Abstract: The automatic construction of large, high-resolution
image vistas (mosaics) is an active area of research in the fields of
photogrammetry [1,2], computer vision [1,4], medical image
processing [4], computer graphics [3] and biometrics [8]. Image
stitching is one of the possible options to get image mosaics. Vista
Creation in image processing is used to construct an image with a
large field of view than that could be obtained with a single
photograph. It refers to transforming and stitching multiple images
into a new aggregate image without any visible seam or distortion in
the overlapping areas. Vista creation process aligns two partial
images over each other and blends them together. Image mosaics
allow one to compensate for differences in viewing geometry. Thus
they can be used to simplify tasks by simulating the condition in
which the scene is viewed from a fixed position with single camera.
While obtaining partial images the geometric anomalies like rotation,
scaling are bound to happen. To nullify effect of rotation of partial
images on process of vista creation, we are proposing rotation
invariant vista creation algorithm in this paper. Rotation of partial
image parts in the proposed method of vista creation may introduce
some missing region in the vista. To correct this error, that is to fill
the missing region further we have used image inpainting method on
the created vista. This missing view regeneration method also
overcomes the problem of missing view [31] in vista due to cropping,
irregular boundaries of partial image parts and errors in digitization
[35]. The method of missing view regeneration generates the missing
view of vista using the information present in vista itself.
Abstract: The theatre-auditorium under investigation following
the highly reflective characteristics of materials used in it (marble,
painted wood, smooth plaster, etc), architectural and structural
features of the Protocol and its intended use (very multifunctional:
Auditorium, theatre, cinema, musicals, conference room) from the
analysis of the statement of fact made by the acoustic simulation
software Ramsete and supported by data obtained through a
campaign of acoustic measurements of the state of fact made on the
spot by a Fonomet Svantek model SVAN 957, appears to be
acoustically inadequate. After the completion of the 3D model
according to the specifications necessary software used forecast in
order to be recognized by him, have made three simulations, acoustic
simulation of the state of and acoustic simulation of two design
solutions.
Improved noise characteristics found in the first design solution,
compared to the state in fact consists therefore in lowering
Reverberation Time that you turn most desirable value, while the
Indicators of Clarity, the Baricentric Time, the Lateral Efficiency,
Ratio of Low Tmedia BR and defined the Speech Intelligibility
improved significantly. Improved noise characteristics found instead
in the second design solution, as compared to first design solution, is
finally mostly in a more uniform distribution of Leq and in lowering
Reverberation Time that you turn the optimum values. Indicators of
Clarity, and the Lateral Efficiency improve further but at the expense
of a value slightly worse than the BR. Slightly vary the remaining
indices.
Abstract: In the present study, the oleaginous fungus
Mortierella alpina CBS 754.68 was screened for arachidonic
acidproduction using inexpensive agricultural by-products as
substrate. Four oilcakes were analysed to choose the best substrate
among them. Sunflower oilcake was the most effective substrate for
ARA production followed by soybean, colza and olive oilcakes. In
the next step, seven variables including substrate particle size,
moisture content, time, temperature, yeast extract supply, glucose
supply and glutamate supply were surveyed and effective variables
for ARA production were determined using a Plackett-Burman
screening design. Analysis results showed that time (12 days),
substrate particle size (1-1.4 mm) and temperature (20ºC) were the
most effective variables for the highest level of ARA production
respectively.
Abstract: In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple
feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated
to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity.
These same results were found in psychiatric studies of human character recognition.
Abstract: In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.
Abstract: Rhizopus oligosporus was used in the present study
for the production of protease enzyme under SSF. Sunflower meal
was used as by-product of oil industry incorporated with organic salts
was employed for the production of protease enzyme. The main
purpose of the present was to study different parameters of protease
productivity, its yields and to optimize basal fermentation conditions.
The optimal conditions found for protease production using
sunflower meal as a substrate in the present study were inoculum size
(1%), substrate (Sunflower meal), substrate concentration (20 g), pH
(3), cultivation period (72 h), incubation temperature (35oC),
substrate to diluent-s ratio (1:2) and tween 81 (1 mL). The maximum
production of protease in the presence of cheaper substrate at low
concentration and stability at acidic pH, these characteristics make
the strain and its enzymes useful in different industry.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Epstein-Barr virus (EBV) is implicated in the pathogenesis of the endemic Burkitt-s lymphoma (BL). The EBVpositive BL-derived cell lines initially maintain the original tumor phenotype of EBV infection (latency I, LatI), but most of them drift toward a lymphoblast phenotype of EBV latency III (LatIII) during in vitro culturing. The aim of the present work was to characterize the B-cell subsets in EBV-positive BL cell lines and to verify whether a particular cell subset correlates with the type of EBV infection. The phenotype analysis of two EBV-negative and eleven EBV-positive (three of LatI and eight of LatIII) BL cell lines was performed by polychromatic flow cytomery, based on expression pattern of CD19, CD10, CD38, CD27, and CD5 markers. Two cell subsets, CD19+CD10+ and CD19+CD10-, were defined in LatIII BL cell lines. In both subsets, the CD27 and CD5 cell surface expression was detected in a proportion of the cells.
Abstract: Iran has diverse climates and each have established distinct properties in their area. The extent and intensity of climatic factors effects on the lives of people living in various regions of Iran is so great that it cannot be simply ignored. In a large part of Iran known as the Central Plateau there is no precipitation for more than half of the year and dry weather and scarcity of fresh water pose an ever present problem for the people of these regions while in north of Iran upon the southern shores of the Caspian Sea the people face 80% humidity caused by the sea and 2 meters of annual precipitation. This article tries to review the past experiences of local architecture of Iran-s various regions so that they can be used to reshape and redirect the urban areas and structure of Iran-s current cities to provide environmental comfort by minimum use of fossil fuels.
