Abstract: A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.
Abstract: Accurate loss minimization is the critical component
for efficient electrical distribution power flow .The contribution of
this work presents loss minimization in power distribution system
through feeder restructuring, incorporating DG and placement of
capacitor. The study of this work was conducted on IEEE
distribution network and India Electricity Board benchmark
distribution system. The executed experimental result of Indian
system is recommended to board and implement practically for
regulated stable output.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: This paper presents the design of a ring-shaped tri-axial fore sensor that can be incorporated into the tip of a guidewire for use in minimally invasive surgery (MIS). The designed sensor comprises a ring-shaped structure located at the center of four cantilever beams. The ringdesign allows surgical tools to be easily passed through which largely simplified the integration process. Silicon nanowires (SiNWs) are used aspiezoresistive sensing elementsembeddedon the four cantilevers of the sensor to detect the resistance change caused by the applied load.An integration scheme with new designed guidewire tip structure having two coils at the distal end is presented. Finite element modeling has been employed in the sensor design to find the maximum stress location in order to put the SiNWs at the high stress regions to obtain maximum output. A maximum applicable force of 5 mN is found from modeling. The interaction mechanism between the designed sensor and a steel wire has been modeled by FEM. A linear relationship between the applied load on the steel wire and the induced stress on the SiNWs were observed.
Abstract: This work concerns the topological optimization
problem for determining the optimal petroleum refinery
configuration. We are interested in further investigating and
hopefully advancing the existing optimization approaches and
strategies employing logic propositions to conceptual process
synthesis problems. In particular, we seek to contribute to this
increasingly exciting area of chemical process modeling by
addressing the following potentially important issues: (a) how the
formulation of design specifications in a mixed-logical-and-integer
optimization model can be employed in a synthesis problem to enrich
the problem representation by incorporating past design experience,
engineering knowledge, and heuristics; and (b) how structural
specifications on the interconnectivity relationships by space (states)
and by function (tasks) in a superstructure should be properly
formulated within a mixed-integer linear programming (MILP)
model. The proposed modeling technique is illustrated on a case
study involving the alternative processing routes of naphtha, in which
significant improvement in the solution quality is obtained.
Abstract: Knee joint forces are available by in vivo measurement
using an instrumented knee prosthesis for small to moderate knee
flexion but not for high flexion yet. We created a 2D mathematical
model of the lower limb incorporating several new features such as a
patello-femoral mechanism, a thigh-calf contact at high knee flexion
and co-contracting muscles' force ratio, then used it to determine knee
joint forces arising from high knee flexions in four kneeling
conditions: rising with legs in parallel, with one foot forward, with or
without arm use. With arms used, the maximum values of knee joint
force decreased to about 60% of those with arms not used. When rising
with one foot forward, if arms are not used, the forward leg sustains a
force as large as that sustained when rising with legs parallel.
Abstract: Environmental aspects plays a central role in environmental management system (EMS) because it is the basis for the identification of an organization-s environmental targets. The
existing methods for the assessment of environmental aspects are grouped into three categories: risk assessment-based (RA-based),
LCA-based and criterion-based methods. To combine the benefits of
these three categories of research, this study proposes an integrated framework, combining RA-, LCA- and criterion-based methods. The
integrated framework incorporates LCA techniques for the identification of the causal linkage for aspect, pathway, receptor and
impact, uses fuzzy logic to assess aspects, considers fuzzy conditions,
in likelihood assessment, and employs a new multi-criteria decision analysis method - multi-criteria and multi-connection comprehensive
assessment (MMCA) - to estimate significant aspects in EMS. The proposed model is verified, using a real case study and the results show
that this method successfully prioritizes the environmental aspects.
