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: In this paper we address the issue of classifying the fluorescent intensity of a sample in Indirect Immuno-Fluorescence (IIF). Since IIF is a subjective, semi-quantitative test in its very nature, we discuss a strategy to reliably label the image data set by using the diagnoses performed by different physicians. Then, we discuss image pre-processing, feature extraction and selection. Finally, we propose two ANN-based classifiers that can separate intrinsically dubious samples and whose error tolerance can be flexibly set. Measured performance shows error rates less than 1%, which candidates the method to be used in daily medical practice either to perform pre-selection of cases to be examined, or to act as a second reader.
Abstract: The objective of the research was to study of foot
anthropometry of children aged 7-12 years in the South of Thailand Thirty-three dimensions were measured on 305 male and 295 female
subjects with 3 age ranges (7-12 years old). The instrumentation consists of four types of anthropometer, digital vernier caliper, digital
height gauge and measuring tape. The mean values and standard
deviations of average age, height, and weight of the male subjects were 9.52(±1.70) years, 137.80(±11.55) cm, and 37.57(±11.65) kg.
Female average age, height, and weight subjects were 9.53(±1.70) years, 137.88(±11.55) cm, and 34.90(±11.57) kg respectively. The
comparison of the 33 comparison measured anthropometric. Between
male and female subjects were sexual differences in size on women in almost all areas of significance (p
Abstract: This paper presents an efficient emission constrained
economic dispatch algorithm that deals with nonlinear cost function
and constraints. It is then incorporated into the dynamic
programming based hydrothermal coordination program. The
program has been tested on a practical utility system having 32
thermal and 12 hydro generating units. Test results show that a slight
increase in production cost causes a substantial reduction in
emission.
Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: Three dimensional simulations are carried out to estimate the effect of wind direction, wind speed and geometry on the flow and dispersion of vehicular pollutant in a street canyon. The pollutant sources are motor vehicles passing between the two buildings. Suitable emission factors for petrol and diesel vehicles at varying vehicle speed are used for the estimation of the rate of emission from the streets. The dispersion of automobile pollutant released from the street is simulated by introducing vehicular emission source term as a fixed-flux boundary condition at the ground level over the road. The emission source term is suitably calculated by adopting emission factors from literature for varying conditions of street traffic. It is observed that increase in wind angle disturbs the symmetric pattern of pollution distribution along the street length. The concentration increases in the far end of the street as compared to the near end.
Abstract: Product Lead Time (PLT) is the period of time from
receiving a customer's order to delivering the final product. PLT is an
indicator of the manufacturing controllability, efficiency and
performance. Due to the explosion in the rate of technological
innovations and the rapid changes in the nature of manufacturing
processes, manufacturing firms can bring the new products to market
quicker only if they can reduce their PLT and speed up the rate at
which they can design, plan, control, and manufacture. Although
there is a substantial body of research on manufacturing relating to
cost and quality issues, there is no much specific research conducted
in relation to the formulation of PLT, despite its significance and
importance. This paper analyzes and formulates PLT which can be
used as a guideline for achieving the shorter PLT. Further more this
paper identifies the causes of delay and factors that contributes to the
increased product lead-time.
Abstract: In this study, Li4SiO4 powder was successfully
synthesized via sol gel method followed by drying at 150oC. Lithium
oxide, Li2O and silicon oxide, SiO2 were used as the starting
materials with citric acid as the chelating agent. The obtained powder
was then sintered at various temperatures. Crystallographic phase
analysis, morphology and ionic conductivity were investigated
systematically employing X-ray diffraction, Fourier Transform
Infrared, Scanning Electron Microscopy and AC impedance
spectroscopy. XRD result showed the formation of pure monoclinic
Li4SiO4 crystal structure with lattice parameters a = 5.140 Å, b =
6.094 Å, c = 5.293 Å, β = 90o in the sample sintered at 750oC. This
observation was confirmed by FTIR analysis. The bulk conductivity
of this sample at room temperature was 3.35 × 10-6 S cm-1 and the
highest bulk conductivity of 1.16 × 10-4 S cm-1 was obtained at
100°C. The results indicated that, the Li4SiO4 compound has
potential to be used as host for LISICON structured solid electrolyte
for low temperature application.
Abstract: Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Abstract: The main purpose of this research paper was to study
the requirements for human capital development in order to be ready
for ASEAN Community. Thai education institutions are encountering
a challenging course of change to be effective members of ASEAN
Economic Community (AEC) in 2015. It was vital that everyone and
every organization participate in the process of becoming part of the
ASEAN community, a pluralistic society. Thai universities will be
required to partake in the human capital development in a variety of
fields. In order to assist the whole nation to enhance potential
development, there was a need to collaborate with other ASEAN
leading universities to do researches to ameliorate the qualifications
and capabilities of university management, administers, professors,
and staffs.
