Abstract: This article describes the implementation of an
experimental model for teaching ICT tools and digital environments
in teachers training college. In most educational systems in the
Western world, new programs were developed in order to bridge the
digital gap between teachers and students. In spite of their
achievements, these programs are limited due to several factors: The
teachers in the schools implement new methods incorporating
technological tools into the curriculum, but meanwhile the
technology changes and advances. The interface of tools changes
frequently, some tools disappear and new ones are invented. These
conditions require an experimental model of training the pre-service
teachers. The appropriate method for instruction within the domain of
ICT tools should be based on exposing the learners to innovations,
helping them to gain experience, teaching them how to deal with
challenges and difficulties on their own, and training them. This
study suggests some principles for this approach and describes step
by step the implementation of this model.
Abstract: Debts reconstruction under some of moratorium
projects is one of important method that highly benefits to both the
Banks and farmers. The method can reduce probabilities for nonprofits
loan. This paper discuss about debts reconstruction and career
development training for farmers in Thailand between 2011 and
2013. The research designed is mix-method between quantitative
survey and qualitative survey. Sample size for quantitative method is
1003 cases. Data gathering procedure is between October and
December 2013. Main results affirmed that debts reconstruction is
needed. And there are numerous benefits from farmers’ career
development training. Many of farmers who attend field school
activities able to bring knowledge learned to apply for the farms’
work. They can reduce production costs. Framers’ quality of life and
their household well-being also improve. This program should apply
in any countries where farmers have highly debts and highly risks for
not return the debts.
Abstract: Mumbai, being traditionally the epicenter of India's
trade and commerce, the existing major ports such as Mumbai and
Jawaharlal Nehru Ports (JN) situated in Thane estuary are also
developing its waterfront facilities. Various developments over the
passage of decades in this region have changed the tidal flux
entering/leaving the estuary. The intake at Pir-Pau is facing the
problem of shortage of water in view of advancement of shoreline,
while jetty near Ulwe faces the problem of ship scheduling due to
existence of shallower depths between JN Port and Ulwe Bunder. In
order to solve these problems, it is inevitable to have information
about tide levels over a long duration by field measurements.
However, field measurement is a tedious and costly affair;
application of artificial intelligence was used to predict water levels
by training the network for the measured tide data for one lunar tidal
cycle. The application of two layered feed forward Artificial Neural
Network (ANN) with back-propagation training algorithms such as
Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to
predict the yearly tide levels at waterfront structures namely at Ulwe
Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe,
and Vashi for a period of lunar tidal cycle (2013) was used to train,
validate and test the neural networks. These trained networks having
high co-relation coefficients (R= 0.998) were used to predict the tide
at Ulwe, and Vashi for its verification with the measured tide for the
year 2000 & 2013. The results indicate that the predicted tide levels
by ANN give reasonably accurate estimation of tide. Hence, the
trained network is used to predict the yearly tide data (2015) for
Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was
predicted by using the neural network which was trained with the
help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The
measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is
maximum amplification of tide by about 10-20 cm with a phase lag
of 10-20 minutes with reference to the tide at Apollo Bunder
(Mumbai). LM training algorithm is faster than GD and with increase
in number of neurons in hidden layer and the performance of the
network increases. The predicted tide levels by ANN at Pir-Pau and
Ulwe provides valuable information about the occurrence of high and
low water levels to plan the operation of pumping at Pir-Pau and
improve ship schedule at Ulwe.
Abstract: The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.
Abstract: In the aviation industry, many faults may occur frequently during the maintenance processes and assembly operations of complex structured aircrafts because of their high dependencies of components. These faults affect the quality of aircraft parts or developed modules adversely. Technical employee requires long time and high labor force while checking the correctness of each component. In addition, the person must be trained regularly because of the ever-growing and changing technology. Generally, the cost of this training is very high. Augmented Reality (AR) technology reduces the cost of training radically and improves the effectiveness of the training. In this study, the usage of AR technology in the aviation industry has been investigated and the effectiveness of AR with heads-up display glasses has been examined. An application has been developed for comparison of production process with AR and manual one.
Abstract: Thoracotomy is a great surgery that has serious pulmonary complications, so purpose of this study was to determine the response of diaphragmatic excursion to inspiratory muscle trainer post thoracotomy. Thirty patients of both sexes (16 men and 14 women) with age ranged from 20 to 40 years old had done thoracotomy participated in this study. The practical work was done in cardiothoracic department, Kasr-El-Aini hospital at faculty of medicine for individuals 3 days Post operatively. Patients were assigned into two groups: group A (study group) included 15 patients (8 men and 7 women) who received inspiratory muscle training by using inspiratory muscle trainer for 20 minutes and routine chest physiotherapy (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Group B (control group) included 15 patients (8 men and 7 women) who received the routine chest physiotherapy only (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Ultrasonography was used to evaluate the changes in diaphragmatic excursion before and after training program. Statistical analysis revealed a significant increase in diaphragmatic excursion in the study group (59.52%) more than control group (18.66%) after using inspiratory muscle trainer post operatively in patients post thoracotomy. It was concluded that the inspiratory muscle training device increases diaphragmatic excursion in patients post thoracotomy through improving inspiratory muscle strength and improving mechanics of breathing and using of inspiratory muscle trainer as a method of physical therapy rehabilitation to reduce post-operative pulmonary complications post thoracotomy.
