Abstract: Direct Torque Control is a control technique in AC
drive systems to obtain high performance torque control. The
conventional DTC drive contains a pair of hysteresis comparators.
DTC drives utilizing hysteresis comparators suffer from high torque
ripple and variable switching frequency. The most common solution
to those problems is to use the space vector depends on the reference
torque and flux. In this Paper The space vector modulation technique
(SVPWM) is applied to 2 level inverter control in the proposed
DTC-based induction motor drive system, thereby dramatically
reducing the torque ripple. Then the controller based on space vector
modulation is designed to be applied in the control of Induction
Motor (IM) with a three-level Inverter. This type of Inverter has
several advantages over the standard two-level VSI, such as a greater
number of levels in the output voltage waveforms, Lower dV/dt, less
harmonic distortion in voltage and current waveforms and lower
switching frequencies. This paper proposes a general SVPWM
algorithm for three-level based on standard two-level SVPWM. The
proposed scheme is described clearly and simulation results are
reported to demonstrate its effectiveness. The entire control scheme is
implemented with Matlab/Simulink.
Abstract: Reverse Engineering is a very important process in
Software Engineering. It can be performed backwards from system
development life cycle (SDLC) in order to get back the source data
or representations of a system through analysis of its structure,
function and operation. We use reverse engineering to introduce an
automatic tool to generate system requirements from its program
source codes. The tool is able to accept the Cµ programming source
codes, scan the source codes line by line and parse the codes to
parser. Then, the engine of the tool will be able to generate system
requirements for that specific program to facilitate reuse and
enhancement of the program. The purpose of producing the tool is to
help recovering the system requirements of any system when the
system requirements document (SRD) does not exist due to
undocumented support of the system.
Abstract: Wind catchers are traditional natural ventilation
systems attached to buildings in order to ventilate the indoor air. The
most common type of wind catcher is four sided one which is
capable to catch wind in all directions. CFD simulation is the perfect
way to evaluate the wind catcher performance. The accuracy of CFD
results is the issue of concern, so sensitivity analyses is crucial to
find out the effect of different settings of CFD on results. This paper
presents a series of 3D steady RANS simulations for a generic
isolated four-sided wind catcher attached to a room subjected to wind
direction ranging from 0º to 180º with an interval of 45º. The CFD
simulations are validated with detailed wind tunnel experiments. The
influence of an extensive range of computational parameters is
explored in this paper, including the resolution of the computational
grid, the size of the computational domain and the turbulence model.
This study found that CFD simulation is a reliable method for wind
catcher study, but it is less accurate in prediction of models with non
perpendicular wind directions.
Abstract: In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.
Abstract: Seasonal variability of nutrients concentration in the Baltic Sea using the 3D ecosystem numerical model 3D-CEMBS has been investigated. Additionally this study shows horizontal and vertical distribution of nutrients in the Baltic Sea. Model domain is an extended Baltic Sea area divided into 600x640 horizontal grid cells. Aside from standard hydrodynamic parameters 3D-CEMBS produces modeled ecological variables such as: three types of phytoplankton, two detrital classes, dissolved oxygen and the nutrients (nitrate, ammonium, phosphate and silicate). The presented model allows prediction of parameters that describe distribution of nutrients concentration and phytoplankton biomass. 3D-CEMBS can be used to study the effect of different hydrodynamic and biogeochemical processes on distributions of these variables in a larger scale.
Abstract: Some theoretical and experimental aspects related to
the conceptual analyses concerning the direct correspondence
identification between the shape, area and orientation of plantar
pressure and obtaining adequate corrective insoles by rapid
prototyping are presented in this paper. In the first part of the paper
there is the theoretical-correlative concept, which is the fundament of
correspondence deduction between plantar surface characteristics and
respectively corrective insoles. In the second part of the paper the
experimental equipment used to analyze and perform the
correspondence stages and then the integral ones between the
analyzed foot shapes and the ones with corrective insoles is
presented. In the final parte the results used to adapt the insoles
obtained by rapid prototyping but also some specific aspects and
conclusions of the conceptual analysis of direct and rapid
correspondence are shown.
Abstract: Membrane distillation (MD) is a rising technology for
seawater or brine desalination process. In this work, an air gap
membrane distillation (AGMD) performance was investigated for
aqueous NaCl solution along with natural ground water and seawater.
