Abstract: The main mission of Ezilla is to provide a friendly
interface to access the virtual machine and quickly deploy the high
performance computing environment. Ezilla has been developed by
Pervasive Computing Team at National Center for High-performance
Computing (NCHC). Ezilla integrates the Cloud middleware,
virtualization technology, and Web-based Operating System (WebOS)
to form a virtual computer in distributed computing environment. In
order to upgrade the dataset and speedup, we proposed the sensor
observation system to deal with a huge amount of data in the
Cassandra database. The sensor observation system is based on the
Ezilla to store sensor raw data into distributed database. We adopt the
Ezilla Cloud service to create virtual machines and login into virtual
machine to deploy the sensor observation system. Integrating the
sensor observation system with Ezilla is to quickly deploy experiment
environment and access a huge amount of data with distributed
database that support the replication mechanism to protect the data
security.
Abstract: This paper presents Faults Forecasting System (FFS)
that utilizes statistical forecasting techniques in analyzing process
variables data in order to forecast faults occurrences. FFS is
proposing new idea in detecting faults. Current techniques used in
faults detection are based on analyzing the current status of the
system variables in order to check if the current status is fault or not.
FFS is using forecasting techniques to predict future timing for faults
before it happens. Proposed model is applying subset modeling
strategy and Bayesian approach in order to decrease dimensionality
of the process variables and improve faults forecasting accuracy. A
practical experiment, designed and implemented in Okayama
University, Japan, is implemented, and the comparison shows that
our proposed model is showing high forecasting accuracy and
BEFORE-TIME.
Abstract: The paper presents a part of the results obtained in a
complex research project on Romanian Grey Steppe breed, owner of
some remarkable qualities such as hardiness, longevity, adaptability,
special resistance to ban weather and diseases and included in the
genetic fund (G.D. no. 822/2008.) from Romania.
Following the researches effectuated, we identified alleles of six
loci, codifying the six types of major milk proteins: alpha-casein S1
(α S1-cz); beta-casein (β-cz); kappa-casein (K-cz); beta-lactoglobulin
(β-lg); alpha-lactalbumin (α-la) and alpha-casein S2 (α S2-cz). In
system αS1-cz allele αs1-Cn B has the highest frequency (0.700), in
system β-cz allele β-Cn A2 ( 0.550 ), in system K-cz allele k-CnA2 (
0.583 ) and heterozygote genotype AB ( 0.416 ) and BB (0.375), in
system β-lg allele β-lgA1 has the highest frequency (0.542 ) and
heterozygote genotype AB ( 0.500 ), in system α-la there is
monomorphism for allele α-la B and similarly in system αS2-cz for
allele αs2-Cn A.
The milk analysis by the isoelectric focalization technique (I.E.F.)
allowed the identification of a new allele for locus αS1-casein, for two
of the individuals under analysis, namely allele called αS1-casein
IRV. When experiments were repeated, we noticed that this is not a
proteolysis band and it really was a new allele that has not been
registered in the specialized literature so far. We identified two
heterozygote individuals, carriers of this allele, namely: BIRV and
CIRV. This discovery is extremely important if focus is laid on the
national genetic patrimony.
Abstract: The draw solute separation process in Forward
Osmosis desalination was simulated in Aspen Plus chemical process
modeling software, to estimate the energy consumption and compare
it with other desalination processes, mainly the Reverse Osmosis
process which is currently most prevalent. The electrolytic chemistry
for the system was retrieved using the Elec – NRTL property method
in the Aspen Plus database. Electrical equivalent of energy required
in the Forward Osmosis desalination technique was estimated and
compared with the prevalent desalination techniques.
Abstract: This paper deals with the design, development & implementation of a temperature sensor using zigbee. The main aim of the work undertaken in this paper is to sense the temperature and to display the result on the LCD using the zigbee technology. ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and 2.4 GHz in most jurisdictions worldwide. The technology is intended to be simpler and cheaper than other WPANs such as Bluetooth. The most capable ZigBee node type is said to require only about 10 % of the software of a typical Bluetooth or Wireless Internet node, while the simplest nodes are about 2 %. However, actual code sizes are much higher, more like 50 % of the Bluetooth code size. ZigBee chip vendors have announced 128-kilobyte devices. In this work undertaken in the design & development of the temperature sensor, it senses the temperature and after amplification is then fed to the micro controller, this is then connected to the zigbee module, which transmits the data and at the other end the zigbee reads the data and displays on to the LCD. The software developed is highly accurate and works at a very high speed. The method developed shows the effectiveness of the scheme employed.
