Volume 12 | Issue 6 |

 Abstract

To improve the quality of distance learning and students' learning effectiveness in the investigated universities, quantitative survey with SPSS19.0 is applied to analyzing data in this study, in which Factor Analysis, Reliability Analysis, Regression Analysis, and Analysis of Variance are utilized for organizing and analyzing data. About 400 students of Kalyana Karnataka region studying in KSOU, Mysore are proceeded questionnaire survey, and 372 valid copies are studied. The research findings show that Distance Learning appears significantly positive effects on Curriculum Instruction in Learning Effectiveness, Distance Learning presents notably positive effects on Technological Media in Learning Effectiveness and Distance learning reveals remarkably positive effects on Curriculum Management in Learning Effectiveness.

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 Keywords

Distance Learning, Learning Effectiveness, Kalyana Karnataka Region

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Dengue fever, a mosquito-borne viral illness, poses a significant global public health threat, especially in tropical and subtropical regions. Caused by four distinct serotypes of the dengue virus, it manifests in a spectrum ranging from mild flu-like symptoms to severe complications such as hemorrhagic fever and shock syndrome. Despite extensive prevention and control efforts, dengue remains a burden with periodic outbreaks, particularly during rainy seasons when mosquito breeding peaks. Accurate and prompt diagnosis of dengue is crucial for effective clinical management and outbreak containment. Conventional diagnostic methods face challenges, including false negatives, delayed results, and reliance on labor-intensive laboratory tests, necessitating a shift towards more efficient and reliable diagnostic approaches. Deep learning models hold the potential to revolutionize dengue diagnosis by leveraging diverse data sources for early detection and prediction. By integrating clinical symptoms, laboratory findings, and epidemiological data, these models offer a comprehensive approach to dengue diagnosis, enabling rapid and accurate case identification. Deep learning algorithms can analyze vast amounts of data to identify patterns and early signs of infection that traditional methods might miss. Siddaganga Medical College & Research Institute is at the forefront of using real-time data for dengue surveillance and diagnosis. Through collaborations with research partners, Siddaganga Hospital has amassed extensive clinical data, including patient demographics, symptoms, and diagnostic test results. Utilizing this rich dataset, deep learning models can identify early signs of dengue infection, facilitating timely interventions and reducing the disease burden. This review highlights the importance of integrating real-time data and fostering collaboration between healthcare providers and data scientists to advance dengue diagnosis and surveillance. By harnessing the power of deep learning models and real-time data streams, institutions like Siddaganga Hospital can enhance their capacity for early detection and response to dengue outbreaks, ultimately mitigating the impact on public health.

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Dengue fever, mosquito-borne illness, public health, diagnosis, deep learning, data integration, epidemiology, early detection, Siddaganga Medical College.

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Herbal plants are commonly utilized as natural pain relievers, particularly in traditional medical systems. However, the scientific data supporting their analgesic effectiveness is weak and frequently contradictory. This study seeks to give a complete overview of plant species and known phytoconstituents having analgesic and anti-inflammatory properties with its uses. The study includes 10 herbal plants from various families, including Curcuma longa , Clove -Syzygium , Ginger , Mint, Feverfew, Willow Bark, Kava Kava, Lavender, Rosemary. These plants' analgesic effect is linked to a variety of phytochemicals, including alkaloids, flavonoids, terpenoids, phenolic acids, saponins, and polysaccharides, which influence distinct pain pathways such as opioid, inflammatory, neuropathic, and nociceptive. This review highlight the potential of herbal plants as a rich source of analgesic substances, providing a natural alternative to synthetic drugs. Further exploration in this area may result in the creation of novel bioactive substances. with better therapeutic activity and selectivity.

