scholarly journals An Improved Secure Enabled Information Sharing on Hybrid Cloud

2021 ◽  
Vol 11 (2) ◽  
pp. 374-386
Author(s):  
Dr.V. Sharmila ◽  
S. Poonguzhali ◽  
M. Srivani ◽  
P. Raghul ◽  
Dr.V. Vennila ◽  
...  

Distributed computing guarantees the adaptable conveyance of figuring administrations in a pay-more only as costs arise way. It permits clients to effectively scale their foundation and save money on the general expense of activity. Anyway Cloud administration contributions can possibly flourish if clients are happy with administration execution. Permitting immediate access and adaptable scaling while at the same time keeping up the help leaves and offering serious costs represents a critical test to Cloud registering suppliers. Moreover administrations will stay accessible over the long haul just if this business creates a steady income stream. To address these difficulties we present novel approach based assistance confirmation control models that target expanding the income of Cloud suppliers while considering educational vulnerability with respect to asset prerequisites. Our assessment shows that arrangement based methodologies measurably altogether outflank the early bird gets the worm draws near, which are still cutting edge. Moreover the outcomes give bits of knowledge in how and how much vulnerability contrarily affects income.

Author(s):  
Haitham Baomar ◽  
Peter J. Bentley

AbstractWe describe the Intelligent Autopilot System (IAS), a fully autonomous autopilot capable of piloting large jets such as airliners by learning from experienced human pilots using Artificial Neural Networks. The IAS is capable of autonomously executing the required piloting tasks and handling the different flight phases to fly an aircraft from one airport to another including takeoff, climb, cruise, navigate, descent, approach, and land in simulation. In addition, the IAS is capable of autonomously landing large jets in the presence of extreme weather conditions including severe crosswind, gust, wind shear, and turbulence. The IAS is a potential solution to the limitations and robustness problems of modern autopilots such as the inability to execute complete flights, the inability to handle extreme weather conditions especially during approach and landing where the aircraft’s speed is relatively low, and the uncertainty factor is high, and the pilots shortage problem compared to the increasing aircraft demand. In this paper, we present the work done by collaborating with the aviation industry to provide training data for the IAS to learn from. The training data is used by Artificial Neural Networks to generate control models automatically. The control models imitate the skills of the human pilot when executing all the piloting tasks required to pilot an aircraft between two airports. In addition, we introduce new ANNs trained to control the aircraft’s elevators, elevators’ trim, throttle, flaps, and new ailerons and rudder ANNs to counter the effects of extreme weather conditions and land safely. Experiments show that small datasets containing single demonstrations are sufficient to train the IAS and achieve excellent performance by using clearly separable and traceable neural network modules which eliminate the black-box problem of large Artificial Intelligence methods such as Deep Learning. In addition, experiments show that the IAS can handle landing in extreme weather conditions beyond the capabilities of modern autopilots and even experienced human pilots. The proposed IAS is a novel approach towards achieving full control autonomy of large jets using ANN models that match the skills and abilities of experienced human pilots and beyond.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Sun ◽  
Fei Zhang ◽  
Jing Li ◽  
Yicheng Yang ◽  
Xiaolin Diao ◽  
...  

Abstract Background With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can improve semantic interoperability. One key improvement of openEHR is that it allows for the use of existing archetypes. The crucial problem is how to improve the precision and resolve ambiguity in the archetype retrieval. Method Based on the query expansion technology and Word2Vec model in Nature Language Processing (NLP), we propose to find synonyms as substitutes for original search terms in archetype retrieval. Test sets in different medical professional level are used to verify the feasibility. Result Applying the approach to each original search term (n = 120) in test sets, a total of 69,348 substitutes were constructed. Precision at 5 (P@5) was improved by 0.767, on average. For the best result, the P@5 was up to 0.975. Conclusions We introduce a novel approach that using NLP technology and corpus to find synonyms as substitutes for original search terms. Compared to simply mapping the element contained in openEHR to an external dictionary, this approach could greatly improve precision and resolve ambiguity in retrieval tasks. This is helpful to promote the application of openEHR and advance EHR information sharing.


2020 ◽  
Vol 245 ◽  
pp. 03036
Author(s):  
M S Doidge ◽  
P. A. Love ◽  
J Thornton

In this work we describe a novel approach to monitor the operation of distributed computing services. Current monitoring tools are dominated by the use of time-series histograms showing the evolution of various metrics. These can quickly overwhelm or confuse the viewer due to the large number of similar looking graphs. We propose a supplementary approach through the sonification of real-time data streamed directly from a variety of distributed computing services. The real-time nature of this method allows operations staff to quickly detect problems and identify that a problem is still ongoing, avoiding the case of investigating an issue a-priori when it may already have been resolved. In this paper we present details of the system architecture and provide a recipe for deployment suitable for both site and experiment teams.


2018 ◽  
Vol 7 (1.7) ◽  
pp. 156
Author(s):  
S Ravikumar ◽  
E Kannan

One of the immense risk to benefit accessibility in distributed computing is Distributed Denial of Service. Here a novel approach has been proposed to limit SDO [Strewn Defiance of Overhaul] assaults. This has been wanted to accomplish by a canny quick motion horde organize. An astute horde arrange is required to guarantee independent coordination and portion of horde hubs to play out its handing-off tasks. Clever Water Drop calculation has been adjusted for appropriated and parallel advancement. The quick motion system was utilized to keep up availability between horde hubs, customers, and servers. We have intended to reproduce this as programming comprising of different customer hubs and horde hubs


2021 ◽  
Vol 10 (1) ◽  
pp. 13-17
Author(s):  
S. Ravichandran ◽  
J. Sathiamoorthy

Distributed computing has been imagined as the cutting edge engineering of IT Enterprise. It moves the application programming and information bases to the incorporated enormous server farms, where the administration of the information and administrations may not be completely dependable. There are various security issues for distributed computing as it envelops numerous innovations including networks, information bases, working frameworks, virtualization, asset planning, exchange the board, load adjusting, simultaneousness control and memory the executives. Putting away information in an outsider's cloud framework causes genuine worry over information secrecy. Hence, security issues for a large number of these frameworks and advancements are material to distributed computing. We propose a key worker encryption conspire and incorporate it with a decentralized deletion code with the end goal that a safe conveyed stockpiling key framework is defined respectively.


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