Abstract: The aim of this research is to understand how the
emerging power bloc BRICS employs infrastructure development
narratives to construct a new world order. BRICS is an international
body consisting of five emerging countries that collaborate on
economic and political issues: Brazil, Russia, India, China, and South
Africa. This study explores the projection of infrastructure
development narratives through an analysis of BRICS’ attention to
infrastructure investment and financing, its support of the New
Partnership on African Development and the establishment of the
New Development Bank in Shanghai. The theory of Strategic
Narratives is used to explore BRICS’ commitment to infrastructure
development and to distinguish three layers: system narratives
(BRICS as a global actor to propose development reform), identity
narratives (BRICS as a collective identity joining efforts to act upon
development aspirations) and issue narratives (BRICS committed to a
range of issues of which infrastructure development is prominent).
The methodology that is employed is a narrative analysis of BRICS’
official documents, media statements, and website imagery. A
comparison of these narratives illuminates tensions at the three layers
and among the five member states. Identifying tensions among
development infrastructure narratives provides an indication of how
policymaking for infrastructure development could be improved.
Subsequently, it advances BRICS’ ability to act as a global actor to
construct a new world order.
Abstract: The recent instability in economy was found to be
influencing the situation in Malaysia whether directly or indirectly.
Taking that into consideration, the government needs to find the best
approach to balance its citizen’s socio-economic strata level urgently.
Through education platform is among the efforts planned and acted
upon for the purpose of balancing the effects of the influence,
through the exposure of social entrepreneurial activity towards youth
especially those in higher institution level. Armed with knowledge
and skills that they gained, with the support by entrepreneurial
culture and environment while in campus; indirectly, the students will
lean more on making social entrepreneurship as a career option when
they graduate. Following the issues of marketability and workability
of current graduates that are becoming dire, research involving how
far the willingness of student to create social innovation that
contribute to the society without focusing solely on personal gain is
relevant enough to be conducted. With that, this research is
conducted with the purpose of identifying the level of entrepreneurial
intention and social entrepreneurship among higher institution
students in Malaysia. Stratified random sampling involves 355
undergraduate students from five public universities had been made
as research respondents and data were collected through surveys. The
data was then analyzed descriptively using min score and standard
deviation. The study found that the entrepreneurial intention of higher
education students are on moderate level, however it is the contrary
for social entrepreneurship activities, where it was shown on a high
level. This means that while the students only have moderate level of
willingness to be a social entrepreneur, they are very committed to
created social innovation through the social entrepreneurship
activities conducted. The implication from this study can be
contributed towards the higher institution authorities in prediction the
tendency of student in becoming social entrepreneurs. Thus, the
opportunities and facilities for realizing the courses related to social
entrepreneurship must be created expansively so that the vision of
creating as many social entrepreneurs as possible can be achieved.
Abstract: This paper presents the design and analysis of Liquid Crystal (LC) based tunable reflectarray antenna with slot embedded patch element configurations within X-band frequency range. The slots are shown to modify the surface current distribution on the patch element of reflectarray which causes the resonant patch element to provide different resonant frequencies depending on the slot dimensions. The simulated results are supported and verified by waveguide scattering parameter measurements of different reflectarray unit cells. Different rectangular slots on patch element have been fabricated and a change in resonant frequency from 10.46GHz to 8.78GHz has been demonstrated as the width of the rectangular slot is varied from 0.2W to 0.6W. The rectangular slot in the center of the patch element has also been utilized for the frequency tunable reflectarray antenna design based on K-15 Nematic LC. For the active reflectarray antenna design, a frequency tunability of 1.2% from 10GHz to 9.88GHz has been demonstrated with a dynamic phase range of 103° provided by the measured scattering parameter results. Time consumed by liquid crystals for reconfiguration, which is one of the drawback of LC based design, has also been disused in this paper.
