Abstract: Skin color can provide a useful and robust cue
for human-related image analysis, such as face detection,
pornographic image filtering, hand detection and tracking,
people retrieval in databases and Internet, etc. The major
problem of such kinds of skin color detection algorithms is
that it is time consuming and hence cannot be applied to a real
time system. To overcome this problem, we introduce a new
fast technique for skin detection which can be applied in a real
time system. In this technique, instead of testing each image
pixel to label it as skin or non-skin (as in classic techniques),
we skip a set of pixels. The reason of the skipping process is
the high probability that neighbors of the skin color pixels are
also skin pixels, especially in adult images and vise versa. The
proposed method can rapidly detect skin and non-skin color
pixels, which in turn dramatically reduce the CPU time
required for the protection process. Since many fast detection
techniques are based on image resizing, we apply our
proposed pixel skipping technique with image resizing to
obtain better results. The performance evaluation of the
proposed skipping and hybrid techniques in terms of the
measured CPU time is presented. Experimental results
demonstrate that the proposed methods achieve better result
than the relevant classic method.
Abstract: Due to adverse pressure gradient along the diverging
walls of wide-angled diffusers, the attached flow separates from
one wall and remains attached permanently to the other wall in a
process called stalling. Stalled diffusers render the whole fluid flow
system, in which they are part of, very inefficient. There is then an
engineering need to try to understand the whole process of diffuser
stall if any meaningful attempts to improve on diffuser efficiency
are to be made. In this regard, this paper provides a data bank
contribution for the mean flow-field in wide-angled diffusers where
the complete velocity and static pressure fields, and pressure recovery
data for diffusers in the fully stalled flow regime are experimentally
measured. The measurements were carried out at Reynolds numbers
between 1.07×105 and 2.14×105 based on inlet hydraulic diameter
and centreline velocity for diffusers whose divergence angles were
between 30Ôùª and 50Ôùª. Variation of Reynolds number did not significantly
affect the velocity and static pressure profiles. The wall static
pressure recovery was found to be more sensitive to changes in the
Reynolds number. By increasing the velocity from 10 m/s to 20 m/s,
the wall static pressure recovery increased by 8.31%. However, as the
divergence angle was increased, a similar increase in the Reynolds
number resulted in a higher percentage increase in pressure recovery.
Experimental results showed that regardless of the wall to which
the flow was attached, both the velocity and pressure fields were
replicated with discrepancies below 2%.
Abstract: The experimental results on combustion of rice husk
in a conical fluidized bed combustor (referred to as the conical FBC)
using silica sand as the bed material are presented in this paper. The
effects of excess combustion air and combustor loading as well as the
sand bed height on the combustion pattern in FBC were investigated.
Temperatures and gas concentrations (CO and NO) along over the
combustor height as well as in the flue gas downstream from the ash
collecting cyclone were measured. The results showed that the axial
temperature profiles in FBC were explicitly affected by the
combustor loading whereas the excess air and bed height were found
to have minor influences on the temperature pattern. Meanwhile, the
combustor loading and the excess air significantly affected the axial
CO and NO concentration profiles; however, these profiles were
almost independent of the bed height. The combustion and thermal
efficiencies for this FBC were quantified for different operating
conditions.
Abstract: Aggressive scaling of MOS devices requires use of ultra-thin gate oxides to maintain a reasonable short channel effect and to take the advantage of higher density, high speed, lower cost etc. Such thin oxides give rise to high electric fields, resulting in considerable gate tunneling current through gate oxide in nano regime. Consequently, accurate analysis of gate tunneling current is very important especially in context of low power application. In this paper, a simple and efficient analytical model has been developed for channel and source/drain overlap region gate tunneling current through ultra thin gate oxide n-channel MOSFET with inevitable deep submicron effect (DSME).The results obtained have been verified with simulated and reported experimental results for the purpose of validation. It is shown that the calculated tunnel current is well fitted to the measured one over the entire oxide thickness range. The proposed model is suitable enough to be used in circuit simulator due to its simplicity. It is observed that neglecting deep sub-micron effect may lead to large error in the calculated gate tunneling current. It is found that temperature has almost negligible effect on gate tunneling current. It is also reported that gate tunneling current reduces with the increase of gate oxide thickness. The impact of source/drain overlap length is also assessed on gate tunneling current.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: Internal combustion engines rejects 30-40% of the
energy supplied by fuel to the environment through exhaust gas. thus, there is a possibility for further significant improvement of efficiency with the utilization of exhaust gas energy and its conversion to mechanical energy or electrical energy. The Thermo-Electric
Generator (TEG) will be located in the exhaust system and will make use of an energy flow between the warmer exhaust gas and the external environment. Predict to th optimum position of temperature
distribution and the performance of TEG through numerical analysis.
The experimental results obtained show that the power output significantly increases with the temperature difference between cold
and hot sides of a thermoelectric generator.
Abstract: The aim of this study was to investigate the influence
of reaction temperature and wheat straw moisture content on the
pyrolysis product yields, in the temperature range of 475-575 °C.
