Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: The electric power industry is currently undergoing an unprecedented reform. One of the most exciting and potentially profitable recent developments is increasing usage of artificial intelligence techniques. The intention of this paper is to give an overview of using neural network (NN) techniques in power systems. According to the growth rate of NNs application in some power system subjects, this paper introduce a brief overview in fault diagnosis, security assessment, load forecasting, economic dispatch and harmonic analyzing. Advantages and disadvantages of using NNs in above mentioned subjects and the main challenges in these fields have been explained, too.
Abstract: A number of previous studies were rarely considered
the effects of transient non-uniform balloon expansion on evaluation
of the properties and behaviors of stents during stent expansion, nor
did they determine parameters to maximize the performances driven
by mechanical characteristics. Therefore, in order to fully understand
the mechanical characteristics and behaviors of stent, it is necessary to
consider a realistic modeling of transient non-uniform balloon-stent
expansion. The aim of the study is to propose design parameters
capable of improving the ability of vascular stent through a
comparative study of seven commercial stents using finite element
analyses of a realistic transient non-uniform balloon-stent expansion
process. In this study, seven representative commercialized stents were
evaluated by finite element (FE) analysis in terms of the criteria based
on the itemized list of Food and Drug Administration (FDA) and
European Standards (prEN). The results indicate that using stents
composed of opened unit cells connected by bend-shaped link
structures and controlling the geometrical and morphological features
of the unit cell strut or the link structure at the distal ends of stent may
improve mechanical characteristics of stent. This study provides a
better method at the realistic transient non-uniform balloon-stent
expansion by investigating the characteristics, behaviors, and
parameters capable of improving the ability of vascular stent.
Abstract: Improving the reactive power and voltage profile of a
distribution substation is investigated in this paper. The purpose is to
properly determination of the shunt capacitors on/off status and
suitable tap changer (TC) position of a substation transformer. In
addition, the limitation of secondary bus voltage, the maximum
allowable number of switching operation in a day for on load tap
changer and on/off status of capacitors are taken into account. To
achieve these goals, an artificial neural network (ANN) is designed to
provide preliminary scheduling. Input of ANN is active and reactive
powers of transformer and its primary and secondary bus voltages.
The output of ANN is capacitors on/off status and TC position. The
preliminary schedule is further refined by fuzzy dynamic
programming in order to reach the final schedule. The operation of
proposed method in Q/V improving is compared with the results
obtained by operator operation in a distribution substation.
Abstract: This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.
Abstract: Nuclear matrix protein 22 (NMP22) is a FDA approved
biomarker for bladder cancer. The objective of this study is to develop
a simple NMP22 immumosensor (NMP22-IMS) for accurate
measurement of NMP22. The NMP22-IMS was constructed with
NMP22 antibody immobilized on screen-printed carbon electrodes.
The construction procedures and antibody immobilization are simple.
Results showed that the NMP22-IMS has an excellent (r2³0.95)
response range (20 – 100 ng/mL). In conclusion, a simple and reliable
NMP22-IMS was developed, capable of precisely determining urine
NMP22 level.
Abstract: In recent years application of natural antimicrobials
instead of conventional ones, due to their hazardous effects on health,
has got serious attentions. On the basis of the results of different
studies, chitosan, a natural bio-degradable and non-toxic
biopolysaccharide derived from chitin, has potential to be used as a
natural antimicrobial. Chitosan has exhibited high antimicrobial
activity against a wide variety of pathogenic and spoilage
microorganisms, including fungi, and Gram-positive and Gramnegative
bacteria. The antimicrobial action is influenced by intrinsic
factors such as the type of chitosan, the degree of chitosan
polymerization and extrinsic factors such as the microbial organism,
the environmental conditions and presence of the other components.
The use of chitosan in food systems should be based on sufficient
knowledge of the complex mechanisms of its antimicrobial mode of
action. In this article we review a number of studies on the
investigation of chitosan antimicrobial properties and application of
them in culture and food mediums.
Abstract: According to FDA (Food and Drug Administration of the United States), vinegar is definedas a sour liquid containing at least 4 grams acetic acid in 100 cubic centimeter (4% solution of acetic acid) of solution that is produced from sugary materials by alcoholic fermentation. In the base of microbial starters, vinegars could be contained of more than 50 types of volatile and aromatic substances that responsible for their sweet taste and smelling. Recently the vinegar industry has a great proportion in agriculture, food and microbial biotechnology. The acetic acid bacteria are from the family Acetobacteraceae. Regarding to the latest version of Bergy-s Mannual of Systematic Bacteriology that has categorized bacteria in the base of their 16s RNA differences, the most important acetic acid genera are included Acetobacter (genus I), Gluconacetobacter (genus VIII) and Gluconobacter (genus IX). The genus Acetobacter that is primarily used in vinegar manufacturing plants is a gram negative, obligate aerobe coccus or rod shaped bacterium with the size 0.6 - 0.8 X 1.0 - 4.0 μm, nonmotile or motile with peritrichous flagella and catalase positive – oxidase negative biochemically. Some strains are overoxidizer that could convert acetic acid to carbon dioxide and water.In this research one Acetobacter native strain with high acetic acid productivity was isolated from Iranian white – red cherry. We used two specific culture media include Carr medium [yeast extract, 3%; ethanol, 2% (v/v); bromocresol green, 0.002%; agar, 2% and distilled water, 1000 ml], Frateur medium [yeast extract, 10 g/l; CaCO3, 20 g/l; ethanol, 20 g/l; agar, 20 g/l and distilled water, 1000 ml] and an industrial culture medium. In addition to high acetic acid production and high growth rate, this strain had a good tolerance against ethanol concentration that was examined using modified Carr media with 5%, 7% and 9% ethanol concentrations. While the industrial strains of acetic acid bacteria grow in the thermal range of 28 – 30 °C, this strain was adapted for growth in 34 – 36 °C after 96 hours incubation period. These dramatic characteristics suggest a potential biotechnological strain in production of cherry vinegar with a sweet smell and different nutritional properties in comparison to recent vinegar types. The lack of growth after 24, 48 and 72 hours incubation at 34 – 36 °C and the growth after 96 hours indicates a good and fast thermal flexibility of this strain as a significant characteristic of biotechnological and industrial strains.
