Volume 9 | Issue 5 |

 Abstract

The coronavirus 2019(COVID-19), which first occur in wuhan city of China in December 2019, spread quickly around the world and became a plague. It is necessary to detect the positive cases as early as possible so as to prevent the further spread of this disease. Application of convolutional neural networks (CNN) techniques coupled with medical imaging can be helpful for the accurate detection of this disease. In this project a new model for automated COVID-19 detection using raw chest X-ray images is used. The model is developed to supply accurate diagnosis for binary classification (COVID vs No-Findings). Our model produced an accuracy of 98.44%. The sequential model was used to train a model using Keras and Tensorflow. We introduced convolutional layers and implemented different filtering on each layer.

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 Keywords

Convolutional Neural Networks, Keras, Tensor-flow, Feature Extraction, Sequential Model.

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 Abstract

Improving employee engagement in an organization has become a priority concern as committed employees follow the vision, principles, and intent of their jobs. Employee engagement is seen as a significant indicator of good results in organizations. Considering the value of employee engagement, this paper discusses possible talent management practices scenarios in Indian public sector banks and how they improve employee engagement. Additionally, it explores how talent management practices and employee engagement in Indian public sector banks could affect employee retention and performance. This research indicates several verifiable theories that talent management approaches are impacting the productivity and success of employees. This further demonstrates that talent management practices affects firm results. This research suggests validating these hypotheses on the survey focused on employees' data from the top four banks of the public sector in Rajasthan, India. The study would add to the literature on talent management by analyzing how talent management practices influence organizational outcomes, including retention of employees and the performance of employees.

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 Keywords

Talent management practices; employee engagement; employee retention; employee performance.

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 Abstract

In this paper we have designed a Circular microstrip patch antenna operating at 5GHz using FEM based EM simulator software - Ansys HFSS v15.0 The circular patch antenna is designed on a FR4 substrate with di electric constant & 4.4 and height of the substrate is 1.6mm. Several antenna characteristics such as return loss, radiation pattern, percentage bandwidth, directivity, antenna gain, radiation efficiency etc. are studied. The designed circular patch antenna shows return loss value well below -30dB and a percentage bandwidth equal to 3.79% is achieved. Also, a good directivity value of 3.59dBi and antenna gain equal to 1.78dBi is ob serIn this paper we have designed a Circular microstrip patch antenna operating at 5GHz using FEM based EM simulator software - Ansys HFSS v15.0 The circular patch antenna is designed on a FR4 substrate with di electric constant & 4.4 and height of the substrate is 1.6mm. Several antenna characteristics such as return loss, radiation pattern, percentage bandwidth, directivity, antenna gain, radiation efficiency etc. are studied. The designed circular patch antenna shows return loss value well below -30dB and a percentage bandwidth equal to 3.79% is achieved. Also, a good directivity value of 3.59dBi and antenna gain equal to 1.78dBi is ob served. Since the circular microstrip patch antenna is designed at C band it is applicable in different satellite communication applications such as transponder etc. ved. Since the circular microstrip patch antenna is designed at C band it is applicable in different satellite communication applications such as transponder etc.

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 Keywords

Circular Microstrip patch antenna, Percentage Bandwidth, Directivity, Antenna Gain, HFSS

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Audio sentiment analysis using automatic speech recognition is an emerging research area where opinion or sentiment exhibited by a speaker is detected from natural audio. It is relatively under-explored when compared to text based sentiment detection.

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 Keywords

Audio recognizer, Machine Learning, Sentiment Analysis, Maximum Entropy Text Sentiment Detection algorithm.

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 Abstract

The objectives of the present study was to highlight the use of medicinal plants treating numerous diseases of plants with different etiologies throughout the history. The main aim of this research paper is to determine the in vitro antifungal activity of zingiber rhizome extract against some isolated fungi viz., F. oxysporum, F. solani, F. moniliforme, H. sativum, C. lindemuthianum, C. lunata, R. solani, A. solani from different vegetables. Both the aqueous and alcoholic extracts of zingiber were screened for the phytochemical constituents and were tested against fungal pathogens. Result of phytochemical screening, revealed the presence of tannins, alkaloids, saponins, flavonoids, steroids and cardiac glycosides. The aqueous extract exhibited less fungitoxic activity as compared to methanolic extracts. The methanol extract of Z. offinale was also effective against all the pathogens with highest inhibition of mycelial was recorded in A. solani with 86.41% and lowest by C. lunata with 73.99% inhibition of mycelial growth.

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 Keywords

Medicinal Plants, Phytochemical Screening, Fungal Pathogens, Aqueous extract, Methanolic Extract.

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 Abstract

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 Keywords

Keywords: Customer Delight, Customer Satisfaction, Customer retention, repurchase intention, word-of-mouth.

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 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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 Keywords

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

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 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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 Keywords

Diabetes, Classification, Deep learning, Machine Learning

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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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 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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 Keywords

strategic supply chain management for freight forwarders in valuable cargo

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Creative Commons Attribution 4.0 and The Open Definition