Abstract: In this paper we investigate the influence of external
noise on the inference of network structures. The purpose of our
simulations is to gain insights in the experimental design of microarray
experiments to infer, e.g., transcription regulatory networks
from microarray experiments. Here external noise means, that the
dynamics of the system under investigation, e.g., temporal changes of
mRNA concentration, is affected by measurement errors. Additionally
to external noise another problem occurs in the context of microarray
experiments. Practically, it is not possible to monitor the mRNA
concentration over an arbitrary long time period as demanded by the
statistical methods used to learn the underlying network structure. For
this reason, we use only short time series to make our simulations
more biologically plausible.
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: 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: Business and IT alignment has continued as a
top concern for business and IT executives for almost three
decades. Many researchers have conducted empirical studies on
the relationship between business-IT alignment and performance.
Yet, these approaches, lacking a social perspective, have had little
impact on sustaining performance and competitive advantage. In
addition to the limited alignment literature that explores
organisational learning that is represented in shared understanding,
communication, cognitive maps and experiences.
Hence, this paper proposes an integrated process that enables
social and intellectual dimensions through the concept of
organisational learning. In particular, the feedback and feedforward
process which provide a value creation across dynamic
multilevel of learning. This mechanism enables on-going
effectiveness through development of individuals, groups and
organisations, which improves the quality of business and IT
strategies and drives to performance.
Abstract: In this paper, we proposed a method to design a
model-following adaptive controller for linear/nonlinear plants.
Radial basis function neural networks (RBF-NNs), which are known
for their stable learning capability and fast training, are used to
identify linear/nonlinear plants. Simulation results show that the
proposed method is effective in controlling both linear and nonlinear
plants with disturbance in the plant input.
Abstract: The Information and Communication Technologies
(ICTs), and the Wide World Web (WWW) have fundamentally
altered the practice of teaching and learning world wide. Many
universities, organizations, colleges and schools are trying to apply
the benefits of the emerging ICT. In the early nineties the term
learning object was introduced into the instructional technology
vernacular; the idea being that educational resources could be broken
into modular components for later combination by instructors,
learners, and eventually computes into larger structures that would
support learning [1]. However in many developing countries, the use
of ICT is still in its infancy stage and the concept of learning object
is quite new. This paper outlines the learning object design
considerations for developing countries depending on learning
environment.
Abstract: Using activity theory, organisational theory and
didactics as theoretical foundations, a comprehensive model of the
organisational dimensions relevant for learning and knowledge
transfer will be developed. In a second step, a Learning Assessment
Guideline will be elaborated. This guideline will be designed to
permit a targeted analysis of organisations to identify the status quo
in those areas crucial to the implementation of learning and
knowledge transfer. In addition, this self-analysis tool will enable
learning managers to select adequate didactic models for e- and
blended learning. As part of the European Integrated Project
"Process-oriented Learning and Information Exchange" (PROLIX),
this model of organisational prerequisites for learning and knowledge
transfer will be empirically tested in four profit and non-profit
organisations in Great Britain, Germany and France (to be finalized
in autumn 2006). The findings concern not only the capability of the
model of organisational dimensions, but also the predominant
perceptions of and obstacles to learning in organisations.
Abstract: This paper provides a key driver-based conceptual framework that can be used to improve a firm-s success in commercializing technology and in new product innovation resulting from collaboration with other organizations through strategic alliances. Based on a qualitative study using an interview approach, strategic alliances of entrepreneurs in the food processing industry in Thailand are explored. This paper describes factors affecting decisions to collaborate through alliances. It identifies four issues: maintaining the efficiency of the value chain for production capability, adapting to present and future competition, careful assessment of value of outcomes, and management of innovation. We consider five driving factors: resource orientation, assessment of risk, business opportunity, sharing of benefits and confidence in alliance partners. These factors will be of interest to entrepreneurs and policy makers with regard to further understanding of the direction of business strategies.
Abstract: The objectives of this research paper were to study the
influencing factors that contributed to the success of electronic
commerce (e-commerce) and to study the approach to enhance the
standard of e-commerce for small and medium enterprises (SME).
The research paper focused the study on only sole proprietorship
SMEs in Bangkok, Thailand. The factors contributed to the success
of SME included business management, learning in the organization,
business collaboration, and the quality of website. A quantitative and
qualitative mixed research methodology was used. In terms of
quantitative method, a questionnaire was used to collect data from
251 sole proprietorships. The System Equation Model (SEM) was
utilized as the tool for data analysis. In terms of qualitative method,
an in-depth interview, a dialogue with experts in the field of ecommerce
for SMEs, and content analysis were used.
By using the adjusted causal relationship structure model, it was
revealed that the factors affecting the success of e-commerce for
SMEs were found to be congruent with the empirical data. The
hypothesis testing indicated that business management influenced the
learning in the organization, the learning in the organization
influenced business collaboration and the quality of the website, and
these factors, in turn, influenced the success of SMEs. Moreover, the
approach to enhance the standard of SMEs revealed that the majority
of respondents wanted to enhance the standard of SMEs to a high
level in the category of safety of e-commerce system, basic structure
of e-commerce, development of staff potentials, assistance of budget
and tax reduction, and law improvement regarding the e-commerce
respectively.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
Abstract: Self-efficacy, self-reliance, and motivation were
examined in a quasi-experimental study with 178 sophomore
university students. Participants used an interactive cardiovascular
anatomy and physiology CD-ROM, and completed a 15-item
questionnaire. Reliability of the questionnaire was established using
Cronbach-s alpha. Post-tests and course grades were examined using
a t-test, demonstrating no significance. Results of an item-to-item
analysis of the questionnaire showed overall satisfaction with the
teaching methodology and varied results for self-efficacy, selfreliance,
and motivation. Kendall-s Tau was calculated for all items
in the questionnaire.
