Abstract: The effects of different parameters on the
hydrodynamics of trickle bed reactors were discussed for Newtonian
and non-Newtonian foaming systems. The varying parameters are
varying liquid velocities, gas flow velocities and surface tension. The
range for gas velocity is particularly large, thanks to the use of dense
gas to simulate very high pressure conditions. This data bank has
been used to compare the prediction accuracy of the different
trendlines and transition points from the literature. More than 240
experimental points for the trickle flow (GCF) and foaming pulsing
flow (PF/FPF) regime were obtained for present study.
Hydrodynamic characteristics involving dynamic liquid saturation
significantly influenced by gas and liquid flow rates. For 15 and 30
ppm air-aqueous surfactant solutions, dynamic liquid saturation
decreases with higher liquid and gas flow rates considerably in high
interaction regime. With decrease in surface tension i.e. for 45 and 60
ppm air-aqueous surfactant systems, effect was more pronounced
with decreases dynamic liquid saturation very sharply during regime
transition significantly at both low liquid and gas flow rates.
Abstract: This paper presents recent work on the improvement
of the robotics vision based control strategy for underwater pipeline
tracking system. The study focuses on developing image processing
algorithms and a fuzzy inference system for the analysis of the
terrain. The main goal is to implement the supervisory fuzzy learning
control technique to reduce the errors on navigation decision due to
the pipeline occlusion problem. The system developed is capable of
interpreting underwater images containing occluded pipeline, seabed
and other unwanted noise. The algorithm proposed in previous work
does not explore the cooperation between fuzzy controllers,
knowledge and learnt data to improve the outputs for underwater
pipeline tracking. Computer simulations and prototype simulations
demonstrate the effectiveness of this approach. The system accuracy
level has also been discussed.
Abstract: Based on experimental data using accelerometry technology there was developed an analytical model that approximates human induced ground reaction forces in vertical, longitudinal and lateral directions ascending and descending the stairs. Proposed dynamic loading factors and corresponding phase shifts for the first five harmonics of continuous walking force history in case of stair ascend and descend. Into account is taken imperfectness of individual footfall forcing functions, differences between continuous walking force histories among individuals. There is proposed mean synthetic continuous walking force history that can be used in numerical simulations of human movement on the stairs.
Abstract: This article addresses feature selection for breast
cancer diagnosis. The present process contains a wrapper approach
based on Genetic Algorithm (GA) and case-based reasoning (CBR).
GA is used for searching the problem space to find all of the possible
subsets of features and CBR is employed to estimate the evaluation
result of each subset. The results of experiment show that the
proposed model is comparable to the other models on Wisconsin
breast cancer (WDBC) dataset.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: Initial values of reference vectors have significant influence on recognition accuracy in LVQ. There are several existing techniques, such as SOM and k-means, for setting initial values of reference vectors, each of which has provided some positive results. However, those results are not sufficient for the improvement of recognition accuracy. This study proposes an ACO-used method for initializing reference vectors with an aim to achieve recognition accuracy higher than those obtained through conventional methods. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to the wine data and English vowel data and comparing its results with those of conventional methods.
Abstract: A mathematical model of the surface roughness
has been developed by using response surface methodology
(RSM) in grinding of AISI D2 cold work tool steels. Analysis
of variance (ANOVA) was used to check the validity of the
model. Low and high value for work speed and feed rate are
decided from design of experiment. The influences of all
machining parameters on surface roughness have been
analyzed based on the developed mathematical model. The
developed prediction equation shows that both the feed rate
and work speed are the most important factor that influences
the surface roughness. The surface roughness was found to be
the lowers with the used of low feed rate and low work speed.
Accuracy of the best model was proved with the testing data.
Abstract: This paper is a description approach to predict
incoming and outgoing data rate in network system by using
association rule discover, which is one of the data mining
techniques. Information of incoming and outgoing data in each
times and network bandwidth are network performance
parameters, which needed to solve in the traffic problem. Since
congestion and data loss are important network problems. The result
of this technique can predicted future network traffic. In addition,
this research is useful for network routing selection and network
performance improvement.
