Abstract: IP networks are evolving from data communication
infrastructure into many real-time applications such as video
conferencing, IP telephony and require stringent Quality of Service
(QoS) requirements. A rudimentary issue in QoS routing is to find a
path between a source-destination pair that satisfies two or more endto-
end constraints and termed to be NP hard or complete. In this
context, we present an algorithm Multi Constraint Path Problem
Version 3 (MCPv3), where all constraints are approximated and
return a feasible path in much quicker time. We present another
algorithm namely Delay Coerced Multi Constrained Routing
(DCMCR) where coerce one constraint and approximate the
remaining constraints. Our algorithm returns a feasible path, if exists,
in polynomial time between a source-destination pair whose first
weight satisfied by the first constraint and every other weight is
bounded by remaining constraints by a predefined approximation
factor (a). We present our experimental results with different
topologies and network conditions.
Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
Abstract: L-asparaginase was extracted from pathogenic
Escherichia coli which was isolated from urinary tract infection
patients. L-asparaginase was purified 96-fold by ultrafiltration, ion
exchange and gel filtration giving 39.19% yield with final specific
activity of 178.57 IU/mg. L-asparaginase showed 138,356±1,000
Dalton molecular weight with 31024±100 Dalton molecular mass.
Kinetic properties of enzyme resulting 1.25×10-5 mM Km and
2.5×10-3 M/min Vmax. L-asparaginase showed a maximum activity
at pH 7.5 when incubated at 37 ºC for 30 min and illustrated its full
activity (100%) after 15 min incubation at 20-37 ºC, while 70% of its
activity was lost when incubated at 60 ºC. L-asparaginase showed
cytotoxicity to U937 cell line with IC50 0.5±0.19 IU/ml, and
selectivity index (SI=7.6) about 8 time higher selectivity over the
lymphocyte cells. Therefore, the local pathogenic E. coli strains may
be used as a source of high yield of L-asparaginase to produce anti
cancer agent with high selectivity.
Abstract: In this paper we propose a simple adaptive algorithm
iteratively solving the unit-norm constrained optimization problem.
Instead of conventional parameter norm based normalization,
the proposed algorithm incorporates scalar normalization which is
computationally much simpler. The analysis of stationary point is
presented to show that the proposed algorithm indeed solves the
constrained optimization problem. The simulation results illustrate
that the proposed algorithm performs as good as conventional ones
while being computationally simpler.
Abstract: In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.
Abstract: This paper describes identification of the two poles
unstable SOPDT process, especially with large time delay. A new
modified relay feedback identification method for two poles unstable
SOPDT process is proposed. Furthermore, for the two poles unstable
SOPDT process, an additional Derivative controller is incorporated
parallel with relay to relax the constraint on the ratio of delay to the
unstable time constant, so that the exact model parameters of
unstable processes can be identified. To cope with measurement
noise in practice, a low pass filter is suggested to get denoised output
signal toimprove the exactness of model parameter of unstable
process. PID Lead-lag tuning formulas are derived for two poles
unstable (SOPDT) processes based on IMC principle. Simulation
example illustrates the effectiveness and the simplicity of the
proposed identification and control method.
Abstract: This paper summarizes and compares approaches to
solving the knapsack problem and its known application in capital
budgeting. The first approach uses deterministic methods and can be
applied to small-size tasks with a single constraint. We can also
apply commercial software systems such as the GAMS modelling
system. However, because of NP-completeness of the problem, more
complex problem instances must be solved by means of heuristic
techniques to achieve an approximation of the exact solution in a
reasonable amount of time. We show the problem representation and
parameter settings for a genetic algorithm framework.
Abstract: Studies were carried out on the comparative study of the production of Avicelase enzyme using sugarcane bagasse-SCB in two different statuses (i.e. treated and untreated SCB) by thermophilic Geobacillus stearothermophilus at 50ºC. Only four thermophilic bacterial isolates were isolated and assayed for Avicelase production using UntSCB and TSCB. Only one isolate selected as most potent and identified as G. stearothermophilus used in this study. A specific endo-β-1,4-D-glucanase (Avicelase EC 3.2.1.91) was partially purified from a thermophilic bacterial strain was isolated from different soil samples when grown on cellulose enrichment SCB substrate as the sole carbon source. Results shown that G. stearothermophilus was the better Avicelase producer strain. Avicelase had an optimum pH and temperature 7.0 and 50ºC for both UntSCB and TSCB and exhibited good pH stability between "5-8" and "4-9", however, good temperature stability between (30-80ºC) for UntSCB and TSCB, respectively. Other factors affecting the production of Avicelase were compared (i.e. SCB concentration, inoculum size and different incubation periods), all results observed and obtained were revealed that the TSCB was exhibited maximal enzyme activity in comparison with the results obtained from UntSCB, so, the TSCB was enhancing the Avicelase production.
