Abstract: Brick is one of the most common masonry units used as building material. Due to the demand, different types of waste have been investigated to be incorporated into the bricks. Many types of sludge have been incorporated in fired clay brick for example marble sludge, stone sludge, water sludge, sewage sludge, and ceramic sludge. The utilization of these waste materials in fired clay bricks usually has positive effects on the properties such as lightweight bricks with improved shrinkage, porosity, and strength. This paper reviews on utilization of different types of sludge wastes into fired clay bricks. Previous investigations have demonstrated positive effects on the physical and mechanical properties as well as less impact towards the environment. Thus, the utilizations of sludge waste could produce a good quality of brick and could be one of alternative disposal methods for the sludge wastes.
Abstract: Interactive push VOD system is a new kind of system
that incorporates push technology and interactive technique. It can
push movies to users at high speeds at off-peak hours for optimal
network usage so as to save bandwidth. This paper presents effective
software-based solution for processing mass downstream data at
terminals of interactive push VOD system, where the service can
download movie according to a viewer-s selection. The downstream
data is divided into two catalogs: (1) the carousel data delivered
according to DSM-CC protocol; (2) IP data delivered according to
Euro-DOCSIS protocol. In order to accelerate download speed and
reduce data loss rate at terminals, this software strategy introduces
caching, multi-thread and resuming mechanisms. The experiments
demonstrate advantages of the software-based solution.
Abstract: The possibilities of mobile technology generate new
demands for vocational teacher trainers to transform their approach
to work and to incorporate its usage into their ordinary educational
practice. This paper presents findings of a focus discussion group
(FDG) session on the usage of iPads within a school of vocational
teacher education (SoVTE). It aims to clarify how the teacher
trainers are using iPads and what has changed in their work during
the usage of iPads. The analytical framework bases on content
analysis and expansive learning cycle. It was not only found what
kind of a role iPads played in their daily practices but it brought also
into attention how a cultural change regarding the usage of social
media and mobile technology was desperately needed in the whole
work community. Thus, the FGD was abducted for developing the
knowledge practices of the community of the SoVTE.
Abstract: According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.
Abstract: There are four challenges of sustainable development
and in corporate level sustainability management-s role is to answer
for ecological sustainability challenge, social sustainability challenge,
economic sustainability challenges to environment and social
management and integration challenge of corporate sustainable
challenges by the help of different concepts, methods, instruments,
which are in the toolbox of sustainability management. These
instruments, concepts have different relevance in these challenges,
and according to different literatures environmental management is
outside of social and integration challenge. Main aim of this paper is
to represent the answer for the question that: is it true that social and
integration point of view is outside of the concept environmental
accounting? Using literature review and primer research at the end of
the paper the answer will be confirmed.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: This paper reviews various approaches that have been
used for the modeling and simulation of large-scale engineering
systems and determines their appropriateness in the development of a
RICS modeling and simulation tool. Bond graphs, linear graphs,
block diagrams, differential and difference equations, modeling
languages, cellular automata and agents are reviewed. This tool
should be based on linear graph representation and supports symbolic
programming, functional programming, the development of noncausal
models and the incorporation of decentralized approaches.
Abstract: In this paper we propose a method for vision systems
to consistently represent functional dependencies between different
visual routines along with relational short- and long-term knowledge
about the world. Here the visual routines are bound to visual properties
of objects stored in the memory of the system. Furthermore,
the functional dependencies between the visual routines are seen
as a graph also belonging to the object-s structure. This graph is
parsed in the course of acquiring a visual property of an object to
automatically resolve the dependencies of the bound visual routines.
Using this representation, the system is able to dynamically rearrange
the processing order while keeping its functionality. Additionally, the
system is able to estimate the overall computational costs of a certain
action. We will also show that the system can efficiently use that
structure to incorporate already acquired knowledge and thus reduce
the computational demand.
