Abstract: Tanzania secondary schools in rural areas are geographically and socially isolated, hence face a number of problems in getting learning materials resulting in poor performance in National examinations. E-learning as defined to be the use of information and communication technology (ICT) for supporting the educational processes has motivated Tanzania to apply ICT in its education system. There has been effort to improve secondary school education using ICT through several projects. ICT for e-learning to Tanzania rural secondary school is one of the research projects conceived by the University of Dar-es-Salaam through its College of Engineering and Technology. The main objective of the project is to develop a tool to enable ICT support rural secondary school. The project is comprehensive with a number of components, one being development of e-learning management system (e-LMS) for Tanzania secondary schools. This paper presents strategies of developing e-LMS. It shows the importance of integrating action research methodology with the modeling methods as presented by model driven architecture (MDA) and the usefulness of Unified Modeling Language (UML) on the issue of modeling. The benefit of MDA will go along with the development based on software development life cycle (SDLC) process, from analysis and requirement phase through design and implementation stages as employed by object oriented system analysis and design approach. The paper also explains the employment of open source code reuse from open source learning platforms for the context sensitive development of the e-LMS for Tanzania secondary schools.
Abstract: High Strength Concrete (HSC) is defined as concrete
that meets special combination of performance and uniformity
requirements that cannot be achieved routinely using conventional
constituents and normal mixing, placing, and curing procedures. It is
a highly complex material, which makes modeling its behavior a very
difficult task. This paper aimed to show possible applicability of
Neural Networks (NN) to predict the slump in High Strength
Concrete (HSC). Neural Network models is constructed, trained and
tested using the available test data of 349 different concrete mix
designs of High Strength Concrete (HSC) gathered from a particular
Ready Mix Concrete (RMC) batching plant. The most versatile
Neural Network model is selected to predict the slump in concrete.
The data used in the Neural Network models are arranged in a format
of eight input parameters that cover the Cement, Fly Ash, Sand,
Coarse Aggregate (10 mm), Coarse Aggregate (20 mm), Water,
Super-Plasticizer and Water/Binder ratio. Furthermore, to test the
accuracy for predicting slump in concrete, the final selected model is
further used to test the data of 40 different concrete mix designs of
High Strength Concrete (HSC) taken from the other batching plant.
The results are compared on the basis of error function (or
performance function).
Abstract: A model of user behaviour based automated planning
is introduced in this work. The behaviour of users of web interactive
systems can be described in term of a planning domain encapsulating
the timed actions patterns representing the intended user profile. The
user behaviour recognition is then posed as a planning problem
where the goal is to parse a given sequence of user logs of the
observed activities while reaching a final state.
A general technique for transforming a timed finite state automata
description of the behaviour into a numerical parameter planning
model is introduced.
Experimental results show that the performance of a planning
based behaviour model is effective and scalable for real world
applications. A major advantage of the planning based approach is to
represent in a single automated reasoning framework problems of
plan recognitions, plan synthesis and plan optimisation.
Abstract: In this study, numerical simulations on laminar flow in
sinusoidal wavy shaped tubes were conducted for mean Reynolds
number of 250, which is in the range of physiological flow-rate and
investigated flow structures, pressure distribution and particle
trajectories both in steady and periodic inflow conditions. For
extensive comparisons, various wave lengths and amplitudes of sine
function for geometry of tube models were employed. The results
showed that small amplitude secondary curvature has significant
influence on the nature of flow patterns and particle mixing
mechanism. This implies that characterizing accurate geometry is
essential in accurate predicting of in vivo hemodynamics and may
motivate further study on any possibility of reflection of secondary
flow on vascular remodeling and pathophysiology.
Abstract: This paper focuses on the development of bond graph
dynamic model of the mechanical dynamics of an excavating mechanism
previously designed to be used with small tractors, which are
fabricated in the Engineering Workshops of Jomo Kenyatta University
of Agriculture and Technology. To develop a mechanical dynamics
model of the manipulator, forward recursive equations similar to
those applied in iterative Newton-Euler method were used to obtain
kinematic relationships between the time rates of joint variables
and the generalized cartesian velocities for the centroids of the
links. Representing the obtained kinematic relationships in bondgraphic
form, while considering the link weights and momenta as
the elements led to a detailed bond graph model of the manipulator.
The bond graph method was found to reduce significantly the number
of recursive computations performed on a 3 DOF manipulator for a
mechanical dynamic model to result, hence indicating that bond graph
method is more computationally efficient than the Newton-Euler
method in developing dynamic models of 3 DOF planar manipulators.
