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: Given the importance of ports as links in the global
supply chains and because they are key elements to induce
competitiveness in their hinterlands, the number of studies devoted to
port governance, management and operations has increased in the last
decades. Some of these studies address the port governance model as
an element to improve coordination among the actors of the portlogistics
chain and to generate a better port performance. In this
context, the present study analyzes the governance of Port of Santos
through individual interviews with port managers, based on a
conceptual model that considers the key dimensions associated with
port governance. The results reinforce the usefulness of the applied
model and highlight some existing improvement opportunities in the
port studied.
Abstract: Strong anion exchange resins with QN+OH-, have the
potential to be developed and employed as heterogeneous catalyst for
transesterification, as they are chemically stable to leaching of the
functional group. Nine different SIERs (SIER1-9) with QN+OH-were
prepared by suspension polymerization of vinylbenzyl chloridedivinylbenzene
(VBC-DVB) copolymers in the presence of n-heptane
(pore-forming agent). The amine group was successfully grafted into
the polymeric resin beads through functionalization with
trimethylamine. These SIERs are then used as a catalyst for the
transesterification of triacetin with methanol. A set of differential
equations that represents the Langmuir-Hinshelwood-Hougen-
Watson (LHHW) and Eley-Rideal (ER) models for the
transesterification reaction were developed. These kinetic models of
LHHW and ER were fitted to the experimental data. Overall, the
synthesized ion exchange resin-catalyzed reaction were welldescribed
by the Eley-Rideal model compared to LHHW models,
with sum of square error (SSE) of 0.742 and 0.996, respectively.
Abstract: Factors affecting construction unit cost vary
depending on a country’s political, economic, social and
technological inclinations. Factors affecting construction costs have
been studied from various perspectives. Analysis of cost factors
requires an appreciation of a country’s practices. Identified cost
factors provide an indication of a country’s construction economic
strata. The purpose of this paper is to identify the essential factors
that affect unit cost estimation and their breakdown using artificial
neural networks. Twenty five (25) identified cost factors in road
construction were subjected to a questionnaire survey and employing
SPSS factor analysis the factors were reduced to eight. The 8 factors
were analysed using neural network (NN) to determine the
proportionate breakdown of the cost factors in a given construction
unit rate. NN predicted that political environment accounted 44% of
the unit rate followed by contractor capacity at 22% and financial
delays, project feasibility and overhead & profit each at 11%. Project
location, material availability and corruption perception index had
minimal impact on the unit cost from the training data provided.
Quantified cost factors can be incorporated in unit cost estimation
models (UCEM) to produce more accurate estimates. This can create
improvements in the cost estimation of infrastructure projects and
establish a benchmark standard to assist the process of alignment of
work practises and training of new staff, permitting the on-going
development of best practises in cost estimation to become more
effective.
Abstract: Artificial Neural Network (ANN) can be trained using
back propagation (BP). It is the most widely used algorithm for
supervised learning with multi-layered feed-forward networks.
Efficient learning by the BP algorithm is required for many practical
applications. The BP algorithm calculates the weight changes of
artificial neural networks, and a common approach is to use a twoterm
algorithm consisting of a learning rate (LR) and a momentum
factor (MF). The major drawbacks of the two-term BP learning
algorithm are the problems of local minima and slow convergence
speeds, which limit the scope for real-time applications. Recently the
addition of an extra term, called a proportional factor (PF), to the
two-term BP algorithm was proposed. The third increases the speed
of the BP algorithm. However, the PF term also reduces the
convergence of the BP algorithm, and criteria for evaluating
convergence are required to facilitate the application of the three
terms BP algorithm. Although these two seem to be closely related,
as described later, we summarize various improvements to overcome
the drawbacks. Here we compare the different methods of
convergence of the new three-term BP algorithm.
Abstract: Liposome plays an important role in medical and
pharmaceutical science as e.g. nano scale drug carriers. Liposomes
are vesicles of varying size consisting of a spherical lipid bilayer and
an aqueous inner compartment. Magnet-driven liposome used for the
targeted delivery of drugs to organs and tissues. These liposome
preparations contain encapsulated drug components and finely
dispersed magnetic particles.
Liposomes are vesicles of varying size consisting of a spherical
lipid bilayer and an aqueous inner compartment that are generated in
vitro. These are useful in terms of biocompatibility, biodegradability,
and low toxicity, and can control biodistribution by changing the size,
lipid composition, and physical characteristics. Furthermore,
liposomes can entrap both hydrophobic and hydrophilic drugs and are
able to continuously release the entrapped substrate, thus being useful
drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles
that encapsulate magneticor paramagnetic nanoparticles. They are
applied as contrast agents for magnetic resonance imaging (MRI).
The biological synthesis of nanoparticles using plant extracts plays
an important role in the field of nanotechnology. Green-synthesized
magnetite nanoparticles-protein hybrid has been produced by treating
Iron (III) / Iron (II) chloride with the leaf extract of Datura inoxia.
