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It is a well-known fact that some criminals follow perpetual methods of operations known as modi operandi. Modus operandi is a commonly used term to describe the habits in committing crimes. These modi operandi are used in relating criminals to crimes for which the suspects have not yet been recognized. This paper presents the design, implementation and evaluation of a new method to find connections between crimes and criminals using modi operandi. The method involves generating a feature matrix for a particular criminal based on the flow of events of his/her previous convictions. Then, based on the feature matrix, two representative modi operandi are generated: complete modus operandi and dynamic modus operandi. These two representative modi operandi are compared with the flow of events of the crime at hand, in order to generate two other outputs: completeness probability (CP) and deviation probability (DP). CP and DP are used as inputs to a fuzzy inference system to generate a score which is used in providing a measurement for the similarity between the suspect and the crime at hand. The method was evaluated using actual crime data and ten other open data sets. In addition, comparison with nine other classification algorithms showed that the proposed method performs competitively with other related methods proving that the performance of the new method is at an acceptable level.

Line clipping operation is a bottleneck in most of computer graphics applications. There are situations when millions of line segments need to be clipped against convex polyhedrons with millions of facets. An algorithm to clip line segments against a convex polyhedron is proposed in this work. The salient feature of the proposed algorithm is that it minimizes the number of computations by ignoring unnecessary intersection calculations. The other advantage of the proposed algorithm is that it needs minimum details about the convex polyhedron; the equations of the facets and the centroid. Therefore, it improves the efficiency of the algorithm. The line segment may have zero length (a point) or positive length. When line segment is just a point which is outside with respect to at least one facet, it should be rejected as the line segment is outside the convex polyhedron. When the line segment is parallel to a facet and one of its end points is outside, that line segment is also completely outside and it should also be rejected. Unless the line segment belongs to none of the above two cases, it should be pruned against each facet in a certain order. In this case, the intersection points with only some of the facets need to be computed and some other intersection calculations can be ignored. If the line segment is completely outside then it becomes a single point. That means the two end points coincide. But due to the precision error they do not exactly coincide. Therefore, approximate equality should be tested. By using this property, completely outside line segments can be identified. Having two end points outside does not necessarily keep the line segment completely outside. The widely used Cyrus Beck algorithm computes all the intersection points with each facet of the polyhedron while the proposed algorithm successfully avoids some of the intersection point calculations. In the best case; it is capable of avoiding all the unnecessary intersection calculations. An experimental comparison between the Cyrus Beck algorithm and the proposed algorithm was carried out. Random polyhedrons were created with different number of facets. Random points were generated and they were considered as end points of line segments. For a given polyhedron, the number of clock cycles consumed to clip 10 8 number of line segments was computed using the Cyrus Beck algorithm and the proposed algorithm. For a polyhedron with four vertices, the proposed algorithm is 1.02 times faster than the Cyrus Beck algorithm. For a polyhedron with nine vertices, the proposed algorithm is 1.16 times faster than the Cyrus Beck algorithm.

The manual crime recording and investigation systems in police stations all around the world are generating piles of crime documents which make storage and retrieval of reliable crime information extremely difficult as well as inefficient. Furthermore, investigators of central authorities have to manually search through these documents and communicate between the relevant police stations to obtain required information. Eventually, delays in information flow between investigators of crime incidents cannot be avoided. Sri Lanka Police too have been facing the same set of issues over many years. To get rid of pilling of large number of documents annually in police stations, Sri Lanka Police is allowed to destroy the documents related to solved crimes which are older than five years. This may destroy not only "closed files", but also very valuable information that can be used in future crime investigations.To overcome this problem, this paper proposes a web-based framework with geographical information support which contains a centralized database for crime data storage and retrieval. Geographical capabilities of the framework support not only spatial analysis but also provide an efficient solution to current manual crime map generation. Our highly secured and user friendly framework follows the state of the art layered architecture which provides an optimized data model for fast access and easy analysis of crime data. The solution consists of an affluent set of data mining tools which are essential in any crime investigation process. Security of data is ensured with data encryption for sensitive information and by limiting access to the data through a role based access method. Further the data is only accessible through a virtual private network (VPN) connecting all the police stations and other relevant departments of the Police. The The manual crime recording and investigation systems in police stations all around the world 42 are generating piles of crime documents which make storage and retrieval of reliable crime 43 information extremely difficult as well as inefficient. Furthermore, investigators of central 44 authorities have to manually search through these documents and communicate between the 45 relevant police stations to obtain required information. Eventually, delays in information flow 46 between investigators of crime incidents cannot be avoided. Sri Lanka Police too have been 47 facing the same set of issues over many years. To get rid of pilling of large number of 48 documents annually in police stations, Sri Lanka Police is allowed to destroy the documents 49 related to solved crimes which are older than five years. This may destroy not only "closed 50 files", but also very valuable information that can be used in future crime investigations.To 51 overcome this problem, this paper proposes a web-based framework with geographical 52 information support which contains a centralized database for crime data storage and 53 retrieval. Geographical capabilities of the framework support not only spatial ...

Controlling the complexity of software applications is an essential part of the software development process as it directly affects maintenance activities such as reusability, understandability, modifiability and testability. However, as stated by Tom DeMarco "You cannot control what you cannot measure". Thus, over the years many complexity metrics have been proposed with the intention of controlling and minimizing the complexity associated with software. However, majority of these proposed complexity metrics are based on only one aspect of complexity. The CB measure introduced by Chhillar and Bhasin is one metric which relies on a number of complexity factors to decide on the complexity of a program. However, italso has some shortcomings and can be further improved. Thus, this paper attempts to propose some additional complexity factors that the CB measure has not considered, to further improve it. The paper also presents an extensive coverage about the software complexity metrics proposed in the literature.