Abstract: The goal of this work is to improve the efficiency and the reliability of the automatic artifact rejection, in particular from the Electroencephalographic (EEG) recordings. Artifact rejection is a key topic in signal processing. The artifacts are unwelcome signals that may occur during the signal acquisition and that may alter the analysis of the signals themselves. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we enhance this technique introducing the Renyi-s entropy. The performance of our method was tested exploiting the Independent Component scalp maps and it was compared to the performance of the method in literature and it showed to outperform it.
Abstract: In the present research, steam cracking of two types of
feedstocks i.e., naphtha and ethane is simulated for Pyrocrack1-1 and
2/2 coil configurations considering two key parameters of coil outlet
temperature (COT) and coil capacity using a radical based kinetic
model. The computer model is confirmed using the industrial data
obtained from Amirkabir Petrochemical Complex. The results are in
good agreement with performance data for naphtha cracking in a
wide range of severity (0.4-0.7), and for ethane cracking on various
conversions (50-70). It was found that Pyrocrack2-2 coil type is an
appropriate choice for steam cracking of ethane at reasonable
ethylene yield while resulting in much lower tube wall temperature
while Pyrocrack1-1 coil type is a proper selection for liquid
feedstocks i.e. naphtha. It can be used for cracking of liquid
feedstocks at optimal ethylene yield whereas not exceeding the
allowable maximum tube temperature.
Abstract: When programming in languages such as C, Java, etc.,
it is difficult to reconstruct the programmer's ideas only from the
program code. This occurs mainly because, much of the programmer's
ideas behind the implementation are not recorded in the code during
implementation. For example, physical aspects of computation such as
spatial structures, activities, and meaning of variables are not required
as instructions to the computer and are often excluded. This makes the
future reconstruction of the original ideas difficult. AIDA, which is a
multimedia programming language based on the cyberFilm model, can
solve these problems allowing to describe ideas behind programs
using advanced annotation methods as a natural extension to
programming. In this paper, a development environment that
implements the AIDA language is presented with a focus on the
annotation methods. In particular, an actual scientific numerical
computation code is created and the effects of the annotation methods
are analyzed.
Abstract: In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.
Abstract: Breast cancer detection techniques have been reported
to aid radiologists in analyzing mammograms. We note that most
techniques are performed on uncompressed digital mammograms.
Mammogram images are huge in size necessitating the use of
compression to reduce storage/transmission requirements. In this
paper, we present an algorithm for the detection of
microcalcifications in the JPEG2000 domain. The algorithm is based
on the statistical properties of the wavelet transform that the
JPEG2000 coder employs. Simulation results were carried out at
different compression ratios. The sensitivity of this algorithm ranges
from 92% with a false positive rate of 4.7 down to 66% with a false
positive rate of 2.1 using lossless compression and lossy compression
at a compression ratio of 100:1, respectively.
Abstract: Many algorithms are available for sorting the unordered elements. Most important of them are Bubble sort, Heap sort, Insertion sort and Shell sort. These algorithms have their own pros and cons. Shell Sort which is an enhanced version of insertion sort, reduces the number of swaps of the elements being sorted to minimize the complexity and time as compared to insertion sort. Shell sort improves the efficiency of insertion sort by quickly shifting values to their destination. Average sort time is O(n1.25), while worst-case time is O(n1.5). It performs certain iterations. In each iteration it swaps some elements of the array in such a way that in last iteration when the value of h is one, the number of swaps will be reduced. Donald L. Shell invented a formula to calculate the value of ?h?. this work focuses to identify some improvement in the conventional Shell sort algorithm. ''Enhanced Shell Sort algorithm'' is an improvement in the algorithm to calculate the value of 'h'. It has been observed that by applying this algorithm, number of swaps can be reduced up to 60 percent as compared to the existing algorithm. In some other cases this enhancement was found faster than the existing algorithms available.
Abstract: Sustainability in rural production system can only be achieved if it can suitably satisfy the local requirement as well as the outside demand with the changing time. With the increased pressure from the food sector in a globalised world, the agrarian economy
needs to re-organise its cultivable land system to be compatible with new management practices as well as the multiple needs of various stakeholders and the changing resource scenario. An attempt has been made to transform this problem into a multi-objective decisionmaking problem considering various objectives, resource constraints and conditional constraints. An interactive fuzzy multi-objective
programming approach has been used for such a purpose taking a
case study in Indian context to demonstrate the validity of the method.
