Abstract: Combining classifiers is a useful method for solving
complex problems in machine learning. The ECOC (Error Correcting
Output Codes) method has been widely used for designing combining
classifiers with an emphasis on the diversity of classifiers. In this
paper, in contrast to the standard ECOC approach in which individual
classifiers are chosen homogeneously, classifiers are selected
according to the complexity of the corresponding binary problem. We
use SATIMAGE database (containing 6 classes) for our experiments.
The recognition error rate in our proposed method is %10.37 which
indicates a considerable improvement in comparison with the
conventional ECOC and stack generalization methods.
Abstract: Naive Bayes Nearest Neighbor (NBNN) and its variants, i,e., local NBNN and the NBNN kernels, are local feature-based classifiers that have achieved impressive performance in image classification. By exploiting instance-to-class (I2C) distances (instance means image/video in image/video classification), they avoid quantization errors of local image descriptors in the bag of words (BoW) model. However, the performances of NBNN, local NBNN and the NBNN kernels have not been validated on video analysis. In this paper, we introduce these three classifiers into human action recognition and conduct comprehensive experiments on the benchmark KTH and the realistic HMDB datasets. The results shows that those I2C based classifiers consistently outperform the SVM classifier with the BoW model.
Abstract: Heavy metals have bad effects on environment and
soils and it can uptake by natural HAP .natural Hap is an inexpensive
material that uptake large amounts of various heavy metals like Zn
(II) .Natural HAP (N-HAP), extracted from bovine cortical bone ash,
is a good choice for substitution of commercial HAP. Several
experiments were done to investigate the sorption capacity of Zn (II)
to N-HAP in various particles sizes, temperatures, initial
concentrations, pH and reaction times. In this study, the sorption of
Zinc ions from a Zn solution onto HAP particles with sizes of 1537.6
nm and 47.6 nm at three initial pH values of 4.50, 6.00 and 7.50 was
studied. The results showed that better performance was obtained
through a 47.6 nm particle size and higher pH values. The
experimental data were analyzed using Langmuir, Freundlich, and
Arrhenius equations for equilibrium, kinetic and thermodynamic
studies. The analysis showed a maximum adsorption capacity of NHAP
as being 1.562 mmol/g at a pH of 7.5 and small particle size.
Kinetically, the prepared N-HAP is a feasible sorbent that retains Zn
(II) ions through a favorable and spontaneous sorption process.
Abstract: Gaharu that produced by Aquilaria spp. is classified as
one of the most valuable forest products traded internationally as it is
very resinous, fragrant and highly valuable heartwood. Gaharu has
been widely used in aromatheraphy, medicine, perfume and religious
practices. This work aimed to determine the factors affecting solid
liquid extraction of gaharu oil using hexane as solvent under
experimental condition. The kinetics of extraction was assumed and
verified based on a second-order mechanism. The effect of three
main factors, which were temperature, reaction time and solvent to
solid ratio were investigated to achieve maximum oil yield. The
optimum condition were found at temperature 65°C, 9 hours reaction
time and solvent to solid ratio of 12:1 with 14.5% oil yield. The
kinetics experimental data agrees and well fitted with the second
order extraction model. The initial extraction rate (h) was 0.0115
gmL-1min-1; the extraction capacity (Cs) was 1.282gmL-1; the second
order extraction constant (k) was 0.007 mLg-1min-1 and coefficient of
determination, R2 was 0.945.
Abstract: Emphasis on the advancement of new materials and technology has been there for the past few decades. The global development towards using cheap and durable materials from renewable resources contributes to sustainable development. An experimental investigation of mechanical behaviour of sisal fibre-reinforced concrete is reported for making a suitable building material in terms of reinforcement. Fibre reinforced Composite is one such material, which has reformed the concept of high strength. Sisal fibres are abundantly available in the hot areas. Sisal fibre has emerged as a reinforcing material for concretes, used in civil structures. In this work, properties such as hardness and tensile strength of sisal fibre reinforced cement composites with 6, 12, 18 and 24% by weight of sisal fibres were assessed. Sisal fibre reinforced cement composite slabs with long sisal fibres were manufactured using a cast hand lay up technique. Mechanical response was measured under tension. The high energy absorption capacity of the developed composite system was reflected in high toughness values under tension respectively.
