819 research outputs found
Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields
Automated Facial Expression Recognition (FER) has been a challenging task for
decades. Many of the existing works use hand-crafted features such as LBP, HOG,
LPQ, and Histogram of Optical Flow (HOF) combined with classifiers such as
Support Vector Machines for expression recognition. These methods often require
rigorous hyperparameter tuning to achieve good results. Recently Deep Neural
Networks (DNN) have shown to outperform traditional methods in visual object
recognition. In this paper, we propose a two-part network consisting of a
DNN-based architecture followed by a Conditional Random Field (CRF) module for
facial expression recognition in videos. The first part captures the spatial
relation within facial images using convolutional layers followed by three
Inception-ResNet modules and two fully-connected layers. To capture the
temporal relation between the image frames, we use linear chain CRF in the
second part of our network. We evaluate our proposed network on three publicly
available databases, viz. CK+, MMI, and FERA. Experiments are performed in
subject-independent and cross-database manners. Our experimental results show
that cascading the deep network architecture with the CRF module considerably
increases the recognition of facial expressions in videos and in particular it
outperforms the state-of-the-art methods in the cross-database experiments and
yields comparable results in the subject-independent experiments.Comment: To appear in 12th IEEE Conference on Automatic Face and Gesture
Recognition Worksho
Facial Expression Recognition from World Wild Web
Recognizing facial expression in a wild setting has remained a challenging
task in computer vision. The World Wide Web is a good source of facial images
which most of them are captured in uncontrolled conditions. In fact, the
Internet is a Word Wild Web of facial images with expressions. This paper
presents the results of a new study on collecting, annotating, and analyzing
wild facial expressions from the web. Three search engines were queried using
1250 emotion related keywords in six different languages and the retrieved
images were mapped by two annotators to six basic expressions and neutral. Deep
neural networks and noise modeling were used in three different training
scenarios to find how accurately facial expressions can be recognized when
trained on noisy images collected from the web using query terms (e.g. happy
face, laughing man, etc)? The results of our experiments show that deep neural
networks can recognize wild facial expressions with an accuracy of 82.12%
Heegard-Berger and Cascade Source Coding Problems with Common Reconstruction Constraints
For the HB problem with the CR constraint, the rate-distortion function is
derived under the assumption that the side information sequences are
(stochastically) degraded. The rate-distortion function is also calculated
explicitly for three examples, namely Gaussian source and side information with
quadratic distortion metric, and binary source and side information with
erasure and Hamming distortion metrics. The rate-distortion function is then
characterized for the HB problem with cooperating decoders and (physically)
degraded side information. For the cascade problem with the CR constraint, the
rate-distortion region is obtained under the assumption that side information
at the final node is physically degraded with respect to that at the
intermediate node. For the latter two cases, it is worth emphasizing that the
corresponding problem without the CR constraint is still open. Outer and inner
bounds on the rate-distortion region are also obtained for the cascade problem
under the assumption that the side information at the intermediate node is
physically degraded with respect to that at the final node. For the three
examples mentioned above, the bounds are shown to coincide. Finally, for the HB
problem, the rate-distortion function is obtained under the more general
requirement of constrained reconstruction, whereby the decoder's estimate must
be recovered at the encoder only within some distortion.Comment: to appear in IEEE Trans. Inform. Theor
The Effects of Different Roughness Configurations on Aerodynamic Performance of Wind Turbine Airfoil and Blade
