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: The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.
Abstract: The daily growing use of agents in software environments, because of many reasons such as independence and intelligence is not a secret anymore. One of such environments in which there is a prominent job for the agents would be emarketplaces in which a user is able to give those agents the responsibility of buying and selling, instead of searching the emarketplace himself. Making up a framework which has sufficient attention to the required roles and their relations, is the first step of achieving such e-markets. In this paper, we suggest a framework in order to establish such e-markets and we will continue investigating the roles such as seller or buyer and the relations in JADE environment in details.
Abstract: Design for Disassembly (DfD) aims to reuse the
structural components instead of demolition followed by recycling of
the demolition debris. This concept preserves the invested embodied
energy of materials, thus reducing inputs of new embodied energy
during materials reprocessing or remanufacturing. Both analytical and
experimental research on a proposed DfD beam-column connection
for use in residential apartments is currently investigated at the
National University of Singapore in collaboration with the Housing
and Development Board of Singapore. The present study reports on
the results of a numerical analysis of the proposed connection utilizing
finite element analysis. The numerical model was calibrated and
validated by comparison against experimental results. Results of a
parametric study will also be presented and discussed.
Abstract: This paper presents a time control liquids mixing
system in the tanks as an application of fuzzy time control discrete
model. The system is designed for a wide range of industrial
applications. The simulation design of control system has three
inputs: volume, viscosity, and selection of product, along with the
three external control adjustments for the system calibration or to
take over the control of the system autonomously in local or
distributed environment. There are four controlling elements: rotatory
motor, grinding motor, heating and cooling units, and valves
selection, each with time frame limit. The system consists of three
controlled variables measurement through its sensing mechanism for
feed back control. This design also facilitates the liquids mixing
system to grind certain materials in tanks and mix with fluids under
required temperature controlled environment to achieve certain
viscous level. Design of: fuzzifier, inference engine, rule base,
deffuzifiers, and discrete event control system, is discussed. Time
control fuzzy rules are formulated, applied and tested using
MATLAB simulation for the system.
Abstract: Flour from Mucuna beans (Mucuna pruriens) were
used in producing texturized meat analogue using a single screw
extruder to monitor modifications on the proximate composition and
the functional properties at high moisture level. Response surface
methodology based on Box Behnken design at three levels of barrel
temperature (110, 120, 130°C), screw speed (100,120,140rpm) and
feed moisture (44, 47, 50%) were used in 17 runs. Regression models
describing the effect of variables on the product responses were
obtained. Descriptive profile analyses and consumer acceptability
test were carried out on optimized flavoured extruded meat analogue.
Responses were mostly affected by barrel temperature and moisture
level and to a lesser extent by screw speed. Optimization results
based on desirability concept indicated that a barrel temperature of
120.15°C, feed moisture of 47% and screw speed of 119.19 rpm
would produce meat analogue of preferable proximate composition,
functional and sensory properties which reveals consumers` likeness
for the product.
Abstract: Petrology and geochemical characteristics of granitic
rocks from South Sulawesi, especially from Polewaliand Masamba
area are presented in order to elucidate their origin of magma and
geodynamic setting. The granitic rocks in these areas are dominated by
granodiorite and granite in composition. Quartz, K-feldspar and
plagioclase occur as major phases with hornblende and biotite as
major ferromagnesian minerals. All of the samples were plotted in
calc-alkaline field, show metaluminous affinity and typical of I-type
granitic rock. Harker diagram indicates that granitic rocks experienced
fractional crystallization during magmatic evolution. Both groups
displayed an extreme enrichment of LILE, LREE and a slight negative
Eu anomaly which resemble upper continental crust affinity. They
were produced from partial melting of upper continental crust and
have close relationship of sources composition within a suite. The
geochemical characteristics explained the arc related subduction
environment which later give an evidence of continent-continent
collision between Australia-derived microcontinent and Sundalandto
form continental arc environment.
