Abstract: This research deals with a flexible flowshop
scheduling problem with arrival and delivery of jobs in groups and
processing them individually. Due to the special characteristics of
each job, only a subset of machines in each stage is eligible to
process that job. The objective function deals with minimization of
sum of the completion time of groups on one hand and minimization
of sum of the differences between completion time of jobs and
delivery time of the group containing that job (waiting period) on the
other hand. The problem can be stated as FFc / rj , Mj / irreg which
has many applications in production and service industries. A
mathematical model is proposed, the problem is proved to be NPcomplete,
and an effective heuristic method is presented to schedule
the jobs efficiently. This algorithm can then be used within the body
of any metaheuristic algorithm for solving the problem.
Abstract: This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.
Abstract: This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.
Abstract: This study reports an empirical investigation of
fatigue crack initiation and propagation in 2024 T351 aluminium
alloy using constant amplitude loading. In initiation stage, local
strain approach at the notch was used and in stable propagation stage
NASGRO model was applied.
In this investigation, the flat plate of double through crack at hole
is used. Based on experimental results (AFGROW Database), effect
of stress ratio, R, is highlights on fatigue initiation life (FIL) and
fatigue crack growth rate (FCGR). The increasing of dimension of
hole characterizing the notch effect decrease the fatigue life.
Abstract: Samples of CoFe2-xCrxO4 where x varies from 0.0 to 0.5 were prepared by co-precipitation route. These samples were sintered at 750°C for 2 hours. These particles were characterized by X-ray diffraction (XRD) at room temperature. The FCC spinel structure was confirmed by XRD patterns of the samples. The crystallite sizes of these particles were calculated from the most intense peak by Scherrer formula. The crystallite sizes lie in the range of 37-60 nm. The lattice parameter was found decreasing upon substitution of Cr. DC electrical resistivity was measured as a function of temperature. The room temperature thermoelectric power was measured for the prepared samples. The magnitude of Seebeck coefficient depends on the composition and resistivity of the samples.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.
Abstract: The knowledge of the nature of loading is very
important in order to hold account on the total behavior such as
vibration, shock, fatigue, etc. Fatigue present 90% of failure when
loadings fatigues are very complex. In this paper a study of double
through crack at hole for plate subjected to fatigue loading is
presented. Various modes loading are studied where the applied load
is the same one. The fatigue life is given where the effect of stress
ratio is highlighted. This work is conducted on aluminum alloy 2024
T351 used for much aerospace and aeronautics applications. The
fatigue crack growth behavior with constant amplitude is studied
using the AFGROW code when Forman model is applied. The
fatigue crack growth rate and fatigue life for different loading modes
are compared with variation of others geometrical parameter such as
thickness and dimensions of notch hole.
Abstract: In recent years various types of electric vehicles
has gained again increasing attention as an environmentally
benign technology in transport. Especially for urban areas with
high local pollution this Zero-emission technology (at the point
of use) is considered to provide proper solutions. Yet, the bad
economics and the limited driving ranges are still major barriers
for a broader market penetration of battery electric vehicles
(BEV) and of fuel cell vehicles (FCV). The major result of our
analyses is that the most important precondition for a further
dissemination of BEV in urban areas are emission-free zones.
This is an instrument which allows the promotion of BEV
without providing excessive subsidies. In addition, it is
important to note that the full benefits of EV can only be
harvested if the electricity used is produced from renewable
energy sources. That is to say, it has to be ensured that the use of
BEV in urban areas is clearly linked to a green electricity
purchase model. And moreover, the introduction of a CO2-
emission-based tax system would support this requirement.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is certainly one of the most known among these algorithms. In robust-FCM, noise is modeled as a separate cluster and is characterized by a prototype that has a constant distance δ from all data points. Distance δ determines the boundary of the noise cluster and therefore is a critical parameter of the algorithm. Though some approaches have been proposed to automatically determine the most suitable δ for the specific application, up to today an efficient and fully satisfactory solution does not exist. The aim of this paper is to propose a novel method to compute the optimal δ based on the analysis of the distribution of the percentage of objects assigned to the noise cluster in repeated executions of the robust-FCM with decreasing values of δ . The extremely encouraging results obtained on some data sets found in the literature are shown and discussed.
Abstract: In this research, we propose a weighted class based
queuing (WCBQ) mechanism to provide class differentiation and to
reduce the load for the IMS (IP Multimedia Subsystem) presence
server (PS). The tasks of admission controller for the PS are
demonstrated. Analysis and simulation models are developed to
quantify the performance of WCBQ scheme. An optimized dropping
time frame has been developed based on which some of the preexisting
messages are dropped from the PS-buffer. Cost functions are
developed and simulation comparison has been performed with FCFS
(First Come First Served) scheme. The results show that the PS
benefits significantly from the proposed queuing and dropping
algorithm (WCBQ) during heavy traffic.
Abstract: This paper deals with the simulation of a Boost Power Factor Correction (PFC) Converter with Electro Magnetic Interference (EMI) Filter. The diode rectifier with output capacitor gives poor power factor. The Boost Converter of PFC Circuit is analyzed and then simulated with diode rectifier. The Boost PFC Converter with EMI Filter is simulated for resistive load. The power factor is improved using the proposed converter.
