Abstract: Introducing survivability into embedded real-time system (ERTS) can improve the survivability power of the system. This paper mainly discusses about the survivability of ERTS. The first is the survivability origin of ERTS. The second is survivability analysis. According to the definition of survivability based on survivability specification and division of the entire survivability analysis process for ERTS, a survivability analysis profile is presented. The quantitative analysis model of this profile is emphasized and illuminated in detail, the quantifying analysis of system was showed helpful to evaluate system survivability more accurate. The third is platform design of survivability analysis. In terms of the profile, the analysis process is encapsulated and assembled into one platform, on which quantification, standardization and simplification of survivability analysis are all achieved. The fourth is survivability design. According to character of ERTS, strengthened design method is selected to realize system survivability design. Through the analysis of embedded mobile video-on-demand system, intrusion tolerant technology is introduced in whole survivability design.
Abstract: One of the criteria in production scheduling is Make
Span, minimizing this criteria causes more efficiently use of the
resources specially machinery and manpower. By assigning some
budget to some of the operations the operation time of these activities
reduces and affects the total completion time of all the operations
(Make Span). In this paper this issue is practiced in parallel flow
shops. At first we convert parallel flow shop to a network model and
by using a linear programming approach it is identified in order to
minimize make span (the completion time of the network) which
activities (operations) are better to absorb the predetermined and
limited budget. Minimizing the total completion time of all the
activities in the network is equivalent to minimizing make span in
production scheduling.
Abstract: This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).
Abstract: NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.
Abstract: Wireless sensor networks (WSN) are currently
receiving significant attention due to their unlimited potential. These
networks are used for various applications, such as habitat
monitoring, automation, agriculture, and security. The efficient nodeenergy
utilization is one of important performance factors in wireless
sensor networks because sensor nodes operate with limited battery
power. In this paper, we proposed the MiSense hierarchical cluster
based routing algorithm (MiCRA) to extend the lifetime of sensor
networks and to maintain a balanced energy consumption of nodes.
MiCRA is an extension of the HEED algorithm with two levels of
cluster heads. The performance of the proposed protocol has been
examined and evaluated through a simulation study. The simulation
results clearly show that MiCRA has a better performance in terms of
lifetime than HEED. Indeed, MiCRA our proposed protocol can
effectively extend the network lifetime without other critical
overheads and performance degradation. It has been noted that there
is about 35% of energy saving for MiCRA during the clustering
process and 65% energy savings during the routing process compared
to the HEED algorithm.
Abstract: Synthesis gas manufacturing by steam reforming of hydrocarbons is an important industrial process. High endothermic nature of the process makes it one of the most cost and heat intensive processes. In the present work, composite effect of different inert gases on synthesis gas yield, feed gas conversion and temperature distribution along the reactor length has been studied using a heterogeneous model. Mathematical model was developed as a first stage and validated against the existing process models. With the addition of inert gases, a higher yield of synthesis gas is observed. Simultaneously the rector outlet temperature drops to as low as 810 K. It was found that Xenon gives the highest yield and conversion while Helium gives the lowest temperature. Using Xenon inert gas 20 percent reduction in outlet temperature was observed compared to traditional case.
Abstract: This paper presents two simplified models to
determine nodal voltages in power distribution networks. These
models allow estimating the impact of the installation of reactive
power compensations equipments like fixed or switched capacitor
banks. The procedure used to develop the models is similar to the
procedure used to develop linear power flow models of transmission
lines, which have been widely used in optimization problems of
operation planning and system expansion. The steady state non-linear
load flow equations are approximated by linear equations relating the
voltage amplitude and currents. The approximations of the linear
equations are based on the high relationship between line resistance
and line reactance (ratio R/X), which is valid for power distribution
networks. The performance and accuracy of the models are evaluated
through comparisons with the exact results obtained from the
solution of the load flow using two test networks: a hypothetical
network with 23 nodes and a real network with 217 nodes.
Abstract: The dynamics of User Datagram Protocol (UDP) traffic
over Ethernet between two computers are analyzed using nonlinear
dynamics which shows that there are two clear regimes in the data
flow: free flow and saturated. The two most important variables
affecting this are the packet size and packet flow rate. However,
this transition is due to a transcritical bifurcation rather than phase
transition in models such as in vehicle traffic or theorized large-scale
computer network congestion. It is hoped this model will help lay
the groundwork for further research on the dynamics of networks,
especially computer networks.
Abstract: High speed networks provide realtime variable bit rate
service with diversified traffic flow characteristics and quality
requirements. The variable bit rate traffic has stringent delay and
packet loss requirements. The burstiness of the correlated traffic
makes dynamic buffer management highly desirable to satisfy the
Quality of Service (QoS) requirements. This paper presents an
algorithm for optimization of adaptive buffer allocation scheme for
traffic based on loss of consecutive packets in data-stream and buffer
occupancy level. Buffer is designed to allow the input traffic to be
partitioned into different priority classes and based on the input
traffic behavior it controls the threshold dynamically. This algorithm
allows input packets to enter into buffer if its occupancy level is less
than the threshold value for priority of that packet. The threshold is
dynamically varied in runtime based on packet loss behavior. The
simulation is run for two priority classes of the input traffic –
realtime and non-realtime classes. The simulation results show that
Adaptive Partial Buffer Sharing (ADPBS) has better performance
than Static Partial Buffer Sharing (SPBS) and First In First Out
(FIFO) queue under the same traffic conditions.
