Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: The quantitative study of cell mechanics is of
paramount interest, since it regulates the behaviour of the living cells
in response to the myriad of extracellular and intracellular
mechanical stimuli. The novel experimental techniques together with
robust computational approaches have given rise to new theories and
models, which describe cell mechanics as combination of
biomechanical and biochemical processes. This review paper
encapsulates the existing continuum-based computational approaches
that have been developed for interpreting the mechanical responses of
living cells under different loading and boundary conditions. The
salient features and drawbacks of each model are discussed from both
structural and biological points of view. This discussion can
contribute to the development of even more precise and realistic
computational models of cell mechanics based on continuum
approaches or on their combination with microstructural approaches,
which in turn may provide a better understanding of
mechanotransduction in living cells.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: Bicycle Level of Service (BLOS) is a measure for
evaluating street conditions for cyclists. Currently, various methods
are proposed for BLOS. These analytical methods however have
some drawbacks: they usually assume cyclists as users that can share
street facilities with motorized vehicles, it is not easy to link them to
design process and they are not easy to follow. In addition, they only
support a narrow range of cycling facilities and may not be applicable
for all situations. Along this, the current paper introduces various
effective design factors for bicycle-friendly streets. This study
considers cyclists as users of streets who have special needs and
facilities. Therefore, the key factors that influence BLOS based on
different cycling facilities that are proposed by developed guidelines
and literature are identified. The combination of these factors
presents a complete set of effective design factors for bicycle-friendly
streets. In addition, the weight of each factor in existing BLOS
models is estimated and these effective factors are ranked based on
these weights. These factors and their weights can be used in further
studies to propose special bicycle-friendly street design model.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: This paper presents a state-of-the-art survey of the
operations research models developed for internal audit planning.
Two alternative approaches have been followed in the literature for
audit planning: (1) identifying the optimal audit frequency; and (2)
determining the optimal audit resource allocation. The first approach
identifies the elapsed time between two successive audits, which can
be presented as the optimal number of audits in a given planning
horizon, or the optimal number of transactions after which an audit
should be performed. It also includes the optimal audit schedule. The
second approach determines the optimal allocation of audit frequency
among all auditable units in the firm. In our review, we discuss both
the deterministic and probabilistic models developed for audit
planning. In addition, game theory models are reviewed to find the
optimal auditing strategy based on the interactions between the
auditors and the clients.
Abstract: Single angle connections, which are bolted to the beam
web and the column flange, are studied to investigate their
moment-rotation behavior. Elastic–perfectly plastic material behavior
is assumed. ABAQUS software is used to analyze the nonlinear
behavior of a single angle connection. The identical geometric and
material conditions with Lipson’s test are used for verifying finite
element models. Since Kishi and Chen’s Power model and Lee and
Moon’s Log model are accurate only for a limited range of mechanism,
simpler and more accurate hyperbolic function models are proposed.
Abstract: This study investigates the effects of the lead angle
and chip thickness variation on surface roughness during the
machining of compacted graphite iron using ceramic cutting tools
under dry cutting conditions. Analytical models were developed for
predicting the surface roughness values of the specimens after the
face milling process. Experimental data was collected and imported
to the artificial neural network model. A multilayer perceptron model
was used with the back propagation algorithm employing the input
parameters of lead angle, cutting speed and feed rate in connection
with chip thickness. Furthermore, analysis of variance was employed
to determine the effects of the cutting parameters on surface
roughness. Artificial neural network and regression analysis were
used to predict surface roughness. The values thus predicted were
compared with the collected experimental data, and the
corresponding percentage error was computed. Analysis results
revealed that the lead angle is the dominant factor affecting surface
roughness. Experimental results indicated an improvement in the
surface roughness value with decreasing lead angle value from 88° to
45°.
Abstract: This paper presents Carrier Sense Multiple Access
(CSMA) communication models based on SoC design methodology.
Such a model can be used to support the modeling of the complex
wireless communication systems. Therefore, the use of such
communication model is an important technique in the construction
of high-performance communication. SystemC has been chosen
because it provides a homogeneous design flow for complex designs
(i.e. SoC and IP-based design). We use a swarm system to validate
CSMA designed model and to show how advantages of incorporating
communication early in the design process. The wireless
communication created through the modeling of CSMA protocol that
can be used to achieve communication between all the agents and to
coordinate access to the shared medium (channel).
Abstract: 3-roller conical bending process is widely used in the
industries for manufacturing of conical sections and shells. It
involves static as well dynamic bending stages. Analytical models for
prediction of bending force during static as well as dynamic bending
stage are available in the literature. In this paper bending forces
required for static bending stage and dynamic bending stages have
been compared using the analytical models. It is concluded that force
required for dynamic bending is very less as compared to the bending
force required during the static bending stage.
Abstract: Rapid Prototyping (RP) technologies enable physical
parts to be produced from various materials without depending on the
conventional tooling. Fused Deposition Modeling (FDM) is one of
the famous RP processes used at present. Tensile strength and
compressive strength resistance will be identified for different sample
structures and different layer orientations of ABS rapid prototype
solid models. The samples will be fabricated by a FDM rapid
prototyping machine in different layer orientations with variations in
internal geometrical structure. The 0° orientation where layers were
deposited along the length of the samples displayed superior strength
and impact resistance over all the other orientations. The anisotropic
properties were probably caused by weak interlayer bonding and
interlayer porosity.
