introduction: The non-stress test (NST) is a simple, noninvasive way of checking on your baby's health. The test, sometimes called a cardiotocography, records your baby's movement, heartbeat, and contractions. It notes changes in heart rhythm when your baby goes from resting to moving, or during contractions if you're in labor. Your baby's heart should beat faster when active just like yours. The NST can reassure you that your baby is healthy and getting enough oxygen. It's called a non -stress test because the test won't bother your baby. Your doctor won't use medications to make your baby move. The NST records what your baby is doing naturally. Objectives: 1). To assess the of fetal parameters during non-stress test. 2). To assess the effectiveness of maternal positioning on findings of the fetal parameters during non-stress test. 3). To assess the association between fetal parameters with the demographical variable. Method: An quantitative approach with pre-experimental one group short case study research design was adopted for this study. The sample comprised of 60 antenatal mothers. Sample was selected by using purposive sampling technique. Data collection was done from 14nd February to 20th February at Shree Janani hospital Dharmpur and 2 march 2020 to 22 march 2020 at Shrimad Raj Chandra hospital Dharmpur data was collected by using numerical scale. Data was analyzed using descriptive and inferential statistics. Result: In all the three position the fetal heart rate was normal from the range 100-160 b/m. The fetal movement are easily observed in left lateral position (42) participants and less observe in supine position (47) participants and for the number of accelerations the normal result found in the semi-setting position (45) participants. Thus, investigator concluded that the experimental study is good method of providing left lateral maternal positioning during non-stress test. Interpretations and conclusion: In all the three position the fetal heart rate was normal from the range 100-160 b/m. The fetal movement are easily observed in left lateral position (42) participants and less observe in supine position (47) participants and for the number of accelerations the normal result found in the semi-setting position (45) participants. Thus, investigator concluded that the experimental study is good method of providing left lateral maternal positioning during non-stress test.

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 Keywords

DF(Degree of freedom), NST(Non-stress test), S( Significant) NS(Non-significant) H(hypothesis) n(sample size)

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Many locations, including hospitals, universities, corporate offices, etc., have prominent signs that read "KEEP YOUR MOBILE PHONES SILENT!!" It is common for people to forget to place their phones in "Silent Mode," even though it isn't always possible--for example, during important meetings or presentations. Almost fully automated profile switching will be available via an Android app for automated profile switching. This application will enable the device to go into silent mode based on the data users enter into the database, based on what they need.

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Auto Silent, Silent modes, automatic profile switching

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A hookworm belonging to the genus Ancylostoma (Dubini,1843) isolated from the small intestine of a canid Canis aureus (Linnaeus) which was found dead from a new host locality, village Kandraur district Bilaspur Himachal Pradesh. The worm is bent dorsally, cuticle transversely striated; buccal capsule large with three pairs of ventro-lateral teeth and two lancets in the deep of the buccal capsule; dorsal ray forked distally each branch further trifurcates; genital cone oboid with two pairs of genital papillae; spicules equal, long filamentous, 0.650-0.765 mm long with tapering tips; gubernaculum 0.144-0.180 mm long; vulva in the posterior third of the body 3.240-3.510 mm from the tip of tail; tail conical with a spine at the tip 0.006 mm long . This zoonotic worm is transmitted orally or percutaneously, causing a disease ancylostomiasis in humans, domestic and wild animals. The main symptoms of ancylostomiasis are mucous haemorrhagic diarrhoea and anaemia.

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 Keywords

hookworm, Ancylostom caninum, canid Canis aureus, Himachal Pradesh

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Creative Commons Attribution 4.0 and The Open Definition