Abstract: The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.
Abstract: In this paper, we study the knapsack sharing problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of a tree search for optimally solving the problem. The used method combines two complementary phases: a reduction interval search phase and a branch and bound procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for decomposing the problem into a series of knapsack problems. Second, the tree search procedure is applied in order to attain a set of optimal capacities characterizing the knapsack problems. Finally, the performance of the proposed optimal algorithm is evaluated on a set of instances of the literature and its runtime is compared to the best exact algorithm of the literature.
Abstract: Animated graph gives some good impressions in
presenting information. However, not many people are able to produce it because the process of generating an animated graph requires some technical skills. This work presents Content
Management System with Animated Graph (CMS-AG). It is a webbased system enabling users to produce an effective and interactive
graphical report in a short time period. It allows for three levels of user authentication, provides update profile, account management, template management, graph management, and track changes. The system development applies incremental development approach, object-oriented concepts and Web programming technologies. The design architecture promotes new technology of reporting. It also helps user cut off unnecessary expenses, save time and learn new things on different levels of users. In this paper, the developed system is described.
Abstract: The double difference sequence space I2 (M, of fuzzy numbers for both 1 < p < oo and 0 < p < 1, is introduced. Some general properties of this sequence space are studied. Some inclusion relations involving this sequence space are obtained.
Abstract: Experiments were carried out on the survival and growth of Rasbora daniconius, Puntius ticto and Puntius conchonius. The motivation of the study was to obtain information for growing the fish on a commercial scale for their use as biological control agents against mosquito larvae. The effects of temperature, total hardness, DO, pH and feed on the growth of fish were also investigated. Excessive value of total hardness was found because very rich calcium ion is present in Chitrakoot area. There was significant increases in growth rates of fish as temperature was increased from 280C to 300C. Further increases in temperature up to 320C, did not further affect growth. The positive and highly significant correlations 0.991488, 0.9581 and 0.9935 were found between length and weight of P. ticto, P. conchonius and R. daniconius respectively. The regression was significant at 5% level of probability.
Abstract: EEG signal is one of the oldest measures of brain
activity that has been used vastly for clinical diagnoses and
biomedical researches. However, EEG signals are highly
contaminated with various artifacts, both from the subject and from
equipment interferences. Among these various kinds of artifacts,
ocular noise is the most important one. Since many applications such
as BCI require online and real-time processing of EEG signal, it is
ideal if the removal of artifacts is performed in an online fashion.
Recently, some methods for online ocular artifact removing have
been proposed. One of these methods is ARMAX modeling of EEG
signal. This method assumes that the recorded EEG signal is a
combination of EOG artifacts and the background EEG. Then the
background EEG is estimated via estimation of ARMAX parameters.
The other recently proposed method is based on adaptive filtering.
This method uses EOG signal as the reference input and subtracts
EOG artifacts from recorded EEG signals. In this paper we
investigate the efficiency of each method for removing of EOG
artifacts. A comparison is made between these two methods. Our
undertaken conclusion from this comparison is that adaptive filtering
method has better results compared with the results achieved by
ARMAX modeling.
Abstract: With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.
Abstract: Although, it is a long time that human know about
the importance of environment in life, but at the last decade of 20
century, the space that was full of hot scientific, collegial and
political were made in environmental challenge, So much that, this
problem not only disarrange the peace and security of life, but also it
has threatened human existence. One of the problems in last years
that are significant for authorities is unsatisfactory achieved results
against of using huge cost for magnificent environmental projects.
This subject leads thinker to this thought that for solving the
environmental problems it is needed new methods include of
sociology, ethics and philosophic, etc. methods apart of technical
affairs. Environment ethics is a new branch of philosophic ethics
discussion that discusses about the ethics relationship between
humans and universe that is around them. By notifying to the above
considered affairs, in today world, necessity of environmental ethics
for environment management is reduplicated. In the following the
article has been focused on environmental ethics role and
environmental management methods and techniques for developing
it.
