Abstract: This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Abstract: Cutting fluids, usually in the form of a liquid, are
applied to the chip formation zone in order to improve the cutting
conditions. Cutting fluid can be expensive and represents a biological
and environmental hazard that requires proper recycling and
disposal, thus adding to the cost of the machining operation. For
these reasons dry cutting or dry machining has become an
increasingly important approach; in dry machining no coolant or
lubricant is used. This paper discussed the effect of the dry cutting on
cutting force and tool life when machining aerospace materials
(Haynes 242) with using two different coated carbide cutting tools
(TiAlN and TiN/MT-TiCN/TiN). Response surface method (RSM)
was used to minimize the number of experiments. ParTiAlN Swarm
Optimisation (PSO) models were developed to optimize the
machining parameters (cutting speed, federate and axial depth) and
obtain the optimum cutting force and tool life. It observed that
carbide cutting tool coated with TiAlN performed better in dry
cutting compared with TiN/MT-TiCN/TiN. On other hand, TiAlN
performed more superior with using of 100 % water soluble coolant.
Due to the high temperature produced by aerospace materials, the
cutting tool still required lubricant to sustain the heat transfer from
the workpiece.
Abstract: Rutting is one of the major load-related distresses in airport flexible pavements. Rutting in paving materials develop gradually with an increasing number of load applications, usually appearing as longitudinal depressions in the wheel paths and it may be accompanied by small upheavals to the sides. Significant research has been conducted to determine the factors which affect rutting and how they can be controlled. Using the experimental design concepts, a series of tests can be conducted while varying levels of different parameters, which could be the cause for rutting in airport flexible pavements. If proper experimental design is done, the results obtained from these tests can give a better insight into the causes of rutting and the presence of interactions and synergisms among the system variables which have influence on rutting. Although traditionally, laboratory experiments are conducted in a controlled fashion to understand the statistical interaction of variables in such situations, this study is an attempt to identify the critical system variables influencing airport flexible pavement rut depth from a statistical DoE perspective using real field data from a full-scale test facility. The test results do strongly indicate that the response (rut depth) has too much noise in it and it would not allow determination of a good model. From a statistical DoE perspective, two major changes proposed for this experiment are: (1) actual replication of the tests is definitely required, (2) nuisance variables need to be identified and blocked properly. Further investigation is necessary to determine possible sources of noise in the experiment.
Abstract: The experiments were performed in a batch set up
under different concentrations of Cu (II) (0.2 g.l-1 to 0.9 g.l-1), pH (4-
6), temperatures (20oC – 40oC) with varying teak leaves powder (as
biosorbent) dosage of 0.3 g.l-1 to 0.5 g.l-1. The kinetics of interactions
were tested with pseudo first order Lagergran equation and the value
for k1 was found to be 6.909 x 10-3 min-1. The biosorption data gave
a good fit with Langmuir and Fruendlich isotherms and the Langmuir
monolayer capacity (qm) was found to be 166.78 mg. g-1. Similarly
the Freundlich adsorption capacity (Kf) was estimated as 2.49 l g-1.
The mean values of the thermodynamic parameters ΔH, ΔS, and ΔG
were -62.42 KJ. mol-1, -0.219 KJ.mol-1 K-1 and -1.747 KJ.mol-1 at
293 K from a solution containing 0.4 g l-1 of Cu(II) showing the
biosorption to be thermodynamically favourable. These results show
good potentiality of using teak leaves as a biosorbent for the removal
of Cu(II) from aqueous solutions.
Abstract: During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of Standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67HV from 21HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.
Abstract: This paper propose a new circuit design which
monitor total leakage current during standby mode and generates the
optimal reverse body bias voltage, by using the adaptive body bias
(ABB) technique to compensate die-to-die parameter variations.
Design details of power monitor are examined using simulation
framework in 65nm and 32nm BTPM model CMOS process.
Experimental results show the overhead of proposed circuit in terms
of its power consumption is about 10 μW for 32nm technology and
about 12 μW for 65nm technology at the same power supply voltage
as the core power supply. Moreover the results show that our
proposed circuit design is not far sensitive to the temperature
variations and also process variations. Besides, uses the simple
blocks which offer good sensitivity, high speed, the continuously
feedback loop.
Abstract: Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.
Abstract: Ambient hydrolysis products in moist air and
hydrolysis kinetics in argon with humidity of RH1.5% for
polycrystalline LiH powders and sintered bulks were investigated by
X-ray diffraction, Raman spectroscopy and gravimetry. The results
showed that the hydrolysis products made up a layered structure of
LiOH•H2O/LiOH/Li2O from surface of the sample to inside. In low
humid argon atmosphere, the primary hydrolysis product was Li2O
rather than LiOH. The hydrolysis kinetic curves of LiH bulks present a
paralinear shape, which could be explained by the “Layer Diffusion
Control" model. While a three-stage hydrolysis kinetic profile was
observed for LiH powders under the same experimental conditions.
