Abstract: Segmentation of left ventricle (LV) from cardiac
ultrasound images provides a quantitative functional analysis of the
heart to diagnose disease. Active Shape Model (ASM) is widely used
for LV segmentation, but it suffers from the drawback that
initialization of the shape model is not sufficiently close to the target,
especially when dealing with abnormal shapes in disease. In this work,
a two-step framework is improved to achieve a fast and efficient LV
segmentation. First, a robust and efficient detection based on Hough
forest localizes cardiac feature points. Such feature points are used to
predict the initial fitting of the LV shape model. Second, ASM is
applied to further fit the LV shape model to the cardiac ultrasound
image. With the robust initialization, ASM is able to achieve more
accurate segmentation. The performance of the proposed method is
evaluated on a dataset of 810 cardiac ultrasound images that are mostly
abnormal shapes. This proposed method is compared with several
combinations of ASM and existing initialization methods. Our
experiment results demonstrate that accuracy of the proposed method
for feature point detection for initialization was 40% higher than the
existing methods. Moreover, the proposed method significantly
reduces the number of necessary ASM fitting loops and thus speeds up
the whole segmentation process. Therefore, the proposed method is
able to achieve more accurate and efficient segmentation results and is
applicable to unusual shapes of heart with cardiac diseases, such as left
atrial enlargement.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Background modeling and subtraction in video
analysis has been widely used as an effective method for moving
objects detection in many computer vision applications. Recently, a
large number of approaches have been developed to tackle different
types of challenges in this field. However, the dynamic background
and illumination variations are the most frequently occurred problems
in the practical situation. This paper presents a favorable two-layer
model based on codebook algorithm incorporated with local binary
pattern (LBP) texture measure, targeted for handling dynamic
background and illumination variation problems. More specifically,
the first layer is designed by block-based codebook combining with
LBP histogram and mean value of each RGB color channel. Because
of the invariance of the LBP features with respect to monotonic
gray-scale changes, this layer can produce block wise detection results
with considerable tolerance of illumination variations. The pixel-based
codebook is employed to reinforce the precision from the output of the
first layer which is to eliminate false positives further. As a result, the
proposed approach can greatly promote the accuracy under the
circumstances of dynamic background and illumination changes.
Experimental results on several popular background subtraction
datasets demonstrate very competitive performance compared to
previous models.
Abstract: Companies face increasing challenges in research due
to higher costs and risks. The intensifying technology complexity and
interdisciplinarity require unique know-how. Therefore, companies
need to decide whether research shall be conducted internally or
externally with partners. On the other hand, research institutes meet
increasing efforts to achieve good financing and to maintain high
research reputation. Therefore, relevant research topics need to be
identified and specialization of competency is necessary. However,
additional competences for solving interdisciplinary research projects
are also often required. Secured financing can be achieved by
bonding industry partners as well as public fundings. The realization
of faster and better research drives companies and research institutes
to cooperate in organized research networks, which are managed by
an administrative organization. For an effective and efficient
cooperation, necessary processes, roles, tools and a set of rules need
to be determined. Goal of this paper is to show the state-of-art
research and to propose a governance framework for organized
research networks.
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: Green and renewable energy is getting extraordinary
consideration today, because of ecological concerns made by blazing
of fossil powers. Photovoltaic and wind power generation are the
basic decisions for delivering power in this respects. Producing
power by the sun based photovoltaic systems is known to the world,
yet control makers may get confounded to pick between on-grid and
off-grid systems. In this exploration work, an endeavor is made to
compare the off-grid (stand-alone) and on-grid (grid-connected)
frameworks. The work presents relative examination, between two
distinctive PV frameworks situated at V.V.P. Engineering College,
Rajkot. The first framework is 100 kW remain solitary and the
second is 60 kW network joined. The real-time parameters compared
are; output voltage, load current, power in-flow, power output,
performance ratio, yield factor, and capacity factor. The voltage
changes and the power variances in both frameworks are given
exceptional consideration and the examination is made between the
two frameworks to judge the focal points and confinements of both
the frameworks.
