Abstract: This research aims at modeling and simulating the effects of nanofluids on cylindrical heat pipes thermal performance using the ANSYS-FLUENT CFD commercial software. The heat pipe outer wall temperature distribution, thermal resistance, liquid pressure and axial velocity in presence of suspended nano-scaled solid particle (i.e. Cu, Al2O3 and TiO2) within the fluid (water) were investigated. The effect of particle concentration and size were explored and it is concluded that the thermal performance of the heat pipe is improved when using nanofluid as the system working fluid. Additionally, it was observed that the thermal resistance of the heat pipe drops as the particle concentration level increases and particle radius decreases.
Abstract: The Random Coefficient Dynamic Regression (RCDR)
model is to developed from Random Coefficient Autoregressive
(RCA) model and Autoregressive (AR) model. The RCDR model
is considered by adding exogenous variables to RCA model. In this
paper, the concept of the Maximum Likelihood (ML) method is used
to estimate the parameter of RCDR(1,1) model. Simulation results
have shown the AIC and BIC criterion to compare the performance of
the the RCDR(1,1) model. The variables as the stationary and weakly
stationary data are good estimates where the exogenous variables
are weakly stationary. However, the model selection indicated that
variables are nonstationarity data based on the stationary data of the
exogenous variables.
Abstract: In this work we develop an object extraction method
and propose efficient algorithms for object motion characterization.
The set of proposed tools serves as a basis for development of objectbased
functionalities for manipulation of video content. The
estimators by different algorithms are compared in terms of quality
and performance and tested on real video sequences. The proposed
method will be useful for the latest standards of encoding and
description of multimedia content – MPEG4 and MPEG7.
Abstract: The importance of nurturing, accumulating, and efficiently deploying knowledge resources through formal structures and organisational mechanisms is well understood. Recent trends in knowledge management (KM) highlight that the effective creation and transfer of knowledge can also rely upon extra-organisational channels, such as, informal networks. The perception exists that the role of informal networks in knowledge creation and performance has been underestimated in the organisational context. Literature indicates that many managers fail to comprehend and successfully exploit the potential role of informal networks to create value for their organisations. This paper investigates: 1) whether managers share work-specific knowledge with informal contacts within and outside organisational boundaries; and 2) what do they think is the importance of this knowledge collaboration in their learning and work outcomes.
Abstract: Fully customized hardware based technology provides high performance and low power consumption by specializing the tasks in hardware but lacks design flexibility since any kind of changes require re-design and re-fabrication. Software based solutions operate with software instructions due to which a great flexibility is achieved from the easy development and maintenance of the software code. But this execution of instructions introduces a high overhead in performance and area consumption. In past few decades the reconfigurable computing domain has been introduced which overcomes the traditional trades-off between flexibility and performance and is able to achieve high performance while maintaining a good flexibility. The dramatic gains in terms of chip performance and design flexibility achieved through the reconfigurable computing systems are greatly dependent on the design of their computational units being integrated with reconfigurable logic resources. The computational unit of any reconfigurable system plays vital role in defining its strength. In this research paper an RFU based computational unit design has been presented using the tightly coupled, multi-threaded reconfigurable cores. The proposed design has been simulated for VLIW based architectures and a high gain in performance has been observed as compared to the conventional computing systems.
Abstract: A comparison between the performance of Latin and
Arabic handwritten digits recognition problems is presented. The
performance of ten different classifiers is tested on two similar
Arabic and Latin handwritten digits databases. The analysis shows
that Arabic handwritten digits recognition problem is easier than that
of Latin digits. This is because the interclass difference in case of
Latin digits is smaller than in Arabic digits and variances in writing
Latin digits are larger. Consequently, weaker yet fast classifiers are
expected to play more prominent role in Arabic handwritten digits
recognition.
Abstract: In many industries, control charts is one of the most
frequently used tools for quality management. Hotelling-s T2 is used
widely in multivariate control chart. However, it has little defect when
detecting small or medium process shifts. The use of supplementary
sensitizing rules can improve the performance of detection. This study
applied sensitizing rules for Hotelling-s T2 control chart to improve the
performance of detection. Support vector machines (SVM) classifier
to identify the characteristic or group of characteristics that are
responsible for the signal and to classify the magnitude of the mean
shifts. The experimental results demonstrate that the support vector
machines (SVM) classifier can effectively identify the characteristic
or group of characteristics that caused the process mean shifts and the
magnitude of the shifts.
