Abstract: Maintenance is one of the most important activities in
the shipyard industry. However, sometimes it is not supported by
adequate services from the shipyard, where inaccuracy in estimating
the duration of the ship maintenance is still common. This makes
estimation of ship maintenance duration is crucial. This study uses
Data Mining approach, i.e., CART (Classification and Regression
Tree) to estimate the duration of ship maintenance that is limited to
dock works or which is known as dry docking. By using the volume
of dock works as an input to estimate the maintenance duration, 4
classes of dry docking duration were obtained with different linear
model and job criteria for each class. These linear models can then be
used to estimate the duration of dry docking based on job criteria.
Abstract: The school / university orientation interests a broad and
often badly informed public. Technically, it is an important
multicriterion decision problem, which supposes the combination of
much academic professional and/or lawful knowledge, which in turn
justifies software resorting to the techniques of Artificial Intelligence.
CORUS is an expert system of the "Conseil et ORientation
Universitaire et Scolaire", based on a knowledge representation
language (KRL) with rules and objects, called/ known as Ibn Rochd.
CORUS was developed thanks to DéGSE, a workshop of cognitive
engineering which supports this LRC. CORUS works out many
acceptable solutions for the case considered, and retains the most
satisfactory among them. Several versions of CORUS have extended
its services gradually.
Abstract: The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.
Abstract: This article illustrates a model selection management approach for virtual prototypes in interactive simulations. In those numerical simulations, the virtual prototype and its environment are modelled as a multiagent system, where every entity (prototype,human, etc.) is modelled as an agent. In particular, virtual prototyp ingagents that provide mathematical models of mechanical behaviour inform of computational methods are considered. This work argues that selection of an appropriate model in a changing environment,supported by models? characteristics, can be managed by the deter-mination a priori of specific exploitation and performance measures of virtual prototype models. As different models exist to represent a single phenomenon, it is not always possible to select the best one under all possible circumstances of the environment. Instead the most appropriate shall be selecting according to the use case. The proposed approach consists in identifying relevant metrics or indicators for each group of models (e.g. entity models, global model), formulate their qualification, analyse the performance, and apply the qualification criteria. Then, a model can be selected based on the performance prediction obtained from its qualification. The authors hope that this approach will not only help to inform engineers and researchers about another approach for selecting virtual prototype models, but also assist virtual prototype engineers in the systematic or automatic model selection.
Abstract: The study investigated the 2011 TPGA Ever Rich
Championship – North Bay Open spectators- on-the-site spectating
motivations, experiences, and satisfactions. The research was
conducted on a convenience sample of the on-the-spot spectators at the
North Bay Golf and Country Club. A total of 200 questionnaires were
distributed, of which 185 valid questionnaires were collected,
approaching a 92.5% response rate. The data obtained was analyzed
with statistical techniques. First, the data showed significant
differences in motivations, experiences, and satisfactions relative to
demographic variables among the on-the-spot spectators. Second,
spectating motivation, experience, and satisfaction were significantly
related to one another.
Abstract: We report on the development of a model to
understand why the range of experience with respect to HIV
infection is so diverse, especially with respect to the latency period.
To investigate this, an agent-based approach is used to extract highlevel
behaviour which cannot be described analytically from the set
of interaction rules at the cellular level. A network of independent
matrices mimics the chain of lymph nodes. Dealing with massively
multi-agent systems requires major computational effort. However,
parallelisation methods are a natural consequence and advantage of
the multi-agent approach and, using the MPI library, are here
implemented, tested and optimized. Our current focus is on the
various implementations of the data transfer across the network.
Three communications strategies are proposed and tested, showing
that the most efficient approach is communication based on the
natural lymph-network connectivity.
Abstract: New exact three-wave solutions including periodic two-solitary solutions and doubly periodic solitary solutions for the (2+1)-dimensional asymmetric Nizhnik-Novikov- Veselov (ANNV) system are obtained using Hirota's bilinear form and generalized three-wave type of ansatz approach. It is shown that the generalized three-wave method, with the help of symbolic computation, provides an e¤ective and powerful mathematical tool for solving high dimensional nonlinear evolution equations in mathematical physics.