Abstract: Laboratory classes in Electrical Engineering are often hampered by safety issues, as students have to work on high voltage lines. One solution is to make use of virtual laboratory simulations, to help students understand the concepts taught in their coursework. In this context, we have conceived and implemented virtual lab experiments in connection with the study of earthing arrangements. In this work, software was developed, which aid student in understanding the working of a residual current device (RCD) in a TT earthing system. Various parameters, such as the earthing resistances, leakage currents and harmonics were included for a TT system with RCD connection.
Abstract: High power laser – total emissivity method (HPL-TE method) for determination of coatings relative total emissivity dependent on the temperature is introduced. Method principle, experimental and evaluation parts of the method are described. Computer model of HPL-TE method is employed to perform the sensitivity analysis of the effect of method parameters on the sample surface temperature in the positions where the surface temperature and radiation heat flux are measured.
Abstract: Numerical analysis of flow characteristics and
separation efficiency in a high-efficiency cyclone has been performed.
Several models based on the experimental observation for a design
purpose were proposed. However, the model is only estimated the
cyclone's performance under the limited environments; it is difficult to
obtain a general model for all types of cyclones. The purpose of this
study is to find out the flow characteristics and separation efficiency
numerically. The Reynolds stress model (RSM) was employed instead
of a standard k-ε or a k-ω model which was suitable for isotropic
turbulence and it could predict the pressure drop and the Rankine
vortex very well. For small particles, there were three significant
components (entrance of vortex finder, cone, and dust collector) for
the particle separation. In the present work, the particle re-entraining
phenomenon from the dust collector to the cyclone body was observed
after considerable time. This re-entrainment degraded the separation
efficiency and was one of the significant factors for the separation
efficiency of the cyclone.
Abstract: Advertising today has already become an integral part
of human life as a building block of the consumer community. A
component of the value chain of the media, advertising sector is
struggling increasingly harder to find new methods to reach
consumers. The tendency towards experimental marketing practices
is increasing day by day, especially to divert consumers from the idea
“They are selling something to me.” It is therefore considered a good
idea to investigate the trust in ad media of consumers, who are today
exposed to a great bulk of information from advertising sector.
In this study, the current value of ad media for the young
consumer will be investigated. Data on various ad media reliability
will be comparatively analyzed and young consumers will be traced
by including university students in the study. In this research, which
will be performed on students studying at the Selçuk University
(Turkey) by random sampling method, data will be obtained by
survey technique and evaluated by a statistical analysis.
Abstract: This paper presents a rule-based text- to- speech
(TTS) Synthesis System for Standard Malay, namely SMaTTS. The
proposed system using sinusoidal method and some pre- recorded
wave files in generating speech for the system. The use of phone
database significantly decreases the amount of computer memory
space used, thus making the system very light and embeddable. The
overall system was comprised of two phases the Natural Language
Processing (NLP) that consisted of the high-level processing of text
analysis, phonetic analysis, text normalization and morphophonemic
module. The module was designed specially for SM to overcome
few problems in defining the rules for SM orthography system before
it can be passed to the DSP module. The second phase is the Digital
Signal Processing (DSP) which operated on the low-level process of
the speech waveform generation. A developed an intelligible and
adequately natural sounding formant-based speech synthesis system
with a light and user-friendly Graphical User Interface (GUI) is
introduced. A Standard Malay Language (SM) phoneme set and an
inclusive set of phone database have been constructed carefully for
this phone-based speech synthesizer. By applying the generative
phonology, a comprehensive letter-to-sound (LTS) rules and a
pronunciation lexicon have been invented for SMaTTS. As for the
evaluation tests, a set of Diagnostic Rhyme Test (DRT) word list was
compiled and several experiments have been performed to evaluate
the quality of the synthesized speech by analyzing the Mean Opinion
Score (MOS) obtained. The overall performance of the system as
well as the room for improvements was thoroughly discussed.
Abstract: Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.
Abstract: The concerns about clean environment and high oil
prices driving forces for the research on alternative fuels. The
research efforts directed towards improving the performance of C.I
engines using vegetable oil as fuel. The paper deals results of
performance of a four stroke, single cylinder C.I. engine by preheated
neat Karanja oil is done from 30
o
C to 100
o
C. The performance of the
engine was studied for a speed range between 1500 to 4000 rpm, with
the engine operated under full load conditions. The performance
parameters considered for comparing are brake specific fuel
consumption, thermal efficiency, brake power, Nox emission of the
engine. The engine offers lower thermal efficiency when it is
powered by preheated neat Karanja oil at higher speed. The power
developed and Nox emission increase with the increase in the fuel
inlet temperature and the specific fuel consumption is higher than
diesel fuel operation at all elevated fuel inlet temperature.
