Volume 11 | Issue 10 |

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HUMAN RIGHTS

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HUMAN RIGHTS

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Stock price prediction is an essential task for investors, traders to make informed decision and earn high return. In this study, we will look at the topic of stock price prediction. The price prediction will help the traders and investors to make a idea of the stocks price. Artificial intelligence (AI) in the sense of machine learning and deep learning algorithms can help solve problems. machine learning algorithm has an ability to capture complex pattern and relationship in stock market data . the model is train on the stock price data over the year and is capable of predicting the future stock price. The input data is preprocessed using various technique such as normalization and generalization. The model is evaluated using various performance metrics including mean square error and mean absolute error.

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Price Prediction, Machine learning, Prediction ,LSTM Model , Deep Learning, Price Prediction

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Reinforced concrete, Elevated temperature, Earthquake, Plastic hinge.

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A large amount of almond shell is disposed of every year. The anatomical and chemical characteristics of Indian almond shell are investigated in this paper in order to contribute to better utilization of these shells. The object of the study to introduce the type of concrete that is more costly effective when compared to other concretes. The test results of an ongoing study are an attempt to use the low-cost solid waste material almond shell as a coarse aggregate in the production of structural weight concrete. The BS8110 standards specified acceptable limits for the span reflection ratio of lightweight structural concrete and this study shows the AS concrete complies with this. The micromorphology, surface elements, thermal stability, crystallization, chemical composition and relative properties of almond shell are analyzed. The utilization organic waste materials in concrete beneficial factor for environment. Few studies have been conducted on the use of almond shells in concrete and have shown good potential. This study has investigated the properties and the mechanical behavior of almond shells partially replacing the conventional aggregates in concrete. The replacements were 25, 50, and 75%. The almond shells show a uniform grading in its natural state when obtained from local farmers. Since the organic material is highly porous, it tends to absorb much of the water content in the mix which reduces the slump. Furthermore, with a 5% almond shells replacement, the specimens have shown a compressive strength of 17.03 MPa with density of 1850 kg/m3 which is within the limits of the ACI and BS standards and identified as a structural lightweight concrete. Further recommendations for future studies have been identified based on the results of this study. It can be concluded that for lightweight concrete as a structural material, almond shell shows great as a coarse aggregate. This result especially has significance for low-cost applications such as in housing construction.

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Almond shell, Fine aggregate, Coarse aggregate, Cement, Water

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Chemical admixture, Polycarboxile ether super plasticizer, Non-Destructive test, Ultrasonic pulse velocity, Rebound hammer and Pavements.

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ABSTRACT- Introduction- Vajikarana is one among eight branches of Astangayurveda which is concerned with aphrodisiacs, virility and improving health of progeny the main aim of Vajikaran is always successful copulation for healthy reproduction, with sexual pleasure being just an additional benefit; therefore it is considered a part of 'eugeny.' . Variety of drugs and their preparations (Yoga) have been mentioned in Ayurvedic texts for Vajikarana. VanariGutika mentioned by Bhavaparkasha in Vajikarana chapter and VanariAvaleha a different dosage form having the same ingredients as VanariGutika were selected for clinical trial. Methods- Total 30 patients were selected from the OPD of R.A Podar Ayurveda Medical College ,Worli,Mumbai. The patients were randomly divided into two groups and named as Group A(Vanari Gutika), Group B (Vanari Avaleha) with 15 patients in each group. Result-Highly Significant Results were seen in Group A & Group B in Subjective Parameters. In objective (semen analysis) parameter group A showed no statistically significant changes in Semen Volume, Sperm Count but statistically significant result was found in Sperm Motility% and Sperm Normal Morphology % and group B showed statistically significant results in all objective parameters . Conclusion-Intergroup comparison showed no Statistical significance, though clinically relief in symptoms were observed in both groups

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Keywords- VanariGutika, VanariAvaleha, Vajikarana

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Worldwide, colon cancer is among the top causes of cancer-related fatalities. Accurately identifying and classifying colon cancer early on may significantly improve patient outcomes. In recent years, image analysis has shown promise as a technique for locating and categorizing malignant tissues in the colon. The purpose of this research is to assess methods for visual colon cancer detection and classification. As part of the study technique, samples of both malignant and non-cancerous colon tissues were used to create a collection of picture data. Several preprocessing; methods, including color normalization and picture enhancement, are used to improve image quality. Utilizing techniques like texture analysis and morphological procedures, discriminative characteristics are derived from the photos. Several classification methods, such as support vector machines SVM random forests and PSO ( particle swarm optimization ), are used to categorize the photos into noncancerous groups.

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SVM, Normalization, Texture analysis Enhancement, Malignant and PSO

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It is challenging to make precise assessments of real estate prices due to its elevated individual prices, complicated influencing factors, and ambiguous attribute selection. As a result of the high demand for owner-occupied and investment properties, real estate is also a substantial concern for society. A hot topic for research by major institutions has been how to accurately estimate its price. Real world applications of real estate valuation impose stringent requirements on the acquisition of datasets and the generalizability of models. On the basis of SRGCNN, a spatial regression model with excellent generalizability, this project introduces an external attention mechanism to construct the A-SRGCNN model .For spatial regression, A-SRGCNN employs graph convolutional neural networks, and the external attention mechanism implicitly considers the relationship between property data. Experiments indicate that the A-SRGCNN model outperforms the benchmark model and has improved real estate price estimation accuracy. In the meantime, this project employs the A-SRGCNN model to conduct zonal experiments and time-division experiments and it is revealed that real estate prices exhibit spatial aggregation and price aggregation, with comparable prices within the zones, and that the A-SRGCNN model is effective at predicting house prices.

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GRAPH CONVOLUTIONAL NETWORK-BASED MODEL FOR MEGACITY REAL ESTATE VALUATION

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The Concrete is the most widely used building material in the world, due to its strength, durability and low cost. However, there is always a demand for improving the durability properties of concrete, especially in the face of the ever-increasing demand for sustainable construction materials. This study aims to investigate the durability properties of concrete when jute fibers are used as a reinforcing material. Jute fibers are obtained from the stem of the jute plant, which is a fast-growing crop that requires minimal fertilizer and pesticide input. Jute fibers are also biodegradable and renewable, making them an attractive option for sustainable construction materials. The use of jute fibers in concrete has been found to enhance the mechanical properties of concrete and reduce shrinkage. In this study, the effect of jute fibers on the durability properties of concrete is investigated. The durability properties considered in this study are the water absorption, acid resistance and sulphate resistance of concrete. The jute fibers were added to the concrete at varying percentages of 0.5%, 1%, and 2% by weight of cement.

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durability, jute fiber

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