Abstract: Emotions are related with learning processes and
physiological signals can be used to detect them for the
personalization of learning resources and to control the pace of
instruction. A model of relevant emotions has been developed, where
specific combinations of emotions and cognition processes are
connected and integrated with the concept of 'flow', in order to
improve learning. The cardiac pulse is a reliable signal that carries
useful information about the subject-s emotional condition; it is
detected using a classroom chair adapted with non invasive EMFi
sensor and an acquisition system that generates a ballistocardiogram
(BCG), the signal is processed by an algorithm to obtain
characteristics that match a specific emotional condition. The
complete chair system is presented in this work, along with a
framework for the personalization of learning resources.
Abstract: This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
Abstract: To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).
Abstract: This paper presents an analytical method to solve
governing consolidation parabolic partial differential equation (PDE)
for inelastic porous Medium (soil) with consideration of variation of
equation coefficient under cyclic loading. Since under cyclic loads,
soil skeleton parameters change, this would introduce variable
coefficient of parabolic PDE. Classical theory would not rationalize
consolidation phenomenon in such condition. In this research, a
method based on time space mapping to a virtual time space along
with superimposing rule is employed to solve consolidation of
inelastic soils in cyclic condition. Changes of consolidation
coefficient applied in solution by modification of loading and
unloading duration by introducing virtual time. Mapping function is
calculated based on consolidation partial differential equation results.
Based on superimposing rule a set of continuous static loads in
specified times used instead of cyclic load. A set of laboratory
consolidation tests under cyclic load along with numerical
calculations were performed in order to verify the presented method.
Numerical solution and laboratory tests results showed accuracy of
presented method.
Abstract: The lecture represents significant advances in
understanding of the transfer processes mechanism in turbulent
separated flows. Based upon experimental data suggesting the
governing role of generated local pressure gradient that takes place in
the immediate vicinity of the wall in separated flow as a result of
intense instantaneous accelerations induced by large-scale vortex
flow structures similarity laws for mean velocity and temperature and
spectral characteristics and heat and mass transfer law for turbulent
separated flows have been developed. These laws are confirmed by
available experimental data. The results obtained were employed for
analysis of heat and mass transfer in some very complex processes
occurring in technological applications such as impinging jets, heat
transfer of cylinders in cross flow and in tube banks, packed beds
where processes manifest distinct properties which allow them to be
classified under turbulent separated flows. Many facts have got an
explanation for the first time.
Abstract: the objective of this study is to measure the levels of
cellulas activity of ostrich GI microorganisms, and comparing it with
the levels of cellulas activity of rumen-s microorganisms, and also to
estimate the probability of increasing enzyme activity with injecting
different dosages (30%, 50% and 70%) of pure anaerobic goat rumen
fungi. The experiment was conducted in laboratory and under a
complete anaerobic condition (in vitro condition). 40 ml of
“CaldWell" medium and 1.4g wheat straw were placed in incubator
for an hour. The cellulase activity of ostrich microorganisms was
compared with other treatments, and then different dosages (30%,
50% and 70%) of pure anaerobic goat rumen fungi were injected to
ostrich microorganism-s media. Due to the results, cattle and goat
with 2.13 and 2.08 I.U (international units) respectively showed the
highest activity and ostrich with 0.91 (I.U) had the lowest cellulose
activity (p < 0.05). Injecting 30% and 50% of anaerobic fungi had no
significant incensement in enzyme activity, but with injecting 70% of
rumen fungi to ostrich microorganisms culture a significant increase
was observed 1.48 I.U. (p < 0.05).
Abstract: The presented work is motivated by a french law regarding nuclear waste management. In order to avoid the limitation coming with the usage of the existing scenario codes, as COSI, VISION or FAMILY, the Core Library for Advance Scenario Simulation (CLASS) is being develop. CLASS is an open source tool, which allows any user to simulate an electronuclear scenario. The main CLASS asset, is the possibility to include any type of reactor, even a complitely new concept, through the generation of its ACSII evolution database. In the present article, the CLASS working basis will be presented as well as a simple exemple in order to show his potentiel. In the considered exemple, the effect of the transmutation will be assessed on Minor Actinide Inventory produced by PWR reactors.
Abstract: The demand for autonomous resource
management for distributed systems has increased in recent
years. Distributed systems require an efficient and powerful
communication mechanism between applications running on
different hosts and networks. The use of mobile agent
technology to distribute and delegate management tasks
promises to overcome the scalability and flexibility limitations
of the currently used centralized management approach. This
work proposes a multiagent system that adopts mobile agents
as a technology for tasks distribution, results collection, and
management of resources in large-scale distributed systems. A
new mobile agent-based approach for collecting results from
distributed system elements is presented. The technique of
artificial intelligence based on intelligent agents giving the
system a proactive behavior. The presented results are based
on a design example of an application operating in a mobile
environment.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: Process planning and production scheduling play
important roles in manufacturing systems. In this paper a multiobjective
mixed integer linear programming model is presented for
the integrated planning and scheduling of multi-product. The aim is
to find a set of high-quality trade-off solutions. This is a
combinatorial optimization problem with substantially large solution
space, suggesting that it is highly difficult to find the best solutions
with the exact search method. To account for it, a PSO-based
algorithm is proposed by fully utilizing the capability of the
exploration search and fast convergence. To fit the continuous PSO
in the discrete modeled problem, a solution representation is used in
the algorithm. The numerical experiments have been performed to
demonstrate the effectiveness of the proposed algorithm.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.