Abstract: Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
Abstract: Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Abstract: Teaching methods include lectures, workshops and
tutorials for the presentation and discussion of ideas have become out
of date; were developed outside the discipline of architecture from
the college of engineering and do not satisfy the architectural
students’ needs and causes them many difficulties in integrating
structure into their design. In an attempt to improve structure
teaching methods, this paper focused upon proposing a supportive
teaching/learning tool using multi-media applications which seeks to
better meet the architecture student’s needs and capabilities and
improve the understanding and application of basic and intermediate
structural engineering and technology principles. Before introducing
the use of multi-media as a supportive teaching tool, a questionnaire
was distributed to third year students of a structural design course
who were selected as a sample to be surveyed forming a sample of 90
cases. The primary aim of the questionnaire was to identify the
students’ learning style and to investigate whether the selected
method of teaching could make the teaching and learning process
more efficient. Students’ reaction on the use of this method was
measured using three key elements indicating that this method is an
appropriate teaching method for the nature of the students and the
course as well.
Abstract: Purpose: The key aim of the research was to identify
the secondary stressors experienced by businesses affected by single
or repeated flooding and to determine to what extent businesses were
affected by these stressors, along with any resulting impact on health.
Additionally the research aimed to establish the likelihood of
businesses being re-exposed to the secondary stressors through
assessing awareness of flood risk, implementation of property
protection measures and level of community resilience. Design/methodology/approach: The chosen research method
involved the distribution of a questionnaire survey to businesses
affected by either single or repeated flood events. The questionnaire
included the Impact of Event Scale (a 15-item self-report measure
which assesses subjective distress caused by traumatic events). Findings: 55 completed questionnaires were returned by flood
impacted businesses. 89% of the businesses had sustained internal
flooding, while 11% had experienced external flooding. The results
established that the key secondary stressors experienced by
businesses, in order of priority, were: flood damage, fear of
reoccurring flooding, prevention of access to the premise/closure,
loss of income, repair works, length of closure and insurance issues.
There was a lack of preparedness for potential future floods and
consequent vulnerability to the emergence of secondary stressors
among flood affected businesses, as flood resistance or flood
resilience measures had only been implemented by 11% and 13%
respectively. In relation to the psychological repercussions, the
Impact of Event scores suggested that potential prevalence of posttraumatic
stress disorder (PTSD) was noted among 8 out of 55
respondents (l5%). Originality/value: The results improve understanding of the
enduring repercussions of flood events on businesses, indicating that
not only residents may be susceptible to the detrimental health
impacts of flood events and single flood events may be just as likely
as reoccurring flooding to contribute to ongoing stress. Lack of
financial resources is a possible explanation for the lack of
implementation of property protection measures among businesses,
despite 49% experiencing flooding on multiple occasions. Therefore
it is recommended that policymakers should consider potential
sources of financial support or grants towards flood defences for
flood impacted businesses. Any form of assistance should be made
available to businesses at the earliest opportunity as there was no
significant association between the time of the last flood event and
the likelihood of experiencing PTSD symptoms.
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: In this paper, an approach for the liver tumor detection
in computed tomography (CT) images is represented. The detection
process is based on classifying the features of target liver cell to
either tumor or non-tumor. Fractional differential (FD) is applied for
enhancement of Liver CT images, with the aim of enhancing texture
and edge features. Later on, a fusion method is applied to merge
between the various enhanced images and produce a variety of
feature improvement, which will increase the accuracy of
classification. Each image is divided into NxN non-overlapping
blocks, to extract the desired features. Support vector machines
(SVM) classifier is trained later on a supplied dataset different from
the tested one. Finally, the block cells are identified whether they are
classified as tumor or not. Our approach is validated on a group of
patients’ CT liver tumor datasets. The experiment results
demonstrated the efficiency of detection in the proposed technique.
Abstract: This work aims to investigate the structure–property
relationship in ternary nanocomposites consisting of polypropylene
as the matrix, polyamide 66 as the minor phase and treated nanoclay
DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems
with polypropylene grafted maleic anhydride PP-g-MAH as a
compatibilizer were prepared via melt compounding and
characterized in terms of nanoclay content. Morphological structure
was investigated by scanning electron microscopy. The rheological
behavior of the nanocomposites was determined by various methods,
viz melt flow index (MFI) and parallel plate rheological
measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous
morphology supporting the compatibility improvement between PP,
PA66, and nanoclay. SEM results revealed the formation of
nanocomposites as the nanoclay was intercalated and exfoliated. In
the ternary nanocomposites, the rheological behavior showed that, the
complex viscosity is increased with increasing the nanoclay. The results showed that the use of nanoclay affects the variations
of storage modulus (G′), loss modulus (G″) and the melt elasticity.
