Abstract: A registration framework for image-guided robotic
surgery is proposed for three emergency neurosurgical procedures,
namely Intracranial Pressure (ICP) Monitoring, External Ventricular
Drainage (EVD) and evacuation of a Chronic Subdural Haematoma
(CSDH). The registration paradigm uses CT and white light as
modalities. This paper presents two simulation studies for a
preliminary evaluation of the registration protocol: (1) The loci of the
Target Registration Error (TRE) in the patient-s axial, coronal and
sagittal views were simulated based on a Fiducial Localisation Error
(FLE) of 5 mm and (2) Simulation of the actual framework using
projected views from a surface rendered CT model to represent white
light images of the patient. Craniofacial features were employed as
the registration basis to map the CT space onto the simulated
intraoperative space. Photogrammetry experiments on an artificial
skull were also performed to benchmark the results obtained from the
second simulation. The results of both simulations show that the
proposed protocol can provide a 5mm accuracy for these
neurosurgical procedures.
Abstract: DC-DC converters are widely used in regulated switched mode power supplies and in DC motor drive applications. There are several sources of unwanted nonlinearity in practical power converters. In addition, their operation is characterized by switching that gives birth to a variety of nonlinear dynamics. DC-DC buck and boost converters controlled by pulse-width modulation (PWM) have been simulated. The voltage waveforms and attractors obtained from the circuit simulation have been studied. With the onset of instability, the phenomenon of subharmonic oscillations, quasi-periodicity, bifurcations, and chaos have been observed. This paper is mainly motivated by potential contributions of chaos theory in the design, analysis and control of power converters, in particular and power electronics circuits, in general.
Abstract: The dynamics of the Autonomous Underwater
Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate
accurately because of the variations of these coefficients with
different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain
the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line
adaptive fuzzy model and adaptive neural fuzzy network (ANFN)
model techniques to overcome the uncertain external disturbance and
the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according
to the back propagation algorithm based upon the error between the
identified model and the actual output of the plant. The proposed
ANFN model adopts a functional link neural network (FLNN) as the
consequent part of the fuzzy rules. Thus, the consequent part of the
ANFN model is a nonlinear combination of input variables. Fuzzy
control system is applied to guide and control the AUV using both
adaptive models and mathematical model. Simulation results show
the superiority of the proposed adaptive neural fuzzy network
(ANFN) model in tracking of the behavior of the AUV accurately
even in the presence of noise and disturbance.
Abstract: This paper presents an adaptive nonlinear position
controller with velocity constraint, capable of combining the
input-output linearization technique and Lyapunov stability theory.
Based on the Lyapunov stability theory, the adaptation law of the
proposed controller is derived along with the verification of the overall
system-s stability. Computer simulation results demonstrate that the
proposed controller is robust and it can ensure transient stability of
BLDCM, under the occurrence of a large sudden fault.
Abstract: An application framework provides a reusable design
and implementation for a family of software systems. Application
developers extend the framework to build their particular
applications using hooks. Hooks are the places identified to show
how to use and customize the framework. Hooks define Framework
Interface Classes (FICs) and their possible specifications, which
helps in building reusable test cases for the implementations of these
classes. In applications developed using gray-box frameworks, FICs
inherit framework classes or use them without inheritance. In this
paper, a test-case generation technique is extended to build test cases
for FICs built for gray-box frameworks. A tool is developed to
automate the introduced technique.
Abstract: Financial forecasting using machine learning techniques has received great efforts in the last decide . In this ongoing work, we show how machine learning of graphical models will be able to infer a visualized causal interactions between different banks in the Saudi equities market. One important discovery from such learned causal graphs is how companies influence each other and to what extend. In this work, a set of graphical models named Gaussian graphical models with developed ensemble penalized feature selection methods that combine ; filtering method, wrapper method and a regularizer will be shown. A comparison between these different developed ensemble combinations will also be shown. The best ensemble method will be used to infer the causal relationships between banks in Saudi equities market.
Abstract: People usually have a telephone voice, which means
they adjust their speech to fit particular situations and to blend in with
other interlocutors. The question is: Do we speak differently to
different people? This possibility has been suggested by social
psychologists within Accommodation Theory [1]. Converging toward
the speech of another person can be regarded as a polite speech
strategy while choosing a language not used by the other interlocutor
can be considered as the clearest example of speech divergence [2].
