Abstract: Estimation time and cost of work completion in a
project and follow up them during execution are contributors to
success or fail of a project, and is very important for project
management team. Delivering on time and within budgeted cost
needs to well managing and controlling the projects. To dealing with
complex task of controlling and modifying the baseline project
schedule during execution, earned value management systems have
been set up and widely used to measure and communicate the real
physical progress of a project. But it often fails to predict the total
duration of the project. In this paper data mining techniques is used
predicting the total project duration in term of Time Estimate At
Completion-EAC (t). For this purpose, we have used a project with
90 activities, it has updated day by day. Then, it is used regular
indexes in literature and applied Earned Duration Method to
calculate time estimate at completion and set these as input data for
prediction and specifying the major parameters among them using
Clem software. By using data mining, the effective parameters on
EAC and the relationship between them could be extracted and it is
very useful to manage a project with minimum delay risks. As we
state, this could be a simple, safe and applicable method in prediction
the completion time of a project during execution.
Abstract: Sustainable development is one of the most debated
issues, recently. In terms of providing more livable Earth continuity,
while Production activities are going on, on the other hand protecting
the environment has importance. As a strategy for sustainable
development, eco-innovation is the application of innovations to
reduce environmental burdens. Endeavors to understand ecoinnovation
processes have been affected from environmental
economics and innovation economics from neoclassical economics,
and evolutionary economics other than neoclassical economics. In
the light of case study analyses, this study aims to display activities
in this field through case studies after explaining the theoretical
framework of eco-innovations. This study consists of five sections
including introduction and conclusion. In the second part of the study
identifications of the concepts related with eco-innovation are
described and eco-innovations are classified. Third section considers
neoclassical and evolutionary approaches from neoclassical
economics and evolutionary economics, respectively. Fourth section
gives the case studies of successful eco-innovations. Last section is
the conclusion part and offers suggestions for future eco-innovation
research according to the theoretical framework and the case studies.
Abstract: Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.
Abstract: Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.
Abstract: Mobile Ad hoc networks (MANETs) are collections
of wireless mobile nodes dynamically reconfiguring and collectively
forming a temporary network. These types of networks assume
existence of no fixed infrastructure and are often useful in battle-field
tactical operations or emergency search-and-rescue type of
operations where fixed infrastructure is neither feasible nor practical.
They also find use in ad hoc conferences, campus networks and
commercial recreational applications carrying multimedia traffic. All
of the above applications of MANETs require guaranteed levels of
performance as experienced by the end-user. This paper focuses on
key challenges in provisioning predetermined levels of such Quality
of Service (QoS). It also identifies functional areas where QoS
models are currently defined and used. Evolving functional areas
where performance and QoS provisioning may be applied are also
identified and some suggestions are provided for further research in
this area. Although each of the above functional areas have been
discussed separately in recent research studies, since these QoS
functional areas are highly correlated and interdependent, a
comprehensive and comparative analysis of these areas and their
interrelationships is desired. In this paper we have attempted to
provide such an overview.
Abstract: Nowadays, HPC, Grid and Cloud systems are evolving
very rapidly. However, the development of infrastructure solutions
related to HPC is lagging behind. While the existing infrastructure is
sufficient for simple cases, many computational problems have more
complex requirements.Such computational experiments use different
resources simultaneously to start a large number of computational
jobs.These resources are heterogeneous. They have different
purposes, architectures, performance and used software.Users need a
convenient tool that allows to describe and to run complex
computational experiments under conditions of HPC environment.
This paper introduces a modularworkflow system called SEGL
which makes it possible to run complex computational experiments
under conditions of a real HPC organization. The system can be used
in a great number of organizations, which provide HPC power.
Significant requirements to this system are high efficiency and
interoperability with the existing HPC infrastructure of the
organization without any changes.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.
