scholarly journals Design and Analysis of Large Data Processing Techniques

2014 ◽  
Vol 100 (8) ◽  
pp. 24-28 ◽  
Author(s):  
Madhavi Vaidya ◽  
Shrinivas Deshpande ◽  
Vilas Thakare
2006 ◽  
Vol 46 (9) ◽  
pp. S693-S707 ◽  
Author(s):  
P Varela ◽  
M.E Manso ◽  
A Silva ◽  
the CFN Team ◽  
the ASDEX Upgrade Team

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3966
Author(s):  
Luigi Carassale ◽  
Elena Rizzetto

Bladed disks are key components of turbomachines and their dynamic behavior is strongly conditioned by their small accidental lack of symmetry referred to as blade mistuning. The experimental identification of mistuned disks is complicated due to several reasons related both to measurement and data processing issues. This paper describes the realization of a test rig designed to investigate the behavior of mistuned disks and develop or validate data processing techniques for system identification. To simplify experiments, using the opposite than in the real situation, the disk is fixed, while the excitation is rotating. The response measured during an experiment carried out in the resonance-crossing condition is used to compare three alternative techniques to estimate the frequency-response function of the disk.


2021 ◽  
Vol 75 (3) ◽  
pp. 76-82
Author(s):  
G.T. Balakayeva ◽  
◽  
D.K. Darkenbayev ◽  
M. Turdaliyev ◽  
◽  
...  

The growth rate of these enterprises has increased significantly in the last decade. Research has shown that over the past two decades, the amount of data has increased approximately tenfold every two years - this exceeded Moore's Law, which doubles the power of processors. About thirty thousand gigabytes of data are accumulated every second, and their processing requires an increase in the efficiency of data processing. Uploading videos, photos and letters from users on social networks leads to the accumulation of a large amount of data, including unstructured ones. This leads to the need for enterprises to work with big data of different formats, which must be prepared in a certain way for further work in order to obtain the results of modeling and calculations. In connection with the above, the research carried out in the article on processing and storing large data of an enterprise, developing a model and algorithms, as well as using new technologies is relevant. Undoubtedly, every year the information flows of enterprises will increase and in this regard, it is important to solve the issues of storing and processing large amounts of data. The relevance of the article is due to the growing digitalization, the increasing transition to professional activities online in many areas of modern society. The article provides a detailed analysis and research of these new technologies.


2021 ◽  
Vol 14 (7) ◽  
pp. 1167-1174
Author(s):  
Zsolt István ◽  
Soujanya Ponnapalli ◽  
Vijay Chidambaram

Most modern data processing pipelines run on top of a distributed storage layer, and securing the whole system, and the storage layer in particular, against accidental or malicious misuse is crucial to ensuring compliance to rules and regulations. Enforcing data protection and privacy rules, however, stands at odds with the requirement to achieve higher and higher access bandwidths and processing rates in large data processing pipelines. In this work we describe our proposal for the path forward that reconciles the two goals. We call our approach "Software-Defined Data Protection" (SDP). Its premise is simple, yet powerful: decoupling often changing policies from request-level enforcement allows distributed smart storage nodes to implement the latter at line-rate. Existing and future data protection frameworks can be translated to the same hardware interface which allows storage nodes to offload enforcement efficiently both for company-specific rules and regulations, such as GDPR or CCPA. While SDP is a promising approach, there are several remaining challenges to making this vision reality. As we explain in the paper, overcoming these will require collaboration across several domains, including security, databases and specialized hardware design.


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