Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: The permanent magnet synchronous motor (PMSM) is
very useful in many applications. Vector control of PMSM is popular
kind of its control. In this paper, at first an optimal vector control for
PMSM is designed and then results are compared with conventional
vector control. Then, it is assumed that the measurements are noisy
and linear quadratic Gaussian (LQG) methodology is used to filter
the noises. The results of noisy optimal vector control and filtered
optimal vector control are compared to each other. Nonlinearity of
PMSM and existence of inverter in its control circuit caused that the
system is nonlinear and time-variant. With deriving average model,
the system is changed to nonlinear time-invariant and then the
nonlinear system is converted to linear system by linearization of
model around average values. This model is used to optimize vector
control then two optimal vector controls are compared to each other.
Simulation results show that the performance and robustness to noise
of the control system has been highly improved.
Abstract: This paper presents a method to support dynamic
packing in cases when no collision-free path can be found. The
method, which is primarily based on path planning and shrinking of
geometries, suggests a minimal geometry design change that results
in a collision-free assembly path. A supplementing approach to
optimize geometry design change with respect to redesign cost is
described. Supporting this dynamic packing method, a new method
to shrink geometry based on vertex translation, interweaved with
retriangulation, is suggested. The shrinking method requires neither
tetrahedralization nor calculation of medial axis and it preserves the
topology of the geometry, i.e. holes are neither lost nor introduced.
The proposed methods are successfully applied on industrial
geometries.
Abstract: The Aggregate Production Plan (APP) is a schedule of
the organization-s overall operations over a planning horizon to
satisfy demand while minimizing costs. It is the baseline for any
further planning and formulating the master production scheduling,
resources, capacity and raw material planning. This paper presents a
methodology to model the Aggregate Production Planning problem,
which is combinatorial in nature, when optimized with Genetic
Algorithms. This is done considering a multitude of constraints of
contradictory nature and the optimization criterion – overall cost,
made up of costs with production, work force, inventory, and
subcontracting. A case study of substantial size, used to develop the
model, is presented, along with the genetic operators.
Abstract: This paper introduces a framework based on the collaboration of multi agent and hyper-heuristics to find a solution of the real single machine production problem. There are many techniques used to solve this problem. Each of it has its own advantages and disadvantages. By the collaboration of multi agent system and hyper-heuristics, we can get more optimal solution. The hyper-heuristics approach operates on a search space of heuristics rather than directly on a search space of solutions. The proposed framework consists of some agents, i.e. problem agent, trainer agent, algorithm agent (GPHH, GAHH, and SAHH), optimizer agent, and solver agent. Some low level heuristics used in this paper are MRT, SPT, LPT, EDD, LDD, and MON
Abstract: The study of the transport coefficients in electronic
devices is currently carried out by analytical and empirical models.
This study requires several simplifying assumptions, generally
necessary to lead to analytical expressions in order to study the
different characteristics of the electronic silicon-based devices.
Further progress in the development, design and optimization of
Silicon-based devices necessarily requires new theory and modeling
tools. In our study, we use the PSO (Particle Swarm Optimization)
technique as a computational tool to develop analytical approaches in
order to study the transport phenomenon of the electron in crystalline
silicon as function of temperature and doping concentration. Good
agreement between our results and measured data has been found.
The optimized analytical models can also be incorporated into the
circuits simulators to study Si-based devices without impact on the
computational time and data storage.
Abstract: The review performed on the condition of energy
consumption & rate in Iran, shows that unfortunately the subject of
optimization and conservation of energy in active industries of
country lacks a practical & effective method and in most factories,
the energy consumption and rate is more than in similar industries of
industrial countries. The increasing demand of electrical energy and
the overheads which it imposes on the organization, forces
companies to search for suitable approaches to optimize energy
consumption and demand management. Application of value
engineering techniques is among these approaches. Value
engineering is considered a powerful tool for improving profitability.
These tools are used for reduction of expenses, increasing profits,
quality improvement, increasing market share, performing works in
shorter durations, more efficient utilization of sources & etc.
In this article, we shall review the subject of value engineering and
its capabilities for creating effective transformations in industrial
organizations, in order to reduce energy costs & the results have
been investigated and described during a case study in Mazandaran
wood and paper industries, the biggest consumer of energy in north
of Iran, for the purpose of presenting the effects of performed tasks
in optimization of energy consumption by utilizing value engineering
techniques in one case study.
