Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.
Abstract: Prediction of bacterial virulent protein sequences can
give assistance to identification and characterization of novel
virulence-associated factors and discover drug/vaccine targets against
proteins indispensable to pathogenicity. Gene Ontology (GO)
annotation which describes functions of genes and gene products as a
controlled vocabulary of terms has been shown effectively for a
variety of tasks such as gene expression study, GO annotation
prediction, protein subcellular localization, etc. In this study, we
propose a sequence-based method Virulent-GO by mining informative
GO terms as features for predicting bacterial virulent proteins.
Each protein in the datasets used by the existing method
VirulentPred is annotated by using BLAST to obtain its homologies
with known accession numbers for retrieving GO terms. After
investigating various popular classifiers using the same five-fold
cross-validation scheme, Virulent-GO using the single kind of GO
term features with an accuracy of 82.5% is slightly better than
VirulentPred with 81.8% using five kinds of sequence-based features.
For the evaluation of independent test, Virulent-GO also yields better
results (82.0%) than VirulentPred (80.7%). When evaluating single
kind of feature with SVM, the GO term feature performs much well,
compared with each of the five kinds of features.
Abstract: Biofuels, like biobutanol, have been recognized for
being renewable and sustainable fuels which can be produced from
lignocellulosic biomass. To convert lignocellulosic biomass to
biofuel, pretreatment process is an important step to remove
hemicelluloses and lignin to improve enzymatic hydrolysis. Dilute
acid pretreatment has been successful developed for pretreatment of
corncobs and the optimum conditions of dilute sulfuric and
phosphoric acid pretreatment were obtained at 120 °C for 5 min with
15:1 liquid to solid ratio and 140 °C for 10 min with 10:1 liquid to
solid ratio, respectively. The result shows that both of acid
pretreatments gave the content of total sugar approximately 34–35
g/l. In case of inhibitor content (furfural), phosphoric acid
pretreatment gives higher than sulfuric acid pretreatment.
Characterizations of corncobs after pretreatment indicate that both of
acid pretreatments can improve enzymatic accessibility and the better
results present in corncobs pretreated with sulfuric acid in term of
surface area, crystallinity, and composition analysis.
Abstract: Recent trends in building constructions in Libya are
more toward tall (high-rise) building projects. As a consequence, a
better estimation of the lateral loading in the design process is
becoming the focal of a safe and cost effective building industry. Byin-
large, Libya is not considered a potential earthquake prone zone,
making wind is the dominant design lateral loads. Current design
practice in the country estimates wind speeds on a mere random
bases by considering certain factor of safety to the chosen wind
speed. Therefore, a need for a more accurate estimation of wind
speeds in Libya was the motivation behind this study. Records of
wind speed data were collected from 22 metrological stations in
Libya, and were statistically analysed. The analysis of more than four
decades of wind speed records suggests that the country can be
divided into four zones of distinct wind speeds. A computer “survey"
program was manipulated to draw design wind speeds contour map
for the state of Libya.
The paper presents the statistical analysis of Libya-s recorded
wind speed data and proposes design wind speed values for a 50-year
return period that covers the entire country.
Abstract: A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.
Abstract: We introduce the notion of strongly ω -Gorenstein modules, where ω is a faithfully balanced self-orthogonal module. This gives a common generalization of both Gorenstein projective (injective) modules and ω-Gorenstein modules. We investigate some characterizations of strongly ω -Gorenstein modules. Consequently, some properties under change of rings are obtained.
Abstract: The aim of this paper to characterize a larger set of
wavelet functions for implementation in a still image compression
system using SPIHT algorithm. This paper discusses important
features of wavelet functions and filters used in sub band coding to
convert image into wavelet coefficients in MATLAB. Image quality
is measured objectively using peak signal to noise ratio (PSNR) and
its variation with bit rate (bpp). The effect of different parameters is
studied on different wavelet functions. Our results provide a good
reference for application designers of wavelet based coder.
Abstract: The Block Sorting problem is to sort a given
permutation moving blocks. A block is defined as a substring
of the given permutation, which is also a substring of the
identity permutation. Block Sorting has been proved to be
NP-Hard. Until now two different 2-Approximation algorithms
have been presented for block sorting. These are the best known
algorithms for Block Sorting till date. In this work we present
a different characterization of Block Sorting in terms of a
transposition cycle graph. Then we suggest a heuristic,
which we show to exhibit a 2-approximation performance
guarantee for most permutations.
