Abstract: This paper deals with efficient computation of
probability coefficients which offers computational simplicity as
compared to spectral coefficients. It eliminates the need of inner
product evaluations in determination of signature of a combinational
circuit realizing given Boolean function. The method for computation
of probability coefficients using transform matrix, fast transform
method and using BDD is given. Theoretical relations for achievable
computational advantage in terms of required additions in computing
all 2n probability coefficients of n variable function have been
developed. It is shown that for n ≥ 5, only 50% additions are needed
to compute all probability coefficients as compared to spectral
coefficients. The fault detection techniques based on spectral
signature can be used with probability signature also to offer
computational advantage.
Abstract: In an era of knowledge explosion, the growth of data
increases rapidly day by day. Since data storage is a limited resource,
how to reduce the data space in the process becomes a challenge issue.
Data compression provides a good solution which can lower the
required space. Data mining has many useful applications in recent
years because it can help users discover interesting knowledge in large
databases. However, existing compression algorithms are not
appropriate for data mining. In [1, 2], two different approaches were
proposed to compress databases and then perform the data mining
process. However, they all lack the ability to decompress the data to
their original state and improve the data mining performance. In this
research a new approach called Mining Merged Transactions with the
Quantification Table (M2TQT) was proposed to solve these problems.
M2TQT uses the relationship of transactions to merge related
transactions and builds a quantification table to prune the candidate
itemsets which are impossible to become frequent in order to improve
the performance of mining association rules. The experiments show
that M2TQT performs better than existing approaches.
Abstract: We introduce, a new interactive 3D simulation system of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). The system is comprised of: (1) a physiologically accurate parameterized 3D model of the eyes, eyelids, and eyebrow regions; and (2) a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D eye simulation system, created using state-of-the-art computer animation technology and 'optimized' for use with an interactive and web deliverable platform, is, to our knowledge, the most advanced/realistic available so far for applications to character animation and medical pedagogy.
Abstract: In this paper we present a system for classifying videos
by frequency spectra. Many videos contain activities with repeating
movements. Sports videos, home improvement videos, or videos
showing mechanical motion are some example areas. Motion of these
areas usually repeats with a certain main frequency and several side
frequencies. Transforming repeating motion to its frequency domain
via FFT reveals these frequencies. Average amplitudes of frequency
intervals can be seen as features of cyclic motion. Hence determining
these features can help to classify videos with repeating movements.
In this paper we explain how to compute frequency spectra for video
clips and how to use them for classifying. Our approach utilizes series
of image moments as a function. This function again is transformed
into its frequency domain.
Abstract: Today, building automation is advancing from simple
monitoring and control tasks of lightning and heating towards more
and more complex applications that require a dynamic perception
and interpretation of different scenes occurring in a building. Current
approaches cannot handle these newly upcoming demands. In this
article, a bionically inspired approach for multimodal, dynamic scene
perception and interpretation is presented, which is based on neuroscientific
and neuro-psychological research findings about the perceptual
system of the human brain. This approach bases on data from diverse
sensory modalities being processed in a so-called neuro-symbolic
network. With its parallel structure and with its basic elements being
information processing and storing units at the same time, a very
efficient method for scene perception is provided overcoming the
problems and bottlenecks of classical dynamic scene interpretation
systems.
Abstract: One major difficulty that faces developers of
concurrent and distributed software is analysis for concurrency based
faults like deadlocks. Petri nets are used extensively in the
verification of correctness of concurrent programs. ECATNets [2] are
a category of algebraic Petri nets based on a sound combination of
algebraic abstract types and high-level Petri nets. ECATNets have
'sound' and 'complete' semantics because of their integration in
rewriting logic [12] and its programming language Maude [13].
Rewriting logic is considered as one of very powerful logics in terms
of description, verification and programming of concurrent systems.
We proposed in [4] a method for translating Ada-95 tasking
programs to ECATNets formalism (Ada-ECATNet). In this paper,
we show that ECATNets formalism provides a more compact
translation for Ada programs compared to the other approaches based
on simple Petri nets or Colored Petri nets (CPNs). Such translation
doesn-t reduce only the size of program, but reduces also the number
of program states. We show also, how this compact Ada-ECATNet
may be reduced again by applying reduction rules on it. This double
reduction of Ada-ECATNet permits a considerable minimization of
the memory space and run time of corresponding Maude program.
