Abstract: An unsupervised classification algorithm is derived
by modeling observed data as a mixture of several mutually
exclusive classes that are each described by linear combinations of
independent non-Gaussian densities. The algorithm estimates the
data density in each class by using parametric nonlinear functions
that fit to the non-Gaussian structure of the data. This improves
classification accuracy compared with standard Gaussian mixture
models. When applied to textures, the algorithm can learn basis
functions for images that capture the statistically significant structure
intrinsic in the images. We apply this technique to the problem of
unsupervised texture classification and segmentation.
Abstract: The purpose of this research was to study the inspector performance by using computer based training (CBT). Visual inspection task was printed circuit board (PCB) simulated on several types of defects. Subjects were 16 undergraduate randomly selected from King Mongkut-s University of Technology Thonburi and test for 20/20. Then, they were equally divided on performance into two groups (control and treatment groups) and were provided information before running the experiment. Only treatment group was provided feedback information after first experiment. Results revealed that treatment group was showed significantly difference at the level of 0.01. The treatment group showed high percentage on defects detected. Moreover, the attitude of inspectors on using the CBT to inspection was showed on good. These results have been showed that CBT could be used for training to improve inspector performance.
Abstract: In this paper, we present a new method for
incorporating global shift invariance in support vector machines.
Unlike other approaches which incorporate a feature extraction stage,
we first scale the image and then classify it by using the modified
support vector machines classifier. Shift invariance is achieved by
replacing dot products between patterns used by the SVM classifier
with the maximum cross-correlation value between them. Unlike the
normal approach, in which the patterns are treated as vectors, in our
approach the patterns are treated as matrices (or images). Crosscorrelation
is computed by using computationally efficient
techniques such as the fast Fourier transform. The method has been
tested on the ORL face database. The tests indicate that this method
can improve the recognition rate of an SVM classifier.
Abstract: Network-Centric Air Defense Missile Systems
(NCADMS) represents the superior development of the air defense
missile systems and has been regarded as one of the major research
issues in military domain at present. Due to lack of knowledge and
experience on NCADMS, modeling and simulation becomes an effective
approach to perform operational analysis, compared with
those equation based ones. However, the complex dynamic interactions
among entities and flexible architectures of NCADMS put forward
new requirements and challenges to the simulation framework
and models. ABS (Agent-Based Simulations) explicitly addresses
modeling behaviors of heterogeneous individuals. Agents have capability
to sense and understand things, make decisions, and act on the
environment. They can also cooperate with others dynamically to
perform the tasks assigned to them. ABS proves an effective approach
to explore the new operational characteristics emerging in
NCADMS. In this paper, based on the analysis of network-centric
architecture and new cooperative engagement strategies for
NCADMS, an agent-based simulation framework by expanding the
simulation framework in the so-called System Effectiveness Analysis
Simulation (SEAS) was designed. The simulation framework specifies
components, relationships and interactions between them, the
structure and behavior rules of an agent in NCADMS. Based on scenario
simulations, information and decision superiority and operational
advantages in NCADMS were analyzed; meanwhile some
suggestions were provided for its future development.
Abstract: The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.
Abstract: Pollution emission levels of aircraft engines are a
nowadays high concern. Any technological advance that could reduce
emission levels is always welcome. In what concerns aircraft engines,
a possible solution for this problem could be the use of regenerators
and intercoolers. These components might reduce the specific fuel
consumption, increase efficiency and specific thrust and consequently
reduce the pollution levels of the engine. This is not a novel solution.
These heat exchangers are already is use in stationary engines. For
aircraft engines, the extra weight of the needed hardware could
overcome the fuel saved. This work compares a conventional engine
with configurations that use intercoolers and regenerators.
Abstract: The Informational Infrastructures of small and medium-sized manufacturing enterprises are relatively poor, there are serious shortages of capitals which can be invested in informatization construction, computer hardware and software resources, and human resources. To address the informatization issue in small and medium-sized manufacturing enterprises, and enable them to the application of advanced management thinking and enhance their competitiveness, the paper establish a manufacturing-oriented small and medium-sized enterprises informatization platform based on the ASP business intelligence technology, which effectively improves the scientificity of enterprises decision and management informatization.
Abstract: Hypernetworks are a generalized graph structure
representing higher-order interactions between variables. We present a
method for self-organizing hypernetworks to learn an associative
memory of sentences and to recall the sentences from this memory.
This learning method is inspired by the “mental chemistry" model of
cognition and the “molecular self-assembly" technology in
biochemistry. Simulation experiments are performed on a corpus of
natural-language dialogues of approximately 300K sentences
collected from TV drama captions. We report on the sentence
completion performance as a function of the order of word-interaction
and the size of the learning corpus, and discuss the plausibility of this
architecture as a cognitive model of language learning and memory.
Abstract: Location-based services (LBS) exploit the known
location of a user to provide services dependent on their geographic
context and personalized needs [1].