The present study sets out to investigate such processes in the course
of everyday telephone conversations. Using Joos-s [3] model of
formality in spoken English, the researchers try to explore
convergence to or divergence from the addressee. The results
propound the actuality that lexical choice, and subsequently, patterns
of style vary intriguingly in concordance with the person being
addressed.
Abstract: Crawling movement as a motive mode seen in nature
of some animals such as snakes possesses a specific syntactic and
dynamic analysis. Serpentine robot designed by inspiration from
nature and snake-s crawling motion, is regarded as a crawling robot.
In this paper, a serpentine robot with spiral motion model will be
analyzed. The purpose of this analysis is to calculate the vertical and
tangential forces along snake-s body and to determine the parameters
affecting on these forces. Two types of serpentine robots have been
designed in order to examine the achieved relations explained below.
Abstract: This paper addresses the problem of asymptotic tracking
control of a linear parabolic partial differential equation with indomain
point actuation. As the considered model is a non-standard
partial differential equation, we firstly developed a map that allows
transforming this problem into a standard boundary control problem
to which existing infinite-dimensional system control methods can
be applied. Then, a combination of energy multiplier and differential
flatness methods is used to design an asymptotic tracking controller.
This control scheme consists of stabilizing state-feedback derived
from the energy multiplier method and feed-forward control based
on the flatness property of the system. This approach represents
a systematic procedure to design tracking control laws for a class
of partial differential equations with in-domain point actuation. The
applicability and system performance are assessed by simulation
studies.
Abstract: The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Abstract: A total of twenty tensile biopsies were collected from
children undergoing tonsillectomy from teaching hospital ENT
department and Kurdistan private hospital in sulaimani city. All
biopsies were homogenized and cultured; the obtained bacterial
isolates were purified and identified by biochemical tests and VITEK
2 compact system. Among the twenty studied samples, only one
Pseudomonas putida with probability of 99% was isolated.
Antimicrobial susceptibility was carried out by disk diffusion
method, Pseudomonas putida showed resistance to all antibiotics
used except vancomycin. The isolate further subjected to PCR and
DNA sequence analysis of blaVIM gene using different set of primers
for different regions of VIM gene. The results were found to be PCR
positive for the blaVIM gene. To determine the sequence of blaVIM
gene, DNA sequencing performed. Sequence alignment of blaVIM
gene with previously recorded blaVIM gene in NCBI- database showed
that P. putida isolate have different blaVIM gene.
Abstract: In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.
Abstract: The effect of different combinations of response
feedback on the performance of active control system on nonlinear
frames has been studied in this paper. To this end different feedback
combinations including displacement, velocity, acceleration and full
response feedback have been utilized in controlling the response of
an eight story bilinear hysteretic frame which has been subjected to a
white noise excitation and controlled by eight actuators which could
fully control the frame. For active control of nonlinear frame
Newmark nonlinear instantaneous optimal control algorithm has been
used which a diagonal matrix has been selected for weighting
matrices in performance index. For optimal design of active control
system while the objective has been to reduce the maximum drift to
below the yielding level, Distributed Genetic Algorithm (DGA) has
been used to determine the proper set of weighting matrices. The
criteria to assess the effect of each combination of response feedback
have been the minimum required control force to reduce the
maximum drift to below the yielding drift. The results of numerical
simulation show that the performance of active control system is
dependent on the type of response feedback where the velocity
feedback is more effective in designing optimal control system in
comparison with displacement and acceleration feedback. Also using
full feedback of response in controller design leads to minimum
control force amongst other combinations. Also the distributed
genetic algorithm shows acceptable convergence speed in solving the
optimization problem of designing active control systems.
Abstract: The indoor airflow with a mixed natural/forced convection
was numerically calculated using the laminar and turbulent
approach. The Boussinesq approximation was considered for a simplification
of the mathematical model and calculations. The results
obtained, such as mean velocity fields, were successfully compared
with experimental PIV flow visualizations. The effect of the distance
between the cooled wall and the heat exchanger on the temperature
and velocity distributions was calculated. In a room with a simple
shape, the computational code OpenFOAM demonstrated an ability to
numerically predict flow patterns. Furthermore, numerical techniques,
boundary type conditions and the computational grid quality were
examined. Calculations using the turbulence model k-omega had a
significant effect on the results influencing temperature and velocity
distributions.
