Abstract: The segmentation of endovascular tools in fluoroscopy images can be accurately performed automatically or by minimum user intervention, using known modern techniques. It has been proven in literature, but no clinical implementation exists so far because the computational time requirements of such technology have not yet been met. A classical segmentation scheme is composed of edge enhancement filtering, line detection, and segmentation. A new method is presented that consists of a vector that propagates in the image to track an edge as it advances. The filtering is performed progressively in the projected path of the vector, whose orientation allows for oriented edge detection, and a minimal image area is globally filtered. Such an algorithm is rapidly computed and can be implemented in real-time applications. It was tested on medical fluoroscopy images from an endovascular cerebral intervention. Ex- periments showed that the 2D tracking was limited to guidewires without intersection crosspoints, while the 3D implementation was able to cope with such planar difficulties.
Abstract: Laboratory activities have produced benefits in
student learning. With current drives of new technology resources
and evolving era of education methods, renewal status of learning
and teaching in laboratory methods are in progress, for both learners
and the educators. To enhance learning outcomes in laboratory works
particularly in engineering practices and testing, learning via handson
by instruction may not sufficient. This paper describes and
compares techniques and implementation of traditional (expository)
with open-ended laboratory (problem-based) for two consecutive
cohorts studying environmental laboratory course in civil engineering
program. The transition of traditional to problem-based findings and
effect were investigated in terms of course assessment student
feedback survey, course outcome learning measurement and student
performance grades. It was proved that students have demonstrated
better performance in their grades and 12% increase in the course
outcome (CO) in problem-based open-ended laboratory style than
traditional method; although in perception, students has responded
less favorable in their feedback.
Abstract: This paper offers a case study, in which
methodological aspects of cell design for transformation the
production process are applied. The cell redesign in this work is
tightly focused to reach optimization of material flows under real
manufacturing conditions. Accordingly, more individual techniques
were aggregated into compact methodical procedure with aim to built
one-piece flow production. Case study was concentrated on relatively
typical situation of transformation from batch production to cellular
manufacturing.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: In-core memory requirement is a bottleneck in solving
large three dimensional Navier-Stokes finite element problem
formulations using sparse direct solvers. Out-of-core solution
strategy is a viable alternative to reduce the in-core memory
requirements while solving large scale problems. This study
evaluates the performance of various out-of-core sequential solvers
based on multifrontal or supernodal techniques in the context of
finite element formulations for three dimensional problems on a
Windows platform. Here three different solvers, HSL_MA78,
MUMPS and PARDISO are compared. The performance of these
solvers is evaluated on a 64-bit machine with 16GB RAM for finite
element formulation of flow through a rectangular channel. It is
observed that using out-of-core PARDISO solver, relatively large
problems can be solved. The implementation of Newton and
modified Newton's iteration is also discussed.
Abstract: Nowadays, engineering ceramics have significant
applications in different industries such as; automotive, aerospace,
electrical, electronics and even martial industries due to their
attractive physical and mechanical properties like very high hardness
and strength at elevated temperatures, chemical stability, low friction
and high wear resistance. However, these interesting properties plus
low heat conductivity make their machining processes too hard,
costly and time consuming. Many attempts have been made in order
to make the grinding process of engineering ceramics easier and
many scientists have tried to find proper techniques to economize
ceramics' machining processes. This paper proposes a new diamond
plunge grinding technique using ultrasonic vibration for grinding
Alumina ceramic (Al2O3). For this purpose, a set of laboratory
equipments have been designed and simulated using Finite Element
Method (FEM) and constructed in order to be used in various
measurements. The results obtained have been compared with the
conventional plunge grinding process without ultrasonic vibration
and indicated that the surface roughness and fracture strength
improved and the grinding forces decreased.
