Volume 11 | Issue 11 |

 Abstract

Aquaculture is now more profitable business within a short time. These businesses help the best impact in socio-economic condition. Vannamei culture is now a very profitable business within a short time with help for good employment chances. RM rate not possible to increase the profit margin for farmers. Maximum countries have huge production & they supply to all over world in the cheapest rate. Global factors bad impact of economic condition in post covid situation of importing countries Now business policy is reflected for sustainability in problem situation.

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Future of Vannamei

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Cassia alata, commonly known as the ringworm bush or Senna alata, is a medicinal plant widely recognized for its therapeutic potential. This study aimed to perform a comprehensive phytochemical analysis of the leaf extract of Cassia alata using High-Performance Thin-Layer Chromatography (HPTLC) and identify the presence of bioactive compounds. The leaves of Cassia alata were collected, air-dried, powdered, and subjected to sequential extraction using appropriate solvents. The resulting extracts were concentrated, and the dried residue was dissolved in suitable solvents for HPTLC analysis. Silica gel-coated plates were used as the stationary phase, while different mobile phases were employed to achieve optimal separation and resolution of compounds. Preliminary phytochemical screening of the leaf extract revealed the presence of proteins, amino acids, sugars, monosachharides, alkaloids, tanins, sterols, saponins. HPTLC analysis provided detailed information about the phytochemical composition of the leaf extract by comparing the chromatographic profiles with standard compounds and applying suitable detection methods. The HPTLC analysis of Cassia alata leaf extract identified several bioactive compounds, including flavonoids such as quercetin, kaempferol, and their derivatives. These flavonoids are known for their antioxidant, anti-inflammatory, and antimicrobial properties. Additionally, other compounds, such as phenolic acids, alkaloids, and terpenes, were also detected in the leaf extract, suggesting their potential therapeutic activities.

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Cassia, alata, HPTLC, Phytochmicals

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Financial fraud poses a significant threat to business and individual alike Detecting fraudulent transactions in financial data is crucial to safeguarding asset and maintaining trust in financial systems. The project explores the application of One-Class SVM as an effective and efficient tool for identifying fraudulent transactions within large datasets. Financial institutions, payment processors and e-commerce platforms commonly employ such fraud detection techniques to safeguard against financial losses and maintain trust among their customers. The use of One-Class SVM is particularly valuable in situations where fraudulent cases are rare and difficult to distinguish from normal transactions, using traditional classification techniques.-- Financial fraud poses a significant threat to business and individual alike Detecting fraudulent transactions in financial data is crucial to safeguarding asset and maintaining trust in financial systems. The project explores the application of One-Class SVM as an effective and efficient tool for identifying fraudulent transactions within large datasets. Financial institutions, payment processors and e-commerce platforms commonly employ such fraud detection techniques to safeguard against financial losses and maintain trust among their customers. The use of One-Class SVM is particularly -- Financial fraud poses a significant threat to business and individual alike Detecting fraudulent transactions in financial data is crucial to safeguarding asset and maintaining trust in financial systems. The project explores the application of One-Class SVM as an effective and efficient tool for identifying fraudulent transactions within large datasets. Financial institutions, payment processors and e-commerce platforms commonly employ such fraud detection techniques to safeguard against financial losses and maintain trust among their customers. The use of One-Class SVM is particularly valuable in situations where fraudulent cases are rare and difficult to distinguish from normal transactions, using traditional classification techniques.in situations where fraudulent cases are rare and difficult to distinguish from normal transactions, using traditional classification techniques.

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Customer, Financial System, One-Class SVM, Classification technique

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The objective of the present study was to understand the relationship between organisational commitment and locus of control in the service and business sector. Organizational commitment is defined as a view of an organization's member's psychology towards his/her attachment to the organization that he/she is working for, while, locus of control refers to the extent to which individuals believe that they can control events that affect them. Individuals with a high internal locus of control believe that events result primarily from their own behaviour and actions. It was hypothesized that a statistically significant difference was found between business and service sector on the measure of locus of control and organisational commitment. Also, it was hypothesized that significant relation between the above constructs. A two-group design was followed, sample, questionnaires, data was analysed with the help of descriptive and inferential statistics such that t test and correlation were used as a method of analysis. Result indicated no statistically significant difference on the measure of locus of control and organisational commitment between service and business sector. Also, there was no significant relationship between the two variables. The study also posed some limitations and suggested future directions Index Terms:Organisational Commitment, Locus of Control,Business,Service

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Index Terms:Organisational Commitment, Locus of Control,Business,Service

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The novel deals with the modern indian classic that depicts dreadfulpictures of the bengal famine of 1943.

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Famine suffered

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Medicinal plants can be used to treat a wide range of medical conditions. Herbal medicines are frequently used in healthcare. Artemisia pallens Well DC (Asteraceae) are among the most significant medicinal herbs. The plant has been used as a disease treatment by numerous different tribes. The plant's antidiabetic, antifungal, anti-inflammatory, wound-healing, insecticidal, and antibacterial characteristics are only a few of the acts that have been discovered. Chemical elements present in Artemisia pallens Well DC species include alkaloids, glycosides, triterpenoids, phenols, flavonoids, saponins, and tannins. The goal of the current study was to isolate, purify, and characterise the active chemical principle from the Artemisia pallens (Aerial parts). For the extraction process, aerial part of Artemisia pallens species was extracted by soxhelet extraction. The various phytochemical tests were performed. TLC and column chromatography was performed to isolate the compound. The isolated compounds were further characterized by using UV, IR, NMR and GC-MS. The anti-inflammatory activity and anti-viral activity was evaluated by using in-vitro model. In the in-vitro Anti HIV activity was carried out by using pepsin-inhibition assay, choloroform fraction II, showed good inhibition assay activity than the methanol fraction I. In the in-vitro anti-inflammatory activity was carried out by using Egg albumin protein denaturation assay, both methanol Fraction I, showed good inhibition assay activity than the choloroform fraction II.