Abstract: This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post-surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.
Abstract: The paper focuses on the distance laboratory
organisation for training the electrical engineering staff and students
in the fields of electrical drive and power electronics. To support
online knowledge acquisition and professional enhancement, new
challenges in remote education based on an active learning approach
with self-assessment have been emerged by the authors. Following
the literature review and explanation of the improved assessment
methodology, the concept and technological basis of the labs
arrangement are presented. To decrease the gap between the distance
study of the up-to-date equipment and other educational activities in
electrical engineering, the improvements in the following-up the
learners’ progress and feedback composition are introduced. An
authoring methodology that helps to personalise knowledge
acquisition and enlarge Web-based possibilities is described.
Educational management based on self-assessment is discussed.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: English like any other language is rich by means of arbitrary, conventional, symbols which lend it to lot of inconsistencies in spelling, phonology, syntax, and morphology. The research examines the irregularities prevalent in the structure and meaning of some ‘er’ lexical items in English and its implication to vocabulary acquisition. It centers its investigation on the derivational suffix ‘er’, which changes the grammatical category of word. English language poses many challenges to Second Language Learners because of its irregularities, exceptions, and rules. One of the meaning of –er derivational suffix is someone or somebody who does something. This rule often confuses the learners when they meet with the exceptions in normal discourse. The need to investigate instances of such inconsistencies in the formation of –er words and the meanings given to such words by the students motivated this study. For this purpose, some senior secondary two (SS2) students in six randomly selected schools in the metropolis were provided a large number of alphabetically selected ‘er’ suffix ending words, The researcher opts for a test technique, which requires them to provide the meaning of the selected words with- er. The marking of the test was scored on the scale of 1-0, where correct formation of –er word and meaning is scored one while wrong formation and meaning is scored zero. The number of wrong and correct formations of –er words meaning were calculated using percentage. The result of this research shows that a large number of students made wrong generalization of the meaning of the selected -er ending words. This shows how enormous the inconsistencies are in English language and how are affect the learning of English. Findings from the study revealed that though students mastered the basic morphological rules but the errors are generally committed on those vocabulary items that are not frequently in use. The study arrives at this conclusion from the survey of their textbook and their spoken activities. Therefore, the researcher recommends that there should be effective reappraisal of language teaching through implementation of the designed curriculum to reflect on modern strategies of teaching language, identification, and incorporation of the exceptions in rigorous communicative activities in language teaching, language course books and tutorials, training and retraining of teachers on the strategies that conform to the new pedagogy.
Abstract: Average temperatures worldwide are expected to
continue to rise. At the same time, major cities in developing
countries are becoming increasingly populated and polluted.
Governments are tasked with the problem of overheating and air
quality in residential buildings. This paper presents the development
of a model, which is able to estimate the occupant exposure
to extreme temperatures and high air pollution within domestic
buildings. Building physics simulations were performed using the
EnergyPlus building physics software. An accurate metamodel is
then formed by randomly sampling building input parameters and
training on the outputs of EnergyPlus simulations. Metamodels are
used to vastly reduce the amount of computation time required when
performing optimisation and sensitivity analyses. Neural Networks
(NNs) have been compared to a Radial Basis Function (RBF)
algorithm when forming a metamodel. These techniques were
implemented using the PyBrain and scikit-learn python libraries,
respectively. NNs are shown to perform around 15% better than RBFs
when estimating overheating and air pollution metrics modelled by
EnergyPlus.
Abstract: In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.
Abstract: The study is the way to identify the problems that
occur in organizing short course’s lifelong learning in the information
and communication technology (ICT) education which are faced by
the lecturer and staff at the Mara Skill Institute and Industrial
Training Institute in Pahang Malaysia. The important aspects of these
issues are classified to five which are selecting the courses
administrative. Fifty lecturers and staff were selected as a respondent.
The sample is selected by using the non-random sampling method
purpose sampling. The questionnaire is used as a research instrument
and divided into five main parts. All the data that gain from the
questionnaire are analyzed by using the SPSS in term of mean,
standard deviation and percentage. The findings showed, there are the
problems occur in organizing the short course for lifelong learning in
ICT education.
Abstract: In 2009, the new HRM policy was implemented in
Qatar for public sector organisations. The purpose of this research is
to examine how Qatar’s 2009 HRM policy was significant in
influencing employee retention in public organisations. The
conducted study utilised quantitative methodology to analyse the data
on employees’ perceptions of such HRM practices as Performance
Management, Rewards and Promotion, Training and Development
associated with the HRM policy in public organisations in
comparison to semi-private organisations. Employees of seven public
and semi-private organisations filled in the questionnaire based on
the 5-point Likert scale to present quantitative results. The data was
analysed with the correlation and multiple regression statistical
analyses. It was found that Performance Management had the
relationship with Employee Retention, and Rewards and Promotion
influenced Job Satisfaction in public organisations. Relationship
between Job Satisfaction and Employee Retention was also observed.
