scholarly journals A model for mobile point-to-point data-flow networks without channel sharing

1996 ◽  
pp. 504-519 ◽  
Author(s):  
Radu Grosu ◽  
Ketil Stølen
Keyword(s):  
Data Flow ◽  
Flow Networks ◽  
Point Data ◽  
Point To Point

scholarly journals Using Internet Streamed Data for Sport Visualization

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Rex G. Cammack ◽  
Paul Hunt
Keyword(s):  
Performance Analysis ◽  
Real Time ◽  
Data Flow ◽  
Tracking Data ◽  
Web Mapping ◽  
Dynamic Mapping ◽  
Complex Point ◽  
Point Data ◽  
Athlete Performance

<p><strong>Abstract.</strong> In many modern sports, athlete tracking for athlete performance analysis is a common practice. Most of the time this athlete tracking is done during training sessions. At some World Tour cycling races the broadcasting company and race organizers use athlete tracking data during race events for various graphical for fans of the sport. This research attempt to use the race real time broadcast of data to produce a web mapping application that will show detailed cycling race tactics and other mapping forms in near real time. This research focuses on data flow and processing for dynamic mapping of complex point data patterns.</p>

scholarly journals Measuring Similarity of Deforestation Patterns in Time and Space across Differences in Resolution

Geomatics ◽  
2021 ◽  
Vol 1 (4) ◽  
pp. 464-495
Author(s):  
Desi Suyamto ◽  
Lilik Prasetyo ◽  
Yudi Setiawan ◽  
Arief Wijaya ◽  
Kustiyo Kustiyo ◽  
...  
Keyword(s):  
Geometric Feature ◽  
Data Sets ◽  
Temporal Data ◽  
Spatial And Temporal Patterns ◽  
Data Set ◽  
Point Matching ◽  
Point Patterns ◽  
Visual Sensing ◽  
Point Data ◽  
Point To Point

This article demonstrated an easily applicable method for measuring the similarity between a pair of point patterns, which applies to spatial or temporal data sets. Such a measurement was performed using similarity-based pattern analysis as an alternative to conventional approaches, which typically utilize straightforward point-to-point matching. Using our approach, in each point data set, two geometric features (i.e., the distance and angle from the centroid) were calculated and represented as probability density functions (PDFs). The PDF similarity of each geometric feature was measured using nine metrics, with values ranging from zero (very contrasting) to one (exactly the same). The overall similarity was defined as the average of the distance and angle similarities. In terms of sensibility, the method was shown to be capable of measuring, at a human visual sensing level, two pairs of hypothetical patterns, presenting reasonable results. Meanwhile, in terms of the method′s sensitivity to both spatial and temporal displacements from the hypothetical origin, the method is also capable of consistently measuring the similarity of spatial and temporal patterns. The application of the method to assess both spatial and temporal pattern similarities between two deforestation data sets with different resolutions was also discussed.

Offline Data Sharing Model Based on Encrypted XML Files

2012 ◽  
Vol 488-489 ◽  
pp. 1574-1581
Author(s):  
Wen Yong Weng ◽  
Jian Su ◽  
Xiao Jie Yang ◽  
Zhe Bing Wang
Keyword(s):  
Data Sharing ◽  
Software Module ◽  
Interactive Mode ◽  
Model Based ◽  
Proposed Model ◽  
Extensible Markup ◽  
Xml Signature ◽  
Data Files ◽  
Point Data ◽  
Point To Point

A confidentiality system generally needs to operate under a non-network environment. Hence, the adoption of an offline model is necessary to realize data sharing. An offline data-sharing model based on encrypted Extensible Markup Language (XML) files is designed. The combination of various techniques, such as XML mode, XML encryption, and XML signature, and the introduction of the Security Solution Support Center enable the proposed model to achieve a safe point-to-point data interactive mode and a security-based software module. The software system based on this model can ensure that data files generated from the data provider could only be identified and verified by the authorized data receiver.

Simulation on Optimized Intrusion Detection of Multi-Layer, Distributed and Large Differences Database

2014 ◽  
Vol 556-562 ◽  
pp. 2886-2889
Author(s):  
Nuo Wang ◽  
Yan Li ◽  
Li Min Yuan
Keyword(s):  
Intrusion Detection ◽  
Detection Algorithm ◽  
Data Detection ◽  
Detection Accuracy ◽  
Hierarchical Processing ◽  
Detection Model ◽  
Categorical Attributes ◽  
Point Data ◽  
Point To Point ◽  
Database Intrusion Detection

Different from the traditional single databases, there is a big difference between different layers’ data of multi-level database. The differentiation of categorical attributes is small. Traditional database intrusion detection process is simply to consider the point to point data detection between the layers, without considering the similarity between the layers and ignoring the optimization for detected properties of the applied classification between the levels, resulting in lower detection accuracy. In order to avoid the above-mentioned defects of the conventional algorithm, this paper propos an intrusion detection model of multi-layered network by introducing the coarse-to-fine concept. The intrusion feature of computer database is extracted to be used as the basis for intrusion detection of database. The particle swarm distinguish tree is established to make the hierarchical processing for nodes. Through the probability operation of database intrusion detection in different layers, intrusion detection of multi-layer, distributed and large differences database can be achieved. Experimental results show that the use of the intrusion detection algorithm for multi-layer, distributed and large differences database, can increase the security of the database, ensure the safe operation of the database.

Operating Systems Principles for Data Flow Networks

Computer ◽  
1978 ◽  
Vol 11 (7) ◽  
pp. 86-96 ◽  
Author(s):  
P.J. Denning
Keyword(s):  
Operating Systems ◽  
Data Flow ◽  
Flow Networks

Fuzzy Incidence Blocks and their Applications in Illegal Migration Problems

2017 ◽  
Vol 13 (03) ◽  
pp. 245-260 ◽  
Author(s):  
Sunil Mathew ◽  
John N. Mordeson
Keyword(s):  
International Migration ◽  
Concrete Structure ◽  
Data Flow ◽  
Flow Networks ◽  
Illegal Migration

Incidence blocks in fuzzy incidence graphs (FIGs) are studied in this paper. Incidence relations play very important roles in several natural and human made networks like road, pipe, power and data flow networks. Incidence blocks are characterized using strongest strong incidence paths. A more concrete structure called cyclically strong FIG (CSFIG) is also introduced and an application of fuzzy incidence blocks in illegal international migration is proposed.

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