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: In this paper a new approach to face recognition is
presented that achieves double dimension reduction, making the
system computationally efficient with better recognition results and
out perform common DCT technique of face recognition. In pattern
recognition techniques, discriminative information of image
increases with increase in resolution to a certain extent, consequently
face recognition results change with change in face image resolution
and provide optimal results when arriving at a certain resolution
level. In the proposed model of face recognition, initially image
decimation algorithm is applied on face image for dimension
reduction to a certain resolution level which provides best
recognition results. Due to increased computational speed and feature
extraction potential of Discrete Cosine Transform (DCT), it is
applied on face image. A subset of coefficients of DCT from low to
mid frequencies that represent the face adequately and provides best
recognition results is retained. A tradeoff between decimation factor,
number of DCT coefficients retained and recognition rate with
minimum computation is obtained. Preprocessing of the image is
carried out to increase its robustness against variations in poses and
illumination level. This new model has been tested on different
databases which include ORL , Yale and EME color database.
Abstract: The bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.
Abstract: The evaluation of residual reliability of large sized
parallel computer interconnection systems is not practicable with
the existing methods. Under such conditions, one must go for
approximation techniques which provide the upper bound and lower
bound on this reliability. In this context, a new approximation method
for providing bounds on residual reliability is proposed here. The
proposed method is well supported by two algorithms for simulation
purpose. The bounds on residual reliability of three different categories
of interconnection topologies are efficiently found by using
the proposed method
Abstract: Given the motivation of maps impact in enhancing the
perception of the quality of life in a region, this work examines the
use of spatial analytical techniques in exploring the role of space in
shaping human development patterns in Assiut governorate.
Variations of human development index (HDI) of the governorate-s
villages, districts and cities are mapped using geographic information
systems (GIS). Global and local spatial autocorrelation measures are
employed to assess the levels of spatial dependency in the data and to
map clusters of human development. Results show prominent
disparities in HDI between regions of Assiut. Strong patterns of
spatial association were found proving the presence of clusters on the
distribution of HDI. Finally, the study indicates several "hot-spots" in
the governorate to be area of more investigations to explore the
attributes of such levels of human development. This is very
important for accomplishing the development plan of poorest regions
currently adopted in Egypt.
Abstract: This paper proposes a “soft systems" approach to
domain-driven design of computer-based information systems. We
propose a systemic framework combining techniques from Soft
Systems Methodology (SSM), the Unified Modelling Language
(UML), and an implementation pattern known as “Naked Objects".
We have used this framework in action research projects that have
involved the investigation and modelling of business processes using
object-oriented domain models and the implementation of software
systems based on those domain models. Within the proposed
framework, Soft Systems Methodology (SSM) is used as a guiding
methodology to explore the problem situation and to generate a
ubiquitous language (soft language) which can be used as the basis
for developing an object-oriented domain model. The domain model
is further developed using techniques based on the UML and is
implemented in software following the “Naked Objects"
implementation pattern. We argue that there are advantages from
combining and using techniques from different methodologies in this
way.
The proposed systemic framework is overviewed and justified as
multimethodologyusing Mingers multimethodology ideas.
This multimethodology approach is being evaluated through a
series of action research projects based on real-world case studies. A
Peer-Tutoring case study is presented here as a sample of the
framework evaluation process
Abstract: Silver nano-particles have been used for antibacterial
purpose and it is also believed to have removal of odorous compounds,
oxidation capacity as a metal catalyst. In this study, silver
nano-particles in nano sizes (5-30 nm) were prepared on the surface of
NaHCO3, the supporting material, using a sputtering method that
provided high silver content and minimized conglomerating problems
observed in the common AgNO3 photo-deposition method. The silver
nano-particles were dispersed by dissolving Ag-NaHCO3 into water,
and the dispersed silver nano-particles in the aqueous phase were
applied to remove inorganic odor compounds, H2S, in a scrubbing
reactor. Hydrogen sulfide in the gas phase was rapidly removed by the
silver nano-particles, and the concentration of sulfate (SO4
2-) ion
increased with time due to the oxidation reaction by silver as a
catalyst. Consequently, the experimental results demonstrated that the
silver nano-particles in the aqueous solution can be successfully
applied to remove odorous compounds without adding additional
energy sources and producing any harmful byproducts
Abstract: In image processing and visualization, comparing two
bitmapped images needs to be compared from their pixels by matching
pixel-by-pixel. Consequently, it takes a lot of computational time
while the comparison of two vector-based images is significantly
faster. Sometimes these raster graphics images can be approximately
converted into the vector-based images by various techniques. After
conversion, the problem of comparing two raster graphics images
can be reduced to the problem of comparing vector graphics images.
