Abstract: In synchronized games players make their moves simultaneously
rather than alternately. Synchronized Quadromineering is
the synchronized version of Quadromineering, a variants of a classical
two-player combinatorial game called Domineering. Experimental
results for small m × n boards (with m + n < 15) and some
theoretical results for general k × n boards (with k = 4, 5, 6) are
presented. Moreover, some Synchronized Quadromineering variants
are also investigated.
Abstract: The environmental impact caused by industries is an issue that, in the last 20 years, has become very important in terms of society, economics and politics in Colombia. Particularly, the tannery process is extremely polluting because of uneffective treatments and regulations given to the dumping process and atmospheric emissions. Considering that, this investigation is intended to propose a management model based on the integration of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, that prioritizes the strategic components of the organizations. As a result, a management model will be obtained and it will provide a strategic perspective through a systemic approach to the tanning process. This will be achieved through the use of Multicriteria Decision tools, along with Quality Function Deployment and Fuzzy Logic. The strategic approach that embraces the management model using the alignment of Lean Supply Chain, Green Supply Chain, Cleaner Production and ISO 14001-2004, is an integrated perspective that allows a gradual frame of the tactical and operative elements through the correct setting of the information flow, improving the decision making process. In that way, Small Medium Enterprises (SMEs) could improve their productivity, competitiveness and as an added value, the minimization of the environmental impact. This improvement is expected to be controlled through a Dashboard that helps the Organization measure its performance along the implementation of the model in its productive process.
Abstract: Because nodes are usually battery-powered, the energy
presents a very scarce resource in wireless sensor networks. For this
reason, the design of medium access control had to take energy
efficiency as one of its hottest concerns. Accordingly, in order to
improve the energy performance of MAC schemes in wireless sensor
networks, several ways can be followed. In fact, some researchers try
to limit idle listening while others focus on mitigating overhearing
(i.e. a node can hear a packet which is destined to another node)
or reducing the number of the used control packets. We, in this
paper, propose a new hybrid MAC protocol termed ELE-MAC
(i.e. Energy Latency Efficient MAC). The ELE-MAC major design
goals are energy and latency efficiencies. It adopts less control
packets than SMAC in order to preserve energy. We carried out ns-
2 simulations to evaluate the performance of the proposed protocol.
Thus, our simulation-s results prove the ELE-MAC energy efficiency.
Additionally, our solution performs statistically the same or better
latency characteristic compared to adaptive SMAC.
Abstract: The value of emission factor was calculated in the
older type of Diesel engine operating on an engine testing bench and
then compared with the parameters monitored under similar
conditions when the EnviroxTM additive was applied. It has been
found out that the additive based on CeO2 nanoparticles reduces
emission of NOx. The dependencies of NOx emissions on reduced
torque, engine power and revolutions have been observed as well.
Abstract: Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.
Abstract: This paper presents an overview of the multiobjective shortest path problem (MSPP) and a review of essential and recent issues regarding the methods to its solution. The paper further explores a multiobjective evolutionary algorithm as applied to the MSPP and describes its behavior in terms of diversity of solutions, computational complexity, and optimality of solutions. Results show that the evolutionary algorithm can find diverse solutions to the MSPP in polynomial time (based on several network instances) and can be an alternative when other methods are trapped by the tractability problem.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: A novel adaptive fuzzy trajectory tracking algorithm of Stewart platform based motion platform is proposed to compensate path deviation and degradation of controller-s performance due to actuator torque limit. The algorithm can be divided into two parts: the real-time trajectory shaping part and the joint space adaptive fuzzy controller part. For a reference trajectory in task space whenever any of the actuators is saturated, the desired acceleration of the reference trajectory is modified on-line by using dynamic model of motion platform. Meanwhile an additional action with respect to the difference between the nominal and modified trajectories is utilized in the non-saturated region of actuators to reduce the path error. Using modified trajectory as input, the joint space controller incorporates compute torque controller, leg velocity observer and fuzzy disturbance observer with saturation compensation. It can ensure stability and tracking performance of controller in present of external disturbance and position only measurement. Simulation results verify the effectiveness of proposed control scheme.
