19,420 research outputs found
The effect of manganese oxide on the sinterability of hydroxyapatite
The sinterability of manganese oxide (MnO2) doped hydroxyapatite (HA) ranging from 0.05 to 1 wt% was investigated. Green samples were prepared and sintered in air at temperatures ranging from 1000 to 1400 °C. Sintered bodies were characterized to determine the phase stability, grain size, bulk density, hardness, fracture toughness and Young's modulus. XRD analysis revealed that the HA phase stability was not disrupted throughout the sintering regime employed. In general, samples containing less than 0.5 wt% MnO2 and when sintered at lower temperatures exhibited higher mechanical properties than the undoped HA. The study revealed that all the MnO2-doped HA achieved >99% relative density when sintered at 1100–1250 °C as compared to the undoped HA which could only attained highest value of 98.9% at 1150 °C. The addition of 0.05 wt% MnO2 was found to be most beneficial as the samples exhibited the highest hardness of 7.58 GPa and fracture toughness of 1.65 MPam1/2 as compared to 5.72 GPa and 1.22 MPam1/2 for the undoped HA when sintered at 1000 °C. Additionally, it was found that the MnO2-doped samples attained E values above 110 GPa when sintered at temperature as low as 1000 °C if compared to 1050 °C for the undoped HA
Learning algorithms for multi-class pattern classification and problems associated with on-line handwritten character recognition
On-line handwritten alphanumeric character recognition system and learning algorithm for multiclass pattern classificatio
Less is More: Micro-expression Recognition from Video using Apex Frame
Despite recent interest and advances in facial micro-expression research,
there is still plenty room for improvement in terms of micro-expression
recognition. Conventional feature extraction approaches for micro-expression
video consider either the whole video sequence or a part of it, for
representation. However, with the high-speed video capture of micro-expressions
(100-200 fps), are all frames necessary to provide a sufficiently meaningful
representation? Is the luxury of data a bane to accurate recognition? A novel
proposition is presented in this paper, whereby we utilize only two images per
video: the apex frame and the onset frame. The apex frame of a video contains
the highest intensity of expression changes among all frames, while the onset
is the perfect choice of a reference frame with neutral expression. A new
feature extractor, Bi-Weighted Oriented Optical Flow (Bi-WOOF) is proposed to
encode essential expressiveness of the apex frame. We evaluated the proposed
method on five micro-expression databases: CAS(ME), CASME II, SMIC-HS,
SMIC-NIR and SMIC-VIS. Our experiments lend credence to our hypothesis, with
our proposed technique achieving a state-of-the-art F1-score recognition
performance of 61% and 62% in the high frame rate CASME II and SMIC-HS
databases respectively.Comment: 14 pages double-column, author affiliations updated, acknowledgment
of grant support adde
TV-GAN: Generative Adversarial Network Based Thermal to Visible Face Recognition
This work tackles the face recognition task on images captured using thermal
camera sensors which can operate in the non-light environment. While it can
greatly increase the scope and benefits of the current security surveillance
systems, performing such a task using thermal images is a challenging problem
compared to face recognition task in the Visible Light Domain (VLD). This is
partly due to the much smaller amount number of thermal imagery data collected
compared to the VLD data. Unfortunately, direct application of the existing
very strong face recognition models trained using VLD data into the thermal
imagery data will not produce a satisfactory performance. This is due to the
existence of the domain gap between the thermal and VLD images. To this end, we
propose a Thermal-to-Visible Generative Adversarial Network (TV-GAN) that is
able to transform thermal face images into their corresponding VLD images
whilst maintaining identity information which is sufficient enough for the
existing VLD face recognition models to perform recognition. Some examples are
presented in Figure 1. Unlike the previous methods, our proposed TV-GAN uses an
explicit closed-set face recognition loss to regularize the discriminator
network training. This information will then be conveyed into the generator
network in the forms of gradient loss. In the experiment, we show that by using
this additional explicit regularization for the discriminator network, the
TV-GAN is able to preserve more identity information when translating a thermal
image of a person which is not seen before by the TV-GAN
Peningkatan Kinerja Toyota Avanza 1.5 Dengan Penambahan Supercharger Elektrik
Di era mobilitas ini, perkembangan teknologi kendaraan bermotor terutama mobil terus berkembang. Peningkatan kinerja Toyota avanza 1.5 dengan menggunakan supercharger konvensional yang berfungsi memasukan udara ke ruang bakar yang biasa dilakukan untuk meningkatkan kinerja mesin menggunkan tenaga dari putaran mesin. Sedangkan supercharger elektrik bekerja seperti halnya supercharger konvensional dengan menggunakan sumber tenaga penggerak motor listrik DC 12 V yang diambil dari aki mobil tanpa memebebani mesin. Dengan adanya penambahan supercharger elektrik pada Toyota avanza terjadi penigkatan torsi dan daya. Namum secara persen tidak signifikan tetapi torsi dan daya meningkat pada rpm 1500-3500
Optimal Cache-Oblivious Mesh Layouts
A mesh is a graph that divides physical space into regularly-shaped regions.
