Abstract: In many cases, there are some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrate models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long term research project is given to compare the suggested model with the MpO model.
Abstract: This study proposes a multi-response surface
optimization problem (MRSOP) for determining the proper choices
of a process parameter design (PPD) decision problem in a noisy
environment of a grease position process in an electronic industry.
The proposed models attempts to maximize dual process responses
on the mean of parts between failure on left and right processes. The
conventional modified simplex method and its hybridization of the
stochastic operator from the hunting search algorithm are applied to
determine the proper levels of controllable design parameters
affecting the quality performances. A numerical example
demonstrates the feasibility of applying the proposed model to the
PPD problem via two iterative methods. Its advantages are also
discussed. Numerical results demonstrate that the hybridization is
superior to the use of the conventional method. In this study, the
mean of parts between failure on left and right lines improve by
39.51%, approximately. All experimental data presented in this
research have been normalized to disguise actual performance
measures as raw data are considered to be confidential.
Abstract: Study was conducted to determine the concentration of
copper, cadmium, lead and zinc in Cabomba furcata that found
abundance in Lake Chini. This aquatic plant was collected randomly
within the lake for heavy metal determination. Water quality
measurement was undertaken in situ for temperature, pH,
conductivity and dissolved oksigen using portable multi sensor probe
YSI model 556. The C. furcata was digested using wet digestion
method and heavy metal concentrations were analysed using Atomic
Absorption Spectrometer (AAS) Perkin Elmer 4100B (flame
method). Result of water quality classify Lake Chini between class II
to class III using Malaysian Water Quality Standard. According to
this standard, Lake Chini has moderate quality, which normal for
natural lake. Heavy metal concentrations in C.furcata were low and
found to be lower than the critical toxic value in aquatic plants. Oneway
ANOVA test indicated the heavy metal concentrations in
C.furcata were significantly differ between sampling location. Water
quality and heavy metal concentrations indicates that Lake Chini was
not receives anthropogenic load from nearby activities.
Abstract: In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Abstract: In this paper a new method is suggested for
distributed data-mining by the probability patterns. These patterns
use decision trees and decision graphs. The patterns are cared to be
valid, novel, useful, and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
By using the suggested method we will be able to extract the useful
information from massive and multi-relational data bases.
Abstract: In this paper, the existence of multiple positive
solutions for a class of third-order three-point discrete boundary value
problem is studied by applying algebraic topology method.
Abstract: In this paper we present a new approach to deal with
image segmentation. The fact that a single segmentation result do not
generally allow a higher level process to take into account all the
elements included in the image has motivated the consideration of
image segmentation as a multiobjective optimization problem. The
proposed algorithm adopts a split/merge strategy that uses the result
of the k-means algorithm as input for a quantum evolutionary
algorithm to establish a set of non-dominated solutions. The
evaluation is made simultaneously according to two distinct features:
intra-region homogeneity and inter-region heterogeneity. The
experimentation of the new approach on natural images has proved
its efficiency and usefulness.
Abstract: Drilling is the most common machining operation and it forms the highest machining cost in many manufacturing activities including automotive engine production. The outcome of this operation depends upon many factors including utilization of proper cutting tool geometry, cutting tool material and the type of coating used to improve hardness and resistance to wear, and also cutting parameters. With the availability of a large array of tool geometries, materials and coatings, is has become a challenging task to select the best tool and cutting parameters that would result in the lowest machining cost or highest profit rate. This paper describes an algorithm developed to help achieve good performances in drilling operations by automatically determination of proper cutting tools and cutting parameters. It also helps determine machining sequences resulting in minimum tool changes that would eventually reduce machining time and cost where multiple tools are used.
Abstract: The objective of the present investigation was to
evaluate the morphology of Escherchia coli bacteria in interaction
with SiO2 nanoparticles.
This study was made by atomic force microscopy and quartz
crystal microbalance using SiO2 nanoparticles with 10nm, 50nm and
100nm diameter and bacteria immobilized on polyelectrolyte
multilayer films obtained by spin coating or by “layer by layer”
(LbL) method.
Abstract: A new deployment of the multiple criteria decision
making (MCDM) techniques: the Simple Additive Weighting
(SAW), and the Technique for Order Preference by Similarity to
Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in
this paper. Rather than exclusive reference to mean and variance as in
the traditional mean-variance method, the criteria used in this
demonstration are the first four moments of the portfolio distribution.
Each asset is evaluated based on its marginal impacts to portfolio
higher moments that are characterized by trapezoidal fuzzy numbers.
Then centroid-based defuzzification is applied to convert fuzzy
numbers to the crisp numbers by which SAW and TOPSIS can be
deployed. Experimental results suggest the similar efficiency of these
MCDM approaches to selecting dominant assets for an optimal
portfolio under higher moments. The proposed approaches allow
investors flexibly adjust their risk preferences regarding higher
moments via different schemes adapting to various (from
conservative to risky) kinds of investors. The other significant
advantage is that, compared to the mean-variance analysis, the
portfolio weights obtained by SAW and TOPSIS are consistently
well-diversified.
Abstract: Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.
Abstract: A new code for spectral-amplitude coding optical
code-division multiple-access system is proposed called Random
diagonal (RD) code. This code is constructed using code segment and
data segment. One of the important properties of this code is that the
cross correlation at data segment is always zero, which means that
Phase Intensity Induced Noise (PIIN) is reduced. For the performance
analysis, the effects of phase-induced intensity noise, shot noise, and
thermal noise are considered simultaneously. Bit-error rate (BER)
performance is compared with Hadamard and Modified Frequency
Hopping (MFH) codes. It is shown that the system using this new
code matrices not only suppress PIIN, but also allows larger number
of active users compare with other codes. Simulation results shown
that using point to point transmission with three encoded channels,
RD code has better BER performance than other codes, also its found
that at 0 dbm PIIN noise are 10-10 and 10-11 for RD and MFH
respectively.
