Volume 9 | Issue 10

 Abstract

Rivers playing a significant role in shaping the cultural geography of regions. Rivers are not just natural phenomena, they are deeply cultural spaces that shape and are shaped by human experiences. The present study tries to assess and analyse the role of Periyar River in shaping the cultural geography of Kalady - Aluva region of Kerala. The cultural geography of Kalady was shaped by both the Periyar and the number of spiritual centres of this river basin. The river ghats of Kalady are inextricably linked with the culture, tradition and beliefs of the people. Aluva is an urban river basin, popularly known for the long sandy stretch called Aluva Manappuram is the cultural landmark of this region. The religious and spiritual centres, ghats, and river basin spaces play a crucial role in providing a place for socio-cultural gatherings. The cultural centres in the river basins exhibit the importance of river in shaping the cultural landscape of the region.

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Cultural Geography, Periyar River, Spiritual Landscape, Cultural Landscape

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The rapid advancements in deep learning architectures have transformed various fields, enabling significant improvements in performance and efficiency. This study presents a comparative analysis of several state-of-the-art deep learning architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers, and Generative Adversarial Networks (GANs). We evaluate their performance based on key metrics such as accuracy, precision, recall, F1 score, and computational efficiency. By conducting experiments on diverse datasets relevant to real-world applications, including healthcare, autonomous vehicles, and natural language processing, we identify the strengths and weaknesses of each architecture. Our findings reveal that while some architectures excel in specific tasks, others offer versatility across multiple domains. The implications of these advancements are discussed, highlighting their potential to drive innovation in various industries. This study aims to provide insights for researchers and practitioners in selecting appropriate deep learning models tailored to their specific applications, thereby advancing the field of artificial intelligence.

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Deep Learning, Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers.

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When automation is driving the competitiveness of your business, organizations need ML to optimize their process. Process automation is vital within enterprise systems such as SAP to decrease manual interference, raise accuracy, and enhance operational flexibility. This paper investigates how to integrate ML into the SAP frameworks to automate core business functions, such as predictive analytics, anomaly detection, and decision processes. This study offers a framework of process automation using contemporary ML algorithms applied to process data, which exploits SAP's inherent capabilities for optimization. The research is to review existing literature on SAP's capacity to automate and implement ML and the challenges in implementation. The paper further details a complete methodology to embed ML models into SAP's enterprise systems and discusses case studies for implementations. Performance metrics and optimization outcomes are referenced via graphs and tables as visuals. Finally, this study concludes with future research directions and the possibility of future advancements in ML-enabled SAP process automation.

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 Keywords

Machine Learning (ML). Process Automation, SAP Frameworks, Predictive Analytics, Optimization

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 Abstract

Gavamayana Samvastara Satrasya Swaroopa Vivaranam

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Gavamayana Samvastara Satrasya Swaroopa Vivaranam

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Salesforce, a leading cloud-based Customer Relationship Management (CRM) platform, offers a suite of tools and applications designed to enhance business operations and decision-making processes. As organizations increasingly rely on data-driven strategies, optimizing Salesforce implementation has become crucial for improving business performance. This paper explores the strategies and methodologies for maximizing the effectiveness of Salesforce to drive better decision-making and overall business outcomes. The study begins by analyzing the core components of Salesforce, including its Sales Cloud, Service Cloud, Marketing Cloud, and Analytics Cloud, to understand their roles in facilitating decision-making. It then delves into best practices for customizing Salesforce solutions to align with organizational goals, focusing on areas such as data integration, automation, and user adoption. Key strategies discussed include tailoring Salesforce dashboards and reports to provide actionable insights, leveraging artificial intelligence (AI) and machine learning for predictive analytics, and implementing process automation to streamline operations. A significant aspect of this research is the exploration of data quality and management within Salesforce. Ensuring accurate, complete, and timely data is essential for reliable decision-making. The paper examines techniques for data cleansing, validation, and governance to maintain data integrity and improve the accuracy of business insights. It also highlights the importance of real-time data processing and how Salesforce's cloud-based infrastructure supports dynamic, on-the-go decision-making. User adoption and engagement are critical for the success of Salesforce implementation. The study reviews strategies for effective change management, including user training, support, and feedback mechanisms. It emphasizes the role of user-centric design in driving higher engagement and satisfaction, thereby maximizing the return on investment in Salesforce. Additionally, the paper addresses the integration of Salesforce with other enterprise systems, such as ERP and marketing automation tools. Seamless integration ensures that data flows smoothly across systems, providing a unified view of business operations and enhancing the accuracy of decision-making. The research explores various integration methods and tools available within the Salesforce ecosystem, including APIs and third-party connectors. Case studies of organizations that have successfully optimized their Salesforce implementations are presented to illustrate real-world applications and outcomes. These case studies provide insights into the practical challenges and solutions encountered during the optimization process, offering valuable lessons for other businesses. In conclusion, the paper underscores the transformative potential of an optimized Salesforce implementation for enhancing decision-making and business performance. By leveraging Salesforce's comprehensive suite of tools and adhering to best practices in customization, data management, and user engagement, organizations can achieve significant improvements in operational efficiency, strategic insight, and overall business success

