Sharif University of TechnologyScientia Iranica1026-309815620081201Optimum Learning Rate in Back-Propagation Neural Network for Classication of Satellite Images (IRS-1D)3078ENJ.AminiDepartment of Geomatics Engineering,University of TehranJournal Article20090725Remote sensing data are essentially used for land cover and vegetation classication. However,
classes of interest are often imperfectly separable in the feature space provided by the spectral
data. Application of Neural Networks (NN) to the classication of satellite images is increasingly
emerging. Without any assumption about the probabilistic model to be made, the networks are
capable of forming highly non-linear decision boundaries in the feature space. Training has an
important role in the NN. There are several algorithms for training and the Variable Learning
Rate (VLR) is one of the fastest. In this paper, a network that focuses on the determination of
an optimum learning rate is proposed for the classication of satellite images. Dierent networks
with the same conditions are used for this and the results showed that a network with one hidden
layer with 20 neurons is suitable for the classication of IRS-1D satellite images. An optimum
learning rate between the ranges of 0.001-0.006 was determined for training the VLR algorithm.
This range can be used for training algorithms in which the learning rate is constant.https://scientiairanica.sharif.edu/article_3078_937f22e01666e42a930951c555d6521a.pdfSharif University of TechnologyScientia Iranica1026-309815620081201On the Solvability of @ in a Class of Hypo-Analytic Manifolds3079ENA.R.BahrainiDepartment of Mathematics,Sharif University of TechnologyJournal Article20090725The solvability of @ operator in a class of hypo-analytic manifolds in complex dimension 2 is
studied. Suitable weighted L2 spaces are introduced for establishing an a priori inequality. The
regularity of the solutions is shown by using a theory of degenerate elliptic operators, developed
by Grusin and Visik. The theorem obtained is a degenerate version for the @ problem in strictly
pseudo-convex domains.https://scientiairanica.sharif.edu/article_3079_475de2393c357a7f8b1f73e7eeb2512b.pdfSharif University of TechnologyScientia Iranica1026-309815620081201On the Poincare Index of Isolated Invariant Sets3080ENM.R.RazvanDepartment of Mathematics,Sharif University of TechnologyM.FotouhiDepartment of Mathematics,Sharif University of TechnologyJournal Article20090725In this paper, the Conley index theory is used to examine the Poincare index of an isolated
invariant set. Some limiting conditions on a critical point of a planar vector eld are obtained
to be an isolated invariant set. As a result, the existence of innitely many homoclinic orbits for
a critical point with the Poincare index greater than one is shown.https://scientiairanica.sharif.edu/article_3080_b7d97ad9e3f8d55dbdc72e09d86c28ff.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Stability Analysis of a Window-Based High-Speed Hierarchical Rate Allocation Algorithm3081ENP.GoudarziDepartment of Electrical & Computer Engineering,Isfahan University of TechnologyJournal Article20090725Providing the stability of any rate allocation algorithm is a challenging issue in current high-speed
networks. Some researchers, such as Kelly, Massoulie, Vinnicombe and Johari, have shown
the stability of their rate-based rate allocation algorithms using dierent approaches. Some
other researchers have investigated the stability of the second-order, rate-based, rate allocation
algorithms under some simplifying constraints. Mo et al. have proved the stability of the rstorder,
window-based rate allocation algorithms, using control theory concepts, for a wide range
of fairness criteria. In the current work, the stability property of a second-order, high-speed
and window-based rate allocation strategy has been investigated using the Lyapunov approach.
