Abstract: Shape memory alloy (SMA) actuators have found a
wide range of applications due to their unique properties such as high
force, small size, lightweight and silent operation. This paper presents
the development of compact (SMA) actuator and cooling system in
one unit. This actuator is developed for multi-fingered hand. It
consists of nickel-titanium (Nitinol) SMA wires in compact forming.
The new arrangement insulates SMA wires from the human body by
housing it in a heat sink and uses a thermoelectric device for rejecting
heat to improve the actuator performance. The study uses
optimization methods for selecting the SMA wires geometrical
parameters and the material of a heat sink. The experimental work
implements the actuator prototype and measures its response.
Abstract: In the literature of information theory, there is
necessity for comparing the different measures of fuzzy entropy and
this consequently, gives rise to the need for normalizing measures of
fuzzy entropy. In this paper, we have discussed this need and hence
developed some normalized measures of fuzzy entropy. It is also
desirable to maximize entropy and to minimize directed divergence
or distance. Keeping in mind this idea, we have explained the method
of optimizing different measures of fuzzy entropy.
Abstract: In this paper we use exponential particle swarm
optimization (EPSO) to cluster data. Then we compare between
(EPSO) clustering algorithm which depends on exponential variation
for the inertia weight and particle swarm optimization (PSO)
clustering algorithm which depends on linear inertia weight. This
comparison is evaluated on five data sets. The experimental results
show that EPSO clustering algorithm increases the possibility to find
the optimal positions as it decrease the number of failure. Also show
that (EPSO) clustering algorithm has a smaller quantization error
than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm
more accurate than (PSO) clustering algorithm.
Abstract: This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.
Abstract: It is observed that the Weighted least-square (WLS)
technique, including the modifications, results in equiripple error
curve. The resultant error as a percent of the ideal value is highly
non-uniformly distributed over the range of frequencies for which the
differentiator is designed. The present paper proposes a modification
to the technique so that the optimization procedure results in lower
maximum relative error compared to the ideal values. Simulation
results for first order as well as higher order differentiators are given
to illustrate the excellent performance of the proposed method.
Abstract: This was the first document revealing the
investigation of protein hydrolysate production optimization from J.
curcas cake. Proximate analysis of raw material showed 18.98%
protein, 5.31% ash, 8.52% moisture and 12.18% lipid. The
appropriate protein hydrolysate production process began with
grinding the J. curcas cake into small pieces. Then it was suspended
in 2.5% sodium hydroxide solution with ratio between solution/ J.
curcas cake at 80:1 (v/w). The hydrolysis reaction was controlled at
temperature 50 °C in water bath for 45 minutes. After that, the
supernatant (protein hydrolysate) was separated using centrifuge at
8000g for 30 minutes. The maximum yield of resulting protein
hydrolysate was 73.27 % with 7.34% moisture, 71.69% total protein,
7.12% lipid, 2.49% ash. The product was also capable of well
dissolving in water.
Abstract: This paper will discuss about an active power generator scheduling method in order to increase the limit level of steady state systems. Some power generator optimization methods such as Langrange, PLN (Indonesian electricity company) Operation, and the proposed Z-Thevenin-based method will be studied and compared in respect of their steady state aspects. A method proposed in this paper is built upon the thevenin equivalent impedance values between each load respected to each generator. The steady state stability index obtained with the REI DIMO method. This research will review the 500kV-Jawa-Bali interconnection system. The simulation results show that the proposed method has the highest limit level of steady state stability compared to other optimization techniques such as Lagrange, and PLN operation. Thus, the proposed method can be used to create the steady state stability limit of the system especially in the peak load condition.
Abstract: In this paper, a PSO-based approach is proposed to
derive a digital controller for redesigned digital systems having an interval plant based on resemblance of the extremal gain/phase
margins. By combining the interval plant and a controller as an interval system, extremal GM/PM associated with the loop transfer function
can be obtained. The design problem is then formulated as an optimization problem of an aggregated error function revealing the deviation on the extremal GM/PM between the redesigned digital
system and its continuous counterpart, and subsequently optimized by
a proposed PSO to obtain an optimal set of parameters for the digital controller. Computer simulations have shown that frequency
responses of the redesigned digital system having an interval plant bare a better resemblance to its continuous-time counter part by the incorporation of a PSO-derived digital controller in comparison to those obtained using existing open-loop discretization methods.
Abstract: Increasing energy absorption is a significant parameter
in vehicle design. Absorbing more energy results in decreasing
occupant damage. Limitation of the deflection in a side impact results
in decreased energy absorption (SEA) and increased peak load (PL).
Hence a high crash force jeopardizes passenger safety and vehicle
integrity. The aims of this paper are to determine suitable dimensions
and material of a square beam subjected to side impact, in order to
maximize SEA and minimize PL. To achieve this novel goal, the
geometric parameters of a square beam are optimized using the
response surface method (RSM).multi-objective optimization is
performed, and the optimum design for different response features is
obtained.
Abstract: Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.
Abstract: This paper presents preliminary results regarding system-level power awareness for FPGA implementations in wireless sensor networks. Re-configurability of field programmable gate arrays (FPGA) allows for significant flexibility in its applications to embedded systems. However, high power consumption in FPGA becomes a significant factor in design considerations. We present several ideas and their experimental verifications on how to optimize power consumption at high level of designing process while maintaining the same energy per operation (low-level methods can be used additionally). This paper demonstrates that it is possible to estimate feasible power consumption savings even at the high level of designing process. It is envisaged that our results can be also applied to other embedded systems applications, not limited to FPGA-based.
