Abstract: Load balancing in distributed computer systems is the
process of redistributing the work load among processors in the
system to improve system performance. Most of previous research in
using fuzzy logic for the purpose of load balancing has only
concentrated in utilizing fuzzy logic concepts in describing
processors load and tasks execution length. The responsibility of the
fuzzy-based load balancing process itself, however, has not been
discussed and in most reported work is assumed to be performed in a
distributed fashion by all nodes in the network. This paper proposes a
new fuzzy dynamic load balancing algorithm for homogenous
distributed systems. The proposed algorithm utilizes fuzzy logic in
dealing with inaccurate load information, making load distribution
decisions, and maintaining overall system stability. In terms of
control, we propose a new approach that specifies how, when, and by
which node the load balancing is implemented. Our approach is
called Centralized-But-Distributed (CBD).
Abstract: The future of Higher Education Institutions (HEI) depend on their ability to attract and retain students, increase recognition and prestige. In order to respond to the 'customers' increasingly demanding, HEI need to identify the key factors that influence the satisfaction of a 'customers', thereby creating competitive advantages. These determinants of satisfaction are important elements that guide the strategy of an institution and allow the successful achievement of strategic plans, both teaching and administrative, to offer their ‘costumers’ services and products with higher quality. Following this way of thinking, the purpose of this study was to evaluate the satisfaction with the service quality of the School of Technology and Management of Bragança (ESTiG), of the Polytechnic Institute of Bragança, identifying, thus, the dimensions related to the quality of services that might influence students' satisfaction. The results showed that, in general, the students are satisfied with the performance of ESTiG.
Abstract: Depression is a serious mental health problem that
affects people of all ages, including children and adolescents. Studies
showed that female gender is one of the risk factors may influence
the development of depression in adolescents. However, some of the
studies from Turkey suggested that gender does not lead to any
significant difference in the youth depression level. Therefore, the
presented study investigated whether girls differ from boys in respect
of depression. The association between genders and test scores for
the adolescents in a population of primary and secondary school
students was also evaluated. The study was consisting of 254
adolescents (122 boys and 132 girls) with a mean age of 13.86±1.43
(Mean±SD) ranging from 12-16 years. Psychological assessment was
performed using Children-s Depression Inventory (CDI). Chi-square
and Student-s t-test statistics were employed to analyze the data. The
mean of the CDI scores of the girls were higher than boys- CDI
scores (t = -4.580, p = 0.001). Higher ratio appeared for the girls
when they compared with boy group-s depression levels using a CDI
cut-off point of 19 (p = 0.001, Odds Ratio = 2,603). The findings of
the present study suggested that adolescent girls have high level of
depression than adolescent boys aged between 12-16 years in
Turkey. Although some studies reported that there is no any
differences depression level between adolescent boys and girls in
Turkey, result of the present study showed that adolescent girls have
high level of depression than adolescent boys in Turkey.
Abstract: People have the habitual pitch level which is used when people say something generally. However this pitch should be changed irregularly in the presence of noise. So it is useful to estimate SNR of speech signal by pitch. In this paper, we obtain the energy of input speech signal and then we detect a stationary region on voiced speech. And we get the pitch period by NAMDF for the stationary region that is not varied pitch rapidly. After getting pitch, each frame is divided by pitch period and the likelihood of closed pitch is estimated. In this paper, we proposed new parameter, NLF, to estimate the SNR of received speech signal. The NLF is derived from the correlation of near pitch periods. The NLF is obtained for each stationary region in voiced speech. Finally we confirmed good performance of the estimation of the SNR of received input speech in the presence of noise.
Abstract: In this paper we present a Adaptive Neuro-Fuzzy
System (ANFIS) with inputs the lagged dependent variable for the
prediction of Gross domestic Product growth rate in six countries.
We compare the results with those of Autoregressive (AR) model.
We conclude that the forecasting performance of neuro-fuzzy-system
in the out-of-sample period is much more superior and can be a very
useful alternative tool used by the national statistical services and the
banking and finance industry.
Abstract: One of the major parts of a jet engine is air intake,
which provides proper and required amount of air for the engine to
operate. There are several aerodynamic parameters which should be
considered in design, such as distortion, pressure recovery, etc. In
this research, the effects of lip ice accretion on pitot intake
performance are investigated. For ice accretion phenomenon, two
supervised multilayer neural networks (ANN) are designed, one for
ice shape prediction and another one for ice roughness estimation
based on experimental data. The Fourier coefficients of transformed
ice shape and parameters include velocity, liquid water content
(LWC), median volumetric diameter (MVD), spray time and
temperature are used in neural network training. Then, the subsonic
intake flow field is simulated numerically using 2D Navier-Stokes
equations and Finite Volume approach with Hybrid mesh includes
structured and unstructured meshes. The results are obtained in
different angles of attack and the variations of intake aerodynamic
parameters due to icing phenomenon are discussed. The results show
noticeable effects of ice accretion phenomenon on intake behavior.
