Abstract: This study is concerned with the optimization of
fermentation parameters for the hyper production of mannanase from
Fusarium oxysporum SS-25 employing two step statistical strategy
and kinetic characterization of crude enzyme preparation. The
Plackett-Burman design used to screen out the important factors in
the culture medium revealed 20% (w/w) wheat bran, 2% (w/w) each
of potato peels, soyabean meal and malt extract, 1% tryptone, 0.14%
NH4SO4, 0.2% KH2PO4, 0.0002% ZnSO4, 0.0005% FeSO4, 0.01%
MnSO4, 0.012% SDS, 0.03% NH4Cl, 0.1% NaNO3 in brewer’s spent
grain based medium with 50% moisture content, inoculated with
2.8×107 spores and incubated at 30oC for 6 days to be the main
parameters influencing the enzyme production. Of these factors, four
variables including soyabean meal, FeSO4, MnSO4 and NaNO3 were
chosen to study the interactive effects and their optimum levels in
central composite design of response surface methodology with the
final mannanase yield of 193 IU/gds. The kinetic characterization
revealed the crude enzyme to be active over broader temperature and
pH range. This could result in 26.6% reduction in kappa number with
4.93% higher tear index and 1% increase in brightness when used to
treat the wheat straw based kraft pulp. The hydrolytic potential of
enzyme was also demonstrated on both locust bean gum and guar
gum.
Abstract: The emerging Cognitive Radio is combo of both the
technologies i.e. Radio dynamics and software technology. It involve
wireless system with efficient coding, designing, and making them
artificial intelligent to take the decision according to the surrounding
environment and adopt themselves accordingly, so as to deliver the
best QoS. This is the breakthrough from fixed hardware and fixed
utilization of the spectrum. This software-defined approach of
research is centralized at user-definition and application driven
model, various software method are used for the optimization of the
wireless communication. This paper focused on the Spectrum
allocation technique using genetic algorithm GA to evolve radio,
represented by chromosomes. The chromosomes gene represents the
adjustable parameters in given radio and by using GA, evolving over
the generations, the optimized set of parameters are evolved, as per
the requirement of user and availability of the spectrum, in our
prototype the gene consist of 6 different parameters, and the best set
of parameters are evolved according to the application need and
availability of the spectrum holes and thus maintaining best QoS for
user, simultaneously maintaining licensed user rights. The analyzing
tool Matlab is used for the performance of the prototype.
Abstract: Parameters of flow are calculated in vaneless diffusers
with relative width 0,014–0,10. Inlet angles of flow and similarity
criteria were varied. There is information on flow separation,
boundary layer development, configuration of streamlines.
Polytrophic efficiency, loss coefficient and recovery coefficient are
used to compare effectiveness of diffusers. The sample of
optimization of narrow diffuser with conical walls is presented. Three
wide diffusers with narrowing walls are compared. The work is made
in the R&D laboratory “Gas dynamics of turbo machines” of the TU
SPb.
Abstract: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
Abstract: This paper presents an evolutionary algorithm for
solving multi-objective optimization problems-based artificial neural
network (ANN). The multi-objective evolutionary algorithm used in
this study is genetic algorithm while ANN used is radial basis
function network (RBFN). The proposed algorithm named memetic
elitist Pareto non-dominated sorting genetic algorithm-based RBFN
(MEPGAN). The proposed algorithm is implemented on medical
diseases problems. The experimental results indicate that the
proposed algorithm is viable, and provides an effective means to
design multi-objective RBFNs with good generalization capability
and compact network structure. This study shows that MEPGAN
generates RBFNs coming with an appropriate balance between
accuracy and simplicity, comparing to the other algorithms found in
literature.