Abstract: Inner class is a specialized class that defined within a
regular outer class. It is used in some programming languages such as
Java to carry out the task which is related to its outer class. The
functional relatedness between inner class and outer class is always
the main concern of defining an inner class. However, excessive use
of inner class could sabotage the class cohesiveness. In addition,
excessive inner class leads to the difficulty of software maintenance
and comprehension. Our research aims at determining the minimum
threshold for the functional relatedness of inner-outer class. Such
minimum threshold is a guideline for removing or relocating the
excessive inner class. Our research provides a feasible way for
software developers to define inner classes which are functionally
related to the outer class.
Abstract: In this paper we present high performance
dynamically allocated multi-queue (DAMQ) buffer schemes for fault
tolerance systems on chip applications that require an interconnection
network. Two virtual channels shared the same buffer space. Fault
tolerant mechanisms for interconnection networks are becoming a
critical design issue for large massively parallel computers. It is also
important to high performance SoCs as the system complexity keeps
increasing rapidly. On the message switching layer, we make
improvement to boost system performance when there are faults
involved in the components communication. The proposed scheme is
when a node or a physical channel is deemed as faulty, the previous
hop node will terminate the buffer occupancy of messages destined
to the failed link. The buffer usage decisions are made at switching
layer without interactions with higher abstract layer, thus buffer
space will be released to messages destined to other healthy nodes
quickly. Therefore, the buffer space will be efficiently used in case
fault occurs at some nodes.
Abstract: Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.
Abstract: In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
Abstract: Hydrodesulfurization (HDS) of dibenzothiophene
(DBT) in a high pressure batch reactor was done at 320 °C on
CoMoS/Al2O3-B2O3 (4, 10, and 16 wt. % of Boria) using nhexadecane
as solvent, dimethyldisulfide (DMDS) in tetradecane as
sulfur agent, and stirring at 1000 rpm. The effects of boria were
investigated by using X-ray diffraction (XRD), Temperature
programmed desorption (TPD) of ammonia, and Brunauer-Emmet-
Teller (BET) experiments. The results showed that the catalyst
prepared with low boria content (4 wt. %) had HDS activity (in
pseudo first order kinetic constant basis) value ~1.45 times higher to
that of CoMoS/Al2O3 catalyst.
Abstract: Tumour suppressors are key participants in the
prevention of cancer. Regulation of their expression through
miRNAs is important for comprehensive translation inhibition of
tumour suppressors and elucidation of carcinogenesis mechanisms.
We studies the possibility of 1521 miRNAs to bind with 873 mRNAs
of human tumour suppressors using RNAHybrid 2.1 and ERNAhybrid
programmes. Only 978 miRNAs were found to be
translational regulators of 812 mRNAs, and 61 mRNAs did not have
any miRNA binding sites. Additionally, 45.9% of all miRNA binding
sites were located in coding sequences (CDSs), 33.8% were located
in 3' untranslated region (UTR), and 20.3% were located in the
5'UTR. MiRNAs binding with more than 50 target mRNAs and
mRNAs binding with several miRNAs were selected. Hsa-miR-5096
had 15 perfectly complementary binding sites with mRNAs of 14
tumour suppressors. These newly indentified miRNA binding sites
can be used in the development of medicines (anti-sense therapies)
for cancer treatment.
Abstract: In this study, the dispersed model is used to predict
gas phase concentration, liquid drop concentration. The venturi
scrubber efficiency is calculated by gas phase concentration. The
modified model has been validated with available experimental data
of Johnstone, Field and Tasler for a range of throat gas velocities,
liquid to gas ratios and particle diameters and is used to study the
effect of some design parameters on collection efficiency.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Abstract: Accounts of language acquisition differ significantly in their treatment of the role of prediction in language learning. In particular, nativist accounts posit that probabilistic learning about words and word sequences has little to do with how children come to use language. The accuracy of this claim was examined by testing whether distributional probabilities and frequency contributed to how well 3-4 year olds repeat simple word chunks. Corresponding chunks were the same length, expressed similar content, and were all grammatically acceptable, yet the results of the study showed marked differences in performance when overall distributional frequency varied. It was found that a distributional model of language predicted the empirical findings better than a number of other models, replicating earlier findings and showing that children attend to distributional probabilities in an adult corpus. This suggested that language is more prediction-and-error based, rather than on abstract rules which nativist camps suggest.