Abstract: The most common result of analysis of highthroughput
data in molecular biology represents a global list of
genes, ranked accordingly to a certain score. The score can be a
measure of differential expression. Recent work proposed a new
method for selecting a number of genes in a ranked gene list from
microarray gene expression data such that this set forms the
Optimally Functionally Enriched Network (OFTEN), formed by
known physical interactions between genes or their products. Here
we present calculation results of relative connectivity of genes from
META-OFTEN network and tentative biological interpretation of the
most reproducible signal. The relative connectivity and
inbetweenness values of genes from META-OFTEN network were
estimated.
Abstract: In order to provide and maintain effective pedagogy for the burgeoning virtual reality community, it is vital to have trained faculty in the institutions of higher education who will teach these courses and be able to make full use of their academic knowledge and expertise. As the number of online courses continues to grow, there is a need for these institutions to establish mentoring programs that will support the novice online instructor. The environment in which this takes place and the factors that ensure its success are critical to the adoption of the new instructional delivery format taught by both seasoned educators and adjunct instructors. Effective one-on-one mentoring promotes a professional, compassionate and collegial faculty who will provide a consistent and rigorous academic program for students online.
Abstract: In order to provide existing SOAP (Simple Object
Access Protocol)-based Web services with users who are familiar with
REST (REpresentational State Transfer)-style Web services, this
paper proposes Web service providing method using Web service
transformation. This enables SOAP-based service providers to define
rules for mapping from RESTful Web services to SOAP-based ones.
Using these mapping rules, HTTP request messages for RESTful
services are converted automatically into SOAP-based service
invocations. Web service providers need not develop duplicate
RESTful services and they can avoid programming mediation
modules per service. Furthermore, they need not equip mediation
middleware like ESB (Enterprise Service Bus) only for the purpose of
transformation of two different Web service styles.
Abstract: Contour filter strips planted with perennial vegetation
can be used to improve surface and ground water quality by reducing
pollutant, such as NO3-N, and sediment outflow from cropland to a
river or lake. Meanwhile, the filter strips of perennial grass with biofuel
potentials also have economic benefits of producing ethanol. In
this study, The Soil and Water Assessment Tool (SWAT) model was
applied to the Walnut Creek Watershed to examine the effectiveness
of contour strips in reducing NO3-N outflows from crop fields to the
river or lake. Required input data include watershed topography,
slope, soil type, land-use, management practices in the watershed and
climate parameters (precipitation, maximum/minimum air
temperature, solar radiation, wind speed and relative humidity).
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 and location on NO3-N reduction
in the subbasins under various meteorological conditions (dry,
average and wet). Variable sizes of contour strips (10%, 20%, 30%
and 50%, respectively, of a subbasin area) planted with perennial
switchgrass were selected for simulating the effects of strip size and
location on stream water quality. Simulation results showed that a
filter strip having 10%-50% of the subbasin area could lead to 55%-
90% NO3-N reduction in the subbasin during an average rainfall
year. Strips occupying 10-20% of the subbasin area were found to be
more efficient in reducing NO3-N when placed along the contour
than that when placed along the river. The results of this study can
assist in cost-benefit analysis and decision-making in best water
resources management practices for environmental protection.
Abstract: The energy consumption of home femto base stations
(BSs) can be reduced, by turning off the Wi-Fi radio interface when
there is no mobile station (MS) under the coverage of the BSs or
MSs do not transmit or receive data packet for long time, especially
in late night. In the energy-efficient home femto BSs, if MSs have
any data packet to transmit and the Wi-Fi radio interface in off
state, MSs wake up the Wi-Fi radio interface of home femto BSs
by using additional low power radio interface. In this paper, the
performance of the energy-efficient home femto BSs from the aspect
of energy consumption and cumulative average delay, and show the
effect of various parameters on energy consumption and cumulative
average delay. From the results, the tradeoff relationship between
energy consumption and cumulative average delay is shown and thus,
appropriate operation should be needed to balance the tradeoff.