Samples of straw with moisture contents from 1.5 wt % to 15.0 wt %
were fed to a bench scale Pyrolysis Centrifuge Reactor (PCR). The
experimental results show that the changes in straw moisture content
have no significant effect on the distribution of pyrolysis product
yields. The maximum bio-oil yields approximately 60 (wt %, on dry
ash free feedstock basis) was observed around 525 °C - 550 °C for all
straw moisture levels. The water content in the wet straw bio-oil was
the highest. The heating value of bio-oil and solid char were
measured and the percentages of its energy distribution were
calculated. The energy distributions of bio-oil, char and gas were 56-
69 % 24-33 %, and 2-19 %, respectively.
Abstract: One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.
Abstract: Today air-core coils (ACC) are a viable alternative to
ferrite-core coils in a range of applications due to their low induction
effect. An analytical study was carried out and the results were used as
a guide to understand the relationship between the magnet-coil
distance and the resulting attractive magnetic force. Four different
ACC models were fabricated for experimental study. The variation in
the models included the dimensions, the number of coil turns and the
current supply to the coil. Comparison between the analytical and
experimental results for all the models shows an average discrepancy
of less than 10%. An optimized ACC design was selected for the
scanner which can provide maximum magnetic force.
Abstract: Metal matrix composites (MMC) are generating
extensive interest in diverse fields like defense, aerospace, electronics
and automotive industries. In this present investigation, material
removal rate (MRR) modeling has been carried out using an
axisymmetric model of Al-SiC composite during electrical discharge
machining (EDM). A FEA model of single spark EDM was
developed to calculate the temperature distribution.Further, single
spark model was extended to simulate the second discharge. For
multi-discharge machining material removal was calculated by
calculating the number of pulses. Validation of model has been done
by comparing the experimental results obtained under the same
process parameters with the analytical results. A good agreement was
found between the experimental results and the theoretical value.
Abstract: This paper introduces a low cost INS/GPS algorithm for
land vehicle navigation application. The data fusion process is done
with an extended Kalman filter in cascade configuration mode. In
order to perform numerical simulations, MATLAB software has been
developed. Loosely coupled configuration is considered. The results
obtained in this work demonstrate that a low-cost INS/GPS navigation
system is partially capable of meeting the performance requirements
for land vehicle navigation. The relative effectiveness of the kalman
filter implementation in integrated GPS/INS navigation algorithm is
highlighted. The paper also provides experimental results; field test
using a car is carried out.
Abstract: This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.
Abstract: The motion of a sphere moving along the axis of a
rotating viscous fluid is studied at high Reynolds numbers and
moderate values of Taylor number. The Higher Order Compact
Scheme is used to solve the governing Navier-Stokes equations. The
equations are written in the form of Stream function, Vorticity
function and angular velocity which are highly non-linear, coupled
and elliptic partial differential equations. The flow is governed by
two parameters Reynolds number (Re) and Taylor number (T). For
very low values of Re and T, the results agree with the available
experimental and theoretical results in the literature. The results are
obtained at higher values of Re and moderate values of T and
compared with the experimental results. The results are fourth order
accurate.
Abstract: The carbon based coils with the nanometer scale have
the 3 dimension helix geometry. We synthesized the carbon nano-coils
by the use of chemical vapor deposition technique with iron and tin as
the catalysts. The fabricated coils have the external diameter of
ranging few hundred nm to few thousand nm. The Scanning
Electro-Microscope (SEM) and Tunneling Electro-Microscope has
shown detail images of the coil-s structure. The fabrication of the
carbon nano-coils can be grown on the metal and non-metal substrates,
such as the stainless steel and silicon substrates. Besides growth on the
flat substrate; they also can be grown on the stainless steel wires. After
the synthesis of the coils, the mechanical and electro-mechanical
property is measured. The experimental results were reported.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: Minimum Quantity Lubrication (MQL) technique
obtained a significant attention in machining processes to reduce
environmental loads caused by usage of conventional cutting fluids.
Recently nanofluids are finding an extensive application in the field
of mechanical engineering because of their superior lubrication and
heat dissipation characteristics. This paper investigates the use of a
nanofluid under MQL mode to improve grinding characteristics of
Ti-6Al-4V alloy. Taguchi-s experimental design technique has been
used in the present investigation and a second order model has been
established to predict grinding forces and surface roughness.
Different concentrations of water based Al2O3 nanofluids were
applied in the grinding operation through MQL setup developed in
house and the results have been compared with those of conventional
coolant and pure water. Experimental results showed that grinding
forces reduced significantly when nano cutting fluid was used even at
low concentration of the nano particles and surface finish has been
found to improve with higher concentration of the nano particles.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.
Abstract: Rule Discovery is an important technique for mining
knowledge from large databases. Use of objective measures for
discovering interesting rules leads to another data mining problem,
although of reduced complexity. Data mining researchers have
studied subjective measures of interestingness to reduce the volume
of discovered rules to ultimately improve the overall efficiency of
KDD process.
In this paper we study novelty of the discovered rules as a
subjective measure of interestingness. We propose a hybrid approach
based on both objective and subjective measures to quantify novelty
of the discovered rules in terms of their deviations from the known
rules (knowledge). We analyze the types of deviation that can arise
between two rules and categorize the discovered rules according to
the user specified threshold. We implement the proposed framework
and experiment with some public datasets. The experimental results
are promising.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.