Abstract: The process of laser absorption in the skin during
laser irradiation was a critical point in medical application
treatments. Delivery the correct amount of laser light is a critical
element in photodynamic therapy (PDT). More amounts of laser
light able to affect tissues in the skin and small amount not able to
enhance PDT procedure in skin. The knowledge of the skin tone
laser dependent distribution of 635 nm radiation and its penetration
depth in skin is a very important precondition for the investigation of
advantage laser induced effect in (PDT) in epidermis diseases
(psoriasis). The aim of this work was to estimate an optimum effect
of diode laser (635 nm) on the treatment of epidermis diseases in
different color skin. Furthermore, it is to improve safety of laser in
PDT in epidermis diseases treatment. Advanced system analytical
program (ASAP) which is a new approach in investigating the PDT,
dependent on optical properties of different skin color was used in
present work. A two layered Realistic Skin Model (RSM); stratum
corneum and epidermal with red laser (635 nm, 10 mW) were used
for irradiative transfer to study fluence and absorbance in different
penetration for various human skin colors. Several skin tones very
fair, fair, light, medium and dark are used to irradiative transfer. This
investigation involved the principles of laser tissue interaction when
the skin optically injected by a red laser diode. The results
demonstrated that the power characteristic of a laser diode (635 nm)
can affect the treatment of epidermal disease in various color skins.
Power absorption of the various human skins were recorded and
analyzed in order to find the influence of the melanin in PDT
treatment in epidermal disease. A two layered RSM show that the
change in penetration depth in epidermal layer of the color skin has a
larger effect on the distribution of absorbed laser in the skin; this is
due to the variation of the melanin concentration for each color.
Abstract: This paper details the application of a genetic
programming framework for induction of useful classification rules
from a database of income statements, balance sheets, and cash flow
statements for North American public companies. Potentially
interesting classification rules are discovered. Anomalies in the
discovery process merit further investigation of the application of
genetic programming to the dataset for the problem domain.
Abstract: This paper presents the application of an enhanced
Particle Swarm Optimization (EPSO) combined with Gaussian
Mutation (GM) for solving the Dynamic Economic Dispatch (DED)
problem considering the operating constraints of generators. The
EPSO consists of the standard PSO and a modified heuristic search
approaches. Namely, the ability of the traditional PSO is enhanced
by applying the modified heuristic search approach to prevent the
solutions from violating the constraints. In addition, Gaussian
Mutation is aimed at increasing the diversity of global search, whilst
it also prevents being trapped in suboptimal points during search. To
illustrate its efficiency and effectiveness, the developed EPSO-GM
approach is tested on the 3-unit and 10-unit 24-hour systems
considering valve-point effect. From the experimental results, it can
be concluded that the proposed EPSO-GM provides, the accurate
solution, the efficiency, and the feature of robust computation
compared with other algorithms under consideration.
Abstract: Fatigue is the major threat in service of steel structure
subjected to fluctuating loads. With the additional effect of corrosion
and presence of weld joints the fatigue failure may become more
critical in structural steel. One of the apt examples of such structural
is the sailing ship. This is experiencing a constant stress due to
floating and a pulsating bending load due to the waves. This paper
describes an attempt to verify theory of fatigue in fracture mechanics
approach with experimentation to determine the constants of crack
growth curve. For this, specimen is prepared from the ship building
steel and it is subjected to a pulsating bending load with a known
defect. Fatigue crack and its nature is observed in this experiment.
Application of fracture mechanics approach in fatigue with a simple
practical experiment is conducted and constants of crack growth
equation are investigated.
