Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: An attempt has been made to determine the strength
and impact properties of Cr-Mo steel weld and base materials by
varying the current during manual metal arc welding. Toughness over
a temperature range from -32 to 100°C of base, heat affected zone
(HAZ) and weld zones at three current settings are made. It is
observed that the deterioration in notch toughness at any zone with
the temperature decreases. The values of notch toughness for all
zones at -32°C are almost same for any current settings. The values
of notch toughness at HAZ area are higher than that of weld area due
to the coarsening of ferrite grain of HAZ occurs with higher heat
input. From microhardness and microstructure result, it can be
concluded that large inclusion content in weld deposit is the cause of
lower notch toughness value.
Abstract: This paper presents a hybrid fuzzy-PD plus PID
(HFPP) controller and its application to steam distillation process for
essential oil extraction system. Steam temperature is one of the most
significant parameters that can influence the composition of essential
oil yield. Due to parameter variations and changes in operation
conditions during distillation, a robust steam temperature controller becomes nontrivial to avoid the degradation of essential oil quality.
Initially, the PRBS input is triggered to the system and output of steam temperature is modeled using ARX model structure. The
parameter estimation and tuning method is adopted by simulation
using HFPP controller scheme. The effectiveness and robustness of
proposed controller technique is validated by real time
implementation to the system. The performance of HFPP using 25 and 49 fuzzy rules is compared. The experimental result demonstrates the proposed HFPP using 49 fuzzy rules achieves a
better, consistent and robust controller compared to PID when considering the test on tracking the set point and the effects due to disturbance.
Abstract: The vehicle routing problem (VRP) is a famous combinatorial optimization problem. Because of its well-known difficulty, metaheuristics are the most appropriate methods to tackle large and realistic instances. The goal of this paper is to highlight the key ideas for designing VRP metaheuristics according to the following criteria: efficiency, speed, robustness, and ability to take advantage of the problem structure. Such elements can obviously be used to build solution methods for other combinatorial optimization problems, at least in the deterministic field.
Abstract: This paper investigates the spatial structure of employment in the Jakarta Metropolitan Area (JMA), with reference to the concept of the Southeast Asian extended metropolitan region (EMR). A combination of factor analysis and local Getis-Ord (Gi*) hot-spot analysis is used to identify clusters of employment in the region, including those of the urban and agriculture sectors. Spatial statistical analysis is further used to probe the spatial association of identified employment clusters with their surroundings on several dimensions, including the spatial association between the central business district (CBD) in Jakarta city on employment density in the region, the spatial impacts of urban expansion on population growth and the degree of urban-rural interaction. The degree of spatial interaction for the whole JMA is measured by the patterns of commuting trips destined to the various employment clusters. Results reveal the strong role of the urban core of Jakarta, and the regional CBD, as the centre for mixed job sectors such as retail, wholesale, services and finance. Manufacturing and local government services, on the other hand, form corridors radiating out of the urban core, reaching out to the agriculture zones in the fringes. Strong associations between the urban expansion corridors and population growth, and urban-rural mix, are revealed particularly in the eastern and western parts of JMA. Metropolitan wide commuting patterns are focussed on the urban core of Jakarta and the CBD, while relatively local commuting patterns are shown to be prevalent for the employment corridors.
Abstract: Characteristics and sonocatalytic activity of zeolite
Y catalysts loaded with TiO2 using impregnation and ion exchange
methods for the degradation of amaranth dye were investigated.
The Ion-exchange method was used to encapsulate the TiO2 into
the internal pores of the zeolite while the incorporation of TiO2
mostly on the external surface of zeolite was carried out using the
impregnation method. Different characterization techniques were
used to elucidate the physicochemical properties of the produced
catalysts. The framework of zeolite Y remained virtually
unchanged after the encapsulation of TiO2 while the crystallinity of
zeolite decreased significantly after the incorporation of 15 wt% of
TiO2. The sonocatalytic activity was enhanced by TiO2
incorporation with maximum degradation efficiencies of 50% and
68% for the encapsulated titanium and titanium loaded onto the
zeolite, respectively after 120min of reaction. Catalysts
characteristics and sonocatalytic behaviors were significantly
affected by the preparation method and the location of TiO2
introduced with zeolite structure. Behaviors in the sonocatalytic
process were successfully correlated with the characteristics of the
catalysts used.
Abstract: Studies in neuroscience suggest that both global and
local feature information are crucial for perception and recognition of
faces. It is widely believed that local feature is less sensitive to
variations caused by illumination, expression and illumination. In
this paper, we target at designing and learning local features for face
recognition. We designed three types of local features. They are
semi-global feature, local patch feature and tangent shape feature.