In order to enhance the performance of the AGMD process in
desalination, that is, to get more flux, it is necessary to study the
effect of operating parameters on the yield of distillate water. The
influence of operational parameters such as feed flow rate, feed
temperature, feed salt concentration, coolant temperature and air gap
thickness on the membrane distillation (MD) permeation flux have
been investigated for low and high salt solution. the natural
application of ground water and seawater over 90 h continuous
operation, scale deposits observed on the membrane surface and
reduction in flux represents 23% for ground water and 60% for
seawater, in 90 h. This reduction was eliminated (less than 14 %) by
acidification of feed water. Hence, promote the research attention in
apply of AGMD for the ground water as well as seawater
desalination over today-s conventional RO operation.
Abstract: The small interfering RNA (siRNA) alters the
regulatory role of mRNA during gene expression by translational
inhibition. Recent studies show that upregulation of mRNA because
serious diseases like cancer. So designing effective siRNA with good
knockdown effects plays an important role in gene silencing. Various
siRNA design tools had been developed earlier. In this work, we are
trying to analyze the existing good scoring second generation siRNA
predicting tools and to optimize the efficiency of siRNA prediction
by designing a computational model using Artificial Neural Network
and whole stacking energy (%G), which may help in gene silencing
and drug design in cancer therapy. Our model is trained and tested
against a large data set of siRNA sequences. Validation of our results
is done by finding correlation coefficient of experimental versus
observed inhibition efficacy of siRNA. We achieved a correlation
coefficient of 0.727 in our previous computational model and we
could improve the correlation coefficient up to 0.753 when the
threshold of whole tacking energy is greater than or equal to -32.5
kcal/mol.
Abstract: The aim of this study was to develop a storm water quality improvement strategy plan (WQISP) which assists managers and decision makers of local city councils in enhancing their activities to improve regional water quality. City of Gosnells in Western Australia has been considered as a case study. The procedure on developing the WQISP consists of reviewing existing water quality data, identifying water quality issues in the study areas and developing a decision making tool for the officers, managers and decision makers. It was found that land use type is the main factor affecting the water quality. Therefore, activities, sources and pollutants related to different land use types including residential, industrial, agricultural and commercial are given high importance during the study. Semi-structured interviews were carried out with coordinators of different management sections of the regional councils in order to understand the associated management framework and issues. The issues identified from these interviews were used in preparing the decision making tool. Variables associated with the defined “value versus threat" decision making tool are obtained from the intensive literature review. The main recommendations provided for improvement of water quality in local city councils, include non-structural, structural and management controls and potential impacts of climate change.
Abstract: Land surface temperature (LST) is an important
parameter to study in urban climate. The understanding of the
influence of biophysical factors could improve the establishment of
modeling urban thermal landscape. It is well established that climate
hold a great influence on the urban landscape. However, it has been
recognize that climate has a low priority in urban planning process,
due to the complex nature of its influence. This study will focus on
the relatively cloud free Landsat Thematic Mapper image of the study
area, acquired on the 2nd March 2006. Correlation analyses were
conducted to identify the relationship of LST to the biophysical
factors; vegetation indices, impervious surface, and albedo to
investigate the variation of LST. We suggest that the results can be
considered by the stackholders during decision-making process to
create a cooler and comfortable environment in the urban landscape
for city dwellers.
Abstract: Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.
Abstract: The antimicrobial, antiplasmid and cytotoxic activities of marine algae Halimeda opuntia and Sarconema filiforme were investigated. Antimicrobial bioassay against some human pathogenic bacteria and yeast were conducted using disc diffusion method. Halimeda extract exhibited antibacterial activity against six species of microrganisms, with significant inhibition against Staphylococcus aureus. While Sarconema extract was better potent as antifungal against Candida albicans. Comparative antibacterial studies showed that Halimeda extract showed equivalent or better activity as compared with commercial antibiotic when tested against Staphylococcus aureus. Further tests conducted using dilution method showed both extracts as having bacteriostatic mode of action against the tested microorganisms. Methanol extract of two species showed significant cytotoxicity (LC50
Abstract: To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.
