Abstract: Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.
Abstract: In this paper, we address the problem of reducing the
switching activity (SA) in on-chip buses through the use of a bus
binding technique in high-level synthesis. While many binding
techniques to reduce the SA exist, we present yet another technique for
further reducing the switching activity. Our proposed method
combines bus binding and data sequence reordering to explore a wider
solution space. The problem is formulated as a multiple traveling
salesman problem and solved using simulated annealing technique.
The experimental results revealed that a binding solution obtained
with the proposed method reduces 5.6-27.2% (18.0% on average) and
2.6-12.7% (6.8% on average) of the switching activity when compared
with conventional binding-only and hybrid binding-encoding
methods, respectively.
Abstract: This paper aims to develop a NOx emission model of
an acid gas incinerator using Nelder-Mead least squares support
vector regression (LS-SVR). Malaysia DOE is actively imposing the
Clean Air Regulation to mandate the installation of analytical
instrumentation known as Continuous Emission Monitoring System
(CEMS) to report emission level online to DOE . As a hardware
based analyzer, CEMS is expensive, maintenance intensive and often
unreliable. Therefore, software predictive technique is often
preferred and considered as a feasible alternative to replace the
CEMS for regulatory compliance. The LS-SVR model is built based
on the emissions from an acid gas incinerator that operates in a LNG
Complex. Simulated Annealing (SA) is first used to determine the
initial hyperparameters which are then further optimized based on the
performance of the model using Nelder-Mead simplex algorithm.
The LS-SVR model is shown to outperform a benchmark model
based on backpropagation neural networks (BPNN) in both training
and testing data.
Abstract: Truss optimization problem has been vastly studied
during the past 30 years and many different methods have been
proposed for this problem. Even though most of these methods
assume that the design variables are continuously valued, in reality,
the design variables of optimization problems such as cross-sectional
areas are discretely valued. In this paper, an improved hill climbing
and an improved simulated annealing algorithm have been proposed
to solve the truss optimization problem with discrete values for crosssectional
areas. Obtained results have been compared to other
methods in the literature and the comparison represents that the
proposed methods can be used more efficiently than other proposed
methods
Abstract: In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.
Abstract: The aim of the present work is to study the effect of annealing on the vibration damping capacity of high-chromium (16%) ferromagnetic steel. The alloys were prepared from raw materials of 99.9% purity melted in a high frequency induction furnace under high vacuum. The samples were heat-treated in vacuum at various temperatures (800 to 1200ºC) for 1 hour followed by slow cooling (120ºC/h). The inverted torsional pendulum method was used to evaluate the vibration damping capacity. The results indicated that the vibration damping capacity of the alloys is influenced by annealing and there exists a critical annealing temperature after 1000ºC. The damping capacity increases quickly below the critical temperature since the magnetic domains move more easily.
Abstract: The electrical and structural properties of Hf/Al/Ni/Au
(20/100/25/50 nm) ohmic contact to n-GaN are reported in this study.
Specific contact resistivities of Hf/Al/Ni/Au based contacts have been
investigated as a function of annealing temperature and achieve the
lowest value of 1.09´10-6 Ω·cm2 after annealing at 650 oC in vacuum.
A detailed mechanism of ohmic contact formation is discussed. By
using different chemical analyses, it is anticipated that the formation of
Hf-Al-N alloy might be responsible to form low temperature ohmic
contacts for the Hf-based scheme to n-GaN.
Abstract: Scheduling for the flexible job shop is very important
in both fields of production management and combinatorial
optimization. However, it quit difficult to achieve an optimal solution
to this problem with traditional optimization approaches owing to the
high computational complexity. The combining of several
optimization criteria induces additional complexity and new
problems. In this paper, a Pareto approach to solve the multi
objective flexible job shop scheduling problems is proposed. The
objectives considered are to minimize the overall completion time
(makespan) and total weighted tardiness (TWT). An effective
simulated annealing algorithm based on the proposed approach is
presented to solve multi objective flexible job shop scheduling
problem. An external memory of non-dominated solutions is
considered to save and update the non-dominated solutions during
the solution process. Numerical examples are used to evaluate and
study the performance of the proposed algorithm. The proposed
algorithm can be applied easily in real factory conditions and for
large size problems. It should thus be useful to both practitioners and
researchers.
Abstract: In this paper a hybrid technique of Genetic Algorithm
and Simulated Annealing (HGASA) is applied for Fractal Image
Compression (FIC). With the help of this hybrid evolutionary
algorithm effort is made to reduce the search complexity of matching
between range block and domain block. The concept of Simulated
Annealing (SA) is incorporated into Genetic Algorithm (GA) in order
to avoid pre-mature convergence of the strings. One of the image
compression techniques in the spatial domain is Fractal Image
Compression but the main drawback of FIC is that it involves more
computational time due to global search. In order to improve the
computational time along with acceptable quality of the decoded
image, HGASA technique has been proposed. Experimental results
show that the proposed HGASA is a better method than GA in terms
of PSNR for Fractal image Compression.
