Abstract: This paper analyzes the linkage between migration,
economic globalization and terrorism concerns. On a broad level, I
analyze Canadian economic and political considerations, searching
for causal relationships between political and economic actors on the
one hand, and Canadian immigration law on the other. Specifically,
the paper argues that there are contradictory impulses affecting state
sovereignty. These impulses are are currently being played out in the
field of Canadian immigration law through several proposed changes
to Canada-s Immigration and Refugee Protection Act (IRPA). These
changes reflect an ideological conception of sovereignty that is
intrinsically connected with decision-making capacity centered on an
individual. This conception of sovereign decision-making views
Parliamentary debate and bureaucratic inefficiencies as both equally
responsible for delaying essential decisions relating to the protection
of state sovereignty, economic benefits and immigration control This
paper discusses these concepts in relation to Canadian immigration
policy under Canadian governments over the past twenty five years.
Abstract: The present paper deals with the most adopted technical
solutions for the enhancement of the lift force of a wing. In fact,
during several flight conditions (such as take off and landing), the
lift force needs to be dramatically enhanced. Both trailing edge
devices (such as flaps) and leading edge ones (such as slats) are
described. Finally, the most advanced aerodynamic solutions to avoid
the separation of the boundary layer from aircraft wings at high angles
of attack are reviewed.
Abstract: Decision tree algorithms have very important place at
classification model of data mining. In literature, algorithms use
entropy concept or gini index to form the tree. The shape of the
classes and their closeness to each other some of the factors that
affect the performance of the algorithm. In this paper we introduce a
new decision tree algorithm which employs data (attribute) folding
method and variation of the class variables over the branches to be
created. A comparative performance analysis has been held between
the proposed algorithm and C4.5.
Abstract: AAM has been successfully applied to face alignment,
but its performance is very sensitive to initial values. In case the initial
values are a little far distant from the global optimum values, there
exists a pretty good possibility that AAM-based face alignment may
converge to a local minimum. In this paper, we propose a progressive
AAM-based face alignment algorithm which first finds the feature
parameter vector fitting the inner facial feature points of the face and
later localize the feature points of the whole face using the first
information. The proposed progressive AAM-based face alignment
algorithm utilizes the fact that the feature points of the inner part of the
face are less variant and less affected by the background surrounding
the face than those of the outer part (like the chin contour). The
proposed algorithm consists of two stages: modeling and relation
derivation stage and fitting stage. Modeling and relation derivation
stage first needs to construct two AAM models: the inner face AAM
model and the whole face AAM model and then derive relation matrix
between the inner face AAM parameter vector and the whole face
AAM model parameter vector. In the fitting stage, the proposed
algorithm aligns face progressively through two phases. In the first
phase, the proposed algorithm will find the feature parameter vector
fitting the inner facial AAM model into a new input face image, and
then in the second phase it localizes the whole facial feature points of
the new input face image based on the whole face AAM model using
the initial parameter vector estimated from using the inner feature
parameter vector obtained in the first phase and the relation matrix
obtained in the first stage. Through experiments, it is verified that the
proposed progressive AAM-based face alignment algorithm is more
robust with respect to pose, illumination, and face background than the
conventional basic AAM-based face alignment algorithm.
Abstract: In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.
Abstract: In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Abstract: This paper presents a novel method for inferring the
odor based on neural activities observed from rats- main olfactory
bulbs. Multi-channel extra-cellular single unit recordings were done
by micro-wire electrodes (tungsten, 50μm, 32 channels) implanted in
the mitral/tufted cell layers of the main olfactory bulb of anesthetized
rats to obtain neural responses to various odors. Neural response
as a key feature was measured by substraction of neural firing rate
before stimulus from after. For odor inference, we have developed a
decoding method based on the maximum likelihood (ML) estimation.
The results have shown that the average decoding accuracy is about
100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. This
work has profound implications for a novel brain-machine interface
system for odor inference.
Abstract: The proliferation of web application and the pervasiveness of mobile technology make web-based attacks even more attractive and even easier to launch. Web Application Firewall (WAF) is an intermediate tool between web server and users that provides comprehensive protection for web application. WAF is a negative security model where the detection and prevention mechanisms are based on predefined or user-defined attack signatures and patterns. However, WAF alone is not adequate to offer best defensive system against web vulnerabilities that are increasing in number and complexity daily. This paper presents a methodology to automatically design a positive security based model which identifies and allows only legitimate web queries. The paper shows a true positive rate of more than 90% can be achieved.
Abstract: Persuasive technology has been applied in marketing,
health, environmental conservation, safety and other domains and is
found to be quite effective in changing people-s attitude and
behaviours. This research extends the application domains of
persuasive technology to information security awareness and uses a
theory-driven approach to evaluate the effectiveness of a web-based
program developed based on the principles of persuasive technology
to improve the information security awareness of end users. The
findings confirm the existence of a very strong effect of the webbased
program in raising users- attitude towards information security
aware behavior. This finding is useful to the IT researchers and
practitioners in developing appropriate and effective education
strategies for improving the information security attitudes for endusers.
