Abstract: In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.
Abstract: A research program is conducted to evaluate the
mechanical properties of Ultra High Performance Concrete, target
compressive strength at the age of 28 days being more than 150 MPa.
The methodology to develop such mix has been explained. The
material properties, mix design and curing regime are determined.
The material attributes are understood by studying the stress strain
behaviour of UHPC cylinders under uniaxial compressive loading.
The load –crack mouth opening displacement (cmod) of UHPC
beams, flexural strength and fracture energy was evaluated using
third point loading test. Compressive strength and Split tensile
strength results are determined to find out the compressive and tensile
behaviour. Residual strength parameters are presented vividly
explaining the flexural performance, toughness of concrete.Durability
studies were also done to compare the effect of fibre to that of a
control mix For all the studies the Mechanical properties were
evaluated by varying the percentage and aspect ratio of steel fibres
The results reflected that higher aspect ratio and fibre volume
produced drastic changes in the cube strength, cylinder strength, post
peak response, load-cmod, fracture energy flexural strength, split
tensile strength, residual strength and durability. In regards to null
application of UHPC in India, an initiative is undertaken to
comprehend the mechanical behaviour of UHPC, which will be vital
for longer run in commercialization for structural applications.
Abstract: The recent development of humanoid robots has led robot designers to imagine a great variety of anthropomorphic forms for human-like machine. Which form is the best ? We try to answer this question from a double meaning of the anthropomorphism : a positive anthropomorphism corresponing to the realization of an effective anthropomorphic form object and a negative one corresponding to our natural tendency in certain circumstances to give human attributes to non-human beings. We postulate that any humanoid robot is concerned by both these two anthropomorphism kinds. We propose to use gestalt theory and Heider-s balance theory in order to analyze how negative anthropomorphism can influence our perception of human-like robots. From our theoretical approach we conclude that an “even shape" as defined by gestalt theory is not a sufficient condition for a good integration of future humanoid robots into a human community. Aesthetic perception of the robot cannot be splitted from a social perception : a humanoid robot, any how the efforts made for improving its appearance, could be rejected if it is devoted to a task with too high affective implications.
Abstract: Color constancy algorithms are generally based on the
simplified assumption about the spectral distribution or the reflection
attributes of the scene surface. However, in reality, these assumptions
are too restrictive. The methodology is proposed to extend existing
algorithm to applying color constancy locally to image patches rather
than globally to the entire images.
In this paper, a method based on low-level image features using
superpixels is proposed. Superpixel segmentation partition an image
into regions that are approximately uniform in size and shape. Instead
of using entire pixel set for estimating the illuminant, only superpixels
with the most valuable information are used. Based on large scale
experiments on real-world scenes, it can be derived that the estimation
is more accurate using superpixels than when using the entire image.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear particle
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear particle. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear debris
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self-organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear debris. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: In this study we tried to replicate the unconscious
thought advantage (UTA), which states that complex decisions are
better handled by unconscious thinking. We designed an experiment
in e-prime using similar material as the original study (choosing
between four different apartments, each described by 12 attributes).
A total of 73 participants (52 women (71.2%); 18 to 62 age:
M=24.63; SD=8.7) took part in the experiment. We did not replicate
the results suggested by UTT. However, from the present study we
cannot conclude whether this was the case of flaws in the theory or
flaws in our experiment and we discuss several ways in which the
issue of UTA could be examined further.