Abstract: Assembly line balancing problem is aimed to divide
the tasks among the stations in assembly lines and optimize some
objectives. In assembly lines the workload on stations is different
from each other due to different tasks times and the difference in
workloads between stations can cause blockage or starvation in some
stations in assembly lines. Buffers are used to store the semi-finished
parts between the stations and can help to smooth the assembly
production. The assembly line balancing and buffer sizing problem
can affect the throughput of the assembly lines. Assembly line
balancing and buffer sizing problems have been studied separately in
literature and due to their collective contribution in throughput rate of
assembly lines, balancing and buffer sizing problem are desired to
study simultaneously and therefore they are considered concurrently
in current research. Current research is aimed to maximize
throughput, minimize total size of buffers in assembly line and
minimize workload variations in assembly line simultaneously. A
multi objective optimization objective is designed which can give
better Pareto solutions from the Pareto front and a simple example
problem is solved for assembly line balancing and buffer sizing
simultaneously. Current research is significant for assembly line
balancing research and it can be significant to introduce optimization
approaches which can optimize current multi objective problem in
future.
Abstract: Risperidone (RISP) is an antipsychotic agent and has
low water solubility and nontargeted delivery results in numerous
side effects. Hence, an attempt was made to develop SLNs hydrogel
for intranasal delivery of RISP to achieve maximum bioavailability
and reduction of side effects. RISP loaded SLNs composed of 1.65%
(w/v) lipid mass were produced by high shear homogenization (HSH)
coupled ultrasound (US) method using glycerylmonostearate (GMS)
or Imwitor 900K (solid lipid). The particles were loaded with 0.2%
(w/v) of the RISP & surface-tailored with a 2.02% (w/v) non-ionic
surfactant Tween® 80. Optimization was done using 32 factorial
design using Design Expert® software. The prepared SLNs
dispersion incorporated into Polycarbophil AA1 hydrogel (0.5%
w/v). The final gel formulation was evaluated for entrapment
efficiency, particle size, rheological properties, X ray diffraction, in
vitro diffusion, ex vivo permeation using sheep nasal mucosa and
histopathological studies for nasocilliary toxicity. The entrapment
efficiency of optimized SLNs was found to be 76 ± 2%,
polydispersity index
Abstract: Chemical Reaction Optimization (CRO) is an
optimization metaheuristic inspired by the nature of chemical
reactions as a natural process of transforming the substances from
unstable to stable states. Starting with some unstable molecules with
excessive energy, a sequence of interactions takes the set to a state of
minimum energy. Researchers reported successful application of the
algorithm in solving some engineering problems, like the quadratic
assignment problem, with superior performance when compared with
other optimization algorithms. We adapted this optimization
algorithm to the Printed Circuit Board Drilling Problem (PCBDP)
towards reducing the drilling time and hence improving the PCB
manufacturing throughput. Although the PCBDP can be viewed as
instance of the popular Traveling Salesman Problem (TSP), it has
some characteristics that would require special attention to the
transactions that explore the solution landscape. Experimental test
results using the standard CROToolBox are not promising for
practically sized problems, while it could find optimal solutions for
artificial problems and small benchmarks as a proof of concept.
Abstract: Wireless mesh networking is rapidly gaining in
popularity with a variety of users: from municipalities to enterprises,
from telecom service providers to public safety and military
organizations. This increasing popularity is based on two basic facts:
ease of deployment and increase in network capacity expressed in
bandwidth per footage; WMNs do not rely on any fixed
infrastructure. Many efforts have been used to maximizing
throughput of the network in a multi-channel multi-radio wireless
mesh network. Current approaches are purely based on either static or
dynamic channel allocation approaches. In this paper, we use a
hybrid multichannel multi radio wireless mesh networking
architecture, where static and dynamic interfaces are built in the
nodes. Dynamic Adaptive Channel Allocation protocol (DACA), it
considers optimization for both throughput and delay in the channel
allocation. The assignment of the channel has been allocated to be codependent
with the routing problem in the wireless mesh network and
that should be based on passage flow on every link. Temporal and
spatial relationship rises to re compute the channel assignment every
time when the pattern changes in mesh network, channel assignment
algorithms assign channels in network. In this paper a computing
path which captures the available path bandwidth is the proposed
information and the proficient routing protocol based on the new path
which provides both static and dynamic links. The consistency
property guarantees that each node makes an appropriate packet
forwarding decision and balancing the control usage of the network,
so that a data packet will traverse through the right path.