Abstract: The identification and classification of weeds are of
major technical and economical importance in the agricultural
industry. To automate these activities, like in shape, color and
texture, weed control system is feasible. The goal of this paper is to
build a real-time, machine vision weed control system that can detect
weed locations. In order to accomplish this objective, a real-time
robotic system is developed to identify and locate outdoor plants
using machine vision technology and pattern recognition. The
algorithm is developed to classify images into broad and narrow class
for real-time selective herbicide application. The developed
algorithm has been tested on weeds at various locations, which have
shown that the algorithm to be very effectiveness in weed
identification. Further the results show a very reliable performance
on weeds under varying field conditions. The analysis of the results
shows over 90 percent classification accuracy over 140 sample
images (broad and narrow) with 70 samples from each category of
weeds.
Abstract: A facile vapour deposition method of synthesis of vertically aligned ZnO nanowires on carbon seed layer was developed. The received samples were investigated on electronic microscope JSM-6490 LA JEOL and x-ray diffractometer X, pert MPD PRO. The photoluminescence spectra (PL) of obtained ZnO samples at a room temperature were studied using He-Cd laser (325 nm line) as excitation source.
Abstract: In order to obtain an accurate result of the heat transfer
of the rib in the internal cooling Rectangular channel, using separation
of variables, analytical solutions of three dimensional steady-state heat
conduction in rectangular ribs are given by solving three dimensional
steady-state function of the rectangular ribs. Therefore, we can get
solution of three dimensional temperature field in the rib. Based on the
solution, we can get how the Bi number affected on heat transfer.
Furthermore, comparisons of the analytical and numerical results
indicate agreement on temperature field in the rib.
Abstract: This paper presents a microstrip meandered open
circuited stub with bandstop characteristic. The proposed structure is
designed on a high frequency laminate with dielectric constant of 4.0
and board thickness of 0.508 millimeters. The scattering parameters
and electromagnetic field distributions at various frequencies are
investigated by modeling the structure with three dimensional
electromagnetic simulation tool. In order to describe the resonant
and bandstop characteristic of the meandered open circuited stub, a
Smith chart as well as electric field at various frequencies and phases
is illustrated accordingly. The structure can be an alternative method
in suppressing the harmonic response of a bandpass filter.
Abstract: In this paper, a new time discontinuous expanded mixed finite element method is proposed and analyzed for two-order convection-dominated diffusion problem. The proofs of the stability of the proposed scheme and the uniqueness of the discrete solution are given. Moreover, the error estimates of the scalar unknown, its gradient and its flux in the L1( ¯ J,L2( )-norm are obtained.
Abstract: Fatigue life prediction and evaluation are the key
technologies to assure the safety and reliability of automotive rubber
components. The objective of this study is to develop the fatigue
analysis process for vulcanized rubber components, which is
applicable to predict fatigue life at initial product design step. Fatigue
life prediction methodology of vulcanized natural rubber was
proposed by incorporating the finite element analysis and fatigue
damage parameter of maximum strain appearing at the critical location
determined from fatigue test. In order to develop an appropriate
fatigue damage parameter of the rubber material, a series of
displacement controlled fatigue test was conducted using threedimensional
dumbbell specimen with different levels of mean
displacement. It was shown that the maximum strain was a proper
damage parameter, taking the mean displacement effects into account.
Nonlinear finite element analyses of three-dimensional dumbbell
specimens were performed based on a hyper-elastic material model
determined from the uni-axial tension, equi-biaxial tension and planar
test. Fatigue analysis procedure employed in this study could be used
approximately for the fatigue design.
Abstract: Distributed denial-of-service (DDoS) attacks pose a
serious threat to network security. There have been a lot of
methodologies and tools devised to detect DDoS attacks and reduce
the damage they cause. Still, most of the methods cannot
simultaneously achieve (1) efficient detection with a small number of
false alarms and (2) real-time transfer of packets. Here, we introduce
a method for proactive detection of DDoS attacks, by classifying the
network status, to be utilized in the detection stage of the proposed
anti-DDoS framework. Initially, we analyse the DDoS architecture
and obtain details of its phases. Then, we investigate the procedures
of DDoS attacks and select variables based on these features. Finally,
we apply the k-nearest neighbour (k-NN) method to classify the
network status into each phase of DDoS attack. The simulation result
showed that each phase of the attack scenario is classified well and
we could detect DDoS attack in the early stage.