Abstract: The threshold voltage and capacitance voltage characteristics of ultra-thin Silicon-on-Insulator MOSFET are greatly influenced by the thickness and doping concentration of the silicon film. In this work, the capacitance voltage characteristics and threshold voltage of the device have been analyzed with quantum mechanical effects using the Self-Consistent model. Reduction of channel thickness and adding doping impurities cause an increase in the threshold voltage. Moreover, the temperature effects cause a significant amount of threshold voltage shift. The temperature dependence of threshold voltage has also been observed with Self- Consistent approach which are well supported from experimental performance of practical devices.
Abstract: Support Vector Machine (SVM) is a recent class of statistical classification and regression techniques playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM is applied to an infrared (IR) binary communication system with different types of channel models including Ricean multipath fading and partially developed scattering channel with additive white Gaussian noise (AWGN) at the receiver. The structure and performance of SVM in terms of the bit error rate (BER) metric is derived and simulated for these channel stochastic models and the computational complexity of the implementation, in terms of average computational time per bit, is also presented. The performance of SVM is then compared to classical binary signal maximum likelihood detection using a matched filter driven by On-Off keying (OOK) modulation. We found that the performance of SVM is superior to that of the traditional optimal detection schemes used in statistical communication, especially for very low signal-to-noise ratio (SNR) ranges. For large SNR, the performance of the SVM is similar to that of the classical detectors. The implication of these results is that SVM can prove very beneficial to IR communication systems that notoriously suffer from low SNR at the cost of increased computational complexity.
Abstract: In the context of sensor networks, where every few
dB saving counts, the novel node cooperation schemes are reviewed
where MIMO techniques play a leading role. These methods could be
treated as joint approach for designing physical layer of their
communication scenarios. Then we analyzed the BER performance
of transmission diversity schemes under a general fading channel
model and proposed a power allocation strategy to the transmitting
sensor nodes. This approach is then compared to an equal-power
assignment method and its performance enhancement is verified by
the simulation. Another key point of the contribution lies in the
combination of optimal power allocation and sensor nodes-
cooperation in a transmission diversity regime (MISO). Numerical
results are given through figures to demonstrate the optimality and
efficiency of proposed combined approach.
Abstract: SoftBoost is a recently presented boosting algorithm,
which trades off the size of achieved classification margin and
generalization performance. This paper presents a performance
evaluation of SoftBoost algorithm on the generic object recognition
problem. An appearance-based generic object recognition
model is used. The evaluation experiments are performed using
a difficult object recognition benchmark. An assessment with respect
to different degrees of label noise as well as a comparison to
the well known AdaBoost algorithm is performed. The obtained
results reveal that SoftBoost is encouraged to be used in cases
when the training data is known to have a high degree of noise.
Otherwise, using Adaboost can achieve better performance.
Abstract: This paper introduces a new variable step-size APA with decorrelation of AR input process is based on the MSD analysis. To achieve a fast convergence rate and a small steady-state estimation error, he proposed algorithm uses variable step size that is determined by minimising the MSD. In addition, experimental results show that the proposed algorithm is achieved better performance than the other algorithms.
Abstract: This paper presents a formant-tracking linear prediction
(FTLP) model for speech processing in noise. The main focus of this
work is the detection of formant trajectory based on Hidden Markov
Models (HMM), for improved formant estimation in noise. The
approach proposed in this paper provides a systematic framework for
modelling and utilization of a time- sequence of peaks which satisfies
continuity constraints on parameter; the within peaks are modelled
by the LP parameters. The formant tracking LP model estimation
is composed of three stages: (1) a pre-cleaning multi-band spectral
subtraction stage to reduce the effect of residue noise on formants
(2) estimation stage where an initial estimate of the LP model of
speech for each frame is obtained (3) a formant classification using
probability models of formants and Viterbi-decoders. The evaluation
results for the estimation of the formant tracking LP model tested
in Gaussian white noise background, demonstrate that the proposed
combination of the initial noise reduction stage with formant tracking
and LPC variable order analysis, results in a significant reduction in
errors and distortions. The performance was evaluated with noisy
natual vowels extracted from international french and English vocabulary
speech signals at SNR value of 10dB. In each case, the
estimated formants are compared to reference formants.
Abstract: This paper investigates the issue of building decision
trees from data with imprecise class values where imprecision is
encoded in the form of possibility distributions. The Information
Affinity similarity measure is introduced into the well-known gain
ratio criterion in order to assess the homogeneity of a set of
possibility distributions representing instances-s classes belonging to
a given training partition. For the experimental study, we proposed an
information affinity based performance criterion which we have used
in order to show the performance of the approach on well-known
benchmarks.
Abstract: This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.
