Abstract: With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.
Abstract: We study in this paper the effect of the scene
changing on image sequences coding system using Embedded
Zerotree Wavelet (EZW). The scene changing considered here is the
full motion which may occurs. A special image sequence is generated
where the scene changing occurs randomly. Two scenarios are
considered: In the first scenario, the system must provide the
reconstruction quality as best as possible by the management of the
bit rate (BR) while the scene changing occurs. In the second scenario,
the system must keep the bit rate as constant as possible by the
management of the reconstruction quality. The first scenario may be
motivated by the availability of a large band pass transmission
channel where an increase of the bit rate may be possible to keep the
reconstruction quality up to a given threshold. The second scenario
may be concerned by the narrow band pass transmission channel
where an increase of the bit rate is not possible. In this last case,
applications for which the reconstruction quality is not a constraint
may be considered. The simulations are performed with five scales
wavelet decomposition using the 9/7-tap filter bank biorthogonal
wavelet. The entropy coding is performed using a specific defined
binary code book and EZW algorithm. Experimental results are
presented and compared to LEAD H263 EVAL. It is shown that if
the reconstruction quality is the constraint, the system increases the
bit rate to obtain the required quality. In the case where the bit rate
must be constant, the system is unable to provide the required quality
if the scene change occurs; however, the system is able to improve
the quality while the scene changing disappears.
Abstract: We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.
Abstract: Controlled release urea has become popular in agricultural industry as it helps to solve environmental issues and increase crop yield. Recently biomass was identified to replace the polymer used as a coating material in the conventional coated urea. In this paper spreading and contact angle of biomass droplet (lignin, cellulose and clay) on urea surface are investigated experimentally. There were two tests were conducted, sessile drop for contact angle measurement and pendant drop for contact angle measurement. A different concentration of biomass droplet was released from 30 mm above a substrate. Glass was used as a controlled substrate. Images were recorded as soon as the droplet impacted onto the urea before completely adsorb into the urea. Digitized droplets were then used to identify the droplet-s surface tension and contact angle. There is large difference observed between the low surface tension and high surface tension liquids, where the wetting and spreading diameter is higher for lower surface tension. From the contact angle results, the data showed that the biomass coating films were possible as wetting liquid (θ < 90º). Contact angle of biomass coating material gives good indication for the wettablity of a liquid on urea surface.
Abstract: Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.
Abstract: In this paper, an improved edge detection algorithm
based on fuzzy combination of mathematical morphology and
wavelet transform is proposed. The combined method is proposed to
overcome the limitation of wavelet based edge detection and
mathematical morphology based edge detection in noisy images.
Experimental results show superiority of the proposed method, as
compared to the traditional Prewitt, wavelet based and morphology
based edge detection methods. The proposed method is an effective
edge detection method for noisy image and keeps clear and
continuous edges.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: This paper presents the results of the experimental
tests of the cooling performance of a 12,000-Btu/h modified air
conditioner (referred to as M-AC) that use the ground as a heat sink
of a condenser. In the tests, cooling capacity of M-AC with an
optimal length of a condensing coil as well as life expectancy of
copper coil buried underground were investigated. The lengths of
copper coil fabricated and used as condenser coil of M-AC were set
at 67, 50, 40 and 30 m whereas that of a 12,000-Btu/h conventional
split-type air conditioner (referred to as C-AC) was about 22 m. The
results showed that the ground can absorb heat rejected from a
condenser of M-AC. The coefficient of performance (COP) of C-AC
was about 2.5 whereas those of M-AC were found to be higher. It
was found that the values of COP of M-AC with condensing coils of
67, 50 and 40 m long were about 6.9, 5.5 and 3.3, respectively, while
that of 30-m-long one was found to be about 2.1. The electrical
consumptions of M-AC were found lower than that of C-AC in the
range of 11.5 – 15.5%. Additionally, life expectancy of underground
condensing coil of M-AC was found to be over 7 years.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: A Comparison and evaluation of the different
condition monitoring (CM) techniques was applied experimentally
on RC e.g. Dynamic cylinder pressure and crankshaft Instantaneous
Angular Speed (IAS), for the detection and diagnosis of valve faults
in a two - stage reciprocating compressor for a programme of
condition monitoring which can successfully detect and diagnose a
fault in machine. Leakage in the valve plate was introduced
experimentally into a two-stage reciprocating compressor. The effect
of the faults on compressor performance was monitored and the
differences with the normal, healthy performance noted as a fault
signature been used for the detection and diagnosis of faults.
The paper concludes with what is considered to be a unique
approach to condition monitoring. First, each of the two most useful
techniques is used to produce a Truth Table which details the
circumstances in which each method can be used to detect and
diagnose a fault. The two Truth Tables are then combined into a
single Decision Table to provide a unique and reliable method of
detection and diagnosis of each of the individual faults introduced
into the compressor. This gives accurate diagnosis of compressor
faults.
Abstract: 17α-ethynylestradiol (EE2) is a synthetic estrogen
used as a key ingredient in an oral contraceptives pill. EE2 is an
endocrine disrupting compound, high in estrogenic potency.
