Abstract: According to dramatic growth of internet services, an easy and prompt service deployment has been important for internet service providers to successfully maintain time-to-market. Before global service deployment, they have to pay the big cost for service evaluation to make a decision of the proper system location, system scale, service delay and so on. But, intra-Lab evaluation tends to have big gaps in the measured data compared with the realistic situation, because it is very difficult to accurately expect the local service environment, network congestion, service delay, network bandwidth and other factors. Therefore, to resolve or ease the upper problems, we propose multiple cloud based GPES Broker system and use case that helps internet service providers to alleviate the above problems in beta release phase and to make a prompt decision for their service launching. By supporting more realistic and reliable evaluation information, the proposed GPES Broker system saves the service release cost and enables internet service provider to make a prompt decision about their service launching to various remote regions.
Abstract: Skin color can provide a useful and robust cue
for human-related image analysis, such as face detection,
pornographic image filtering, hand detection and tracking,
people retrieval in databases and Internet, etc. The major
problem of such kinds of skin color detection algorithms is
that it is time consuming and hence cannot be applied to a real
time system. To overcome this problem, we introduce a new
fast technique for skin detection which can be applied in a real
time system. In this technique, instead of testing each image
pixel to label it as skin or non-skin (as in classic techniques),
we skip a set of pixels. The reason of the skipping process is
the high probability that neighbors of the skin color pixels are
also skin pixels, especially in adult images and vise versa. The
proposed method can rapidly detect skin and non-skin color
pixels, which in turn dramatically reduce the CPU time
required for the protection process. Since many fast detection
techniques are based on image resizing, we apply our
proposed pixel skipping technique with image resizing to
obtain better results. The performance evaluation of the
proposed skipping and hybrid techniques in terms of the
measured CPU time is presented. Experimental results
demonstrate that the proposed methods achieve better result
than the relevant classic method.
Abstract: The success of an electronic system in a System-on- Chip is highly dependent on the efficiency of its interconnection network, which is constructed from routers and channels (the routers move data across the channels between nodes). Since neither classical bus based nor point to point architectures can provide scalable solutions and satisfy the tight power and performance requirements of future applications, the Network-on-Chip (NoC) approach has recently been proposed as a promising solution. Indeed, in contrast to the traditional solutions, the NoC approach can provide large bandwidth with moderate area overhead. The selected topology of the components interconnects plays prime rule in the performance of NoC architecture as well as routing and switching techniques that can be used. In this paper, we present two generic NoC architectures that can be customized to the specific communication needs of an application in order to reduce the area with minimal degradation of the latency of the system. An experimental study is performed to compare these structures with basic NoC topologies represented by 2D mesh, Butterfly-Fat Tree (BFT) and SPIN. It is shown that Cluster mesh (CMesh) and MinRoot schemes achieves significant improvements in network latency and energy consumption with only negligible area overhead and complexity over existing architectures. In fact, in the case of basic NoC topologies, CMesh and MinRoot schemes provides substantial savings in area as well, because they requires fewer routers. The simulation results show that CMesh and MinRoot networks outperforms MESH, BFT and SPIN in main performance metrics.
Abstract: Optimum communication and performance in
Wireless Sensor Networks, constitute multi-facet challenges due to
the specific networking characteristics as well as the scarce resource
availability. Furthermore, it is becoming increasingly apparent that
isolated layer based approaches often do not meet the demands posed
by WSNs applications due to omission of critical inter-layer
interactions and dependencies. As a counterpart, cross-layer is
receiving high interest aiming to exploit these interactions and
increase network performance. However, in order to clearly identify
existing dependencies, comprehensive performance studies are
required evaluating the effect of different critical network parameters
on system level performance and behavior.This paper-s main
objective is to address the need for multi-parametric performance
evaluations considering critical network parameters using a well
known network simulator, offering useful and practical conclusions
and guidelines. The results reveal strong dependencies among
considered parameters which can be utilized by and drive future
research efforts, towards designing and implementing highly efficient
protocols and architectures.
