Abstract: Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.
Abstract: The chemical degradation of dieldrin in ferric
sulfide and iron powder aqueous suspension was investigated
in laboratory batch type experiments. To identify the reaction
mechanism, reduced copper was used as reductant. More than
90% of dieldrin was degraded using both reaction systems after
29 days. Initial degradation rate of the pesticide using ferric
sulfide was superior to that using iron powder. The reaction
schemes were completely dissimilar even though the ferric ion
plays an important role in both reaction systems. In the case of
metallic iron powder, dieldrin undergoes partial dechlorination.
This reaction proceeded by reductive hydrodechlorination with
the generation of H+, which arise by oxidation of ferric iron.
This reductive reaction was accelerated by reductant but
mono-dechlorination intermediates were accumulated. On the
other hand, oxidative degradation was observed in the reaction
with ferric sulfide, and the stable chemical structure of dieldrin
was decomposed into water-soluble intermediates. These
reaction intermediates have no chemical structure of drin class.
This dehalogenation reaction assumes to occur via the adsorbed
hydroxyl radial generated on the surface of ferric sulfide.
Abstract: Complex networks have been intensively studied across
many fields, especially in Internet technology, biological engineering,
and nonlinear science. Software is built up out of many interacting
components at various levels of granularity, such as functions, classes,
and packages, representing another important class of complex networks.
It can also be studied using complex network theory. Over the
last decade, many papers on the interdisciplinary research between
software engineering and complex networks have been published.
It provides a different dimension to our understanding of software
and also is very useful for the design and development of software
systems. This paper will explore how to use the complex network
theory to analyze software structure, and briefly review the main
advances in corresponding aspects.
Abstract: This document details the process of developing a
wireless device that captures the basic movements of the foot (plantar
flexion, dorsal flexion, abduction, adduction.), and the knee
movement (flexion). It implements a motion capture system by using
a hardware based on optical fiber sensors, due to the advantages in
terms of scope, noise immunity and speed of data transmission and
reception. The operating principle used by this system is the detection
and transmission of joint movement by mechanical elements and
their respective measurement by optical ones (in this case infrared).
Likewise, Visual Basic software is used for reception, analysis and
signal processing of data acquired by the device, generating a 3D
graphical representation in real time of each movement. The result is
a boot in charge of capturing the movement, a transmission module
(Implementing Xbee Technology) and a receiver module for
receiving information and sending it to the PC for their respective
processing.
The main idea with this device is to help on topics such as
bioengineering and medicine, by helping to improve the quality of
life and movement analysis.
Abstract: In quality control of freeze-dried durian, crispiness is
a key quality index of the product. Generally, crispy testing has to be
done by a destructive method. A nondestructive testing of the
crispiness is required because the samples can be reused for other
kinds of testing. This paper proposed a crispiness classification
method of freeze-dried durians using fuzzy logic for decision
making. The physical changes of a freeze-dried durian include the
pores appearing in the images. Three physical features including (1)
the diameters of pores, (2) the ratio of the pore area and the
remaining area, and (3) the distribution of the pores are considered to
contribute to the crispiness. The fuzzy logic is applied for making the
decision. The experimental results comparing with food expert
opinion showed that the accuracy of the proposed classification
method is 83.33 percent.
Abstract: Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. SEPN nets are well adapted extension of predicate nets for the definition and manipulation of stratified programs. This formalism is characterized by two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimization (maximal stratification, incremental updates ...). We propose, in this paper, useful algorithms for manipulating stratified programs using SEPN. These algorithms were implemented and validated with STRPRO tool.
Abstract: Researches related to standard product model and
development of neutral manufacturing interfaces for numerical
control machines becomes a significant topic since the last 25 years.