Although EE2 exhibits low degree of biodegradability with common
microorganisms in wastewater treatment plants (WWTPs), this
compound can be biotransformed by ammonia-oxidizing bacteria
(AOB) via a co-metabolism mechanism in WWTPs. This study
aimed to investigate the effect of real wastewater on
biotransformation of EE2 by AOB. A preliminary experiment on the
effect of nitrite and pH levels on abiotic transformation of EE2
suggested that the abiotic transformation occurred at only pH
Abstract: Three alumina-supported Pt-Sn catalysts have been
prepared by means of co-impregnation and characterized by XRD and
N2 adsorption. The influence of catalyst composition and reaction
conditions on the conversion and selectivity were investigated in the
hydrogenation of acetic acid in an isothermal integral fixed bed
reactor. The experiments were performed on the temperature interval
468-548 K, liquid hourly space velocity (LHSV) of 0.3-0.7h-1,
pressures between 1.0 and 5.0Mpa. A good compromise of
0.75%Pt-1.5%Sn can act as an optimized acetic acid hydrogenation
catalyst, and the conversion and selectivity can be tuned through the
variation of reaction conditions.
Abstract: Mining sequential patterns from large customer transaction databases has been recognized as a key research topic in database systems. However, the previous works more focused on mining sequential patterns at a single concept level. In this study, we introduced concept hierarchies into this problem and present several algorithms for discovering multiple-level sequential patterns based on the hierarchies. An experiment was conducted to assess the performance of the proposed algorithms. The performances of the algorithms were measured by the relative time spent on completing the mining tasks on two different datasets. The experimental results showed that the performance depends on the characteristics of the datasets and the pre-defined threshold of minimal support for each level of the concept hierarchy. Based on the experimental results, some suggestions were also given for how to select appropriate algorithm for a certain datasets.
Abstract: Experimental investigations were carried out in the
Manchester Tidal flow Facility (MTF) to study the flow patterns in
the region around and adjacent to a hypothetical headland in tidal
(oscillatory) ambient flow. The Planar laser-induced fluorescence
(PLIF) technique was used for visualization, with fluorescent dye
released at specific points around the headland perimeter and in its
adjacent recirculation zone. The flow patterns can be generalized into
the acceleration, stable flow and deceleration stages for each halfcycle,
with small variations according to location, which are more
distinct for low Keulegan-Carpenter number (KC) cases. Flow
patterns in the mixing region are unstable and complex, especially in
the recirculation zone. The flow patterns are in agreement with
previous visualizations, and support previous results in steady
ambient flow. It is suggested that the headland lee could be a viable
location for siting of pollutant outfalls.
Abstract: A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.
Abstract: There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.
Abstract: This paper presents a experiment to estimate the
influences of cutting conditions in microstructure changes of
machining austenitic 304 stainless steel, especially for wear insert. The
wear insert were prefabricated with a width of 0.5 mm. And the forces,
temperature distribution, RS, and microstructure changes were
measured by force dynamometer, infrared thermal camera, X-ray
diffraction, XRD, SEM, respectively. The results told that the different
combinations of machining condition have a significant influence on
machined surface microstructure changes. In addition to that, the
ANOVA and AOMwere used to tell the different influences of cutting
speed, feed rate, and wear insert.
Abstract: In this paper, we present local image descriptor using
VQ-SIFT for more effective and efficient image retrieval. Instead of
SIFT's weighted orientation histograms, we apply vector quantization
(VQ) histogram as an alternate representation for SIFT features.
Experimental results show that SIFT features using VQ-based local
descriptors can achieve better image retrieval accuracy than the
conventional algorithm while the computational cost is significantly
reduced.
Abstract: This paper present an effective method to accurately reconstruct and measure the 3D curve edges of small industrial parts based on stereo vision. To effectively fit the curve of the measured parts using a series of line segments in the images, a strategy from coarse to fine is employed based on multi-scale curve fitting. After reconstructing the 3D curve of a hole through a curved surface, its axis is adjusted so that it is parallel to the Z axis with least squares error and the dimensions of the hole can be calculated on the XY plane easily. Experimental results show that the presented method can accurately measure the dimensions of round holes through a curved surface.
Abstract: In this study, the effect of nanofluids on the pool film
boiling was experimentally investigated at saturated condition under
atmospheric pressure. For this purpose, four different water-based
nanofluids (Al2O3, SiO2, TiO2 and CuO) with 0.1% particle volume
fraction were prepared. To investigate the boiling heat transfer, a
cylindrical rod with high temperature was used. The rod heated up to
high temperatures was immersed into nanofluids. The center
temperature of rod during the cooling process was recorded by using
a K-type thermocouple. The quenching curves showed that the pool
boiling heat transfer was strongly dependent on the nanoparticle
materials. During the repetitive quenching tests, the cooling time
decreased and thus, the film boiling vanished. Consequently, the
primary reason of this was the change of the surface characteristics
due to the nanoparticles deposition on the rod-s surface.