Abstract: Classification of electroencephalogram (EEG) signals
extracted during mental tasks is a technique that is actively pursued
for Brain Computer Interfaces (BCI) designs. In this paper, we
compared the classification performances of univariateautoregressive
(AR) and multivariate autoregressive (MAR) models
for representing EEG signals that were extracted during different
mental tasks. Multilayer Perceptron (MLP) neural network (NN)
trained by the backpropagation (BP) algorithm was used to classify
these features into the different categories representing the mental
tasks. Classification performances were also compared across
different mental task combinations and 2 sets of hidden units (HU): 2
to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different
mental tasks from 4 subjects were used in the experimental study and
combinations of 2 different mental tasks were studied for each
subject. Three different feature extraction methods with 6th order
were used to extract features from these EEG signals: AR
coefficients computed with Burg-s algorithm (ARBG), AR
coefficients computed with stepwise least square algorithm (ARLS)
and MAR coefficients computed with stepwise least square
algorithm. The best results were obtained with 20 to 100 HU using
ARBG. It is concluded that i) it is important to choose the suitable
mental tasks for different individuals for a successful BCI design, ii)
higher HU are more suitable and iii) ARBG is the most suitable
feature extraction method.
Abstract: In this paper, we propose a new method to distinguish
between arousal and relaxation states by using multiple features
acquired from a photoplethysmogram (PPG) and support vector
machine (SVM). To induce arousal and relaxation states in subjects, 2
kinds of sound stimuli are used, and their corresponding biosignals are
obtained using the PPG sensor. Two features–pulse to pulse interval
(PPI) and pulse amplitude (PA)–are extracted from acquired PPG
data, and a nonlinear classification between arousal and relaxation is
performed using SVM.
This methodology has several advantages when compared with
previous similar studies. Firstly, we extracted 2 separate features from
PPG, i.e., PPI and PA. Secondly, in order to improve the classification
accuracy, SVM-based nonlinear classification was performed.
Thirdly, to solve classification problems caused by generalized
features of whole subjects, we defined each threshold according to
individual features.
Experimental results showed that the average classification
accuracy was 74.67%. Also, the proposed method showed the better
identification performance than the single feature based methods.
From this result, we confirmed that arousal and relaxation can be
classified using SVM and PPG features.
Abstract: Manufacturing companies are facing a broad variety
of challenges caused by a dynamic production environment. To
succeed in such an environment, it is crucial to minimize the loss of
time required to trigger the adaptation process of a company-s
production structures. This paper presents an approach for the
continuous monitoring of production structures by neurologic
principles. It enhances classical monitoring concepts, which are
principally focused on reactive strategies, and enables companies to
act proactively. Thereby, strategic aspects regarding the
harmonization of certain life cycles are integrated into the decision
making process for triggering the reconfiguration process of the
production structure.
Abstract: Importance of strategic planning is unquestionable. However, the practical implementation of a strategic plan faces too many obstacles. The aim of the article is explained the importance of strategic planning and to find how companies in Moravian-Silesian Region deal with strategic planning, and to introduce the model, which helps to set strategic goals in financial indicators area. This model should be part of the whole process of strategic planning and can be use to predict the future values of financial indicators of the company with regard to the factor, which influence these indicators.
Abstract: This paper presents a subjective job scheduler based
on a 3-layer Backpropagation Neural Network (BPNN) and a greedy
alignment procedure in order formulates a real-life situation. The
BPNN estimates critical values of jobs based on the given subjective
criteria. The scheduler is formulated in such a way that, at each time
period, the most critical job is selected from the job queue and is
transferred into a single machine before the next periodic job arrives.
If the selected job is one of the oldest jobs in the queue and its
deadline is less than that of the arrival time of the current job, then
there is an update of the deadline of the job is assigned in order to
prevent the critical job from its elimination. The proposed
satisfiability criteria indicates that the satisfaction of the scheduler
with respect to performance of the BPNN, validity of the jobs and the
feasibility of the scheduler.
Abstract: Organic farmers across Saskatchewan face soil
phosphorus (P) shortages. Due to the restriction on inputs in organic
systems, farmers rely on crop rotation and naturally-occurring
arbuscular mycorrhizal fungi (AMF) for plant P supply. Crop rotation
is important for disease, pest, and weed management. Crops that are
not colonized by AMF (non-mycorrhizal) can decrease colonization
of a following crop. An experiment was performed to quantify soil P
cycling in four cropping sequences under organic management and
determine if mustard (non-mycorrhizal) was delaying the
colonization of subsequent wheat. Soils from the four cropping
sequences were measured for inorganic soil P (Pi), AMF spore
density (SD), phospholipid fatty acid analysis (PLFA, for AMF
biomarker counts), and alkaline phosphatase activity (ALPase,
related to AMF metabolic activity). Plants were measured for AMF
colonization and P content and uptake of above-ground biomass. A
lack of difference in AMF activity indicated that mustard was not
depressing colonization. Instead, AMF colonization was largely
determined by crop type and crop rotation.
Abstract: Power System Security is a major concern in real time
operation. Conventional method of security evaluation consists of
performing continuous load flow and transient stability studies by
simulation program. This is highly time consuming and infeasible
for on-line application. Pattern Recognition (PR) is a promising
tool for on-line security evaluation. This paper proposes a Support
Vector Machine (SVM) based binary classification for static and
transient security evaluation. The proposed SVM based PR approach
is implemented on New England 39 Bus and IEEE 57 Bus systems.