In this paper, a detail description of STEP implementation on turnmill
manufacturing has been discussed. It shows requirements of
information contents from ISO14649 data model. It covers to
describe the design of STEP-NC framework applicable to turn-mill
manufacturing. In the framework, EXPRESS-G and UML modeling
tools are used to depict the information contents of the system and
established the bases of information model requirement. A product
and manufacturing data model applicable for STEP compliant
manufacturing. The next generation turn-mill operations
requirements have been represented by a UML diagram. An object
oriented classes of ISO1449 has been developed on Visual Basic dot
NET platform for binding the static information model represented
by the UML diagram. An architect of the proposed system
implementation has been given on the bases of the design and
manufacturing module of STEP-NC interface established. Finally, a
part 21 file process plan generated for an illustration of turn-mill
components.
Abstract: This paper presents a new feature based dense stereo
matching algorithm to obtain the dense disparity map via dynamic
programming. After extraction of some proper features, we use some
matching constraints such as epipolar line, disparity limit, ordering
and limit of directional derivative of disparity as well. Also, a coarseto-
fine multiresolution strategy is used to decrease the search space
and therefore increase the accuracy and processing speed. The
proposed method links the detected feature points into the chains and
compares some of the feature points from different chains, to
increase the matching speed. We also employ color stereo matching
to increase the accuracy of the algorithm. Then after feature
matching, we use the dynamic programming to obtain the dense
disparity map. It differs from the classical DP methods in the stereo
vision, since it employs sparse disparity map obtained from the
feature based matching stage. The DP is also performed further on a
scan line, between any matched two feature points on that scan line.
Thus our algorithm is truly an optimization method. Our algorithm
offers a good trade off in terms of accuracy and computational
efficiency. Regarding the results of our experiments, the proposed
algorithm increases the accuracy from 20 to 70%, and reduces the
running time of the algorithm almost 70%.
Abstract: In the power quality analysis non-stationary nature
of voltage distortions require some precise and powerful analytical
techniques. The time-frequency representation (TFR) provides a
powerful method for identification of the non-stationary of the
signals. This paper investigates a comparative study on two
techniques for analysis and visualization of voltage distortions with
time-varying amplitudes. The techniques include the Discrete
Wavelet Transform (DWT), and the S-Transform. Several power
quality problems are analyzed using both the discrete wavelet
transform and S–transform, showing clearly the advantage of the S–
transform in detecting, localizing, and classifying the power quality
problems.
Abstract: This paper presents a model for the evaluation of
energy performance and aerodynamic forces acting on a three-bladed
small vertical axis Darrieus wind turbine depending on blade chord
curvature with respect to rotor axis.
The adopted survey methodology is based on an analytical code
coupled to a solid modeling software, capable of generating the
desired blade geometry depending on the blade design geometric
parameters, which is linked to a finite volume CFD code for the
calculation of rotor performance.
After describing and validating the model with experimental data,
the results of numerical simulations are proposed on the bases of two
different blade profile architectures, which are respectively
characterized by a straight chord and by a curved one, having a chord
radius equal to rotor external circumference. A CFD campaign of
analysis is completed for three blade-candidate airfoil sections, that is
the recently-developed DU 06-W-200 cambered blade profile, a
classical symmetrical NACA 0021 and its derived cambered airfoil,
characterized by a curved chord, having a chord radius equal to rotor
external circumference.
The effects of blade chord curvature on angle of attack, blade
tangential and normal forces are first investigated and then the
overall rotor torque and power are analyzed as a function of blade
azimuthal position, achieving a numerical quantification of the
influence of blade camber on overall rotor performance.
Abstract: Since the conception of JML, many tools, applications and implementations have been done. In this context, the users or developers who want to use JML seem surounded by many of these tools, applications and so on. Looking for a common infrastructure and an independent language to provide a bridge between these tools and JML, we developed an approach to embedded contracts in XML for Java: XJML. This approach offer us the ability to separate preconditions, posconditions and class invariants using JML and XML, so we made a front-end which can process Runtime Assertion Checking, Extended Static Checking and Full Static Program Verification. Besides, the capabilities for this front-end can be extended and easily implemented thanks to XML. We believe that XJML is an easy way to start the building of a Graphic User Interface delivering in this way a friendly and IDE independency to developers community wich want to work with JML.
Abstract: This work presents a neural network model for the
clustering analysis of data based on Self Organizing Maps (SOM).
