Browsing by Author "Nizamani, Sarwat"

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    Crime Analysis using Open Source Information
    Nizamani, Sarwat; Memon, Nasrullah; Shah, Azhar Ali; Nizamani, Sehrish Basir; Nizamani, Saad; Ismaili, Imdad Ali; Nizamani, Sehrish Basir (University of Sindh, 2015-12-09)
    In this paper, we present a method of crime analysis from open source information. We employed un-supervised methods of data mining to explore the facts regarding the crimes of an area of interest. The analysis is based on well known clustering and association techniques. The results show that the proposed method of crime analysis is efficient and gives a broad picture of the crimes of an area to analyst without much effort. The analysis is evaluated using manual approach, which reveals that the results produced by the proposed approach are comparable to the manual analysis, while a great amount of time is saved.
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    An Efficient Partitioning Clustering Algorithm
    Nizamani, Saad; Dahri, Kamran; Nizamani, Sehrish Basir; Nizamani, Sarwat; Laghari, Gulsher (Sindh University Press, 2015-01-25)
    Clustering is an unsupervised classification method, used in various disciplines, with a goal of organizing objects into different groups. Various methods and algorithms exist for clustering which attempt to find better clustering results. In clustering, choosing the centroids is a very sensitive concern as it is the essential element to do the clustering. This paper presents a novel partitioning clustering method that generates better clusters which is efficient in terms of Rand Index and Purity compared to traditional K-means algorithms. Experiments are performed on various datasets from UCI machine learning repository to obtain clusters and results show that the proposed method generates better clusters in terms of Purity and Rand Index.
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    On the computational models for the analysis of illicit activities
    Nizamani, Sarwat; Nizamani, Saad; Nizamani, Sehrish Basir; Ismaili, Imdad Ali (University of Sindh, 2014-10-20)
    This paper presents a study on the advancement of computational models for the analysis of illicit activities. Computational models are being adapted to address a number of social problems since the development of computers. Computational model are divided into three categories and discussed that how computational models can help in analyzing the illicit activities. The present study sheds a new light on the area of research that will aid to researchers in the field as well as the law and enforcement agencies.