Abstract: In the paper, the relative performances on spectral
classification of short exon and intron sequences of the human and
eleven model organisms is studied. In the simulations, all
combinations of sixteen one-sequence numerical representations, four
threshold values, and four window lengths are considered. Sequences
of 150-base length are chosen and for each organism, a total of
16,000 sequences are used for training and testing. Results indicate
that an appropriate combination of one-sequence numerical
representation, threshold value, and window length is essential for
arriving at top spectral classification results. For fixed-length
sequences, the precisions on exon and intron classification obtained
for different organisms are not the same because of their genomic
differences. In general, precision increases as sequence length
increases.
Abstract: This paper aims at identifying and analyzing the
knowledge transmission channels in textile and clothing clusters
located in Brazil and in Europe. Primary data was obtained through
interviews with key individuals. The collection of primary data was
carried out based on a questionnaire with ten categories of indicators
of knowledge transmission. Secondary data was also collected
through a literature review and through international organizations
sites. Similarities related to the use of the main transmission channels
of knowledge are observed in all cases. The main similarities are:
influence of suppliers of machinery, equipment and raw materials;
imitation of products and best practices; training promoted by
technical institutions and businesses; and cluster companies being
open to acquire new knowledge. The main differences lie in the
relationship between companies, where in Europe the intensity of this
relationship is bigger when compared to Brazil. The differences also
occur in importance and frequency of the relationship with the
government, with the cultural environment, and with the activities of
research and development. It is also found factors that reduce the
importance of geographical proximity in transmission of knowledge,
and in generating trust and the establishment of collaborative
behavior.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: The one-class support vector machine “support vector
data description” (SVDD) is an ideal approach for anomaly or outlier
detection. However, for the applicability of SVDD in real-world
applications, the ease of use is crucial. The results of SVDD are
massively determined by the choice of the regularisation parameter C
and the kernel parameter of the widely used RBF kernel. While for
two-class SVMs the parameters can be tuned using cross-validation
based on the confusion matrix, for a one-class SVM this is not
possible, because only true positives and false negatives can occur
during training. This paper proposes an approach to find the optimal
set of parameters for SVDD solely based on a training set from
one class and without any user parameterisation. Results on artificial
and real data sets are presented, underpinning the usefulness of the
approach.
Abstract: Much research into handwritten Thai character
recognition have been proposed, such as comparing heads of
characters, Fuzzy logic and structure trees, etc. This paper presents a
system of handwritten Thai character recognition, which is based on
the Ant-minor algorithm (data mining based on Ant colony
optimization). Zoning is initially used to determine each character.
Then three distinct features (also called attributes) of each character
in each zone are extracted. The attributes are Head zone, End point,
and Feature code. All attributes are used for construct the
classification rules by an Ant-miner algorithm in order to classify
112 Thai characters. For this experiment, the Ant-miner algorithm is
adapted, with a small change to increase the recognition rate. The
result of this experiment is a 97% recognition rate of the training set
(11200 characters) and 82.7% recognition rate of unseen data test
(22400 characters).
Abstract: this paper presents a novel neural network controller
with composite adaptation low to improve the trajectory tracking
problems of biped robots comparing with classical controller. The
biped model has 5_link and 6 degrees of freedom and actuated by
Plated Pneumatic Artificial Muscle, which have a very high power to
weight ratio and it has large stoke compared to similar actuators. The
proposed controller employ a stable neural network in to approximate
unknown nonlinear functions in the robot dynamics, thereby
overcoming some limitation of conventional controllers such as PD
or adaptive controllers and guarantee good performance. This NN
controller significantly improve the accuracy requirements by
retraining the basic PD/PID loop, but adding an inner adaptive loop
that allows the controller to learn unknown parameters such as
friction coefficient, therefore improving tracking accuracy.
Simulation results plus graphical simulation in virtual reality show
that NN controller tracking performance is considerably better than
PD controller tracking performance.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: It well recognized that one feature that makes a
successful company is its ability to successfully align its business goals with its information communication technologies platform.
Enterprise Resource Planning (ERP) systems contribute to achieve better performance by integrating various business functions and
providing support for information flows. However, the technological
systems complexity is known to prevent the business users to exploit in an efficient way the Enterprise Resource Planning Systems (ERP).
This paper aims to investigate the role of training in improving the
usage of ERP systems. To this end, we have designed an instrument
survey to employees of a Norwegian multinational global provider of
technology solutions. Based on the analysis of collected data, we have delineated a training model that could be high relevance for
both researchers and practitioners as a step towards a better
understanding of ERP system implementation.
Abstract: Participation in sporting activities can lead to injury.