Abstract: Present study summarizes the control of Vibrio
alginolyticus infection in hatchery reared Clownfish, Amphiprion
sebae with the extract of the mangrove plant, Avicennia marina.
Fishes with visible symptoms of hemorrhagic spots were chosen and
the genomic DNA of the causative bacterium was isolated and
sequenced based on 16S rDNA gene. The in vitro assay revealed that
a fraction of A. marina leaf extract elucidated with ethyl acetate:
methanol (6:4) showed a high activity (28 mm) at 125 μg/ml
concentrations. About 4 % of the fraction fed along with live V.
alginolyticus was significantly decreased the cumulative mortality
(P
Abstract: recurrent neural network (RNN) is an efficient tool for
modeling production control process as well as modeling services. In
this paper one RNN was combined with regression model and were
employed in order to be checked whether the obtained data by the
model in comparison with actual data, are valid for variable process
control chart. Therefore, one maintenance process in workshop of
Esfahan Oil Refining Co. (EORC) was taken for illustration of
models. First, the regression was made for predicting the response
time of process based upon determined factors, and then the error
between actual and predicted response time as output and also the
same factors as input were used in RNN. Finally, according to
predicted data from combined model, it is scrutinized for test values
in statistical process control whether forecasting efficiency is
acceptable. Meanwhile, in training process of RNN, design of
experiments was set so as to optimize the RNN.
Abstract: This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. The experiments reveal superior results in terms of speed and convergence to achieve a solution.
Abstract: This text studies glass bottle intelligent inspector
based machine vision instead of manual inspection. The system
structure is illustrated in detail in this paper. The text presents the
method based on watershed transform methods to segment the
possible defective regions and extract features of bottle wall by rules.
Then wavelet transform are used to exact features of bottle finish
from images. After extracting features, the fuzzy support vector
machine ensemble is putted forward as classifier. For ensuring that
the fuzzy support vector machines have good classification ability,
the GA based ensemble method is used to combining the several
fuzzy support vector machines. The experiments demonstrate that
using this inspector to inspect glass bottles, the accuracy rate may
reach above 97.5%.
Abstract: This study experimentally investigates the heat transfer effects of forced convection and natural convection under different substrate openings design. A computational fluid dynamics (CFD) model was established and implemented to verify and explain the experimental results and heat transfer behavior. It is found that different opening position will destroy the growth of the boundary layer on substrates to alter the cooling ability for both forced under low Reynolds number and natural convection. Nevertheless, having too many opening may reduce heat conduction and affect the overall heat transfer performance. This study provides future researchers with a guideline on designing and electronic package manufacturing.
Abstract: The use of contour strips of perennial vegetation with
bio-fuel potential can improve surface water quality by reducing
NO3-N and sediment outflow from cropland to surface water-bodies.
It also has economic benefits of producing ethanol. In this study,
The Soil and Water Assessment Tool (SWAT) model was applied to
a watershed in Iowa, USA to examine the effectiveness of contour
strips of switch grass in reducing the NO3-N outflows from crop
fields to rivers or lakes. Numerical experiments were conducted to
identify potential subbasins in the watershed that have high water
quality impact, and to examine the effects of strip size on NO3-N
reduction under various meteorological conditions, i.e. dry, average
and wet years. Useful information was obtained for the evaluation of
economic feasibility of growing switch grass for bio-fuel in contour
strips. The results can assist in cost-benefit analysis and decisionmaking
in best management practices for environmental protection.
Abstract: Researchers have long had trouble in measurement of
Exchangeable Sodium Ratio (ESR) at salt-affected soils. this
parameter are often determined using laborious and time consuming
laboratory tests, but it may be more appropriate and economical to
develop a method which uses a more simple soil salinity index. The
aim of this study was to determine the relationship between
exchangeable sodium ratio (ESR) and sodium adsorption ratio (SAR)
in some salt-affected soils of Khuzestan plain. To this purpose, two
experimental areas (S1, S2) of Khuzestan province-IRAN were
selected and four treatments with three replications by series of
double rings were applied. The treatments were included 25cm,
50cm, 75cm and 100cm water application. The statistical results of
the study indicated that in order to predict soil ESR based on soil
SAR the linear regression model ESR=0.2048+0.0066 SAR
(R2=0.53) & ESR=0.0564+0.0171 SAR (R2=0.76) can be
recommended in Pilot S1 and S2 respectively.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.