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Artemisia pallens Well DC, soxhelet extraction, anti HIV, anti-inflammatory, phytochemicals, Isolation

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The landscape of education is undergoing a profound transformation, driven by the ever- advancing field of Artificial Intelligence (AI). This research paper delves into the pivotal role of AI in revolutionizing the educational sector, aiming to empower the future of learning. With a backdrop of the current challenges faced by educational institutions worldwide, we explore the ways in which AI is effectively applied in education, including intelligent tutoring systems, personalized learning, and adaptive assessment. Highlighting the benefits, our research underscores the improvement in learning outcomes, enhanced accessibility, and the increased efficiency AI brings to educational processes. However, no transformation comes without challenges and concerns. This paper addresses critical issues related to data privacy, ethics, and the digital divide, while also examining potential biases inherent in AI algorithms. The inclusion of case studies reveals successful implementations of AI in education, demonstrating the real impact on student performance and engagement. Furthermore, we investigate the synergy of AI with teaching and learning, emphasizing how AI empowers educators to craft more effective teaching materials and personalize education to cater to individual student needs. We also explore AI's role in data-driven decision- making, showing how it assists institutions in resource allocation and student support. Looking ahead, the paper predicts future trends and innovations in AI for education, such as the integration of virtual reality and chatbots. It examines the ethical considerations surrounding AI adoption, with a focus on student data privacy and transparency. Recommendations and best practices are offered to guide educational institutions, policymakers, and stakeholders in the responsible and effective integration of AI. In conclusion, this research underscores the potential of AI to reshape education and drive learning outcomes to new heights. It emphasizes the importance of ethical and responsible AI implementation as we embark on a journey to empower the future of education through AI technology.

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Ai

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The rise in technological advancements and Social Networking Sites (SNS) made people more engaged in their virtual lives. Research has revealed that people feel more comfortable posting their feelings, including suicidal thoughts, on SNS than discussing them through face-to-face settings due to the social stigma associated with mental health .Many suicidal deaths can be prevented by understanding how people communicate their distress related thoughts. Early understanding of the risk factors and warning signs can decrease the threshold for suicide and help prevent many deaths. This Project aims to develop a system that can detect suicidal ideation on Twitter tweets using DL models. In this project we trained several Deep learning models such as LSTM, GRU, and CNN.

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Deep Learning, LSTM (Long Short-Term Memory),CNN(Convolutional Neural Network),GRU(Gated Recurrent Unit).

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Ayurveda is the most ancient and well documented system of medicine which has two aims-maintenance of positive health and the cure of diseases. In current scenario, we are faced with a host of health problems. The herbs which are used to enhance the resistance of body against infections have been a leading theory of Ayurveda and for this there is an independent group of immunomodulatory drugs called as Rasayana. According to modern science, Rasayana can be compared to anti-oxidant, anti-stress, immunomodulatory drugs etc. Immunomodulatory drugs alter the response of the immune system by promotion of health as well as prevention and extermination of the diseases. Antioxidant drugs are having ability to put a break on the oxidation that damages the cells. Similarly in Ayurveda, Rasayana dravyas are also act at various levels like Rasa, Agni and Srotasa. Ayurveda is not just science that deals with diseases and their treatment. It is a way of life that describes how to stay healthy and improve longevity. Rajanighantu is one of the our ancient literature textbook of ayurveda and it has mentioned 37 dravyas as Rasayana.So, screening of Rasayana dravyas from Raj Nighantu can provide useful information to medical practitioners. These Rasayana dravyas can ultimately become useful in healthy individuals and in patients suffering from various infections or diseases in maintaining and enhancing their natural immunity. Here an effort has been carried out to explore the mode of action of Rasayana herbs listed in Raj Nighantu . Also this paper makes an attempt to study Rasapanchkas of these Rasayana dravyas to assess their probable mode of action as Rasayana.

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Rasayan, Immunity, Raj Nighantu, Rasapanchaka , immunomodulator.

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Vehicle counting, classification, and detection have become essential tasks in modern transportation systems and surveillance applications. This abstract presents a comprehensive overview of these critical functions using OpenCV, a popular computer vision library. Vehicle counting involves tracking and tallying the number of vehicles passing through a specific region. OpenCV provides tools for frame differencing, contour detection, and object tracking, allowing for real-time and accurate vehicle counting in various scenarios. Classification goes a step further by categorizing vehicles into different classes, such as cars, trucks, or motorcycles. OpenCV can leverage deep learning models like Convolutional Neural Networks (CNNs) to achieve high-precision vehicle classification based on image features. Vehicle detection, on the other hand, identifies and localizes vehicles within an image or video stream. OpenCV offers pre-trained models like Haar Cascades and YOLO(You Only Look Once) for robust vehicle detection.

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object detection, YOLO, OpenCV, CNN ,

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