Abstract: As application of re-activation of backside on power
device Insulated Gate Bipolar Transistor (IGBT), laser annealing was
employed to irradiate amorphous silicon substrate, and resistivities
were measured using four point probe measurement. For annealing
the amorphous silicon two lasers were used at wavelength of visible
green (532 nm) together with Infrared (793 nm). While the green
laser efficiently increased temperature at top surface the Infrared
laser reached more deep inside and was effective for melting the
top surface. A finite element method was employed to evaluate time
dependent thermal distribution in silicon substrate.
Abstract: In this paper, we propose a novel algorithm for
delineating the endocardial wall from a human heart ultrasound scan.
We assume that the gray levels in the ultrasound images are
independent and identically distributed random variables with
different Rician Inverse Gaussian (RiIG) distributions. Both synthetic
and real clinical data will be used for testing the algorithm. Algorithm
performance will be evaluated using the expert radiologist evaluation
of a soft copy of an ultrasound scan during the scanning process and
secondly, doctor’s conclusion after going through a printed copy of
the same scan. Successful implementation of this algorithm should
make it possible to differentiate normal from abnormal soft tissue and
help disease identification, what stage the disease is in and how best
to treat the patient. We hope that an automated system that uses this
algorithm will be useful in public hospitals especially in Third World
countries where problems such as shortage of skilled radiologists and
shortage of ultrasound machines are common. These public hospitals
are usually the first and last stop for most patients in these countries.
Abstract: This paper presents a remote on-line diagnostic system
for vehicles via the use of On-Board Diagnostic (OBD), GPS, and 3G
techniques. The main parts of the proposed system are on-board
computer, vehicle monitor server, and vehicle status browser. First,
the on-board computer can obtain the location of deriver and vehicle
status from GPS receiver and OBD interface, respectively. Then
on-board computer will connect with the vehicle monitor server
through 3G network to transmit the real time vehicle system status.
Finally, vehicle status browser could show the remote vehicle status
including vehicle speed, engine rpm, battery voltage, engine coolant
temperature, and diagnostic trouble codes. According to the
experimental results, the proposed system can help fleet managers and
car knockers to understand the remote vehicle status. Therefore this
system can decrease the time of fleet management and vehicle repair
due to the fleet managers and car knockers who find the diagnostic
trouble messages in time.
Abstract: Wavelength multiplexing (WDM) technology along
with optical amplifiers is used for optical communication systems in
S-band, C-band and L-band. To improve the overall system
performance Hybrid amplifiers consisting of cascaded TDFA and
EDFA with different gain bandwidths are preferred for long haul
wavelength multiplexed optical communication systems. This paper
deals with statistical analysis of different configuration of hybrid
amplifier i.e. analysis of TDFA-EDFA configuration and EDFA –
TDFA configuration. In this paper One-Way ANOVA method is used
for statistical analysis.
Abstract: This paper analyzed the perception of e-commerce
application services by construction material traders in Malaysia.
Five attributes were tested: usability, reputation, trust, privacy and
familiarity. Study methodology consists of survey questionnaire and
statistical analysis that includes reliability analysis, factor analysis,
ANOVA and regression analysis. The respondents were construction
material traders, including hardware stores in Klang Valley, Kuala
Lumpur.
Findings support that usability and familiarity with e-commerce
services in Malaysia have insignificant influence on the acceptance of
e-commerce application. However, reputation, trust and privacy
attributes have significant influence on the choice of e-commerce
acceptance by construction material traders. E-commerce
applications studied included customer database, e-selling, emarketing,
e-payment, e-buying and online advertising. Assumptions
are made that traders have basic knowledge and exposure to ICT
services. i.e. internet service and computers. Study concludes that
reputation, privacy and trust are the three website attributes that
influence the acceptance of e-commerce by construction material
traders.
Abstract: Monitoring the tool flank wear without affecting the
throughput is considered as the prudent method in production
technology. The examination has to be done without affecting the
machining process. In this paper we proposed a novel work that is
used to determine tool flank wear by observing the sound signals
emitted during the turning process. The work-piece material we used
here is steel and aluminum and the cutting insert was carbide
material. Two different cutting speeds were used in this work. The
feed rate and the cutting depth were constant whereas the flank wear
was a variable. The emitted sound signal of a fresh tool (0 mm flank
wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely
worn tool (0.4mm and above flank wear) during turning process were
recorded separately using a high sensitive microphone. Analysis
using Singular Value Decomposition was done on these sound
signals to extract the feature sound components. Observation of the
results showed that an increase in tool flank wear correlates with an
increase in the values of SVD features produced out of the sound
signals for both the materials. Hence it can be concluded that wear
monitoring of tool flank during turning process using SVD features
with the Fuzzy C means classification on the emitted sound signal is
a potential and relatively simple method.