Abstract: This paper proposes new algorithms for the computeraided
design and manufacture (CAD/CAM) of 3D woven multi-layer
textile structures. Existing commercial CAD/CAM systems are often
restricted to the design and manufacture of 2D weaves. Those
CAD/CAM systems that do support the design and manufacture of
3D multi-layer weaves are often limited to manual editing of design
paper grids on the computer display and weave retrieval from stored
archives. This complex design activity is time-consuming, tedious
and error-prone and requires considerable experience and skill of a
technical weaver. Recent research reported in the literature has
addressed some of the shortcomings of commercial 3D multi-layer
weave CAD/CAM systems. However, earlier research results have
shown the need for further work on weave specification, weave
generation, yarn path editing and layer binding. Analysis of 3D
multi-layer weaves in this research has led to the design and
development of efficient and robust algorithms for the CAD/CAM of
3D woven multi-layer textile structures. The resulting algorithmically
generated weave designs can be used as a basis for lifting plans that
can be loaded onto looms equipped with electronic shedding
mechanisms for the CAM of 3D woven multi-layer textile structures.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: Real-time 3D applications have to guarantee
interactive rendering speed. There is a restriction for the number of
polygons which is rendered due to performance of a graphics hardware
or graphics algorithms. Generally, the rendering performance will be
drastically increased when handling only the dynamic 3d models,
which is much fewer than the static ones. Since shapes and colors of
the static objects don-t change when the viewing direction is fixed, the
information can be reused. We render huge amounts of polygon those
cannot handled by conventional rendering techniques in real-time by
using a static object image and merging it with rendering result of the
dynamic objects. The performance must be decreased as a
consequence of updating the static object image including removing
an static object that starts to move, re-rending the other static objects
being overlapped by the moving ones. Based on visibility of the object
beginning to move, we can skip the updating process. As a result, we
enhance rendering performance and reduce differences of rendering
speed between each frame. Proposed method renders total
200,000,000 polygons that consist of 500,000 dynamic polygons and
the rest are static polygons in about 100 frames per second.
Abstract: The authors present a mixed method for reducing the order of the large-scale dynamic systems. In this method, the denominator polynomial of the reduced order model is obtained by using the modified pole clustering technique while the coefficients of the numerator are obtained by Pade approximations. This method is conceptually simple and always generates stable reduced models if the original high-order system is stable. The proposed method is illustrated with the help of the numerical examples taken from the literature.
Abstract: A geothermal power plant multiple simulator for
operators training is presented. The simulator is designed to be
installed in a wireless local area network and has a capacity to train
one to six operators simultaneously, each one with an independent
simulation session. The sessions must be supervised only by one
instructor. The main parts of this multiple simulator are: instructor
and operator-s stations. On the instructor station, the instructor
controls the simulation sessions, establishes training exercises and
supervises each power plant operator in individual way. This station
is hosted in a Main Personal Computer (NS) and its main functions
are: to set initial conditions, snapshots, malfunctions or faults,
monitoring trends, and process and soft-panel diagrams. On the other
hand the operators carry out their actions over the power plant
simulated on the operator-s stations; each one is also hosted in a PC.
The main software of instructor and operator-s stations are executed
on the same NS and displayed in PCs through graphical Interactive
Process Diagrams (IDP). The geothermal multiple simulator has been
installed in the Geothermal Simulation Training Center (GSTC) of
the Comisi├│n Federal de Electricidad, (Federal Commission of
Electricity, CFE), Mexico, and is being utilized as a part of the
training courses for geothermal power plant operators.
Abstract: Environmental awareness and depletion of the
petroleum resources are among vital factors that motivate a number
of researchers to explore the potential of reusing natural fiber as an
alternative composite material in industries such as packaging,
automotive and building constructions. Natural fibers are available in
abundance, low cost, lightweight polymer composite and most
importance its biodegradability features, which often called “ecofriendly"
materials. However, their applications are still limited due
to several factors like moisture absorption, poor wettability and large
scattering in mechanical properties. Among the main challenges on
natural fibers reinforced matrices composite is their inclination to
entangle and form fibers agglomerates during processing due to
fiber-fiber interaction. This tends to prevent better dispersion of the
fibers into the matrix, resulting in poor interfacial adhesion between
the hydrophobic matrix and the hydrophilic reinforced natural fiber.
Therefore, to overcome this challenge, fiber treatment process is one
common alternative that can be use to modify the fiber surface
topology by chemically, physically or mechanically technique.
Nevertheless, this paper attempt to focus on the effect of
mercerization treatment on mechanical properties enhancement of
natural fiber reinforced composite or so-called bio composite. It
specifically discussed on mercerization parameters, and natural fiber
reinforced composite mechanical properties enhancement.
Abstract: The article deals with development, design and
implementation of a mathematical model of the human respiratory
system. The model is designed in order to simulate distribution of
important intrapulmonary parameters along the bronchial tree such as
pressure amplitude, tidal volume and effect of regional mechanical
lung properties upon the efficiency of various ventilatory techniques.
Therefore exact agreement of the model structure with the lung
anatomical structure is required. The model is based on the lung
morphology and electro-acoustic analogy is used to design the
model.
