International Journal of Computer Networks and Communications Security

Volume 4, Issue 6, June 2015

 

 

 

Cost Effective FMCW Radar for Doppler and Ranging

Pages: 137-140 (4) | [Full Text] PDF (822 KB)
HA Abbasi, SH Shaukat, I Shaheen, Z Khitab
Electrical Engineering Department, Army Public College of Management & Sciences, Rawalpindi, Pakistan

Abstract -
The complexity and high cost factor has restricted the use of Radar technology in daily life common applications, due to which the interest and this field itself is waning out among student community. In this paper we present a simple, cost effective Radar system of FMCW architecture working in 2.4GHz ISM Band. The system is designed as a training module for microwave laboratory. Modes of operation includes Ranging and Doppler measurement. Despite low cost and less circuitry involved than existing systems desirable results are obtained.
 
Index Terms - FMCW, CW Ranging, Doppler, ISM

Citation - HA Abbasi, SH Shaukat, I Shaheen, Z Khitab. "Cost Effective FMCW Radar for Doppler and Ranging." International Journal of Computer Science and Software Engineering 4, no. 6 (2015): 137-140.

 

Workload Schedulers - Genesis, Algorithms and Comparisons

Pages: 141-155 (15) | [Full Text] PDF (329 KB)
L. Sliwko, V. Getov
Faculty of Science and Technology, University of Westminster, 115 New Cavendish Street, United Kingdom

Abstract -
In this article we provide brief descriptions of three classes of schedulers: Operating Systems Process Schedulers, Cluster Systems Jobs Schedulers and Big Data Schedulers. We describe their evolution from early adoptions to modern implementations, considering both the use and features of algorithms. In summary, we discuss differences between all presented classes of schedulers and discuss their chronological development. In conclusion we highlight similarities in the focus of scheduling strategies design, applicable to both local and distributed systems.
 
Index Terms - Schedulers, Workload, Cluster, Cloud, Process, Big Data

Citation - L. Sliwko, V. Getov. "Workload Schedulers - Genesis, Algorithms and Comparisons." International Journal of Computer Science and Software Engineering 4, no. 6 (2015): 141-155.

 

Reflections on Temporal Analysis with Landsat 5 e 8 Images - The Use of the NDBI to the Evaluation of Urban Expansion between 2010 e 2014, in the Marica City, in Rio de Janeiro - Brazil

Pages: 156-159 (4) | [Full Text] PDF (747 KB)
EMFR Souza
Department of Geography, Federal University of Rio de Janeiro, Laboratory Espaco de Sensoriamento Remoto Rio de Janeiro, RJ 21941-916, Brazil

Abstract -
This article proposes to evaluate the use of Normalized Difference Built-up Index, to identification of the urban areas from satellite images Landsat 5 e 8, indicating the advantages and problems faced. The results show a great difference between the scenes TM, Landsat 5 e OLI do Landsat 8. The Radiometric difference interfere directly in the calculation of NDBI. The areas with urban expansion are overestimated in 2010 and underestimated in 2014 when are compared the indexes generated with Landsat 5 TM sensor images and OLI Landsat 8. Some areas for exposed soil and wetlands are regarded as urban land in the Landsat 5. In this situation it is suggested to use the same kind of images, ie imagens Landsat 5 and Landsat 8 from different periods; or do the normalization between scenes.
 
Index Terms - Remote Sensing, Urban, Landsat Image, NDBI, Mapping

Citation - EMFR Souza. "Reflections on Temporal Analysis with Landsat 5 e 8 Images - The Use of the NDBI to the Evaluation of Urban Expansion between 2010 e 2014, in the Marica City, in Rio de Janeiro - Brazil." International Journal of Computer Science and Software Engineering 4, no. 6 (2015): 156-159.

 

Determining a Cluster Centroid of K-Means Clustering Using Genetic Algorithm

Pages: 160-164 (5) | [Full Text] PDF (297 KB)
Hartono, E Ongko, D Abdullah
Department of Computer Science, University of Sumatera Utara, Medan, Indonesia

Abstract -
Clustering is a function of data mining that served to define clusters (groups) of the object in which objects are in one cluster have in common with other objects that are in the same cluster and the object is different from the other objects in different clusters. One method of clustering that can be used is the K-Means Clustering are included in the category of partitioning methods. One of the stages yan important in the K-Means Clustering is the cluster centroid determination, which will determine the placement of an object into a cluster based on the shortest distance between the object coordinate with cluster centroid. Genetic algorithms can be used in determining the initial value of the cluster centroid. the data set used in this study is the Iris data sets derived from the UCI Machine Learning Repository. Genetic algorithm is a heuristic search algorithm based on the idea of natural selection that Occurs in the process of evolution and genetic operations. This algorithm perform an intelligent search for a solution and have a broad spectrum of possible sollution. The determination of the initial value of the cluster centroid using genetic algorithms can provide better results than by using random numbers.
 
Index Terms - Clustering, K-Means Clustering, Cluster Centroid, Genetic Algorithm

Citation - Hartono, E Ongko, D Abdullah. "Determining a Cluster Centroid of K-Means Clustering Using Genetic Algorithm." International Journal of Computer Science and Software Engineering 4, no. 6 (2015): 160-164.