Abstract: The purpose of this research is to determine the
knowledge and skills possessed by instructional design (ID)
practitioners in Malaysia. As ID is a relatively new field in the
country and there seems to be an absence of any studies on its
community of practice, the main objective of this research is to
discover the tasks and activities performed by ID practitioners in
educational and corporate organizations as suggested by the
International Board of Standards for Training, Performance and
Instruction. This includes finding out the ID models applied in the
course of their work. This research also attempts to identify the
barriers and issues as to why some ID tasks and activities are rarely
or never conducted. The methodology employed in this descriptive
study was a survey questionnaire sent to 30 instructional designers
nationwide. The results showed that majority of the tasks and
activities are carried out frequently enough but omissions do occur
due to reasons such as it being out of job scope, the decision was
already made at a higher level, and the lack of knowledge and skills.
Further investigations of a qualitative manner should be conducted
to achieve a more in-depth understanding of ID practices in
Malaysia
Abstract: This research contribution is drafted to present the
orbit design, orbit propagator and geomagnetic field estimator for the
nanosatellites specifically for the upcoming CUBESAT, ICUBE-1 of
the Institute of Space Technology (IST), Islamabad, Pakistan. The
ICUBE mission is designed for the low earth orbit at the approximate
height of 700KM. The presented research endeavor designs the
Keplarian elements for ICUBE-1 orbit while incorporating the
mission requirements and propagates the orbit using J2 perturbations,
The attitude determination system of the ICUBE-1 consists of
attitude determination sensors like magnetometer and sun sensor. The
Geomagnetic field estimator is developed according to the model of
International Geomagnetic Reference Field (IGRF) for comparing the
magnetic field measurements by the magnetometer for attitude
determination. The output of the propagator namely the Keplarians
position and velocity vectors and the magnetic field vectors are
compared and verified with the same scenario generated in the
Satellite Tool Kit (STK).
Abstract: Segmentation techniques based on Active Contour
Models have been strongly benefited from the use of prior information
during their evolution. Shape prior information is captured from
a training set and is introduced in the optimization procedure to
restrict the evolution into allowable shapes. In this way, the evolution
converges onto regions even with weak boundaries. Although
significant effort has been devoted on different ways of capturing
and analyzing prior information, very little thought has been devoted
on the way of combining image information with prior information.
This paper focuses on a more natural way of incorporating the
prior information in the level set framework. For proof of concept
the method is applied on hippocampus segmentation in T1-MR
images. Hippocampus segmentation is a very challenging task, due
to the multivariate surrounding region and the missing boundary
with the neighboring amygdala, whose intensities are identical. The
proposed method, mimics the human segmentation way and thus
shows enhancements in the segmentation accuracy.
Abstract: In this paper the reference current for Voltage Source
Converter (VSC) of the Shunt Active Power Filter (SAPF) is
generated using Synchronous Reference Frame method,
incorporating the PI controller with anti-windup scheme. The
proposed method improves the harmonic filtering by compensating
the winding up phenomenon caused by the integral term of the PI
controller.
Using Reference Frame Transformation, the current is transformed
from om a - b - c stationery frame to rotating 0 - d - q frame. Using
the PI controller, the current in the 0 - d - q frame is controlled to
get the desired reference signal. A controller with integral action
combined with an actuator that becomes saturated can give some
undesirable effects. If the control error is so large that the integrator
saturates the actuator, the feedback path becomes ineffective because
the actuator will remain saturated even if the process output changes.
The integrator being an unstable system may then integrate to a very
large value, the phenomenon known as integrator windup.
Implementing the integrator anti-windup circuit turns off the
integrator action when the actuator saturates, hence improving the
performance of the SAPF and dynamically compensating harmonics
in the power network. In this paper the system performance is
examined with Shunt Active Power Filter simulation model.
Abstract: In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.
A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.
Abstract: Most routing protocols (DSR, AODV etc.) that have
been designed for wireless adhoc networks incorporate the broadcasting
operation in their route discovery scheme. Probabilistic broadcasting
techniques have been developed to optimize the broadcast operation
which is otherwise very expensive in terms of the redundancy
and the traffic it generates. In this paper we have explored percolation
theory to gain a different perspective on probabilistic broadcasting
schemes which have been actively researched in the recent years.
