Abstract: Solar sunspot rotation, latitudinal bands are studied based on intelligent computation methods. A combination of image fusion method with together tree decomposition is used to obtain quantitative values about the latitudes of trajectories on sun surface that sunspots rotate around them. Daily solar images taken with SOlar and Heliospheric (SOHO) satellite are fused for each month separately .The result of fused image is decomposed with Quad Tree decomposition method in order to achieve the precise information about latitudes of sunspot trajectories. Such analysis is useful for gathering information about the regions on sun surface and coordinates in space that is more expose to solar geomagnetic storms, tremendous flares and hot plasma gases permeate interplanetary space and help human to serve their technical systems. Here sunspot images in September, November and October in 2001 are used for studying the magnetic behavior of sun.
Abstract: The focal spot of a high intensity focused ultrasound
transducer is small. To heat a large target volume, multiple treatment spots are required. If the power of each treatment spot is fixed, it could
results in insufficient heating of initial spots and over-heating of later ones, which is caused by the thermal diffusion. Hence, to produce a
uniform heated volume, the delivered energy of each treatment spot
should be properly adjusted. In this study, we proposed an iterative, extrapolation technique to adjust the required ultrasound energy of
each treatment spot. Three different scanning pathways were used to evaluate the performance of this technique. Results indicate that by using the proposed technique, uniform heating volume could be obtained.
Abstract: A multi-agent system is developed here to predict
monthly details of the upcoming peak of the 24th solar magnetic
cycle. While studies typically predict the timing and magnitude of
cycle peaks using annual data, this one utilizes the unsmoothed
monthly sunspot number instead. Monthly numbers display more
pronounced fluctuations during periods of strong solar magnetic
activity than the annual sunspot numbers. Because strong magnetic
activities may cause significant economic damages, predicting
monthly variations should provide different and perhaps helpful
information for decision-making purposes. The multi-agent system
developed here operates in two stages. In the first, it produces twelve
predictions of the monthly numbers. In the second, it uses those
predictions to deliver a final forecast. Acting as expert agents, genetic
programming and neural networks produce the twelve fits and
forecasts as well as the final forecast. According to the results
obtained, the next peak is predicted to be 156 and is expected to
occur in October 2011- with an average of 136 for that year.
Abstract: The breakdown strength characteristic of Low Density
Polyethylene films (LDPE) under DC voltage application and the
effect of water absorption have been studied. Mainly, our experiment
was investigated under two conditions; dry and heavy water
absorption. Under DC ramp voltage, the result found that the
breakdown strength under heavy water absorption has a lower value
than dry condition. In order to clarify the effect, the temperature rise of
film was observed using non contact thermograph until the occurrence
of the electrical breakdown and the conduction current of the sample
was also measured in correlation with the thermograph measurement.
From the observations, it was shown that under the heavy water
absorption, the hot spot in the samples appeared at lower voltage. At
the same voltage the temperature of the hot spot and conduction
current was higher than that under the dry condition. The measurement
result has a good correlation between the existence of a critical field
for conduction current and thermograph observation. In case of the
heavy water absorption, the occurrence of the threshold field was
earlier than the dry condition as result lead to higher of conduction
current and the temperature rise appears after threshold field was
significantly increased in increasing of field. The higher temperature
rise was caused by the higher current conduction as the result the
insulation leads to breakdown to the lower field application.
Abstract: The presented paper is related to the design methods and neutronic characterization of the reactivity control system in the large power unit of Generation IV Gas cooled Fast Reactor – GFR2400. The reactor core is based on carbide pin fuel type with the application of refractory metallic liners used to enhance the fission product retention of the SiCcladding. The heterogeneous design optimization of control rod is presented and the results of rods worth and their interferences in a core are evaluated. In addition, the idea of reflector removal as an additive reactivity management option is investigated and briefly described.
Abstract: In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.