Abstract: Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.
Abstract: This paper presents an optimal design of linear phase
digital high pass finite impulse response (FIR) filter using Improved
Particle Swarm Optimization (IPSO). 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. An iterative method is introduced to find the
optimal solution of FIR filter design problem. Evolutionary
algorithms like real code genetic algorithm (RGA), particle swarm
optimization (PSO), improved particle swarm optimization (IPSO)
have been used in this work for the design of linear phase high pass
FIR filter. IPSO is an improved PSO that proposes a new definition
for the velocity vector and swarm updating and hence the solution
quality is improved. A comparison of simulation results reveals the
optimization efficacy of the algorithm over the prevailing
optimization techniques for the solution of the multimodal, nondifferentiable,
highly non-linear, and constrained FIR filter design
problems.
Abstract: Modeling of a manufacturing system enables one to
identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper
proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a
static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few
parameters such as utilization, cycle time, throughput, and batch size.
The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far
below the limit value 32%. Therefore, the model developed in this
study is a valuable alternative model in evaluating a manufacturing system
Abstract: In this paper usefulness of quasi-Newton iteration
procedure in parameters estimation of the conditional variance
equation within BHHH algorithm is presented. Analytical solution of
maximization of the likelihood function using first and second
derivatives is too complex when the variance is time-varying. The
advantage of BHHH algorithm in comparison to the other
optimization algorithms is that requires no third derivatives with
assured convergence. To simplify optimization procedure BHHH
algorithm uses the approximation of the matrix of second derivatives
according to information identity. However, parameters estimation in
a/symmetric GARCH(1,1) model assuming normal distribution of
returns is not that simple, i.e. it is difficult to solve it analytically.
Maximum of the likelihood function can be founded by iteration
procedure until no further increase can be found. Because the
solutions of the numerical optimization are very sensitive to the
initial values, GARCH(1,1) model starting parameters are defined.
The number of iterations can be reduced using starting values close
to the global maximum. Optimization procedure will be illustrated in
framework of modeling volatility on daily basis of the most liquid
stocks on Croatian capital market: Podravka stocks (food industry),
Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla
stocks (information-s-communications industry).
Abstract: The essentiality of maintenance assessment and
maintenance optimization in design stage is analyzed, and the existent
problems of conventional maintenance design method are illuminated.
MDMVM (Maintenance Design Method based Virtual Maintenance)
is illuminated, and the process of MDMVM established, and the
MDMVM architecture is given out. The key techniques of MDMVM
are analyzed, and include maintenance design based KBE (Knowledge
Based Engineering) and virtual maintenance based physically
attribute. According to physical property, physically based modeling,
visual object movement control, the simulation of operation force and
maintenance sequence planning method are emphatically illuminated.
Maintenance design system based virtual maintenance is established in
foundation of maintenance design method.
Abstract: Direct fermentation of 226 white rose tapioca stem to
ethanol by Fusarium oxysporum was studied in a batch reactor.
Fermentation of ethanol can be achieved by sequential pretreatment
using dilute acid and dilute alkali solutions using 100 mesh tapioca
stem particles. The quantitative effects of substrate concentration, pH
and temperature on ethanol concentration were optimized using a full
factorial central composite design experiment. The optimum process
conditions were then obtained using response surface methodology.
The quadratic model indicated that substrate concentration of 33g/l,
pH 5.52 and a temperature of 30.13oC were found to be optimum for
maximum ethanol concentration of 8.64g/l. The predicted optimum
process conditions obtained using response surface methodology was
verified through confirmatory experiments. Leudeking-piret model
was used to study the product formation kinetics for the production
of ethanol and the model parameters were evaluated using
experimental data.
Abstract: In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Abstract: In this work, statistical experimental design was
applied for the optimization of medium constituents for Gentamicin
production by Micromsonospora echinospora subs pallida (MTCC
708) in a batch reactor and the results are compared with the ANN
predicted values. By central composite design, 50 experiments are
carried out for five test variables: Starch, Soya bean meal, K2HPO4,
CaCO3 and FeSO4. The optimum condition was found to be: Starch
(8.9,g/L), Soya bean meal (3.3 g/L), K2HPO4 (0.8 g/L), CaCO3 (4
g/L) and FeSO4 (0.03 g/L). At these optimized conditions, the yield
of gentamicin was found to be 1020 mg/L. The R2 values were found
to be 1 for ANN training set, 0.9953 for ANN test set, and 0.9286 for
RSM.
Abstract: To improve the dynamics response of the vehicle
passive suspension, a two-terminal mass is suggested to connect in
parallel with the suspension strut. Three performance criteria, tire grip,
ride comfort and suspension deflection, are taken into consideration to
optimize the suspension parameters. However, the three criteria are
conflicting and non-commensurable. For this reason, the Chebyshev
goal programming method is applied to find the best tradeoff among
the three objectives. A simulation case is presented to describe the
multi-objective optimization procedure. For comparison, the
Chebyshev method is also employed to optimize the design of a
conventional passive suspension. The effectiveness of the proposed
design method has been clearly demonstrated by the result. It is also
shown that the suspension with a two-terminal mass in parallel has
better performance in terms of the three objectives.