This theory has helped us estimate the value of broadcast probability
in a wireless adhoc network as a function of the size of the network.
We also show that, operating at those optimal values of broadcast
probability there is at least 25-30% reduction in packet regeneration
during successful broadcasting.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.
Abstract: LDPC codes could be used in magnetic storage devices because of their better decoding performance compared to other error correction codes. However, their hardware implementation results in large and complex decoders. This one of the main obstacles the decoders to be incorporated in magnetic storage devices. We construct small high girth and rate 2 columnweight codes from cage graphs. Though these codes have low performance compared to higher column weight codes, they are easier to implement. The ease of implementation makes them more suitable for applications such as magnetic recording. Cages are the smallest known regular distance graphs, which give us the smallest known column-weight 2 codes given the size, girth and rate of the code.
Abstract: The main objective of this paper is to determine the
isolated effect of silica fume on tensile, compressive and flexure strengths on high strength lightweight concrete. Many experiments
were carried out by replacing cement with different percentages of silica fume at different constant water-binder ratio keeping other mix
design variables constant. The silica fume was replaced by 0%, 5%,
10%, 15%, 20% and 25% for a water-binder ratios ranging from 0.26
to 0.42. For all mixes, split tensile, compressive and flexure strengths
were determined at 28 days. The results showed that the tensile, compressive and flexure strengths increased with silica fume incorporation but the optimum replacement percentage is not
constant because it depends on the water–cementitious material (w/cm) ratio of the mix. Based on the results, a relationship between
split tensile, compressive and flexure strengths of silica fume concrete was developed using statistical methods.
Abstract: A general purpose viscous flow solver Ansys CFX
was used to solve the unsteady three-dimensional (3D) Reynolds
Averaged Navier-Stokes Equation (RANSE) for simulating a 3D
numerical viscous wave tank. A flap-type wave generator was
incorporated in the computational domain to generate the desired
incident waves. Authors have made effort to study the physical
behaviors of Flap type wave maker with governing parameters.
Dependency of the water fill depth, Time period of oscillations and
amplitude of oscillations of flap were studied. Effort has been made
to establish relations between parameters. A validation study was
also carried out against CFD methodology with wave maker theory.
It has been observed that CFD results are in good agreement with
theoretical results. Beaches of different slopes were introduced to
damp the wave, so that it should not cause any reflection from
boundary. As a conclusion this methodology can simulate the
experimental wave-maker for regular wave generation for different
wave length and amplitudes.
Abstract: Designing modern machine tools is a complex task. A
simulation tool to aid the design work, a virtual machine, has
therefore been developed in earlier work. The virtual machine
considers the interaction between the mechanics of the machine
(including structural flexibility) and the control system. This paper
exemplifies the usefulness of the virtual machine as a tool for product
development. An optimisation study is conducted aiming at
improving the existing design of a machine tool regarding weight and
manufacturing accuracy at maintained manufacturing speed. The
problem can be categorised as constrained multidisciplinary multiobjective
multivariable optimisation. Parameters of the control and
geometric quantities of the machine are used as design variables. This
results in a mix of continuous and discrete variables and an
optimisation approach using a genetic algorithm is therefore
deployed. The accuracy objective is evaluated according to
international standards. The complete systems model shows nondeterministic
behaviour. A strategy to handle this based on statistical
analysis is suggested. The weight of the main moving parts is reduced
by more than 30 per cent and the manufacturing accuracy is
improvement by more than 60 per cent compared to the original
design, with no reduction in manufacturing speed. It is also shown
that interaction effects exist between the mechanics and the control,
i.e. this improvement would most likely not been possible with a
conventional sequential design approach within the same time, cost
and general resource frame. This indicates the potential of the virtual
machine concept for contributing to improved efficiency of both
complex products and the development process for such products.
Companies incorporating such advanced simulation tools in their
product development could thus improve its own competitiveness as
well as contribute to improved resource efficiency of society at large.
Abstract: Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.