Abstract: In any trust model, the two information sources that a peer relies on to predict trustworthiness of another peer are direct experience as well as reputation. These two vital components evolve over time. Trust evolution is an important issue, where the objective is to observe a sequence of past values of a trust parameter and determine the future estimates. Unfortunately, trust evolution algorithms received little attention and the proposed algorithms in the literature do not comply with the conditions and the nature of trust. This paper contributes to this important problem in the following ways: (a) presents an algorithm that manages and models trust evolution in a P2P environment, (b) devises new mechanisms for effectively maintaining trust values based on the conditions that influence trust evolution , and (c) introduces a new methodology for incorporating trust-nurture incentives into the trust evolution algorithm. Simulation experiments are carried out to evaluate our trust evolution algorithm.
Abstract: This paper presents the comparative study of coded
data methods for finding the benefit of concealing the natural data
which is the mercantile secret. Influential parameters of the number
of replicates (rep), treatment effects (τ) and standard deviation (σ)
against the efficiency of each transformation method are investigated.
The experimental data are generated via computer simulations under
the specified condition of the process with the completely
randomized design (CRD). Three ways of data transformation consist
of Box-Cox, arcsine and logit methods. The difference values of F
statistic between coded data and natural data (Fc-Fn) and hypothesis
testing results were determined. The experimental results indicate
that the Box-Cox results are significantly different from natural data
in cases of smaller levels of replicates and seem to be improper when
the parameter of minus lambda has been assigned. On the other hand,
arcsine and logit transformations are more robust and obviously,
provide more precise numerical results. In addition, the alternate
ways to select the lambda in the power transformation are also
offered to achieve much more appropriate outcomes.
Abstract: Solar power plants(SPPs) have shown a lot of good outcomes
in providing a various functions depending on industrial expectations by
deploying ad-hoc networking with helps of light loaded and battery powered
sensor nodes. In particular, it is strongly requested to develop an algorithm to
deriver the sensing data from the end node of solar power plants to the sink node
on time. In this paper, based on the above observation we have proposed an
IEEE802.15.4 based self routing scheme for solar power plants. The proposed
beacon based priority routing Algorithm (BPRA) scheme utilizes beacon
periods in sending message with embedding the high priority data and thus
provides high quality of service(QoS) in the given criteria. The performance
measures are the packet Throughput, delivery, latency, total energy
consumption. Simulation results under TinyOS Simulator(TOSSIM) have
shown the proposed scheme outcome the conventional Ad hoc On-Demand
Distance Vector(AODV) Routing in solar power plants.
Abstract: Over the years, there is a growing trend towards
quality-based specifications in highway construction. In many
Quality Control/Quality Assurance (QC/QA) specifications, the
contractor is primarily responsible for quality control of the process,
whereas the highway agency is responsible for testing the acceptance
of the product. A cooperative investigation was conducted in Illinois
over several years to develop a prototype End-Result Specification
(ERS) for asphalt pavement construction. The final characteristics of
the product are stipulated in the ERS and the contractor is given
considerable freedom in achieving those characteristics. The risk for
the contractor or agency depends on how the acceptance limits and
processes are specified. Stochastic simulation models are very useful
in estimating and analyzing payment risk in ERS systems and these
form an integral part of the Illinois-s prototype ERS system. This
paper describes the development of an innovative methodology to
estimate the variability components in in-situ density, air voids and
asphalt content data from ERS projects. The information gained from
this would be crucial in simulating these ERS projects for estimation
and analysis of payment risks associated with asphalt pavement
construction. However, these methods require at least two parties to
conduct tests on all the split samples obtained according to the
sampling scheme prescribed in present ERS implemented in Illinois.
Abstract: A key element of many distribution systems is the
routing and scheduling of vehicles servicing a set of customers. A
wide variety of exact and approximate algorithms have been
proposed for solving the vehicle routing problems (VRP). Exact
algorithms can only solve relatively small problems of VRP, which is
classified as NP-Hard. Several approximate algorithms have proven
successful in finding a feasible solution not necessarily optimum.