The model was verified by comparing the joint torque expressions
of a two link planar manipulator to those obtained using Newton-
Euler and Lagrangian methods as analyzed in robotic textbooks. The
expressions were found to agree indicating that the model captures
the aspects of rigid body dynamics of the manipulator. Based on
the model developed, actuator sizing and valve sizing methodologies
were developed and used to obtain the optimal sizes of the pistons
and spool valve ports respectively. It was found that using the pump
with the sized flow rate capacity, the engine of the tractor is able to
power the excavating mechanism in digging a sandy-loom soil.
Abstract: In recent methodological articles related to structural equation modeling (SEM), the question of how to measure endogenous formative variables has been raised as an urgent, unresolved issue. This research presents an empirical application from the CRM system development context to test a recently developed technique, which makes it possible to measure endogenous formative constructs in structural models. PLS path modeling is used to demonstrate the feasibility of measuring antecedent relationships at the formative indicator level, not the formative construct level. Empirical results show that this technique is a promising approach to measure antecedent relationships of formative constructs in SEM.
Abstract: Motion detection is very important in image
processing. One way of detecting motion is using optical flow.
Optical flow cannot be computed locally, since only one independent
measurement is available from the image sequence at a point, while
the flow velocity has two components. A second constraint is needed.
The method used for finding the optical flow in this project is
assuming that the apparent velocity of the brightness pattern varies
smoothly almost everywhere in the image. This technique is later
used in developing software for motion detection which has the
capability to carry out four types of motion detection. The motion
detection software presented in this project also can highlight motion
region, count motion level as well as counting object numbers. Many
objects such as vehicles and human from video streams can be
recognized by applying optical flow technique.
Abstract: This paper presents a hybrid electric scooter model developed and simulated using Matlab/Simulink. This hybrid scooter modeled has a parallel hybrid structure. The main propulsion units consist of a two stroke internal combustion engine and a hub motor attached to the front wheel of the scooter. The methodology used to optimize the energy and fuel consumption of the hybrid electric scooter is the multi-mode approach. Various case studies were presented to check the model and were compared to the literatures. Results shown that the model developed was feasible and valuable.
Abstract: Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.
Abstract: This paper presents modeling and analysis of 12-phase distribution static compensator (DSTATCOM), which is capable of balancing the source currents in spite of unbalanced loading and phase outages. In addition to balance the supply current, the power factor can be set to a desired value. The theory of instantaneous symmetrical components is used to generate the twelve-phase reference currents. These reference currents are then tracked using current controlled voltage source inverter, operated in a hysteresis band control scheme. An ideal compensator in place of physical realization of the compensator is used. The performance of the proposed DTATCOM is validated through MATLAB simulation and detailed simulation results are given.
Abstract: Leptospirosis occurs worldwide (except the
poles of the earth), urban and rural areas, developed and
developing countries, especially in Thailand. It can be
transmitted to the human by rats through direct and indirect
ways. Human can be infected by either touching the infected rats
or contacting with water, soil containing urine from the infected
rats through skin, eyes and nose. The data of the people who
are infected with this disease indicates that most of the
patients are adults. The transmission of this disease is studied
through mathematical model. The population is separated into human
and rat. The human is divided into two classes, namely juvenile
and adult. The model equation is constructed for each class. The
standard dynamical modeling method is then used for
analyzing the behaviours of solutions. In addition, the
conditions of the parameters for the disease free and endemic
states are obtained. Numerical solutions are shown to support the
theoretical predictions. The results of this study guide the way to
decrease the disease outbreak.
Abstract: Perceptions of quality from both designers and users
perspective have now stretched beyond the traditional usability,
incorporating abstract and subjective concepts. This has led to a shift
in human computer interaction research communities- focus; a shift
that focuses on achieving user experience (UX) by not only fulfilling
conventional usability needs but also those that go beyond them. The
term UX, although widely spread and given significant importance,
lacks consensus in its unified definition. In this paper, we survey
various UX definitions and modeling frameworks and examine them
as the foundation for proposing a UX evolution lifecycle framework
for understanding UX in detail. In the proposed framework we identify
the building blocks of UX and discuss how UX evolves in various
phases. The framework can be used as a tool to understand experience
requirements and evaluate them, resulting in better UX design and
hence improved user satisfaction.
Abstract: The control design for unmanned underwater vehicles (UUVs) is challenging due to the uncertainties in the complex dynamic modeling of the vehicle as well as its unstructured operational environment. To cope with these difficulties, a practical robust control is therefore desirable. The paper deals with the application of coefficient diagram method (CDM) for a robust control design of an autonomous underwater vehicle. The CDM is an algebraic approach in which the characteristic polynomial and the controller are synthesized simultaneously. Particularly, a coefficient diagram (comparable to Bode diagram) is used effectively to convey pertinent design information and as a measure of trade-off between stability, response speed and robustness. In the polynomial ring, Kharitonov polynomials are employed to analyze the robustness of the controller due to parametric uncertainties.