Abstract: A pilot plant for continuous flow microwave-assisted
chemical reaction combined with microreactors was developed and
water heating tests were conducted for evaluation of the developed
plant. We developed a microwave apparatus having a single
microwave generator that can heat reaction solutions in four reaction
fields simultaneously in order to increase throughput. We also
designed a four-branch waveguide using electromagnetic simulation,
and found that the transmission efficiency at 99%. Finally, we
developed the pilot plant using the developed microwave apparatus
and conducted water heating tests. The temperatures in the respective
reaction fields were controlled within ±1.1 K at 353.2 K. Moreover,
the energy absorption rates by the water were about 90% in the
respective reaction fields, whereas the energy absorption rate was
about 40% when 100 cm3 of water was heated by a commercially
available multimode microwave chemical reactor.
Abstract: The knee bracing steel frame (KBF) is a new kind of energy dissipating frame, which combines excellent ductility and lateral stiffness. In this framing system, a special form of diagonal brace connected to a knee element instead of beam-column joint, is investigated. Recently, a similar system was proposed and named as chevron knee bracing system (CKB) which in comparison with the former system has a better energy absorption characteristic and at the same time retains the elastic nature of the structures. Knee bracing can provide a stiffer bracing system but reduces the ductility of the steel frame. Chevron knee bracing can be employed to provide the desired ductility level for a design. In this article, relation between seismic performance and structural parameters of the two above mentioned systems are investigated and compared. Frames with similar dimensions but various heights in both systems are designed according to Iranian code of practice for seismic resistant design of building, and then based on a non-linear push over static analysis; the seismic parameters such as behavior factor and performance levels are compared.
Abstract: This paper presents the adaptation of the knowledge management model and intellectual capital measurement NOVA to the needs of work or research project must be developed when conducting a program of graduate-level master. Brackets are added in each of the blocks which is represented in the original model NOVA and which allows to represent those involved in each of these.
Abstract: Combining classifiers is a useful method for solving
complex problems in machine learning. The ECOC (Error Correcting
Output Codes) method has been widely used for designing combining
classifiers with an emphasis on the diversity of classifiers. In this
paper, in contrast to the standard ECOC approach in which individual
classifiers are chosen homogeneously, classifiers are selected
according to the complexity of the corresponding binary problem. We
use SATIMAGE database (containing 6 classes) for our experiments.
The recognition error rate in our proposed method is %10.37 which
indicates a considerable improvement in comparison with the
conventional ECOC and stack generalization methods.
Abstract: Heavy metals have bad effects on environment and
soils and it can uptake by natural HAP .natural Hap is an inexpensive
material that uptake large amounts of various heavy metals like Zn
(II) .Natural HAP (N-HAP), extracted from bovine cortical bone ash,
is a good choice for substitution of commercial HAP. Several
experiments were done to investigate the sorption capacity of Zn (II)
to N-HAP in various particles sizes, temperatures, initial
concentrations, pH and reaction times. In this study, the sorption of
Zinc ions from a Zn solution onto HAP particles with sizes of 1537.6
nm and 47.6 nm at three initial pH values of 4.50, 6.00 and 7.50 was
studied. The results showed that better performance was obtained
through a 47.6 nm particle size and higher pH values. The
experimental data were analyzed using Langmuir, Freundlich, and
Arrhenius equations for equilibrium, kinetic and thermodynamic
studies. The analysis showed a maximum adsorption capacity of NHAP
as being 1.562 mmol/g at a pH of 7.5 and small particle size.
Kinetically, the prepared N-HAP is a feasible sorbent that retains Zn
(II) ions through a favorable and spontaneous sorption process.
Abstract: The prediction of transmembrane helical segments
(TMHs) in membrane proteins is an important field in the
bioinformatics research. In this paper, a method based on discrete
wavelet transform (DWT) has been developed to predict the number
and location of TMHs in membrane proteins. PDB coded as 1F88 was
chosen as an example to describe the prediction of the number and
location of TMHs in membrane proteins by using this method. One
group of test data sets that contain total 19 protein sequences was
utilized to access the effect of this method. Compared with the
prediction results of DAS, PRED-TMR2, SOSUI, HMMTOP2.0 and
TMHMM2.0, the obtained results indicate that the presented method
has higher prediction accuracy.