The phytochemicals present in the leaf extracts act as a reducing as
well stabilizing agents preventing agglomeration, which include
flavonoids, phenolic compounds, cardiac glycosides, proteins and
sugars.
The magnetite nanoparticles-protein hybrid has been trapped
inside the aqueous core of the liposome prepared by reversed phase
evaporation (REV) method using oleic and linoleic acid which has
been shown to be driven under magnetic field confirming the
formation magnetic liposome (ML). Chemical characterization of
stealth magnetic liposome has been performed by breaking the
liposome and release of magnetic nanoparticles. The presence iron
has been confirmed by colour complex formation with KSCN and
UV-Vis study using spectrophotometer Cary 60, Agilent.
This magnet driven liposome using nanoparticles-protein hybrid
can be a smart vesicles for the targeted drug delivery.
Abstract: Many wireless sensor network applications require
K-coverage of the monitored area. In this paper, we propose a
scalable harmony search based algorithm in terms of execution
time, K-Coverage Enhancement Algorithm (KCEA), it attempts to
enhance initial coverage, and achieve the required K-coverage degree
for a specific application efficiently. Simulation results show that
the proposed algorithm achieves coverage improvement of 5.34%
compared to K-Coverage Rate Deployment (K-CRD), which achieves
1.31% when deploying one additional sensor. Moreover, the proposed
algorithm is more time efficient.
Abstract: The recommended limit for cadmium concentration in
potable water is less than 0.005 mg/L. A continuous biosorption
process using indigenous red seaweed, Gracilaria corticata, was
performed to remove cadmium from the potable water. The process
was conducted under fixed conditions and the breakthrough curves
were achieved for three consecutive sorption-desorption cycles. A
modeling based on Artificial Neural Network (ANN) was employed
to fit the experimental breakthrough data. In addition, a simplified
semi empirical model, Thomas, was employed for this purpose. It
was found that ANN well described the experimental data (R2>0.99)
while the Thomas prediction were a bit less successful with R2>0.97.
The adjusted design parameters using the nonlinear form of Thomas
model was in a good agreement with the experimentally obtained
ones. The results approve the capability of ANN to predict the
cadmium concentration in potable water.
Abstract: Nowadays, Photovoltaic-PV Farms/ Parks and large
PV-Smart Grid Interface Schemes are emerging and commonly
utilized in Renewable Energy distributed generation. However, PVhybrid-
Dc-Ac Schemes using interface power electronic converters
usually has negative impact on power quality and stabilization of
modern electrical network under load excursions and network fault
conditions in smart grid. Consequently, robust FACTS based
interface schemes are required to ensure efficient energy utilization
and stabilization of bus voltages as well as limiting switching/fault
onrush current condition. FACTS devices are also used in smart grid-
Battery Interface and Storage Schemes with PV-Battery Storage
hybrid systems as an elegant alternative to renewable energy
utilization with backup battery storage for electric utility energy and
demand side management to provide needed energy and power
capacity under heavy load conditions. The paper presents a robust
interface PV-Li-Ion Battery Storage Interface Scheme for
Distribution/Utilization Low Voltage Interface using FACTS
stabilization enhancement and dynamic maximum PV power tracking
controllers.
Digital simulation and validation of the proposed scheme is done
using MATLAB/Simulink software environment for Low Voltage-
Distribution/Utilization system feeding a hybrid Linear-Motorized
inrush and nonlinear type loads from a DC-AC Interface VSC-6-
pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion
Storage Battery.
Abstract: In this work, neural networks methods MLP type were
applied to a database from an array of six sensors for the detection of
three toxic gases. The choice of the number of hidden layers and the
weight values are influential on the convergence of the learning
algorithm. We proposed, in this article, a mathematical formula to
determine the optimal number of hidden layers and good weight
values based on the method of back propagation of errors. The results
of this modeling have improved discrimination of these gases and
optimized the computation time. The model presented here has
proven to be an effective application for the fast identification of
toxic gases.
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: The use of eXtensible Markup Language (XML) in
web, business and scientific databases lead to the development of
methods, techniques and systems to manage and analyze XML data.
Semi-structured documents suffer due to its heterogeneity and
dimensionality. XML structure and content mining represent
convergence for research in semi-structured data and text mining. As
the information available on the internet grows drastically, extracting
knowledge from XML documents becomes a harder task. Certainly,
documents are often so large that the data set returned as answer to a
query may also be very big to convey the required information. To
improve the query answering, a Semantic Tree Based Association
Rule (STAR) mining method is proposed. This method provides
intentional information by considering the structure, content and the
semantics of the content. The method is applied on Reuter’s dataset
and the results show that the proposed method outperforms well.
Abstract: A field experiment was carried out at Arab El-
Awammer Research Station, Agric. Res. Center. Assiut Governorate
during summer seasons of 2013 and 2014. The present study assessed
the effect of cowpea with maize intercropping on yield and its
components. The experiment comprised of three treatments (sole
cowpea, sole maize and cowpea-maize intercrop). The experimental
design was a randomized complete block with four replications.