Abstract: A steady two-dimensional magnetohydrodynamics
flow and heat transfer over a stretching vertical sheet influenced by
radiation and porosity is studied. The governing boundary layer
equations of partial differential equations are reduced to a system of
ordinary differential equations using similarity transformation. The
system is solved numerically by using a finite difference scheme
known as the Keller-box method for some values of parameters,
namely the radiation parameter N, magnetic parameter M, buoyancy
parameter l , Prandtl number Pr and permeability parameter K. The
effects of the parameters on the heat transfer characteristics are
analyzed and discussed. It is found that both the skin friction
coefficient and the local Nusselt number decrease as the magnetic
parameter M and permeability parameter K increase. Heat transfer
rate at the surface decreases as the radiation parameter increases.
Abstract: Power cables are vulnerable to failure due to aging or
defects that occur with the passage of time under continuous
operation and loading stresses. PD detection and characterization
provide information on the location, nature, form and extent of the
degradation. As a result, PD monitoring has become an important
part of condition based maintenance (CBM) program among power
utilities. Online partial discharge (PD) localization of defect sources
in power cable system is possible using the time of flight method.
The information regarding the time difference between the main and
reflected pulses and cable length can help in locating the partial
discharge source along the cable length. However, if the length of
the cable is not known and the defect source is located at the extreme
ends of the cable or in the middle of the cable, then double ended
measurement is required to indicate the location of PD source. Use of
multiple sensors can also help in discriminating the cable PD or local/
external PD. This paper presents the experience and results from
online partial discharge measurements conducted in the laboratory
and the challenges in partial discharge source localization.
Abstract: A diamond-like carbon (DLC) based solid-lubricant
film was designed and DLC films were successfully prepared using a
microwave plasma enhanced magnetron sputtering deposition
technology. Post-test characterizations including Raman
spectrometry, X-ray diffraction, nano-indentation test, adhesion test,
friction coefficient test were performed to study the influence of
substrate bias voltage on the mechanical properties of the W- and
S-doped DLC films. The results indicated that the W- and S-doped
DLC films also had the typical structure of DLC films and a better
mechanical performance achieved by the application of a substrate
bias of -200V.
Abstract: Due to growing environmental concerns of the cement
industry, alternative cement technologies have become an area of
increasing interest. It is now believed that new binders are
indispensable for enhanced environmental and durability
performance. Self-compacting Geopolymer concrete is an innovative
method and improved way of concreting operation that does not
require vibration for placing it and is produced by complete
elimination of ordinary Portland cement.
This paper documents the assessment of the compressive strength
and workability characteristics of low-calcium fly ash based selfcompacting
geopolymer concrete. The essential workability
properties of the freshly prepared Self-compacting Geopolymer
concrete such as filling ability, passing ability and segregation
resistance were evaluated by using Slump flow, V-funnel, L-box and
J-ring test methods. The fundamental requirements of high
flowability and segregation resistance as specified by guidelines on
Self Compacting Concrete by EFNARC were satisfied. In addition,
compressive strength was determined and the test results are included
here. This paper also reports the effect of extra water, curing time and
curing temperature on the compressive strength of self-compacting
geopolymer concrete. The test results show that extra water in the
concrete mix plays a significant role. Also, longer curing time and
curing the concrete specimens at higher temperatures will result in
higher compressive strength.
Abstract: Visually impaired people find it extremely difficult to
acquire basic and vital information necessary for their living.
Therefore, they are at a very high risk of being socially excluded as a
result of poor access to information. In recent years, several attempts
have been made in improving the communication methods for
visually impaired people which involve tactile sensation such as
finger Braille, manual alphabets and the print on palm method and
several other electronic devices. But, there are some problems which
arise in such methods such as lack of privacy and lack of
compatibility to computer environment. This paper describes a low
cost Braille hand glove for blind people using slot sensors and
vibration motors with the help of which they can read and write emails,
text messages and read e-books. This glove allows the person
to type characters based on different Braille combination using six
slot sensors. The vibration in six different positions of the glove
which matches to the Braille code allows them to read characters.
Abstract: Physical urban form is recognized to be the media for
human transactions. It directly influences the travel demand of people
in a specific urban area and the amount of energy used for
transportation. Distorted, sprawling form often creates sustainability
problems in urban areas. It is declared in EU strategic planning
documents that compact urban form and mixed land use pattern must
be given the main focus to achieve better sustainability in urban
areas, but the methods to measure and compare these characteristics
are still not clear.
This paper presents the simple methods to measure the spatial
characteristics of urban form by analyzing the location and
distribution of objects in an urban environment. The extended CA
(cellular automata) model is used to simulate urban development
scenarios.
