Abstract: Protein 3D structure prediction has always been an
important research area in bioinformatics. In particular, the
prediction of secondary structure has been a well-studied research
topic. Despite the recent breakthrough of combining multiple
sequence alignment information and artificial intelligence algorithms
to predict protein secondary structure, the Q3 accuracy of various
computational prediction algorithms rarely has exceeded 75%. In a
previous paper [1], this research team presented a rule-based method
called RT-RICO (Relaxed Threshold Rule Induction from Coverings)
to predict protein secondary structure. The average Q3 accuracy on
the sample datasets using RT-RICO was 80.3%, an improvement
over comparable computational methods. Although this demonstrated
that RT-RICO might be a promising approach for predicting
secondary structure, the algorithm-s computational complexity and
program running time limited its use. Herein a parallelized
implementation of a slightly modified RT-RICO approach is
presented. This new version of the algorithm facilitated the testing of
a much larger dataset of 396 protein domains [2]. Parallelized RTRICO
achieved a Q3 score of 74.6%, which is higher than the
consensus prediction accuracy of 72.9% that was achieved for the
same test dataset by a combination of four secondary structure
prediction methods [2].
Abstract: The study analyzed the risk and returns of commercial-property in Southwestern Nigeria and selected stocksmarket investment between 2000 and 2009; compared the inflation hedging characteristics and diversification potentials of investing in commercial-property and selected stock- market investment. Primary data were collected on characteristics, rental and capital values of commercial- properties from their property managers through the use of questionnaire. Secondary data on stock prices and dividends on banking, insurance and conglomerates sectors were sourced from the Nigerian Stock Exchange (2000-2009). The result showed that average return on all the selected stock- investments was higher than that of commercial-property. As regards risk, commercial-property indicated lower risk, compared to stocks. Also the stock-investment had better inflation hedging capacity than commercial-properties; combination of both had diversification potentials. The study concluded that stock-market investment offered attractive higher return than commercial-property although with higher risk and there could be diversification benefits in combining commercial-property with stock- investment.
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.
Abstract: The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on 'Intelligent agents' another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.
Abstract: Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.
Abstract: In this work, thermoelastic damping effect on the hemi- spherical shells is investigated. The material is selected silicon, and heat conduction equation for thermal flow is solved to obtain the temperature profile in which bending approximation with inextensional assumption of the model. Using the temperature profile, eigen-value analysis is performed to get the natural frequencies of hemispherical shells. Effects of mode numbers, radii and radial thicknesses of the model on the natural frequencies are analyzed in detail. Furthermore, the quality factor (Q-factor) is defined, and discussed for the ring and hemispherical shell.
Abstract: This paper presents methodologies for developing an
intelligent CAD system assisting in analysis and design of
reconfigurable special machines. It describes a procedure for
determining feasibility of utilizing these machines for a given part
and presents a model for developing an intelligent CAD system. The
system analyzes geometrical and topological information of the given
part to determine possibility of the part being produced by
reconfigurable special machines from a technical point of view. Also
feasibility of the process from a economical point of view is
analyzed. Then the system determines proper positioning of the part
considering details of machining features and operations needed.
This involves determination of operation types, cutting tools and the
number of working stations needed. Upon completion of this stage
the overall layout of the machine and machining equipment required
are determined.
Abstract: Variable speed drives are growing and varying. Drives expanse depend on progress in different part of science like power system, microelectronic, control methods, and so on. Artificial intelligent contains hard computation and soft computation. Artificial intelligent has found high application in most nonlinear systems same as motors drive. Because it has intelligence like human but there are no sentimental against human like angriness and.... Artificial intelligent is used for various points like approximation, control, and monitoring. Because artificial intelligent techniques can use as controller for any system without requirement to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and reliability of drives increase and volume, weight and cost of them decrease.