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Salesforce, CRM, decision-making, business performance, data integration, automation, AI, machine learning, data quality, user adoption, system integration

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Key-value stores are pivotal in modern database architectures due to their simplicity and scalability. However, achieving consistent reads in distributed environments poses significant challenges. This paper explores various optimization techniques designed to ensure consistent reads in key-value stores, focusing on eventual consistency, strong consistency, and hybrid models. We delve into the mechanics of widely-used techniques such as quorum-based approaches, versioning, conflict resolution, and caching strategies. The analysis begins with eventual consistency, which allows read operations to return possibly stale data in favor of higher availability and partition tolerance. This approach's advantage is highlighted through techniques like gossip protocols and anti-entropy mechanisms, which synchronize data over time without immediate consistency. In contrast, strong consistency models prioritize consistency over availability, ensuring that all read operations reflect the most recent write operations. Techniques like Paxos and Raft are examined for their ability to maintain strong consistency through consensus algorithms, albeit at the cost of reduced availability and increased latency. Hybrid models, such as causal consistency, offer a middle ground, allowing reads to be consistent within causally related operations while still offering some level of availability. The paper also explores client-centric consistency models like session consistency, which provide a more tailored approach to consistency by focusing on individual client interactions. Through a series of benchmarks and case studies, this research demonstrates the trade-offs inherent in each optimization technique, providing insights into their applicability based on workload characteristics and system requirements. We also explore emerging trends and future directions in key-value store optimization, such as machine learning-based predictive models for consistency management. Ultimately, this paper aims to equip database architects and engineers with a comprehensive understanding of the techniques available for optimizing consistent reads, empowering them to make informed decisions when designing and implementing key-value stores.

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Key-value stores, consistent reads, eventual consistency, strong consistency, quorum-based approaches, versioning, conflict resolution, caching strategies, Paxos, Raft, causal consistency, client-centric consistency, session consistency, machine learning-based predictive models.

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C?rv?ka is a major materialistic Philosophical school in Indian Philosophy. Their main point is to emphasis on man`s glorification in this universe. Human life is full of hazardous problems as social, economic, natural and many more. The key point of c?rv?ka about man's happiness lies in his own daily days thinking. The problems of social injustice, discrimination of sex, caste are eventually mitigated in their ethical overview. Present life is more important to them and enjoyment in this life is highly appreciated in c?rv?kas ethical theory.

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Happiness, material life, perceptual knowledge, pleasure.

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Abstract Sustainable development has become the buzz word all over the globe from past few decades. Sustainable agriculture is necessary to attain the goal of sustainable development. Green revolution has brought spectacular increase in production and productivity in our country. Food production has increased from 69 million tonnes in 1965 to 275 million tonnes in 2016-17. The increased food grains supply during the last five decades in many parts of the country has ensured national food security. But it has shown the undesirable effects on natural resources, such as soil, water, biodiversity and human health. Farmers are using more fertilizers to get the yield as they were getting with lesser fertilizers twenty to thirty years ago. Consumption of chemical fertilizers {NPK) has been increasing in India during the past fifty three years. It was only 5.43 lakh tones in 1963-64 i.e., before green revolution and reached 259.49 lakh tones in 2016-17. Consumption of pesticides increased from 24.32 thousand tonnes in 1970-71 to 52.75 thousand tones in 2016-17. Injudicious use of fertilizers and exorbitant use of pesticides has led to enormous levels of chemicals buildup in our environment. . It is adversely affecting the health of human being, plants and animals. The present system of agriculture is unsustainable and self destructive. In this context the present study focus on the trends in consumption of fertilizer and pesticides in Indian agriculture and the need for organic farming in India.