Abstract: The advancement of smartphones, wireless
networking and Near Field Communication (NFC) technology have
opened up a new approach to indoor navigation. Although NFC
technology has been used to support electronic commerce, access
control, and ticketing, there is a lack of research work on building
NFC-based indoor navigation system for smartphone users. This
paper presents an indoor interactive navigation system (named
I2Navi) based on NFC technology for users to navigate within a
building with ease using their smartphones. The I2Navi system has
been implemented at the Faculty of Engineering (FOE), Multimedia
University (MMU) to enable students, parents, visitors who own
NFC-enabled Android smartphones to navigate themselves within the
faculty. An evaluation is carried out and the results show positive
response to the proposed indoor navigation system using NFC and
smartphone technologies.
Abstract: Mel Frequency Cepstral Coefficient (MFCC) features
are widely used as acoustic features for speech recognition as well
as speaker recognition. In MFCC feature representation, the Mel frequency
scale is used to get a high resolution in low frequency region,
and a low resolution in high frequency region. This kind of processing
is good for obtaining stable phonetic information, but not suitable
for speaker features that are located in high frequency regions. The
speaker individual information, which is non-uniformly distributed
in the high frequencies, is equally important for speaker recognition.
Based on this fact we proposed an admissible wavelet packet based
filter structure for speaker identification. Multiresolution capabilities
of wavelet packet transform are used to derive the new features.
The proposed scheme differs from previous wavelet based works,
mainly in designing the filter structure. Unlike others, the proposed
filter structure does not follow Mel scale. The closed-set speaker
identification experiments performed on the TIMIT database shows
improved identification performance compared to other commonly
used Mel scale based filter structures using wavelets.
Abstract: Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techniques on vessel segmentation from 3- D rotational angiography (3DRA) images is investigated and a new technique of segmentation is proposed. This method consists in: preprocessing step of image enhancement, then K-Means (KM), Fuzzy C-Means (FCM) and Expectation Maximization (EM) clustering are used to separate vessel pixels from background and artery pixels from vein pixels when possible. A post processing step of removing false-alarm components is applied before constructing a three-dimensional volume of the vessels. The proposed method was tested on six datasets along with a medical assessment of an expert. Obtained results showed encouraging segmentations.
Abstract: Stainless steel has been employed in many
engineering applications ranging from pharmaceutical equipment to
piping in the nuclear reactors and storage to chemical products. In
this attempt, simulation of fatigue crack growth based on
experimental results of austenitic stainless steel 304L was presented
using AFGROW code when NASGRO mode laws adopted. Double
through crack at hole specimen is used in this investigation under
constant amplitude loading. Effect of mean stress is highlighted.
Results show that fatigue crack growth rate (FCGR) and fatigue life
were affected by maximum applied load and dimension of hole. An
equivalent of Paris law for this material was estimated.
Abstract: A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.
Abstract: In this paper we study the fuzzy c-mean clustering algorithm
combined with principal components method. Demonstratively
analysis indicate that the new clustering method is well rather than
some clustering algorithms. We also consider the validity of clustering
method.
Abstract: Power cables are vulnerable to failure due to aging or
defects that occur with the passage of time under continuous
operation and loading stresses. PD detection and characterization
provide information on the location, nature, form and extent of the
degradation. As a result, PD monitoring has become an important
part of condition based maintenance (CBM) program among power
utilities. Online partial discharge (PD) localization of defect sources
in power cable system is possible using the time of flight method.
The information regarding the time difference between the main and
reflected pulses and cable length can help in locating the partial
discharge source along the cable length. However, if the length of
the cable is not known and the defect source is located at the extreme
ends of the cable or in the middle of the cable, then double ended
measurement is required to indicate the location of PD source. Use of
multiple sensors can also help in discriminating the cable PD or local/
external PD. This paper presents the experience and results from
online partial discharge measurements conducted in the laboratory
and the challenges in partial discharge source localization.
Abstract: Due to growing environmental concerns of the cement
industry, alternative cement technologies have become an area of
increasing interest. It is now believed that new binders are
indispensable for enhanced environmental and durability
performance. Self-compacting Geopolymer concrete is an innovative
method and improved way of concreting operation that does not
require vibration for placing it and is produced by complete
elimination of ordinary Portland cement.
This paper documents the assessment of the compressive strength
and workability characteristics of low-calcium fly ash based selfcompacting
geopolymer concrete. The essential workability
properties of the freshly prepared Self-compacting Geopolymer
concrete such as filling ability, passing ability and segregation
resistance were evaluated by using Slump flow, V-funnel, L-box and
J-ring test methods. The fundamental requirements of high
flowability and segregation resistance as specified by guidelines on
Self Compacting Concrete by EFNARC were satisfied. In addition,
compressive strength was determined and the test results are included
here. This paper also reports the effect of extra water, curing time and
curing temperature on the compressive strength of self-compacting
geopolymer concrete. The test results show that extra water in the
concrete mix plays a significant role. Also, longer curing time and
curing the concrete specimens at higher temperatures will result in
higher compressive strength.