Abstract: Creativity is marked by the ability or power, to
produce through imaginative skill and create something anew. The
University is one of the great places to improve the talent in
imaginative skill. The purpose of this study was to identify a
creativity of the student in presentation product development. Two
hundred seventeen Technical and Vocational Education (TVE)
students in Universiti Tun Hussein Onn had chosen as a respondent.
This study is to survey the level of creativity which is focused on
knowledge, skills, presentation style, and character of creative
personnel. The level of creativity was measured based on the scale at
low, medium and high followed by mean score level. The data
collected by questionnaire, then analyzed using SPSS version
20.0.The result of the study indicated that the students showed a
higher of creativity (mean score in Knowledge = 4.12 and Skills=
4.02). In conjunction with the findings, implications and
recommendations were suggested forward like to ensconce the
research and improve with a more creativity concept in presentation
product of development for learning and teaching process.
Abstract: Multimodal biometric systems integrate the data presented by multiple biometric sources, hence offering a better performance than the systems based on a single biometric modality. Although the coupling of biometric systems can be done at different levels, the fusion at the scores level is the most common since it has been proven effective than the rest of the fusion levels. However, the scores from different modalities are generally heterogeneous. A step of normalizing the scores is needed to transform these scores into a common domain before combining them. In this paper, we study the performance of several normalization techniques with various fusion methods in a context relating to the merger of three unimodal systems based on the face, the palmprint and the fingerprint. We also propose a new adaptive normalization method that takes into account the distribution of client scores and impostor scores. Experiments conducted on a database of 100 people show that the performances of a multimodal system depend on the choice of the normalization method and the fusion technique. The proposed normalization method has given the best results.
Abstract: Ethnicity identification of face images is of interest in
many areas of application, but existing methods are few and limited.
This paper presents a fusion scheme that uses block-based uniform
local binary patterns and Haar wavelet transform to combine local
and global features. In particular, the LL subband coefficients of the
whole face are fused with the histograms of uniform local binary
patterns from block partitions of the face. We applied the principal
component analysis on the fused features and managed to reduce the
dimensionality of the feature space from 536 down to around 15
without sacrificing too much accuracy. We have conducted a number
of preliminary experiments using a collection of 746 subject face
images. The test results show good accuracy and demonstrate the
potential of fusing global and local features. The fusion approach is
robust, making it easy to further improve the identification at both
feature and score levels.