Although different parts of the problem are stochastic in nature; yet,
limited work relevant to the application of discrete event system
simulation has addressed the problem. Presented here is optimization
using simulation of VRP; where, a simplified problem has been
developed in the ExtendSimTM simulation environment; where,
ExtendSimTM evolutionary optimizer is used to minimize the total
transportation cost of the problem. Results obtained from the model
are very satisfactory. Further complexities of the problem are
proposed for consideration in the future.
Abstract: This paper presents a new technique of compensation
of the effect of variation parameters in the direct field oriented
control of induction motor. The proposed method uses an adaptive
tuning of the value of synchronous speed to obtain the robustness for
the field oriented control. We show that this adaptive tuning allows
having robustness for direct field oriented control to changes in rotor
resistance, load torque and rotational speed. The effectiveness of the
proposed control scheme is verified by numerical simulations. The
numerical validation results of the proposed scheme have presented
good performances compared to the usual direct-field oriented
control.
Abstract: Flow field around hypersonic vehicles is very
complex and difficult to simulate. The boundary layers are squeezed
between shock layer and body surface. Resolution of boundary layer,
shock wave and turbulent regions where the flow field has high
values is difficult of capture. Detached eddy simulation (DES) is a
modification of a RANS model in which the model switches to a
subgrid scale formulation in regions fine enough for LES
calculations. Regions near solid body boundaries and where the
turbulent length scale is less than the maximum grid dimension are
assigned the RANS mode of solution. As the turbulent length scale
exceeds the grid dimension, the regions are solved using the LES
mode. Therefore the grid resolution is not as demanding as pure LES,
thereby considerably cutting down the cost of the computation. In
this research study hypersonic flow is simulated at Mach 8 and
different angle of attacks to resolve the proper boundary layers and
discontinuities. The flow is also simulated in the long wake regions.
Mesh is little different than RANS simulations and it is made dense
near the boundary layers and in the wake regions to resolve it
properly. Hypersonic blunt cone cylinder body with frustrum at angle
5o and 10 o are simulated and there aerodynamics study is performed
to calculate aerodynamics characteristics of different geometries. The
results and then compared with experimental as well as with some
turbulence model (SA Model). The results achieved with DES
simulation have very good resolution as well as have excellent
agreement with experimental and available data. Unsteady
simulations are performed for DES calculations by using duel time
stepping method or implicit time stepping. The simulations are
performed at Mach number 8 and angle of attack from 0o to 10o for
all these cases. The results and resolutions for DES model found
much better than SA turbulence model.
Abstract: Charge Simulation Method (CSM) is one of the very widely used numerical field computation technique in High Voltage (HV) engineering. The high voltage fields of varying non uniformities are encountered in practice. CSM programs being case specific, the simulation accuracies heavily depend on the user (programmers) experience. Here is an effort to understand CSM errors and evolve some guidelines to setup accurate CSM models, relating non uniformities with assignment factors. The results are for the six-point-charge model of sphere-plane gap geometry. Using genetic algorithm (GA) as tool, optimum assignment factors at different non uniformity factors for this model have been evaluated and analyzed. It is shown that the symmetrically placed six-point-charge models can be good enough to set up CSM programs with potential errors less than 0.1% when the field non uniformity factor is greater than 2.64 (field utilization factor less than 52.76%).
Abstract: Single photon detectors have been fabricated NbN
nano wire. These detectors are fabricated from high quality, ultra
high vacuum sputtered NbN thin films on a sapphire substrate. In this
work a typical schematic of the nanowire Single Photon Detector
structure and then driving and measurement electronic circuit are
shown.
The response of superconducting nanowire single photon detectors
during a photo detection event, is modeled by a special electrical
circuits (two circuit).
Finally, current through the wire is calculated by solving
equations of models.
Abstract: This paper presents a simple method for estimation of
additional load as a factor of the existing load that may be drawn
before reaching the point of line maximum loadability of radial
distribution system (RDS) with different realistic load models at
different substation voltages. The proposed method involves a simple
line loadability index (LLI) that gives a measure of the proximity of
the present state of a line in the distribution system. The LLI can use
to assess voltage instability and the line loading margin. The
proposed method also compares with the existing method of
maximum loadability index [10]. The simulation results show that the
LLI can identify not only the weakest line/branch causing system
instability but also the system voltage collapse point when it is near
one. This feature enables us to set an index threshold to monitor and
predict system stability on-line so that a proper action can be taken to
prevent the system from collapse. To demonstrate the validity of the
proposed algorithm, computer simulations are carried out on two bus
and 69 bus RDS.