Abstract: This paper proposed a silicon controller rectifier (SCR)
based ESD protection device to protect low voltage ESD for integrated
circuit. The proposed ESD protection device has low trigger voltage
and high holding voltage compared with conventional SCR-based
ESD protection devices. The proposed ESD protection circuit is
verified and compared by TCAD simulation. This paper verified
effective low voltage ESD characteristics with low trigger voltage of
5.79V and high holding voltage of 3.5V through optimization
depending on design variables (D1, D2, D3 and D4).
Abstract: This paper presents optimization of makespan for ‘n’
jobs and ‘m’ machines flexible job shop scheduling problem with
sequence dependent setup time using genetic algorithm (GA)
approach. A restart scheme has also been applied to prevent the
premature convergence. Two case studies are taken into
consideration. Results are obtained by considering crossover
probability (pc = 0.85) and mutation probability (pm = 0.15). Five
simulation runs for each case study are taken and minimum value
among them is taken as optimal makespan. Results indicate that
optimal makespan can be achieved with more than one sequence of
jobs in a production order.
Abstract: Starting in 2020, an EU-wide CO2-limitation of
95 g/km is scheduled for the average of an OEMs passenger car fleet.
Taking that into consideration additional improvement measures of
the Diesel cycle are necessary in order to reduce fuel consumption
and emissions while boosting, or at the least, keeping performance
values at the same time.
The present article deals with the possibilities of an optimized
air/water charge air cooler, also called iCAC (indirect Charge Air
Cooler) for a Diesel passenger car amongst extreme-boundary
conditions. In this context, the precise objective was to show the
impact of improved intercooling with reference to the engine working
process (fuel consumption and NOx-emissions). Several extremeboundaries
- e.g. varying ambient temperatures or mountainous
routes - that will become very important in the near future regarding
RDE (Real Driving emissions) were subject of the investigation.
With the introduction of RDE in 2017 (EU6c measure), the
controversial NEDC (New European Driving Cycle) will belong to
the past and the OEMs will have to avoid harmful emissions in any
conceivable real life situation.
This is certainly going to lead to optimization-measurements at the
powertrain, which again is going to make the implementation of
iCACs, presently solely used for the premium class, more and more
attractive for compact class cars. The investigations showed a benefit
in FC between 1 and 3% for the iCAC in real world conditions.
Abstract: In this paper, student admission process is studied to
optimize the assignment of vacant seats with three main objectives.
Utilizing all vacant seats, satisfying all programs of study admission
requirements and maintaining fairness among all candidates are the
three main objectives of the optimization model. Seat Assignment
Method (SAM) is used to build the model and solve the optimization
problem with help of Northwest Coroner Method and Least Cost
Method. A closed formula is derived for applying the priority of
assigning seat to candidate based on SAM.
Abstract: Container handling problems at container terminals
are NP-hard problems. This paper presents an approach using
discrete-event simulation modeling to optimize solution for storage
space allocation problem, taking into account all various interrelated
container terminal handling activities. The proposed approach is
applied on a real case study data of container terminal at Alexandria
port. The computational results show the effectiveness of the
proposed model for optimization of storage space allocation in
container terminal where 54% reduction in containers handling time
in port is achieved.
Abstract: The ad hoc networks are the future of wireless
technology as everyone wants fast and accurate error free information
so keeping this in mind Bit Error Rate (BER) and power is optimized
in this research paper by using the Genetic Algorithm (GA). The
digital modulation techniques used for this paper are Binary Phase
Shift Keying (BPSK), M-ary Phase Shift Keying (M-ary PSK), and
Quadrature Amplitude Modulation (QAM). This work is
implemented on Wireless Ad Hoc Networks (WLAN). Then it is
analyze which modulation technique is performing well to optimize
the BER and power of WLAN.