The designing of semi-global feature aims at taking advantage of
global-like feature and meanwhile avoiding suppressing AdaBoost
algorithm in boosting weak classifies established from small local
patches. The designing of local patch feature targets at automatically
selecting discriminative features, and is thus different with traditional
ways, in which local patches are usually selected manually to cover
the salient facial components. Also, shape feature is considered in
this paper for frontal view face recognition. These features are
selected and combined under the framework of boosting algorithm
and cascade structure. The experimental results demonstrate that the
proposed approach outperforms the standard eigenface method and
Bayesian method. Moreover, the selected local features and
observations in the experiments are enlightening to researches in
local feature design in face recognition.
Abstract: To improve the material characteristics of single- and
poly-crystals of pure copper, the respective relationships between crystallographic orientations and microstructures, and the bending and mechanical properties were examined. And texture distribution is also
analyzed. A grain refinement procedure was performed to obtain a
grained structure. Furthermore, some analytical results related to
crystal direction maps, inverse pole figures, and textures were obtained from SEM-EBSD analyses. Results showed that these
grained metallic materials have peculiar springback characteristics with various bending angles.
Abstract: An alarming emergence of multidrug-resistant strains
of the tuberculosis pathogen Mycobacterium tuberculosis and
continuing high worldwide incidence of tuberculosis has invigorated
the search for novel drug targets. The enzyme glutamate racemase
(MurI) in bacteria catalyzes the stereoconversion of L-glutamate to
D-glutamate which is a component of the peptidoglycan cell wall of
the bacterium. The inhibitors targeted against MurI from several
bacterial species have been patented and are advocated as promising
antibacterial agents. However there are none available against MurI
from Mycobacterium tuberculosis, due to the lack of its threedimensional
structure. This work accomplished two major objectives.
First, the tertiary structure of MtMurI was deduced computationally
through homology modeling using the templates from bacterial
homologues. It is speculated that like in other Gram-positive bacteria,
MtMurI exists as a dimer and many of the protein interactions at the
dimer interface are also conserved. Second, potent candidate
inhibitors against MtMurI were identified through docking against
already known inhibitors in other organisms.
Abstract: Application of nanoparticles as additives in membrane
synthesis for improving the resistance of membranes against fouling
has triggered recent interest in new membrane types. However, most
nanoparticle-enhanced membranes suffer from the tradeoff between
permeability and selectivity. In this study, nano-WS2 was explored as
the additive in membrane synthesis by non-solvent induced phase
separation. Blended PES-WS2 flat-sheet membranes with the
incorporation of ultra-low concentrations of nanoparticles (from 0.025
to 0.25%, WS2/PES ratio) were manufactured and investigated in
terms of permeability, fouling resistance and solute rejection.
Remarkably, a significant enhancement in the permeability was
observed as a result of the incorporation of ultra-low fractions of
nano-WS2 to the membrane structure. Optimal permeability values
were obtained for modified membranes with 0.10%
nanoparticle/polymer concentration ratios. Furthermore, fouling
resistance and solute rejection were significantly improved by the
incorporation of nanoparticles into the membrane matrix. Specifically,
fouling resistance of modified membrane can increase by around 50%.
Abstract: This research is a comparative study of complexity, as a multidimensional concept, in the context of streetscape composition in Algeria and Japan. 80 streetscapes visual arrays have been collected and then presented to 20 participants, with different cultural backgrounds, in order to be categorized and classified according to their degrees of complexity. Three analysis methods have been used in this research: cluster analysis, ranking method and Hayashi Quantification method (Method III). The results showed that complexity, disorder, irregularity and disorganization are often conflicting concepts in the urban context. Algerian daytime streetscapes seem to be balanced, ordered and regular, and Japanese daytime streetscapes seem to be unbalanced, regular and vivid. Variety, richness and irregularity with some aspects of order and organization seem to characterize Algerian night streetscapes. Japanese night streetscapes seem to be more related to balance, regularity, order and organization with some aspects of confusion and ambiguity. Complexity characterized mainly Algerian avenues with green infrastructure. Therefore, for Japanese participants, Japanese traditional night streetscapes were complex. And for foreigners, Algerian and Japanese avenues nightscapes were the most complex visual arrays.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.
Abstract: Artificial Neural Network (ANN) has been
extensively used for classification of heart sounds for its
discriminative training ability and easy implementation. However, it
suffers from overparameterization if the number of nodes is not
chosen properly. In such cases, when the dataset has redundancy
within it, ANN is trained along with this redundant information that
results in poor validation. Also a larger network means more
computational expense resulting more hardware and time related
cost. Therefore, an optimum design of neural network is needed
towards real-time detection of pathological patterns, if any from heart
sound signal. The aims of this work are to (i) select a set of input
features that are effective for identification of heart sound signals and
(ii) make certain optimum selection of nodes in the hidden layer for a
more effective ANN structure. Here, we present an optimization
technique that involves Singular Value Decomposition (SVD) and
QR factorization with column pivoting (QRcp) methodology to
optimize empirically chosen over-parameterized ANN structure.
Input nodes present in ANN structure is optimized by SVD followed
by QRcp while only SVD is required to prune undesirable hidden
nodes. The result is presented for classifying 12 common
pathological cases and normal heart sound.