Abstract: The integration between technology of remote
sensing, information from the data of digital image, and modeling
technology for the simulation of water quality will provide easiness
during the observation on the quality of water changes on the river
surface. For example, Ciliwung River which is contaminated with
non-point source pollutant from household wastes, particularly on its
downstream. This fact informed that the quality of water in this river
is getting worse. The land use for settlements and housing ranges
between 62.84% - 81.26% on the downstream of Ciliwung River,
give a significant picture in seeing factors that affected the water
quality of Ciliwung River.
Abstract: The challenge in the swing-up problem of double
inverted pendulum on a cart (DIPC) is to design a controller that
bring all DIPC's states, especially the joint angles of the two links,
into the region of attraction of the desired equilibrium. This paper
proposes a new method to swing-up DIPC based on a series of restto-
rest maneuvers of the first link about its vertically upright
configuration while holding the cart fixed at the origin. The rest-torest
maneuvers are designed such that each one results in a net gain
in energy of the second link. This results in swing-up of DIPC-s
configuration to the region of attraction of the desired equilibrium. A
three-step algorithm is provided for swing-up control followed by the
stabilization step. Simulation results with a comparison to an
experimental work done in the literature are presented to demonstrate
the efficacy of the approach.
Abstract: To help overcome limits to the density of conventional SRAMs and leakage current of SRAM cell in nanoscaled CMOS technology, we have developed a four-transistor SRAM cell. The newly developed CMOS four-transistor SRAM cell uses one word-line and one bit-line during read/write operation. This cell retains its data with leakage current and positive feedback without refresh cycle. The new cell size is 19% smaller than a conventional six-transistor cell using same design rules. Also the leakage current of new cell is 60% smaller than a conventional sixtransistor SRAM cell. Simulation result in 65nm CMOS technology shows new cell has correct operation during read/write operation and idle mode.
Abstract: In this article, the flow behavior around a NACA 0012 airfoil which is oscillating with different Reynolds numbers and in various amplitudes has been investigated numerically. Numerical simulations have been performed with ANSYS software. First, the 2- D geometry has been studied in different Reynolds numbers and angles of attack with various numerical methods in its static condition. This analysis was to choose the best turbulent model and comparing the grids to have the optimum one for dynamic simulations. Because the analysis was to study the blades of wind turbines, the Reynolds numbers were not arbitrary. They were in the range of 9.71e5 to 22.65e5. The angle of attack was in the range of -41.81° to 41.81°. By choosing the forward wind speed as the independent parameter, the others like Reynolds and the amplitude of the oscillation would be known automatically. The results show that the SST turbulent model is the best choice that leads the least numerical error with respect the experimental ones. Also, a dynamic stall phenomenon is more probable at lower wind speeds in which the lift force is less.
Abstract: In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Abstract: Estimating the reliability of a computer network has been a subject of great interest. It is a well known fact that this problem is NP-hard. In this paper we present a very efficient combinatorial approach for Monte Carlo reliability estimation of a network with unreliable nodes and unreliable edges. Its core is the computation of some network combinatorial invariants. These invariants, once computed, directly provide pure and simple framework for computation of network reliability. As a specific case of this approach we obtain tight lower and upper bounds for distributed network reliability (the so called residual connectedness reliability). We also present some simulation results.
Abstract: This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.
Abstract: In this paper is being described a possible use of
virtualization technology in teaching computer networks. The
virtualization can be used as a suitable tool for creating virtual
network laboratories, supplementing the real laboratories and
network simulation software in teaching networking concepts. It will
be given a short description of characteristic projects in the area of
virtualization technology usage in network simulation, network
experiments and engineering education. A method for implementing
laboratory has also been explained, together with possible laboratory
usage and design of laboratory exercises. At the end, the laboratory
test results of virtual laboratory are presented as well.