Abstract: ZnO-SnO2 i.e. Zinc-Tin-Oxide (ZTO) thin films were
deposited on glass substrate with varying concentrations (ZnO:SnO2
- 100:0, 90:10, 70:30 and 50:50 wt.%) at room temperature by flash
evaporation technique. These deposited ZTO film were annealed at
450 0C in vacuum. These films were characterized to study the effect
of annealing on the structural, electrical, and optical properties.
Atomic force microscopy (AFM) and Scanning electron microscopy
(SEM) images manifest the surface morphology of these ZTO thin
films. The apparent growth of surface features revealed the formation
of nanostructure ZTO thin films. The small value of surface
roughness (root mean square RRMS) ensures the usefulness in
optical coatings. The sheet resistance was also found to be decreased
for both types of films with increasing concentration of SnO2. The
optical transmittance found to be decreased however blue shift has
been observed after annealing.
Abstract: In the present work homogeneous silica film on
silicon was fabricated by colloidal silica sol. The silica sol precursor
with uniformly granular particle was derived by the alkaline
hydrolysis of tetraethoxyorthosilicate (TEOS) in presence of glycerol
template. The film was prepared by dip coating process. The
templated hetero-structured silica film was annealed at elevated
temperatures to generate nano- and meso porosity in the film. The
film was subsequently annealed at different temperatures to make it
defect free and abrasion resistant. The sol and the film were
characterized by the measurement of particle size distribution,
scanning electron microscopy, XRD, FTIR spectroscopy,
transmission electron microscopy, atomic force microscopy,
measurement of the refractive index, thermal conductivity and
abrasion resistance. The porosity of the films decreased whereas
refractive index and dielectric constant of it `increased with the
increase in the annealing temperature. The thermal conductivity of
the films increased with the increase in the film thickness. The
developed porous silica film holds strong potential for use in
different areas.
Abstract: This paper presents a hybrid approach for solving nqueen problem by combination of PSO and SA. PSO is a population based heuristic method that sometimes traps in local maximum. To solve this problem we can use SA. Although SA suffer from many iterations and long time convergence for solving some problems, By good adjusting initial parameters such as temperature and the length of temperature stages SA guarantees convergence. In this article we use discrete PSO (due to nature of n-queen problem) to achieve a good local maximum. Then we use SA to escape from local maximum. The experimental results show that our hybrid method in comparison of SA method converges to result faster, especially for high dimensions n-queen problems.
Abstract: In this paper, Zinc Oxide (ZnO) thin films are deposited on glass substrate by sol-gel method. The ZnO thin films with well defined orientation were acquired by spin coating of zinc acetate dehydrate monoethanolamine (MEA), de-ionized water and isopropanol alcohol. These films were pre-heated at 275°C for 10 min and then annealed at 350°C, 450°C and 550°C for 80 min. The effect of annealing temperature and different thickness on structure and surface morphology of the thin films were verified by Atomic Force Microscopy (AFM). It was found that there was a significant effect of annealing temperature on the structural parameters of the films such as roughness exponent, fractal dimension and interface width. Thin films also were characterizied by X-ray Diffractometery (XRD) method. XRD analysis revealed that the annealed ZnO thin films consist of single phase ZnO with wurtzite structure and show the c-axis grain orientation. Increasing annealing temperature increased the crystallite size and the c-axis orientation of the film after 450°C. Also In this study, ZnO thin films in different thickness have been prepared by sol-gel method on the glass substrate at room temperature. The thicknesses of films are 100, 150 and 250 nm. Using fractal analysis, morphological characteristics of surface films thickness in amorphous state were investigated. The results show that with increasing thickness, surface roughness (RMS) and lateral correlation length (ξ) are decreased. Also, the roughness exponent (α) and growth exponent (β) were determined to be 0.74±0.02 and 0.11±0.02, respectively.
Abstract: Cell formation is the first step in the design of cellular
manufacturing systems. In this study, a general purpose
computational scheme employing a hybrid tabu search algorithm as
the core is proposed to solve the cell formation problem and its
variants. In the proposed scheme, great flexibilities are left to the
users. The core solution searching algorithm embedded in the scheme
can be easily changed to any other meta-heuristic algorithms, such as
the simulated annealing, genetic algorithm, etc., based on the
characteristics of the problems to be solved or the preferences the
users might have. In addition, several counters are designed to control
the timing of conducting intensified solution searching and diversified
solution searching strategies interactively.