In this research, viscous and turbulent flow is simulated numerically on an E387 airfoil as well as on a turbine blade. The main objective of this paper is to investigate various configurations of roughness to find a solution in order to mitigate roughness destructive impacts. Hence, the sand grain roughness is distributed uniformly along pressure side, suction side and both sides during the manufacturing process. Navier-Stokes equations are discretized by the finite volume method and are solved by SIMPLE algorithm. Results indicated that in contrast with previous studies, the roughness will be useful if it is applied on only pressure side of the airfoil. In this condition, the lift coefficient is increased to and 1.2% compare to the airfoil with rough and smooth sides, respectively. However, in 3-D simulation, the lift coefficient of the blade with pressure surface roughness is less than smooth blade, but still its destructive impacts are much less than of both surfaces roughness and suction surfaces roughness. Therefore, it can be deduced that in order to reveal the influence of roughness, the simulation must be accomplished in three dimensions.Article History: Received Jun 12th 2017; Received in revised form August 27th 2017; Accepted Oct 3rd 2017; Available onlineHow to Cite This Article: Jafari, K., Djavareshkian, M.H., Feshalami, B.H. (2017) The Effects of Different Roughness Configurations on Aerodynamic Performance of Wind Turbine Airfoil and Blade. International Journal of Renewable Energy Develeopment, 6(3), 273-281.https://doi.org/10.14710/ijred.6.3.273-28
Entanglement Capacity of Nonlocal Hamiltonians : A Geometric Approach
We develop a geometric approach to quantify the capability of creating
entanglement for a general physical interaction acting on two qubits. We use
the entanglement measure proposed by us for -qubit pure states (PRA
\textbf{77}, 062334 (2008)). Our procedure reproduces the earlier results (PRL
\textbf{87}, 137901 (2001)). The geometric method has the distinct advantage
that it gives an experimental way to monitor the process of optimizing
entanglement production.Comment: 8 pages, 1 figure
The impact of board and hotel characteristics on biodiversity reporting: Market diversification as a moderator
Purpose: This study aims to explain how board and hotel characteristics affect biodiversity reporting and to test the moderating effect of market diversification. Design/methodology/approach: The annual reports of 105 hotels were examined for the period between 2016 and 2017 to analyse these hotels’ biodiversity reporting using content analysis. The partial least squares technique was used to test the proposed relationships. Findings: The results show that the number of board members who are also on the corporate social responsibility committee, number of board members who are in environmental organizations, the star rating of the hotel, hotel size and hotel location have significant positive effects on the extent of biodiversity reporting. In addition, market diversification moderates positively the effects of number of board members with environmental experience and number of board members from environmental organizations on the extent of biodiversity reporting. Practical implications: The results of this study will be useful in enabling hotel manager and investors to become knowledgeable about these aspects of boards, which lead to higher biodiversity reporting. This study can also inform policymakers about the types of hotels that are less likely to disclose biodiversity reports and to develop effective enforcement of regulations. Originality/value: These findings extend the literature on biodiversity reporting by exploring the importance of board and hotel characteristics on the extent of biodiversity reporting and testing the moderating effect of market diversification
Anti-Candida activity of ethanolic extracts of Iranian endemic medicinal herbs against Candida albicans
It has long been known that herbs and their extracts have antimicrobial activities. Heracleum
lasiopetalum Boiss., Satureja bachtiarica Bunge., Thymus daenensis Celak., Echiophora platyloba L.,
Dracocephalum multicaule Benth., Kelussia odoratissima Mozaff. and Achillea kellalensis Boiss. are
Iranian endemic plant species that have been traditionally used as medicinal herbs and spices in
different regions of Iran especially Central Zagross. Seven ethanolic extracts of endemic medicinal
herbs and one extract of native medicinal herb (Stachys lavandulifolia Vahl.) collected from
Chaharmahal va Bakhtiari province of Iran were assayed for the in vitro antifungal activity against
Candida albicans (ATCC1023), using agar dilution methods. Most of the extracts showed relatively high
anti-Candida activity against the tested fungi with the diameter of inhibition zone ranging between 8 and
17 mm. The extracts of S. bachtiarica and T. daenensis exhibited high inhibitory effect against C.
albicans. The extracts of S. bachtiarica and T. daenensis were characterized using HPLC, the major
components of S. bachtiarica and T. daenensis were carvacrol and thymol, respectively. The minimum
inhibitory concentration (MIC) values for active extract range between 25 and 50 µg/ml. In conclusion, it
can be said that the extract of some of the Iranian endemic medicinal plants (S. bachtiarica and T.
daenensis) could be used as natural anti-Candida
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