Abstract: The aim of this work is to present a multi-objective optimization method to find maximum efficiency kinematics for a flapping wing unmanned aerial vehicle. We restrained our study to rectangular wings with the same profile along the span and to harmonic dihedral motion. It is assumed that the birdlike aerial vehicle (whose span and surface area were fixed respectively to 1m and 0.15m2) is in horizontal mechanically balanced motion at fixed speed. We used two flight physics models to describe the vehicle aerodynamic performances, namely DeLaurier-s model, which has been used in many studies dealing with flapping wings, and the model proposed by Dae-Kwan et al. Then, a constrained multi-objective optimization of the propulsive efficiency is performed using a recent evolutionary multi-objective algorithm called є-MOEA. Firstly, we show that feasible solutions (i.e. solutions that fulfil the imposed constraints) can be obtained using Dae-Kwan et al.-s model. Secondly, we highlight that a single objective optimization approach (weighted sum method for example) can also give optimal solutions as good as the multi-objective one which nevertheless offers the advantage of directly generating the set of the best trade-offs. Finally, we show that the DeLaurier-s model does not yield feasible solutions.
Abstract: A robust still image face localization algorithm
capable of operating in an unconstrained visual environment is
proposed. First, construction of a robust skin classifier within a
shifted HSV color space is described. Then various filtering
operations are performed to better isolate face candidates and
mitigate the effect of substantial non-skin regions. Finally, a novel
Bhattacharyya-based face detection algorithm is used to compare
candidate regions of interest with a unique illumination-dependent
face model probability distribution function approximation.
Experimental results show a 90% face detection success rate despite
the demands of the visually noisy environment.
Abstract: The objective of this study is to present the test
results of variable air volume (VAV) air conditioning system
optimized by two objective genetic algorithm (GA). The objective
functions are energy savings and thermal comfort. The optimal set
points for fuzzy logic controller (FLC) are the supply air temperature
(Ts), the supply duct static pressure (Ps), the chilled water
temperature (Tw), and zone temperature (Tz) that is taken as the
problem variables. Supply airflow rate and chilled water flow rate are
considered to be the constraints. The optimal set point values are
obtained from GA process and assigned into fuzzy logic controller
(FLC) in order to conserve energy and maintain thermal comfort in
real time VAV air conditioning system. A VAV air conditioning
system with FLC installed in a software laboratory has been taken for
the purpose of energy analysis. The total energy saving obtained in
VAV GA optimization system with FLC compared with constant air
volume (CAV) system is expected to achieve 31.5%. The optimal
duct static pressure obtained through Genetic fuzzy methodology
attributes to better air distribution by delivering the optimal quantity
of supply air to the conditioned space. This combination enhanced
the advantages of uniform air distribution, thermal comfort and
improved energy savings potential.
Abstract: This paper considers the design of a motion planner
that will simultaneously accomplish control and motion planning of a
n-link nonholonomic mobile manipulator, wherein, a n-link
holonomic manipulator is coupled with a nonholonomic mobile
platform, within an obstacle-ridden environment. This planner,
derived from the Lyapunov-based control scheme, generates
collision-free trajectories from an initial configuration to a final
configuration in a constrained environment cluttered with stationary
solid objects of different shapes and sizes. We demonstrate the
efficiency of the control scheme and the resulting acceleration
controllers of the mobile manipulator with results through computer
simulations of an interesting scenario.
Abstract: Exchange algorithm with constraints on magnitude and phase error separately in new way is presented in this paper. An important feature of the algorithms presented in this paper is that they allow for design constraints which often arise in practical filter design problems. Meeting required minimum stopband attenuation or a maximum deviation from the desired magnitude and phase responses in the passbands are common design constraints that can be handled by the methods proposed here. This new algorithm may have important advantages over existing technique, with respect to the speed and stability of convergence, memory requirement and low ripples.
