Abstract: Most CT reconstruction system x-ray computed
tomography (CT) is a well established visualization technique in
medicine and nondestructive testing. However, since CT scanning
requires sampling of radiographic projections from different viewing
angles, common CT systems with mechanically moving parts are too
slow for dynamic imaging, for instance of multiphase flows or live
animals. A large number of X-ray projections are needed to
reconstruct CT images, so the collection and calculation of the
projection data consume too much time and harmful for patient. For
the purpose of solving the problem, in this study, we proposed a
method for tomographic reconstruction of a sample from a limited
number of x-ray projections by using linear interpolation method. In
simulation, we presented reconstruction from an experimental x-ray
CT scan of a Aluminum phantom that follows to two steps: X-ray
projections will be interpolated using linear interpolation method and
using it for CT reconstruction based upon Ordered Subsets
Expectation Maximization (OSEM) method.
Abstract: This paper presents a complete procedure for tool path
planning and blade machining in 5-axis manufacturing. The actual
cutting contact and cutter locations can be determined by lead and tilt
angles. The tool path generation is implemented by piecewise curved
approximation and chordal deviation detection. An application about
drive surface method promotes flexibility of tool control and stability
of machine motion. A real manufacturing process is proposed to
separate the operation into three regions with five stages and to modify
the local tool orientation with an interactive algorithm.
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: Delivering course material via a virtual environment
is beneficial to today-s students because it offers the interactivity,
real-time interaction and social presence that students of all ages
have come to accept in our gaming rich community. It is essential
that the Net Generation also known as Generation Why, have
exposure to learning communities that encompass interactivity to
form social and educational connections. As student and professor
become interconnected through collaboration and interaction in a
virtual learning space, relationships develop and students begin to
take on an individual identity. With this in mind the research project
was developed to investigate the use of virtual environments on
student satisfaction and the effectiveness of course delivery.
Furthermore, the project was designed to integrate both interactive
(real-time) classes conducted in the Virtual Reality (VR)
environment while also creating archived VR sessions for student use
in retaining and reviewing course content.
Abstract: The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others.
Abstract: Prime Factorization based on Quantum approach in
two phases has been performed. The first phase has been achieved at
Quantum computer and the second phase has been achieved at the
classic computer (Post Processing). At the second phase the goal is to
estimate the period r of equation xrN ≡ 1 and to find the prime factors
of the composite integer N in classic computer. In this paper we
present a method based on Randomized Approach for estimation the
period r with a satisfactory probability and the composite integer N
will be factorized therefore with the Randomized Approach even the
gesture of the period is not exactly the real period at least we can find
one of the prime factors of composite N. Finally we present some
important points for designing an Emulator for Quantum Computer
Simulation.
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: Sharing motivations of viral advertisements by
consumers and the impacts of these advertisements on the
perceptions for brand will be questioned in this study. Three
fundamental questions are answered in the study. These are
advertisement watching and sharing motivations of individuals,
criteria of liking viral advertisement and the impact of individual
attitudes for viral advertisement on brand perception respectively.
This study will be carried out via a viral advertisement which was
practiced in Turkey. The data will be collected by survey method and
the sample of the study consists of individuals who experienced the
practice of sample advertisement. Data will be collected by online
survey method and will be analyzed by using SPSS statistical
package program.
Recently traditional advertisement mind have been changing. New
advertising approaches which have significant impacts on consumers
have been argued. Viral advertising is a modernist advertisement
mind which offers significant advantages to brands apart from
traditional advertising channels such as television, radio and
magazines. Viral advertising also known as Electronic Word-of-
Mouth (eWOM) consists of free spread of convincing messages sent
by brands among interpersonal communication. When compared to
the traditional advertising, a more provocative thematic approach is
argued.
The foundation of this approach is to create advertisements that
are worth sharing with others by consumers. When that fact is taken
into consideration, in a manner of speaking it can also be stated that
viral advertising is media engineering.
The content worth sharing makes people being a volunteer
spokesman of a brand and strengthens the emotional bonds among
brand and consumer. Especially for some sectors in countries which
are having traditional advertising channel limitations, viral
advertising creates vital advantages.
Abstract: This paper aims to present the main instruments used
in the economic literature for measuring the price risk, pointing out
on the advantages brought by the conditional variance in this respect.
The theoretical approach will be exemplified by elaborating an
EGARCH model for the price returns of wheat, both on Romanian
and on international market. To our knowledge, no previous
empirical research, either on price risk measurement for the
Romanian markets or studies that use the ARIMA-EGARCH
methodology, have been conducted. After estimating the
corresponding models, the paper will compare the estimated
conditional variance on the two markets.
Abstract: This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.
Abstract: Our study proposes an alternative method in building
Fuzzy Rule-Based System (FRB) from Support Vector Machine
(SVM). The first set of fuzzy IF-THEN rules is obtained through
an equivalence of the SVM decision network and the zero-ordered
Sugeno FRB type of the Adaptive Network Fuzzy Inference System
(ANFIS). The second set of rules is generated by combining the
first set based on strength of firing signals of support vectors using
Gaussian kernel. The final set of rules is then obtained from the
second set through input scatter partitioning. A distinctive advantage
of our method is the guarantee that the number of final fuzzy IFTHEN
rules is not more than the number of support vectors in the
trained SVM. The final FRB system obtained is capable of performing
classification with results comparable to its SVM counterpart, but it
has an advantage over the black-boxed SVM in that it may reveal
human comprehensible patterns.