Abstract: Most papers model Joint Replenishment Problem
(JRP) as a (kT,S) where kT is a multiple value for a common review
period T,and S is a predefined order up to level. In general the (T,S)
policy is characterized by a long out of control period which requires
a large amount of safety stock compared to the (R,Q) policy. In this
paper a probabilistic model is built where an item, call it item(i),
with the shortest order time between interval (T)is modeled under
(R,Q) policy and its inventory is continuously reviewed, while the
rest of items (j) are periodically reviewed at a definite time
corresponding to item
Abstract: Lighvan cheese is basically made from sheep milk in
the area of Sahand mountainside which is located in the North West
of Iran. The main objective of this study was to investigate the effect
of enterococci isolated from traditional Lighvan cheese on the quality
of Iranian UF white during ripening. The experimental design was
split plot based on randomized complete blocks, main plots were four
types of starters and subplots were different ripening durations.
Addition of Enterococcus spp. did not significantly (P
Abstract: This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.
Abstract: In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.
Abstract: Missing data yields many analysis challenges. In case of complex survey design, in addition to dealing with missing data, researchers need to account for the sampling design to achieve useful inferences. Methods for incorporating sampling weights in neural network imputation were investigated to account for complex survey designs. An estimate of variance to account for the imputation uncertainty as well as the sampling design using neural networks will be provided. A simulation study was conducted to compare estimation results based on complete case analysis, multiple imputation using a Markov Chain Monte Carlo, and neural network imputation. Furthermore, a public-use dataset was used as an example to illustrate neural networks imputation under a complex survey design
Abstract: Impurity metals such as manganese and cadmium
from high-tenor cobalt electrolyte solution were selectively removed
by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters
such as pH, organic concentration, O/A ratio, kinetics etc. were
investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount
of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the
extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium
using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single
contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as
with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities
removal process for the production of pure cobalt with less trouble in the electrowinning circuit.
Abstract: Human heart valves diseased by congenital heart
defects, rheumatic fever, bacterial infection, cancer may cause stenosis
or insufficiency in the valves. Treatment may be with medication but
often involves valve repair or replacement (insertion of an artificial
heart valve). Bileaflet mechanical heart valves (BMHVs) are widely
implanted to replace the diseased heart valves, but still suffer from
complications such as hemolysis, platelet activation, tissue
overgrowth and device failure. These complications are closely related
to both flow characteristics through the valves and leaflet dynamics. In
this study, the physiological flow interacting with the moving leaflets
in a bileaflet mechanical heart valve (BMHV) is simulated with a
strongly coupled implicit fluid-structure interaction (FSI) method
which is newly organized based on the Arbitrary-Lagrangian-Eulerian
(ALE) approach and the dynamic mesh method (remeshing) of
FLUENT. The simulated results are in good agreement with previous
experimental studies. This study shows the applicability of the present
FSI model to the complicated physics interacting between fluid flow
and moving boundary.
Abstract: Single Minute Exchange of Dies (SMED) mainly focuses on recognition of internal and external activities. It is concerned particularly with transferring internal activities into external ones in as many numbers as possible, by also minimizing the internal ones. The validity of the method and procedures are verified by an application a Styrofoam manufacturing process where setup times are critical for time reduction. Significant time savings have been achieved with minimum investment. Further, the issues related with employer safety and ergonomics principles during die exchange are noted.
Abstract: Preparation of size controlled nano-particles of silver catalyst on carbon substrate from e-waste has been investigated. Chemical route was developed by extraction of the metals available in nitric acid followed by treatment with hydrofluoric acid. Silver metal particles deposited with an average size 4-10 nm. A stabilizer concentration of 10- 40 g/l was used. The average size of the prepared silver decreased with increase of the anode current density. Size uniformity of the silver nano-particles was improved distinctly at higher current density no more than 20mA... Grain size increased with EK time whereby aggregation of particles was observed after 6 h of reaction.. The chemical method involves adsorption of silver nitrate on the carbon substrate. Adsorbed silver ions were directly reduced to metal particles using hydrazine hydrate. Another alternative method is by treatment with ammonia followed by heating the carbon loaded-silver hydroxide at 980°C. The product was characterized with the help of XRD, XRF, ICP, SEM and TEM techniques.
Abstract: The current work focuses on rephrasing the harmful
effects of mercury that is being released from a number of sources.
Most of the sources are from the industrial waste water. Different
techniques of mercury removal have been discussed and a brief
comparison among these has been made. The experimental work has
been conducted for two most widely used methods of mercury
removal and comparison in terms of their efficiency has been made.