Abstract: This paper presents a web based remote access
microcontroller laboratory. Because of accelerated development in
electronics and computer technologies, microcontroller-based devices
and appliances are found in all aspects of our daily life. Before the
implementation of remote access microcontroller laboratory an
experiment set is developed by teaching staff for training
microcontrollers. Requirement of technical teaching and industrial
applications are considered when experiment set is designed.
Students can make the experiments by connecting to the experiment
set which is connected to the computer that set as the web server. The
students can program the microcontroller, can control digital and
analog inputs and can observe experiment. Laboratory experiment
web page can be accessed via www.elab.aku.edu.tr address.
Abstract: The reliability of the tools developed to learn the
learning styles is essential to find out students- learning styles
trustworthily. For this purpose, the psychometric features of Grasha-
Riechman Student Learning Style Inventory developed by Grasha
was studied to contribute to this field. The study was carried out on
6th, 7th, and 8th graders of 10 primary education schools in Konya.
The inventory was applied twice with an interval of one month, and
according to the data of this application, the reliability coefficient
numbers of the 6 sub-dimensions pointed in the theory of the
inventory was found to be medium. Besides, it was found that the
inventory does not have a structure with 6 factors for both
Mathematics and English courses as represented in the theory.
Abstract: The Artificial immune systems algorithms are Meta
heuristic optimization method, which are used for clustering and
pattern recognition applications are abundantly. These algorithms in
multimodal optimization problems are more efficient than genetic
algorithms. A major drawback in these algorithms is their slow
convergence to global optimum and their weak stability can be
considered in various running of these algorithms. In this paper,
improved Artificial Immune System Algorithm is introduced for the
first time to overcome its problems of artificial immune system. That
use of the small size of a local search around the memory antibodies
is used for improving the algorithm efficiently. The credibility of the
proposed approach is evaluated by simulations, and it is shown that
the proposed approach achieves better results can be achieved
compared to the standard artificial immune system algorithms
Abstract: An additive fuzzy system comprising m rules with
n inputs and p outputs in each rule has at least t m(2n + 2 p + 1)
parameters needing to be tuned. The system consists of a large
number of if-then fuzzy rules and takes a long time to tune its
parameters especially in the case of a large amount of training data
samples. In this paper, a new learning strategy is investigated to cope
with this obstacle. Parameters that tend toward constant values at the
learning process are initially fixed and they are not tuned till the end
of the learning time. Experiments based on applications of the
additive fuzzy system in function approximation demonstrate that the
proposed approach reduces the learning time and hence improves
convergence speed considerably.
Abstract: Recently, Thai education system is engaged in serious and promising reforms. One of the crucial elements in most of these educational reforms is the teacher professional development. Teachers today are under growing pressure to perform. However, most new teachers are not adequately prepared to meet the expectation. Consequently, this paper seeks to investigate the opinion of mentor teachers and university supervisors about professional development in the aspect of learning management skill of the preservice teachers in Rajabhat Universities, then compare the opinion between the mentor teachers and university supervisors about professional development in the aspect of learning management skill of the pre-service teachers. The study involved a cohort of 40 university supervisors and 77 mentor teachers. The research concludes by showing that mentor teachers viewed pre-service teacher as a professional teacher with an effective learning management skill. However, in the perspective of the university supervisor, pre-service teachers still have inadequate learning management skill.
Abstract: The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.
Abstract: In this paper, we present a novel technique called Self-Learning Expert System (SLES). Unlike Expert System, where there is a need for an expert to impart experiences and knowledge to create the knowledge base, this technique tries to acquire the experience and knowledge automatically. To display this technique at work, a simulation of a mobile robot navigating through an environment with obstacles is employed using visual basic. The mobile robot will move through this area without colliding with any obstacle and save the path that it took. If the mobile robot has to go through a similar environment again, then it will apply this experience to help it move through quicker without having to check for collision.
Abstract: In this paper, a new learning approach for network
intrusion detection using naïve Bayesian classifier and ID3 algorithm
is presented, which identifies effective attributes from the training
dataset, calculates the conditional probabilities for the best attribute
values, and then correctly classifies all the examples of training and
testing dataset. Most of the current intrusion detection datasets are
dynamic, complex and contain large number of attributes. Some of
the attributes may be redundant or contribute little for detection
making. It has been successfully tested that significant attribute
selection is important to design a real world intrusion detection
systems (IDS). The purpose of this study is to identify effective
attributes from the training dataset to build a classifier for network
intrusion detection using data mining algorithms. The experimental
results on KDD99 benchmark intrusion detection dataset demonstrate
that this new approach achieves high classification rates and reduce
false positives using limited computational resources.
Abstract: This paper presents the results of the authors in designing, experimenting, assessing and transferring an innovative approach to energy education in secondary schools, aimed to enhance the quality of learning in terms of didactic curricula and pedagogic methods. The training is online delivered to youngsters via e-Books and portals specially designed for this purpose or by learning by doing via interactive games. An online educational methodology is available teachers.