Abstract: Treatment of tar-containing wastewater is necessary
for the successful operation of biomass gasification plants (BGPs). In
the present study, tar-containing wastewater was treated using lime
and alum for the removal of in-organics, followed by adsorption on
powdered activated carbon (PAC) for the removal of organics. Limealum
experiments were performed in a jar apparatus and activated
carbon studies were performed in an orbital shaker. At optimum
concentrations, both lime and alum individually proved to be capable
of removing color, total suspended solids (TSS) and total dissolved
solids (TDS), but in both cases, pH adjustment had to be carried out
after treatment. The combination of lime and alum at the dose ratio
of 0.8:0.8 g/L was found to be optimum for the removal of inorganics.
The removal efficiency achieved at optimum
concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity,
TSS and TDS, respectively. The major advantages of the lime-alum
combination were observed to be as follows: no requirement of pH
adjustment before and after treatment and good settleability of
sludge. Coagulation-precipitation followed by adsorption on PAC
resulted in 92.3% chemical oxygen demand (COD) removal and
100% phenol removal at equilibrium. Ammonia removal efficiency
was found to be 11.7% during coagulation-flocculation and 36.2%
during adsorption on PAC. Adsorption of organics on PAC in terms
of COD and phenol followed Freundlich isotherm with Kf = 0.55 &
18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may
prove to be one of the fastest and most techno-economically feasible
methods for the treatment of tar-containing wastewater generated
from BGPs.
Abstract: This paper describes the use of artificial neural
networks (ANN) for predicting non-linear layer moduli of flexible
airfield pavements subjected to new generation aircraft (NGA)
loading, based on the deflection profiles obtained from Heavy
Weight Deflectometer (HWD) test data. The HWD test is one of the
most widely used tests for routinely assessing the structural integrity
of airport pavements in a non-destructive manner. The elastic moduli
of the individual pavement layers backcalculated from the HWD
deflection profiles are effective indicators of layer condition and are
used for estimating the pavement remaining life. HWD tests were
periodically conducted at the Federal Aviation Administration-s
(FAA-s) National Airport Pavement Test Facility (NAPTF) to
monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test
gear trafficking on the structural condition of flexible pavement
sections. In this study, a multi-layer, feed-forward network which
uses an error-backpropagation algorithm was trained to approximate
the HWD backcalculation function. The synthetic database generated
using an advanced non-linear pavement finite-element program was
used to train the ANN to overcome the limitations associated with
conventional pavement moduli backcalculation. The changes in
ANN-based backcalculated pavement moduli with trafficking were
used to compare the relative severity effects of the aircraft landing
gears on the NAPTF test pavements.
Abstract: For a spatiotemporal database management system,
I/O cost of queries and other operations is an important performance
criterion. In order to optimize this cost, an intense research on
designing robust index structures has been done in the past decade.
With these major considerations, there are still other design issues
that deserve addressing due to their direct impact on the I/O cost.
Having said this, an efficient buffer management strategy plays a key
role on reducing redundant disk access. In this paper, we proposed an
efficient buffer strategy for a spatiotemporal database index
structure, specifically indexing objects moving over a network of
roads. The proposed strategy, namely MONPAR, is based on the data
type (i.e. spatiotemporal data) and the structure of the index
structure. For the purpose of an experimental evaluation, we set up a
simulation environment that counts the number of disk accesses
while executing a number of spatiotemporal range-queries over the
index. We reiterated simulations with query sets with different
distributions, such as uniform query distribution and skewed query
distribution. Based on the comparison of our strategy with wellknown
page-replacement techniques, like LRU-based and Prioritybased
buffers, we conclude that MONPAR behaves better than its
competitors for small and medium size buffers under all used query-distributions.
Abstract: The contribution deals with problem of take-off phase of back somersault with twisting with various numbers of twists along longitudinal body axis. The aim was to evaluate the changes in angles during transition phase from back handspring to back somersault using 3D kinematic analysis of the somersaults. We used Simi Motion System for the 3D kinematic analysis of the observed gymnastic element performed by Czech Republic female representative and 2008 Summer Olympic Games participant. The results showed that the higher the number of twists, the smaller the touchdown angle in which the gymnasts lands on the pad in the beginning of take-off phase. In back somersault with one twist (180°) the average angle is 54°, in 1080° back somersault the average angle is 45.9°. These results may help to improve technical training of sports gymnasts.
Abstract: Adenylate kinase (AK) catalyse the phosphotransferase
reaction plays an important role in cellular energy homeostasis. The
inhibitors of bacterial AK are useful in the treatment of several
bacterial infections. To the novel inhibitors of AK, docking studies
performed by using the 3D structure of Bacillus stearothermophilus
adenylate kinase from protein data bank (IZIP). 46 Quinoxaline
analogues were docked in 1ZIP and selected the highly interacting
compounds based on their binding energies, for further studies
Abstract: Rapid progress in audio compression technology has contributed to the explosive growth of music available in digital form today. In a reversal of ideas, this work makes use of a recently proposed efficient audio compression scheme to develop three important applications in the context of Music Information Retrieval (MIR) for the effective manipulation of large music databases, namely automatic music recommendation (AMR), digital rights management (DRM) and audio finger-printing for song identification. The performance of these three applications has been evaluated with respect to a database of songs collected from a diverse set of genres.