Abstract: Femtocells are regarded as a milestone for next
generation cellular networks. As femtocells are deployed in an
unplanned manner, there is a chance of assigning same resource to
neighboring femtocells. This scenario may induce co-channel
interference and may seriously affect the service quality of
neighboring femtocells. In addition, the dominant transmit power of a
femtocell will induce co-tier interference to neighboring femtocells.
Thus to jointly handle co-tier and co-channel interference, we
propose an interference-free power and resource block allocation
(IFPRBA) algorithm for closely located, closed access femtocells.
Based on neighboring list, inter-femto-base station distance and
uplink noise power, the IFPRBA algorithm assigns non-interfering
power and resource to femtocells. The IFPRBA algorithm also
guarantees the quality of service to femtouser based on the
knowledge of resource requirement, connection type, and the
tolerable delay budget. Simulation result shows that the interference
power experienced in IFPRBA algorithm is below the tolerable
interference power and hence the overall service success ratio, PRB
efficiency and network throughput are maximum when compared to
conventional resource allocation framework for femtocell (RAFF)
algorithm.
Abstract: The paper involves a chain of activities from
synthesis, establishment of the methodology for characterization and
testing of novel protective materials through the pilot production and
application on model supports.
It summarizes the results regarding the development of the pilot
production protocol for newly developed self-cleaning materials. The
optimization of the production parameters was completed in order to
improve the most important functional properties (mineralogy
characteristics, particle size, self-cleaning properties and
photocatalytic activity) of the newly designed nanocomposite
material.
Abstract: Axial flow fans, while incapable of developing high
pressures, they are well suitable for handling large volumes of air at
relatively low pressures. In general, they are low in cost and possess
good efficiency, and can have blades of airfoil shape. Axial flow fans
show good efficiencies, and can operate at high static pressures if
such operation is necessary. Our objective is to model and analyze
the flow through AXIAL FANS using CFD Software and draw
inference from the obtained results, so as to get maximum efficiency.
The performance of an axial fan was simulated using CFD and the
effect of variation of different parameters such as the blade number,
noise level, velocity, temperature and pressure distribution on the
blade surface was studied. This paper aims to present a final 3D CAD
model of axial flow fan. Adapting this model to the available
components in the market, the first optimization was done. After this
step, CFX flow solver is used to do the necessary numerical analyses
on the aerodynamic performance of this model. This analysis results
in a final optimization of the proposed 3D model which is presented
in this article.
Abstract: Now-a-days autonomous mobile robots have found
applications in diverse fields. An autonomous robot system must be
able to behave in an intelligent manner to deal with complex and
changing environment. This work proposes the performance of path
planning and navigation of autonomous mobile robot using
Gravitational Search Algorithm (GSA), Simulated Annealing (SA)
and Particle Swarm optimization (PSO) based intelligent controllers
in an unstructured environment. The approach not only finds a valid
collision free path but also optimal one. The main aim of the work is
to minimize the length of the path and duration of travel from a
starting point to a target while moving in an unknown environment
with obstacles without collision. Finally, a comparison is made
between the three controllers, it is found that the path length and time
duration made by the robot using GSA is better than SA and PSO
based controllers for the same work.
Abstract: This paper proposes a new technique to design a
fixed-structure robust loop shaping controller for the pneumatic
servosystem. In this paper, a new method based on a particle swarm
optimization (PSO) algorithm for tuning the weighting function
parameters to design an H∞ controller is presented. The PSO
algorithm is used to minimize the infinity norm of the transfer
function of the nominal closed loop system to obtain the optimal
parameters of the weighting functions. The optimal stability margin is
used as an objective in PSO for selecting the optimal weighting
parameters; it is shown that the proposed method can simplify the
design procedure of H∞ control to obtain optimal robust controller for
pneumatic servosystem. In addition, the order of the proposed
controller is much lower than that of the conventional robust loop
shaping controller, making it easy to implement in practical works.
Also two-degree-of-freedom (2DOF) control design procedure is
proposed to improve tracking performance in the face of noise and
disturbance. Result of simulations demonstrates the advantages of the
proposed controller in terms of simple structure and robustness
against plant perturbations and disturbances.