Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: Automatic currency note recognition invariably
depends on the currency note characteristics of a particular country
and the extraction of features directly affects the recognition ability.
Sri Lanka has not been involved in any kind of research or
implementation of this kind. The proposed system “SLCRec" comes
up with a solution focusing on minimizing false rejection of notes.
Sri Lankan currency notes undergo severe changes in image quality
in usage. Hence a special linear transformation function is adapted to
wipe out noise patterns from backgrounds without affecting the
notes- characteristic images and re-appear images of interest. The
transformation maps the original gray scale range into a smaller
range of 0 to 125. Applying Edge detection after the transformation
provided better robustness for noise and fair representation of edges
for new and old damaged notes. A three layer back propagation
neural network is presented with the number of edges detected in row
order of the notes and classification is accepted in four classes of
interest which are 100, 500, 1000 and 2000 rupee notes. The
experiments showed good classification results and proved that the
proposed methodology has the capability of separating classes
properly in varying image conditions.
Abstract: in this work, we present a new strategy of direct adaptive control denoted: Extended minimal controller synthesis (EMCS). This algorithm is designed for an induction motor, which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The main motivation of the EMCS control is to enhance the robustness of the MRAC algorithms, i.e. the rejection of bounded effects of rapidly varying external disturbances.
Abstract: The fundamental aim of extended expansion concept is
to achieve higher work done which in turn leads to higher thermal
efficiency. This concept is compatible with the application of
turbocharger and LHR engine. The Low Heat Rejection engine was
developed by coating the piston crown, cylinder head inside with
valves and cylinder liner with partially stabilized zirconia coating of
0.5 mm thickness. Extended expansion in diesel engines is termed as
Miller cycle in which the expansion ratio is increased by reducing the
compression ratio by modifying the inlet cam for late inlet valve
closing. The specific fuel consumption reduces to an appreciable level
and the thermal efficiency of the extended expansion turbocharged
LHR engine is improved.
In this work, a thermodynamic model was formulated and
developed to simulate the LHR based extended expansion
turbocharged direct injection diesel engine. It includes a gas flow
model, a heat transfer model, and a two zone combustion model. Gas
exchange model is modified by incorporating the Miller cycle, by
delaying inlet valve closing timing which had resulted in considerable
improvement in thermal efficiency of turbocharged LHR engines. The
heat transfer model, calculates the convective and radiative heat
transfer between the gas and wall by taking into account of the
combustion chamber surface temperature swings. Using the two-zone
combustion model, the combustion parameters and the chemical
equilibrium compositions were determined. The chemical equilibrium
compositions were used to calculate the Nitric oxide formation rate by
assuming a modified Zeldovich mechanism. The accuracy of this
model is scrutinized against actual test results from the engine. The
factors which affect thermal efficiency and exhaust emissions were
deduced and their influences were discussed. In the final analysis it is
seen that there is an excellent agreement in all of these evaluations.
Abstract: In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images.
Abstract: Nonspecific protein adsorption generally occurs on
any solid surfaces and usually has adverse consequences. Adsorption
of proteins onto a solid surface is believed to be the initial and
controlling step in biofouling. Surfaces modified with end-tethered
poly(ethylene glycol) (PEG) have been shown to be protein-resistant
to some degree. In this study, the adsorption of β-casein and
lysozyme was performed on 6 different types of surfaces where PEG
was tethered onto stainless steel by polyethylene imine (PEI) through
either OH or NHS end groups. Protein adsorption was also performed
on the bare stainless steel surface as a control. The adsorption was
conducted at 23 °C and pH 7.2. In situ QCM-D was used to
determine PEG adsorption kinetics, plateau PEG chain densities,
protein adsorption kinetics and plateau protein adsorbed quantities.
PEG grafting density was the highest for a NHS coupled chain,
around 0.5 chains / nm2. Interestingly, lysozyme which has smaller
size than β-casein, appeared to adsorb much less mass than that of β-
casein. Overall, the surface with high PEG grafting density exhibited
a good protein rejection.
Abstract: A high precision temperature insensitive current and voltage reference generator is presented. It is specifically developed for temperature compensated oscillator. The circuit, designed using MXIC 0.5um CMOS technology, has an operating voltage that ranges from 2.6V to 5V and generates a voltage of 1.21V and a current of 6.38 ӴA. It exhibits a variation of ±0.3nA for the current reference and a stable output for voltage reference as the temperature is varied from 0°C to 70°C. The power supply rejection ratio obtained without any filtering capacitor at 100Hz and 10MHz is -30dB and -12dB respectively.
Abstract: This paper deals with a design method of a discrete
modified Internal Model Control (IMC) for a plant with an integrator
and dead time. If there is a load disturbance in the input or output side
of the plant, the proposed control system can eliminate the steady-state
error caused by it. The disturbance compensator in this method is
simple and its order is low regardless of that of a plant. The simulation
studies show that the proposed method has superior performance for a
load disturbance rejection and robustness.
Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: Matching algorithms have significant importance in
speaker recognition. Feature vectors of the unknown utterance are
compared to feature vectors of the modeled speakers as a last step in
speaker recognition. A similarity score is found for every model in
the speaker database. Depending on the type of speaker recognition,
these scores are used to determine the author of unknown speech
samples. For speaker verification, similarity score is tested against a
predefined threshold and either acceptance or rejection result is
obtained. In the case of speaker identification, the result depends on
whether the identification is open set or closed set. In closed set
identification, the model that yields the best similarity score is
accepted. In open set identification, the best score is tested against a
threshold, so there is one more possible output satisfying the
condition that the speaker is not one of the registered speakers in
existing database. This paper focuses on closed set speaker
identification using a modified version of a well known matching
algorithm. The results of new matching algorithm indicated better
performance on YOHO international speaker recognition database.