The development and arrival of broadband mobile data networks
supported with mobile terminals equipped with new location
technologies like GPS have finally created opportunities for
implementation of LBS applications. But, from the other side,
collecting location information data in general raises privacy
concerns.
This paper presents results from two surveys of LBS acceptance in
Croatia. The first survey was administered on 181 students, and the
second extended survey involved pattern of 180 Croatian citizens.
We developed questionnaire which consists of descriptions of 15
different applications with scale which measures perceptions and
attitudes of users towards these applications.
We report the results to identify potential commercial applications
for LBS in B2C segment. Our findings suggest that some types of
applications like emergency&safety services and navigation have
significantly higher rate of acceptance than other types.
Abstract: A new observer based fault detection and diagnosis
scheme for predicting induction motors- faults is proposed in this
paper. Prediction of incipient faults, using different variants of
Kalman filter and their relative performance are evaluated. Only soft
faults are considered for this work. The data generation, filter
convergence issues, hypothesis testing and residue estimates are
addressed. Simulink model is used for data generation and various
types of faults are considered. A comparative assessment of the
estimates of different observers associated with these faults is
included.
Abstract: Heavy rainfall greatly affects the aerodynamic performance of the aircraft. There are many accidents of aircraft caused by aerodynamic efficiency degradation by heavy rain.
In this Paper we have studied the heavy rain effects on the aerodynamic efficiency of cambered NACA 64-210 and symmetric
NACA 0012 airfoils. Our results show significant increase in drag and decrease in lift. We used preprocessing software gridgen for creation of geometry and mesh, used fluent as solver and techplot as postprocessor. Discrete phase modeling called DPM is used to model the rain particles using two phase flow approach. The rain particles are assumed to be inert.
Both airfoils showed significant decrease in lift and increase in drag in simulated rain environment. The most significant difference between these two airfoils was the NACA 64-210 more sensitivity than NACA 0012 to liquid water content (LWC). We believe that the results showed in this paper will be useful for the designer of the commercial aircrafts and UAVs, and will be helpful for training of the pilots to control the airplanes in heavy rain.
Abstract: The Kowsar dam supply water for different usages
such as drinking, industrial, agricultural and aquaculture farms
usages and located next to the city of Dehdashat in Kohgiluye and
Boyerahmad province in southern Iran. There are some towns and
villages on the Kowsar dam watersheds, which Dehdasht and Choram
are the most important and populated cities in this area. The study
was undertaken to assess the status of water quality in the urban areas
of the Kowsar dam. A total of 28 water samples were collected from
6 stations on surface water and 1 station from groundwater on the
watershed of the Kowsar dam. All the samples were analyzed for Ni
concentration using standard procedures. The results were compared
with other national and international standards. Among the analyzed
samples, as the maximum value of Nickel (0.01 mg/L) was observed
on the station 2 at the autumn 2010, all the samples analyzed were
within the maximum admissible limits by the United States
Environmental Protection Agency, EU, WHO and the Iranian. In
general results of the present study have shown that a Ni mean value
of station No. 2 with 0.006 mg/L is higher than the other stations. Ni
level of all samples and stations have had normal values and this is an
indication of pollution potential and hazards because of human
activity and waste water of towns in the areas, which can effect on
human health implications in future. This research, therefore,
recommends the government and other responsible authorities to take
suitable improving measures in the Kowsar dam watersheds.
Abstract: In aerospace applications, interactions of airflow with
aircraft structures can result in undesirable structural deformations.
This structural deformation in turn, can be predicted if the natural
modes of the structure are known. This can be achieved through
conventional modal testing that requires a known excitation force in
order to extract these dynamic properties. This technique can be
experimentally complex because of the need for artificial excitation
and it is also does not represent actual operational condition. The
current work presents part of research work that address the practical
implementation of operational modal analysis (OMA) applied to a
cantilevered hybrid composite plate employing single contactless
sensing system via laser vibrometer. OMA technique extracts the
modal parameters based only on the measurements of the dynamic
response. The OMA results were verified with impact hammer modal
testing and good agreement was obtained.
Abstract: Rapid progress in process automation and tightening
quality standards result in a growing demand being placed on fault
detection and diagnostics methods to provide both speed and
reliability of motor quality testing. Doubly fed induction generators
are used mainly for wind energy conversion in MW power plants.
This paper presents a detection of an inter turn stator and an open
phase faults, in a doubly fed induction machine whose stator and
rotor are supplied by two pulse width modulation (PWM) inverters.
The method used in this article to detect these faults, is based on
Park-s Vector Approach, using a neural network.
