Abstract: The characteristic requirement for producing
rectangular shape bottles was a uniform thickness of the plastic bottle
wall. Die shaping was a good technique which controlled the wall
thickness of bottles. An advance technology which was the finite
element method (FEM) for blowing parison to be a rectangular shape
bottle was conducted to reduce waste plastic from a trial and error
method of a die shaping and parison control method. The artificial
intelligent (AI) comprised of artificial neural network and genetic
algorithm was selected to optimize the die gap shape from the FEM
results. The application of AI technique could optimize the suitable
die gap shape for the parison blow molding which did not depend on
the parison control method to produce rectangular bottles with the
uniform wall. Particularly, this application can be used with cheap
blow molding machines without a parison controller therefore it will
reduce cost of production in the bottle blow molding process.
Abstract: Vehicular Adhoc Network (VANET) is a new
technology which aims to ensure intelligent inter-vehicle
communications, seamless internet connectivity leading to improved
road safety, essential alerts, and access to comfort and entertainment.
VANET operations are hindered by mobile node’s (vehicles)
uncertain mobility. Routing algorithms use metrics to evaluate which
path is best for packets to travel. Metrics like path length (hop count),
delay, reliability, bandwidth, and load determine optimal route. The
proposed scheme exploits link quality, traffic density, and
intersections as routing metrics to determine next hop. This study
enhances Geographical Routing Protocol (GRP) using fuzzy
controllers while rules are optimized with Bee Swarm Optimization
(BSO). Simulations results are compared to conventional GRP.
Abstract: In this paper, an analysis of some model order
reduction techniques is presented. A new hybrid algorithm for model
order reduction of linear time invariant systems is compared with the
conventional techniques namely Balanced Truncation, Hankel Norm
reduction and Dominant Pole Algorithm (DPA). The proposed hybrid
algorithm is known as Clustering Dominant Pole Algorithm (CDPA),
is able to compute the full set of dominant poles and its cluster center
efficiently. The dominant poles of a transfer function are specific
eigenvalues of the state space matrix of the corresponding dynamical
system. The effectiveness of this novel technique is shown through
the simulation results.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: In this paper, we propose an intelligent system that is
used for monitoring the health conditions of patients. Monitoring the
health condition of patients is a complex problem that involves
different medical units and requires continuous monitoring especially
in rural areas because of inadequate number of available specialized
physicians. The proposed system will improve patient care and drive
costs down comparing to the existing system in Jordan. The proposed
system will be the start point to faster and improve the
communication between different units in the health system in
Jordan. Connecting patients and their physicians beyond hospital
doors regarding their geographical area is an important issue in
developing the health system in Jordan. The ability of making
medical decisions, the quality of medical is expected to be improved.
Abstract: Generally the natural environment is made up of air,
water and soil. The release of emission of industrial waste into
anyone of the components of the environment causes pollution.
Industrial pollution significantly threatens the inherent right of
people, to the enjoyment of a safe and secure environment. The aim
of this paper is to assess the effect of environmental pollution and
health risks of residents living near Ewekoro cement factory. The
research made use of IKONOS imagery for Geographical
Information System (GIS) to buffer and extract buildings that are less
than 1km to the factory, within 1km to 5km and above 5km to the
factory. Also questionnaire was used to elicit information on the
socio-economic factors, effect of environmental pollution on
residents and measures adopted to control industrial pollution on the
residents. Findings show that most buildings that fall between less
than 1km and 1km to 5km to the factory have high health risk in the
study area. The study recommended total relocation for the residents
of the study area to reduce health risk problems.
Abstract: This paper presents small signal stability study carried
over the 140-Bus, 31-Machine, 5-Area MEPE system and validated
on free and open source software: PSAT. Well-established linearalgebra
analysis, eigenvalue analysis, is employed to determine the
small signal dynamic behavior of test system. The aspects of local
and interarea oscillations which may affect the operation and
behavior of power system are analyzed. Eigenvalue analysis is carried
out to investigate the small signal behavior of test system and the
participation factors have been determined to identify the
participation of the states in the variation of different mode shapes.
Also, the variations in oscillatory modes are presented to observe the
damping performance of the test system.
Abstract: The concentration levels of six heavy metals (Cd, Cr,
Fe, Ni, Pb and Zn) and two mineral elements (Ca and Mg) were
determined in soil samples collected from the vicinity of two auto
mechanic workshops in Sabon-Gari, Kaduna state, Nigeria, using
Atomic Absorption Spectrometry (AAS), in order to compare the
gradation of their concentrations with distance and depth of soil from
the workshop sites. At site 1, concentrations of Lead, Chromium, Iron
and Zinc were generally found to be above the World Health
Organization limits, while those of Nickel and Cadmium fell within
the limits. Iron had the highest concentration with a range of 176.274
ppm to 489.127 ppm at depths of 5 cm to 15 cm and a distance range
of 5 m to 15 m, while the concentration of cadmium was least with a
range of 0.001 ppm to 0.008 ppm at similar depth and distance
ranges. In addition, there was more of calcium (11.521 ppm to
121.709 ppm), in all the samples, than magnesium (11.293 ppm to
21.635 ppm). Similar results were obtained for site II. The
concentrations of all the metals analyzed showed a downward
gradient with increase in depth and distance from both workshop sites
except for iron and zinc at site 2. The immediate and remote
implications of these findings on the biota are discussed.