Abstract: Decision fusion is one of hot research topics in
classification area, which aims to achieve the best possible
performance for the task at hand. In this paper, we
investigate the usefulness of this concept to improve change
detection accuracy in remote sensing. Thereby, outputs of
two fuzzy change detectors based respectively on
simultaneous and comparative analysis of multitemporal
data are fused by using fuzzy integral operators. This
method fuses the objective evidences produced by the
change detectors with respect to fuzzy measures that express
the difference of performance between them. The proposed
fusion framework is evaluated in comparison with some
ordinary fuzzy aggregation operators. Experiments carried
out on two SPOT images showed that the fuzzy integral was
the best performing. It improves the change detection
accuracy while attempting to equalize the accuracy rate in
both change and no change classes.
Abstract: In this paper variation of spot price and total profits of
the generating companies- through wholesale electricity trading are
discussed with and without Central Generating Stations (CGS) share
and seasonal variations are also considered. It demonstrates how
proper analysis of generators- efficiencies and capabilities, types of
generators owned, fuel costs, transmission losses and settling price
variation using the solutions of Optimal Power Flow (OPF), can
allow companies to maximize overall revenue. It illustrates how
solutions of OPF can be used to maximize companies- revenue under
different scenarios. And is also extended to computation of Available
Transfer Capability (ATC) is very important to the transmission
system security and market forecasting. From these results it is
observed that how crucial it is for companies to plan their daily
operations and is certainly useful in an online environment of
deregulated power system. In this paper above tasks are demonstrated
on 124 bus real-life Indian utility power system of Andhra Pradesh
State Grid and results have been presented and analyzed.
Abstract: In this cyber age, the job market has been rapidly transforming and being digitalized. Submitting a paper-based curriculum vitae (CV) nowadays does not grant a job seeker a high employability rate. This paper calls for attention on the creation of mobile Curriculum Vitae or m-CV (http://mcurriculumvitae. blogspot.com), a sample of an individual CV developed using weblog, which can enhance the job hunter especially fresh graduate-s higher marketability rate. This study is designed to identify the perceptions held by Malaysian university students regarding m-CV grounded on a modified Technology Acceptance Model (TAM). It measures the strength and the direction of relationships among three major variables – Perceived Ease of Use (PEOU), Perceived Usefulness (PU) and Behavioral Intention (BI) to use. The finding shows that university students generally accepted adopting m-CV since they perceived m-CV to be more useful rather than easy to use. Additionally, this study has confirmed TAM to be a useful theoretical model in helping to understand and explain the behavioral intention to use Web 2.0 application-weblog publishing their CV. The result of the study has underlined another significant positive value of using weblog to create personal CV. Further research of m-CV has been highlighted in this paper.
Abstract: The use of wind energy for electricity generation is
growing rapidly across the world and in Portugal. However, the
geographical characteristics of the country along with the average
wind regime and with the environmental restrictions imposed to these
projects create limitations to the exploit of the onshore wind
resource. The best onshore wind spots are already committed and the
possibility of offshore wind farms in the Portuguese cost is now
being considered. This paper aims to make a contribution to the
evaluation of offshore wind power projects in Portugal. The technical
restrictions are addressed and the strategic, environmental and
financial interest of the project is analysed from the private company
and public points of view. The results suggest that additional support
schemes are required to ensure private investors interest for these
projects. Assuming an approach of direct substitution of energy
sources for electricity generation, the avoided CO2 equivalent
emissions for an offshore wind power project were quantified. Based
on the conclusions, future research is proposed to address the
environmental and social impacts of these projects.
Abstract: The mechanism behind the electromigration and
thermomigration failure in flip-chip solder joints with Cu-pillar bumps
was investigated in this paper through using finite element method.
Hot spot and the current crowding occurrs in the upper corner of
copper column instead of solders of the common solder ball. The
simulation results show that the change in thermal gradient is
noticeable, which might greatly affect the reliability of solder joints
with Cu-pillar bumps under current stressing. When the average
applied current density is increased from 1×104 A/cm2 to 3×104 A/cm2
in solders, the thermal gradient would increase from 74 K/cm to 901
K/cm at an ambient temperature of 25°C. The force from thermal
gradient of 901 K/cm can nearly induce thermomigration by itself.
With the increase in applied current, the thermal gradient is growing. It
is proposed that thermomigration likely causes a serious reliability
issue for Cu column based interconnects.
