Volume 9 | Issue 5 |

 Abstract

The performance of the cutting tool subjected to vibration depends upon the operational parameters of the systems. The experimentation is the most reliable means of investigating the vibrational behaviour of the cutting tool during the turning operation on work-piece. However, the empirical expressions developed based on the well-designed experimental observations give much reliable predictions. Hence, the core objective of the present study is to apply design of experiment (DOE) approach on the vibration study of cutting tool considering the four key variables: rotational speed (N) of the spindle i.e. work-piece, feed rate (f), depth of cut (DOC) (dc) and the work-piece diameter (D). Based on the observations, the optimum parameter values identified are: N = 350 RPM, f = 0.15mm/rev, dc = 0.3 mm and D = 40 mm. Moreover, the second order polynomial equation with cross-terms has been identified as the more suitable regression expression than the second and third order polynomial.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tool Vibration, Regression Equation, Design of Experiment, ANOVA Model.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Diabetes mellitus has become a leading concern in the modern society. The number of factors that cause diabetes can be unhealthy lifestyle, lack of exercise, deficient diet, age, genetics, obesity etc. In this research, the proposed methodology tries to improve the accuracy and specificity of predicting diabetes using different machine learning techniques. Experiments observed on Pima Indian Diabetes Dataset and diabetes type dataset have validated the effectiveness and ascendancy of the proposed method.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diabetes, Classification, Deep learning, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

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This paper presents the launch of our VESPA structure through 3 distinctive use cases. In the first place, we use VESPA to recognize and respond powerfully to infection contamination with accessible cloud assets in section. The utilization case introduced in the past part is stretched out to a genuine situation.Second, section subtleties how to utilize VESPA to accomplish different IaaS security level exchange and response in a portable cloud setting. At long last, we utilized the system to benchmark informing capacities and execution overhead into Section.The utilization case turns typical use to perform hostile testing, additionally named fluffing, against the hypervisor. This paper explained how we set up the VESPA system in the sense of the hypervisor and showed that subtle trade-offs are needed for adaptation. Although our assessment shows mitigated outcomes for quick integration, with some tuning, we think it is an appropriate approach. The latest public vulnerabilities have been effectively stopped and the simultaneous fuzzing of drivers dynamically exposes hidden weaknesses. Mixing both security and attack offers a modern, not well-tested solution to third-party code. It is expensive to incorporate VESPA features into the hypervisor and improve the TCB, but it will also boost performance. For more study into this layer, a lighter version of the framework without the unused features (policy structures, dynamic reconfiguration, multi-domain) is a strong candidate.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

VESPA, Cloud, IaaS Security Level, Hostile Testing, Hypervisor.

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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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strategic supply chain management for freight forwarders in valuable cargo

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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

 Keywords

Biotechnology - Biotech and Agrisector - Role of Biotechnology - Area, Production and yield of Plants- Kharif Production .

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Production of waste materials from agriculture in India is increasing day by day. Agricultural wastes are biologically decomposed in the open. Agricultural waste materials can help increase the strength of concrete. The world is now focusing on alternative material sources that cause less harm to the environment. Tons of banana waste are discarded in India, which emit large amounts of methane gas and carbon dioxide, which are harmful to the body when inside and also cause global warming. Banana Leaves Ash is an agricultural product. It has the ability to replace a building material that is cement. Also, many researches has been carried out to use different types of waste in concrete to produce a much economical and sustainable product. The ashes of banana leaves have a pozzolanic reaction that sometimes occurs in cement. After growing a banana tree for consumption of fruits only and discarding the trunks, the use of banana leaves should be explored after the fruits have been harvested. Banana leaf is easily available, it is inexpensive and environmentally friendly. Banana leaf ashes were produced by the process of burning dried banana leaves and collecting its residues. Banana leaf ashes have a lower specific gravity value than normal cement. This makes the resulting concrete lighter with greater proportions of cement. Replacement of cement with banana leaf ash will be beneficial for low-income areas, which will benefit because of its high availability and ease of source and processes that will not be able to keep up with itself. Difficulties are occurring with decreasing average loads on structures that make up the cost and other parameters such as foundation work to reduce cement.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Banana leave ash, Concrete Compressive strength, Cement replacement

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The most fundamental input of the construction sector is concrete, which would be a massively complicated element. Concrete is among the most common structural construction materials due to its strength. Since some manufacturers manufacture out of reach and low quality, there is a growing demand for earthquake-resistant design in the fully prepared concrete industry. Concrete's strength-gaining properties are influenced by a variety of factors. This research aims to use the results of early compressive strength tests to predict strength properties at various ages. The ability to estimate the determination and strength of normal concrete using the early day strength properties result has been examined. Including both concrete and regional concrete mixes, a basic numerical equation forecast the concrete strength at any age is proposed. The goal of this article is to show how artificial neural networks (ANN) and machine learning can be used to forecast the compressive strength of high-performance concrete. On the other side, we'll evaluate the errors of all of the techniques we're using. The dataset used was obtained from the UCI Machine Learning repository. As a result of the research, it was discovered that the Random Forest Algorithm and Artificial Intelligent gives the best performance when all input parameters were used, including cement, slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate, and age.

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 Keywords

Concrete, Strength, Artificial Intelligent, Machine Learning, Performance, Features.

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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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Green marketing , consumer perception ,consumers study

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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

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Virtual platform, scraped questions, OCR, Quiz generation, API, Fetching question

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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

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Bhartrhari Kalashakti Vakyapadiya Shabda Brahma

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Creative Commons Attribution 4.0 and The Open Definition