Abstract: In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Abstract: ZnO nanostructures including nanowires, nanorods,
and nanoneedles were successfully deposited on GaAs substrates,
respectively, by simple two-step chemical method for the first time. A
ZnO seed layer was firstly pre-coated on the O2-plasma treated
substrate by sol-gel process, followed by the nucleation of ZnO
nanostructures through hydrothermal synthesis. Nanostructures with
different average diameter (15-250 nm), length (0.9-1.8 μm), density
(0.9-16×109 cm-2) were obtained via adjusting the growth time and
concentration of precursors. From the reflectivity spectra, we
concluded ordered and taper nanostructures were preferential for
photovoltaic applications. ZnO nanoneedles with an average diameter
of 106 nm, a moderate length of 2.4 μm, and the density of 7.2×109
cm-2 could be synthesized in the concentration of 0.04 M for 18 h.
Integrated with the nanoneedle array, the power conversion efficiency
of single junction solar cell was increased from 7.3 to 12.2%,
corresponding to a 67% improvement.
Abstract: Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel
obtained by sol gel synthesis was used as gas sensor. Gas sensing
properties of different gases such as hydrogen, petroleum and
humidity were investigated. Applying XRD and TEM the size of the
nanocrystals is found to be 7.5 nm. SEM shows a highly porous
structure with submicron meter-sized voids present throughout the
sample. FTIR measurement shows different chemical groups
identifying the obtained series of gels. The sample was n-type
semiconductor according to the thermoelectric power and electrical
conductivity. It can be seen that the sensor response curves from
130oC to 150oC show a rapid increase in sensitivity for all types of
gas injection, low response values for heating period and the rapid
high response values for cooling period. This result may suggest that
this material is able to act as gas sensor during the heating and
cooling process.
Abstract: A method is presented for using thermo-mechanical fatigue analysis as a tool in the design of automotive heat exchangers. Use of infra-red thermography to measure the real thermal history in the heat exchanger reduces the time necessary for calculating design parameters and improves prediction accuracy. Thermal shocks are the primary cause of heat exchanger damage. Thermo-mechanical simulation is based on the mean behavior of the aluminum tubes used in the heat exchanger. An energetic fatigue criterion is used to detect critical zones.
Abstract: The nature, prevalence, cellular composition of
leukocyte infiltrates and immunohistochemical characteristics of
their constituent cells in the liver of patients with chronic viral
hepatitis B and C were investigated. It was found that the area of
distribution and cellular composition of infiltrates depended on the
virus type and process activity. The expediency of
immunohistochemical study using leukocyte infiltrates from liver
biopsies of patients with viral hepatitis aimed at clarifying diagnosis,
making prognosis, and choice of optimal treatment with elements of
immune correction is emphasized.
Abstract: This paper presents a spectroscopic study on doping
of Vanadyl pathalocyanine (VOPc) by [6,6]-phenyl C61 butyric acid
methyl ester (PCBM). The films are characterized by UV/Vis/NIR
spectroscopy. A drastic increase in the absorption coefficient has
been observed with increasing dopant concentration. Optical
properties of VOPc:PCBM films deposited by spin coating technique
were studied in detail. Optical band gap decreased with the PCBM
incorporation in the VOPc film. Optical band gap calculated from the
absorption spectra decreased from 3.32 eV to 3.26 eV with a
variation of 0–75 % of PCBM concentration in the VOPC films.
Abstract: Water quality is a subject of ongoing concern.
Deterioration of water quality has initiated serious management
efforts in many countries. This study endeavors to automatically
classify water quality. The water quality classes are evaluated using 6
factor indices. These factors are pH value (pH), Dissolved Oxygen
(DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen
(NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform).