Abstract: Company mergers and acquisitions reached their peak
in the twenty-first century. Mergers and acquisitions have become one
of the competitive strategies for external growth. In general, it is
believed that mergers and acquisitions can create synergies. However,
they require complete information technology system and service
integration, especially in the banking industry. Much of the research
has focused on performance evaluation, shareholder equity allocation,
or even the increase of company market value after the merger and
acquisition, whereas few scholars have focused on information system
integration post merger and acquisition. This study indicates the role
of information systems after a merger and acquisition, explaining the
benefits of information system integration using a merger and
acquisition case in the banking industry as an example. In addition, we
discuss factors that affect the performance of information system
integration, and utilize system dynamics to interpret the relationship
among factors that affect information system integration performance
in the banking industry after a merger and acquisition.
Abstract: Numerous experimental tests for post-installed anchor systems drilled in hardened concrete were conducted in order to estimate pull-out and shear strength accounting for uncertainties such as torque ratios, embedment depths and different diameters in demands. In this study, the strength of the systems was significantly changed by the effect of those three uncertainties during pull-out experimental tests, whereas the shear strength of the systems was not affected by torque ratios. It was also shown that concrete cone failure or damage mechanism was generally investigated during and after pull-out tests and in shear strength tests, mostly the anchor systems were failed prior to failure of primary structural system. Furthermore, 3D finite element model for the anchor systems was created by ABAQUS for the numerical analysis. The verification of finite element model was identical till the failure points to the load-displacement relationship specified by the experimental tests.
Abstract: The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.
Abstract: One of the important applications of gas turbines is
their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for
determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance
data. For this reason a method was developed for determining the
exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable
error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is
based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General
Electric gas turbine design data for validation of methodologies. The
result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from
design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of
analyzer instruments, the method can be suitable alternative for gas
turbine standard performance test. In advance two methods are
proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between
the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the
method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.
Abstract: The passive electrical properties of a tissue depends
on the intrinsic constituents and its structure, therefore by measuring
the complex electrical impedance of the tissue it might be possible to
obtain indicators of the tissue state or physiological activity [1].
Complete bio-impedance information relative to physiology and
pathology of a human body and functional states of the body tissue or
organs can be extracted by using a technique containing a fourelectrode
measurement setup. This work presents the estimation
measurement setup based on the four-electrode technique. First, the
complex impedance is estimated by three different estimation
techniques: Fourier, Sine Correlation and Digital De-convolution and
then estimation errors for the magnitude, phase, reactance and
resistance are calculated and analyzed for different levels of
disturbances in the observations. The absolute values of relative
errors are plotted and the graphical performance of each technique is
compared.
Abstract: In this paper three basic approaches and different
methods under each of them for extracting region of interest (ROI)
from stationary images are explored. The results obtained for each of
the proposed methods are shown, and it is demonstrated where each
method outperforms the other. Two main problems in ROI
extraction: the channel selection problem and the saliency reversal
problem are discussed and how best these two are addressed by
various methods is also seen. The basic approaches are 1) Saliency
based approach 2) Wavelet based approach 3) Clustering based
approach. The saliency approach performs well on images containing
objects of high saturation and brightness. The wavelet based
approach performs well on natural scene images that contain regions
of distinct textures. The mean shift clustering approach partitions the
image into regions according to the density distribution of pixel
intensities. The experimental results of various methodologies show
that each technique performs at different acceptable levels for
various types of images.
Abstract: This paper details a new concept of using compressed air as a potential zero pollution power source for motorbikes. In place of an internal combustion engine, the motorbike is equipped with an air turbine transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor diameters, casing diameters and ratio of rotor to casing diameters of the turbine have been considered and analyzed. It is concluded that the work output is found optimum for some typical values of rotor / casing diameter ratios. In this study, the maximum power works out to 3.825 kW (5.20 HP) for casing diameter of 200 mm and rotor to casing diameter ratio of 0.65 to 0.60 which is sufficient to run motorbike.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: Performance of a limited Round-Robin (RR) rule is
studied in order to clarify the characteristics of a realistic sharing
model of a processor. Under the limited RR rule, the processor
allocates to each request a fixed amount of time, called a quantum, in a
fixed order. The sum of the requests being allocated these quanta is
kept below a fixed value. Arriving requests that cannot be allocated
quanta because of such a restriction are queued or rejected. Practical
performance measures, such as the relationship between the mean
sojourn time, the mean number of requests, or the loss probability and
the quantum size are evaluated via simulation. In the evaluation, the
requested service time of an arriving request is converted into a
quantum number. One of these quanta is included in an RR cycle,
which means a series of quanta allocated to each request in a fixed
order. The service time of the arriving request can be evaluated using
the number of RR cycles required to complete the service, the number
of requests receiving service, and the quantum size. Then an increase
or decrease in the number of quanta that are necessary before service is
completed is reevaluated at the arrival or departure of other requests.
