Abstract: In this study, a multi objective optimization for end
milling of Al 6061 alloy has been presented to provide better
surface quality and higher Material Removal Rate (MRR). The input
parameters considered for the analysis are spindle speed, depth of cut
and feed. The experiments were planned as per Taguchis design of
experiment, with L27 orthogonal array. The Grey Relational Analysis
(GRA) has been used for transforming multiple quality responses
into a single response and the weights of the each performance
characteristics are determined by employing the Principal Component
Analysis (PCA), so that their relative importance can be properly and
objectively described. The results reveal that Taguchi based G-PCA
can effectively acquire the optimal combination of cutting parameters.
Abstract: Feature selection has been used in many fields such as
classification, data mining and object recognition and proven to be
effective for removing irrelevant and redundant features from the
original dataset. In this paper, a new design of distributed intrusion
detection system using a combination feature selection model based
on bees and decision tree. Bees algorithm is used as the search
strategy to find the optimal subset of features, whereas decision tree
is used as a judgment for the selected features. Both the produced
features and the generated rules are used by Decision Making Mobile
Agent to decide whether there is an attack or not in the networks.
Decision Making Mobile Agent will migrate through the networks,
moving from node to another, if it found that there is an attack on one
of the nodes, it then alerts the user through User Interface Agent or
takes some action through Action Mobile Agent. The KDD Cup 99
dataset is used to test the effectiveness of the proposed system. The
results show that even if only four features are used, the proposed
system gives a better performance when it is compared with the
obtained results using all 41 features.
Abstract: Particle size distribution, the most important
characteristics of aerosols, is obtained through electrical
characterization techniques. The dynamics of charged nanoparticles
under the influence of electric field in Electrical Mobility
Spectrometer (EMS) reveals the size distribution of these particles.
The accuracy of this measurement is influenced by flow conditions,
geometry, electric field and particle charging process, therefore by
the transfer function (transfer matrix) of the instrument. In this work,
a wire-cylinder corona charger was designed and the combined fielddiffusion
charging process of injected poly-disperse aerosol particles
was numerically simulated as a prerequisite for the study of a
multichannel EMS. The result, a cloud of particles with no uniform
charge distribution, was introduced to the EMS. The flow pattern and
electric field in the EMS were simulated using Computational Fluid
Dynamics (CFD) to obtain particle trajectories in the device and
therefore to calculate the reported signal by each electrometer.
According to the output signals (resulted from bombardment of
particles and transferring their charges as currents), we proposed a
modification to the size of detecting rings (which are connected to
electrometers) in order to evaluate particle size distributions more
accurately. Based on the capability of the system to transfer
information contents about size distribution of the injected particles,
we proposed a benchmark for the assessment of optimality of the
design. This method applies the concept of Von Neumann entropy
and borrows the definition of entropy from information theory
(Shannon entropy) to measure optimality. Entropy, according to the
Shannon entropy, is the ''average amount of information contained in
an event, sample or character extracted from a data stream''.
Evaluating the responses (signals) which were obtained via various
configurations of detecting rings, the best configuration which gave
the best predictions about the size distributions of injected particles,
was the modified configuration. It was also the one that had the
maximum amount of entropy. A reasonable consistency was also
observed between the accuracy of the predictions and the entropy
content of each configuration. In this method, entropy is extracted
from the transfer matrix of the instrument for each configuration.
Ultimately, various clouds of particles were introduced to the
simulations and predicted size distributions were compared to the
exact size distributions.
Abstract: Grains, including oats (Avena sativa L.), have been
recognized functional foods, because provide beneficial effect on the
health of the consumer and decrease the risk of various diseases. Oats
are good source of soluble fibre, essential amino acids, unsaturated
fatty acids, vitamins and minerals. Oat breeders have developed oat
varieties and improved yielding ability potential of oat varieties.