Abstract: Testing accounts for the major percentage of technical
contribution in the software development process. Typically, it
consumes more than 50 percent of the total cost of developing a
piece of software. The selection of software tests is a very important
activity within this process to ensure the software reliability
requirements are met. Generally tests are run to achieve maximum
coverage of the software code and very little attention is given to the
achieved reliability of the software. Using an existing methodology,
this paper describes how to use Bayesian Belief Networks (BBNs) to
select unit tests based on their contribution to the reliability of the
module under consideration. In particular the work examines how the
approach can enhance test-first development by assessing the quality
of test suites resulting from this development methodology and
providing insight into additional tests that can significantly reduce
the achieved reliability. In this way the method can produce an
optimal selection of inputs and the order in which the tests are
executed to maximize the software reliability. To illustrate this
approach, a belief network is constructed for a modern software
system incorporating the expert opinion, expressed through
probabilities of the relative quality of the elements of the software,
and the potential effectiveness of the software tests. The steps
involved in constructing the Bayesian Network are explained as is a
method to allow for the test suite resulting from test-driven
development.
Abstract: In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: Fatigue cracking continues to be the main challenges in
improving the performance of bituminous mixture pavements. The
purpose of this paper is to look at some aspects of the effects of fine
aggregate properties on the fatigue behaviour of hot mixture asphalt.
Two types of sand (quarry and mining sand) with two conventional
bitumen (PEN 50/60 & PEN 80/100) and four polymers modified
bitumen PMB (PM1_82, PM1_76, PM2_82 and PM2_76) were used.
Physical, chemical and mechanical tests were performed on the sands
to determine their effect when incorporated with a bituminous
mixture. According to the beam fatigue results, quarry sand that has
more angularity, rougher, higher shear strength and a higher
percentage of Aluminium oxide presented higher resistance to
fatigue. Also a PMB mixture gives better fatigue results than
conventional mixtures, this is due to the PMB having better viscosity
property than that of the conventional bitumen.
Abstract: Business process modeling has become an accepted
means for designing and describing business operations. Thereby,
consistency of business process models, i.e., the absence of modeling
faults, is of upmost importance to organizations. This paper presents
a concept and subsequent implementation for detecting faults in
business process models and for computing a measure of their
consistency. It incorporates not only syntactic consistency but also
semantic consistency, i.e., consistency regarding the meaning of
model elements from a business perspective.
Abstract: Minimally invasive surgery (MIS) is now being widely used as a preferred choice for various types of operations. The need to detect various tactile properties, justifies the key role of tactile sensing that is currently missing in MIS. In this regard, Laparoscopy is one of the methods of minimally invasive surgery that can be used in kidney stone removal surgeries. At this moment, determination of the exact location of stone during laparoscopy is one of the limitations of this method that no scientific solution has been found for so far. Artificial tactile sensing is a new method for obtaining the characteristics of a hard object embedded in a soft tissue. Artificial palpation is an important application of artificial tactile sensing that can be used in different types of surgeries. In this study, a new method for determining the exact location of stone during laparoscopy is presented. In the present study, the effects of stone existence on the surface of kidney were investigated using conceptual 3D model of kidney containing a simulated stone. Having imitated palpation and modeled it conceptually, indications of stone existence that appear on the surface of kidney were determined. A number of different cases were created and solved by the software and using stress distribution contours and stress graphs, it is illustrated that the created stress patterns on the surface of kidney show not only the existence of stone inside, but also its exact location. So three-dimensional analysis leads to a novel method of predicting the exact location of stone and can be directly applied to the incorporation of tactile sensing in artificial palpation, helping surgeons in non-invasive procedures.
