Learning and manipulating human's fingertip bending data for sign language translation using PCA-BMU classifier

Nowadays the classification of fingers movement could be used to classify or categorize many kinds of human finger motions including the classification of sign language for verbal communication.Principal Component Analysis (PCA) is one of classical method that capable to be verity the finger motions for various alphabets by reducing the dimensional dataset of finger movements.The objective of this paper is to analyze the human finger motions / movements between thumbs,index and middle fingers while bending the fingers using PCA-BMU based techniques. The used of low cost DataGlove “GloveMAP” which is based on fingers adapted postural movement (or EigenFingers) of the principal component was applied in order to translate the finger bending to the sign language alphabets. Preliminary experimental results have shown that the “GloveMAP” DataGlove capable to measure several human Degree of Freedom (DoF), by “translating” them into a virtual commands for the interaction in the virtual world

Multi-objective optimization to enhance the performance of thermo-electric generator combined with heat pipe-heat sink under forced convection

The performance of Thermo-Electric Generator (TEG) is negatively affected by heat sink lack of design. The heat pipe heat sink (HP-HS) has the best performance compared to other conventional cooling systems which uses TEG. In medium temperature range below 300 °C, HP-HS is the most appropriate heat exchanger of the TEG. However, the effect of some parameters of fin space, fin length, fin height, fin materials and optimum geometry of the cold side of the TEG HP-HS under forced convection (FC) has not been fully studied. The objective of this paper is to conduct an analytical and statistical study on these parameters effect on the performance of the TEG. In addition, this paper determines the optimum geometry of HP-HS and materials of aluminum (AL) and copper (CO) at 250 °C of heat source temperatures. Central composite design model (CCD) has been used to design the experiments using response surface methodology (RSM). The multi-objective optimization using RSM is applied to determine the optimum geometry of HP-HS in terms of maximising the TEG power output (P), TEG efficiency (η), and minimising HP-HS cost ($). Compared with the literature, the results showed an improvement in TEG performance. The maximum P and η after optimization were 9.6 W and 3.3$/P, at 7.57 USD/W, as compared to AL, at 8.74 USD. Finally, this study shows an improvement in HP-HS cost; a reduction of 29% was achieved compared with the estimated HP-HS cost in literature