Abstract: This paper deals with motion planning of multiple
mobile robots. Mobile robots working together to achieve several
objectives have many advantages over single robot system. However,
the planning and coordination between the mobile robots is
extremely difficult. In the present investigation rule-based and rulebased-
neuro-fuzzy techniques are analyzed for multiple mobile
robots navigation in an unknown or partially known environment.
The final aims of the robots are to reach some pre-defined goals.
Based upon a reference motion, direction; distances between the
robots and obstacles; and distances between the robots and targets;
different types of rules are taken heuristically and refined later to find
the steering angle. The control system combines a repelling influence
related to the distance between robots and nearby obstacles and with
an attracting influence between the robots and targets. Then a hybrid
rule-based-neuro-fuzzy technique is analysed to find the steering
angle of the robots. Simulation results show that the proposed rulebased-
neuro-fuzzy technique can improve navigation performance in
complex and unknown environments compared to this simple rulebased
technique.
Abstract: The objective of this study was to investigate the effects of dietary supplementation with raw or heat-treated sunflower oil seed with two levels of 7.5% or 15% on unsaturated fatty acids in milk fat and performances of high-yielding lactating cows. Twenty early lactating Holstein cows were used in a complete randomized design. Treatments included: 1) CON, control (without sunflower oil seed). 2) LS-UT, 7.5% raw sunflower oil seed. 3) LS-HT, 7.5% heat-treated sunflower oil seed. 4) HS-UT, 15% raw sunflower oil seed. 5) HS-HT, 15% heat-treated sunflower oil seed. Experimental period lasted for 4 wk, with first 2 wk used for adaptation to the diets. Supplementation with 7.5% raw sunflower seed (LS-UT) tended to decrease milk yield, with 28.37 kg/d compared with the control (34.75 kg/d). Milk fat percentage was increased with the HS-UT treatment that obtained 3.71% compared with CON that was 3.39% and without significant different. Milk protein percent was decreased high level sunflower oil seed treatments (15%) with 3.18% whereas CON treatment is caused 3.40% protein. The cows fed added low sunflower heat-treated (LS-HT) produced milk with the highest content of total unsaturated fatty acid with 32.59 g/100g of milk fat compared with the HS-UT with 23.59 g/100g of milk fat. Content of C18 unsaturated fatty acids in milk fat increased from 21.68 g/100g of fat in the HS-UT to 22.50, 23.98, 27.39 and 30.30 g/100g of fat from the cow fed HS-HT, CON, LS-UT and LS-HT treatments, respectively. C18:2 isomers of fatty acid in milk were greater by LSHT supplementation with significant effect (P < 0.05). Total of C18 unsaturated fatty acids content was significantly higher in milk of animal fed added low heat-treated sunflower (7.5%) than those fed with high sunflower. In all, results of this study showed that diet cow's supplementation with sunflower oil seed tended to reduce milk production of lactating cows but can improve C18 UFA (Unsaturated Fatty Acid) content in milk fat. 7.5% level of sunflower oil seed that heated seemed to be the optimal source to increase UFA production.
Abstract: Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.
Abstract: The underground shopping mall has the constructional
problem of the fire evacuation. Also, the people sometimes lose their
direction and information of current time in the mall. If the
emergencies such as terrorist explosions or gas explosions are
happened, they have to go out soon. Under such circumstances, inside
of the mall has high risk for life. In this research, the authors propose a
way that he/she can go out from the underground shopping mall
quickly. If the narrow exits are discovered by using active RFID
(Radio Frequency Identification) tags and using cellular phones, they
can evacuate as soon as possible. To verify this hypothesis, the authors
design the model and carry out the agent-based simulation. They treat,
as a case study, the Tenjin mall in Fukuoka Prefecture in Japan. The
result of the simulation is that the case of the pedestrian with using
active RFID tags and cellular phones reduced the amount of time to
spend on the evacuation. Even if the diffusion of RFID tags and
cellular phones was not perfect, they could show the effectiveness of
reducing the time of evacuation.
Abstract: Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, real-coded genetic algorithm (RCGA) optimization technique is applied to design robust power system stabilizer for both singlemachine infinite-bus (SMIB) and multi-machine power system. The design problem of the proposed controller is formulated as an optimization problem and RCGA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.
Abstract: Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.
Abstract: A Reading Comprehend (RC) Platform has been
constructed and developed to facilitate children-s English reading
comprehension. Like a learning bridge, the RC Platform focuses on
the integration of rich media and picture-book texts. The study is to
examine the effects of the project within the RC Platform for children.
Two classes of fourth graders were selected from a public elementary
school in an urban area of central Taiwan. The findings taken from the
survey showed that the students demonstrated high interest in the RC
Platform. The students benefited greatly and enjoyed reading via the
technology-enhanced project within the RC Platform. This Platform is
a good reading bridge to enrich students- learning experiences and
enhance their performance in English reading comprehension.
Abstract: In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.