Abstract: In North America, Most power distribution systems
employ a four-wire multi-grounded neutral (MGN) design. This paper has explained the inherent characteristics of multi-grounded three-phase four-wire distribution systems under unbalanced
situations. As a result, the mechanism of voltage swell and voltage sag in MGN feeders becomes difficult to understand. The simulation
tool that has been used in this paper is MATLAB under Windows software. In this paper the equivalent model of a full-scale multigrounded
distribution system implemented by MATLAB is
introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.
Abstract: In mobile environments, unspecified numbers of transactions
arrive in continuous streams. To prove correctness of their
concurrent execution a method of modelling an infinite number of
transactions is needed. Standard database techniques model fixed
finite schedules of transactions. Lately, techniques based on temporal
logic have been proposed as suitable for modelling infinite schedules.
The drawback of these techniques is that proving the basic
serializability correctness condition is impractical, as encoding (the
absence of) conflict cyclicity within large sets of transactions results
in prohibitively large temporal logic formulae. In this paper, we show
that, under certain common assumptions on the graph structure of
data items accessed by the transactions, conflict cyclicity need only
be checked within all possible pairs of transactions. This results in
formulae of considerably reduced size in any temporal-logic-based
approach to proving serializability, and scales to arbitrary numbers
of transactions.
Abstract: The statistical distributions are modeled in explaining
nature of various types of data sets. Although these distributions are
mostly uni-modal, it is quite common to see multiple modes in the
observed distribution of the underlying variables, which make the
precise modeling unrealistic. The observed data do not exhibit
smoothness not necessarily due to randomness, but could also be due
to non-randomness resulting in zigzag curves, oscillations, humps
etc. The present paper argues that trigonometric functions, which
have not been used in probability functions of distributions so far,
have the potential to take care of this, if incorporated in the
distribution appropriately. A simple distribution (named as, Sinoform
Distribution), involving trigonometric functions, is illustrated in the
paper with a data set. The importance of trigonometric functions is
demonstrated in the paper, which have the characteristics to make
statistical distributions exotic. It is possible to have multiple modes,
oscillations and zigzag curves in the density, which could be suitable
to explain the underlying nature of select data set.
Abstract: There are many approaches proposed for solving
Sudoku puzzles. One of them is by modelling the puzzles as block
world problems. There have been three model for Sudoku solvers
based on this approach. Each model expresses Sudoku solver as
a parameterized multi agent systems. In this work, we propose a
new model which is an improvement over the existing models. This
paper presents the development of a Sudoku solver that implements
all the proposed models. Some experiments have been conducted to
determine the performance of each model.
Abstract: The application of a simple microcontroller to deal
with a three variable input and a single output fuzzy logic controller,
with Proportional – Integral – Derivative (PID) response control
built-in has been tested for an automatic voltage regulator. The
fuzzifiers are based on fixed range of the variables of output voltage.
The control output is used to control the wiper motor of the auto
transformer to adjust the voltage, using fuzzy logic principles, so that
the voltage is stabilized. In this report, the author will demonstrate
how fuzzy logic might provide elegant and efficient solutions in the
design of multivariable control based on experimental results rather
than on mathematical models.
Abstract: In this work, we developed the concept of
supercompression, i.e., compression above the compression standard
used. In this context, both compression rates are multiplied. In fact,
supercompression is based on super-resolution. That is to say,
supercompression is a data compression technique that superpose
spatial image compression on top of bit-per-pixel compression to
achieve very high compression ratios. If the compression ratio is very
high, then we use a convolutive mask inside decoder that restores the
edges, eliminating the blur. Finally, both, the encoder and the
complete decoder are implemented on General-Purpose computation
on Graphics Processing Units (GPGPU) cards. Specifically, the
mentio-ned mask is coded inside texture memory of a GPGPU.
Abstract: The sensitivity of orifice plate metering to disturbed
flow (either asymmetric or swirling) is a subject of great concern to
flow meter users and manufacturers. The distortions caused by pipe
fittings and pipe installations upstream of the orifice plate are major
sources of this type of non-standard flows. These distortions can alter
the accuracy of metering to an unacceptable degree. In this work, a
multi-scale object known as metal foam has been used to generate a
predetermined turbulent flow upstream of the orifice plate. The
experimental results showed that the combination of an orifice plate
and metal foam flow conditioner is broadly insensitive to upstream
disturbances. This metal foam demonstrated a good performance in
terms of removing swirl and producing a repeatable flow profile
within a short distance downstream of the device. The results of using
a combination of a metal foam flow conditioner and orifice plate for
non-standard flow conditions including swirling flow and asymmetric
flow show this package can preserve the accuracy of metering up to
the level required in the standards.
Abstract: The unanticipated brittle fracture of connection of the
steel moment resisting frame (SMRF) occurred in 1994 the Northridge
earthquake. Since then, the researches for the vulnerability of
connection of the existing SMRF and for rehabilitation of those
buildings were conducted. This paper suggests performance-based
optimal seismic retrofit technique using connection upgrade. For
optimal design, a multi-objective genetic algorithm(NSGA-II) is used.
One of the two objective functions is to minimize initial cost and
another objective function is to minimize lifetime seismic damages
cost. The optimal algorithm proposed in this paper is performed
satisfying specified performance objective based on FEMA 356. The
nonlinear static analysis is performed for structural seismic
performance evaluation. A numerical example of SAC benchmark
SMRF is provided using the performance-based optimal seismic
retrofit technique proposed in this paper