Therefore, the aim of investigation was to analyze the composition of
perspective oat varieties and breeding lines grains grown in different
conditions and evaluate functional properties. In the studied samples
content of protein, starch, β-glucans, total dietetic fibre, composition
of amino acids and vitamin E were determined. The results of
analysis showed that protein content depending of varieties ranged
9.70% to 17.30% total dietary fibre 13.66 g100g-1 to 30.17 g100g-1,
content of β-glucans 2.7 g100g-1 to 3.5 g100g-1, amount of
vitamin E (α-tocopherol) determined from 4 mgkg-1 to 9.9 mgkg-1.
The sums of essential amino acids in oat grain samples were
determined from 31.63 gkg-1 to 54.90 gkg-1. It is concluded that
amino acids composition of husked and naked oats grown in organic
or conventional conditions is close to optimal for human health.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: To tackle the air pollution issues, Plug-in Hybrid
Electric Vehicles (PHEVs) are proposed as an appropriate solution.
Charging a large amount of PHEV batteries, if not controlled, would
have negative impacts on the distribution system. The control process
of charging of these vehicles can be centralized in parking lots that
may provide a chance for better coordination than the individual
charging in houses. In this paper, an optimization-based approach is
proposed to determine the optimum PHEV parking capacities in
candidate nodes of the distribution system. In so doing, a profile for
charging and discharging of PHEVs is developed in order to flatten
the network load profile. Then, this profile is used in solving an
optimization problem to minimize the distribution system losses. The
outputs of the proposed method are the proper place for PHEV
parking lots and optimum capacity for each parking. The application
of the proposed method on the IEEE-34 node test feeder verifies the
effectiveness of the method.
Abstract: In order to study the effect of different levels of triple
super phosphate chemical fertilizer and biological phosphate fertilizer
(fertile 2) on some morphological traits of corn this research was
carried out in Ahvaz in 2002 as a factorial experiment in randomized
complete block design with 4 replications). The experiment included
two factors: first, biological phosphate fertilizer (fertile 2) at three
levels of 0, 100, 200 g/ha; second, triple super phosphate chemical
fertilizer at three levels of 0, 60, 90 kg/ha of pure phosphorus (P2O5).
The obtained results indicated that fertilizer treatments had a
significant effect on some morphological traits at 1% probability
level. In this regard, P2B2 treatment (100 g/ha biological phosphate
fertilizer (fertile 2) and 60 kg/ha triple super phosphate fertilizer) had
the greatest plant height, stem diameter, number of leaves and ear
length. It seems that in Ahvaz weather conditions, decrease of
consumption of triple superphosphate chemical fertilizer to less than
a half along with the consumption of biological phosphate fertilizer
(fertile 2) is highly important in order to achieve optimal results.
Therefore, it can be concluded that biological fertilizers can be used
as a suitable substitute for some of the chemical fertilizers in
sustainable agricultural systems.
Abstract: The goal of this paper is to present the diagnostic
contribution that the screening instrument, Mini-Mental State
Examination-2: Expanded Version (MMSE-2:EV), brings in
detecting the cognitive impairment or in monitoring the progress of
degenerative disorders. The diagnostic signification is underlined by
the interpretation of the MMSE-2:EV scores, resulted from the test
application to patients with mild and major neurocognitive disorders.
The cases were selected from current practice, in order to cover vast
and significant neurocognitive pathology: mild cognitive impairment,
Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s
disease, conversion of the mild cognitive impairment into
Alzheimer’s disease. The MMSE-2:EV version was used: it was
applied one month after the initial assessment, three months after the
first reevaluation and then every six months, alternating the blue and
red forms. Correlated with age and educational level, the raw scores
were converted in T scores and then, with the mean and the standard
deviation, the z scores were calculated. The differences of raw scores
between the evaluations were analyzed from the point of view of
statistic signification, in order to establish the progression in time of
the disease. The results indicated that the psycho-diagnostic approach
for the evaluation of the cognitive impairment with MMSE-2:EV is
safe and the application interval is optimal. In clinical settings with a
large flux of patients, the application of the MMSE-2:EV is a safe
and fast psychodiagnostic solution. The clinicians can draw objective
decisions and for the patients: it does not take too much time and
energy, it does not bother them and it doesn’t force them to travel
frequently.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: Steepest descent method is a simple gradient method
for optimization. This method has a slow convergence in heading to
the optimal solution, which occurs because of the zigzag form of the
steps. Barzilai and Borwein modified this algorithm so that it
performs well for problems with large dimensions. Barzilai and
Borwein method results have sparked a lot of research on the method
of steepest descent, including alternate minimization gradient method
and Yuan method. Inspired by previous works, we modified the step
size of the steepest descent method. We then compare the
modification results against the Barzilai and Borwein method,
alternate minimization gradient method and Yuan method for
quadratic function cases in terms of the iterations number and the
running time. The average results indicate that the steepest descent
method with the new step sizes provide good results for small
dimensions and able to compete with the results of Barzilai and
Borwein method and the alternate minimization gradient method for
large dimensions. The new step sizes have faster convergence
compared to the other methods, especially for cases with large
dimensions.