Abstract: The ever increasing use of World Wide Web in the
existing network, results in poor performance. Several techniques
have been developed for reducing web traffic by compressing the size
of the file, saving the web pages at the client side, changing the burst
nature of traffic into constant rate etc. No single method was
adequate enough to access the document instantly through the
Internet. In this paper, adaptive hybrid algorithms are developed for
reducing web traffic. Intelligent agents are used for monitoring the
web traffic. Depending upon the bandwidth usage, user-s preferences,
server and browser capabilities, intelligent agents use the best
techniques to achieve maximum traffic reduction. Web caching,
compression, filtering, optimization of HTML tags, and traffic
dispersion are incorporated into this adaptive selection. Using this
new hybrid technique, latency is reduced to 20 – 60 % and cache hit
ratio is increased 40 – 82 %.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: The Internet is the global data communications
infrastructure based on the interconnection of both public and private
networks using protocols that implement Internetworking on a global
scale. Hence the control of protocol and infrastructure development,
resource allocation and network operation are crucial and interlinked
aspects. Internet Governance is the hotly debated and contentious
subject that refers to the global control and operation of key Internet
infrastructure such as domain name servers and resources such as
domain names. It is impossible to separate technical and political
positions as they are interlinked. Furthermore the existence of a
global market, transparency and competition impact upon Internet
Governance and related topics such as network neutrality and
security. Current trends and developments regarding Internet
governance with a focus on the policy-making process, security and
control have been observed to evaluate current and future
implications on the Internet. The multi stakeholder approach to
Internet Governance discussed in this paper presents a number of
opportunities, issues and developments that will affect the future
direction of the Internet. Internet operation, maintenance and
advisory organisations such as the Internet Corporation for Assigned
Names and Numbers (ICANN) or the Internet Governance Forum
(IGF) are currently in the process of formulating policies for future
Internet Governance. Given the controversial nature of the issues at
stake and the current lack of agreement it is predicted that
institutional as well as market governance will remain present for the
network access and content.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: Characteristics and sonocatalytic activity of zeolite
Y catalysts loaded with TiO2 using impregnation and ion exchange
methods for the degradation of amaranth dye were investigated.
The Ion-exchange method was used to encapsulate the TiO2 into
the internal pores of the zeolite while the incorporation of TiO2
mostly on the external surface of zeolite was carried out using the
impregnation method. Different characterization techniques were
used to elucidate the physicochemical properties of the produced
catalysts. The framework of zeolite Y remained virtually
unchanged after the encapsulation of TiO2 while the crystallinity of
zeolite decreased significantly after the incorporation of 15 wt% of
TiO2. The sonocatalytic activity was enhanced by TiO2
incorporation with maximum degradation efficiencies of 50% and
68% for the encapsulated titanium and titanium loaded onto the
zeolite, respectively after 120min of reaction. Catalysts
characteristics and sonocatalytic behaviors were significantly
affected by the preparation method and the location of TiO2
introduced with zeolite structure. Behaviors in the sonocatalytic
process were successfully correlated with the characteristics of the
catalysts used.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in the form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studied with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.
Abstract: Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, many real life optimization problems often
require finding optimal solution to complex high dimensional,
multimodal problems involving computationally very expensive
fitness function evaluations. Use of evolutionary algorithms in such
problem domains is thus practically prohibitive. An attractive
alternative is to build meta models or use an approximation of the
actual fitness functions to be evaluated. These meta models are order
of magnitude cheaper to evaluate compared to the actual function
evaluation. Many regression and interpolation tools are available to
build such meta models. This paper briefly discusses the
architectures and use of such meta-modeling tools in an evolutionary
optimization context. We further present two evolutionary algorithm
frameworks which involve use of meta models for fitness function
evaluation. The first framework, namely the Dynamic Approximate
Fitness based Hybrid EA (DAFHEA) model [14] reduces
computation time by controlled use of meta-models (in this case
approximate model generated by Support Vector Machine
regression) to partially replace the actual function evaluation by
approximate function evaluation. However, the underlying
assumption in DAFHEA is that the training samples for the metamodel
are generated from a single uniform model. This does not take
into account uncertain scenarios involving noisy fitness functions.
The second model, DAFHEA-II, an enhanced version of the original
DAFHEA framework, incorporates a multiple-model based learning
approach for the support vector machine approximator to handle
noisy functions [15]. Empirical results obtained by evaluating the
frameworks using several benchmark functions demonstrate their
efficiency