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
Abstract: In this paper, the effect of grades 32.4 and 42.5
Portland-limestone cements generally used for concrete production in
Nigeria on concrete compressive strength is investigated.
Investigation revealed that the compressive strength of concrete
produced with Portland-limestone cement grade 42.5 is generally
higher than that produced with cement grade 32.5. The percentage
difference between the compressive strengths of the concrete cubes
produced with Portland-limestone cement grades 42.5 and 32.5 is
inversely proportional to the richness of the concrete with the highest
and the least percentage difference associated with the 1:2:4 and
1:1:2 mix ratios respectively. It is recommended that cement grade
42.5 be preferred for construction in Nigeria as this will lead to the
construction of stronger concrete structures, which will reduce the
incidence of failure of building and other concrete structures at no
additional cost since the cost of both cement grades are the same.
Abstract: The well been of human beings on construction site is
very important, many man power had been lost through accidents
which kills or make workers physically unfit to carry out construction
activities, these in turn have multiple effects on the whole economy.
Thus it is necessary to put all safety items and regulations in place
before construction activities can commence. This study was carried
out in Ondo state of Nigeria to known and analyse the state of health
and safety of construction workers in the state. The study was done
using first hand observation method, 50 construction project sites
were visited in 10 major towns of Ondo state, questionnaires were
distributed and the results were analysed. The result show that
construction workers are being exposed to a lot of construction site
hazards due to lack of inadequate safety programmes and nonprovision
of appropriate safety materials for workers on site. From the
data gotten for each site visited and the statistical analysis, it can be
concluded that occurrence of accident on construction sites depends
significantly on the available safety facilities on the sites. The result of
the regression statistics show that the level of significant of the
dependence of occurrence of accident on the availability of safety
items on site is 0.0362 which is less than 0.05 maximum significant
level required. Therefore a vital way of sustaining our building
strategy is by given a detail attention to provision of adequate health
and safety items on construction sites which will reduce the
occurrence of accident, loss of man power and death of skilled
workers among others.
Abstract: The emerging Cognitive Radio is combo of both the
technologies i.e. Radio dynamics and software technology. It involve
wireless system with efficient coding, designing, and making them
artificial intelligent to take the decision according to the surrounding
environment and adopt themselves accordingly, so as to deliver the
best QoS. This is the breakthrough from fixed hardware and fixed
utilization of the spectrum. This software-defined approach of
research is centralized at user-definition and application driven
model, various software method are used for the optimization of the
wireless communication. This paper focused on the Spectrum
allocation technique using genetic algorithm GA to evolve radio,
represented by chromosomes. The chromosomes gene represents the
adjustable parameters in given radio and by using GA, evolving over
the generations, the optimized set of parameters are evolved, as per
the requirement of user and availability of the spectrum, in our
prototype the gene consist of 6 different parameters, and the best set
of parameters are evolved according to the application need and
availability of the spectrum holes and thus maintaining best QoS for
user, simultaneously maintaining licensed user rights. The analyzing
tool Matlab is used for the performance of the prototype.
Abstract: Construction cost estimation is one of the most
important aspects of construction project design. For generations, the
process of cost estimating has been manual, time-consuming and
error-prone. This has partly led to most cost estimates to be unclear
and riddled with inaccuracies that at times lead to over- or underestimation
of construction cost. The development of standard set of
measurement rules that are understandable by all those involved in a
construction project, have not totally solved the challenges. Emerging
Building Information Modelling (BIM) technologies can exploit
standard measurement methods to automate cost estimation process
and improve accuracies. This requires standard measurement
methods to be structured in ontological and machine readable format;
so that BIM software packages can easily read them. Most standard
measurement methods are still text-based in textbooks and require
manual editing into tables or Spreadsheet during cost estimation. The
aim of this study is to explore the development of an ontology based
on New Rules of Measurement (NRM) commonly used in the UK for
cost estimation. The methodology adopted is Methontology, one of
the most widely used ontology engineering methodologies. The
challenges in this exploratory study are also reported and
recommendations for future studies proposed.