Meshes computations form the basis of many applications, e.g. finite-element
methods, image rendering, and collision detection. In one important mesh
primitive, called a mesh update, each mesh vertex stores a value and repeatedly
updates this value based on the values stored in all neighboring vertices. The
performance of a mesh update depends on the layout of the mesh in memory.
This paper shows how to find a memory layout that guarantees that the mesh
update has asymptotically optimal memory performance for any set of memory
parameters. Such a memory layout is called cache-oblivious. Formally, for a
-dimensional mesh , block size , and cache size (where
), the mesh update of uses memory transfers.
The paper also shows how the mesh-update performance degrades for smaller
caches, where .
The paper then gives two algorithms for finding cache-oblivious mesh layouts.
The first layout algorithm runs in time both in expectation
and with high probability on a RAM. It uses memory
transfers in expectation and memory
transfers with high probability in the cache-oblivious and disk-access machine
(DAM) models. The layout is obtained by finding a fully balanced decomposition
tree of and then performing an in-order traversal of the leaves of the
tree. The second algorithm runs faster by almost a factor
in all three memory models, both in expectation and with high probability. The
layout obtained by finding a relax-balanced decomposition tree of and then
performing an in-order traversal of the leaves of the tree
Evidence of Environmental Quenching at Redshift z ~ 2
We report evidence of environmental quenching among galaxies at redshift ~ 2,
namely the probability that a galaxy quenches its star formation activity is
enhanced in the regions of space in proximity of other quenched, more massive
galaxies. The effect is observed as strong clustering of quiescent galaxies
around quiescent galaxies on angular scales \theta < 20 arcsec, corresponding
to a proper(comoving) scale of 168 (502) kpc at z = 2. The effect is observed
only for quiescent galaxies around other quiescent galaxies; the probability to
find star-forming galaxies around quiescent or around star-forming ones is
consistent with the clustering strength of galaxies of the same mass and at the
same redshift, as observed in dedicated studies of galaxy clustering. The
effect is mass dependent in the sense that the quenching probability is
stronger for galaxies of smaller mass () than for more
massive ones, i.e. it follows the opposite trend with mass relative to
gravitational galaxy clustering. The spatial scale where the effect is observed
suggests these environments are massive halos, in which case the observed
effect would likely be satellite quenching. The effect is also redshift
dependent in that the clustering strength of quiescent galaxies around other
quiescent galaxies at z = 1.6 is ~ 1.7 times larger than that of the galaxies
with the same stellar mass at z = 2.6. This redshift dependence allows for a
crude estimate of the time scale of environmental quenching of low-mass
galaxies, which is in the range 1.5 - 4 Gyr, in broad agreement with other
estimates and with our ideas on satellite quenching.Comment: 12 pages, 9 figures, Accepted for publication in Ap
Performance enhancement of single-chamber sediment-microbial fuel cell with variation in cathode surface area
This study investigates the impact of cathode surface area on single chamber sediment-microbial fuel cell (S-MFC). A fixed graphite anode surface area of 0.000471m2 has been used on four S-MFCs coupled with four carbon fiber cloth cathode electrodes with variation of surface area. Pond sediment has been used as the anode medium that inoculated with acetate as substrate to ramp up the amount of electrochemical-active bacteria (EAB). The S-MFCs has been operated and monitored for 120 hours using Arduino based data logger. The outcomes of this observation period have indicated the S-MFC with larger cathode surface area (0.01m2) possess smaller internal resistance (123.96±2.68 Ω) and thus performed significantly better than other S-MFC with the smaller cathode surface area, resulting with average voltage and current of 0.598±0.008V and 4.827±0.124mA respectively, where a maximum power density of 2.867mW with a coulombic efficiency of 64.63% was achieved. Successful performance increase suggests enlargement of the cathode area could be the alternative to reduce the internal resistance in traditional MFCs for electricity generation
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