Abstract: This paper presents a state-of-the-art survey of the
operations research models developed for internal audit planning.
Two alternative approaches have been followed in the literature for
audit planning: (1) identifying the optimal audit frequency; and (2)
determining the optimal audit resource allocation. The first approach
identifies the elapsed time between two successive audits, which can
be presented as the optimal number of audits in a given planning
horizon, or the optimal number of transactions after which an audit
should be performed. It also includes the optimal audit schedule. The
second approach determines the optimal allocation of audit frequency
among all auditable units in the firm. In our review, we discuss both
the deterministic and probabilistic models developed for audit
planning. In addition, game theory models are reviewed to find the
optimal auditing strategy based on the interactions between the
auditors and the clients.
Abstract: This study conducts simulation analyses to find the
optimal debt ceiling of Taiwan, while factoring in welfare
maximization under a dynamic stochastic general equilibrium
framework. The simulation is based on Taiwan's 2001 to 2011
economic data and shows that welfare is maximized at a debt/GDP
ratio of 0.2, increases in the debt/GDP ratio leads to increases in both
tax and interest rates and decreases in the consumption ratio and
working hours. The study results indicate that the optimal debt ceiling
of Taiwan is 20% of GDP, where if the debt/GDP ratio is greater than
40%, the welfare will be negative and result in welfare loss.
Abstract: Haynes 25 alloy (also known as L-605 alloy) is cobalt
based super alloy which has widely applications such as aerospace
industry, turbine and furnace parts, power generators and heat
exchangers and petroleum refining components due to its excellent
characteristics. However, the workability of this alloy is more
difficult compared to normal steels or even stainless. In present work,
an experimental investigation was performed under cryogenic
cooling to determine cutting tool wear patterns and obtain optimal
cutting parameters in turning of cobalt based superalloy Haynes 25.
In experiments, uncoated carbide tool was used and cutting speed (V)
and feed rate (f) were considered as test parameters. Tool wear
(VBmax) were measured for process performance indicators.
Analysis of variance (ANOVA) was performed to determine the
importance of machining parameters.
Abstract: In recent years, multi-antenna techniques are being considered as a potential solution to increase the flow of future wireless communication systems. The objective of this article is to study the emission and reception system MIMO (Multiple Input Multiple Output), and present the different reception decoding techniques. First we will present the least complex technical, linear receivers such as the zero forcing equalizer (ZF) and minimum mean squared error (MMSE). Then a nonlinear technique called ordered successive cancellation of interferences (OSIC) and the optimal detector based on the maximum likelihood criterion (ML), finally, we simulate the associated decoding algorithms for MIMO system such as ZF, MMSE, OSIC and ML, thus a comparison of performance of these algorithms in MIMO context.