Abstract: This paper presents a speed fuzzy sliding mode
controller for a vector controlled induction machine (IM) fed by a
voltage source inverter (PWM).
The sliding mode based fuzzy control method is developed to
achieve fast response, a best disturbance rejection and to maintain a
good decoupling.
The problem with sliding mode control is that there is high
frequency switching around the sliding mode surface. The FSMC is
the combination of the robustness of Sliding Mode Control (SMC)
and the smoothness of Fuzzy Logic (FL). To reduce the torque
fluctuations (chattering), the sign function used in the conventional
SMC is substituted with a fuzzy logic algorithm.
The proposed algorithm was simulated by Matlab/Simulink
software and simulation results show that the performance of the
control scheme is robust and the chattering problem is solved.
Abstract: This research is a collaborative narrative research, which is mixed with issues of selected papers and researcher's experience as an anonymous user on social networking sites. The objective of this research is to understand the reasons of the regular users who reject to contact with anonymous users, and to study the communication traditions used in the selected studies. Anonymous users are rejected by regular users, because of the fear of cyber bully, the fear of unpleasant behaviors, and unwillingness of changing communication norm. The suggestion for future research design is to use longitudinal design or quantitative design; and the theory in rhetorical tradition should be able to help develop a strong trust message.
Abstract: Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.
Abstract: This paper intends to identify the ethnic Kazakhstani
Koreans- political process of identity formation by exploring their
narrative and practice about the state language represented in the
course of their becoming the new citizens of a new independent state.
The Russophone Kazakhstani Koreans- inability to speak the official
language of their affiliated state is considered there as dissatisfying the
basic requirement of citizens of the independent state, so that they are
becoming marginalized from the public sphere. Their contradictory
attitude that at once demonstrates nominal reception and practical
rejection of the obligatory state language unveils a high barrier inside
between their self-language and other-language. In this paper, the
ethnic Korean group-s conflicting linguistic identity is not seen as a
free and simple choice, but as a dynamic struggle and political process
in which the subject-s past experiences and memories intersect with
the external elements of pressure.
Abstract: This paper proposes an innovative methodology for
Acceptance Sampling by Variables, which is a particular category of
Statistical Quality Control dealing with the assurance of products
quality. Our contribution lies in the exploitation of machine learning
techniques to address the complexity and remedy the drawbacks of
existing approaches. More specifically, the proposed methodology
exploits Artificial Neural Networks (ANNs) to aid decision making
about the acceptance or rejection of an inspected sample. For any
type of inspection, ANNs are trained by data from corresponding
tables of a standard-s sampling plan schemes. Once trained, ANNs
can give closed-form solutions for any acceptance quality level and
sample size, thus leading to an automation of the reading of the
sampling plan tables, without any need of compromise with the
values of the specific standard chosen each time. The proposed
methodology provides enough flexibility to quality control engineers
during the inspection of their samples, allowing the consideration of
specific needs, while it also reduces the time and the cost required for
these inspections. Its applicability and advantages are demonstrated
through two numerical examples.
Abstract: To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
correlated.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.
Abstract: Prickly pear juice has received renewed attention with regard to the effects of processing and preservation on its sensory qualities (colour, taste, flavour, aroma, astringency, visual browning and overall acceptability). Juice was prepared by homogenizing fruit and treating the pulp with pectinase (Aspergillus niger). Juice treatments applied were sugar addition, acidification, heat-treatment, refrigeration, and freezing and thawing. Prickly pear pulp and juice had unique properties (low pH 3.88, soluble solids 3.68 oBrix and high titratable acidity 0.47). Sensory profiling and descriptive analyses revealed that non-treated juice had a bitter taste with high astringency whereas treated prickly pear was significantly sweeter. All treated juices had a good sensory acceptance with values approximating or exceeding 7. Regression analysis of the consumer sensory attributes for non-treated prickly pear juice indicated an overwhelming rejection, while treated prickly pear juice received overall acceptability. Thus, educed favourable sensory responses and may have positive implications for consumer acceptability.
Abstract: A high performance computer includes a fast
processor and millions bytes of memory. During the data processing,
huge amount of information are shuffled between the memory and
processor. Because of its small size and its effectiveness speed, cache
has become a common feature of high performance computers.
Enhancing cache performance proved to be essential in the speed up
of cache-based computers. Most enhancement approaches can be
classified as either software based or hardware controlled. The
performance of the cache is quantified in terms of hit ratio or miss
ratio. In this paper, we are optimizing the cache performance based
on enhancing the cache hit ratio. The optimum cache performance is
obtained by focusing on the cache hardware modification in the way
to make a quick rejection to the missed line's tags from the hit-or
miss comparison stage, and thus a low hit time for the wanted line in
the cache is achieved. In the proposed technique which we called
Even- Odd Tabulation (EOT), the cache lines come from the main
memory into cache are classified in two types; even line's tags and
odd line's tags depending on their Least Significant Bit (LSB). This
division is exploited by EOT technique to reject the miss match line's
tags in very low time compared to the time spent by the main
comparator in the cache, giving an optimum hitting time for the
wanted cache line. The high performance of EOT technique against
the familiar mapping technique FAM is shown in the simulated
results.