The model evolves during the training stage towards a hierarchical
structure according to the input requirements. The hierarchical structure
symbolizes a specialization tool that provides refinements of the
classification process. The structure behaves like a single map with
different resolutions depending on the region to analyze. The benefits
and performance of the algorithm are discussed in application to the
Iris dataset, a classical example for pattern recognition.
Abstract: One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.
Abstract: Texture classification is a trendy and a catchy
technology in the field of texture analysis. Textures, the repeated
patterns, have different frequency components along different
orientations. Our work is based on Texture Classification and its
applications. It finds its applications in various fields like Medical
Image Classification, Computer Vision, Remote Sensing,
Agricultural Field, and Textile Industry. Weed control has a major
effect on agriculture. A large amount of herbicide has been used for
controlling weeds in agriculture fields, lawns, golf courses, sport
fields, etc. Random spraying of herbicides does not meet the exact
requirement of the field. Certain areas in field have more weed
patches than estimated. So, we need a visual system that can
discriminate weeds from the field image which will reduce or even
eliminate the amount of herbicide used. This would allow farmers to
not use any herbicides or only apply them where they are needed. A
machine vision precision automated weed control system could
reduce the usage of chemicals in crop fields. In this paper, an
intelligent system for automatic weeding strategy Multi Resolution
Combined Statistical & spatial Frequency is used to discriminate the
weeds from the crops and to classify them as narrow, little and broad
weeds.
Abstract: In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the BMI trends for this unique population
was of particular interest. The nexus between health, physical
activity and aging is complex and has raised much interest in recent
times due to the realization that a multifaceted approach is necessary
in order to counteract the obesity pandemic. By investigating age
based trends within a population adhering to competitive sport at
older ages, further insight might be gleaned to assist in understanding
one of many factors influencing this relationship.BMI was derived
using data gathered on a total of 6,071 masters athletes (51.9% male,
48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at
the Sydney World Masters Games (2009). Using linear and loess
regression it was demonstrated that the usual tendency for prevalence
of higher BMI increasing with age was reversed in the sample. This
trend in reversal was repeated for both male and female only sub-sets
of the sample participants, indicating the possibility of improved
prevalence of BMI with increasing age for both the sample as a
whole and these individual sub-groups.This evidence of improved
classification in one index of health (reduced BMI) for masters
athletes (when compared to the general population) implies there are
either improved levels of this index of health with aging due to
adherence to sport or possibly the reduced BMI is advantageous and
contributes to this cohort adhering (or being attracted) to masters
sport at older ages.
Abstract: In this paper, a neural network technique is applied to
real-time classifying media while a projectile is penetrating through
them. A laboratory-scaled penetrating setup was built for the
experiment. Features used as the network inputs were extracted from
the acceleration of penetrator. 6000 set of features from a single
penetration with known media and status were used to train the neural
network. The trained system was tested on 30 different penetration
experiments. The system produced an accuracy of 100% on the
training data set. And, their precision could be 99% for the test data
from 30 tests.
Abstract: The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.
Abstract: This paper is concerned with the existence of a linear copositive Lyapunov function(LCLF) for a special class of switched positive linear systems(SPLSs) composed of continuousand discrete-time subsystems. Firstly, by using system matrices, we construct a special kind of matrices in appropriate manner. Secondly, our results reveal that the Hurwitz stability of these matrices is equivalent to the existence of a common LCLF for arbitrary finite sets composed of continuous- and discrete-time positive linear timeinvariant( LTI) systems. Finally, a simple example is provided to illustrate the implication of our results.
Abstract: Organization of video databases is becoming difficult
task as the amount of video content increases. Video classification
based on the content of videos can significantly increase the speed of
tasks such as browsing and searching for a particular video in a
database. In this paper, a content-based videos classification system
for the classes indoor and outdoor is presented. The system is
intended to be used on a mobile platform with modest resources. The
algorithm makes use of the temporal redundancy in videos, which
allows using an uncomplicated classification model while still
achieving reasonable accuracy. The training and evaluation was done
on a video database of 443 videos downloaded from a video sharing
service. A total accuracy of 87.36% was achieved.