Abstract: In this paper, some experiments of liquid dispersion flow driven by explosion in vertical plane were carried out using a liquid explosive dispersion device with film cylindrical constraints. The separated time series describing the breakup shape and dispersion process of liquid were recorded with high speed CMOS camera. The experimental results were analyzed and some essential characteristics of liquid dispersing flow are presented.
Abstract: Mobile learning (M-learning) integrates mobile
devices and wireless computing technology to enhance the current
conventional learning system. However, there are constraints which
are affecting the implementation of platform and device independent
M-learning. The main aim of this research is to fulfill the following
main objectives: to develop platform independent mobile learning
tool (M-LT) for structured programming course, and evaluate its
effectiveness and usability using ADDIE instructional design model
(ISD) as M-LT life cycle. J2ME (Java 2 micro edition) and XML
(Extensible Markup Language) were used to develop platform
independent M-LT. It has two modules lecture materials and quizzes.
This study used Quasi experimental design to measure effectiveness
of the tool. Meanwhile, questionnaire is used to evaluate the usability
of the tool. Finally, the results show that the system was effective and
also usability evaluation was positive.
Abstract: In this paper, we introduce an mobile agent framework
with proactive load balancing for ambient intelligence (AmI) environments.
One of the main obstacles of AmI is the scalability in
which the openness of AmI environment introduces dynamic resource
requirements on agencies. To mediate this scalability problem, our
framework proposes a load balancing module to proactively analyze
the resource consumption of network bandwidth and preferred agencies
to suggest the optimal communication method to its user. The
framework generally formulates an AmI environment that consists
of three main components: (1) mobile devices, (2) hosts or agencies,
and (3) directory service center (DSC). A preliminary implementation
was conducted with NetLogo and the experimental results show that
the proposed approach provides enhanced system performance by
minimizing the network utilization to provide users with responsive
services.
Abstract: This paper presents a sensor-based motion planning algorithm for 3-DOF car-like robots with a nonholonomic constraint. Similar to the classic Bug family algorithms, the proposed algorithm enables the car-like robot to navigate in a completely unknown environment using only the range sensor information. The car-like robot uses the local range sensor view to determine the local path so that it moves towards the goal. To guarantee that the robot can approach the goal, the two modes of motion are repeated, termed motion-to-goal and wall-following. The motion-to-goal behavior lets the robot directly move toward the goal, and the wall-following behavior makes the robot circumnavigate the obstacle boundary until it meets the leaving condition. For each behavior, the nonholonomic motion for the car-like robot is planned in terms of the instantaneous turning radius. The proposed algorithm is implemented to the real robot and the experimental results show the performance of proposed algorithm.
Abstract: In this study, the effect of mechanical activation on the synthesis of Fe3Al/Al2O3 nanocomposite has been investigated by using mechanochemical method. For this purpose, Aluminum powder and hematite as precursors, with stoichiometric ratio, have been utilized and other effective parameters in milling process were kept constant. Phase formation analysis, crystallite size measurement and lattice strain were studied by X-ray diffraction (XRD) by using Williamson-Hall method as well as microstructure and morphology were explored by Scanning electron microscopy (SEM). Also, Energy-dispersive X-ray spectroscopy (EDX) analysis was used in order to probe the particle distribution. The results showed that after 30-hour milling, the reaction was started, combustibly done and completed.
Abstract: The importance of supply chain and logistics
management has been widely recognised. Effective management of
the supply chain can reduce costs and lead times and improve
responsiveness to changing customer demands. This paper proposes a
multi-matrix real-coded Generic Algorithm (MRGA) based
optimisation tool that minimises total costs associated within supply
chain logistics. According to finite capacity constraints of all parties
within the chain, Genetic Algorithm (GA) often produces infeasible
chromosomes during initialisation and evolution processes. In the
proposed algorithm, chromosome initialisation procedure, crossover
and mutation operations that always guarantee feasible solutions
were embedded. The proposed algorithm was tested using three sizes
of benchmarking dataset of logistic chain network, which are typical
of those faced by most global manufacturing companies. A half
fractional factorial design was carried out to investigate the influence
of alternative crossover and mutation operators by varying GA
parameters. The analysis of experimental results suggested that the
quality of solutions obtained is sensitive to the ways in which the
genetic parameters and operators are set.
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.