Abstract: Model-checking tools such as Symbolic Model Verifier
(SMV) and NuSMV are available for checking hardware designs.
These tools can automatically check the formal legitimacy of a
design. However, NuSMV is too low level for describing a complete
hardware design. It is therefore necessary to translate the system
definition, as designed in a language such as Verilog or VHDL, into
a language such as NuSMV for validation. In this paper, we present
a meta hardware description language, Melasy, that contains a code
generator for existing hardware description languages (HDLs) and
languages for model checking that solve this problem.
Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: In this work the opportunity of construction of the
qualifiers for face-recognition systems based on conjugation criteria
is investigated. The linkage between the bipartite conjugation, the
conjugation with a subspace and the conjugation with the null-space
is shown. The unified solving rule is investigated. It makes the
decision on the rating of face to a class considering the linkage
between conjugation values. The described recognition method can
be successfully applied to the distributed systems of video control
and video observation.
Abstract: This paper describes the challenges on the requirements engineering for developing an enterprise applications in higher
education environment. The development activities include software implementation, maintenance, and enhancement and support for online
transaction processing and overnight batch processing.
Generally, an enterprise application for higher education environment
may include Student Information System (SIS), HR/Payroll system,
Financial Systems etc. By the way, there are so many challenges in
requirement engineering phases in order to provide two distinctive
services that are production processing support and systems
development.
Abstract: This article investigates a contribution of synthesized visual speech. Synthesis of visual speech expressed by a computer consists in an animation in particular movements of lips. Visual speech is also necessary part of the non-manual component of a sign language. Appropriate methodology is proposed to determine the quality and the accuracy of synthesized visual speech. Proposed methodology is inspected on Czech speech. Hence, this article presents a procedure of recording of speech data in order to set a synthesis system as well as to evaluate synthesized speech. Furthermore, one option of the evaluation process is elaborated in the form of a perceptual test. This test procedure is verified on the measured data with two settings of the synthesis system. The results of the perceptual test are presented as a statistically significant increase of intelligibility evoked by real and synthesized visual speech. Now, the aim is to show one part of evaluation process which leads to more comprehensive evaluation of the sign speech synthesis system.
Abstract: Accounts of language acquisition differ significantly in their treatment of the role of prediction in language learning. In particular, nativist accounts posit that probabilistic learning about words and word sequences has little to do with how children come to use language. The accuracy of this claim was examined by testing whether distributional probabilities and frequency contributed to how well 3-4 year olds repeat simple word chunks. Corresponding chunks were the same length, expressed similar content, and were all grammatically acceptable, yet the results of the study showed marked differences in performance when overall distributional frequency varied. It was found that a distributional model of language predicted the empirical findings better than a number of other models, replicating earlier findings and showing that children attend to distributional probabilities in an adult corpus. This suggested that language is more prediction-and-error based, rather than on abstract rules which nativist camps suggest.
Abstract: A novel concept to balance and tradeoff between
make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in
the hybrid MTS/MTO environment is determining whether a product
is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with
the uncertainty and ambiguity of data as well as experts- and
managers- linguistic judgments, the proposed model is equipped with
fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the
literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed
model can actually be implemented.
Abstract: The purpose of this paper is to shed light on the
controversial subject of tax incentives to promote regional
development. Although extensive research has been conducted, a
review of the literature gives an inconclusive answer to whether
economic incentives are effective. One reason is the fact that for
some researchers “effective" means the significant location of new
firms in targeted areas, while for others the creation of jobs
regardless if new firms are arriving in a significant fashion. We
present this dichotomy by analyzing a tax incentive program via both
alternatives: location and job creation. The contribution of the paper
is to inform policymakers about the potential opportunities and
pitfalls when designing incentive strategies. This is particularly
relevant, given that both the US and Europe have been promoting
incentives as a tool for regional economic development.
Abstract: Methanol-to-olefins (MTO) coupled with
transformation of coal or natural gas to methanol gives an interesting
and promising way to produce ethylene and propylene. To investigate
solid concentration in gas-solid fluidized bed for methanol-to-olefins
process catalyzed by SAPO-34, a cold model experiment system is
established in this paper. The system comprises a gas distributor in a
300mm internal diameter and 5000mm height acrylic column, the
fiber optic probe system and series of cyclones. The experiments are
carried out at ambient conditions and under different superficial gas
velocity ranging from 0.3930m/s to 0.7860m/s and different initial bed
height ranging from 600mm to 1200mm. The effects of radial
distance, axial distance, superficial gas velocity, initial bed height on
solid concentration in the bed are discussed. The effects of distributor
shape and porosity on solid concentration are also discussed. The
time-averaged solid concentration profiles under different conditions
are obtained.
Abstract: Self-organizing map (SOM) is a well known data
reduction technique used in data mining. It can reveal structure in
data sets through data visualization that is otherwise hard to detect
from raw data alone. However, interpretation through visual
inspection is prone to errors and can be very tedious. There are
several techniques for the automatic detection of clusters of code
vectors found by SOM, but they generally do not take into account
the distribution of code vectors; this may lead to unsatisfactory
clustering and poor definition of cluster boundaries, particularly
where the density of data points is low. In this paper, we propose the
use of an adaptive heuristic particle swarm optimization (PSO)
algorithm for finding cluster boundaries directly from the code
vectors obtained from SOM. The application of our method to
several standard data sets demonstrates its feasibility. PSO algorithm
utilizes a so-called U-matrix of SOM to determine cluster boundaries;
the results of this novel automatic method compare very favorably to
boundary detection through traditional algorithms namely k-means
and hierarchical based approach which are normally used to interpret
the output of SOM.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Abstract: The problem of mapping tasks onto a computational grid with the aim to minimize the power consumption and the makespan subject to the constraints of deadlines and architectural requirements is considered in this paper. To solve this problem, we propose a solution from cooperative game theory based on the concept of Nash Bargaining Solution. The proposed game theoretical technique is compared against several traditional techniques. The experimental results show that when the deadline constraints are tight, the proposed technique achieves superior performance and reports competitive performance relative to the optimal solution.