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 Keywords

Analgesic , Anti-inflammatory

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POLITICAL DEFECTION AND DEMOCRACY IN INDIA MANISHA KUMARI Doctoral Research Scholar Department of Political Science Netaji Subhas University Jamshedpur, Jharkhand Email Id- manishakumari16726@gmail.com ABSTRACT In the present paper, the politics of Defection is playing havoc with Indian Democracy. Representatives elected by the people change their political parties to topple the government. Frequent changing of political parties for political gains has weakened Indian democracy making it impossible to establish democratic values in the political fabric of the society or the article attempts to study the phenomenon of party defection to understand the impact it may have on political parties. Before 1967, there was no serious problem of political party dominance in India. This was because at that time the Indian National Congress was the only political party that enjoyed the confidence of people. The phrase Aaya Ram Gaya Ram gained popularity in Indian politics in 1967 when Gayalal, a Haryana MLA, changed his party three times in a single day. The anti defection law seeks to prevent political defection that may be due to remuneration or other similar considerations. The present anti-defection law was passed by the parliament in the year 1985 by the 52nd Constitutional Amendment which added the tenth schedule to the Constitution.

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Political Defection, Indian Democracy, Neharuvian View

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The "Waste Wise: Engaging the City in Plastic Recycling" project tackles the challenges of modern urban waste management by introducing an innovative online platform. In today's urbanized world, traditional waste disposal methods struggle with the increasing volumes of scrap materials and public waste. "Waste Wise" operates as a dynamic digital ecosystem, streamlining scrap collection through an intuitive mobile application. Citizens can effortlessly report and schedule scrap pickups, incentivized by a rewards system offering digital coins and discount coupons. Simultaneously, scrap collectors benefit from real-time location details, optimizing their responsiveness. The platform extends its impact with a public waste reporting feature, allowing citizens to capture images of waste accumulations. These reports are seamlessly relayed to municipal authorities, facilitating swift and targeted public waste collection efforts. The integration of GPS technology ensures accurate tracking of scrap collectors, enabling efficient navigation. "Waste Wise" envisions a paradigm shift in waste- management, leveraging technology for proactive citizen engagement, empowering scrap collectors, and enhancing collaboration with municipal authorities. The project aspires to create cleaner, more sustainable urban environments, marking significant strides towards intelligent and collaborative waste management. This abstract encapsulates the essence of "Waste Wise"--a transformative solution that combines user-friendly technology, incentives, and collaborative reporting to address the complexities of urban waste management in a sustainable and efficient manner.

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Recycling

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Geographical Information Systems (GIS) have emerged as indispensable tools in the realm of disaster risk management, offering a comprehensive approach to understanding, mitigating, and responding to natural hazards. This abstract explores the multifaceted role of GIS in disaster risk management, highlighting its significance in hazard mapping, vulnerability assessment, and emergency response preparedness.GIS facilitates hazard mapping by integrating diverse spatial datasets, including topography, land use, and historical hazard occurrences. Through sophisticated spatial analysis, GIS identifies high-risk areas prone to floods, earthquakes, wildfires, and other hazards, enabling policymakers to prioritize resources for mitigation efforts and land-use planning. GIS plays a crucial role in vulnerability assessment by integrating socio-economic and environmental data to identify vulnerable populations, critical infrastructure, and assets at risk. This information empowers decision-makers to tailor interventions such as evacuation plans and resource allocation, ensuring the resilience of communities in the face of disasters.GIS enhances emergency response and preparedness by integrating real-time data feeds, facilitating situational awareness, resource allocation, and coordination among response agencies. By providing decision-makers with accurate spatial information, GIS enables timely and effective response efforts, ultimately reducing the impact of disasters on communities.GIS serves as a vital tool in disaster risk management, offering invaluable capabilities in hazard mapping, vulnerability assessment, and emergency response preparedness. Its integration of spatial data and analytical tools enables decision-makers to make informed decisions, enhance resilience, and safeguard lives and livelihoods in the face of natural hazards.