Results indicated that intercropped maize plants with cowpea,
exhibited greater potentiality and resulted in higher values of most of
the studied criteria viz., plant height, number of ears/plant, number of
rows/ear, number of grains/row, grains weight/ear, 100–grain weight
and straw and grain yields. Fresh and dry forage yields of cowpea
were lower in intercropping with maize than sole. Furthermore, the
combined of the two seasons revealed that the total Land Equivalent
Ratio (LER) between cowpea and maize was 1.65. The Aggressivity
(A) maize was 0.45 and cowpea was -0.45. This showed that maize
was the dominant crop, whereas cowpea was the dominated. The
Competitive Ratio (CR) indicated that maize more competitive than
cowpea, maize was 1.75 and cowpea was 0.57. The Actual Yield
Loss (AYL) maize was 0.05 and cowpea was -0.40. The Monetary
Advantage Index (MAI) was 2360.80.
Abstract: The IEEE 802.22 working group aims to drive the
Digital Video Broadcasting-Terrestrial (DVB-T) bands for data
communication to the rural area without interfering the TV broadcast.
In this paper, we arrive at a closed-form expression for average
detection probability of Fusion center (FC) with multiple antenna
over the κ − μ fading channel model. We consider a centralized
cooperative multiple antenna network for reporting. The DVB-T
samples forwarded by the secondary user (SU) were combined using
Maximum ratio combiner at FC, an energy detection is performed
to make the decision. The fading effects of the channel degrades
the detection probability of the FC, a generalized independent and
identically distributed (IID) κ − μ and an additive white Gaussian
noise (AWGN) channel is considered for reporting and sensing
respectively. The proposed system performance is verified through
simulation results.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
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 star network is one of the promising
interconnection networks for future high speed parallel computers, it
is expected to be one of the future-generation networks. The star
network is both edge and vertex symmetry, it was shown to have
many gorgeous topological proprieties also it is owns hierarchical
structure framework. Although much of the research work has been
done on this promising network in literature, it still suffers from
having enough algorithms for load balancing problem. In this paper
we try to work on this issue by investigating and proposing an
efficient algorithm for load balancing problem for the star network.
The proposed algorithm is called Star Clustered Dimension Exchange
Method SCDEM to be implemented on the star network. The
proposed algorithm is based on the Clustered Dimension Exchange
Method (CDEM). The SCDEM algorithm is shown to be efficient in
redistributing the load balancing as evenly as possible among all
nodes of different factor networks.
Abstract: To develop AZ91D magnesium alloys with improved
properties, we have applied TiN and VN/TiN multilayer coatings
using DC magnetron sputter technique. Coating structure, surface
morphology, chemical bonding and corrosion resistance of coatings
were analyzed by x-ray diffraction (XRD), scanning electron
microscope (SEM), x-ray photoelectron spectroscopy (XPS), and
tafel extrapolation method, respectively. XPS analysis reveal that VN
overlayer reacts with oxygen at the VN/TiN interface and forms more
stable TiN layer. Morphological investigations and the corrosion
results show that VN/TiN multilayer thin film coatings are quite
effective to optimize the corrosion resistance of Mg alloys.
Abstract: The final step to complete the “Analytical Systems
Engineering Process” is the “Allocated Architecture” in which all
Functional Requirements (FRs) of an engineering system must be
allocated into their corresponding Physical Components (PCs). At
this step, any design for developing the system’s allocated
architecture in which no clear pattern of assigning the exclusive
“responsibility” of each PC for fulfilling the allocated FR(s) can be
found is considered a poor design that may cause difficulties in
determining the specific PC(s) which has (have) failed to satisfy a
given FR successfully. The present study utilizes the Axiomatic
Design method principles to mathematically address this problem and
establishes an “Axiomatic Model” as a solution for reaching good
alternatives for developing the allocated architecture. This study
proposes a “loss Function”, as a quantitative criterion to monetarily
compare non-ideal designs for developing the allocated architecture
and choose the one which imposes relatively lower cost to the
system’s stakeholders. For the case-study, we use the existing design
of U. S. electricity marketing subsystem, based on data provided by
the U.S. Energy Information Administration (EIA). The result for
2012 shows the symptoms of a poor design and ineffectiveness due to
coupling among the FRs of this subsystem.
Abstract: Rhodamine B (RB) is a toxic dye used extensively in
textile industry, which must be remediated before its drainage to
environment. In the present study, supported gold nanoparticles on
commercially available titania and zincite were successfully prepared
and then their activity on the photodegradation of RB under UV A
light irradiation were evaluated. The synthesized photocatalysts were
characterized by ICP, BET, XRD, and TEM. Kinetic results showed
that Au/TiO2 was an inferior photocatalyst to Au/ZnO. This
observation could be attributed to the strong reflection of UV
irradiation by gold nanoparticles over TiO2 support.