Abstract: The concerns about clean environment and high oil
prices driving forces for the research on alternative fuels. The
research efforts directed towards improving the performance of C.I
engines using vegetable oil as fuel. The paper deals results of
performance of a four stroke, single cylinder C.I. engine by preheated
neat Karanja oil is done from 30
o
C to 100
o
C. The performance of the
engine was studied for a speed range between 1500 to 4000 rpm, with
the engine operated under full load conditions. The performance
parameters considered for comparing are brake specific fuel
consumption, thermal efficiency, brake power, Nox emission of the
engine. The engine offers lower thermal efficiency when it is
powered by preheated neat Karanja oil at higher speed. The power
developed and Nox emission increase with the increase in the fuel
inlet temperature and the specific fuel consumption is higher than
diesel fuel operation at all elevated fuel inlet temperature.
Abstract: Present study summarizes the control of Vibrio
alginolyticus infection in hatchery reared Clownfish, Amphiprion
sebae with the extract of the mangrove plant, Avicennia marina.
Fishes with visible symptoms of hemorrhagic spots were chosen and
the genomic DNA of the causative bacterium was isolated and
sequenced based on 16S rDNA gene. The in vitro assay revealed that
a fraction of A. marina leaf extract elucidated with ethyl acetate:
methanol (6:4) showed a high activity (28 mm) at 125 μg/ml
concentrations. About 4 % of the fraction fed along with live V.
alginolyticus was significantly decreased the cumulative mortality
(P
Abstract: This paper describes a combined mathematicalgraphical
approach for optimum tool path planning in order to
improve machining efficiency. A methodology has been used that
stabilizes machining operations by adjusting material removal rate in
pocket milling operations while keeping cutting forces within limits.
This increases the life of cutting tool and reduces the risk of tool
breakage, machining vibration, and chatter. Case studies reveal the
fact that application of this approach could result in a slight increase
of machining time, however, a considerable reduction of tooling cost,
machining vibration, noise and chatter can be achieved in addition to
producing a better surface finish.
Abstract: For collecting data from all sensor nodes, some
changes in Dynamic Source Routing (DSR) protocol is proposed. At
each hop level, route-ranking technique is used for distributing
packets to different selected routes dynamically. For calculating rank
of a route, different parameters like: delay, residual energy and
probability of packet loss are used. A hybrid topology of
DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path
Routing) is formed, where braided topology is used in different
faulty zones of network. For reducing energy consumption, variant
transmission ranges is used instead of fixed transmission range. For
reducing number of packet drop, a fuzzy logic inference scheme is
used to insert different types of delays dynamically. A rule based
system infers membership function strength which is used to
calculate the final delay amount to be inserted into each of the node
at different clusters.
In braided path, a proposed 'Dual Line ACK Link'scheme is
proposed for sending ACK signal from a damaged node or link to a
parent node to ensure that any error in link or any node-failure
message may not be lost anyway. This paper tries to design the
theoretical aspects of a model which may be applied for collecting
data from any large hanging iron structure with the help of wireless
sensor network. But analyzing these data is the subject of material
science and civil structural construction technology, that part is out
of scope of this paper.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
Abstract: Because of architectural condition and structure application, sometimes mass source and stiffness source are not coincidence, and the structure is irregular. The structure is also might be asymmetric as an asymmetric bracing in plan which leads to unbalance distribution of stiffness or because of unbalance distribution of the mass. Both condition lead to eccentricity and torsion in the structure. The deficiency of ordinary code to evaluate the performance of steel structures against earthquake has been caused designing based on performance level or capacity spectrum be used. By using the mentioned methods it is possible to design a structure that its behavior against different earthquakes be predictive. In this article 5- story buildings with different percentage of asymmetric which is because of stiffness changes and kind of bracing (x and chevron bracing) have been designed. The static and dynamic nonlinear analysis under three acceleration recording has been done. Finally performance level of the structure has been evaluated.