Abstract: Bicycle usage for exercise, recreation, and commuting
to work in Australia shows that pedal cycling is the fourth most
popular activity with 10.6% increase in participants between 2001
and 2007. As with other means of transport, accident and injury
becomes common although mandatory bicycle helmet wearing has
been introduced. The research aims to develop a face surrogate made
of sandwich of rigid foam and rubber sheets to represent human
facial bone under blunt impact. The facial surrogate will serve as an
important test device for further development of facial-impact
protection for cyclist. A test procedure was developed to simulate the
energy of impact and record data to evaluate the effect of impact on
facial bones. Drop tests were performed to establish a suitable
combination of materials. It was found that the sandwich structure of
rigid extruded-polystyrene foam (density of 40 kg/m3 with a pattern
of 6-mm-holes), Neoprene rubber sponge, and Abrasaflex rubber
backing, had impact characteristics comparable to that of human
facial bone. In particular, the foam thickness of 30 mm and 25 mm
was found suitable to represent human zygoma (cheekbone) and
maxilla (upper-jaw bone), respectively.
Abstract: In China, with the rapid urbanization and
industrialization, and highly accelerated economic development have
resulted in degradation of water resource. The water quality
deterioration usual result from eutrophication in most cases, so how to
dispose this type pollution water higher efficiently is an urgent task.
Hower, different with traditional technology, constructed wetlands are
effective treatment systems that can be very useful because they are
simple technology and low operational cost. A pilot-scale treatment
including constructed wetlands was constructed at XingYun Lake,
Yuxi, China, and operated as primary treatment measure before
eutrophic-lake water draining to riverine landscape. Water quality
indices were determined during the experiment, the results indicated
that treatment removal efficiencies were high for Nitrate nitrogen,
Chlorophyll–a and Algae, the final removal efficiency reached to
95.20%, 93.33% and 99.87% respectively, but the removal efficiency
of Total phosphorous and Total nitrogen only reach to 68.83% and
50.00% respectively.
Abstract: The problem addressed herein is the efficient management of the Grid/Cluster intense computation involved, when the preconditioned Bi-CGSTAB Krylov method is employed for the iterative solution of the large and sparse linear system arising from the discretization of the Modified Helmholtz-Dirichlet problem by the Hermite Collocation method. Taking advantage of the Collocation ma-trix's red-black ordered structure we organize efficiently the whole computation and map it on a pipeline architecture with master-slave communication. Implementation, through MPI programming tools, is realized on a SUN V240 cluster, inter-connected through a 100Mbps and 1Gbps ethernet network,and its performance is presented by speedup measurements included.
Abstract: Today’s technology is heavily dependent on web applications. Web applications are being accepted by users at a very rapid pace. These have made our work efficient. These include webmail, online retail sale, online gaming, wikis, departure and arrival of trains and flights and list is very long. These are developed in different languages like PHP, Python, C#, ASP.NET and many more by using scripts such as HTML and JavaScript. Attackers develop tools and techniques to exploit web applications and legitimate websites. This has led to rise of web application security; which can be broadly classified into Declarative Security and Program Security. The most common attacks on the applications are by SQL Injection and XSS which give access to unauthorized users who totally damage or destroy the system. This paper presents a detailed literature description and analysis on Web Application Security, examples of attacks and steps to mitigate the vulnerabilities.
Abstract: Self-organizing map (SOM) is a well known data
reduction technique used in data mining. It can reveal structure in
data sets through data visualization that is otherwise hard to detect
from raw data alone. However, interpretation through visual
inspection is prone to errors and can be very tedious. There are
several techniques for the automatic detection of clusters of code
vectors found by SOM, but they generally do not take into account
the distribution of code vectors; this may lead to unsatisfactory
clustering and poor definition of cluster boundaries, particularly
where the density of data points is low. In this paper, we propose the
use of an adaptive heuristic particle swarm optimization (PSO)
algorithm for finding cluster boundaries directly from the code
vectors obtained from SOM. The application of our method to
several standard data sets demonstrates its feasibility. PSO algorithm
utilizes a so-called U-matrix of SOM to determine cluster boundaries;
the results of this novel automatic method compare very favorably to
boundary detection through traditional algorithms namely k-means
and hierarchical based approach which are normally used to interpret
the output of SOM.
Abstract: Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new
part directly from 3 Dimensional Computer Aided Design (3D CAD)
model, building new part on the existing old component and repairing an existing high valued component parts that would have
been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the
underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing
parameters and studying many parameters at the same time makes it
further complex to understand. In this study, the effect of laser power
and powder flow rate on physical properties (deposition height and
deposition width), metallurgical property (microstructure) and
mechanical (microhardness) properties on laser deposited most
widely used aerospace alloy are studied. Also, because the Ti6Al4V
is very expensive, and LMD is capable of reducing buy-to-fly ratio
of aerospace parts, the material utilization efficiency is also studied.
Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow
rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and
scanning speed constant at 2 l/min and 0.005 m/s respectively. The
deposition height / width are found to increase with increase in laser
power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces
material utilization. The results are presented and fully discussed.