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Organic farming, Indian farmers, Agriculture

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The main aim of this study is to assess the cyber security measures used in mobile banking. Nowadays, cyber security in mobile banking is something that needs to be taken into consideration. Banking systems against security threats are activities to protect the expected future value of the information contained in the processing cycle from the threat of danger, both known and unknown potentials, by applying the rules of procedure and protection on IT and banking systems. The impact of activity against this danger is expected to minimize the potential for losses on any threat to protect information, maintain the stability of the process, and reduce the risk of disruption to the activities [1]. Data security is the protection of data from destructive forces and unwanted actions. The concept of "cyber security" originates from "data security," where the information security system aims to create a condition where an organization's information can compete with high confidentiality, integrity, and accessibility. But now, it is closely related to efforts to address the threat to information and IT technology, considering the prospect of an attack against the source of information up to a state of information in transit, because the higher the intensity of information technology, the greater the threat [1]. And the threat is not necessarily a bad thing sourced from domestic and the possibility of information leakage due to an uncontrolled cyber-attack. An attack is an act of intelligence that cannot be underestimated.

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Mobile banking, security measures, fraud, cyber security, systems, computing, software, operating systems, Android, hacking, data breach, authentication, Mobile users

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Because of the British legacy and its influence on contemporary public administration, the civil servants in India lacks Individual Social Responsibility (ISR) in their profession. In this background, this research attempt to study the understanding and practice of ISR by in-service civil servant in Karnataka at their individual and professional level respectively. The nature of the study is descriptive and exploratory. A non-probability sampling technique is adopted. The studies rely on both primary and secondary data. The sample size is 160 consisting of four districts, all level official groups and three types of areas in Karnataka. It used to statistical analysis, such as - percentage analysis and descriptive analysis data interpretation and analysis. The research concludes that, most of the in-service civil servants in Karnataka are aware about the concept of ISR. However, it not well practiced in their profession due many reasons. The study received many valuable suggestions to better practice of ISR by civil servants in Karnataka.

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Individual Social Responsibility, Civil Servant, Public Administration and Karnataka Administration.

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The understanding about the literary context is an integral part of the study of any work of literature. The context in which the literature of a period is placed defines the contours of that work. It adds to the knowledge about the undercurrents which advertently or inadvertently influence the shaping up of different genres of literature. Similar is the scenario of literature from Kashmir, it is filled with moral perplexity, uncertainty, nostalgia, illusion and loss. A wave of different writers is competing to jump into the fray and make their voices heard. Including women and men alike, the ongoing conflict in the region has paved the way for questioning of accepted socio-political and traditional beliefs. The insurgency has changed the very dynamics of the region marked by general disillusionment, skepticism, cynicism and irony. Neurosis, displacement, psychological disorder and social gloom become the order of the day. This paper attempts to have a layered discussion of such a book titled, Tell Her Everything, written by Mirza Waheed.

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Disillusionment, Gloom, Neurosis, Nostalgia, Loss, Uncertainty etc

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The medicinal plants are very much required in both modern healthcare as well as the indigenous healthcare system. The identification and usage of medicinal plants can be considered as living tradition in developing countries like India. The World Health Organization (WHO) opines that nearly 80 percent of primary health care requirements of developing countries are met by the Indigenous knowledge which is of tradition. Such indigenous knowledge system largely depends on the plants which form the bulk of medicines. Unfortunately these plants are facing threat of habitual destruction. The biodiversity as the treasure of flora and fauna should be protected to conserve the indigenous medicinal knowledge and the medicinal plants. Being a ratified country to the Convention on Biological Diversity (CBD) the India has been enacted many laws which directly effects on the existence of medicinal plants. The enacted laws, in one or other way lay some positive and negative effect on the conservation of medicinal plants. But a lot of medicinal plants are disappearing knowingly or unknowingly. Medicinal plants do some protection. It may be in the protected area or other, lack of focused conservation strategy leads to destruction of this valuable healthcare treasure. Most of the plant collections like roots, stem, wood, and sometimes whole plant causes the destructive harvesting. The replacement of local communities who are well known about the medicinal plants leads to depletion of medicinal plants and deprivation of indigenous medicinal knowledge which amounts to great loss of biodiversity. This is threatening to the life and survival of the ethno groups which are depends only on their traditional knowledge for their health care. The indigenous medicinal knowledge is the intellectual asset of local community and its protection strongly affirmed by the World Intellectual Property Organization (WIPO). The major issue with respect to the indigenous medicinal knowledge and plants is the misappropriation by the commercial intellectuals without benefit sharing. India had its bitter experiences with respect to sovereign rights over the natural resources .Fight for right over turmeric, neem, and basmati are the classic examples. Of course such experiences cause to enact the laws to protect our diversified valuable biodiversity which also includes the protection medicinal plants and its knowledge in the local communities. The objective of this article is to analyses the importance of protection of medicinal plants in order to conserve the indigenous medicinal knowledge in India along with the legal issues.