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.
Abstract: In this paper, a tooth shape optimization method for
cogging torque reduction in Permanent Magnet (PM) motors is
developed by using the Reduced Basis Technique (RBT) coupled by
Finite Element Analysis (FEA) and Design of Experiments (DOE)
methods. The primary objective of the method is to reduce the
enormous number of design variables required to define the tooth
shape. RBT is a weighted combination of several basis shapes. The
aim of the method is to find the best combination using the weights
for each tooth shape as the design variables. A multi-level design
process is developed to find suitable basis shapes or trial shapes at
each level that can be used in the reduced basis technique. Each level
is treated as a separated optimization problem until the required
objective – minimum cogging torque – is achieved. The process is
started with geometrically simple basis shapes that are defined by
their shape co-ordinates. The experimental design of Taguchi method
is used to build the approximation model and to perform
optimization. This method is demonstrated on the tooth shape
optimization of a 8-poles/12-slots PM motor.
Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: This paper presents a mathematical model and a
methodology to analyze the losses in transmission expansion
planning (TEP) under uncertainty in demand. The methodology is
based on discrete particle swarm optimization (DPSO). DPSO is a
useful and powerful stochastic evolutionary algorithm to solve the
large-scale, discrete and nonlinear optimization problems like TEP.
The effectiveness of the proposed idea is tested on an actual
transmission network of the Azerbaijan regional electric company,
Iran. The simulation results show that considering the losses even for
transmission expansion planning of a network with low load growth
is caused that operational costs decreases considerably and the
network satisfies the requirement of delivering electric power more
reliable to load centers.
Abstract: In this paper a new approach to face recognition is
presented that achieves double dimension reduction, making the
system computationally efficient with better recognition results and
out perform common DCT technique of face recognition. In pattern
recognition techniques, discriminative information of image
increases with increase in resolution to a certain extent, consequently
face recognition results change with change in face image resolution
and provide optimal results when arriving at a certain resolution
level. In the proposed model of face recognition, initially image
decimation algorithm is applied on face image for dimension
reduction to a certain resolution level which provides best
recognition results. Due to increased computational speed and feature
extraction potential of Discrete Cosine Transform (DCT), it is
applied on face image. A subset of coefficients of DCT from low to
mid frequencies that represent the face adequately and provides best
recognition results is retained. A tradeoff between decimation factor,
number of DCT coefficients retained and recognition rate with
minimum computation is obtained. Preprocessing of the image is
carried out to increase its robustness against variations in poses and
illumination level. This new model has been tested on different
databases which include ORL , Yale and EME color database.
Abstract: Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.
Abstract: In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively
Abstract: In this paper, some practical solid transportation models are formulated considering per trip capacity of each type of conveyances with crisp and rough unit transportation costs. This is applicable for the system in which full vehicles, e.g. trucks, rail coaches are to be booked for transportation of products so that transportation cost is determined on the full of the conveyances. The models with unit transportation costs as rough variables are transformed into deterministic forms using rough chance constrained programming with the help of trust measure. Numerical examples are provided to illustrate the proposed models in crisp environment as well as with unit transportation costs as rough variables.
Abstract: This study investigates the relationship between 10
year bond value, Yen/U.S dollar exchange rate, non-farm payrolls (all
employs) and crude oil to U.S. Dow Jones Sustainability Index. A
GARCH model is used to test these relationships for the period
January 1st 1999 to January 31st 2008 using monthly data. Results
show that an increase of the 10 year bond and non farm payrolls (all
employs) lead to an increase of the D.J.S.I returns. On the contrary
the volatility of the Yen/U.S dollar exchange rates as well as the
increase of crude oil returns has negative effects on the U.S D.J.S.I
returns. This study aims at assisting investors to understand the
influences certain macroeconomic indicators have on the companies-
stock returns as reported by the D.J.S.I.
Abstract: A satured liquid is warmed until boiling in a parallelepipedic boiler. The heat is supplied in a liquid through the horizontal bottom of the boiler, the other walls being adiabatic. During the process of boiling, the liquid evaporates through its free surface by deforming it. This surface which subdivides the boiler into two regions occupied on both sides by the boiled liquid (broth) and its vapor which surmounts it. The broth occupying the region and its vapor the superior region. A two- fluids model is used to describe the dynamics of the broth, its vapor and their interface. In this model, the broth is treated as a monophasic fluid (homogeneous model) and form with its vapor adiphasic pseudo fluid (two-fluid model). Furthermore, the interface is treated as a zone of mixture characterized by superficial void fraction noted α* . The aim of this article is to describe the dynamics of the interface between the boiled fluid and its vapor within a boiler. The resolution of the problem allowed us to show the evolution of the broth and the level of the liquid.