Abstract: In aerospace applications, interactions of airflow with
aircraft structures can result in undesirable structural deformations.
This structural deformation in turn, can be predicted if the natural
modes of the structure are known. This can be achieved through
conventional modal testing that requires a known excitation force in
order to extract these dynamic properties. This technique can be
experimentally complex because of the need for artificial excitation
and it is also does not represent actual operational condition. The
current work presents part of research work that address the practical
implementation of operational modal analysis (OMA) applied to a
cantilevered hybrid composite plate employing single contactless
sensing system via laser vibrometer. OMA technique extracts the
modal parameters based only on the measurements of the dynamic
response. The OMA results were verified with impact hammer modal
testing and good agreement was obtained.
Abstract: The objective of this study is to investigate fire
behaviors, experimentally and numerically, in a scaled version of an
underground station. The effect of ventilation velocity on the fire is
examined. Fire experiments are simulated by burning 10 ml
isopropyl alcohol fuel in a fire pool with dimensions 5cm x 10cm x 4
mm at the center of 1/100 scaled underground station model. A
commercial CFD program FLUENT was used in numerical
simulations. For air flow simulations, k-ω SST turbulence model and
for combustion simulation, non-premixed combustion model are
used. This study showed that, the ventilation velocity is increased
from 1 m/s to 3 m/s the maximum temperature in the station is found
to be less for ventilation velocity of 1 m/s. The reason for these
experimental result lies on the relative dominance of oxygen supply
effect on cooling effect. Without piston effect, maximum temperature
occurs above the fuel pool. However, when the ventilation velocity
increased the flame was tilted in the direction of ventilation and the
location of maximum temperature moves along the flow direction.
The velocities measured experimentally in the station at different
locations are well matched by the CFD simulation results. The
prediction of general flow pattern is satisfactory with the smoke
visualization tests. The backlayering in velocity is well predicted by
CFD simulation. However, all over the station, the CFD simulations
predicted higher temperatures compared to experimental
measurements.
Abstract: Low temperature (LT) is one of the most abiotic
stresses causing loss of yield in wheat (T. aestivum). Four major
genes in wheat (Triticum aestivum L.) with the dominant alleles
designated Vrn–A1,Vrn–B1,Vrn–D1 and Vrn4, are known to have
large effects on the vernalization response, but the effects on cold
hardiness are ambiguous. Poor cold tolerance has restricted winter
wheat production in regions of high winter stress [9]. It was known
that nearly all wheat chromosomes [5] or at least 10 chromosomes of
21 chromosome pairs are important in winter hardiness [15]. The
objective of present study was to clarify the role of each chromosome
in cold tolerance. With this purpose we used 20 isogenic lines of
wheat. In each one of these isogenic lines only a chromosome from
‘Bezostaya’ variety (a winter habit cultivar) was substituted to
‘Capple desprez’ variety. The plant materials were planted in
controlled conditions with 20º C and 16 h day length in moderately
cold areas of Iran at Karaj Agricultural Research Station in 2006-07
and the acclimation period was completed for about 4 weeks in a
cold room with 4º C. The cold hardiness of these isogenic lines was
measured by LT50 (the temperature in which 50% of the plants are
killed by freezing stress).The experimental design was completely
randomized block design (RCBD)with three replicates. The results
showed that chromosome 5A had a major effect on freezing
tolerance, and then chromosomes 1A and 4A had less effect on this
trait. Further studies are essential to understanding the importance of
each chromosome in controlling cold hardiness in wheat.
Abstract: The problem addressed herein is the efficient management of the Grid/Cluster intense computation involved, when the preconditioned Bi-CGSTAB Krylov method is employed for the iterative solution of the large and sparse linear system arising from the discretization of the Modified Helmholtz-Dirichlet problem by the Hermite Collocation method. Taking advantage of the Collocation ma-trix's red-black ordered structure we organize efficiently the whole computation and map it on a pipeline architecture with master-slave communication. Implementation, through MPI programming tools, is realized on a SUN V240 cluster, inter-connected through a 100Mbps and 1Gbps ethernet network,and its performance is presented by speedup measurements included.