Abstract: In this study, the Taguchi method was used to optimize the effect of HALO structure or halo implant variations on threshold voltage (VTH) and leakage current (ILeak) in 45nm p-type Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) device. Besides halo implant dose, the other process parameters which used were Source/Drain (S/D) implant dose, oxide growth temperature and silicide anneal temperature. This work was done using TCAD simulator, consisting of a process simulator, ATHENA and device simulator, ATLAS. These two simulators were combined with Taguchi method to aid in design and optimize the process parameters. In this research, the most effective process parameters with respect to VTH and ILeak are halo implant dose (40%) and S/D implant dose (52%) respectively. Whereas the second ranking factor affecting VTH and ILeak are oxide growth temperature (32%) and halo implant dose (34%) respectively. The results show that after optimizations approaches is -0.157V at ILeak=0.195mA/μm.
Abstract: High precision in motion is required to manipulate the
micro objects in precision industries for micro assembly, cell
manipulation etc. Precision manipulation is achieved based on the
appropriate mechanism design of micro devices such as
microgrippers. Design of a compliant based mechanism is the better
option to achieve a highly precised and controlled motion. This
research article highlights the method of designing a compliant based
three fingered microgripper suitable for holding asymmetric objects.
Topological optimization technique, a systematic method is
implemented in this research work to arrive a topologically optimized
design of the mechanism needed to perform the required micro
motion of the gripper. Optimization technique has a drawback of
generating senseless regions such as node to node connectivity and
staircase effect at the boundaries. Hence, it is required to have post
processing of the design to make it manufacturable. To reduce the
effect of post processing stage and to preserve the edges of the image,
a cubic spline interpolation technique is introduced in the MATLAB
program. Structural performance of the topologically developed
mechanism design is tested using finite element method (FEM)
software. Further the microgripper structure is examined to find its
fatigue life and vibration characteristics.
Abstract: A new design of a planar passive T-micromixer with fin-shaped baffles in the mixing channel is presented. The mixing efficiency and the level of pressure loss in the channel have been investigated by numerical simulations in the range of Reynolds number (Re) 1 to 50. A Mixing index (Mi) has been defined to quantify the mixing efficiency, which results over 85% at both ends of the Re range, what demonstrates the micromixer can enhance mixing using the mechanisms of diffusion (lower Re) and convection (higher Re). Three geometric dimensions: radius of baffle, baffles pitch and height of the channel define the design parameters, and the mixing index and pressure loss are the performance parameters used to optimize the micromixer geometry with a multi-criteria optimization method. The Pareto front of designs with the optimum trade-offs, maximum mixing index with minimum pressure loss, is obtained. Experiments for qualitative and quantitative validation have been implemented.
Abstract: Modern managements of water distribution system
(WDS) need water quality models that are able to accurately predict
the dynamics of water quality variations within the distribution system
environment. Before water quality models can be applied to solve
system problems, they should be calibrated. Although former
researchers use GA solver to calibrate relative parameters, it is
difficult to apply on the large-scale or medium-scale real system for
long computational time. In this paper a new method is designed
which combines both macro and detailed model to optimize the water
quality parameters. This new combinational algorithm uses radial
basis function (RBF) metamodeling as a surrogate to be optimized for
the purpose of decreasing the times of time-consuming water quality
simulation and can realize rapidly the calibration of pipe wall reaction
coefficients of chlorine model of large-scaled WDS. After two cases
study this method is testified to be more efficient and promising, and
deserve to generalize in the future.
Abstract: Development of motor car safety devices has reduced
fatality rates in car accidents. Yet despite this increase in car safety,
neck injuries resulting from rear impact collisions, particularly at low
speed, remain a primary concern. In this study, FEA(Finite Element
Analysis) of seat was performed to evaluate neck injuries in rear
impact. And the FEA result was verified by comparison with the actual
test results. The dummy used in FE model and actual test is BioRID II
which is regarded suitable for rear impact collision analysis. A
threshold of the BioRID II neck injury indicators was also proposed to
upgrade seat performance in order to reduce whiplash injury. To
optimize the seat for a low-speed rear impact collision, a method was
proposed, which is multi-objective optimization idea using DOE
(Design of Experiments) results.
Abstract: PCCI engines can reduce NOx and PM emissions
simultaneously without sacrificing thermal efficiency, but a low
combustion temperature resulting from early fuel injection, and
ignition occurring prior to TDC, can cause higher THC and CO
emissions and fuel consumption. In conclusion, it was found that the
PCCI combustion achieved by the 2-stage injection strategy with
optimized calibration factors (e.g. EGR rate, injection pressure, swirl
ratio, intake pressure, injection timing) can reduce NOx and PM
emissions simultaneously. This research works are expected to
provide valuable information conducive to a development of an
innovative combustion engine that can fulfill upcoming stringent
emission standards.