Abstract: This paper presents an application of a “Systematic
Soft Domain Driven Design Framework” as a soft systems approach
to domain-driven design of information systems development. The
framework use SSM as a guiding methodology within which we have
embedded a sequence of design tasks based on the UML leading to
the implementation of a software system using the Naked Objects
framework. This framework have been used in action research
projects that have involved the investigation and modelling of
business processes using object-oriented domain models and the
implementation of software systems based on those domain models.
Within this framework, Soft Systems Methodology (SSM) is used as
a guiding methodology to explore the problem situation and to
develop the domain model using UML for the given business
domain. The framework is proposed and evaluated in our previous
works, and a real case study “Information Retrieval System for
academic research” is used, in this paper, to show further practice and
evaluation of the framework in different business domain. We argue
that there are advantages from combining and using techniques from
different methodologies in this way for business domain modelling.
The framework is overviewed and justified as multimethodology
using Mingers multimethodology ideas.
Abstract: In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.
Abstract: This paper reviews the model-based qualitative and
quantitative Operations Management research in the context of
Construction Supply Chain Management (CSCM). Construction
industry has been traditionally blamed for low productivity, cost and
time overruns, waste, high fragmentation and adversarial
relationships. The construction industry has been slower than other
industries to employ the Supply Chain Management (SCM) concept
and develop models that support the decision-making and planning.
However the last decade there is a distinct shift from a project-based
to a supply-based approach of construction management. CSCM
comes up as a new promising management tool of construction
operations and improves the performance of construction projects in
terms of cost, time and quality. Modeling the Construction Supply
Chain (CSC) offers the means to reap the benefits of SCM, make
informed decisions and gain competitive advantage. Different
modeling approaches and methodologies have been applied in the
multi-disciplinary and heterogeneous research field of CSCM. The
literature review reveals that a considerable percentage of the CSC
modeling research accommodates conceptual or process models
which present general management frameworks and do not relate to
acknowledged soft Operations Research methods. We particularly
focus on the model-based quantitative research and categorize the
CSCM models depending on their scope, objectives, modeling
approach, solution methods and software used. Although over the last
few years there has been clearly an increase of research papers on
quantitative CSC models, we identify that the relevant literature is
very fragmented with limited applications of simulation,
mathematical programming and simulation-based optimization. Most
applications are project-specific or study only parts of the supply
system. Thus, some complex interdependencies within construction
are neglected and the implementation of the integrated supply chain
management is hindered. We conclude this paper by giving future
research directions and emphasizing the need to develop optimization
models for integrated CSCM. We stress that CSC modeling needs a
multi-dimensional, system-wide and long-term perspective. Finally,
prior applications of SCM to other industries have to be taken into
account in order to model CSCs, but not without translating the
generic concepts to the context of construction industry.
Abstract: Intermittent behavior near the boundary of phase
synchronization in the presence of noise is studied. In certain range of
the coupling parameter and noise intensity the intermittency of eyelet
and ring intermittencies is shown to take place. Main results are
illustrated using the example of two unidirectional coupled Rössler
systems. Similar behavior is shown to take place in two
hydrodynamical models of Pierce diode coupled unidirectional.
Abstract: The flow duration curve (FDC) is an informative
method that represents the flow regime’s properties for a river basin.
Therefore, the FDC is widely used for water resource projects such as
hydropower, water supply, irrigation and water quality management.
The primary purpose of this study is to obtain synthetic daily flow
duration curves for Çoruh Basin, Turkey. For this aim, we firstly
developed univariate auto-regressive moving average (ARMA)
models for daily flows of 9 stations located in Çoruh basin and then
these models were used to generate 100 synthetic flow series each
having same size as historical series. Secondly, flow duration curves
of each synthetic series were drawn and the flow values exceeded 10,
50 and 95% of the time and 95% confidence limit of these flows were
calculated. As a result, flood, mean and low flows potential of Çoruh
basin will comprehensively be represented.
Abstract: To construct the lumped spring-mass model
considering the occupants for the offset frontal crash, the SISAME
software and the NHTSA test data were used. The data on 56 kph 40%
offset frontal vehicle to deformable barrier crash test of a MY2007
Mazda 6 4-door sedan were obtained from NHTSA test database. The
overall behaviors of B-pillar and engine of simulation models agreed
very well with the test data. The trends of accelerations at the driver
and passenger head were similar but big differences in peak values.
The differences of peak values caused the large errors of the HIC36
and 3 ms chest g’s. To predict well the behaviors of dummies, the
spring-mass model for the offset frontal crash needs to be improved.
Abstract: This paper reports the development and application of a 2D1 depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. κ − ε and 2D LES turbulence models were consider in this article. 2D CFD2 simulations for one hill was done to check the depth-averaged model in practise.
Abstract: In dynamic system theory a mathematical model is
often used to describe their properties. In order to find a transfer
matrix of a dynamic system we need to calculate an inverse matrix.
The paper contains the fusion of the classical theory and the
procedures used in the theory of automated control for calculating the
inverse matrix. The final part of the paper models the given problem
by the Matlab.
Abstract: Nowadays, the rapid development of CAD systems’
programming environments results in the creation of multiple
downstream applications, which are developed and becoming
increasingly available. CAD based manufacturing simulations is
gradually following the same trend. Drilling is the most popular holemaking
process used in a variety of industries. A specially built piece
of software that deals with the drilling kinematics is presented. The
cutting forces are calculated based on the tool geometry, the cutting
conditions and the tool/work-piece materials. The results are verified
by experimental work. Finally, the response surface methodology
(RSM) is applied and mathematical models of the total thrust force
and the thrust force developed because of the main cutting edges are
proposed.