Abstract: This study was a part of the three-year longitudinal
research on setting up an math learning model for the disadvantaged
students in Taiwan. A target 2nd grade class with 10 regular students
and 6 disadvantaged students at a disadvantaged area in Taipei
participated in this study. Two units of a market basal math textbook
concerning fractions, three-dimensional figures, weight and capacity
were adapted to enhance their math learning motivations, confidences
and effects. The findings were (1) curriculum adaptation was effective
on enhancing students- learning motivations, confidences and effects;
(2) story-type problems and illustrations decreased difficulties on
understanding math language for students from new immigrant
families and students with special needs; (3) “concrete –
semiconcrete – abstract" teaching strategies and hands-on activities
were essential to raise students learning interests and effects; and (4)
curriculum adaptation knowledge and skills needed to be included in
the pre- and in-service teacher training programs.
Abstract: The objective of this research intends to create a suitable model of distance training for community leaders in the upper northeastern region of Thailand. The implementation of the research process is divided into four steps: The first step is to analyze relevant documents. The second step deals with an interview in depth with experts. The third step is concerned with constructing a model. And the fourth step takes aim at model validation by expert assessments. The findings reveal the two important components for constructing an appropriate model of distance training for community leaders in the upper northeastern region. The first component consists of the context of technology management, e.g., principle, policy and goals. The second component can be viewed in two ways. Firstly, there are elements comprising input, process, output and feedback. Secondly, the sub-components include steps and process in training. The result of expert assessments informs that the researcher-s constructed model is consistent and suitable and overall the most appropriate.
Abstract: Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is easy to get a dataset of interacting proteins as positive examples, there are no experimentally confirmed non-interacting proteins to be considered as negative examples. Therefore, in this paper we solve this problem as a one-class classification problem using one-class support vector machines (SVM). Using only positive examples (interacting protein pairs) in training phase, the one-class SVM achieves accuracy of about 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with comparable accuracy to the binary classifiers that use artificially constructed negative examples.
Abstract: There is inadequate information on the practice of
female genital mutilation (FGM) in the UK, and there are often
myths and perceptions within communities that influence the
effectiveness of prevention programmes. This means it is difficult to
address the trends and changes in the practice in the UK.
To this end, FORWARD undertook novel and innovative research
using the Participatory Ethnographic and Evaluative Research
(PEER) method to explore the views of women from Eritrea, Sudan,
Somalia and Ethiopia that live in London and Bristol (two UK cities).
Women-s views, taken from PEER interviews, reflected reasons for
continued practice of FGM: marriageability, the harnessing and
control of female sexuality, and upholding traditions from their
countries of origin. It was also clear that the main supporters of the
practice were believed to be older women within families and
communities.
Women described the impact FGM was having on their lives as
isolating. And although it was clearly considered a private and
personal matter, they developed a real sense of connection with their
peers within the research process.
The women were overwhelmingly positive about combating the
practice, although they believed it would probably take a while
before it ends completely. They also made concrete
recommendations on how to improve support services for women
affected by FGM: Training for professionals (particularly in
healthcare), increased engagement with, and outreach to,
communities, culturally appropriate materials and information made
available and accessible to communities, and more consequent
implementation of legislation.
Finally, the women asked for more empathy and understanding,
particularly from health professionals. Rather than presenting FGM
as a completely alien and inconceivable practice, it may help for
those looking into these women-s lives and working with them to
understand the social and economic context in which the practice
takes place.
Abstract: The purpose of the study was to find out the efficacy
of selected mobility exercises and participation in special games on psychomotor abilities, functional abilities and skill performance
among intellectually disabled children of age group under 14. Thirty male students who were studying in Balar Kalvi Nilayam and YMCA
College Special School, Chennai, acted as subjects for the study.
They were only mild and moderate in intellectual disability. These
students did not undergo any special training or coaching programme apart from their regular routine physical activity classes as a part of
the curriculum in the school. They were attached at random, based on
age in which 30 belonged to under 14 age group, which was divided
into three equal group of ten for each experimental treatment. 10
students (Treatment group I) underwent calisthenics and special
games participation, 10 students (Treatment group II) underwent
aquatics and special games participation, 10 students (Treatment
group III) underwent yoga and special games participation. The subjects were tested on selected criterion variables prior (pre test)
and after twelve weeks of training (post test). The pre and post test
data collected from three groups on functional abilities(self care,
learning, capacity for independent living), psychomotor
variables(static balance, eye hand coordination, simple reaction time
test) and skill performance (bocce skill, badminton skill, table tennis
skill) were statistically examined for significant difference, by
applying the analysis ANACOVA. Whenever an 'F' ratio for
adjusted test was found to be significant for adjusted post test means,
Scheffe-s test was followed as a post-hoc test to determine which of
the paired mean differences was significant. The result of the study
showed that among under 14 age groups there was a significant improvement on selected criterion variables such as, Balance,
Coordination, self-care and learning and also in Bocce, Badminton & Table Tennis skill performance, due to mobility exercises and
participation in special games. However there were no significant
differences among the groups.
