Volume 11 | Issue 2 |

 Abstract

Tax audit is very important and so the understanding of the same. The research paper is intended to focus on the understanding the provisions and procedures of the tax auditing. The study discusses on the various clause under which the payee can file tax return. The paper also discusses on the process of filing tax return. For the present study a well structed questionnaire were distributed using simple random sample method and 70 responses were considered for the analysis. The study conclude that the payees are well aware about the tax audit and auditing procedure.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tax Audit, Tax filing Procedure, Tax Provisions, Tax Clauses

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Excellence and competitiveness go hand in hand, and require a mindset and culture where all children are encouraged to work on their skill development. Homework is a vital part of learning. It is an extension of the classroom which allows students to internalize information that has been presented in the class. It helps in increasing the knowledge, attitude and skill of the children at each level. The present study intends to ascertain the opinion of secondary school students towards homework. The main objectives of the study are: 1) to compare the opinion of government and private school students towards homework 2) to compare the opinion of boys and girls towards homework. Survey method is adopted for the present study. A well structured opinionnaire is prepared and administered to collect data. The mean, S.D. and t test are computed for data analysis. Findings reveal that government school students have more positive opinion towards homework than the private school students. Both boys and girls do have the same kind of opinion towards homework at secondary level.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Opinion, homework

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present investigation was aimed for comparative assessment of phytochemicals present in Moringa oleifera leaf and branded moringa leaf powder. Natural and branded powders (carbamide forte and Himalayan organics) were taken as samples. Both methanolic/ethanolic extracts of natural and branded samples showed varied amounts of the constituents like alkaloid, flavonoid, tannin, saponin. Natural leaf powder and samples of brand 2 in ethanolic extracts have higher amounts of alkaloids. In case of flavonoids, Natural samples in methanolic extract had higher amounts as compared to the other extracts. All the samples lack terpenoids. Variations in phytochemical constituents among natural and branded samples indicate that some alteration may have happened during processing or preservation. Branded leaf powders must be labelled with the exact amount of constituents present, as this will facilitate consumers to be aware about the constituents present in herbal supplements which is being used as herbal remedies. Therapeutic role of plants is due to phytochemicals present in them. Any alteration or increase in natural constituents, addition of toxins may show negative/ neutral role in curing certain diseases. Present work justifies that constituents of natural and branded powder of moringa varies during the process of manufacturing, processing and preserving.

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 Keywords

Moringa oleifera, phytochemicals, Thin Layer chromatography (TLC), qualitative, quantitative, therapeutic.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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“शब्द तरंग-जीवन की शाश्वत और यथार्थ अभिव्यक्ति”

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The security of a 5G wireless network will be challenged by a wide range of sophisticated hacking methods. We propose and develop a novel cooperative attack detection method that makes use of a hierarchical Reinforcement Learning (RL) mechanism in order to better identify network assaults and focus on protecting 5G wireless networks from the most severe and cutting-edge forms of network assault, such as DDoS and jamming. Distributed detection systems are operated at the several important nodes of the 5G network (AP, BTS, and servers) to accomplish the cooperative detection. Results from our trials show that the suggested RL detection system improves the ability to identify novel malicious actions and assaults. All network activity is analysed for malicious behaviour using IDS powered by machine learning. Enhancing the intrusion detection system's detection rate was the primary objective of the system design, with a focus on false negative and false positive performance measures. Different machine learning models, including SVM and KNN classifiers, are built and compared.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

5G Wireless Network, Reinforcement Learning, Network Attack Detection, Cyber Threats

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The currency exchange market is the largest and most liquid market in the world. The average daily trading volume in the global foreign exchange and related markets is estimated at $4 trillion. Currencies are fundamental to the majority of people in the globe because they must be traded in order to execute international trade and business, the trading of different currencies and the purchase prediction of one currency in relation to another is the topic that never get old. At the end of the day, fair and accurate estimates of these exchange rates manage international transactions and the worldwide financial system. Effectively estimating the currency exchange rate is a challenging task. We developed a Currency Exchange Rate Prediction System that uses machine learning algorithms to predict Exchange Rate accurately.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Trading, Currency Exchange Rate, Estimates, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Construction materials that are friendly to the environment are now being researched and developed all over the globe in an effort to limit the use of natural resources that are depleting at an alarming rate and to cut down on the production of greenhouse gases. In this respect, geopolymer plays an extremely important function, and a large number of researchers have investigated the numerous dimensions of its viability as a material for binding. In order to alter the geopolymerisation reaction of fly ash, ground granulated blast furnace slag (abbreviated as GGBS) has been used into fly ash-based geopolymer concrete (abbreviated as GPC). In this paper, the influence of various proportions of GGBS (0-100%) on Fly Ash based GPC, as well as the effect of the amount of Alkaline Activated Solution (AAS) in the mixture of GPC, is studied to determine how it affects the compressive strength of the GPC under conditions of ambient temperature. It was observed from the results of the experiments that the compressive strength of the GPC increases both with an increase in the percentage of GGBS and also with an increase in the amount of the sodium silicate solution in which the concentration of sodium hydroxide in the aqueous solution is fixed at a constant value of 10M. This was the case even though the amount of sodium hydroxide that was present in the solution remained the same.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Alkaline Solution, GGBS, Geopolymer, Flyash

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Collapsible soils are black cotton soils with extremely high shear strength when dry but rapidly lose strength when wet. Such rapid and significant loss of strength causes significant distress, resulting in extensive cracking and differential settlements, unstable building foundations, and even the collapse of structures built on these soils. Waste marble dust and Ground Granulated Blast Furnace Slag are industrial byproducts that are produced in massive quantities around the world and pose a threat to the environment. As a result, finding a long-term solution for its disposal is critical. The current study used a physio-chemical technique to reduce the collapse potential of black cotton soil. Because the soil is water-sensitive, it must be stabilised. Different percentages of waste marble dust (WMD) and ground granulated blast furnace slag (GGBFS) were used as an admixture. The effect of admixture on soil parameters such as specific gravity, plasticity index, swelling index, and shrinkage limit is investigated in this study. The study's optimization process revealed that adding waste marble dust improved the geotechnical parameters of black cotton soil significantly. Plasticity was reduced while Unconfined Compressive Strength (UCS) increased significantly. This research evaluates the safe disposal of hazardous waste and converts it into suitable material for engineering purposes

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

UCS, GGBFS, WMD

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Because road damage has resulted in numerous deaths, research into road damage detection, particularly hazardous road damage detection and warning, is essential for traffic safety. Existing road damage detection systems mostly process data on the cloud, which has a large latency due to long-distance transmission. Meanwhile, in these systems that require big, carefully labeled datasets to achieve outstanding performance, supervised machine learning methods are typically used. We suggest using Deep Learning to detect and warn about road damage in this study. The foundation of road surface analysis is visual observations by persons and quantitative analysis by pricey tools. Visual inspection, for example, not only necessitates the use of experienced road managers but also takes time and money. Furthermore, visual inspection is inherently unreliable and inconsistent, increasing the risk. Vi- visual inspection of roads by engineers takes a long time due to the length of roads or freeways. As a result, establishing an AI-based automated system that can determine the sort of damage can help to improve and enhance the way road conditions are assessed.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Road Damage Detection, Deep Learning, Image Processing, CNN, etc

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Creative Commons Attribution 4.0 and The Open Definition