Abstract: The wireless sensor networks have been extensively
deployed and researched. One of the major issues in wireless sensor
networks is a developing energy-efficient clustering protocol.
Clustering algorithm provides an effective way to prolong the lifetime
of a wireless sensor networks. In the paper, we compare several
clustering protocols which significantly affect a balancing of energy
consumption. And we propose an Energy-Efficient Distributed
Unequal Clustering (EEDUC) algorithm which provides a new way of
creating distributed clusters. In EEDUC, each sensor node sets the
waiting time. This waiting time is considered as a function of residual
energy, number of neighborhood nodes. EEDUC uses waiting time to
distribute cluster heads. We also propose an unequal clustering
mechanism to solve the hot-spot problem. Simulation results show that
EEDUC distributes the cluster heads, balances the energy
consumption well among the cluster heads and increases the network
lifetime.
Abstract: The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.
Abstract: In this study the elastic-plastic stress distribution in
weld-bonded joint, fabricated from austenitic stainless steel (AISI
304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011,
subjected to axial loading is investigated. This is needed to improve
design procedures and welding codes, and saving efforts in the
cumbersome experiments and analysis. Therefore, a complete 3-D
finite element modelling and analysis of spot welded, bonded and
weld-bonded joints under axial loading conditions is carried out. A
comprehensive systematic experimental program is conducted to
determine many properties and quantities, of the base metals and the
adhesive, needed for FE modelling, such like the elastic – plastic
properties, modulus of elasticity, fracture limit, the nugget and heat
affected zones (HAZ) properties, etc. Consequently, the finite
element models developed, for each case, are used to evaluate
stresses distributions across the entire joint, in both the elastic and
plastic regions. The stress distribution curves are obtained,
particularly in the elastic regions and found to be consistent and in
excellent agreement with the published data. Furthermore, the
stresses distributions are obtained in the weld-bonded joint and
display the best results with almost uniform smooth distribution
compared to spot and bonded cases. The stress concentration peaks at
the edges of the weld-bonded region, are almost eliminated resulting
in achieving the strongest joint of all processes.
Abstract: This paper reviews recent studies and particularly the
effects of Climate Change in the North Tropical Atlantic by studying
atmospheric conditions that prevailed in 2005 ; Coral Bleaching
HotSpot and Hurricane Katrina. In the aim to better understand and
estimate the impact of the physical phenomenon, i.e. Thermal
Oceanic HotSpot (TOHS), isotopic studies of δ18O and δ13C on
marine animals from Guadeloupe (French Caribbean Island) were
carried out. Recorded measures show Sea Surface Temperature (SST)
up to 35°C in August which is much higher than data recorded by
NOAA satellites 32°C. After having reviewed the process that led to
the creation of Hurricane Katrina which hit New Orleans in August
29, 2005, it will be shown that the climatic conditions in the
Caribbean from August to October 2005 have influenced Katrina
evolution. This TOHS is a combined effect of various phenomenon
which represent an additional factor to estimate future climate
changes.
Abstract: This paper presents a new system developed in Java®
for pattern recognition and pattern summarisation in multi-band
(RGB) satellite images. The system design is described in some
detail. Results of testing the system to analyse and summarise
patterns in SPOT MS images and LANDSAT images are also
discussed.
Abstract: This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.
Abstract: A combination of image fusion and quad tree decomposition method is used for detecting the sunspot trajectories in each month and computation of the latitudes of these trajectories in each solar hemisphere. Daily solar images taken with SOHO satellite are fused for each month and the result of fused image is decomposed with Quad Tree decomposition method in order to classifying the sunspot trajectories and then to achieve the precise information about latitudes of sunspot trajectories. Also with fusion we deduce some physical remarkable conclusions about sun magnetic fields behavior. Using quad tree decomposition we give information about the region on sun surface and the space angle that tremendous flares and hot plasma gases permeate interplanetary space and attack to satellites and human technical systems. Here sunspot images in June, July and August 2001 are used for studying and give a method to compute the latitude of sunspot trajectories in each month with sunspot images.