Abstract: The stability of Newtonian and Non-Newtonian extending films under local or global heating or cooling conditions are considered. The thickness-averaged mass, momentum and energy equations with convective and radiative heat transfer are derived, both for Newtonian and non-Newtonian fluids (Maxwell, PTT and Giesekus models considered). The stability of the system is explored using either eigenvalue analysis or transient simulations. The results showed that the influence of heating and cooling on stability strongly depends on the magnitude of the Peclet number. Examples of stabilization or destabilization of heating or cooling are shown for Pe
Abstract: A procedure for the preparation of clarified Pawpaw
Juice was developed. About 750ml Pawpaw pulp was measured into
2 measuring cylinders A & B of capacity 1 litre heated to 400C,
cooled to 200C. 30mls pectinase was added into cylinder A, while
30mls distilled water was added into cylinder B. Enzyme treated
sample (A) was allowed to digest for 5hours after which it was heated
to 900C for 15 minutes to inactivate the enzyme. The heated sample
was cooled and with the aid of a mucillin cloth the pulp was filtered
to obtain the clarified pawpaw juice. The juice was filled into 100ml
plastic bottles, pasteurized at 950C for 45 minutes, cooled and stored
at room temperature. The sample treated with 30mls distilled water
also underwent the same process. Freshly pasteurized sample was
analyzed for specific gravity, titratable acidity, pH, sugars and
ascorbic acid. The remaining sample was then stored for 2 weeks and
the above analyses repeated. There were differences in the results of
the freshly pasteurized samples and stored sample in pH and ascorbic
acid levels, also sample treated with pectinase yielded higher
volumes of juice than that treated with distilled water.
Abstract: Phishing, or stealing of sensitive information on the
web, has dealt a major blow to Internet Security in recent times. Most
of the existing anti-phishing solutions fail to handle the fuzziness
involved in phish detection, thus leading to a large number of false
positives. This fuzziness is attributed to the use of highly flexible and
at the same time, highly ambiguous HTML language. We introduce a
new perspective against phishing, that tries to systematically prove,
whether a given page is phished or not, using the corresponding
original page as the basis of the comparison. It analyzes the layout of
the pages under consideration to determine the percentage distortion
between them, indicative of any form of malicious alteration. The
system design represents an intelligent system, employing dynamic
assessment which accurately identifies brand new phishing attacks
and will prove effective in reducing the number of false positives.
This framework could potentially be used as a knowledge base, in
educating the internet users against phishing.
Abstract: Fermented cassava flours (lafun) sold in Ogun and Oyo
States of Nigeria were collected from 10 markets for a period of two
months and analysed to determine their safety status. The presence of
trace metals was due to high vehicular movement around the drying
sites and markets. Cyanide and moisture contents of samples were
also determined to assess the adequacy of fermentation and drying.
The result showed that sample OWO was found to have the highest
amount of 16.02±0.12mg/kg cyanide while the lowest was found in
sample OJO with 10.51±0.10mg/kg. The results also indicated that
sample TVE had the highest moisture content of 18.50±0.20% while
sample OWO had the lowest amount of 12.46±0.47%. Copper and
lead levels were found to be highest in TVE with values 28.10mg/kg
and 1.1mg/kg respectively, while sample BTS had the lowest values
of 20.6mg/kg and 0.05mg/kg respectively. High value of cyanide
indicated inadequate fermentation.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.
Abstract: Optimization of filter banks based on the knowledge of input statistics has been of interest for a long time. Finite impulse response (FIR) Compaction filters are used in the design of optimal signal adapted orthonormal FIR filter banks. In this paper we discuss three different approaches for the design of interpolated finite impulse response (IFIR) compaction filters. In the first method, the magnitude squared response satisfies Nyquist constraint approximately. In the second and third methods Nyquist constraint is exactly satisfied. These methods yield FIR compaction filters whose response is comparable with that of the existing methods. At the same time, IFIR filters enjoy significant saving in the number of multipliers and can be implemented efficiently. Since eigenfilter approach is used here, the method is less complex. Design of IFIR filters in the least square sense is presented.