Abstract: In this paper, a new hybrid of genetic algorithm (GA)
and simulated annealing (SA), referred to as GSA, is presented. In
this algorithm, SA is incorporated into GA to escape from local
optima. The concept of hierarchical parallel GA is employed to
parallelize GSA for the optimization of multimodal functions. In
addition, multi-niche crowding is used to maintain the diversity in
the population of the parallel GSA (PGSA). The performance of the
proposed algorithms is evaluated against a standard set of multimodal
benchmark functions. The multi-niche crowding PGSA and normal
PGSA show some remarkable improvement in comparison with the
conventional parallel genetic algorithm and the breeder genetic
algorithm (BGA).
Abstract: A spanning tree of a connected graph is a tree which
consists the set of vertices and some or perhaps all of the edges from
the connected graph. In this paper, a model for spanning tree
transformation of connected graphs into single-row networks, namely
Spanning Tree of Connected Graph Modeling (STCGM) will be
introduced. Path-Growing Tree-Forming algorithm applied with
Vertex-Prioritized is contained in the model to produce the spanning
tree from the connected graph. Paths are produced by Path-Growing
and they are combined into a spanning tree by Tree-Forming. The
spanning tree that is produced from the connected graph is then
transformed into single-row network using Tree Sequence Modeling
(TSM). Finally, the single-row routing problem is solved using a
method called Enhanced Simulated Annealing for Single-Row
Routing (ESSR).
Abstract: The most severe damage of the turbine rotor is its
distortion. The rotor straightening process must lead, at the first
stage, to removal of the stresses from the material by annealing and
next, to straightening of the plastic distortion without leaving any
stress by hot spotting. The straightening method does not produce
stress accumulations and the heating technique, developed
specifically for solid forged rotors and disks, enables to avoid local
overheating and structural changes in the material. This process also
does not leave stresses in the shaft material. An experimental study
of hot spotting is carried out on a large turbine rotor and some of the
most important effective parameters that must be considered on
annealing and hot spotting processes are investigated in this paper.
Abstract: In this paper a new approach is proposed for the
adaptation of the simulated annealing search in the field of the
Multi-Objective Optimization (MOO). This new approach is called
Multi-Case Multi-Objective Simulated Annealing (MC-MOSA). It
uses some basics of a well-known recent Multi-Objective Simulated
Annealing proposed by Ulungu et al., which is referred in the
literature as U-MOSA. However, some drawbacks of this algorithm
have been found, and are substituted by other ones, especially in
the acceptance decision criterion. The MC-MOSA has shown better
performance than the U-MOSA in the numerical experiments. This
performance is further improved by some other subvariants of the
MC-MOSA, such as Fast-annealing MC-MOSA, Re-annealing MCMOSA
and the Two-Stage annealing MC-MOSA.
Abstract: Individually Network reconfiguration or Capacitor control
perform well in minimizing power loss and improving voltage
profile of the distribution system. But for heavy reactive power loads
network reconfiguration and for heavy active power loads capacitor
placement can not effectively reduce power loss and enhance
voltage profiles in the system. In this paper, an hybrid approach
that combine network reconfiguration and capacitor placement using
Harmony Search Algorithm (HSA) is proposed to minimize power
loss reduction and improve voltage profile. The proposed approach
is tested on standard IEEE 33 and 16 bus systems. Computational
results show that the proposed hybrid approach can minimize losses
more efficiently than Network reconfiguration or Capacitor control.
The results of proposed method are also compared with results
obtained by Simulated Annealing (SA). The proposed method has
outperformed in terms of the quality of solution compared to SA.
Abstract: We report a lithography-free approach to fabricate the
biomimetics, quasi-beehive Si nanostructures (QBSNs), on
Si-substrates. The self-assembled SiGe nanoislands via the strain
induced surface roughening (Asaro-Tiller-Grinfeld instability) during
in-situ annealing play a key role as patterned sacrifice regions for
subsequent reactive ion etching (RIE) process performed for
fabricating quasi-beehive nanostructures on Si-substrates. As the
measurements of field emission, the bare QBSNs show poor field
emission performance, resulted from the existence of the native oxide
layer which forms an insurmountable barrier for electron emission. In
order to dramatically improve the field emission characteristics, the
platinum nanopillars (Pt-NPs) were deposited on QBSNs to form
Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs
is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2),
and the field enhancement factor (β-value) is significantly increased to
6067. More importantly, the uniform and continuous electrons excite
light emission, due to the surrounding filed emitters from
Pt-NPs/QBSNs, can be easily obtained. This approach does not require
an expensive photolithographic process and possesses great potential
for applications.