It is imperative to consider human different perspective in order to visualize the information data towards users.Many studies proved that personality traits are one of the most significant factors that must be considered to give meaningful value when us\uders see a view.This study tries to give ample\udevidence toward adjusting visual features on tag cloud visualization techniques. Since there is no study has tried to create an algorithm that can customize tag cloud visual\udproperties based on personality traits. Therefore, the main objective of this study is to make tag cloud algorithm with the\udinclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In\udaddition, the utilization of RBS (rule bas\ude system) approach as artificial intelligent method is also taken into account to make\udknowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape\ud.The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences
paper presents a new face parts information analyzer, as a promising model for detecting faces and locating the facial features in images. The main objective is to build fully automated human facial measurements systems from images with complex backgrounds. Detection of facial features such as eye, nose, and mouth is an important step for many subsequent facial image analysis tasks. The study covers the tasks detection, landmark localization and measurement facial part that have traditionally been approached as separate problems with different techniques. Different set of techniques have been introduced recently, for example; principal component analysis, geometric modeling, auto-correlation, deformable template, neural networks, color analysis, window classifiers, view-based Eigen space methods, and elastic graph models. The study present a novel and simple model approach based on a mixture of techniques and algorithms in a shared pool based on Viola-Jones object detection framework algorithm combined with geometric and symmetric information of the face parts from the image in a smart algorithm. The study is a continued part of previous work (1) the proposed model is modestly applied with hundreds of face images taken under different lighting conditions, a number of general assumptions used in this research field are identified.
The aim of this paper is to extract and select features from speech signal that will make it possible to have acceptable speaker recognition rate in real life. A variety of combinations among formants (F1, F2, F3), Linear Predictive Coefficients (LPC), Mel Frequency Cepstral Coefficients (MFCC) and deltaMel Frequency Cepstral Coefficients representing features are considered and their effect in speaker recognition is observed. Two similar volume data sets with differed string (words) are considered in the present study. These two data sets are prepared taking into account two differed data sampling rates. The study reveals another interesting fact that the selection of strings in speaker enrollment process is a matter of importance for accurate result. This means that the speaker will be tested for authentication with the same string with which he was enrolled earlier during the time of his first access to the system. General Terms Feature Extraction and Selection, Pattern Recognition, Artificial Neural Network, Automatic Speaker Recognition
activity of re-testing of only those parts of the program or code, in which some modifications are performed to ensure that errors have not been added and the changes do not affect the other parts of the code, which have not been modified is called as regression testing. Regression testing is essential as it reduces the size of the test suite, thus reducing the time and effort for testing. In this paper, different techniques for the regression test case selection for various programming paradigms are discussed.
Computing has recently emerged as a compelling paradigm for managing and delivering services over the internet. It is now considered as one of the rapidly developing platforms in the various fields related to computer science in one way or another. It is provided in a pay-per-use manner as per the demand of the consumer. Resource allocation in cloud computing is performed with the objective of minimizing the costs related with the management of resources at the provider side. It also involves fulfillment of customer demands and application requirements. Numerous techniques for resource allocation have been proposed and implemented so far in the world of cloud computing but none of which has considered introducing a parameter from the consumer context. Resource allocation being one of the most critical factors which defines the overall efficiency of the cloud, usually involves an attribute on which the whole process of the allocation of resources is based upon. In this report, a policy has been proposed & implemented, keeping in mind the importance of consumer context in cloud. The importance of context in the growth and success of a business has also been discussed.
The dynamics of transcendental function is one of emerging and interesting field of research nowadays. We introduce in this paper the complex dynamics of hyperbolic cosine function of the type {cosh (z ) + z + c = 0} and applied Jungck Ishikawa iteration to generate new Relative Superior Mandelbrot set and Relative Superior Julia set. In order to solve this function by Jungck –type iterative schemes, we write it in the form of Sz = Tz, where the function T, S are defined as Tz = cosh( z ) +c and Sz = z. Only mathematical explanations are derived by applying Jungck Ishikawa Iteration for transcendental function in the literature but in this paper we have generated relative Mandelbrot sets and Relative Julia sets.