Abstract: The aim of this study is to compare the effect of the ultrasonic pre treatment on the removal of heavy metals (Iron, Zinc and Copper) from Acid Mine Drainage (AMD) by Denver Cell flotation. Synthetic AMD and individual metal solutions are used in the initial experiments to optimise the process conditions for real AMD. Three different process methods, ultrasound treatment followed by Denver flotation cell, Denver flotation cell alone and ultrasonic treatments run simultaneously with the Denver flotation cell were tested for every sample. Precipitation of the metal solutions by using sodium hydroxide (NaOH) and application of the optimum frother dosage followed by flotation significantly reduced the metal content of the AMD.
Abstract: Mobile IPv6 (MIPv6) describes how mobile node can change its point of attachment from one access router to another. As a demand for wireless mobile devices increases, many enhancements for macro-mobility (inter-domain) protocols have been proposed, designed and implemented in Mobile IPv6. Hierarchical Mobile IPv6 (HMIPv6) is one of them that is designed to reduce the amount of signaling required and to improve handover speed for mobile connections. This is achieved by introducing a new network entity called Mobility Anchor Point (MAP). This report presents a comparative study of the Hierarchical Mobility IPv6 and Mobile IPv6 protocols and we have narrowed down the scope to micro-mobility (intra-domain). The architecture and operation of each protocol is studied and they are evaluated based on the Quality of Service (QoS) parameter; handover latency. The simulation was carried out by using the Network Simulator-2. The outcome from this simulation has been discussed. From the results, it shows that, HMIPv6 performs best under intra-domain mobility compared to MIPv6. The MIPv6 suffers large handover latency. As enhancement we proposed to HMIPv6 to locate the MAP to be in the middle of the domain with respect to all Access Routers. That gives approximately same distance between MAP and Mobile Node (MN) regardless of the new location of MN, and possible shorter distance. This will reduce the delay since the distance is shorter. As a future work performance analysis is to be carried for the proposed HMIPv6 and compared to HMIPv6.
Abstract: The dramatic increasing of sea-freight container
transportations and the developing trends for using containers in the
multimodal handling systems through the sea, rail, road and land in
nowadays market cause general managers of container terminals to
face challenges such as increasing demand, competitive situation,
new investments and expansion of new activities and need to use new
methods to fulfil effective operations both along quayside and within
the yard. Among these issues, minimizing the turnaround time of
vessels is considered to be the first aim of every container port
system. Regarding the complex structure of container ports, this
paper presents a simulation model that calculates the number of
trucks needed in the Iranian Shahid Rajaee Container Port for
handling containers between the berth and the yard. In this research,
some important criteria such as vessel turnaround time, gantry crane
utilization and truck utilization have been considered. By analyzing
the results of the model, it has been shown that increasing the number
of trucks to 66 units has a significant effect on the performance
indices of the port and can increase the capacity of loading and
unloading up to 10.8%.
Abstract: In this paper multivariable predictive PID controller has
been implemented on a multi-inputs multi-outputs control problem
i.e., quadruple tank system, in comparison with a simple multiloop
PI controller. One of the salient feature of this system is an
adjustable transmission zero which can be adjust to operate in both
minimum and non-minimum phase configuration, through the flow
distribution to upper and lower tanks in quadruple tank system.
Stability and performance analysis has also been carried out for this
highly interactive two input two output system, both in minimum
and non-minimum phases. Simulations of control system revealed
that better performance are obtained in predictive PID design.
Abstract: In current common research reports, salient regions
are usually defined as those regions that could present the main
meaningful or semantic contents. However, there are no uniform
saliency metrics that could describe the saliency of implicit image
regions. Most common metrics take those regions as salient regions,
which have many abrupt changes or some unpredictable
characteristics. But, this metric will fail to detect those salient useful
regions with flat textures. In fact, according to human semantic
perceptions, color and texture distinctions are the main characteristics
that could distinct different regions. Thus, we present a novel saliency
metric coupled with color and texture features, and its corresponding
salient region extraction methods. In order to evaluate the
corresponding saliency values of implicit regions in one image, three
main colors and multi-resolution Gabor features are respectively used
for color and texture features. For each region, its saliency value is
actually to evaluate the total sum of its Euclidean distances for other
regions in the color and texture spaces. A special synthesized image
and several practical images with main salient regions are used to
evaluate the performance of the proposed saliency metric and other
several common metrics, i.e., scale saliency, wavelet transform
modulus maxima point density, and important index based metrics.
Experiment results verified that the proposed saliency metric could
achieve more robust performance than those common saliency
metrics.