Abstract: In this work, a framework to model the Supply Chain
(SC) Collaborative Planning (CP) process is proposed. The main
contributions of this framework concern 1) the presentation of the
decision view, the most important one due to the characteristics of the
process, jointly within the physical, organisation and information
views, and 2) the simultaneous consideration of the spatial and
temporal integration among the different supply chain decision
centres. This framework provides the basis for a realistic and
integrated perspective of the supply chain collaborative planning
process and also the analytical modeling of each of its decisional
activities.
Abstract: The research investigates the causes of unemployment
in Namibia, Nigeria and South Africa and the role of Capital
Accumulation in reducing the unemployment profile of these
economies as proposed by the post-Keynesian economics. This is
conducted through extensive review of literature on the NAIRU
models and focused on the post-Keynesian view of unemployment
within the NAIRU framework. The NAIRU (non-accelerating
inflation rate of unemployment) model has become a dominant
framework used in macroeconomic analysis of unemployment. The
study views the post-Keynesian economics arguments that capital
accumulation is a major determinant of unemployment.
Unemployment remains the fundamental socio-economic challenge
facing African economies. It has been a burden to citizens of those
economies. Namibia, Nigeria, and South Africa are great African
nations battling with high unemployment rates. The high
unemployment rate in the country led the citizens to chase away
foreigners in the country claiming that they have taken away their
jobs. The study proposes there is a strong relationship between
capital accumulation and unemployment in Namibia, Nigeria, and
South Africa, and capital accumulation is responsible for high
unemployment rates in these countries. For the economies to achieve
steady state level of employment and satisfactory level of economic
growth and development, there is need for capital accumulation to
take place. The countries in the study have been selected after a
critical research and investigations. They are selected based on the
following criteria; African economies with high unemployment rates
above 15% and have about 40% of their workforce unemployed. This
level of unemployment is the critical level of unemployment in
Africa as expressed by International Labour Organization (ILO). And
finally, the African countries experience a slow growth in their Gross
fixed capital formation. Adequate statistical measures have been
employed using a time-series analysis in the study and the results
revealed that capital accumulation is the main driver of
unemployment performance in the chosen African countries. An
increase in the accumulation of capital causes unemployment to
reduce significantly. The results of the research work will be useful
and relevant to federal governments and ministries, departments and
agencies (MDAs) of Namibia, Nigeria and South Africa to resolve
the issue of high and persistent unemployment rates in their
economies which are great burden that slows growth and
development of developing economies. Also, the result can be useful
to World Bank, African Development Bank and International Labour
Organization (ILO) in their further research and studies on how to
tackle unemployment in developing and emerging economies.
Abstract: The question of legal liability over injury arising out
of the import and the introduction of GM food emerges as a crucial
issue confronting to promote GM food and its derivatives. There is a
greater possibility of commercialized GM food from the exporting
country to enter importing country where status of approval shall not
be same. This necessitates the importance of fixing a liability
mechanism to discuss the damage, if any, occurs at the level of
transboundary movement or at the market. There was a widespread consensus to develop the Cartagena
Protocol on Biosafety and to give for a dedicated regime on liability
and redress in the form of Nagoya Kuala Lumpur Supplementary
Protocol on the Liability and Redress (‘N-KL Protocol’) at the
international context. The national legal frameworks based on this
protocol are not adequately established in the prevailing food
legislations of the developing countries. The developing economy
like India is willing to import GM food and its derivatives after the
successful commercialization of Bt Cotton in 2002. As a party to the
N-KL Protocol, it is indispensable for India to formulate a legal
framework and to discuss safety, liability, and regulatory issues
surrounding GM foods in conformity to the provisions of the
Protocol. The liability mechanism is also important in the case where
the risk assessment and risk management is still in implementing
stage. Moreover, the country is facing GM infiltration issues with its
neighbors Bangladesh. As a precautionary approach, there is a need
to formulate rules and procedure of legal liability to discuss any kind
of damage occurs at transboundary trade. In this context, the
proposed work will attempt to analyze the liability regime in the
existing Food Safety and Standards Act, 2006 from the applicability
and domestic compliance and to suggest legal and policy options for
regulatory authorities.