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Indigenous, Medicinal plants, Biodiversity, Ethno group, Destructive harvesting.

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In the dynamic landscape of supply chain optimization, effective warehouse management emerges as a critical determinant of business success. This comprehensive guide navigates through the transformative capabilities of SAP Extended Warehouse Management (EWM), a robust solution designed to revolutionize and streamline warehouse operations. Delving into key functionalities, real-world case studies, and best practices, the article illuminates how SAP EWM enhances process efficiency, provides real-time visibility, and fosters scalability in warehouse management. Through exploration of industry-specific success stories and the integration of IoT, the guide serves as an invaluable resource for businesses seeking to unlock the full potential of SAP EWM in modern warehouse optimization

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Supply Chain Transformation, Productivity, Efficiency, SAP S/4 HANA, Extended Warehouse Management

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 Abstract

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EFFECTS OF NATIONAL TOURISM POLICIES ON KARNATAKA TOURISM: AN ANALYSIS

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A STUDY ON PRIVATISATION OF PUBLIC SECTOR ENTERPRISES IN INDIA - AN ECONOMIC ANALYSIS

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The small pulp and paper mill do not have chemical recovery plant because chemical recovery is the most capital intensive single unit operation in a pulp mill. Due to high capital cost, installing a chemical recovery for small mill is not viable. These mills either discharges the cooking liquor into nearby stream or on land which causes water and land pollution. The spent pulping liquor contain lignins as the major organic component responsible for pollution and since lignin is broadly non-biodegradable. The addition of organic matter to the soil usually increases the water holding capacity of the soil. This is because the addition of organic matter increases the number of micro pores and macrospores in the soil either by "gluing" soil particles together or by creating favourable living conditions for soil organism and ultimately soil condition improves. The present study attempt is made to increase the biodegradability by incorporation of nitrogen. The study revealed that the nitrogen enrichment enhanced the biodegradability of lignin. When this modified lignin applied to soil underwent humification and improved the physico chemical properties of soil.

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Lignin, biodegradation, Soil improvement, Lignin modification

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It is well known that the person's share on health in India is borne by the resident here, according to an estimate, India is between 60 to 70% of this borne. At present, after the Corona period, the state of India and Rajasthan are taking a serious attitude towards government health. Special step has also been taken in the context of giving "right to health" in the state of Rajasthan. How effective this special step is, it will be known in the coming time. As far as the investment in health and the person's satisfaction is concerned, it will be necessary to know the opinion of the people of Rajasthan. This is the topic of this paper, because how effective the investment in health is, will depend on the level of satisfaction and it will give direction to the investment. I am doing my research on this appropriation topic.

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individual satisfaction, rajasthan, investment in health, service quality of healthcare

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The purpose of this study is to explore the feasibility of applying hybrid wavelet-machine learning to make predictions about the occurrence of accidents in the construction industry. Building remains one of Canada's deadliest industry despite recent attempts to enhance safety on construction sites. Safety on construction sites may be improved by the development of an Accident Warning System that can anticipate probable incidents and inform those who are at risk [1]. Workers' safety may be improved by keeping an eye on moving items in real time and giving rapid feedback to them on the results. It is a wavelet-machine learning model that is suggested. Using this model, we can anticipate where the observed items will be in the future. An accident warning is sent when the possibility for an accident has been recognized via the analysis of certain data points. As a result, the model is able to forecast accidents and notify those affected far in advance of their occurrence, giving them plenty of time to react [1]. The decision to issue a warning is made based on the projected repercussions of a possible mishap. Construction sites may benefit from the suggested system's ability to foresee and avoid accidents. It may be used to monitor construction site activities in order to limit the number of accidents and deaths on the job site.

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Accident prediction, hybrid wavelet-machine learning, Construction sites, MARS, SVR

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India has been the worshipper of truth and non - violence since the time immemorial. History is witness of this fact that we have not shed blood in the name of religion. We have not invaded any country in the name of expansion of our territory. We have ever been promoting harmony and peace in every nook and corner of the globe. We knew the limitations and limitlessness of our body, mind and soul. The ideologues and exemplars of ancient and modern India have cemented the pillars of our epistemology that is universally acknowledged. The waves and ripples in the rivers have progressed the flow and glow of our fresh thought. The peaks and tops of the mountains have elevated our ideologies and sense of perception. The sages and saints have melted their bones and flesh in making India that we are proud of.

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New Frontiers of Indian Cinema in the 21st Century: A Techno-Socio-Cultural Discourse

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NURSING PROFESSION: A HISTORICAL PERSPECTIVE

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NURSING PROFESSION: A HISTORICAL PERSPECTIVE

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