Abstract: In this paper we propose a method for recognition of
adult video based on support vector machine (SVM). Different kernel
features are proposed to classify adult videos. SVM has an advantage
that it is insensitive to the relative number of training example in
positive (adult video) and negative (non adult video) classes. This
advantage is illustrated by comparing performance between different
SVM kernels for the identification of adult video.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: The paper aims to specify and build a system, a learning support in radiology-senology (breast radiology) dedicated to help assist junior radiologists-senologists in their radiologysenology- related activity based on experience of expert radiologistssenologists. This system is named SAFRS (i.e. system supporting the training of radiologists-senologists). It is based on the exploitation of radiologic-senologic images (primarily mammograms but also echographic images or MRI) and their related clinical files. The aim of such a system is to help breast cancer screening in education. In order to acquire this expert radiologist-senologist knowledge, we have used the CBR (case-based reasoning) approach. The SAFRS system will promote the evolution of teaching in radiology-senology by offering the “junior radiologist" trainees an advanced pedagogical product. It will permit a strengthening of knowledge together with a very elaborate presentation of results. At last, the know-how will derive from all these factors.
Abstract: The study attempted to identify the dominant
intelligences of athletes by comparing the developmental differences
of multiple intelligences between athletes and non-athletes. The
weekly specialized training hours and years of specialized training
was examined to see how it can predict the dominant intelligence with
the age factor controlled. There were 355 participants in the research
(202 athletes and 153 non-athletes). Collected data were analyzed with
one-way MANOVA and multiple hierarchical regression. The results
suggested the dominant intelligences of athletes were Interpersonal
Intelligence, Bodily-Kinesthetic Intelligence, and Intrapersonal
Intelligence. The weekly specialized training hours and years of
specialized training could effectively predict the Interpersonal
Intelligence, Bodily-Kinesthetic Intelligence, and Intrapersonal
Intelligence of athletes. The author suggested the future studies could
focus on the theory construction of weekly specialized training and
years of specialized training. Also, the studies on using “Bridge
strategy" by the athletes to guide disadvantage intelligences with
dominant intelligences are highly valued.
Abstract: For professions of high risk industries, simulation training has always been thought in terms of high degree of fidelity regarding the real operational situation. Due to the recent progress, this way of training is changing, modifying the human-computer and software interactions: the interactions between trainees during simulation training session tend to become virtual, transforming the social-based embodiness (the way subjects integrate social skills for interpersonal relationship with co-workers). On the basis of the analysis of eight different profession trainings, a categorization of interactions has help to produce an analytical tool, the social interactions table. This tool may be very valuable to point out the changes of social interactions when the training sessions are skipping from a high fidelity simulator to a virtual simulator. In this case, it helps the designers of professional training to analyze and to assess the consequences of the potential lack the social-based embodiness.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: This paper presents a new version of the SVM mixture algorithm initially proposed by Kwok for classification and regression problems. For both cases, a slight modification of the mixture model leads to a standard SVM training problem, to the existence of an exact solution and allows the direct use of well known decomposition and working set selection algorithms. Only the regression case is considered in this paper but classification has been addressed in a very similar way. This method has been successfully applied to engine pollutants emission modeling.
Abstract: The purpose of the study was to investigate the
effectiveness of ICT training workshop of tutors of Allama Iqbal
Open University Pakistan. The study was delimited to tutors of
Multan region. The total sample comprised of 100 tutors. All the
tutors who participated in ICT training workshop in Multan region
were taken as sample in the study. A questionnaire having two parts,
based on five point rating scale was developed by the researcher. Part
one was about the competency level of computer skills while Part
two was based on items related to training delivery, structure and
content. Part One of questionnaire had five levels of competency
about computer skills. The questionnaire was personally administered
and collected back by the researcher himself on the last day of
workshop.
The collected data were analyzed by using descriptive statistics.
Through this study it was found that majority of the tutors strongly
agreed that training enhanced their computer skills. Majority of the
respondents consider themselves to be generally competent in the use
of computer. They also agreed that there was appropriate
infrastructure and technical support in lab during training workshop.
Moreover, it was found that the training imparted the knowledge of
pedagogy of using computers for distance education.
Abstract: The utilisation of Industrial Building System (IBS) in construction industry will lead to a safe site condition since minimum numbers of workers are required to be on-site, timely material delivery, systematic component storage, reduction of construction material and waste. These matters are being promoted in the Construction Industry Master Plan (CIMP 2006-2015). However, the enabling factors of IBS that will foster a safer working environment are indefinite; on that basis a research has been conducted. The purpose of this paper is to discuss and identify the relevant factors towards safety improvement for IBS. A quantitative research by way of questionnaire surveys have been conducted to 314 construction companies. The target group was Grade 5 to Grade 7 contractors registered with Construction Industry Development Board (CIDB) which specialise in IBS. The findings disclosed seven factors linked to the safety improvement of IBS construction site in Malaysia. The factors were historical, economic, psychological, technical, procedural, organisational and the environmental factors. From the findings, a psychological factor ranked as the highest and most crucial factor contributing to safer IBS construction site. The psychological factor included the self-awareness and influences from workmates behaviour. Followed by organisational factors, where project management style will encourage the safety efforts. From the procedural factors, it was also found that training was one of the significant factors to improve safety culture of IBS construction site. Another important finding that formed as a part of the environmental factor was storage of IBS components, in which proper planning of the layout would able to contribute to a safer site condition. To conclude, in order to improve safety of IBS construction site, a welltrained and skilled workers are required for IBS projects, thus proper training is permissible and should be emphasised.
