Recently, the major challenge faced by all intelligence-gathering and law-enforcement organizations is to efficiently and accurately analyze the huge volumes of crime data. Self-organizing map (SOM) can be used to visualize crime data into more comprehensible presentation. Although visualization by using SOM has been done by many researchers, a literature review on the subject focuses on crime data has yet to be implemented. Thus, this study reviews researches on visualization of crime data using SOM and improvement in SOM (Fuzzy SOM or FSOM) together with their available software tools. Information and related works on visualization using SOM and FSOM were studied to fully understand the situation. The result of this study clearly shows that SOM and FSOM have been applied to visualize data in various fields of study. However, there is only limited use of them for visualization of crime data by the researchers. The popular software tool for visualization of crime data using SOM is Matlab, followed by Viscovery SOMine, R, GeoVISTA Studio and C/C++ compiler. Finally, this study concludes with a few suggestions for future researches on visualization of crime data.

The development of artificial intelligent systems mainly based on and imitated from human intelligence. However, there is a deviation among scholars and practitioners in artificial intelligence, philosophy and psychology realms about the essence of human intelligence and human intelligent behaviors. This paper re-looks into the issues of deviation in intelligence and intelligent behaviors, and describes the the oretical foundation and the design set forth fora proposed study to re-investigate the essence of intelligence. Inenabling a further investigation, the issues of intelligent theories,the quest of intelligence essence, the intelligent behavior andcomputation and the relationship between intelligent behaviors and artificial intelligence systems are addressed. The paper progresses to justify the investigation by discussing the nature of behavior with its respective issues that channel the discussion into intelligent processes and problem solving processes. Based on these justifications, the investigation embarks on Pragmaticism’s scientific method - a philosophical thought for “a clear idea” promoted by C. S. Peirce 1839 – 1914.

B-spline is widely used in computer graphics in order to construct a smooth curve. In this paper, we discuss about the detection of sharp points on a B-spline curve and the preservation of the sharpness at the corner of the edges as the degree of the curve increases. We have made the removal process for the data that use a huge number of points and then marked the sharp edge points which will be used to calculate the Euclidean distance between the control points. The formulation of automatic knot vector generationby manual marking of points close to the sharp edges is implemented to obtain an algorithm that is capable of detecting the sharp points. The smoothness of the curve is based on the increase in the degree or order of the curve. Thus, to preserve the sharpness of the edges, knot vector repetition is applied corresponding to the sharp points. In addition, knot vectors play an important role in preserving the sharpness of the edges because the changes in knot vectors will produce various shapes of the B-spline curve.