However, no significant differences were observed in the role of
HRM practices in public and semi-private organisations.
Abstract: The use of Computer Aided Design (CAD)
technologies has become pervasive in the Architecture, Engineering
and Construction (AEC) industry. This has led to its inclusion as an
important part of the training module in the curriculum for
Architecture Schools in Nigeria. This paper examines the ethical
questions that arise in the implementation of Computer Aided Design
(CAD) Content of the curriculum for Architectural education. Using
existing literature, it begins this scrutiny from the propriety of
inclusion of CAD into the education of the architect and the
obligations of the different stakeholders in the implementation
process. It also examines the questions raised by the negative use of
computing technologies as well as perceived negative influence of
the use of CAD on design creativity. Survey methodology was
employed to gather data from the Department of Architecture,
Chukwuemeka Odumegwu Ojukwu University Uli, which has been
used as a case study on how the issues raised are being addressed.
The paper draws conclusions on what will make for successful ethical
implementation.
Abstract: The purpose of the study is to investigate the level of
intrinsic motivation of trainers after attending a Continuous
Professional Development Course (CPD) organized by Institute of
Teacher Training Malaysia titled, “Transformation of Teaching and
Learning the Fun Way”. This study employed a survey whereby 96
teacher trainers were given Situational Intrinsic Motivational Scale
(SIMS) Instruments. Confirmatory factor analysis was carried out to
get the validity of this instrument in local setting. Data were analyzed
with SPSS for descriptive statistic. Semi- structured interviews were
also administrated to collect qualitative data on participants’
experiences after participating in the two-day fun-filled program. The
findings showed that the participants’ level of intrinsic motivation
showed higher mean than the amotivation. The results revealed that
the intrinsic motivation mean is 19.0 followed by Identified
regulation with a mean of 17.4, external regulation 9.7 and
amotivation 6.9. The interview data also revealed that the participants
were motivated after attending this training program. It can be
concluded that this program, which was organized by Institute of
Teacher Training Malaysia, was able to enhance participants’ level of
motivation. Self-Determination Theory (SDT) as a multidimensional
approach to motivation was utilized. Therefore, teacher trainers may
have more success using the “The fun way approach” in conducting
training program in future.
Abstract: In this paper, a robust fault detection and isolation
(FDI) scheme is developed to monitor a multivariable nonlinear
chemical process called the Chylla-Haase polymerization reactor,
when it is under the cascade PI control. The scheme employs a radial
basis function neural network (RBFNN) in an independent mode to
model the process dynamics, and using the weighted sum-squared
prediction error as the residual. The Recursive Orthogonal Least
Squares algorithm (ROLS) is employed to train the model to
overcome the training difficulty of the independent mode of the
network. Then, another RBFNN is used as a fault classifier to isolate
faults from different features involved in the residual vector. Several
actuator and sensor faults are simulated in a nonlinear simulation of
the reactor in Simulink. The scheme is used to detect and isolate the
faults on-line. The simulation results show the effectiveness of the
scheme even the process is subjected to disturbances and
uncertainties including significant changes in the monomer feed rate,
fouling factor, impurity factor, ambient temperature, and
measurement noise. The simulation results are presented to illustrate
the effectiveness and robustness of the proposed method.
Abstract: Education and practical training crisis management
members are a topical issue nowadays. The paper deals with the
perspectives and possibilities of "smart solutions" to education for
crisis management staff. Currently, there is a large number of
simulation tools, which notes that they are suitable for practical
training of crisis management staff. The first part of the paper is focused on the introduction of the
technology simulation tools. The simulators aim is to create a
realistic environment for the practical training of extending units of
crisis staff. The second part of the paper concerns the possibilities of using the
simulation technology to the education process. The aim of this
section is to introduce the practical capabilities and potential of the
simulation programs for practical training of crisis management staff.
Abstract: This study aims to investigate the relationships
between human resource management and entrepreneurship in the
view of owner-managers and employees, and among employees with
in the SME in Thailand. The research method used qualitative
method to confirm the phenomenology interest with top management
position which women are regarding their career path by using
purposive sampling method. The results showed that human
resources management has positive relate with the corporate
entrepreneurship are including the recruitment process, training
worker, professional career development and reward system impact
to entrepreneur’s knowledge and innovation of corporate
entrepreneurship in respectively to bring a very reliable way. Then,
the key informant suggested that women’s career experiences
predisposed them to find an alternative route for entrepreneurship,
despite having achieved top management. The understanding factors
that successfully contribute to the development of women
entrepreneurs from career development perspective are critical
endeavour for any type of organization as well.
Abstract: With the increasing dependence of countries on the
critical infrastructure, it increases their vulnerability. Big threat is
primarily in the human factor (personnel of the critical infrastructure)
and in terrorist attacks. It emphasizes the development of
methodology for searching of weak points and their subsequent
elimination. This article discusses methods for the analysis of safety
in the objects of critical infrastructure. It also contains proposal for
methodology for training employees of security services in the
objects of the critical infrastructure and developing scenarios of
attacks on selected objects of the critical infrastructure.