Abstract: Periodic vortex shedding in pulsating flow inside wavy
channel and the effect it has on heat transfer are studied using the
finite volume method. A sinusoidally-varying component is superimposed
on a uniform flow inside a sinusoidal wavy channel and
the effects on the Nusselt number is analyzed. It was found that a
unique optimum value of the pulsation frequency, represented by the
Strouhal number, exists for Reynolds numbers ranging from 125 to
1000. Results suggest that the gain in heat transfer is related to the
process of vortex formation, movement about the troughs of the wavy
channel, and subsequent ejection/destruction through the converging
section. Heat transfer is the highest when the frequencies of the
pulsation and vortex formation approach being in-phase. Analysis of
Strouhal number effect on Nu over a period of pulsation substantiates
the proposed physical mechanism for enhancement. The effect of
changing the amplitude of pulsation is also presented over a period
of pulsation, showing a monotonic increase in heat transfer with
increasing amplitude. The 60% increase in Nusselt number suggests
that sinusoidal fluid pulsation can an effective method for enhancing
heat transfer in laminar, wavy-channel flows.
Abstract: Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.
Abstract: Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
Abstract: In this paper, an efficient structural approach for
recognizing on-line handwritten digits is proposed. After reading
the digit from the user, the slope is estimated and normalized for
adjacent nodes. Based on the changing of signs of the slope values,
the primitives are identified and extracted. The names of these
primitives are represented by strings, and then a finite state
machine, which contains the grammars of the digits, is traced to
identify the digit. Finally, if there is any ambiguity, it will be
resolved. Experiments showed that this technique is flexible and
can achieve high recognition accuracy for the shapes of the digits
represented in this work.
Abstract: Vehicle detection is the critical step for highway monitoring. In this paper we propose background subtraction and edge detection technique for vehicle detection. This technique uses the advantages of both approaches. The practical applications approved the effectiveness of this method. This method consists of two procedures: First, automatic background extraction procedure, in which the background is extracted automatically from the successive frames; Second vehicles detection procedure, which depend on edge detection and background subtraction. Experimental results show the effective application of this algorithm. Vehicles detection rate was higher than 91%.
Abstract: In this article, the phenomenon of nonlinear
consolidation in saturated and homogeneous clay layer is studied.
Considering time-varied drainage model, the excess pore water
pressure in the layer depth is calculated. The Generalized Differential
Quadrature (GDQ) method is used for the modeling and numerical
analysis. For the purpose of analysis, first the domain of independent
variables (i.e., time and clay layer depth) is discretized by the
Chebyshev-Gauss-Lobatto series and then the nonlinear system of
equations obtained from the GDQ method is solved by means of the
Newton-Raphson approach. The obtained results indicate that the
Generalized Differential Quadrature method, in addition to being
simple to apply, enjoys a very high accuracy in the calculation of
excess pore water pressure.
Abstract: In this paper, we employ the approach of linear
programming to propose a new interactive broadcast method. In our
method, a film S is divided into n equal parts and broadcast via k
channels. The user simultaneously downloads these segments from k
channels into the user-s set-top-box (STB) and plays them in order.
Our method assumes that the initial p segments will not have
fast-forwarding capabilities. Every time the user wants to initiate d
times fast-forwarding, according to our broadcasting strategy, the
necessary segments already saved in the user-s STB or are just
download on time for playing. The proposed broadcasting strategy not
only allows the user to pause and rewind, but also to fast-forward.