Abstract: The increasing interest in plant sterol enriched foods
is due to the fact that they reduce blood cholesterol concentrations
without adverse side effects. In this context, enriched foods with
phytosterols may be helpful in protecting population against
atherosclerosis and cardiovascular diseases. The aim of the present
work was to evaluate in a population of Viseu, Portugal, the
consumption habits low-fat, plant sterol-enriched yoghurt. For this
study, 577 inquiries were made and the sample was randomly
selected for people shopping in various supermarkets. The
preliminary results showed that the biggest consumers of these
products were women aged 45 to 65 years old. Most of the people
who claimed to buy these products consumed them once a day. Also,
most of the consumers under antidyslipidemic therapeutics noticed
positive effects on hypercholesterolemia.
Abstract: The possibility of radionuclides-related contamination
of lands at agricultural holdings defines the necessity to apply special
protective measures in plant growing. The aim of researches is to
elucidate the influence of polymers applying on biological migration
of man-made anthropogenic radionuclides 90Sr and 137Cs in the
system water - soil – plant. The tests are being carried out under field
conditions with and without application of polymers in root-inhabited
media in more radioecological tension zone (with the radius of 7 km
from the Armenian Nuclear Power Plant). The polymers on the base
of K+, Caµ, KµCaµ ions were tested. Productivity of pepper
depending on the presence and type of polymer material, content of
artificial radionuclides in waters, soil and plant material has been
determined. The character of different polymers influence on the
artificial radionuclides migration and accumulation in the system
water-soil-plant and accumulation in the plants has been cleared up.
Abstract: Knowledge modelling, a main activity for the development of Knowledge Based Systems, have no set standards and are mostly done in an ad hoc way. There is a lack of support for the transition from abstract level to implementation. In this paper, a methodology for the development of the knowledge model, which is inspired by both Software and Knowledge Engineering, is proposed. Use of UML which is the de-facto standard for modelling in the software engineering arena is explored for knowledge modelling. The methodology proposed, is used to develop a knowledge model of a knowledge based system for recommending suitable hotels for tourists visiting Mauritius.
Abstract: The manufacture of large-scale precision aerospace
components using CNC requires a highly effective maintenance
strategy to ensure that the required accuracy can be achieved over
many hours of production. This paper reviews a strategy for a
maintenance management system based on Failure Mode Avoidance,
which uses advanced techniques and technologies to underpin a
predictive maintenance strategy. It is shown how condition
monitoring (CM) is important to predict potential failures in high
precision machining facilities and achieve intelligent and integrated
maintenance management. There are two distinct ways in which CM
can be applied. One is to monitor key process parameters and
observe trends which may indicate a gradual deterioration of
accuracy in the product. The other is the use of CM techniques to
monitor high status machine parameters enables trends to be
observed which can be corrected before machine failure and
downtime occurs.
It is concluded that the key to developing a flexible and intelligent
maintenance framework in any precision manufacturing operation is
the ability to evaluate reliably and routinely machine tool condition
using condition monitoring techniques within a framework of Failure
Mode Avoidance.
Abstract: The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: Optical 3D measurement of objects is meaningful in
numerous industrial applications. In various cases shape acquisition
of weak textured objects is essential. Examples are repetition parts
made of plastic or ceramic such as housing parts or ceramic bottles as
well as agricultural products like tubers. These parts are often
conveyed in a wobbling way during the automated optical inspection.
Thus, conventional 3D shape acquisition methods like laser scanning
might fail. In this paper, a novel approach for acquiring 3D shape of
weak textured and moving objects is presented. To facilitate such
measurements an active stereo vision system with structured light is
proposed. The system consists of multiple camera pairs and auxiliary
laser pattern generators. It performs the shape acquisition within one
shot and is beneficial for rapid inspection tasks. An experimental
setup including hardware and software has been developed and
implemented.
Abstract: In recent years demolished concrete waste handling and management is the new primary challenging issue faced by the countries all over the world. It is very challenging and hectic problem that has to be tackled in an indigenous manner, it is desirable to completely recycle demolished concrete waste in order to protect natural resources and reduce environmental pollution. In this research paper an experimental study is carried out to investigate the feasibility and recycling of demolished waste concrete for new construction. The present investigation to be focused on recycling demolished waste materials in order to reduce construction cost and resolving housing problems faced by the low income communities of the world. The crushed demolished concrete wastes is segregated by sieving to obtain required sizes of aggregate, several tests were conducted to determine the aggregate properties before recycling it into new concrete. This research shows that the recycled aggregate that are obtained from site make good quality concrete. The compressive strength test results of partial replacement and full recycled aggregate concrete and are found to be higher than the compressive strength of normal concrete with new aggregate.
Abstract: The elimimation of mefenamic acid has been carried
out by photolysis, ozonation, adsorption onto activated carbon (AC)
and combinations of the previous single systems (O3+AC and
O3+UV). The results obtained indicate that mefenamic acid is not
photo-reactive, showing a relatively low quantum yield of the order
of 6 x 10-4 mol Einstein-1. Application of ozone to mefenamic
aqueous solutions instantaneously eliminates the pharmaceutical,
achieving simultaneously a 40% of mineralization. Addition of AC to
the ozonation process does not enhance the process, moreover,
mineralization is completely inhibited if compared to results obtained
by single ozonation. The combination of ozone and UV radiation led
to the best results in terms of mineralization (60% after 120 min).