The methodology involves applying data mining
techniques using multilayer perceptron (MLP) neural network
models. The data consisted of 11 sites of canals in Dusit district in
Bangkok, Thailand. The data is obtained from the Department of
Drainage and Sewerage Bangkok Metropolitan Administration
during 2007-2011. The results of multilayer perceptron neural
network exhibit a high accuracy multilayer perception rate at 96.52%
in classifying the water quality of Dusit district canal in Bangkok
Subsequently, this encouraging result could be applied with plan and
management source of water quality.
Abstract: The paper presents a modelling methodology for
small scale multi-source renewable energy systems. Using historical
site-specific weather data, the relationships of cost, availability and
energy form are visualised as a function of the sizing of photovoltaic
arrays, wind turbines, and battery capacity. The specific dependency
of each site on its own particular weather patterns show that unique
solutions exist for each site. It is shown that in certain cases the
capital component cost can be halved if the desired theoretical
demand availability is reduced from 100% to 99%.
Abstract: In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.
Abstract: The study on the tree growth for four species groups of commercial timber in Koh Kong province, Cambodia-s tropical rainforest is described. The simulation for these four groups had been successfully developed in the 5-year interval through year-60. Data were obtained from twenty permanent sample plots in the duration of thirteen years. The aim for this study was to develop stand table simulation system of tree growth by the species group. There were five steps involved in the development of the tree growth simulation: aggregate the tree species into meaningful groups by using cluster analysis; allocate the trees in the diameter classes by the species group; observe the diameter movement of the species group. The diameter growth rate, mortality rate and recruitment rate were calculated by using some mathematical formula. Simulation equation had been created by combining those parameters. Result showed the dissimilarity of the diameter growth among species groups.
Abstract: A new analytical model is developed which provides
close-formed solutions for both transient indoor and envelope
temperature changes in buildings. Time-dependent boundary
temperature is presented as Fourier series which can approximate real
weather conditions. The final close-formed solutions are simple,
concise, and comprehensive. The model was compared with
numerical results and good accuracy was obtained. The model can
be used as design and control guidelines in engineering applications
for analysing mechanical heat transfer properties for buildings.
Abstract: Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.
Abstract: In biological and biomedical research motif finding tools are important in locating regulatory elements in DNA sequences. There are many such motif finding tools available, which often yield position weight matrices and significance indicators. These indicators, p-values and E-values, describe the likelihood that a motif alignment is generated by the background process, and the expected number of occurrences of the motif in the data set, respectively. The various tools often estimate these indicators differently, making them not directly comparable. One approach for comparing motifs from different tools, is computing the E-value as the product of the p-value and the number of possible alignments in the data set. In this paper we explore the combinatorics of the motif alignment models OOPS, ZOOPS, and ANR, and propose a generic algorithm for computing the number of possible combinations accurately. We also show that using the wrong alignment model can give E-values that significantly diverge from their true values.
Abstract: Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
Abstract: A gene network gives the knowledge of the regulatory
relationships among the genes. Each gene has its activators and
inhibitors that regulate its expression positively and negatively
respectively. Genes themselves are believed to act as activators and
inhibitors of other genes. They can even activate one set of genes and
inhibit another set. Identifying gene networks is one of the most
crucial and challenging problems in Bioinformatics. Most work done
so far either assumes that there is no time delay in gene regulation or
there is a constant time delay. We here propose a Dynamic Time-
Lagged Correlation Based Method (DTCBM) to learn the gene
networks, which uses time-lagged correlation to find the potential
gene interactions, and then uses a post-processing stage to remove
false gene interactions to common parents, and finally uses dynamic
correlation thresholds for each gene to construct the gene network.
DTCBM finds correlation between gene expression signals shifted in
time, and therefore takes into consideration the multi time delay
relationships among the genes. The implementation of our method is
done in MATLAB and experimental results on Saccharomyces
cerevisiae gene expression data and comparison with other methods
indicate that it has a better performance.