Abstract: This paper proposes fractal patterns for power quality
(PQ) detection using color relational analysis (CRA) based classifier.
Iterated function system (IFS) uses the non-linear interpolation in the
map and uses similarity maps to construct various fractal patterns of
power quality disturbances, including harmonics, voltage sag, voltage
swell, voltage sag involving harmonics, voltage swell involving
harmonics, and voltage interruption. The non-linear interpolation
functions (NIFs) with fractal dimension (FD) make fractal patterns
more distinguishing between normal and abnormal voltage signals.
The classifier based on CRA discriminates the disturbance events in a
power system. Compared with the wavelet neural networks, the test
results will show accurate discrimination, good robustness, and faster
processing time for detecting disturbing events.
Abstract: In this study we propose a novel monitor hydraulic
automatic gauge control (HAGC) system based on fuzzy feedforward
controller. This is used in the development of cold rolling
mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average
yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in
the entry steel strip. The proposed method uses a mathematical model
of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In
order to improve the speed of the controller in rejecting disturbances
introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation
results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.
Abstract: In order to study seed yield and seed yield
components in bean under reduced irrigation condition and
assessment drought tolerance of genotypes, 15 lines of White beans
were evaluated in two separate RCB design with 3 replications under
stress and non stress conditions. Analysis of variance showed that
there were significant differences among varieties in terms of traits
under study, indicating the existence of genetic variation among
varieties. The results indicate that drought stress reduced seed yield,
number of seed per plant, biological yield and number of pod in
White been. In non stress condition, yield was highly correlated with
the biological yield, whereas in stress condition it was highly
correlated with harvest index. Results of stepwise regression showed
that, selection can we done based on, biological yield, harvest index,
number of seed per pod, seed length, 100 seed weight. Result of path
analysis showed that the highest direct effect, being positive, was
related to biological yield in non stress and to harvest index in stress
conditions. Factor analysis were accomplished in stress and nonstress
condition a, there were 4 factors that explained more than 76
percent of total variations. We used several selection indices such as
Stress Susceptibility Index ( SSI ), Geometric Mean Productivity (
GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and
Tolerance Index ( TOL ) to study drought tolerance of genotypes, we
found that the best Stress Index for selection tolerance genotypes
were STI, GMP and MP were the greatest correlations between these
Indices and seed yield under stress and non stress conditions. In
classification of genotypes base on phenotypic characteristics, using
cluster analysis ( UPGMA ), all allels classified in 5 separate groups
in stress and non stress conditions.
Abstract: In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).
Abstract: novel and simple method is introduced for rapid and
highly efficient water treatment by reverse osmosis (RO) method using
multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN)
polymer as a flexible, highly efficient, reusable and semi-permeable
mixed matrix membrane (MMM). For this purpose, MWCNTs were
directly synthesized and on-line purified by chemical vapor deposition
(CVD) process, followed by directing the MWCNT bundles towards an
ultrasonic bath, in which PAN polymer was simultaneously suspended
inside a solid porous silica support in water at temperature to ~70 οC.
Fabrication process of MMM was finally completed by hot isostatic
pressing (HIP) process. In accordance with the analytical figures of
merit, the efficiency of fabricated MMM was ~97%. The rate of water
treatment process was also evaluated to 6.35 L min-1. The results reveal
that, the CNT-based MMM is suitable for rapid treatment of different
forms of industrial, sea, drinking and well water samples.