Abstract: This paper presents comparative emission study of
newly introduced gasoline/LPG bifuel automotive engine in Indian
market. Emissions were tested as per LPG-Bharat stage III driving
cycle. Emission tests were carried out for urban cycle and extra urban
cycle. Total time for urban and extra urban cycle was 1180 sec.
Engine was run in LPG mode by using conversion system. Emissions
were tested as per standard procedure and were compared. Corrected
emissions were computed by deducting ambient reading from sample
reading. Paper describes detail emission test procedure and results
obtained. CO emissions were in the range of38.9 to 111.3 ppm. HC
emissions were in the range of 18.2 to 62.6 ppm. Nox emissions were
08 to 3.9 ppm and CO2 emissions were from 6719.2 to 8051 ppm.
Paper throws light on emission results of LPG vehicles recently
introduced in Indian automobile market. Objectives of this
experimental study were to measure emissions of engines in gasoline
& LPG mode and compare them.
Abstract: Very few studies have examined performance
implications of strategic alliance announcements in the information
technologies industry from a resource-based view. Furthermore, none
of these studies have investigated resource congruence and alliance
motive as potential sources of abnormal firm performance. This paper
extends upon current resource-based literature to discover and explore
linkages between these concepts and the practical performance of
strategic alliances. This study finds that strategic alliance
announcements have provided overall abnormal positive returns, and
that marketing alliances with marketing resource incongruence have
also contributed to significant firm performance.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
Abstract: In the present research, a finite element model is
presented to study the geometrical and material nonlinear behavior of
reinforced concrete plane frames considering soil-structure
interaction. The nonlinear behaviors of concrete and reinforcing steel
are considered both in compression and tension up to failure. The
model takes account also for the number, diameter, and distribution
of rebar along every cross section. Soil behavior is taken into
consideration using four different models; namely: linear-, nonlinear
Winkler's model, and linear-, nonlinear continuum model. A
computer program (NARC) is specially developed in order to
perform the analysis. The results achieved by the present model show
good agreement with both theoretical and experimental published
literature. The nonlinear behavior of a rectangular frame resting on
soft soil up to failure using the proposed model is introduced for
demonstration.
Abstract: From past many decades human beings are suffering
from plethora of natural disasters. Occurrence of disasters is a
frequent process; it changes conceptual myths as more and more
advancement are made. Although we are living in technological era
but in developing countries like Pakistan disasters are shaped by
socially constructed roles. The need is to understand the most
vulnerable group of society i.e. females; their issues are complex in
nature because of undermined gender status in the society. There is a
need to identify maximum issues regarding females and to enhance
the achievement of millennium development goals (MDGs). Gender
issues are of great concern all around the globe including Pakistan.
Here female visibility in society is low, and also during disasters, the
failure to understand the reality that concentrates on double burden
including productive and reproductive care. Women have to
contribute a lot in society so we need to make them more disaster
resilient. For this non-structural measures like awareness, trainings
and education must be carried out. In rural and in urban settings in
any disaster like earthquake or flood, elements like gender
perspective, their age, physical health, demographic issues contribute
towards vulnerability. In Pakistan the gender issues in disasters were
of less concern before 2005 earthquake and 2010 floods. Significant
achievements are made after 2010 floods when gender and child cell
was created to provide all facilities to women and girls. The aim of
the study is to highlight all necessary facilities in a disaster to build
coping mechanism in females from basic rights till advance level
including education.
Abstract: The objective of this research is to investigate the
advantages of using large-diameter 0.7 inch prestressing strands in
pretention applications. The advantages of large-diameter strands are
mainly beneficial in the heavy construction applications. Bridges and
tunnels are subjected to a higher daily traffic with an exponential
increase in trucks ultimate weight, which raise the demand for higher
structural capacity of bridges and tunnels. In this research, precast
prestressed I-girders were considered as a case study. Flexure
capacities of girders fabricated using 0.7 inch strands and different
concrete strengths were calculated and compared to capacities of 0.6
inch strands girders fabricated using equivalent concrete strength.
The effect of bridge deck concrete strength on composite deck-girder
section capacity was investigated due to its possible effect on final
section capacity. Finally, a comparison was made to compare the
bridge cross-section of girders designed using regular 0.6 inch strands
and the large-diameter 0.7 inch. The research findings showed that
structural advantages of 0.7 inch strands allow for using fewer bridge
girders, reduced material quantity, and light-weight members. The
structural advantages of 0.7 inch strands are maximized when high
strength concrete (HSC) are used in girder fabrication, and concrete
of minimum 5ksi compressive strength is used in pouring bridge
decks. The use of 0.7 inch strands in bridge industry can partially
contribute to the improvement of bridge conditions, minimize
construction cost, and reduce the construction duration of the project.
Abstract: Several methods have been proposed for color image
compression but the reconstructed image had very low signal to noise
ratio which made it inefficient. This paper describes a lossy
compression technique for color images which overcomes the
drawbacks. The technique works on spatial domain where the pixel
values of RGB planes of the input color image is mapped onto two
dimensional planes. The proposed technique produced better results
than JPEG2000, 2DPCA and a comparative study is reported based
on the image quality measures such as PSNR and MSE.Experiments
on real time images are shown that compare this methodology with
previous ones and demonstrate its advantages.