Abstract: Forecasting the values of the indicators, which
characterize the effectiveness of performance of organizations is of
great importance for their successful development. Such forecasting
is necessary in order to assess the current state and to foresee future
developments, so that measures to improve the organization-s
activity could be undertaken in time. The article presents an
overview of the applied mathematical and statistical methods for
developing forecasts. Special attention is paid to artificial neural
networks as a forecasting tool. Their strengths and weaknesses are
analyzed and a synopsis is made of the application of artificial neural
networks in the field of forecasting of the values of different
education efficiency indicators. A method of evaluation of the
activity of universities using the Balanced Scorecard is proposed and
Key Performance Indicators for assessment of e-learning are
selected. Resulting indicators for the evaluation of efficiency of the
activity are proposed. An artificial neural network is constructed and
applied in the forecasting of the values of indicators for e-learning
efficiency on the basis of the KPI values.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: In order to study the effect of plant density and
competition of wheat with field bindweed (Convolvulus arvensis) on
yield and agronomical properties of wheat(Triticum Sativum) in
irrigated conditions, a factorial experiment as the base of complete
randomize block design in three replication was conducted at the
field of Kamalvand in khoramabad (Lorestan) region of Iran during
2008-2009. Three plant density (Factor A=200, 230 and 260kg/ha)
three cultivar (Factor B=Bahar,Pishtaz and Alvand) and weed control
(Factor C= control and no control of weeds)were assigned in
experiment. Results show that: Plant density had significant effect
(statistically) on seed yield, 1000 seed weight, weed density and dry
weight of weeds, seed yield and harvest index had been meaningful
effect for cultivars. The interaction between plant density and
cultivars for weed density, seed yield, thousand seed weight and
harvest index were significant. 260 kg/ha (plant density) of wheat had
more effect on increasing of seed yield in Bahar cultivar wheat in
khoramabad region of Iran.
Abstract: There has been a strong link between computermediated education and constructivism learning and teaching theory.. Acknowledging how well the constructivism doctrine would work online, it has been established that constructivist views of learning would agreeably correlate with the philosophy of open and distance learning. Asynchronous and synchronous communications have placed online learning on the right track of a constructive learning path. This paper is written based on the social constructivist framework, where knowledge is constructed from social communication and interaction. The study explores the possibility of practicing this theory through incorporating online discussion in the syllabus and the ways it can be implemented to contribute to young people-s personality and social development by addressing some aspects that may contribute to the social problem such as prejudice, ignorance and intolerance.
Abstract: This paper demonstrates a model of an e-Learning
system based on nowadays learning theory and distant education
practice. The relationships in the model are designed to be simple
and functional and do not necessarily represent any particular e-
Learning environments. It is meant to be a generic e-Learning
system model with implications for any distant education course
instructional design. It allows online instructors to move away from
the discrepancy between the courses and body of knowledge. The
interrelationships of four primary sectors that are at the e-Learning
system are presented in this paper. This integrated model includes
[1] pedagogy, [2] technology, [3] teaching, and [4] learning. There
are interactions within each of these sectors depicted by system loop
map.
Abstract: Technology assessment is a vital part of decision process in manufacturing, particularly for decisions on selection of new sustainable manufacturing processes. To assess these processes, a matrix approach is introduced and sustainability assessment models are developed. Case studies show that the matrix-based approach provides a flexible and practical way for sustainability evaluation of new manufacturing technologies such as those used in surface coating. The technology assessment of coating processes reveals that compared with powder coating, the sol-gel coating can deliver better technical, economical and environmental sustainability with respect to the selected sustainability evaluation criteria for a decorative coating application of car wheels.
Abstract: Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.
Abstract: This paper shows how we can integrate
communication modeling into the design modeling at early stages of
the design flow. We consider effect of incorporating noise such as
impulsive noise on system stability. We show that with change of the
system model and investigate the system performance under the
different communication effects. We modeled a unmanned aerial
vehicle (UAV) as a demonstration using SystemC methodology.
Moreover the system is modeled by joining the capabilities of UML
and SystemC to operate at system level.