Abstract: Systems Analysis and Design is a key subject in
Information Technology courses, but students do not find it easy to
cope with, since it is not “precise" like programming and not exact
like Mathematics. It is a subject working with many concepts,
modeling ideas into visual representations and then translating the
pictures into a real life system. To complicate matters users who are
not necessarily familiar with computers need to give their inputs to
ensure that they get the system the need. Systems Analysis and
Design also covers two fields, namely Analysis, focusing on the
analysis of the existing system and Design, focusing on the design of
the new system. To be able to test the analysis and design of a
system, it is necessary to develop a system or at least a prototype of
the system to test the validity of the analysis and design. The skills
necessary in each aspect differs vastly. Project Management Skills,
Database Knowledge and Object Oriented Principles are all
necessary. In the context of a developing country where students
enter tertiary education underprepared and the digital divide is alive
and well, students need to be motivated to learn the necessary skills,
get an opportunity to test it in a “live" but protected environment –
within the framework of a university. The purpose of this article is to
improve the learning experience in Systems Analysis and Design
through reviewing the underlying teaching principles used, the
teaching tools implemented, the observations made and the
reflections that will influence future developments in Systems
Analysis and Design. Action research principles allows the focus to
be on a few problematic aspects during a particular semester.
Abstract: Sound pathways in the enclosures of small earphones
are very narrow. In such narrow pathways, the speed of sound
propagation and the phase of sound waves change because of the air
viscosity. We have developed a new finite element method that
includes the effects of damping due to air viscosity for modeling the
sound pathway. This method is developed as an extension of the
existing finite element method for porous sound-absorbing materials.
The numerical calculation results using the proposed finite element
method are validated against the existing calculation methods.
Abstract: The scale, complexity and worldwide geographical
spread of the LHC computing and data analysis problems are
unprecedented in scientific research. The complexity of processing
and accessing this data is increased substantially by the size and
global span of the major experiments, combined with the limited
wide area network bandwidth available. We present the latest
generation of the MONARC (MOdels of Networked Analysis at
Regional Centers) simulation framework, as a design and modeling
tool for large scale distributed systems applied to HEP experiments.
We present simulation experiments designed to evaluate the
capabilities of the current real-world distributed infrastructure to
support existing physics analysis processes and the means by which
the experiments bands together to meet the technical challenges
posed by the storage, access and computing requirements of LHC
data analysis within the CMS experiment.
Abstract: This paper focuses on developing an integrated
reliable and sophisticated model for ultra large wind turbines And to
study the performance and analysis of vector control on large wind
turbines. With the advance of power electronics technology, direct
driven multi-pole radial flux PMSG (Permanent Magnet Synchronous
Generator) has proven to be a good choice for wind turbines
manufacturers. To study the wind energy conversion systems, it is
important to develop a wind turbine simulator that is able to produce
realistic and validated conditions that occur in real ultra MW wind
turbines. Three different packages are used to simulate this model,
namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind
simulator developed by National Renewable Energy Laboratory
(NREL). The wind turbine mechanical parts are modeled by FAST
(Fatigue, Aerodynamics, Structures and Turbulence) code which is
also developed by NREL. Simulink is used to model the PMSG, full
scale back to back IGBT converters, and the grid.
Abstract: Innovation is being view from four areas of
innovation, product, service, technology, and marketing. Whereas
customer loyalty is composed of customer expectation, perceived
quality, perceived value, corporate image, customer satisfaction,
customer trust/confidence, customer commitment, customer
complaint, and customer loyalty. This study aimed to investigate the
influence of innovation factors to customer loyalty to GSM in the
telecom companies where use of products and services. Structural
Equation Modeling (SEM) using to analyze innovation factors. It was
found the factor of innovation have significant influence on customer
loyalty.
Abstract: This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.
Abstract: As the majority of faults are found in a few of its
modules so there is a need to investigate the modules that are
affected severely as compared to other modules and proper
maintenance need to be done in time especially for the critical
applications. As, Neural networks, which have been already applied
in software engineering applications to build reliability growth
models predict the gross change or reusability metrics. Neural
networks are non-linear sophisticated modeling techniques that are
able to model complex functions. Neural network techniques are
used when exact nature of input and outputs is not known. A key
feature is that they learn the relationship between input and output
through training. In this present work, various Neural Network Based
techniques are explored and comparative analysis is performed for
the prediction of level of need of maintenance by predicting level
severity of faults present in NASA-s public domain defect dataset.
The comparison of different algorithms is made on the basis of Mean
Absolute Error, Root Mean Square Error and Accuracy Values. It is
concluded that Generalized Regression Networks is the best
algorithm for classification of the software components into different
level of severity of impact of the faults. The algorithm can be used to
develop model that can be used for identifying modules that are
heavily affected by the faults.