Abstract: Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
Abstract: The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.
Abstract: In this paper, an efficient structural approach for
recognizing on-line handwritten digits is proposed. After reading
the digit from the user, the slope is estimated and normalized for
adjacent nodes. Based on the changing of signs of the slope values,
the primitives are identified and extracted. The names of these
primitives are represented by strings, and then a finite state
machine, which contains the grammars of the digits, is traced to
identify the digit. Finally, if there is any ambiguity, it will be
resolved. Experiments showed that this technique is flexible and
can achieve high recognition accuracy for the shapes of the digits
represented in this work.
Abstract: Chakri Maha Prasart Throne Hall is the important
Audience hall in Grand Palace, Bangkok, Thailand which was
established in the early reign of King Chulalongkorn (King Rama V)
in 1882. The Throne was designed with the distinguished architecture
by significant blending of Western and Thai Traditional styles under
the Thai Social changing in Colony Era and Thai traditional culture.
The western style was represented of modernization and civilization as
the other European countries. In the other hand, Thai traditional
architecture style with national emblem or Royal emblem was shown
the status and power of Thai King as the Thai believes and culture.
Abstract: In this paper, we present an analytical framework for the evaluation of the uplink performance of multihop cellular networks based on dynamic time division duplex (TDD). New wireless broadband protocols, such as WiMAX, WiBro, and 3G-LTE apply TDD, and mobile communication protocols under standardization (e.g., IEEE802.16j) are investigating mobile multihop relay (MMR) as a future technology. In this paper a novel MMR TDD scheme is presented, where the dynamic range of the frame is shared to traffic resources of asymmetric nature and multihop relaying. The mobile communication channel interference model comprises of inner and co-channel interference (CCI). The performance analysis focuses on the uplink due to the fact that the effects of dynamic resource allocation show significant performance degradation only in the uplink compared to time division multiple access (TDMA) schemes due to CCI [1-3], where the downlink results to be the same or better.The analysis was based on the signal to interference power ratio (SIR) outage probability of dynamic TDD (D-TDD) and TDMA systems,which are the most widespread mobile communication multi-user control techniques. This paper presents the uplink SIR outage probability with multihop results and shows that the dynamic TDD scheme applying MMR can provide a performance improvement compared to single hop applications if executed properly.
Abstract: The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.
Abstract: This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.
Abstract: Soil chemical and physical properties have important
roles in compartment of the environment and agricultural
sustainability and human health. The objectives of this research is
determination of spatial distribution patterns of Cd, Zn, K, pH, TNV,
organic material and electrical conductivity (EC) in agricultural soils
of Natanz region in Esfehan province. In this study geostatistic and
non-geostatistic methods were used for prediction of spatial
distribution of these parameters. 64 composite soils samples were
taken at 0-20 cm depth. The study area is located in south of
NATANZ agricultural lands with area of 21660 hectares. Spatial
distribution of Cd, Zn, K, pH, TNV, organic material and electrical
conductivity (EC) was determined using geostatistic and geographic
information system. Results showed that Cd, pH, TNV and K data
has normal distribution and Zn, OC and EC data had not normal
distribution. Kriging, Inverse Distance Weighting (IDW), Local
Polynomial Interpolation (LPI) and Redial Basis functions (RBF)
methods were used to interpolation. Trend analysis showed that
organic carbon in north-south and east to west did not have trend
while K and TNV had second degree trend. We used some error
measurements include, mean absolute error(MAE), mean squared
error (MSE) and mean biased error(MBE). Ordinary
kriging(exponential model), LPI(Local polynomial interpolation),
RBF(radial basis functions) and IDW methods have been chosen as
the best methods to interpolating of the soil parameters. Prediction
maps by disjunctive kriging was shown that in whole study area was
intensive shortage of organic matter and more than 63.4 percent of
study area had shortage of K amount.