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Purohit, G. N.
- Computing Installation Parameters of CCTV Cameras for Traffic Surveillance
Abstract Views :207 |
PDF Views:138
Authors
Affiliations
1 Department of Computer Science, Banasthali Vidyapith, Jaipur, IN
2 Department of Computer Science, Banasthali Vidyapith, Newai, Rajasthan, IN
1 Department of Computer Science, Banasthali Vidyapith, Jaipur, IN
2 Department of Computer Science, Banasthali Vidyapith, Newai, Rajasthan, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 4, No 6 (2012), Pagination: 105-124Abstract
For properly installing CCTV cameras on any intersection point for traffic surveillance, some parameters need to be determined in order to get maximum benefit. The height, angle of placement of the CCTV camera is used to determine the view or the area that the camera will cover with proper resolution. The resolution should not be too high to cover less traffic and should not be too low to cover large but hardly distinguishable traffic.
This paper concerns with computation of the required CCTV installation parameters for the correct placement of CCTV camera. The simulation experiment has been done in ArcGIS to calculate different parameters and compare different computation results, and provide the necessary parametric specifications to install CCTV at a site. Viewshed Analysis is carried out to find the influence of variations in various parameters on the traffic images. Various comparisons are shown and best parameters are presented in results.
Keywords
CCTV, Viewshed Analysis, Google Earth, ArcGIS, Traffic Surveillance.Full Text
- A Modified K-Means Algorithm that Determines Number of Clusters Automatically
Abstract Views :268 |
PDF Views:2
Authors
Affiliations
1 Banasthali University, Banasthali, Rajasthan, IN
1 Banasthali University, Banasthali, Rajasthan, IN
Source
International Journal of Knowledge Based Computer System, Vol 4, No 2 (2016), Pagination: 8-23Abstract
This paper presents a modified k-means that not only increases classification accuracy but also determines optimal number of clusters automatically. It is a two phase clustering algorithm based on k-means, membership degree and standard deviation. Phase I automatically determines the number of clusters. Standard deviation of membership value helps us to identify number of clusters automatically. The phase II increases the classification accuracy. It does not require number of clusters as parameters like other previous most widely used unsupervised pattern clustering algorithms such as Fuzzy C-means and K-means. Experiments were done on some benchmark datasets and synthetic datasets to evaluate the performance of proposed approach.Keywords
Clustering, Validitymeasures, K-Means, Membership Degree Introduction.
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- Evaluation of Alternative Centrality Measure Algorithm for Tracking Online Community in Social Network
Abstract Views :104 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, Banasthali Vidyapith, Bansthali, Rajasthan, IN
1 Department of Computer Science, Banasthali Vidyapith, Bansthali, Rajasthan, IN
Source
International Journal of Engineering Research, Vol 1, No 1 (2012), Pagination: 28-33Abstract
Network centrality is used to identify the most important/active people at the center of a network or those that are well connected. The tracking of single community in social networks is commonly done using some of the centrality measures employed in social network. The betweenness centrality measures has been used in SCAN (Social Cohesion Analysis of Network) method to track communities in social networks. This paper evaluates new alternative eigenvector centrality measures for tracking community and is more suitable compared to betweenness centrality measures algorithm.Keywords
Social Network Analysis, Centrality, Betweenness Centrality, SCAN, Communities, Eigenvector Centrality.Full Text
- Elliptic Curve Point Multiplication Using MBNR and Point Halving
Abstract Views :133 |
PDF Views:0
Authors
Affiliations
1 Department of Mathematics, Banasthali University, Jaipur-304022, Rajasthan, IN
2 Department of Computer Science, Banasthali University, Jaipur-304022, Rajasthan, IN
3 Department of Computer Science, KNIT, UPTU, Sultanpur-228188, Uttar Pradesh, IN
1 Department of Mathematics, Banasthali University, Jaipur-304022, Rajasthan, IN
2 Department of Computer Science, Banasthali University, Jaipur-304022, Rajasthan, IN
3 Department of Computer Science, KNIT, UPTU, Sultanpur-228188, Uttar Pradesh, IN
Source
International Journal of Advanced Networking and Applications, Vol 3, No 5 (2012), Pagination: 1329-1337Abstract
The fast implementation of elliptic curve cryptosystems relies on the efficient computation of scalar multiplication. As generalization of double base number system of a number k to multi-base number system (MBNR) provides a faster method for the scalar multiplication is most important and costly operation (in terms of time) in ECC, there is always a need of developing a faster method with lower cost. In this paper we optimize the cost of scalar multiplication using halving and add method instead doubling and tripling methods. The cost is reduced from 40% to 50% with respect to the other fastest techniques.Keywords
Double Base Number System, Elliptic Curve Cryptography, Multi-Base Number System, Point Halving, WSN.Full Text