Abstract: Many-core GPUs provide high computing ability and
substantial bandwidth; however, optimizing irregular applications
like SpMV on GPUs becomes a difficult but meaningful task. In this
paper, we propose a novel method to improve the performance of
SpMV on GPUs. A new storage format called HYB-R is proposed to
exploit GPU architecture more efficiently. The COO portion of the
matrix is partitioned recursively into a ELL portion and a COO
portion in the process of creating HYB-R format to ensure that there
are as many non-zeros as possible in ELL format. The method of
partitioning the matrix is an important problem for HYB-R kernel, so
we also try to tune the parameters to partition the matrix for higher
performance. Experimental results show that our method can get
better performance than the fastest kernel (HYB) in NVIDIA-s
SpMV library with as high as 17% speedup.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: Lectins have a good scope in current clinical
microbiology research. In the present study evaluated the
antimicrobial activities of a D-galactose binding lectin (PnL) was
purified from the annelid, Perinereis nuntia (polychaeta) by affinity
chromatography. The molecular mass of the lectin was determined to
be 32 kDa as a single polypeptide by SDS-PAGE under both reducing
and non-reducing conditions. The hemagglutinating activity of the
PnL showed against trypsinized and glutaraldehyde-fixed human
erythrocytes was specifically inhibited by D-Gal, GalNAc,
Galβ1-4Glc and Galα1-6Glc. PnL was evaluated for in vitro
antibacterial screening studies against 11 gram-positive and
gram-negative microorganisms. From the screening results, it was
revealed that PnL exhibited significant antibacterial activity against
gram-positive bacteria. Bacillus megaterium showed the highest
growth inhibition by the lectin (250 μg/disc). However, PnL did not
inhibit the growth of gram-negative bacteria such as Vibrio cholerae
and Pseudomonas sp. PnL was also examined for in vitro antifungal
activity against six fungal phytopathogens. PnL (100 μg/mL) inhibited
the mycelial growth of Alternaria alternata (24.4%). These results
indicate that future findings of lectin applications obtained from
annelids may be of importance to life sciences.
Abstract: The Economic factors are leading to the rise of
infrastructures provides software and computing facilities as a
service, known as cloud services or cloud computing. Cloud services
can provide efficiencies for application providers, both by limiting
up-front capital expenses, and by reducing the cost of ownership over
time. Such services are made available in a data center, using shared
commodity hardware for computation and storage. There is a varied
set of cloud services available today, including application services
(salesforce.com), storage services (Amazon S3), compute services
(Google App Engine, Amazon EC2) and data services (Amazon
SimpleDB, Microsoft SQL Server Data Services, Google-s Data
store). These services represent a variety of reformations of data
management architectures, and more are on the horizon.
Abstract: The main goal in this paper is to quantify the quality of
different techniques for radiation treatment plans, a back-propagation
artificial neural network (ANN) combined with biomedicine theory
was used to model thirteen dosimetric parameters and to calculate
two dosimetric indices. The correlations between dosimetric indices
and quality of life were extracted as the features and used in the ANN
model to make decisions in the clinic. The simulation results show
that a trained multilayer back-propagation neural network model can
help a doctor accept or reject a plan efficiently. In addition, the
models are flexible and whenever a new treatment technique enters
the market, the feature variables simply need to be imported and the
model re-trained for it to be ready for use.
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Stirred tanks have applications in many chemical
processes where mixing is important for the overall performance of
the system. In present work 5%v of the tank is filled by solid particles
with diameter of 700 m that Rushton Turbine and Propeller impeller
is used for stirring. An Eulerian-Eulerian Multi Fluid Model coupled
and for modeling rotating of impeller, moving reference frame
(MRF) technique was used and standard-k- model was selected for
turbulency. Flow field, radial velocity and axial distribution of solid
for both of impellers was investigation and comparison. Comparisons
of simulation results between Rushton Turbine and propeller impeller
shows that final quality of solid-liquid slurry in different rotating
speed for propeller impeller is better than the Rushton Turbine.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: In this paper, we have developed an explicit analytical
drain current model comprising surface channel potential and
threshold voltage in order to explain the advantages of the proposed
Gate Stack Double Diffusion (GSDD) MOSFET design over the
conventional MOSFET with the same geometric specifications that
allow us to use the benefits of the incorporation of the high-k layer
between the oxide layer and gate metal aspect on the immunity of the
proposed design against the self-heating effects. In order to show the
efficiency of our proposed structure, we propose the simulation of the
power chopper circuit. The use of the proposed structure to design a
power chopper circuit has showed that the (GSDD) MOSFET can
improve the working of the circuit in terms of power dissipation and
self-heating effect immunity. The results so obtained are in close
proximity with the 2D simulated results thus confirming the validity
of the proposed model.