Abstract: A feasibility study for the design and construction of a
pilot plant for the extraction of castor oil in South Africa was
conducted. The study emphasized the four critical aspects of project
feasibility analysis, namely technical, financial, market and
managerial aspects. The technical aspect involved research on
existing oil extraction technologies, namely: mechanical pressing and
solvent extraction, as well as assessment of the proposed production
site for both short and long term viability of the project. The site is
on the outskirts of Nkomazi village in the Mpumalanga province,
where connections for water and electricity are currently underway,
potential raw material supply proves to be reliable since the province
is known for its commercial farming. The managerial aspect was
evaluated based on the fact that the current producer of castor oil will
be fully involved in the project while receiving training and technical
assistance from Sasol Technology, the TSC and SEDA. Market and
financial aspects were evaluated and the project was considered
financially viable with a Net Present Value (NPV) of R2 731 687 and
an Internal Rate of Return (IRR) of 18% at an annual interest rate of
10.5%. The payback time is 6years for analysis over the first 10
years with a net income of R1 971 000 in the first year. The project
was thus found to be feasible with high chance of success while
contributing to socio-economic development. It was recommended
for lab tests to be conducted to establish process kinetics that would
be used in the initial design of the plant.
Abstract: This paper presents an exact pruning algorithm with
adaptive pruning interval for general dynamic neural networks
(GDNN). GDNNs are artificial neural networks with internal dynamics.
All layers have feedback connections with time delays to the
same and to all other layers. The structure of the plant is unknown, so
the identification process is started with a larger network architecture
than necessary. During parameter optimization with the Levenberg-
Marquardt (LM) algorithm irrelevant weights of the dynamic neural
network are deleted in order to find a model for the plant as
simple as possible. The weights to be pruned are found by direct
evaluation of the training data within a sliding time window. The
influence of pruning on the identification system depends on the
network architecture at pruning time and the selected weight to be
deleted. As the architecture of the model is changed drastically during
the identification and pruning process, it is suggested to adapt the
pruning interval online. Two system identification examples show
the architecture selection ability of the proposed pruning approach.
Abstract: The main purpose of this study was to establish Professional Competency Contents for International Marketer in Taiwan. To establish these contents a set of interviews with international marketing managers and three rounds of Delphi Technique surveys were employed. Five international marketing managers were interviewed for discussions on definitions, framework, and items of international marketing competency. A questionnaire for the " Delphi Technique Survey " was developed based on the results acquired from the interviews. The resulting questionnaire was distributed to another group of 30 international marketer of trading companies in Taiwan. After three rounds of Delphi Technique Survey with these participants, the "Contents of Professional Competency for International Marketer " was established. Five dimensions and thirty indicators were identified. It is hoped that the proposed contents could be served as a self-evaluation tool for international marketer as well as the basis for staffing and training programs for international marketer in Taiwan.
Abstract: Saturated hydraulic conductivity is one of the soil
hydraulic properties which is widely used in environmental studies
especially subsurface ground water. Since, its direct measurement is
time consuming and therefore costly, indirect methods such as
pedotransfer functions have been developed based on multiple linear
regression equations and neural networks model in order to estimate
saturated hydraulic conductivity from readily available soil
properties e.g. sand, silt, and clay contents, bulk density, and organic
matter. The objective of this study was to develop neural networks
(NNs) model to estimate saturated hydraulic conductivity from
available parameters such as sand and clay contents, bulk density,
van Genuchten retention model parameters (i.e. r
θ , α , and n) as well
as effective porosity. We used two methods to calculate effective
porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s
θ is
saturated water content, FC θ is water content retained at -33 kPa
matric potential, and inf θ is water content at the inflection point.
Total of 311 soil samples from the UNSODA database was divided
into three groups as 187 for the training, 62 for the validation (to
avoid over training), and 62 for the test of NNs model. A commercial
neural network toolbox of MATLAB software with a multi-layer
perceptron model and back propagation algorithm were used for the
training procedure. The statistical parameters such as correlation
coefficient (R2), and mean square error (MSE) were also used to
evaluate the developed NNs model. The best number of neurons in
the middle layer of NNs model for methods (1) and (2) were
calculated 44 and 6, respectively. The R2 and MSE values of the test
phase were determined for method (1), 0.94 and 0.0016, and for
method (2), 0.98 and 0.00065, respectively, which shows that method
(2) estimates saturated hydraulic conductivity better than method (1).
Abstract: A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.