Simulation results verify the stability of the proposed method under a general network scenario.https://scientiairanica.sharif.edu/article_3081_4ec28d70d0f0a33a57df910d0e989acf.pdfSharif University of TechnologyScientia Iranica1026-309815620081201New Half-Pixel Accuracy Motion Estimation Algorithms for Low Bitrate Video Communications3082ENS.KasaeiDepartment of Computer Science and Engineering,Sharif University of Technology0000-0002-3831-0878H.Mahdavi-NasabDepartment of Electrical Engineering,Azad UniversityJournal Article20090725Fractional-pixel accuracy Motion Estimation (ME) has been shown to result in higher quality
reconstructed image sequences in hybrid video coding systems. However, the higher quality is
achieved by notably increased Motion Field (MF) bitrate and more complex computations. In this
paper, new half-pixel block matching ME algorithms are proposed to improve the rate-distortion
characteristics of low bitrate video communications. The proposed methods tend to decrease the
required video bandwidth, while improving the motion compensation quality. The key idea is to
put a deeper focus on the search origin of the ME process, based on center-bias characteristics
of low bitrate video MFs. To employ the benets of Mesh-based ME (MME), the introduced
algorithms are also examined in the framework of a fast MME scheme. Experimental results
show the eciency of the proposed schemes, especially when employed in the MME approach,
so that a reduction of more than 20% in the MF bitrate is achieved when employing typical
QCIF formatted image sequences.https://scientiairanica.sharif.edu/article_3082_e108aab242b72658e068ef52e8774f2d.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Boundedness and Regularity with Nonlinear Dependence of Hessian and Gradient3083ENB.MehriDepartment of Mathematics,Sharif University of TechnologyM.H.NojumiDepartment of Mathematical Sciences,Sharif University of TechnologyJournal Article20090725Sucient conditions for the boundedness and regularity of a function, whose partial derivatives
satisfy a certain set of equations, are presented. Energy methods are used to establish these
results. The asymptotic behavior of the gradient toward a constant function is also investigated.https://scientiairanica.sharif.edu/article_3083_ca51c20f57ecbef80624ee3a2b69691c.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Clock Boosting Router: Increasing the Performance of an Adaptive Router in Network-on-Chip (NoC)3084ENS.E.LeeDepartment of Electrical Engineering,University of CaliforniaN.BagherzadehDepartment of Electrical Engineering,University of CaliforniaJournal Article20090725In this paper, a simple and ecient clock boosting mechanism to increase the performance of an
adaptive router in Network-on-Chip (NoC) is proposed. One of the most serious disadvantages
of a fully adaptive wormhole router is performance degradation due to the routing decision time.
The key idea to overcome this shortcoming is the use of dierent clocks in a head
it and
body
its. The simulation results show that the proposed clock boosting mechanism enhances
the performance of the original adaptive router by increasing the accepted load and decreasing
the average latency in the region of eective bandwidth. The enhanced throughput of a router
results in power saving by reducing the operating frequency of a router for certain communication
bandwidth requirements.https://scientiairanica.sharif.edu/article_3084_1503a212fcb78fdeb4f8dd55dfbe10ec.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Self-Organization in a Particle Swarm Optimized Fuzzy Logic Congestion Detection Mechanism for IP Networks3085ENC.N.NyirendaDepartment of Electrical & Computer Engineering,BeraklyD.S.DawoudDepartment of Electrical & Computer Engineering,BeraklyJournal Article20090725The Fuzzy Logic Congestion Detection (FLCD) algorithm is a recent proposal for congestion
detection in IP networks which combines the good characteristics of both traditional Active
Queue Management (AQM) algorithms and fuzzy logic based AQM algorithms. The
Membership Functions (MFs) of the FLCD algorithm are designed using a Multi-Objective
Particle Swarm Optimization (MOPSO) algorithm, in order to achieve optimal performance
on all the major performance metrics of IP congestion control. The FLCD algorithm achieves
better performance when compared to the basic Fuzzy Logic AQM and Random Explicit
Marking (REM) algorithms. Since the optimization process is undertaken oine and is based
on a single optimization script, the performance of the FLCD algorithm may not be optimal
under dierent network conditions, due to the fact that the IP environment is characterized
by dynamic trac patterns. This paper proposes two online self-learning and organization
structures that enable the FLCD algorithm to learn the system conditions and adjust the
fuzzy rule base in accordance with prevailing conditions. The self-organized FLCD algorithm
is compared with the unorganized FLCD, the basic Fuzzy Logic AQM and the Adaptive
Random Early Detection (RED) algorithms using simulations with dynamic trac patterns.