Abstract: Recent advancements in sensor technologies and
Wireless Body Area Networks (WBANs) have led to the
development of cost-effective healthcare devices which can be used
to monitor and analyse a person-s physiological parameters from
remote locations. These advancements provides a unique opportunity
to overcome current healthcare challenges of low quality service
provisioning, lack of easy accessibility to service varieties, high costs
of services and increasing population of the elderly experienced
globally. This paper reports on a prototype implementation of an
architecture that seamlessly integrates Wireless Body Area Network
(WBAN) with Web services (WS) to proactively collect
physiological data of remote patients to recommend diagnostic
services. Technologies based upon WBAN and WS can provide
ubiquitous accessibility to a variety of services by allowing
distributed healthcare resources to be massively reused to provide
cost-effective services without individuals physically moving to the
locations of those resources. In addition, these technologies can
reduce costs of healthcare services by allowing individuals to access
services to support their healthcare. The prototype uses WBAN body
sensors implemented on arduino fio platforms to be worn by the
patient and an android smart phone as a personal server. The
physiological data are collected and uploaded through GPRS/internet
to the Medical Health Server (MHS) to be analysed. The prototype
monitors the activities, location and physiological parameters such as
SpO2 and Heart Rate of the elderly and patients in rehabilitation.
Medical practitioners would have real time access to the uploaded
information through a web application.
Abstract: The importance of machining process in today-s
industry requires the establishment of more practical approaches to
clearly represent the intimate and severe contact on the tool-chipworkpiece
interfaces. Mathematical models are developed using the
measured force signals to relate each of the tool-chip friction
components on the rake face to the operating cutting parameters in
rough turning operation using multilayers coated carbide inserts.
Nonlinear modeling proved to have high capability to detect the
nonlinear functional variability embedded in the experimental data.
While feedrate is found to be the most influential parameter on the
friction coefficient and its related force components, both cutting
speed and depth of cut are found to have slight influence. Greater
deformed chip thickness is found to lower the value of friction
coefficient as the sliding length on the tool-chip interface is reduced.
Abstract: Electronic Government is one of the special concepts
which has been performed successfully within recent decades.
Electronic government is a digital, wall-free government with a
virtual organization for presenting of online governmental services
and further cooperation in different political/social activities. In order
to have a successful implementation of electronic government
strategy and benefiting from its complete potential and benefits and
generally for establishment and applying of electronic government, it
is necessary to have different infrastructures as the basics of
electronic government with lack of which it is impossible to benefit
from mentioned services. For this purpose, in this paper we have
managed to recognize relevant obstacles for establishment of
electronic government in Iran. All required data for recognition of
obstacles were collected from statistical society of involved
specialists of Ministry of Communications & Information
Technology of Iran and Information Technology Organization of
Tehran Municipality through questionnaire. Then by considering of
five-point Likert scope and μ =3 as the index of relevant factors of
proposed model, we could specify current obstacles against
electronic government in Iran along with some guidelines and
proposal in this regard. According to the results, mentioned obstacles
for applying of electronic government in Iran are as follows:
Technical & technological problems, Legal, judicial & safety
problems, Economic problems and Humanistic Problems.
Abstract: In this paper we propose a mixture of two different
distributions such as Exponential-Gamma, Exponential-Weibull and
Gamma-Weibull to model heterogeneous survival data. Various
properties of the proposed mixture of two different distributions are
discussed. Maximum likelihood estimations of the parameters are
obtained by using the EM algorithm. Illustrative example based on
real data are also given.
Abstract: The literature reports a large number of approaches for
measuring the similarity between protein sequences. Most of these
approaches estimate this similarity using alignment-based techniques
that do not necessarily yield biologically plausible results, for two
reasons.
