A Secured Data Processing Model for Monitoring the Student’s Performance Using Decentralized Application

2022 ◽  
pp. 133-147
Author(s):  
N. Pooranam ◽  
R. Lakshmana Kumar ◽  
G. Ignisha Rajathi
Keyword(s):  
Data Processing ◽  
Student’S Performance ◽  
Secured Data

scholarly journals Attribute Based Collusion Resistant Controlled Secure Data Processing System Using Node Insertion Method

2021 ◽  
Author(s):  
Dhanalakshmi P. ◽  
Rajarajeswari S ◽  
Nripendra Narayan Das ◽  
Karthikeyan C ◽  
L. Chandra Sekhar Reddy ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Processing ◽  
Data Sharing ◽  
Data Storage ◽  
Processing System ◽  
Software Applications ◽  
Attribute Based Encryption ◽  
Secured Data ◽  
Technological World ◽  
Authorized Access

Abstract In the fast-developing technological world, a large number of informational data is obtained out of different software applications and hardware sources. Data storing, sharing of data, and then processing is more effective through the cloud computing method. In practice, the issue faced is a lack of security where the user details are leaked due to the exposure of software and hardware conflict. Among different data sharing technique, cloud computing is the most convenient method to be adapted due to service satisfying features and economy. Attribute-Based-Encryption (ABE) has the potential to detect even a narrow-drawn data sharing. The drawback of the conventional attribute-based encryption (ABE) poor data security and high over-head computation. The customer side satisfaction is not achieved because of security lacking in narrow-drawn informational data sharing as well as processing. The difficulty in achieving a standardized form of data sharing is an unsolved challenge for secured data processing. The attribute-based data sharing method is more effective for secured data processing in cloud computing. Customer satisfaction can be achieved through the secured services of cloud. The customer’s data should be secured and also the customer’s data is under an authorized access. The protection of data in cloud computing includes the usage of hardware solutions for a secured data operation, provides support in data storage, access, sharing, and automated detecting of risk during data processing.

Taxonorics. II. Formats and coding systems for data processing

1970 ◽  
Vol 126 (6) ◽  
pp. 1053-1067 ◽  
Author(s):  
A. R. Feinstein
Keyword(s):  
Data Processing ◽  
Coding Systems

The Karolinska Hospital Information System

1974 ◽  
Vol 13 (03) ◽  
pp. 125-140 ◽  
Author(s):  
Ch. Mellner ◽  
H. Selajstder ◽  
J. Wolodakski
Keyword(s):  
Information System ◽  
Data Processing ◽  
Data Base ◽  
Hospital Information System ◽  
Care Delivery ◽  
Traditional Approach ◽  
Processing System ◽  
Systems Design ◽  
Data Processing System ◽  
Karolinska Hospital

The paper gives a report on the Karolinska Hospital Information System in three parts.In part I, the information problems in health care delivery are discussed and the approach to systems design at the Karolinska Hospital is reported, contrasted, with the traditional approach.In part II, the data base and the data processing system, named T1—J 5, are described.In part III, the applications of the data base and the data processing system are illustrated by a broad description of the contents and rise of the patient data base at the Karolinska Hospital.

Data Screening Methods – Application to Differential Diagnosis in Pancreatic Pathology from Radiological Signs

1978 ◽  
Vol 17 (01) ◽  
pp. 36-40 ◽  
Author(s):  
J.-P. Durbec ◽  
Jaqueline Cornée ◽  
P. Berthezene
Keyword(s):  
Differential Diagnosis ◽  
Mutual Information ◽  
Data Processing ◽  
Screening Methods ◽  
Automatic Data ◽  
Chronic Calcifying Pancreatitis ◽  
Number Of Patients ◽  
Calcifying Pancreatitis ◽  
Pancreatic Pathology ◽  
Data Screening

The practice of systematic examinations in hospitals and the increasing development of automatic data processing permits the storing of a great deal of information about a large number of patients belonging to different diagnosis groups.To predict or to characterize these diagnosis groups some descriptors are particularly useful, others carry no information. Data screening based on the properties of mutual information and on the log cross products ratios in contingency tables is developed. The most useful descriptors are selected. For each one the characterized groups are specified.This approach has been performed on a set of binary (presence—absence) radiological variables. Four diagnoses groups are concerned: cancer of pancreas, chronic calcifying pancreatitis, non-calcifying pancreatitis and probable pancreatitis. Only twenty of the three hundred and forty initial radiological variables are selected. The presence of each corresponding sign is associated with one or more diagnosis groups.

The Software «MMI–calibration 3.0»

Metrologiya ◽  
2020 ◽  
pp. 16-24
Author(s):  
Alexandr D. Chikmarev
Keyword(s):  
Power Series ◽  
Data Processing ◽  
Statistical Treatment ◽  
Correction Function ◽  
Calibration Function ◽  
Measuring Instrument ◽  
Working Standard ◽  
Calibration Protocol ◽  
Error Probabilities ◽  
Continuous Power

A single program has been developed to ensure that the final result of the data processing of the measurement calibration protocol is obtained under normal conditions. The calibration result contains a calibration function or a correction function in the form of a continuous sedate series and a calibration chart based on typical additive error probabilities. Solved the problem of the statistical treatment of the calibration protocol measuring in normal conditions within a single program “MMI–calibration 3.0” that includes identification of the calibration function in a continuous power series of indications of a measuring instrument and chart calibration. An example of solving the problem of calibration of the thermometer by the working standard of the 3rd grade with the help of the “MMI-calibration 3.0” program.

FORMATION OF METASUBJECT COMPETENCIES IN THE COURSE “INFORMATION TECHNOLOGIES” BY MEANS OF THE BIG DATA PROCESSING LANGUAGE R

2019 ◽  
pp. 12-22
Author(s):  
D. M. Nazarov
Keyword(s):  
Data Processing ◽  
Information Technologies ◽  
Data Sets ◽  
Training Methods ◽  
Economic Knowledge ◽  
R Language ◽  
Currency Exchange ◽  
Business Informatics ◽  
Exchange Data ◽  
Processing Language

The article describes the training methods in the course “Information Technologies” for the future bachelors of the directions “Economics”, “Management”, “Finance”, “Business Informatics”, the development of metasubject competencies of the student while his use of tools for data processing by means of the language R. The metasubject essence of the work is to update traditional economic knowledge and skills through various presentation forms of the same data sets. As part of the laboratory work described in the article, future bachelors learn to use the basic tools of the R language and acquire specific skills and abilities in R-Studio using the example of processing currency exchange data. The description of the methods is presented in the form of the traditional Key-by-Key technology, which is widely used in teaching information technologies.

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