Abstract: A myriad of environmental issues face the Nigerian
industrial region, resulting from; oil and gas production, mining,
manufacturing and domestic wastes. Amidst these, much effort has
been directed by stakeholders in the Nigerian oil producing regions,
because of the impacts of the region on the wider Nigerian economy.
Although collaborative environmental management has been noted as
an effective approach in managing environmental issues, little
attention has been given to the roles and practices of stakeholders in
effecting a collaborative environmental management framework for
the Nigerian oil-producing region. This paper produces a framework
to expand and deepen knowledge relating to stakeholders aspects of
collaborative roles in managing environmental issues in the Nigeria
oil-producing region. The knowledge is derived from analysis of
stakeholders’ practices – studied through multiple case studies using
document analysis. Selected documents of key stakeholders –
Nigerian government agencies, multi-national oil companies and host
communities, were analyzed. Open and selective coding was
employed manually during document analysis of data collected from
the offices and websites of the stakeholders. The findings showed
that the stakeholders have a range of roles, practices, interests, drivers
and barriers regarding their collaborative roles in managing
environmental issues. While they have interests for efficient resource
use, compliance to standards, sharing of responsibilities, generating
of new solutions, and shared objectives; there is evidence of major
barriers and these include resource allocation, disjointed policy,
ineffective monitoring, diverse socio- economic interests, lack of
stakeholders’ commitment and limited knowledge sharing. However,
host communities hold deep concerns over the collaborative roles of
stakeholders for economic interests, particularly, where government
agencies and multi-national oil companies are involved. With these
barriers and concerns, a genuine stakeholders’ collaboration is found
to be limited, and as a result, optimal environmental management
practices and policies have not been successfully implemented in the
Nigeria oil-producing region. A framework is produced that describes
practices that characterize collaborative environmental management
might be employed to satisfy the stakeholders’ interests. The
framework recommends critical factors, based on the findings, which
may guide a collaborative environmental management in the oil
producing regions. The recommendations are designed to re-define
the practices of stakeholders in managing environmental issues in the
oil producing regions, not as something wholly new, but as an
approach essential for implementing a sustainable environmental
policy. This research outcome may clarify areas for future research as
well as to contribute to industry guidance in the area of collaborative
environmental management.
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: When evaluating the capacity of a generation park to
cover the load in transmission systems, traditional Loss of Load
Expectation (LOLE) and Expected Energy not Served (EENS)
indices can be used. If those indices allow computing the annual
duration and severity of load non covering situations, they do not take
into account the fact that the load excess is generally shifted from one
penury state (hour or quarter of an hour) to the following one. In this
paper, a sequential Monte Carlo framework is introduced in order to
compute adjusted LOLE and EENS indices. Practically, those
adapted indices permit to consider the effect of load excess transfer
on the global adequacy of a generation park, providing thus a more
accurate evaluation of this quantity.
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: Software quality issues require special attention
especially in view of the demands of quality software product to meet
customer satisfaction. Software development projects in most
organisations need proper defect management process in order to
produce high quality software product and reduce the number of
defects. The research question of this study is how to produce high
quality software and reducing the number of defects. Therefore, the
objective of this paper is to provide a framework for managing
software defects by following defined life cycle processes. The
methodology starts by reviewing defects, defect models, best
practices, and standards. A framework for defect management life
cycle is proposed. The major contribution of this study is to define a
defect management roadmap in software development. The adoption
of an effective defect management process helps to achieve the
ultimate goal of producing high quality software products and
contributes towards continuous software process improvement.