Abstract: In this research work, poly (acrylonitrile-butadienestyrene)/
polypropylene (ABS/PP) blends were processed by melt
compounding in a twin-screw extruder. Upgrading of the thermal
characteristics of the obtained materials was attempted by the
incorporation of organically modified montmorillonite (OMMT), as
well as, by the addition of two types of compatibilizers;
polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS
grafted with maleic anhydride (ABS-g-MAH). The effect of the
above treatments was investigated separately and in combination.
Increasing the PP content in ABS matrix seems to increase the
thermal stability of their blend and the glass transition temperature
(Tg) of SAN phase of ABS. From the other part, the addition of ABS
to PP promotes the formation of its β-phase, which is maximum at 30
wt% ABS concentration, and increases the crystallization temperature
(Tc) of PP. In addition, it increases the crystallization rate of PP.The
β-phase of PP in ABS/PP blends is reduced by the addition of
compatibilizers or/and organoclay reinforcement. The incorporation
of compatibilizers increases the thermal stability of PP and reduces
its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it
decreases slightly the Tgs of PP and SAN phases of ABS/PP blends.
Regarding the storage modulus of the ABS/PP blends, it presents a
change in their behavior at about 10°C and return to their initial
behavior at ~110°C. The incorporation of OMMT to no compatibilized
and compatibilized ABS/PP blends enhances their storage modulus.
Abstract: In this paper, the two-dimension differential transformation method (DTM) is employed to obtain the closed form solutions of the three famous coupled partial differential equation with physical interest namely, the coupled Korteweg-de Vries(KdV) equations, the coupled Burgers equations and coupled nonlinear Schrödinger equation. We begin by showing that how the differential transformation method applies to a linear and non-linear part of any PDEs and apply on these coupled PDEs to illustrate the sufficiency of the method for this kind of nonlinear differential equations. The results obtained are in good agreement with the exact solution. These results show that the technique introduced here is accurate and easy to apply.
Abstract: Texture classification is an important image processing
task with a broad application range. Many different techniques for
texture classification have been explored. Using sparse approximation
as a feature extraction method for texture classification is a relatively
new approach, and Skretting et al. recently presented the Frame
Texture Classification Method (FTCM), showing very good results on
classical texture images. As an extension of that work the FTCM is
here tested on a real world application as detection of abnormalities
in mammograms. Some extensions to the original FTCM that are
useful in some applications are implemented; two different smoothing
techniques and a vector augmentation technique. Both detection of
microcalcifications (as a primary detection technique and as a last
stage of a detection scheme), and soft tissue lesions in mammograms
are explored. All the results are interesting, and especially the results
using FTCM on regions of interest as the last stage in a detection
scheme for microcalcifications are promising.
Abstract: The aim of this paper is to study in depth some methodological aspects of social interventation, focusing on desirable passage from social maternage method to peer advocacy method. For this purpose, we intend analyze social and organizative components, that affect operator's professional action and that are part of his psychological environment, besides the physical and social one. In fact, operator's interventation should not be limited to a pure supply of techniques, nor to take shape as improvised action, but “full of good purposes".
Abstract: Inconel 718, a nickel based super-alloy is an
extensively used alloy, accounting for about 50% by weight of
materials used in an aerospace engine, mainly in the gas turbine
compartment. This is owing to their outstanding strength and
oxidation resistance at elevated temperatures in excess of 5500 C.
Machining is a requisite operation in the aircraft industries for the
manufacture of the components especially for gas turbines. This
paper is concerned with optimization of the surface roughness when
turning Inconel 718 with cermet inserts. Optimization of turning
operation is very useful to reduce cost and time for machining. The
approach is based on Response Surface Method (RSM). In this work,
second-order quadratic models are developed for surface roughness,
considering the cutting speed, feed rate and depth of cut as the cutting
parameters, using central composite design. The developed models
are used to determine the optimum machining parameters. These
optimized machining parameters are validated experimentally, and it
is observed that the response values are in reasonable agreement with
the predicted values.