First, for the case of non-alignable (i.e., not yet definitively aligned
and biologically approved) sequences such as multi-domain, circular
permutation and tandem repeat protein sequences, alignment-based
approaches do not succeed in producing biologically plausible results.
This is due to the nature of the alignment, which is based on the
matching of subsequences in equivalent positions, while non-alignable
proteins often have similar and conserved domains in non-equivalent
positions.
Second, the alignment-based approaches lead to similarity measures
that depend heavily on the parameters set by the user for the alignment
(e.g., gap penalties and substitution matrices). For easily alignable
protein sequences, it's possible to supply a suitable combination of
input parameters that allows such an approach to yield biologically
plausible results. However, for difficult-to-align protein sequences,
supplying different combinations of input parameters yields different
results. Such variable results create ambiguities and complicate the
similarity measurement task.
To overcome these drawbacks, this paper describes a novel and
effective approach for measuring the similarity between protein
sequences, called SAF for Substitution and Alignment Free. Without
resorting either to the alignment of protein sequences or to substitution
relations between amino acids, SAF is able to efficiently detect the
significant subsequences that best represent the intrinsic properties of
protein sequences, those underlying the chronological dependencies of
structural features and biochemical activities of protein sequences.
Moreover, by using a new efficient subsequence matching scheme,
SAF more efficiently handles protein sequences that contain similar
structural features with significant meaning in chronologically
non-equivalent positions. To show the effectiveness of SAF, extensive
experiments were performed on protein datasets from different
databases, and the results were compared with those obtained by
several mainstream algorithms.
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: MATCH project [1] entitle the development of an
automatic diagnosis system that aims to support treatment of colon
cancer diseases by discovering mutations that occurs to tumour
suppressor genes (TSGs) and contributes to the development of
cancerous tumours. The constitution of the system is based on a)
colon cancer clinical data and b) biological information that will be
derived by data mining techniques from genomic and proteomic
sources The core mining module will consist of the popular, well
tested hybrid feature extraction methods, and new combined
algorithms, designed especially for the project. Elements of rough
sets, evolutionary computing, cluster analysis, self-organization maps
and association rules will be used to discover the annotations
between genes, and their influence on tumours [2]-[11].
The methods used to process the data have to address their high
complexity, potential inconsistency and problems of dealing with the
missing values. They must integrate all the useful information
necessary to solve the expert's question. For this purpose, the system
has to learn from data, or be able to interactively specify by a domain
specialist, the part of the knowledge structure it needs to answer a
given query. The program should also take into account the
importance/rank of the particular parts of data it analyses, and adjusts
the used algorithms accordingly.
Abstract: Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.
Abstract: A cancelable palmprint authentication system
proposed in this paper is specifically designed to overcome the
limitations of the contemporary biometric authentication system. In
this proposed system, Geometric and pseudo Zernike moments are
employed as feature extractors to transform palmprint image into a
lower dimensional compact feature representation. Before moment
computation, wavelet transform is adopted to decompose palmprint
image into lower resolution and dimensional frequency subbands.
This reduces the computational load of moment calculation
drastically. The generated wavelet-moment based feature
representation is used to generate cancelable verification key with a
set of random data. This private binary key can be canceled and
replaced. Besides that, this key also possesses high data capture
offset tolerance, with highly correlated bit strings for intra-class
population. This property allows a clear separation of the genuine
and imposter populations, as well as zero Equal Error Rate
achievement, which is hardly gained in the conventional biometric
based authentication system.
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: The new concept of two–dimensional (2D) image
processing implementation for auto-guiding system is shown in this
paper. It is dedicated to astrophotography and operates with
astronomy CCD guide cameras or with self-guided dual-detector
CCD cameras and ST4 compatible equatorial mounts. This idea was
verified by MATLAB model, which was used to test all procedures
and data conversions. Next the circuit prototype was implemented at
Altera MAX II CPLD device and tested for real astronomical object
images. The digital processing speed of CPLD prototype board was
sufficient for correct equatorial mount guiding in real-time system.
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.