عنوان مقاله | نویسنده(ها) | مربوط به کنفرانس | چکیده | خرید مقاله |
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Iraj Ataollahi, Morteza Analoui
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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Grid environment is being a service oriented
infrastructure in which many heterogeneous resources
participate for providing the high performance
computation. On of bug issue in the grid environment
is the vagueness and uncertainty between advertised
resources and requested resources. In this work we
propose a solution for the vagueness and uncertainty
problems based on rough set theory. Here you can see
how the rough set theory is developed to deal with the
problem. We also report the result of the solution
obtained from the simulation in Gridsim simulator. The
comparison has been made between the proposed
method and UDDI and OWL-S combined method.
Rough set theory shows much better precision for the
cases with vagueness and uncertainty.
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Soodeh Aghli Moghaddam, Siamak Mohammadi, Parviz Jabedar Maralani
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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Asynchronous protocols exhibit various noise robustness
and when used in GALS NoC links, they can directly affect the
signal integrity. In this paper we study the noise robustness of
two well-known asynchronous protocols, namely Dual-Rail
(DRP) and Bundled-Data (BDP) in the GALS NoC links, and
subsequently confirm our claims through simulations. We
apply an enhanced version of BDP and DRP to 32/64 parallel
line links, show results in terms of noise robustness using
global interconnect features, specified in the ITRS roadmap
for 32nm technology.
The simulation results for two thousand random generated
inputs show that the number and the amplitude of noise
glitches over ‘0’ state lines as well as the required threshold
voltage needed for avoiding errors in BDP link are much
lower than in DRP's. Therefore, BDP links can present better
signal integrity features and have less overhead compared to
DRP's, employing only some simple noise reduction
techniques and more timing adjustment effort.
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Hadis Mohseni, Shohreh Kasaei
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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Discriminative subspace analysis is a popular approach
for a variety of applications. There is a growing
interest in subspace learning techniques for face
recognition. Principal component analysis (PCA) and
eigenfaces are two important subspace analysis methods
have been widely applied in a variety of areas.
However, the excessive dimension of data space often
causes the curse of dimensionality dilemma, expensive
computational cost, and sometimes the singularity
problem. In this paper, a new supervised discriminative
subspace analysis is presented by encoding face
image as a high order general tensor. As face space
can be considered as a nonlinear submanifold embedded
in the tensor space, a decomposition method called
Tucker tensor is used which can effectively decomposes
this sparse space. The performance of the proposed
method is compared with that of eigenface, Fisherface,
tensor LPP, and ORO4×2 on ORL and Weizermann
databases. Conducted experimental results show the
superiority of the proposed method.
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Bahareh Atoufi, Ali Zakerolhosseini, Caro Lucas
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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Being able to predict the coming seizure can
impressively improve the quality of the patients' lives
since they can be warned to avoid doing risky activities
via a prediction system. Here, a locally linear neuro
fuzzy model is used to predict the EEG time series.
Subsequently, this model is utilized in accompany with
Singular Spectrum Analysis for prediction. Afterward,
an information theoretic criterion is used to select a
reliable subset of input variables which contain more
information about the target signal. Comparison of
three mentioned methods on one hand shows that SSA
enables our prediction model to extract the main
patterns of the EEG signal and highly improves the
prediction accuracy. On the other hand, applying the
method of channel selection to the model yields more
accurate prediction. It is shown that fusion of some
certain signals provides more information about the
target and considerably improves the prediction
ability.
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Monireh Abdoos, Nasser Mozayani, Ahmad Akbari
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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In this paper, we present a new measure for
evaluating similarity changes in a multi agent system.
The similarity measure of the agents changes during
the learning process. The similarity differences are
because of any composition or decomposition of some
agent sets. The presented measure, defines the changes
of homogeneity of agents by composition and
decomposition. The utility of the metrics is
demonstrated in the experimental evaluation of multi
agent foraging. The results show that while the
similarity difference gets a positive value, the
performance grow rapidly.
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Mohamad Hasan Bahari, Asad Azemi, Naser Pariz, Said Khorashadi Zadeh, Seyed Mohsen Davarpanah
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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In this paper, a new fuzzy fading memory (FFM) is
developed in order to aid a modified input estimation
(MIE) technique and enhance its performance in
tracking high maneuvering targets. The MIE has been
introduced recently and performs well in tracking low
and medium maneuvering targets. However, due to
some modeling errors, the accuracy of this tracker may
be seriously degraded in presence of high maneuvers.
To cope with this difficulty, an intelligent approach
based on FFM is presented in this paper. Simulation
results prove the efficiency of the proposed method in
tracking high maneuvering targets.
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Danial Moazen, Kazem Akbari, Alireza Hashemi
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چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران
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With ever increasing complexity of software systems, it
is now more evident than ever that a fundamental
change in software engineering practices is required.
In this paper we discuss the nature of change and its
implications. The notion of passive autonomy is
introduced as a reference to the relative autonomy of
business entities, and we claim that realizing the
passive autonomy in information systems would results
in systems far more adaptable and aligned with
business’ needs. In order to realize this autonomy,
theuse of autonomous agents as representing real
world autonomous entities is suggested. After pointing
out the shortcomings of current agent based
architectures, a new architecture is proposed, based on
indirect, multilateral negotiation. The suitability of this
architecture is demonstrated in a simple case of beer
game and it is shown that the bullwhip effect is
remedied to some extent using this new architectural
approach.
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امیر اسمعیلزاده
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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رضا جوانمرد علی تپه, محمد مهدی عبادزاده, مجتبی ایمانی, مصطفی امینی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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منیره حسینی صیادنورد, مرجان عبدچیری
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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ندا رهبر
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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جواد عباسی آقاملکی, علیرضا احمدیفرد
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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مهدی حاجیزاده, محمدصادق هلفروش, محمدجواد دهقانی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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زهرا میرمحمدی, سعادت پورمظفری, کوروش منوچهری
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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حمید محمد تقیزاده, حسین نظامآبادی پور, سعید سریزدی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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فرزاد کیانی, سجاد یاری, حمیدرضا طهماسبیراد
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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امین زارع, روحالله تقیزاده, منصور ذوالقدری جهرمی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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منصور ولی, ایمان اسمعیلی, سیدعلی سیدصالحی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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محسن تورانی, سیدعلیاصغر بهشتی شیرازی
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پانزدهمین کنفرانس ملی سالانه انجمن کامپیوتر ایران
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