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Geographical Information Systems (GIS) ,Disaster Risk Management, Hazard Mapping, Vulnerability Assessment ,Emergency Response ,Spatial Analysis, Hazard Identification, Resilience, Decision-Making, Spatial Data Integration

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Haruki Murakami's work delves into the tropes of realism and existentialism, the promises of industrialization, and the dilemmas of post-industrial society in a highly developed country. The works of postmodern literature, the fragment narrative, meta-fiction, and hyper-reality are exemplified in his works highlighting the concepts of the distinction between genuine and fake reality. Indeed, in novels like 'Kafka on the Shore' and '1Q84,' a consistent feature in Murakami's work relates to the cultured ambiguity between reality and fantasy which is characteristic of the twentieth century experiencing wars, main nuclear threat, and technological advancement. These contextual antecedents can help explain his portrayal of existential despair and alienation inherent in his characters who act out in societies saturated with consumerist imagery and emaciated of meaning. Allegory and symbolism enhance the user engagement, which alludes to the pop culture, literature, and music to make sure the narrative contains added layers of meaning. His characters frequently experience deep existential crises where they're forced to deal with shattered personalities and the quest for purpose in an anarchy society. This essay shows how Murakami deconstructs reality and renegotiates the definition of the human self in a postmodern way, challenging the readers to ponder on the fact that one can be a writer, or an author of life both in fiction and real life. Thus, using the example of the present- oriented consumption, he simultaneously lampoons the modern post-industrial survivors' obsession with consumption and spills the longing for meaningful existence and acknowledgement of the approved concern with the quest for the evaluation in a society becoming post industrialized.

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Meta-fiction, Storytelling, Capitalism, Existentialism, Loneliness

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Water is very much essential to life, but too much of water can have severe consequences on our communities, society and the environment. Floods are some of the most dramatic and severe natural disasters associeted with water that humans are experiencing for thousands of years. Flood is the overflow of water onto normally a dry land. The flooding of a normally dry area caused by rising of water level in an existing waterway, such as a river or pond is called Flood. Flood is enormous amount of water. Sometimes too much of anything called as Flood. Floods are the most frequent type of natural disaster and occur when an overflow of water submerges land that is usually dry. Generally Flooding is a type of extreme weather and it happens when there is heavy precipitation in a very short amount of time. Generally, floods take hours or even days to develop, giving populations time to prepare or evacuate. But many times floods develop quickly and with little warning, at such times people will not be having any time for preparedness.

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Flood, Disaster, Overflow, Warning, Precipitation

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Electronic banking aids users to get access to their funds through an electronic medium, thereby, eliminating the requirement for the banks' customers to visit the bank to do financial transactions. Since a greater number of customers are now using the internet for a host of their daily activities, this digital medium of banking makes banking far accessible and convenient for users. Electronic banking is also known with the names, like, e-banking, virtual banking, online banking, or internet banking. In simple words, the electronic banking is the use of electronic and telecommunications network for delivering different sort of banking products and services. Moreover, a customer can easily access his bank account and carry transactions by using his computer or mobile phone with the help of e-banking. This study throws light on the factors influencing the customer satisfaction on E-Banking services.

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Internet Banking, Customer Satisfaction, E-Banking, Online Banking.

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Brain tumor detection and segmentation are critical tasks in medical imaging analysis for diagnosis and treatment planning. In recent years, computer vision techniques, particularly those implemented using the OpenCV library, have shown promising results in automating these processes. This paper presents a comprehensive review and analysis of brain tumor detection and segmentation methods employing OpenCV. Various techniques, including image preprocessing, feature extraction, and segmentation algorithms, are explored and compared in terms of their effectiveness, computational efficiency, and applicability to different types of brain tumors. Furthermore, challenges and opportunities in this field are discussed, along with potential future research directions. The findings of this study contribute to the advancement of automated brain tumor detection and segmentation systems, ultimately aiding healthcare professionals in improving diagnosis accuracy and treatment planning.

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Brain tumor, OpenCV, medical imaging, segmentation

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