Abstract: This paper presents a novel method for prediction of
the mechanical behavior of proximal femur using the general
framework of the quantitative computed tomography (QCT)-based
finite element Analysis (FEA). A systematic imaging and modeling
procedure was developed for reliable correspondence between the
QCT-based FEA and the in-vitro mechanical testing. A speciallydesigned
holding frame was used to define and maintain a unique
geometrical reference system during the analysis and testing. The
QCT images were directly converted into voxel-based 3D finite
element models for linear and nonlinear analyses. The equivalent
plastic strain and the strain energy density measures were used to
identify the critical elements and predict the failure patterns. The
samples were destructively tested using a specially-designed gripping
fixture (with five degrees of freedom) mounted within a universal
mechanical testing machine. Very good agreements were found
between the experimental and the predicted failure patterns and the
associated load levels.
Abstract: Based on the thermodynamic theory, the dependence of
sublimation energy of metal on temperature and pressure is discussed,
and the results indicate that the sublimation energy decreases linearly
with the increase of temperature and pressure. Combined with this
result, the blow-off impulse of aluminum induced by pulsed X-ray is
simulated by smoothed particle hydrodynamics (SPH) method. The
numerical results show that, while the change of sublimation energy
with temperature and pressure is considered, the blow-off impulse of
aluminum is larger than the case that the sublimation energy is
assumed to be a constant.
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: We present a hybrid architecture of recurrent neural
networks (RNNs) inspired by hidden Markov models (HMMs). We
train the hybrid architecture using genetic algorithms to learn and
represent dynamical systems. We train the hybrid architecture on a
set of deterministic finite-state automata strings and observe the
generalization performance of the hybrid architecture when presented
with a new set of strings which were not present in the training data
set. In this way, we show that the hybrid system of HMM and RNN
can learn and represent deterministic finite-state automata. We ran
experiments with different sets of population sizes in the genetic
algorithm; we also ran experiments to find out which weight
initializations were best for training the hybrid architecture. The
results show that the hybrid architecture of recurrent neural networks
inspired by hidden Markov models can train and represent dynamical
systems. The best training and generalization performance is
achieved when the hybrid architecture is initialized with random real
weight values of range -15 to 15.
Abstract: In order to study the influence of different methods of controlling weeds such as mechanical weeding and mechanical weeder efficiency analysis in mechanical cultivation conditions, in farming year of 2011 an experiment was done in a farm in coupling and development of technology center in Haraz,Iran. The treatments consisted of (I) control treatment: where no weeding was done, (II) use of mechanical weeding without engine and (III) power mechanical weeding. Results showed that experimental treatments had significantly different effects (p=0.05) on yield traits and number of filled grains per panicle, while treatments had the significant effects on grain weight and dry weight of weeds in the first, second and third weeding methods at 1% of confidence level. Treatment (II) had its most significant effect on number of filled grains per panicle and yield performance standpoint, which was 3705.97 kg ha-1 in its highest peak. Treatment (III) was ranked as second influential with 3559.8 kg ha-1. In addition, under (I) treatments, 2364.73 kg ha-1 of yield produced. The minimum dry weights of weeds in all weeding methods were related to the treatment (II), (III) and (I), respectively. The correlation coefficient analysis showed that total yield had a significant positive correlation with the panicle grain yield per plant (r= 0.55*) and the number of grains per panicle-1 (r= 0.57*) and the number of filled grains (r= 0.63*). Total rice yield also had negative correlation of r= -0. 64* with weed dry weight at second weed sampling time (17 DAT). The weed dry weight at third and fourth sampling times (24 and 40 DAT) had negative correlations of -0.65** and r=-0.61* with rice yield, respectively.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: Cogeneration may be defined as a system which
contains electricity production and regain of the thermo value of
exhaust gases simultaneously. The examination is based on the data-s
of an active cogeneration plant. This study, it is aimed to determine
which component of the system should be revised first to raise the
efficiency and decrease the loss of exergy. For this purpose, second
law analysis of thermodynamics is applied to each component due to
consider the effects of environmental conditions and take the quality
of energy into consideration as well as the quantity of it. The exergy
balance equations are produced and exergy loss is calculated for each
component. 44,44 % loss of exergy in heat exchanger, 29,59 % in
combustion chamber, 18,68 % in steam boiler, 5,25 % in gas turbine
and 2,03 % in compressor is calculated.