Abstract: Medical negligence disputes in Malaysia are mainly resolved through litigation by using the tort system. The tort system, being adversarial in nature has subjected parties to litigation hazards such as delay, excessive costs and uncertainty of outcome. The dissatisfaction of the tort system in compensating medically injured victims has created various alternatives to litigation. Amongst them is the implementation of a no-fault compensation system which would allow compensation to be given without the need of proving fault on the medical personnel. Instead, the community now bears the burden of compensating and at the end, promotes collective responsibility. For Malaysia, introducing a no-fault system would provide a tempting solution and may ultimately, achieve justice for the medical injured victims. Nevertheless, such drastic change requires a great deal of consideration to determine the suitability of the system and whether or not it will eventually cater for the needs of the Malaysian population
Abstract: In this paper a new control strategy based on Brain
Emotional Learning (BEL) model has been introduced. A modified
BEL model has been proposed to increase the degree of freedom,
controlling capability, reliability and robustness, which can be
implemented in real engineering systems.
The performance of the proposed BEL controller has been
illustrated by applying it on different nonlinear uncertain systems,
showing very good adaptability and robustness, while maintaining
stability.
Abstract: The consumption of lactose in acid cheese whey
anaerobic fermentation process under fed-batch conditions was
studied. During fermentation for 100 hours the biogas production
(CO2 and CH4) was analyzed online. Among the standard analyses
FT-IR spectroscopy was used to follow the consumption of lactose by
bacteria. The absorption bands at 990, 894 and 787 cm-1 in the 2nd
derivative spectra were shown to be characteristic for lactose and
were used to follow the lactose conversion. It was shown that acid
cheese whey lactose was converted by bacteria in first 7 hours. In the
spectra of 17, 18 and 95 hour fermentation samples lactose was not
identified and these results correlated with the HPLC data.
Abstract: Web intelligence, if made personal, can fuel the process of building communications around the interests and preferences of each individual customer or prospect, by providing specific behavioral insights about each individual. To become fully efficient, Web intelligence must reach a stage of a high-level maturity, passing throughout a process that involves five steps: (1) Web site analysis; (2) Web site and advertising optimization; (3) Segment targeting; (4) Interactive marketing (online only); and (5) Interactive marketing (online and offline). Discussing these steps in detail, the paper uncovers the real gold mine that is personal-level Web intelligence.
Abstract: A Watson-Crick automaton is recently introduced as a
computational model of DNA computing framework. It works on
tapes consisting of double stranded sequences of symbols. Symbols
placed on the corresponding cells of the double-stranded sequences are
related by a complimentary relation. In this paper, we investigate a
variation of Watson-Crick automata in which both heads read the tape
in reverse directions. They are called reverse Watson-Crick finite
automata (RWKFA). We show that all of following four classes, i.e.,
simple, 1-limited, all-final, all-final and simple, are equal to
non-restricted version of RWKFA.
Abstract: Leonotisleonurus a shrub indigenous to Southern
Africa is widely used in traditional medicine to treat a variety of
conditions ranging from skin diseases and cough to epileptic fits and
‘heart problems’. Studies on the aqueous extract of the leaves have
indicated cycloxegenase enzyme inhibitory activity and an
antihypertensive effect.
Five methanol leaf extract fractions (MLEa - MLEe) of L.
leonurus were tested on anaesthetized normotensive male Wistar rats
(AWR) and isolated perfused working rat hearts (IWH). Fraction
MLEc (0.01mg/kg – 0.05mg/kg) induced significant increases in BP
and HR in AWR and positive chronotropic and inotropic effects in
IWH (1.0mg/ml – 5.0mg/ml). Pre-administration of atenolol
(2.0mg/kg) and prazosin (60μg/kg) significantly inhibited MLEc
effect on HR and MAP respectively in vivo, while atenolol
(7.0mg/ml) pre-perfusion significantly inhibited MLEc effect in vitro.
The hypertensive effect of MLEc is probably via β1agonism.
Results also indicate the presence of multiple cardioactive
compounds in L. leonurus.