Abstract: This paper presents the details of a numerical study of
buckling and post buckling behaviour of laminated carbon fiber
reinforced plastic (CFRP) thin-walled cylindrical shell under axial
compression using asymmetric meshing technique (AMT) by
ABAQUS. AMT is considered to be a new perturbation method to
introduce disturbance without changing geometry, boundary
conditions or loading conditions. Asymmetric meshing affects both
predicted buckling load and buckling mode shapes. Cylindrical shell
having lay-up orientation [0^o/+45^o/-45^o/0^o] with radius to thickness
ratio (R/t) equal to 265 and length to radius ratio (L/R) equal to 1.5 is
analysed numerically. A series of numerical simulations
(experiments) are carried out with symmetric and asymmetric
meshing to study the effect of asymmetric meshing on predicted
buckling behaviour. Asymmetric meshing technique is employed in
both axial direction and circumferential direction separately using
two different methods, first by changing the shell element size and
varying the total number elements, and second by varying the shell
element size and keeping total number of elements constant. The
results of linear analysis (Eigenvalue analysis) and non-linear
analysis (Riks analysis) using symmetric meshing agree well with
analytical results. The results of numerical analysis are presented in
form of non-dimensional load factor, which is the ratio of buckling
load using asymmetric meshing technique to buckling load using
symmetric meshing technique. Using AMT, load factor has about 2%
variation for linear eigenvalue analysis and about 2% variation for
non-linear Riks analysis. The behaviour of load end-shortening curve
for pre-buckling is same for both symmetric and asymmetric meshing
but for asymmetric meshing curve behaviour in post-buckling
becomes extraordinarily complex. The major conclusions are:
different methods of AMT have small influence on predicted
buckling load and significant influence on load displacement curve
behaviour in post buckling; AMT in axial direction and AMT in
circumferential direction have different influence on buckling load
and load displacement curve in post-buckling.
Abstract: This study is used as a definition method to the value
and function in manufacturing sector. In concurrence of discussion
about present condition of modeling method, until now definition of
1D-CAE is ambiguity and not conceptual. Across all the physic fields,
those methods are defined with the formulation of differential
algebraic equation which only applied time derivation and simulation.
At the same time, we propose semi-acausal modeling concept and
differential algebraic equation method as a newly modeling method
which the efficiency has been verified through the comparison of
numerical analysis result between the semi-acausal modeling
calculation and FEM theory calculation.
Abstract: Kazakhstan is currently one of the dynamically
developing states in its region. The stable growth in all sectors of the
economy leads to a corresponding increase in energy consumption.
Thus country consumes significant amount of energy due to the high
level of industrialisation and the presence of energy-intensive
manufacturing such as mining and metallurgy which in turn leads to
low energy efficiency. With allowance for this the Government has
set several priorities to adopt a transition of Republic of Kazakhstan
to a “green economy”. This article provides an overview of
Kazakhstan’s energy efficiency situation in for the period of 1991-
2014. First, the dynamics of production and consumption of
conventional energy resources are given. Second, the potential of
renewable energy sources is summarised followed by the description
of GHG emissions trends in the country. Third, Kazakhstan’ national
initiatives, policies and locally implemented projects in the field of
energy efficiency are described.
Abstract: This paper introduces novel approaches to partitioning
and mapping in terms of model-based embedded multicore system
engineering and further discusses benefits, industrial relevance and
features in common with existing approaches. In order to assess
and evaluate results, both approaches have been applied to a real
industrial application as well as to various prototypical demonstrative
applications, that have been developed and implemented for
different purposes. Evaluations show, that such applications improve
significantly according to performance, energy efficiency, meeting
timing constraints and covering maintaining issues by using
the AMALTHEA platform and the implemented approaches.
Furthermore, the model-based design provides an open, expandable,
platform independent and scalable exchange format between
OEMs, suppliers and developers on different levels. Our proposed
mechanisms provide meaningful multicore system utilization since
load balancing by means of partitioning and mapping is effectively
performed with regard to the modeled systems including hardware,
software, operating system, scheduling, constraints, configuration and
more data.
Abstract: Conventional educational practices, do not offer all
the required skills for teachers to successfully survive in today’s
workplace. Due to poor professional training, a big gap exists across
the curriculum plan and the teacher practices in the classroom. As
such, raising the quality of teaching through ICT-enabled training and
professional development of teachers should be an urgent priority.
‘Mobile Learning’, in that vein, is an increasingly growing field of
educational research and practice across schools and work places. In
this paper, we propose a novel Mobile learning system that allows the
users to learn through an intelligent mobile learning in cooperatively
every-time and every-where. The system will reduce the training cost
and increase consistency, efficiency, and data reliability. To establish
that our system will display neither functional nor performance
failure, the evaluation strategy is based on formal observation of
users interacting with system followed by questionnaires and
structured interviews.
Abstract: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
Abstract: Solenoid operated electromagnetic control valve
(ECV) playing an important role for car’s air conditioning control
system. ECV is used in external variable displacement swash plate
type compressor and controls the entire air conditioning system by
means of a pulse width modulation (PWM) input signal supplying
from an external source (controller). Complete form of ECV contains
number of internal features like valve body, core, valve guide,
plunger, guide pin, plunger spring, bellows etc. While designing the
ECV; dimensions of different internal items must meet the standard
requirements as it is quite challenging. In this research paper,
especially the dimensioning of ECV body and its three pressure ports
through which the air/refrigerant passes are considered. Here internal
leakage test analysis of ECV body is being carried out from its
discharge port (Pd) to crankcase port (Pc) when the guide valve is
placed inside it. The experiments have made both in ordinary and
digital system using different assumptions and thereafter compare the
results.