Abstract: Ontology Matching is a task needed in various applica-tions, for example for comparison or merging purposes. In literature,many algorithms solving the matching problem can be found, butmost of them do not consider instances at all. Mappings are deter-mined by calculating the string-similarity of labels, by recognizinglinguistic word relations (synonyms, subsumptions etc.) or by ana-lyzing the (graph) structure. Due to the facts that instances are oftenmodeled within the ontology and that the set of instances describesthe meaning of the concepts better than their meta information,instances should definitely be incorporated into the matching process.In this paper several novel instance-based matching algorithms arepresented which enhance the quality of matching results obtainedwith common concept-based methods. Different kinds of formalismsare use to classify concepts on account of their instances and finallyto compare the concepts directly.KeywordsInstances, Ontology Matching, Semantic Web
Abstract: This research deals with a flexible flowshop
scheduling problem with arrival and delivery of jobs in groups and
processing them individually. Due to the special characteristics of
each job, only a subset of machines in each stage is eligible to
process that job. The objective function deals with minimization of
sum of the completion time of groups on one hand and minimization
of sum of the differences between completion time of jobs and
delivery time of the group containing that job (waiting period) on the
other hand. The problem can be stated as FFc / rj , Mj / irreg which
has many applications in production and service industries. A
mathematical model is proposed, the problem is proved to be NPcomplete,
and an effective heuristic method is presented to schedule
the jobs efficiently. This algorithm can then be used within the body
of any metaheuristic algorithm for solving the problem.
Abstract: Thanks to the interdisciplinary nature of crises, the
position of researchers in that field is rather difficult. Very often the
traditional methods of research cannot be applied there. The article is
aimed at the changes in crises research. It describes the substance of
individual changes and emphasizes the shift in research approaches
to the crisis.
Abstract: Scheduling of diversified service requests in
distributed computing is a critical design issue. Cloud is a type of
parallel and distributed system consisting of a collection of
interconnected and virtual computers. It is not only the clusters and
grid but also it comprises of next generation data centers. The paper
proposes an initial heuristic algorithm to apply modified ant colony
optimization approach for the diversified service allocation and
scheduling mechanism in cloud paradigm. The proposed optimization
method is aimed to minimize the scheduling throughput to service all
the diversified requests according to the different resource allocator
available under cloud computing environment.
Abstract: Bagging and boosting are among the most popular resampling ensemble methods that generate and combine a diversity of classifiers using the same learning algorithm for the base-classifiers. Boosting algorithms are considered stronger than bagging on noisefree data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using a voting methodology of bagging and boosting ensembles with 10 subclassifiers in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-classifiers, as well as other well known combining methods, on standard benchmark datasets and the proposed technique was the most accurate.
Abstract: This paper simulates the ad-hoc mesh network in rural areas, where such networks receive great attention due to their cost, since installing the infrastructure for regular networks in these areas is not possible due to the high cost. The distance between the communicating nodes is the most obstacles that the ad-hoc mesh network will face. For example, in Terranet technology, two nodes can communicate if they are only one kilometer far from each other. However, if the distance between them is more than one kilometer, then each node in the ad-hoc mesh networks has to act as a router that forwards the data it receives to other nodes. In this paper, we try to find the critical number of nodes which makes the network fully connected in a particular area, and then propose a method to enhance the intermediate node to accept to be a router to forward the data from the sender to the receiver. Much work was done on technological changes on peer to peer networks, but the focus of this paper will be on another feature which is to find the minimum number of nodes needed for a particular area to be fully connected and then to enhance the users to switch on their phones and accept to work as a router for other nodes. Our method raises the successful calls to 81.5% out of 100% attempt calls.
Abstract: The element of justice or al-‘adl in the context of
Islamic critical thinking deals with the notion of justice in a thinking
process which critically rationalizes the truth in a fair and objective
manner with no irrelevant interference that can jeopardize a sound
judgment. This Islamic axiological element is vital in technological
decision making as it addresses the issues of religious values and
ethics that are primarily set to fulfill the purpose of human life on
earth. The main objective of this study was to examine and analyze
the perception of Muslim engineering students in Malaysian higher
education institutions towards the concept of al-‘adl as an essential
element of Islamic critical thinking. The study employed mixed
methods approach that comprises data collection from the
questionnaire survey and the interview responses. A total of 557
Muslim engineering undergraduates from six Malaysian universities
participated in the study. The study generally indicated that Muslim
engineering undergraduates in the higher institutions have rather
good comprehension and consciousness for al-‘adl with a slight
awareness on the importance of objective thinking. Nonetheless there
were a few items on the concept that have implied a comparatively
low perception on the rational justice in Islam as the means to grasp
the ultimate truth.
Abstract: In this paper, a simple active contour based visual
tracking algorithm is presented for outdoor AGV application which is
currently under development at the USM robotic research group
(URRG) lab. The presented algorithm is computationally low cost
and able to track road boundaries in an image sequence and can
easily be implemented on available low cost hardware. The proposed
algorithm used an active shape modeling using the B-spline
deformable template and recursive curve fitting method to track the
current orientation of the road.
Abstract: In very narrow pathways, the speed of sound propagation and the phase of sound waves change due to the air viscosity. We have developed a new finite element method (FEM) that includes the effects of air viscosity for modeling a narrow sound pathway. This method is developed as an extension of the existing FEM for porous sound-absorbing materials. The numerical calculation results for several three-dimensional slit models using the proposed FEM are validated against existing calculation methods.