Abstract: This paper presents a system for discovering
association rules from collections of unstructured documents called
EART (Extract Association Rules from Text). The EART system
treats texts only not images or figures. EART discovers association
rules amongst keywords labeling the collection of textual documents.
The main characteristic of EART is that the system integrates XML
technology (to transform unstructured documents into structured
documents) with Information Retrieval scheme (TF-IDF) and Data
Mining technique for association rules extraction. EART depends on
word feature to extract association rules. It consists of four phases:
structure phase, index phase, text mining phase and visualization
phase. Our work depends on the analysis of the keywords in the
extracted association rules through the co-occurrence of the keywords
in one sentence in the original text and the existing of the keywords
in one sentence without co-occurrence. Experiments applied on a
collection of scientific documents selected from MEDLINE that are
related to the outbreak of H5N1 avian influenza virus.
Abstract: In first stage of each microwave receiver there is Low
Noise Amplifier (LNA) circuit, and this stage has important rule in
quality factor of the receiver. The design of a LNA in Radio
Frequency (RF) circuit requires the trade-off many importance
characteristics such as gain, Noise Figure (NF), stability, power
consumption and complexity. This situation Forces desingners to
make choices in the desing of RF circuits. In this paper the aim is to
design and simulate a single stage LNA circuit with high gain and
low noise using MESFET for frequency range of 5 GHz to 6 GHz.
The desing simulation process is down using Advance Design
System (ADS). A single stage LNA has successfully designed with
15.83 dB forward gain and 1.26 dB noise figure in frequency of 5.3
GHz. Also the designed LNA should be working stably In a
frequency range of 5 GHz to 6 GHz.
Abstract: The consumption of lactose in acid cheese whey
anaerobic fermentation process under fed-batch conditions was
studied. During fermentation for 100 hours the biogas production
(CO2 and CH4) was analyzed online. Among the standard analyses
FT-IR spectroscopy was used to follow the consumption of lactose by
bacteria. The absorption bands at 990, 894 and 787 cm-1 in the 2nd
derivative spectra were shown to be characteristic for lactose and
were used to follow the lactose conversion. It was shown that acid
cheese whey lactose was converted by bacteria in first 7 hours. In the
spectra of 17, 18 and 95 hour fermentation samples lactose was not
identified and these results correlated with the HPLC data.
Abstract: The Non-Rotating Adjustable Stabilizer / Directional
Solution (NAS/DS) is the imitation of a mechanical process or an
object by a directional drilling operation that causes a respond
mathematically and graphically to data and decision to choose the
best conditions compared to the previous mode.
The NAS/DS Auto Guide rotary steerable tool is undergoing final
field trials. The point-the-bit tool can use any bit, work at any
rotating speed, work with any MWD/LWD system, and there is no
pressure drop through the tool. It is a fully closed-loop system that
automatically maintains a specified curvature rate.
The Non–Rotating Adjustable stabilizer (NAS) can be controls
curvature rate by exactly positioning and run with the optimum bit,
use the most effective weight (WOB) and rotary speed (RPM) and
apply all of the available hydraulic energy to the bit. The directional
simulator allowed to specify the size of the curvature rate
performance errors of the NAS tool and the magnitude of the random
errors in the survey measurements called the Directional Solution
(DS).
The combination of these technologies (NAS/DS) will provide
smoother bore holes, reduced drilling time, reduced drilling cost and
incredible targeting precision. This simulator controls curvature rate
by precisely adjusting the radial extension of stabilizer blades on a
near bit Non-Rotating Stabilizer and control process corrects for the
secondary effects caused by formation characteristics, bit and tool
wear, and manufacturing tolerances.
Abstract: Bio-chips are used for experiments on genes and
contain various information such as genes, samples and so on. The
two-dimensional bio-chips, in which one axis represent genes and the
other represent samples, are widely being used these days. Instead of
experimenting with real genes which cost lots of money and much
time to get the results, bio-chips are being used for biological
experiments. And extracting data from the bio-chips with high
accuracy and finding out the patterns or useful information from such
data is very important. Bio-chip analysis systems extract data from
various kinds of bio-chips and mine the data in order to get useful
information. One of the commonly used methods to mine the data is
classification. The algorithm that is used to classify the data can be
various depending on the data types or number characteristics and so
on. Considering that bio-chip data is extremely large, an algorithm that
imitates the ecosystem such as the ant algorithm is suitable to use as an
algorithm for classification. This paper focuses on finding the
classification rules from the bio-chip data using the Ant Colony
algorithm which imitates the ecosystem. The developed system takes
in consideration the accuracy of the discovered rules when it applies it
to the bio-chip data in order to predict the classes.