The first two sections were similar to that of the bulk samples, and the
third section also presents a linear reaction kinetics but with a smaller
reaction rate compared to the second section because of a larger
exothermic effect for the hydrolysis reaction of LiH powder.
Abstract: Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: Face authentication for access control is a face
membership authentication which passes the person of the incoming
face if he turns out to be one of an enrolled person based on face
recognition or rejects if not. Face membership authentication belongs
to the two class classification problem where SVM(Support Vector
Machine) has been successfully applied and shows better performance
compared to the conventional threshold-based classification. However,
most of previous SVMs have been trained using image feature vectors
extracted from face images of each class member(enrolled
class/unenrolled class) so that they are not robust to variations in
illuminations, poses, and facial expressions and much affected by
changes in member configuration of the enrolled class
In this paper, we propose an effective face membership
authentication method based on SVM using class discriminating
features which represent an incoming face image-s associability with
each class distinctively. These class discriminating features are weakly
related with image features so that they are less affected by variations
in illuminations, poses and facial expression.
Through experiments, it is shown that the proposed face
membership authentication method performs better than the threshold
rule-based or the conventional SVM-based authentication methods and
is relatively less affected by changes in member size and membership.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade
Abstract: This paper presents a methodical approach for designing and optimizing process parameters in oil blending industries. Twenty seven replicated experiments were conducted for production of A-Z crown super oil (SAE20W/50) employing L9 orthogonal array to establish process response parameters. Power law model was fitted to experimental data and the obtained model was optimized applying the central composite design (CCD) of response surface methodology (RSM). Quadratic model was found to be significant for production of A-Z crown supper oil. The study recognized and specified four new lubricant formulations that conform to ISO oil standard in the course of analyzing the batch productions of A-Z crown supper oil as: L1: KV = 21.8293Cst, BS200 = 9430.00Litres, Ad102=11024.00Litres, PVI = 2520 Litres, L2: KV = 22.513Cst, BS200 = 12430.00 Litres, Ad102 = 11024.00 Litres, PVI = 2520 Litres, L3: KV = 22.1671Cst, BS200 = 9430.00 Litres, Ad102 = 10481.00 Litres, PVI= 2520 Litres, L4: KV = 22.8605Cst, BS200 = 12430.00 Litres, Ad102 = 10481.00 Litres, PVI = 2520 Litres. The analysis of variance showed that quadratic model is significant for kinematic viscosity production while the R-sq value statistic of 0.99936 showed that the variation of kinematic viscosity is due to its relationship with the control factors. This study therefore resulted to appropriate blending proportions of lubricants base oil and additives and recommends the optimal kinematic viscosity of A-Z crown super oil (SAE20W/50) to be 22.86Cst.
Abstract: Investigation of sandy clay behavior is important since
urban development demands mean that sandy clay areas are
increasingly encountered, especially for transportation
infrastructures. This paper presents the results of the finite element
analysis of the direct shear test (under three vertical loading 44, 96
and 192 kPa) and discusses the effects of different parameters such as
cohesion, friction angle and Young's modulus on the shear strength of
sandy clay. The numerical model was calibrated against the
experimental results of large-scale direct shear tests. The results have
shown that the shear strength was increased with increase in friction
angle and cohesion. However, the shear strength was not influenced
by raising the friction angle at normal stress of 44 kPa. Also, the
effect of different young's modulus factors on stress-strain curve was
investigated.
Abstract: Numerical investigation of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann methods at different Reynolds numbers. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations, streamlines and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The Reynolds numbers affected the physical quantities.
Abstract: A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.
Abstract: Steady state experiments have been conducted for
natural and mixed convection heat transfer, from five different sized
protruding discrete heat sources, placed at the bottom position on a
PCB and mounted on a vertical channel. The characteristic length (
Lh ) of heat sources vary from 0.005 to 0.011 m. The study has been
done for different range of Reynolds number and modified Grashof
number. From the experiment, the surface temperature distribution
and the Nusselt number of discrete heat sources have been obtained
and the effects of Reynold number and Richardson number on them
have been discussed. The objective is to find the rate of heat
dissipation from heat sources, by placing them at the bottom position
on a PCB and to compare both modes of cooling of heat sources.
Abstract: Two completely different approaches for a Gigabit
Ethernet compliant stream transmission over 50m of 1mm PMMA SI-POF have been experimentally demonstrated and are compared in this paper. The first solution is based on a commercial RC-LED
transmission and a careful optimization of the physical layer architecture, realized during the POF-PLUS EU Project. The second solution exploits the performance of an edge-emitting laser at the
transmitter side in order to avoid any sort of electrical equalization at the receiver side.
Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.