Abstract: Rapid Prototyping (RP) is a technology that produces models and prototype parts from 3D CAD model data, CT/MRI scan data, and model data created from 3D object digitizing systems. There are several RP process like Stereolithography (SLA), Solid Ground Curing (SGC), Selective Laser Sintering (SLS), Fused Deposition Modeling (FDM), 3D Printing (3DP) among them SLS and FDM RP processes are used to fabricate pattern of custom cranial implant. RP technology is useful in engineering and biomedical application. This is helpful in engineering for product design, tooling and manufacture etc. RP biomedical applications are design and development of medical devices, instruments, prosthetics and implantation; it is also helpful in planning complex surgical operation. The traditional approach limits the full appreciation of various bony structure movements and therefore the custom implants produced are difficult to measure the anatomy of parts and analyze the changes in facial appearances accurately. Cranioplasty surgery is a surgical correction of a defect in cranial bone by implanting a metal or plastic replacement to restore the missing part. This paper aims to do a comparative study on the dimensional error of CAD and SLS RP Models for reconstruction of cranial defect by comparing the virtual CAD with the physical RP model of a cranial defect.
Abstract: As new challenges emerge in power electrical
workplace safety, it is the responsibility of the systems designer to
seek out new approaches and solutions that address them. Design
decisions made today will impact cost, safety and serviceability of
the installed systems for 40 or 50 years during the useful life for the
owner. Studies have shown that this cost is an order of magnitude of
7 to 10 times the installed cost of the power distribution equipment.
This paper reviews some aspects of earthing system design in power
substation surrounded by residential houses. The electrical potential
rise and split factors are discussed and a few recommendations are
provided to achieve a safety voltage in the area beyond the boundary
of the substation.
Abstract: Software projects are very dynamic and require
recurring adjustments of their project plans. These settings can be
understood as reconfigurations in the schedule, in the resources
allocation and other design elements. Yet, during the planning and
execution of a software project, the integration of specific activities
in the projects with the activities that take part in the organization-s
common activity flow should be considered. This article presents the
results from a systematic review of aspects related to software
projects- dynamic reconfiguration emphasizing the integration of
project management with the organizational flows. A series of studies
was analyzed from the year 2000 to the present. The results of this
work show that there is a diversity of techniques and strategies for
dynamic reconfiguration of software projects-. However, few
approaches consider the integration of software project activities with
the activities that take part in the organization-s common workflow.
Abstract: Knowledge Discovery in Databases (KDD) has
evolved into an important and active area of research because of
theoretical challenges and practical applications associated with the
problem of discovering (or extracting) interesting and previously
unknown knowledge from very large real-world databases. Rough
Set Theory (RST) is a mathematical formalism for representing
uncertainty that can be considered an extension of the classical set
theory. It has been used in many different research areas, including
those related to inductive machine learning and reduction of
knowledge in knowledge-based systems. One important concept
related to RST is that of a rough relation. In this paper we presented
the current status of research on applying rough set theory to KDD,
which will be helpful for handle the characteristics of real-world
databases. The main aim is to show how rough set and rough set
analysis can be effectively used to extract knowledge from large
databases.
Abstract: Continuation of an active call is one of the most important quality measurements in the cellular systems. Handoff process enables a cellular system to provide such a facility by transferring an active call from one cell to another. Different approaches are proposed and applied in order to achieve better handoff service. The principal parameters used to evaluate handoff techniques are: forced termination probability and call blocking probability. The mechanisms such as guard channels and queuing handoff calls decrease the forced termination probability while increasing the call blocking probability. In this paper we present an overview about the issues related to handoff initiation and decision and discuss about different types of handoff techniques available in the literature.
Abstract: The Integrated Performance Modelling Environment
(IPME) is a powerful simulation engine for task simulation and
performance analysis. However, it has no high level cognition such
as memory and reasoning for complex simulation. This article
introduces a knowledge representation and reasoning scheme that can
accommodate uncertainty in simulations of military personnel with
IPME. This approach demonstrates how advanced reasoning models
that support similarity-based associative process, rule-based abstract
process, multiple reasoning methods and real-time interaction can be
integrated with conventional task network modelling to provide
greater functionality and flexibility when modelling operator
performance.