Abstract: Most Decision Support Systems (DSS) for waste
management (WM) constructed are not widely marketed and lack
practical applications. This is due to the number of variables and
complexity of the mathematical models which include the
assumptions and constraints required in decision making. The
approach made by many researchers in DSS modelling is to isolate a
few key factors that have a significant influence to the DSS. This
segmented approach does not provide a thorough understanding of
the complex relationships of the many elements involved. The
various elements in constructing the DSS must be integrated and
optimized in order to produce a viable model that is marketable and
has practical application. The DSS model used in assisting decision
makers should be integrated with GIS, able to give robust prediction
despite the inherent uncertainties of waste generation and the plethora
of waste characteristics, and gives optimal allocation of waste stream
for recycling, incineration, landfill and composting.
Abstract: This paper present the harmonic elimination of hybrid
multilevel inverters (HMI) which could be increase the number of
output voltage level. Total Harmonic Distortion (THD) is one of the
most important requirements concerning performance indices.
Because of many numbers output levels of HMI, it had numerous
unknown variables of eliminate undesired individual harmonic and
THD nonlinear equations set. Optimized harmonic stepped waveform
(OHSW) is solving switching angles conventional method, but most
complicated for solving as added level. The artificial intelligent
techniques are deliberation to solve this problem. This paper presents
the Particle Swarm Optimization (PSO) technique for solving
switching angles to get minimum THD and eliminate undesired
individual harmonics of 15-levels hybrid multilevel inverters.
Consequently it had many variables and could eliminate numerous
harmonics. Both advantages including high level of inverter and
Particle Swarm Optimization (PSO) are used as powerful tools for
harmonics elimination.
Abstract: This paper presents an optimized methodology to
folded cascode operational transconductance amplifier (OTA) design.
The design is done in different regions of operation, weak inversion,
strong inversion and moderate inversion using the gm/ID methodology
in order to optimize MOS transistor sizing.
Using 0.35μm CMOS process, the designed folded cascode OTA
achieves a DC gain of 77.5dB and a unity-gain frequency of 430MHz
in strong inversion mode. In moderate inversion mode, it has a 92dB
DC gain and provides a gain bandwidth product of around 69MHz.
The OTA circuit has a DC gain of 75.5dB and unity-gain frequency
limited to 19.14MHZ in weak inversion region.
Abstract: Traffic Engineering (TE) is the process of controlling
how traffic flows through a network in order to facilitate efficient and
reliable network operations while simultaneously optimizing network
resource utilization and traffic performance. TE improves the
management of data traffic within a network and provides the better
utilization of network resources. Many research works considers intra
and inter Traffic Engineering separately. But in reality one influences
the other. Hence the effective network performances of both inter and
intra Autonomous Systems (AS) are not optimized properly. To
achieve a better Joint Optimization of both Intra and Inter AS TE, we
propose a joint Optimization technique by considering intra-AS
features during inter – AS TE and vice versa. This work considers the
important criterion say latency within an AS and between ASes. and
proposes a Bi-Criteria Latency optimization model. Hence an overall
network performance can be improved by considering this jointoptimization
technique in terms of Latency.
Abstract: Vehicle suspension design must fulfill
some conflicting criteria. Among those is ride comfort
which is attained by minimizing the acceleration
transmitted to the sprung mass, via suspension spring
and damper. Also good handling of a vehicle is a
desirable property which requires stiff suspension and
therefore is in contrast with a vehicle with good ride.
Among the other desirable features of a suspension is
the minimization of the maximum travel of suspension.
This travel which is called suspension working space in
vehicle dynamics literature is also a design constraint
and it favors good ride. In this research a full car 8
degrees of freedom model has been developed and the
three above mentioned criteria, namely: ride, handling
and working space has been adopted as objective
functions. The Multi Objective Programming (MOP)
discipline has been used to find the Pareto Front and
some reasoning used to chose a design point between
these non dominated points of Pareto Front.
Abstract: This paper deals optimized model to investigate the
effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were
conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of
experiments (DOE) method and response surface methodology
(RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through
analysis of variance (ANOVA). The obtained results evidence that as
the material removal rate increases as peak current and pulse on time
increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining
conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about
4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.
Abstract: In recent years, there has been an increasing interest
toward the use of bovine genotyped embryos for commercial embryo
transfer programs. Biopsy of a few cells in morulla stage is essential
for preimplantation genetic diagnosis (PGD). Low amount of DNA
have limited performing the several molecular analyses within PGD
analyses. Whole genome amplification (WGA) promises to eliminate
this problem. We evaluated the possibility and performance of an
improved primer extension preamplification (I-PEP) method with a
range of starting bovine genomic DNA from 1-8 cells into the WGA
reaction. We optimized a short and simple I-PEP (ssI-PEP) procedure
(~3h). This optimized WGA method was assessed by 6 loci specific
polymerase chain reactions (PCRs), included restriction fragments
length polymorphism (RFLP). Optimized WGA procedure possesses
enough sensitivity for molecular genetic analyses through the few
input cells. This is a new era for generating characterized bovine
embryos in preimplantation stage.