Abstract: Continuous upflow filters can combine the nutrient
(nitrogen and phosphate) and suspended solid removal in one unit
process. The contaminant removal could be achieved chemically or
biologically; in both processes the filter removal efficiency depends
on the interaction between the packed filter media and the influent. In
this paper a residence time distribution (RTD) study was carried out
to understand and compare the transfer behaviour of contaminants
through a selected filter media packed in a laboratory-scale
continuous up flow filter; the selected filter media are limestone and
white dolomite. The experimental work was conducted by injecting a
tracer (red drain dye tracer –RDD) into the filtration system and then
measuring the tracer concentration at the outflow as a function of
time; the tracer injection was applied at hydraulic loading rates
(HLRs) (3.8 to 15.2 m h-1). The results were analysed according to
the cumulative distribution function F(t) to estimate the residence
time of the tracer molecules inside the filter media. The mean
residence time (MRT) and variance σ2 are two moments of RTD that
were calculated to compare the RTD characteristics of limestone with
white dolomite. The results showed that the exit-age distribution of
the tracer looks better at HLRs (3.8 to 7.6 m h-1) and (3.8 m h-1) for
limestone and white dolomite respectively. At these HLRs the
cumulative distribution function F(t) revealed that the residence time
of the tracer inside the limestone was longer than in the white
dolomite; whereas all the tracer took 8 minutes to leave the white
dolomite at 3.8 m h-1. On the other hand, the same amount of the
tracer took 10 minutes to leave the limestone at the same HLR. In
conclusion, the determination of the optimal level of hydraulic
loading rate, which achieved the better influent distribution over the
filtration system, helps to identify the applicability of the material as
filter media. Further work will be applied to examine the efficiency
of the limestone and white dolomite for phosphate removal by
pumping a phosphate solution into the filter at HLRs (3.8 to 7.6 m h-1).
Abstract: Model predictive control is a kind of optimal feedback
control in which control performance over a finite future is optimized
with a performance index that has a moving initial time and a moving
terminal time. This paper examines the stability of model predictive
control for linear discrete-time systems with additive stochastic
disturbances. A sufficient condition for the stability of the closed-loop
system with model predictive control is derived by means of a linear
matrix inequality. The objective of this paper is to show the results
of computational simulations in order to verify the effectiveness of
the obtained stability condition.
Abstract: Floorplanning plays a vital role in the physical design
process of Very Large Scale Integrated (VLSI) chips. It is an
essential design step to estimate the chip area prior to the optimized
placement of digital blocks and their interconnections. Since VLSI
floorplanning is an NP-hard problem, many optimization techniques
were adopted in the literature. In this work, a music-inspired
Harmony Search (HS) algorithm is used for the fixed die outline
constrained floorplanning, with the aim of reducing the total chip
area. HS draws inspiration from the musical improvisation process of
searching for a perfect state of harmony. Initially, B*-tree is used to
generate the primary floorplan for the given rectangular hard
modules and then HS algorithm is applied to obtain an optimal
solution for the efficient floorplan. The experimental results of the
HS algorithm are obtained for the MCNC benchmark circuits.
Abstract: This paper proposed the comparison made between
Multi-Carrier Pulse Width Modulation, Sinusoidal Pulse Width
Modulation and Selective Harmonic Elimination Pulse Width
Modulation technique for minimization of Total Harmonic Distortion
in Cascaded H-Bridge Multi-Level Inverter. In Multicarrier Pulse
Width Modulation method by using Alternate Position of Disposition
scheme for switching pulse generation to Multi-Level Inverter.
Another carrier based approach; Sinusoidal Pulse Width Modulation
method is also implemented to define the switching pulse generation
system in the multi-level inverter. In Selective Harmonic Elimination
method using Genetic Algorithm and Particle Swarm Optimization
algorithm for define the required switching angles to eliminate low
order harmonics from the inverter output voltage waveform and
reduce the total harmonic distortion value. So, the results validate that
the Selective Harmonic Elimination Pulse Width Modulation method
does capably eliminate a great number of precise harmonics and
minimize the Total Harmonic Distortion value in output voltage
waveform in compared with Multi-Carrier Pulse Width Modulation
method, Sinusoidal Pulse Width Modulation method. In this paper,
comparison of simulation results shows that the Selective Harmonic
Elimination method can attain optimal harmonic minimization
solution better than Multi-Carrier Pulse Width Modulation method,
Sinusoidal Pulse Width Modulation method.
Abstract: In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.
Abstract: This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.