Abstract: Based on a theoretical erbium-doped fiber amplifier
(EDFA) model, we have proposed an application of disturbance
observer(DOB) with proportional/integral/differential(PID) controller
to EDFA for minimizing gain-transient time of wavelength
-division-multiplexing (WDM) multi channels in optical amplifier in
channel add/drop networks. We have dramatically reduced the
gain-transient time to less than 30μsec by applying DOB with PID
controller to the control of amplifier gain. The proposed DOB-based
gain control algorithm for EDFA was implemented as a digital control
system using TI's DSP(TMS320C28346) chip and experimental
results of the system verify the excellent performance of the proposed
gain control methodology.
Abstract: Highly ordered arrays of TiO2 nanotubes (TiNTs) were grown vertically on Ti foil by electrochemical anodization. We controlled the lengths of these TiNTs from 2.4 to 26.8 ¶üÇóμm while varying the water contents (1, 3, and 6 wt%) of the electrolyte in ethylene glycol in the presence of 0.5 wt% NH4F with anodization for various applied voltages (20–80 V), periods (10–240 min) and temperatures (10–30 oC). For vertically aligned TiNT arrays, not only the increase in their tube lengths, but also their geometric (wall thickness and surface roughness) and crystalline structure lead to a significant influence on photocatalytic activity. The length optimization for methylene blue (MB) photodegradation was 18 μm. Further extending the TiNT length yielded lower photocatalytic activity presumably related to the limited MB diffusion and light-penetration depth into the TiNT arrays. The results indicated that a maximum MB photodegradation rate was obtained for the discrete anatase TiO2 nanotubes with thick and rough walls.
Abstract: In this paper we present a new method for coin
identification. The proposed method adopts a hybrid scheme using
Eigenvalues of covariance matrix, Circular Hough Transform (CHT)
and Bresenham-s circle algorithm. The statistical and geometrical
properties of the small and large Eigenvalues of the covariance
matrix of a set of edge pixels over a connected region of support are
explored for the purpose of circular object detection. Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze
zero elements and contain only a small number of non-zero elements,
they provide an advantage of matrix storage space and computational
time. Neighborhood suppression scheme is used to find the valid
Hough peaks. The accurate position of the circumference pixels is
identified using Raster scan algorithm which uses geometrical
symmetry property. After finding circular objects, the proposed
method uses the texture on the surface of the coins called texton,
which are unique properties of coins, refers to the fundamental micro
structure in generic natural images. This method has been tested on
several real world images including coin and non-coin images. The
performance is also evaluated based on the noise withstanding
capability.
Abstract: Team distillation assisted by microwave extraction
(SDAM) considered as accelerated technique extraction is a
combination of microwave heating and steam distillation, performed
at atmospheric pressure. SDAM has been compared with the same
technique coupled with the cryogrinding of seeds (SDAM -CG).
Isolation and concentration of volatile compounds are performed by a
single stage for the extraction of essential oil from Cuminum
cyminum seeds. The essential oils extracted by these two methods for
5 min were quantitatively (yield) and qualitatively (aromatic profile)
no similar. These methods yield an essential oil with higher amounts
of more valuable oxygenated compounds, and allow substantial
savings of costs, in terms of time, energy and plant material. SDAM
and SDAM-CG is a green technology and appears as a good
alternative for the extraction of essential oils from aromatic plants.
Abstract: In this paper in consideration of each available
techniques deficiencies for speech recognition, an advanced method
is presented that-s able to classify speech signals with the high
accuracy (98%) at the minimum time. In the presented method, first,
the recorded signal is preprocessed that this section includes
denoising with Mels Frequency Cepstral Analysis and feature
extraction using discrete wavelet transform (DWT) coefficients; Then
these features are fed to Multilayer Perceptron (MLP) network for
classification. Finally, after training of neural network effective
features are selected with UTA algorithm.
Abstract: In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.
Abstract: Rockfall is a kind of irregular geological disaster. Its
destruction time, space and movements are highly random. The impact
force is determined by the way and velocity rocks move. The
movement velocity of a rockfall depends on slope gradient of its
moving paths, height, slope surface roughness and rock shapes. For
effectively mitigate and prevent disasters brought by rockfalls, it is
required to precisely calculate the moving paths of a rockfall so as to
provide the best protective design. This paper applies Colorado
Rockfall Simulation Program (CRSP) as our study tool to discuss the
impact of slope shape and surface roughness on the moving paths of a
single rockfall. The analytical results showed that the slope, m=1:1,
acted as the threshold for rockfall bounce height on a monoclinal slight
slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce
height increased as JCR increased. If slope fixed and JRC increased,
the bounce height of rocks increased gradually with reducing
movement velocity. Therefore, the analysis on the moving paths of
rockfalls with CRSP could simulate bouncing of falling rocks. By
analyzing moving paths, velocity, and bounce height of falling rocks,
we could effectively locate impact points of falling rocks on a slope.
Such analysis can be served as a reference for future disaster
prevention and control.
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.