Hence, the problem of comparing pixel-by-pixel can be reduced to
the problem of polynomial comparisons. In computer aided geometric
design (CAGD), the vector graphics images are the composition of
curves and surfaces. Curves are defined by a sequence of control
points and their polynomials. In this paper, the control points will be
considerably used to compare curves. The same curves after relocated
or rotated are treated to be equivalent while two curves after different
scaled are considered to be similar curves. This paper proposed an
algorithm for comparing the polynomial curves by using the control
points for equivalence and similarity. In addition, the geometric
object-oriented database used to keep the curve information has also
been defined in XML format for further used in curve comparisons.
Abstract: The transformation of vocal characteristics aims at
modifying voice such that the intelligibility of aphonic voice is
increased or the voice characteristics of a speaker (source speaker) to
be perceived as if another speaker (target speaker) had uttered it. In
this paper, the current state-of-the-art voice characteristics
transformation methodology is reviewed. Special emphasis is placed
on voice transformation methodology and issues for improving the
transformed speech quality in intelligibility and naturalness are
discussed. In particular, it is suggested to use the modulation theory
of speech as a base for research on high quality voice transformation.
This approach allows one to separate linguistic, expressive, organic
and perspective information of speech, based on an analysis of how
they are fused when speech is produced. Therefore, this theory
provides the fundamentals not only for manipulating non-linguistic,
extra-/paralinguistic and intra-linguistic variables for voice
transformation, but also for paving the way for easily transposing the
existing voice transformation methods to emotion-related voice
quality transformation and speaking style transformation. From the
perspectives of human speech production and perception, the popular
voice transformation techniques are described and classified them
based on the underlying principles either from the speech production
or perception mechanisms or from both. In addition, the advantages
and limitations of voice transformation techniques and the
experimental manipulation of vocal cues are discussed through
examples from past and present research. Finally, a conclusion and
road map are pointed out for more natural voice transformation
algorithms in the future.
Abstract: In this paper, we present a new and effective image indexing technique that extracts features directly from DCT domain. Our proposed approach is an object-based image indexing. For each block of size 8*8 in DCT domain a feature vector is extracted. Then, feature vectors of all blocks of image using a k-means algorithm is clustered into groups. Each cluster represents a special object of the image. Then we select some clusters that have largest members after clustering. The centroids of the selected clusters are taken as image feature vectors and indexed into the database. Also, we propose an approach for using of proposed image indexing method in automatic image classification. Experimental results on a database of 800 images from 8 semantic groups in automatic image classification are reported.
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: This paper presented a modified efficient inductive
powering link based on ASK modulator and proposed efficient class-
E power amplifier. The design presents the external part which is
located outside the body to transfer power and data to the implanted
devices such as implanted Microsystems to stimulate and monitoring
the nerves and muscles. The system operated with low band
frequency 10MHZ according to industrial- scientific – medical (ISM)
band to avoid the tissue heating. For external part, the modulation
index is 11.1% and the modulation rate 7.2% with data rate 1 Mbit/s
assuming Tbit = 1us. The system has been designed using 0.35-μm
fabricated CMOS technology. The mathematical model is given and
the design is simulated using OrCAD P Spice 16.2 software tool and
for real-time simulation, the electronic workbench MULISIM 11 has
been used.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.