A new approach based mobile agent system for ensuring secure big data transmission and storage

2017 ◽  
Author(s):  
Dounya Kassimi ◽  
Okba Kazar ◽  
Hamza Saouli ◽  
Safa Saifi ◽  
Iman Hassani ◽  
...  
Keyword(s):  
Big Data ◽  
Mobile Agent ◽  
Data Transmission ◽  
Agent System ◽  
New Approach ◽  
And Storage

Data Security Research for Cloud Computing

2014 ◽  
Vol 687-691 ◽  
pp. 2764-2767
Author(s):  
Qiang Li ◽  
Kui Yang ◽  
Li Ma
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Transmission ◽  
Data Security ◽  
Network Technology ◽  
Cloud Environment ◽  
Service Model ◽  
Storage Security ◽  
Security Research ◽  
And Storage

With the popularity of the cloud computing, network technology obtains unprecedented development and revolution. Cloud computing is the direction of cyberspace storage in the computer and internet filed. Big data and multi-dimensional storage and calculation along with the cloud computing. Therefore, internet data security is the key point. For example, based on the cloud environment, the big data transmission and storage requires encryption technology. This article will research the data security of cloud computing, design the service model of data security encryption, and realize data transmission and storage security service of computer and internet cloud environment.

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Research on mobile Internet mobile agent system dynamic trust model for cloud computing

2019 ◽  
Vol 16 (7) ◽  
pp. 174-194 ◽  
Author(s):  
Weijin Jiang ◽  
Yang Wang ◽  
Yirong Jiang ◽  
Jiahui Chen ◽  
Yuhui Xu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Agent ◽  
Trust Model ◽  
Mobile Internet ◽  
System Dynamic ◽  
Agent System ◽  
Dynamic Trust

scholarly journals New approach for localization and smart data transmission inside underground mine environment

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Ankita RayChowdhury ◽  
Ankita Pramanik ◽  
Gopal Chandra Roy
Keyword(s):  
Data Transmission ◽  
Signal To Noise Ratio ◽  
Visible Light Communication ◽  
Underground Mine ◽  
Control Room ◽  
Time Data ◽  
New Approach ◽  
Mine Environment ◽  
Surface Control ◽  
Smart Data

AbstractThis paper presents an approach to access real time data from underground mine. Two advance technologies are presented that can improve the adverse environmental effect of underground mine. Visible light communication (VLC) technology is incorporated to estimate the location of miners inside the mine. The distribution of signal to noise ratio (SNR) for VLC system is also studied. In the second part of the paper, long range (LoRa) technology is introduced for transmitting underground information to above the surface control room. This paper also includes details of the LoRa technology, and presents comparison of ranges with existing above the surface technologies.

scholarly journals Wheat Grinding Process with Low Moisture Content: A New Approach for Wholemeal Flour Production

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 32
Author(s):  
Waleed H. Hassoon ◽  
Dariusz Dziki ◽  
Antoni Miś ◽  
Beata Biernacka
Keyword(s):  
Particle Size ◽  
Moisture Content ◽  
Average Particle Size ◽  
Average Particle ◽  
Grinding Process ◽  
Mixing Properties ◽  
New Approach ◽  
Grain Moisture ◽  
Flour Production ◽  
And Storage

The objective of this study was to determine the grinding characteristics of wheat with a low moisture content. Two kinds of wheat—soft spelt wheat and hard Khorasan wheat—were dried at 45 °C to reduce the moisture content from 12% to 5% (wet basis). Air drying at 45 °C and storage in a climatic chamber (45 °C, 10% relative humidity) were the methods used for grain dehydration. The grinding process was carried out using a knife mill. After grinding, the particle size distribution, average particle size and grinding energy indices were determined. In addition, the dough mixing properties of wholemeal flour dough were studied using a farinograph. It was observed that decreasing the moisture content in wheat grains from 12% to 5% made the grinding process more effective. As a result, the average particle size of the ground material was decreased. This effect was found in both soft and hard wheat. Importantly, lowering the grain moisture led to about a twofold decrease in the required grinding energy. Moreover, the flour obtained from the dried grains showed higher water absorption and higher dough stability during mixing. However, the method of grain dehydration had little or no effect on the results of the grinding process or dough properties.

scholarly journals Challenges of Big Data analysis

2014 ◽  
Vol 1 (2) ◽  
pp. 293-314 ◽  
Author(s):  
Jianqing Fan ◽  
Fang Han ◽  
Han Liu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Measurement Errors ◽  
Modern Society ◽  
Big Data Analysis ◽  
Small Scale ◽  
Paradigm Change ◽  
Statistical Inferences ◽  
The One ◽  
And Storage

Abstract Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

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