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: The objective of this study was to examine the
relationship between transformational leadership and innovative work
behavior and to evaluate the mediating role of leader-member
exchange relationships (LMX) on the assumed relationship. This
study has focused on the suggestion that LMX might emerge through
transformational leadership behaviors and thus could mediate the
relationship between transformational leadership and innovative
behavior. A cross-sectional survey research has been conducted on
the relationship these leadership approaches and their impact on
organizational HRM-outcomes have been conducted on two
organizations operating in the technical sector in Istanbul-Turkey.
The results of the research have supported the hypotheses.
Transformational leadership was positively related to the innovative
behaviors and LMX emerged to mediate that relationship.
Abstract: Computer education is referred to as the knowledge
and ability to use computers and related technology efficiently, with a
range of skills covering levels from basic use to advance. Computer
continues to make an ever-increasing impact on all aspect of human
endeavours such as education. With numerous benefits of computer
education, what are the insights of students on computer education?
This study investigated the perception of senior secondary school
students on computer education in Federal Capital Territory (FCT),
Abuja, Nigeria. A sample of 7500 senior secondary schools students
was involved in the study, one hundred (100) private and fifty (50)
public schools within FCT. They were selected by using simple
random sampling technique. A questionnaire [PSSSCEQ] was
developed and validated through expert judgement and reliability coefficient
of 0.84 was obtained. It was used to gather relevant data on
computer education. Findings confirmed that the students in the FCT
had positive perception on computer education. Some factors were
identified that affect students’ perception on computer education. The
null hypotheses were tested using t-test and ANOVA statistical
analyses at 0.05 level of significance. Based on these findings, some
recommendations were made which include competent teachers
should be employed into all secondary schools. This will help
students to acquire relevant knowledge in computer education,
technological supports should be provided to all secondary schools;
this will help the users (students) to solve specific problems in
computer education and financial supports should be provided to
procure computer facilities that will enhance the teaching and the
learning of computer education.
Abstract: Context-aware technologies provide system
applications with the awareness of environmental conditions,
customer behaviours, object movements, etc. Further, with such
capability system applications can be smart to intelligently adapt their
responses to the changing conditions. In regard to business
operations, this promises businesses that their business processes can
run more intelligently, adaptively and flexibly, and thereby either
improve customer experience, enhance reliability of service delivery,
or lower operational cost, to make the business more competitive and
sustainable. Aiming at realising such context-aware business process
management, this paper firstly explores its potential benefit, and then
identifies some gaps between the current business process
management support and the expected. In addition, some preliminary
solutions are also discussed in regard to context definition, rule-based
process execution, run-time process evolution, etc. A framework is
also presented to give a conceptual architecture of context-aware
business process management system to guide system
implementation.
Abstract: This study evaluated to facilitate separation of ABS
plastics from other waste plastics by froth flotation after surface
hydrophilization of ABS with heat treatment. The mild heat treatment
at 100oC for 60s could selectively increase the hydrophilicity of the
ABS plastics surface (i.e., ABS contact angle decreased from 79o to
65.8o) among other plastics mixture. The SEM and XPS results of
plastic samples sufficiently supported the increase in hydrophilic
functional groups and decrease contact angle on ABS surface, after
heat treatment. As a result of the froth flotation (at mixing speed 150
rpm and airflow rate 0.3 L/min) after heat treatment, about 85% of
ABS was selectively separated from other heavy plastics with 100%
of purity. The effect of optimum treatment condition and detailed
mechanism onto separation efficiency in the froth floatation was also
investigated. This research is successful in giving a simple, effective,
and inexpensive method for ABS separation from waste plastics.
Abstract: Recently, Job Recommender Systems have gained
much attention in industries since they solve the problem of
information overload on the recruiting website. Therefore, we
proposed Extended Personalized Job System that has the capability of
providing the appropriate jobs for job seeker and recommending
some suitable information for them using Data Mining Techniques
and Dynamic User Profile. On the other hands, company can also
interact to the system for publishing and updating job information.