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: The ASEAN Economic Community (AEC) is the goal
of regional economic integration by 2015. In the region, tourism is an
activity that is important, especially as a source of foreign currency, a
source of employment creation and a source of income bringing to the
region. Given the complexity of the issues entailing the concept of
sustainable tourism, this paper tries to assess tourism sustainability
with the ASEAN, based on a number of quantitative indicators for all
the ten economies, Thailand, Myanmar, Laos, Vietnam, Malaysia,
Singapore, Indonesia, Philippines, Cambodia, and Brunei. The
methodological framework will provide a number of benchmarks of
tourism activities in these countries. They include identification of the
dimensions; for example, economic, socio-ecologic, infrastructure
and indicators, method of scaling, chart representation and evaluation
on Asian countries. This specification shows that a similar level of
tourism activity might introduce different implementation in the
tourism activity and might have different consequences for the socioecological
environment and sustainability. The heterogeneity of
developing countries exposed briefly here would be useful to detect
and prepare for coping with the main problems of each country in
their tourism activities, as well as competitiveness and value creation
of tourism for ASEAN economic community, and will compare with
other parts of the world.
Abstract: Wind energy is rapidly emerging as the primary
source of electricity in the Philippines, although developing an
accurate wind resource model is difficult. In this study, Weather
Research and Forecasting (WRF) Model, an open source mesoscale
Numerical Weather Prediction (NWP) model, was used to produce a
1-year atmospheric simulation with 4 km resolution on the Ilocos
Region of the Philippines. The WRF output (netCDF) extracts the
annual mean wind speed data using a Python-based Graphical User
Interface. Lastly, wind resource assessment was produced using a
GIS software. Results of the study showed that it is more flexible to
use Python scripts than using other post-processing tools in dealing
with netCDF files. Using WRF Model, Python, and Geographic
Information Systems, a reliable wind resource map is produced.
Abstract: Geological and tectonic framework indicates that
Bangladesh is one of the most seismically active regions in the world.
The Bengal Basin is at the junction of three major interacting plates:
the Indian, Eurasian, and Burma Plates. Besides there are many
active faults within the region, e.g. the large Dauki fault in the north.
The country has experienced a number of destructive earthquakes due
to the movement of these active faults. Current seismic provisions of
Bangladesh are mostly based on earthquake data prior to the 1990.
Given the record of earthquakes post 1990, there is a need to revisit
the design provisions of the code. This paper compares the base shear
demand of three major cities in Bangladesh: Dhaka (the capital city),
Sylhet, and Chittagong for earthquake scenarios of magnitudes
7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In
particular, the stochastic model allows the flexibility to input region
specific parameters such as shear wave velocity profile (that were
developed from Global Crustal Model CRUST2.0) and include the
effects of attenuation as individual components. Effects of soil
amplification were analysed using the Extended Component
Attenuation Model (ECAM). Results show that the estimated base
shear demand is higher in comparison with code provisions leading to
the suggestion of additional seismic design consideration in the study
regions.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: To maintain a healthy balanced loyalty, whether to art
or society, posits a debatable issue. The artist is always on the look
out for the potential tension between those two realms. Therefore,
one of the most painful dilemmas the artist finds is how to function in
a society without sacrificing the aesthetic values of his/her work. In
other words, the life-long awareness of failure which derives from the
concept of the artist as caught between unflattering social realities
and the need to invent genuine art forms becomes a fertilizing soil for
the artists to be tackled. Thus, within the framework of this dilemma,
the question of the responsibility of the artist and the relationship of
the art to politics will be illuminating. To a larger extent, however, in
drama, this dilemma is represented by the fictional characters of the
play. The present paper tackles the idea of the amorality of the artist in
selected plays by Tom Stoppard. However, Stoppard’s awareness of
his situation as a refugee has led him to keep at a distance from
politics. He tried hard to avoid any intervention into the realms of
political debate, especially in his earliest work. On the one hand, it is
not meant that he did not interest in politics as such, but rather he
preferred to question it than to create a fixed ideological position. On
the other hand, Stoppard’s refusal to intervene in politics is ascribed
to his feeling of gratitude to Britain where he settled. As a result,
Stoppard has frequently been criticized for a lack of political
engagement and also for not leaning too much for the left when he
does engage. His reaction to these public criticisms finds expression
in his self-conscious statements which defensively stressed the
artifice of his work. He, like Oscar Wilde thinks that the
responsibility of the artist is devoted to the realm of his/her art.
Consequently, his consciousness for the role of the artist is truly
reflected in his two plays, Artist Descending a Staircase (1972) and
Travesties (1974).