Performance results show that the self-organized FLCD algorithm is more robust than the
other algorithms. Compared to the unorganized FLCD, the new scheme improves the UDP
trac delay for short round trip times and also reduces packet loss rates. In terms of jitter,
fairness and link utilization, it exhibits a similar performance to the unorganized FLCD algorithm.https://scientiairanica.sharif.edu/article_3085_63fa670655ee7814c24e0162e98bd70e.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Genetic Algorithm Based Fuzzy Multi-Objective Approach to FACTS Devices Allocation in FARS Regional Electric Network3086ENM.KalantarDepartment of Electrical Engineering,Iran University of Science and TechnologyM.GitizadehDepartment of Electrical Engineering,Iran University of Science and TechnologyJournal Article20090725In this investigation, a novel approach is presented to nd the optimum locations and capacity
of Flexible AC Transmission Systems (FACTS) devices in a power system using a fuzzy
multi-objective function. Maximising the fuzzy satisfaction allows the optimization algorithm
to simultaneously consider the multiple objectives of the network to obtain active power loss
reduction; i.e., new FACTS devices cost reduction, robustifying the security margin against
voltage collapse, network loadability enhancement and a voltage deviation reduction of the
power system. A Genetic Algorithm (GA) optimization technique is then implemented to
solve the fuzzy multi-objective problem. Operational and control constraints, as well as load
constraints, are considered for optimum device allocation. Also, an estimated annual load prole
has been utilized in a Sequential Quadratic Programming (SQP) optimization sub-problem to
nd the optimum location and capacity of FACTS devices, accurately. A Thyristor Controlled
Series Compensator (TCSC) and a Static Var Compensator (SVC) are utilized as series and
shunt FACTS devices in this study. The Fars regional electric network is selected as a practical
system to validate the performance and eectiveness of the proposed method.https://scientiairanica.sharif.edu/article_3086_677b0491d0ebf41ea8a8d72f60ee312d.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Using Binary Particle Swarm Optimization for Minimization Analysis of Large-Scale Network Attack Graphs3087ENM.AbadiDepartment of Computer Engineering,Tarbiat Modares UniversityS.JaliliDepartment of Computer Engineering,Tarbiat Modares UniversityJournal Article20090725The aim of the minimization analysis of network attack graphs (NAGs) is to nd a minimum
critical set of exploits so that by preventing them an intruder cannot reach his goal using
any attack scenario. This problem is, in fact, a constrained optimization problem. In this
paper, a binary particle swarm optimization algorithm, called SwarmNAG, is presented for the
minimization analysis of large-scale network attack graphs. A penalty function method with a
time-varying penalty coecient is used to convert the constrained optimization problem into
an unconstrained problem. Also, a time-varying velocity clamping, a greedy mutation operator
and a local search heuristic are used to improve the overall performance of the algorithm. The
performance of the SwarmNAG is compared with that of an approximation algorithm for the
minimization analysis of several large-scale network attack graphs. The results of the experiments
show that the SwarmNAG outperforms the approximation algorithm and nds a critical set of
exploits with less cardinality.https://scientiairanica.sharif.edu/article_3087_d3b76fb5085183b049f8dc575cd28997.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Eects of Instrument Transformers Connection Point on Measured Impedance by Distance Relay in Presence of SSSC3088ENS.JamaliDepartment of Electrical Engineering,Sharif University of TechnologyH.ShateriDepartment of Electrical Engineering,Sharif University of TechnologyA.KazemiBiochemical and Bioenvironmental Research Center,Iran University of Science and TechnologyJournal Article20090725This paper presents the measured impedance at the relaying point in the presence of a series
connected Flexible Alternating Current Transmission System (FACTS) device, i.e. Static
Synchronous Series Compensator (SSSC). The presence of SSSC on a transmission line has
a great in
uence on the tripping characteristic of distance relays. The distance relay tripping
characteristic itself depends on power system structural and pre-fault operational conditions
and, especially, the ground fault resistance. In the presence of SSSC, its controlling parameters,
as well as the connection point of the instrument transformers of distance relay aect the
tripping characteristic. Here, measured impedance at the relaying point is calculated, due to
the concerned parameters.https://scientiairanica.sharif.edu/article_3088_26a55fde594eadcccac4482d71ec7386.pdfSharif University of TechnologyScientia Iranica1026-309815620081201Space and Norm Redundancies in Frame Theory3089ENA.NazariDepartment of Mathematical Sciences,Shahid Bahonar University of KermanJournal Article20091221Let f'm : m 2 Mg be a generalized frame in Hilbert space H with frame bounds 0 < A B < 1 and the analysis operator T : H ! L2( ). The paper studies the relation between
(space) redundancy (TH)? and (norm) redundancy A. Also, in case dimH < 1, the e
ect of
the redundancies on the reduction of the total energy of noise is studied.