Abstract: The presence of heavy metals in the environment
could constitute a hazard to food security and public health. These
can be accumulated in aquatic animals such as fish. Samples of four
popular brands of canned fish in the Iranian market (yellowfin tuna,
common Kilka, Kawakawa and longtail tuna) were analyzed for level
of Cr after wet digestion with acids using graphite furnace atomic
absorption spectrophotometry. The mean concentrations for Cr in the
different brands were: 2.57, 3.24, 3.16 and 1.65 μg/g for brands A, B,
C and D respectively. Significant differences were observed in the Cr
levels between all of the different brands of canned fish evaluated in
this study. The Cr concentrations for the varieties of canned fishes
were generally within the FAO/WHO, U.S. FDA and U.S. EPA
recommended limits for fish.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: Bone growth factors, such as Bone Morphogenic
Protein-2 (BMP-2) have been approved by the FDA to replace grafting for some surgical interventions, but the high dose requirement limits its use in patients. Noggin, an extracellular protein, blocks the effect of BMP-2 by binding to BMP. Preventing
the BMP-2/noggin interaction will help increase the free
concentration of BMP-2 and therefore should enhance its efficacy to
induce bone formation. The work presented here involves
computational design of novel small molecule inhibitory agents of BMP-2/noggin interaction, based on our current understanding of
BMP-2, and its known putative ligands (receptors and antagonists). A
successful acquisition of such an inhibitory agent of BMP-2/noggin interaction would allow clinicians to reduce the dose required of
BMP-2 protein in clinical applications to promote osteogenesis. The
available crystal structures of the BMPs, its receptors, and the binding partner noggin were analyzed to identify the critical residues
involved in their interaction. In presenting this study, LUDI de novo design method was utilized to perform virtual screening of a large
number of compounds from a commercially available library against the binding sites of noggin to identify the lead chemical compounds
that could potentially block BMP-noggin interaction with a high specificity.
Abstract: In this paper an alternative visualisation approach of
the wake behind different vehicle body shapes with simplified and
fully-detailed underbody has been proposed and analysed. This
allows for a more clear distinction among the different wake regions.
This visualisation is based on a transformation of the cartesian
coordinates of a chosen wake plane to polar coordinates, using as
filter velocities lower than the freestream. This transformation
produces a polar wake plot that enables the division and
quantification of the wake in a number of sections. In this paper,
local drag has been used to visualise the drag contribution of the flow
by the different sections. Visually, a balanced wake can be observed
by the concentric behaviour of the polar plots. Alternatively,
integration of the local drag of each degree section as a ratio of the
total local drag yields a quantifiable approach of the wake uniformity,
where different sections contribute equally to the local drag, with the
exception of the wheels.
Abstract: In this work, study the location of interface in a stirred vessel with Rushton impeller by computational fluid dynamic was presented. To modeling rotating the impeller, sliding mesh (SM) technique was used and standard k-ε model was selected for turbulence closure. Mean tangential, radial and axial velocities and also turbulent kinetic energy (k) and turbulent dissipation rate (ε) in various points of tank was investigated. Results show sensitivity of system to location of interface and radius of 7 to 10cm for interface in the vessel with existence characteristics cause to increase the accuracy of simulation.
Abstract: In this work study the location of interface in a stirred vessel with a Concave impeller by computational fluid dynamic was presented. To modeling rotating the impeller, sliding mesh (SM) technique was used and standard k-ε model was selected for turbulence closure. Mean tangential, radial and axial velocities and also turbulent kinetic energy (k) and turbulent dissipation rate (ε) in various points of tank was investigated. Results show sensitivity of system to location of interface and radius of 7 to 10cm for interface in the vessel with existence characteristics cause to increase the accuracy of simulation.
Abstract: It is a one-sided hypothesis testing process for assessing bioequivalence. Bootstrap and modified large-sample(MLS) methods are considered to study individual bioequivalence(IBE), type I error and power of hypothesis tests are simulated and compared with FDA(2001). The results show that modified large-sample method is equivalent to the method of FDA(2001) .
Abstract: Gold passbook is an investing tool that is especially
suitable for investors to do small investment in the solid gold. The gold
passbook has the lower risk than other ways investing in gold, but its
price is still affected by gold price. However, there are many factors
can cause influences on gold price. Therefore, building a model to
predict the price of gold passbook can both reduce the risk of
investment and increase the benefits. This study investigates the
important factors that influence the gold passbook price, and utilize
the Group Method of Data Handling (GMDH) to build the predictive
model. This method can not only obtain the significant variables but
also perform well in prediction. Finally, the significant variables of
gold passbook price, which can be predicted by GMDH, are US dollar
exchange rate, international petroleum price, unemployment rate,
whole sale price index, rediscount rate, foreign exchange reserves,
misery index, prosperity coincident index and industrial index.
Abstract: Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.