This system have emerged and supported various platforms such as
web application and android mobile application. In this paper, User
profiles, Implicit User Action, User Feedback, and Clustering
Techniques in WEKA libraries were applied and implemented. In
additions, open source tools like Yii Web Application Framework,
Bootstrap Front End Framework and Android Mobile Technology
were also applied.
Abstract: This paper presents the development of a mobile
application for students at the Faculty of Information Technology,
Rangsit University (RSU), Thailand. RSU upgrades an enrollment
process by improving its information systems. Students can
download the RSU APP easily in order to access the RSU substantial
information. The reason of having a mobile application is to help
students to access the system regardless of time and place. The objectives of this paper include: 1. To develop an application
on iOS platform for those students at the Faculty of Information
Technology, Rangsit University, Thailand. 2. To obtain the students’
perception towards the new mobile app. The target group is those
from the freshman year till the senior year of the faculty of
Information Technology, Rangsit University. The new mobile application, called as RSU APP, is developed by
the department of Information Technology, Rangsit University. It
contains useful features and various functionalities particularly on
those that can give support to students. The core contents of the app
consist of RSU’s announcement, calendar, events, activities, and ebook.
The mobile app is developed on the iOS platform. The user
satisfaction is analyzed from the interview data from 81 interviewees
as well as a Google application like a Google form which 122
interviewees are involved. The result shows that users are satisfied
with the application as they score it the most satisfaction level at 4.67
SD 0.52. The score for the question if users can learn and use the
application quickly is high which is 4.82 SD 0.71. On the other hand,
the lowest satisfaction rating is in the app’s form, apps lists, with the
satisfaction level as 4.01 SD 0.45.
Abstract: Geopolymer composites reinforced with flax fabrics
and nanoclay are fabricated and studied for physical and mechanical
properties using X-Ray Diffraction (XRD), Fourier Transform
Infrared Spectroscopy (FTIR), and Scanning Electron Microscope
(SEM). Nanoclay platelets at a weight of 1.0%, 2.0%, and 3.0% were
added to geopolymer pastes. Nanoclay at 2.0 wt.% was found to
improve density and decrease porosity while improving flexural
strength and post-peak toughness. A microstructural analysis
indicated that nanoclay behaves as filler and as an activator
supporting geopolymeric reaction while producing a higher content
geopolymer gel improving the microstructure of binders. The process
enhances adhesion between the geopolymer matrix and flax fibres.
Abstract: The aim of this paper is to propose a general
framework for storing, analyzing, and extracting knowledge from
two-dimensional echocardiographic images, color Doppler images,
non-medical images, and general data sets. A number of high
performance data mining algorithms have been used to carry out this
task. Our framework encompasses four layers namely physical
storage, object identification, knowledge discovery, user level.
Techniques such as active contour model to identify the cardiac
chambers, pixel classification to segment the color Doppler echo
image, universal model for image retrieval, Bayesian method for
classification, parallel algorithms for image segmentation, etc., were
employed. Using the feature vector database that have been
efficiently constructed, one can perform various data mining tasks
like clustering, classification, etc. with efficient algorithms along
with image mining given a query image. All these facilities are
included in the framework that is supported by state-of-the-art user
interface (UI). The algorithms were tested with actual patient data
and Coral image database and the results show that their performance
is better than the results reported already.
Abstract: Frozen shrimp industry plays an important role in the
development of production industry of the country. There has been a
continuing development to response the increasing demand; however,
there have been some problems in running the enterprises. The
purposes of this study are to: 1) investigate problems related to basic
factors in operating frozen shrimp industry based on the
entrepreneurs’ points of view. The enterprises involved in this study
were small and medium industry receiving Thai Frozen Foods
Association. 2) Compare the problems of the frozen shrimp industry
according to their sizes of operation in 3 provinces of the central
region Thailand. Population in this study consisted of 148 managers
from 148 frozen shrimp enterprises Thai Frozen Foods Association
which 77 were small size and 71 were medium size. The data were
analyzed to find percentage, arithmetic mean, standard deviation, and
independent sample T-test with the significant hypothesis at .05. The
results revealed that the problems of the frozen shrimp industries of
both size were in high level. The needs for government supporting
were in high level. The comparison of the problems and the basic
factors between the small and medium size enterprises showed no
statistically significant level. The problems that they mentioned
included raw materials, labors, production, marketing, and the need
for academic supporting from the government sector.