Tracking these events and calculations enables us to analyze the
performance of our limited RR rule. In particular, we obtain the most
suitable quantum size, which minimizes the mean sojourn time, for the
case in which the switching time for each quantum is considered.
Abstract: Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.
Abstract: Since the last two decades, container transportation
system has been faced under increasing development. This fact
shows the importance of container transportation system as a key role
of container terminals to link between sea and land. Therefore, there
is a continuous need for the optimal use of equipment and facilities in
the ports. Regarding the complex structure of container ports, this
paper presents a simulation model that compares tow storage
strategies for storing containers in the yard. For this purpose, we
considered loading and unloading norm as an important criterion to
evaluate the performance of Shahid Rajaee container port. By
analysing the results of the model, it will be shown that using
marshalling yard policy instead of current storage system has a
significant effect on the performance level of the port and can
increase the loading and unloading norm up to 14%.
Abstract: Worldwide conventional resources of fossil fuel are depleting very fast due to large scale increase in use of transport vehicles every year, therefore consumption rate of oil in transport sector alone has gone very high. In view of this, the major thrust has now been laid upon the search of alternative energy source and also for cost effective energy conversion system. The air converted into compressed form by non conventional or conventional methods can be utilized as potential working fluid for producing shaft work in the air turbine and thus offering the capability of being a zero pollution energy source. This paper deals with the mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine. Effect of expansion action and steady flow work in the air turbine at high admission air pressure of 6 bar, for varying injection to vane angles ratios 0.2-1.6, at the interval of 0.2 and at different vane angles such as 30o, 45o, 51.4o, 60o, 72o, 90o, and 120o for 12, 8, 7, 6, 5, 4 and 3 vanes respectively at speed of rotation 2500 rpm, has been quantified and analyzed here. Study shows that the expansion power has major contribution to total power, whereas the contribution of flow work output has been found varying only up to 19.4%. It is also concluded that for variation of injection to vane angle ratios from 0.2 to 1.2, the optimal power output is seen at vane angle 90o (4 vanes) and for 1.4 to 1.6 ratios, the optimal total power is observed at vane angle 72o (5 vanes). Thus in the vaned type novel air turbine the optimum shaft power output is developed when rotor contains 4-5 vanes for almost all situations of injection to vane angle ratios from 0.2 to 1.6.
Abstract: This paper deals with the application of artificial
neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy
Inference System(ANFIS) approach to Load Frequency Control
(LFC) of multi unequal area hydro-thermal interconnected power
system. The proposed ANFIS controller combines the advantages of
fuzzy controller as well as quick response and adaptability nature of
ANN. Area-1 and area-2 consists of thermal reheat power plant
whereas area-3 and area-4 consists of hydro power plant with electric
governor. Performance evaluation is carried out by using intelligent
controller like ANFIS, ANN and Fuzzy controllers and conventional
PI and PID control approaches. To enhance the performance of
intelligent and conventional controller sliding surface is included.
The performances of the controllers are simulated using
MATLAB/SIMULINK package. A comparison of ANFIS, ANN,
Fuzzy, PI and PID based approaches shows the superiority of
proposed ANFIS over ANN & fuzzy, PI and PID controller for 1%
step load variation.
Abstract: Developers need to evaluate software's performance to make software efficient. This paper suggests a performance evaluation system for embedded software. The suggested system consists of code analyzer, testing agents, data analyzer, and report viewer. The code analyzer inserts additional code dependent on target system into source code and compiles the source code. The testing agents execute performance test. The data analyzer translates raw-level results data to class-level APIs for reporting viewer. The report viewer offers users graphical report views by using the APIs. We hope that the suggested tool will be useful for embedded-related software development,because developers can easily and intuitively analyze software's performance and resource utilization.
Abstract: Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR), Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing (LAR1).Our evaluation is based on energy consumption in mobile ad hoc networks. The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.
Abstract: The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.