Sport injuries have been widely studied in many sports including the
more extreme categories of aquatic board sports. Kitesurfing is a
relatively new water surface action sport, and has not yet been
widely studied in terms of injuries and stress on the body. The aim of
this study was to get information about which injuries that are most
common among kitesurfing participants, where they occur, and their
causes. Injuries were studied using an international open web
questionnaire (n=206).
The results showed that many respondents reported injuries, in
total 251 injuries to knee (24%), ankle (17%), trunk (16%) and
shoulders (10%), often sustained while doing jumps and tricks
(40%). Among the reported injuries were joint injuries (n=101),
muscle/tendon damages (n=47), wounds and cuts (n=36) and bone
fractures (n=28). Also environmental factors and equipment can
influence the risk of injury, or the extent of injury in a hazardous
situation. Conclusively, the information from this retrospective study
supports earlier studies in terms of prevalence and site of injuries.
Suggestively, this information should be used for to build a
foundation of knowledge about the sport for development of
applications for physical training and product development.
Abstract: The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.
Abstract: According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.
Abstract: It is quite essential to form dialogue mechanisms and
dialogue channels to solve intercultural communication issues.
Therefore, every country should develop a intercultural education
project which aims to resolve international communication issues.
For proper mediation training, the first step is to reach an agreement
on the actors to run the project. The strongest mediation mechanisms
in the world should be analyzed and initiated within the educational
policies. A communication-based mediation model should be
developed for international mediation training. Mediators can use
their convincing communication skills as a part of this model. At the
first, fundamental stages of the mediation training should be specified
within the scope of the model. Another important topic at this point is
common sence and peace leaders to act as an ombudsman in this
process. Especially for solving some social issues and conflicts,
common sense leaders acting as an ombudsman would lead to
effective communication. In mediation training that is run by
universities and non-governmental organizations, another phase is to
focus on conducting the meetings. In intercultural mediation training,
one of the most critical topics is to conduct the meeting traffic and
performing a shuttle diplomacy. Meeting traffic is where the mediator
organizes meetings with the parties with initiative powers, in order to
contribute to the solution of the issue, and schedule these meetings.
In this notice titled “ Intercultural mediation training and the training
process of common sense leaders by the leadership of universities
communication and artistic campaigns" , communication models and
strategies about this topic will be constructed and an intercultural art
activities and perspectives will be presented.
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
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: Along with the basic features of students\' culture
information, with its widely usage oriented on implementation of the
new information technologies in educational process that determines
the search for ways of pointing to the similarity of interdisciplinary
connections content, aims and objectives of the study. In this regard,
the article questions about students\' information culture, and also
presented information about the aims and objectives of the
information culture process among students. In the formation of a
professional interest in relevant information, which is an opportunity
to assist in informing the professional activities of the essence of
effective use of interactive methods and innovative technologies in
the learning process. The result of the experiment proves the
effectiveness of the information culture process of students in
training the system of higher education based on the credit
technology. The main purpose of this paper is a comprehensive
review of students\' information culture.
Abstract: Technical laboratories are typically considered as
highly hazardous places in the polytechnic institution when
addressing the problems of high incidences and fatality rates. In
conjunction with several topics covered in the technical curricular,
safety and health precaution should be highlighted in order to
connect to few key ideas of being safe. Therefore the assessment of
safety awareness in terms of safety and health about hazardous and
risks at laboratories is needed and has to be incorporated with
technical education and other training programmes. The purpose of
this study was to determine the efficacy of technical laboratory safety
in one of the polytechnics in northern region. The study examined
three related issues that were; the availability of safety material and
equipment, safety practice adopted by technical teachers and
administrator-s safety attitudes in enforcing safety to the students. A
model of efficacy technical laboratory was developed to test the
linear relationship between existing safety material and equipment,
teachers- safety practice and administrators- attitude in enforcing
safety and to identify which of technical laboratory safety issues was
the most pertinent factor to realize safety in technical laboratory.
This was done by analyzing survey-based data sets particularly those
obtained from samples of 210 students in the polytechnic. The
Pearson Correlation was used to measure the association between the
variables and to test the research hypotheses. The result of the study
has found that there was a significant correlation between existing
safety material and equipment, safety practice adopted by teacher
and administrator-s attitude. There was also a significant relationship
between technical laboratory safety and safety practice adopted by
teacher and between technical laboratory safety and administrator
attitude. Hence, safety practice adopted by teacher and administrator
attitude is vital in realizing technical laboratory safety.
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: In this paper, an overview is made on the educational and research activities in the field of physical medicine and rehabilitation in Libya, including development in rehabilitation science, research, training, occupational therapy, physiotherapy and physiatrist, which are mainly concerned with the patients in Libya[3] [13].