Abstract: Field experiments were conducted at Annamalai University Experimental Farm, Department of Agronomy; to device suitable weed control measures for direct seeded puddled rice and to study the effect of the weed control measures on the soil microbial population. The treatments comprised of incorporation of pressmud @ 6.25 t ha-1 and application of herbicide butachlor @1.5 kg a. i. ha- 1 with and without safener 4 days after sowing (DAS), 8 DAS alone and also in conjunction with hand weeding at 30 DAS. Hand weeding twice and a weedy check were also maintained. At maximum tillering stage, the population of bacteria was significantly reduced by butachlor application. The injury to microbes caused by herbicide disappeared with the advancement of crop's age and at flowering stage of crop, there was no significant difference among the treatments. The fungal and actinomycetes population remained unaltered by weed control treatments at both the stages of observation.
Abstract: Pearson-s correlation coefficient and sequential path
analysis has been used for determining the interrelationship among
yield, yield components, soil minerals and aroma of Khao Dawk Mali
(KDML) 105 rice grown in the area of Tungkularonghai in Roi-Et
province, located in the northeast of Thailand. Pearson-s correlation
coefficient in this study showed that the number of panicles was the
only factor that had positive significant (0.790**) effect on grain
yield. Sequential path analysis revealed that the number of panicles
followed by the number of fertile spikelets and 100-grain weight
were the first-order factors which had positive direct effects on grain
yield. Whereas, other factors analyzed had indirect effects
influencing grain yield. This study also indicated that no significant
relationship was found between the aroma level and any of the
factors analyzed.
Abstract: In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.
Abstract: Application of neural networks in execution of
programmed pulse width modulation (PPWM) of a voltage source
inverter (VSI) is studied in this paper. Using the proposed method it is
possible to cancel out the desired harmonics in output of VSI in
addition to control the magnitude of fundamental harmonic,
contineously. By checking the non-trained values and a performance
index, the most appropriate neural network is proposed. It is shown
that neural networks may solve the custom difficulties of practical
utilization of PPWM such as large size of memory, complex digital
circuits and controlling the magnitude of output voltage in a discrete
manner.
Abstract: The number of users supported in a DS-CDMA
cellular system is typically less than spreading factor (N), and the
system is said to be underloaded. Overloading is a technique to
accommodate more number of users than the spreading factor N. In
O/O overloading scheme, the first set is assigned to the N
synchronous users and the second set is assigned to the additional
synchronous users. An iterative multistage soft decision interference
cancellation (SDIC) receiver is used to remove high level of
interference between the two sets. Performance is evaluated in terms
of the maximum number acceptable users so that the system
performance is degraded slightly compared to the single user
performance at a specified BER. In this paper, the capacity of CDMA
based O/O overloading scheme is evaluated with SDIC receiver. It is
observed that O/O scheme using orthogonal Gold codes provides
25% channel overloading (N=64) for synchronous DS-CDMA
system on an AWGN channel in the uplink at a BER of 1e-5.For a
Rayleigh faded channel, the critical capacity is 40% at a BER of 5e-5
assuming synchronous users. But in practical systems, perfect chip
timing is very difficult to maintain in the uplink.. We have shown that
the overloading performance reduces to 11% for a timing
synchronization error of 0.02Tc for a BER of 1e-5.
Abstract: A major challenge in biomaterials research is the
regulation of protein adsorption which is a key factor for controlling
the subsequent cell adhesion at implant surfaces. The aim of the
present study was to control the adsorption of fibronectin (FN) and
the attachment of MG-63 osteoblasts with an electronic
nanostructure. Shallow doping line lattices with a period of 260 nm
were produced for this purpose by implantation of phosphorous in
silicon wafers. Protein coverage was determined after incubating the
substrate with FN by means of an immunostaining procedure and the
measurement of the fluorescence intensity with a TECAN analyzer.
We observed an increased amount of adsorbed FN on the
nanostructure compared to control substrates. MG-63 osteoblasts
were cultivated for 24h on FN-incubated substrates and their
morphology was assessed by SEM. Preferred orientation and
elongation of the cells in direction of the doping lattice lines was
observed on FN-coated nanostructures.