Volume 10 | Issue 8 |

 Abstract

The massive number of sensors deployed in the Internet of Things (IoT) produce gigantic amounts of data for facilitating a wide range of applications. Deep Learning (DL) would undoubtedly play a role in generating valuable inferences from this massive volume of data and hence will assist in creating smarter IoT. Spamming is the use of messaging or electronic messaging system that send huge amount of data. Spam often fills the internet with multiple copies of a message and are sent to different recipients repeatedly without their request and urges to open them. Spam is type of virus, it is sent for commercial purposes. It can be sent in massive volume by botnets, networks of infected computers. This paper proposed efficient deep learning technique of spam detection for IOT devices application. The simulation is performed using the Python Spyder Software.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Spam. IOT, Python, Deep Learning, Detection, Virus.

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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

 Keywords

Sadaatura, Vasti Chikitsa, Vega Sandhaarana, Lifestyle Disorders

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Creative Commons Attribution 4.0 and The Open Definition

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Investment is a basic requirement of every country. Without investment, no economy will prosper. Investment in the form of FDI is necessary for every country. The investment flow will allow us to invest in different sectors such as agriculture, industry and services. By foreign direct investment, it is possible to convert different types of benefits to the country such as investment, technology, employment, know-how, human resources, skills, knowledge, capabilities from the country. from one country to another. FDI will make the economy stronger. The growth rate of the economy can be determined by the GDP of the country. If the GDP of the country increases, the per capita income of the country will increase, so the living standard of the people will gradually increase, the investments must be by industry and there should be a clear analysis of the investment in the industry., their impact on the unorganized and organized retail sectors as well as on R&D investment and multi-brand retail. There can be inward investment and outward investment, the end result is that the country's economy is expected to grow, in addition to this environmental pollution, the amount of CO2 emissions is also increasing due to this process. industrial. This article was developed based on the existing literature, AND explained the positive and negative aspects of FDI in the Indian economy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

FDI, Indian Economy, Foreign Investments, Environmental Pollution, GDP, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Serial communication is the most well-known approach to send the data the slightest bit at a time over a communication Bus. There are many serial communication protocols such as SPI, CAN, LIN and I2C protocol. CAN and LIN protocols specifications are used for the conformance testing. Conformance testing checks that a product performs as indicated by its predetermined norms. CAN protocols provides with high speed of communication between ECU and modules which are present in autonomous vehicles. CAN protocol serves as a main bus while LIN protocol serves as a sub-bus for the CAN protocol. LIN protocol provides low- cost features. Connecting gateways in between CAN and LIN protocols which exchanges the data between two protocols. For autonomous industry, CAN and LIN protocols are more important along with other protocols such as ethernet, flex-Ray and MOST.

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 Keywords

Serial Communication, Autonomous industry, Modules, BCM and communication protocols.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The unexpected and unplanned first lockdown during the pandemic in the year 2020 had affected the entire economy including the organized and unorganized sectors across the globe. The focal point here is the extent to which the pandemic-induced lockdown has affected the clerical staff and administrative staff in Mumbai. This paper seeks to throw light on the various demographic aspects with special emphasis placed on the change in incomes of the lower income salaried class and possible solutions. As many workplaces opened after the third month of the lockdown, several peons and clerical staff who were either on contract or on temporary basis resumed their jobs but faced pay-cuts. Even though the central government and various state governments announced relief measures and several provisions for the people, it was observed that these measures had not been implemented across all the areas and a majority of the workers and employees did not enjoy any of these benefits. In addition to these issues, the increase in transportation costs and increase in the costs related to healthcare facilities thus had created a further rise in the total expenditure of the peons and clerks who still were either unemployed or were trying to survive on half of their original salaries. The pressure on the peons and their families increased with low salaries or no jobs at all and a huge increase in the expenditure. With no external support from the government or any other institutions, peons faced dark financial situation. Even though the recovery of economy has paced up yet uncertainties persist for the long term, leading to notable damage in the entire section of the community and hence in the future all stakeholders must come together to revive and rework on the policy decisions to sustain crisis periods that benefits the lower-income groups as well as the national interest.

