An enhanced quantum key distribution protocol for security authentication

Kumar, Ankit; Dadheech, Pankaj; Singh, Vijander; Raja, Linesh; Poonia, Ramesh Chandra

doi:10.1080/09720529.2019.1637154

Cited by 70 publications

(9 citation statements)

References 6 publications

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“…This also contains the accuracy of the result with well monopoly with the metadata. Because of its perceptual uniformity, the HSV color space is used in this dissertation [16]. That is, the three components H (Hue), S (Saturation) and V (Value) are closely related with the way human eye perceives the color.…”

Section: Algorithmmentioning

confidence: 99%

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Kumar¹,

Singh²,

Raja³

et al. 2021

Self Cite

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In recent years, scholars have found content-based image recovery to be a particularly interesting and exciting field. This field develops quick image recovery algorithms that are very similar to pictures from various data sources. There is currently a lot of space and sources for data storage. Finally, once data sources are obtained, there is just competition for the exact and best result. The result is filtered using the heuristic correlation based on the above features of the photographs. The overall matching scores are calculated by adding all these individual feature ratings. The recommended method will be used to retrieve all images containing the content of the query image. The scores will be used to rate the match. The results of the combined method simulation demonstrate that the strategy is successful. This proposed model will improve the accuracy of search results. This research model, like the other metadata models on the web, is interactive and familiar for searching pictures from huge databases and data sources. This model also has a number of handy features built in to improve precision and efficiency. Although there are a few little mysteries in this model, they must be answered subsequently.

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Section: Algorithmmentioning

confidence: 99%

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Kumar¹,

Singh²,

Raja³

et al. 2021

Self Cite

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show abstract

“…This section outlines the FOCOMO method into three phases: (i) Data Engineering, (ii) COVID-19 cases forecast, and (iii) Forecast curve normalization. Some decision support systems related for forecasting are available in [32][33] [34]. Each phase has further steps, as shown in Fig.…”

Section: Focomo Modelmentioning

confidence: 99%

FOCOMO: Forecasting and monitoring the worldwide spread of COVID-19 using machine learning methods

Agrawal

Madaan

Roy

et al. 2021

Journal of Interdisciplinary Mathematics

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More than 185 countries get affected in the present SARS-COV-2 (aka COVID-19 or n-Corona virus) epidemic. Experts from different domains are contributing a lot to combat this pandemic effectively. Data analysts have made lots of efforts, IT experts also to forecast the severity of infected cases, the death rate, recovery rate, and other health indicators using various statistical and machine learning models. These forecasting models may motivate and help the policymakers to make the decisions based on these predicted results. Although any prediction on such a pandemic problem is non-monotonic and uncertain, these predictions may help us plan to take the needful actions while dealing with this tragic situation. Lots of symptomatic and asymptotic human behavior are observed while investigating the cases. Also, many countries are making dynamic changes in their policies to combat this pandemic. Therefore, such heterogeneous and dynamic changes in policies and human behavior make the problem of proposing an accurate predicting model more complex. We used machine learning methods to monitor the COVID-19 impact country-wise and developed a FOCOMO model to forecast the severity worldwide till the mid of Oct 2020. We referred to the COVID-19 dataset publicly shared by John Hopkins University. We proposed a purely predictive model to monitor the pandemic (without claiming it as perfect or accurate) into three Phases: i) categorization of countries based on the severity of COVID-19 cases, ii) prediction of daily case reporting, and iii) normalization of flattening the forecasting curve based on deaths and recovery rate. These forecasting models will help monitor and plan the human behaviors and severity of the pandemic country-wise and will provide an opportunity to take some corrective actions for shaping the future.

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“…Here pointer or key value point to the particular row_id. Bitmap index is most efficient in the data warehouse, the reason is, it contains the large query which is suitable for the bitmap index and normally large query contains the WHERE clause, and it makes bitmap index more efficient for query processing [18]. When we insert millions of records in a particular table then we find there are millions of logs that would be generated because internally only one record is executed at a time.…”

Section: Research Articlementioning

confidence: 99%

An Improved Framework for Bitmap Indexes and their Use in Data Warehouse Optimization

Preetha¹

2021

TURCOMAT

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Compression technique is basically used to compress the size of table or reduce the storage area. Oracle already gives this feature for the table compression as well as for the index compression. when index is created on particular column of a table then it contain some space, which require some storage or disk space by this technique we can save our disk space because in industry the company have to purchase the disk space according to the size of the their data and pay according to their disk space. To utilize this disk space for useful records data rather than wasting it. In this paper used the data pump utility for the compression of Bitmap index and table. Data pump utility performed for the logical backups in database.in this paper implemented data pump for compression, to release the space and change the index pointing location. It will not release the space even after deletion of records. This is of special interest for the case to compress the bitmap index and table space along with the’S (Data Manipulation Language).

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An enhanced quantum key distribution protocol for security authentication

Cited by 70 publications

References 6 publications

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

FOCOMO: Forecasting and monitoring the worldwide spread of COVID-19 using machine learning methods

An Improved Framework for Bitmap Indexes and their Use in Data Warehouse Optimization

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