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 Keywords

: Unorganised service sector, Covid-19 Pnademic, Clerical & Administrative Staff and Peons

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Since industrialization is essential to a country's economy, development and industrialization are two parallel wheels for every nation. One of the major businesses in the world, the textile sector offers opportunities to those with no specific training and greatly boosts the economy of many nations. Clothing is one way that the textile industry contributes to human civilization. Numerous environmental risks have been connected to textile effluent. The release of colored wastewater poses a serious risk to both the environment and public health. Since textile wastewater frequently contains a number of contaminants that contaminate the receiving water, it is well-known that it contributes to pollution. Industrial textile processing includes pre-treatment, dyeing, printing, and finishing. A significant by-product of these production processes is chemical pollution. Different organic dyes, chemicals, and auxiliaries are present in textile finishing wastewater, especially dyehouse effluent. In addition to being bright and containing a variety of salts, surfactants, heavy metals, and mineral oils, they also have extreme pH, COD, and BOD values. Therefore, dye bath effluents must be cleaned up before being released into the environment or a municipal wastewater storage facility. There hasn't been a single, cost-effective treatment method that can effectively decolorize textile effluent, which has been a big challenge in recent years. To treat textile wastewater, Physico-chemical and biological (mainly aerobic) systems are frequently employed. In order to reduce COD and BOD, biological processes could be utilized as a pre-treatment decolorization phase in conjunction with conventional treatment methods (such as coagulation-flocculation, and adsorption on activated carbon). This would make them an effective choice for textile dyeing. This study aimed to gain additional knowledge about biological therapy and bioremediation.

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 Keywords

Bioremediation, Biological Treatment, Textile Wastewater.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart disease is becoming one of the most significant reasons for mortality and almost a lot of human beings are suffering from this problem. As we all know it is not so easy to predict the heart disease prior without having very good clinical knowledge. In current days all the predictions are done manually with error rate to find out the abnormalities. In general the manual prediction always makes a lot of errors and a lot of effort is required to process the manual records and hence this motivated me to propose this article in which heart disease prediction can be done by using several Machine Learning algorithms. In general, machine learning is a domain which greatly increases its capabilities in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry. In this proposed work, we propose an ensemble model by collecting several ML classification models in one location and then test which model gives more accuracy in the prediction of heart diseases. This proposed work is trained by using several ML algorithms and then checking the following factors such as accuracy, precision, recall and F1-Score.By conducting various experiments on several ML Algorithms by taking UCI dataset, we finally check which algorithm fits best for efficient heart disease prediction.

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 Keywords

Machine Learning, UCI Dataset, Heart Disease, Ensemble Model, Disease Prediction.

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT India opens a new chapter of its own culture, education spirituality etc. In the same line Buddhism again wake up by the intellectual persons specially the great archeologist Rajendra Lal Mitra who was a pioneer scholar of oriental studies and the renounce Sanskrit Scholar, archivist, historian of Bengal Haraprasad Shastri who innovated charjapada. After discovering the Ashokia Lipi by James Prinsep a British antiquary and colonial administrator, Rajendra Lal Mitra had deeply moved in Buddhism and presented many valuable works like as Bibliotheca Indica, Buddha Gaya: The Great Buddhist Temple, the Hermitage of Sakya Muni. Lalitavistar Sanskrit Buddhist Literature of Nepal etc. Ashok inscriptions are the first legible evidence of Buddhism.

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Mahavihara, Indian Monastic University, Indian Renaissance, Ashokia Lipi, James Prinsep, British antiquary

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Creative Commons Attribution 4.0 and The Open Definition

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In this research paper, I propose a capability maturity model (CMM) for Scientific Data Practices ( SDP) with the core aim of helping hands to assessment and improvement to such practices for building up of effective SDM by content analysis of papers about SDM practices and the reliable management policies. CMM works further by characterizing organizations by level of maturity of these processes. This model will be helpful for data management improvement evaluating SDM practices

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Big Data, Maturity model, Business Analytics, Business value, Scientific Data Management

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Big data, Cloud computing, Health care, Business, Education

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Creative Commons Attribution 4.0 and The Open Definition