The simulation results of SVM classifier is compared with the other
classifier algorithms like Method of Least Squares (MLS), Multi-
Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA)
classifiers.
Abstract: This paper presents a multiband CPW-fed slot antenna
with L-slot bowtie tuning stub. The proposed antenna has been
designed for PCS 1900, UMTS, WLAN 802.11 a/b/g and bluetooth
applications, with a cost-effective FR4 substrate. The proposed
antenna still radiate as omni-directional in azimuth plane and
sufficient bandwidth for all above mentions. The proposed antenna
works as dual-wideband, bandwidth at low frequency band and high
frequency are about 45.49 % and 22.39 % respectively. The
experimental results of the constructed prototype are presented and
also compared with simulation results using a commercial software
tool.
Abstract: Due to rapid economic growth, Indonesia's energy needs is rapidly increasing. Indonesia-s primary energy consumption has doubled in 2007 compared to 2003. Indonesia's status change from oil net-exporter to oil net-importer country recently has increased Indonesia's concern over energy security. Due to this, oil import becomes center of attention in the dynamics of Indonesia's energy security. Conventional studies addressing Indonesia's energy security have focused on energy production sector. This study explores Indonesia-s energy security considering energy import sector by modeling and simulating Indonesia-s energy-related policies using system dynamics. Simulation result of Indonesia's energy security in 2020 in Business-As-Usual scenario shows that in term of supply demand ratio, energy security will be very high, but also it poses high dependence on energy import. The Alternative scenario result shows lower energy security in term of supply demand ratio and much lower dependence on energy import. It is also found that the Alternative scenario produce lower GDP growth.
Abstract: The aim of the paper work is to investigate and predict
the static performance of journal bearing in turbulent flow condition
considering micropolar lubrication. The Reynolds equation has been
modified considering turbulent micropolar lubrication and is solved
for steady state operations. The Constantinescu-s turbulence model is
adopted using the coefficients. The analysis has been done for a
parallel and inertia less flow. Load capacity and friction factor have
been evaluated for various operating parameters.
Abstract: According to celebrated Hurwitz theorem, there exists
four division algebras consisting of R (real numbers), C (complex
numbers), H (quaternions) and O (octonions). Keeping in view
the utility of octonion variable we have tried to extend the three
dimensional vector analysis to seven dimensional one. Starting with
the scalar and vector product in seven dimensions, we have redefined
the gradient, divergence and curl in seven dimension. It is shown
that the identity n(n - 1)(n - 3)(n - 7) = 0 is satisfied only
for 0, 1, 3 and 7 dimensional vectors. We have tried to write all
the vector inequalities and formulas in terms of seven dimensions
and it is shown that same formulas loose their meaning in seven
dimensions due to non-associativity of octonions. The vector formulas
are retained only if we put certain restrictions on octonions and split
octonions.
Abstract: Stairway Ushtobin Village is one of the five villages with original and sustainable architecture in Northwest of Iran along the border of Armenia, which has been able to maintain its environment and sustainable ecosystem. Studying circulation, function and scale (grand, medium and minor) of space, ratio of full and empty spaces, number and height of stairs, ratio of compound volume to luxury spaces, openings, type of local masonry (stone, mud, wood) and form of covering elements have been carried out in four houses of this village comparatively as some samples in this article, and furthermore, this article analyzes that the architectural shapes and organic texture of the village meet the needs of cold and dry climate. Finally, some efficient plans are offered suiting the present needs of the village to have a sustainable architecture.
Abstract: Utilization of waste material in asphalt pavement
would be beneficial in order to find an alternative solution to increase
service life of asphalt pavement and reduce environmental pollution
as well. One of these waste materials is Polyethylene Terephthalate
(PET) which is a type of polyester material and is produced in a large
extent. This research program is investigating the effects of adding
waste PET particles into the asphalt mixture with a maximum size of
2.36 mm. Different percentages of PET were added into the mixture
during dry process. Gap-graded mixture (SMA 14) and PG 80-100
asphalt binder have been used for this study. To evaluate PET
reinforced asphalt mixture different laboratory investigations have
been conducted on specimens. Marshall Stability test was carried
out. Besides, stiffness modulus test and indirect tensile fatigue test
were conducted on specimens at optimum asphalt content. It was
observed that in many cases PET reinforced SMA mixture had better
mechanical properties in comparison with control mixture.
Abstract: In this work a visual and reactive contour following
behaviour is learned by reinforcement. With artificial vision the
environment is perceived in 3D, and it is possible to avoid obstacles
that are invisible to other sensors that are more common in mobile
robotics. Reinforcement learning reduces the need for intervention in
behaviour design, and simplifies its adjustment to the environment,
the robot and the task. In order to facilitate its generalisation to other
behaviours and to reduce the role of the designer, we propose a
regular image-based codification of states. Even though this is much
more difficult, our implementation converges and is robust. Results
are presented with a Pioneer 2 AT on a Gazebo 3D simulator.
Abstract: A new hybrid method to realise high-precision
distortion determination for optical ultra-precision 3D measurement
systems based on stereo cameras using active light projection is
introduced. It consists of two phases: the basic distortion
determination and the refinement. The refinement phase of the
procedure uses a plane surface and projected fringe patterns as
calibration tools to determine simultaneously the distortion of both
cameras within an iterative procedure. The new technique may be
performed in the state of the device “ready for measurement" which
avoids errors by a later adjustment. A considerable reduction of
distortion errors is achieved and leads to considerable improvements
of the accuracy of 3D measurements, especially in the precise
measurement of smooth surfaces.
Abstract: Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
Abstract: A simple analytical model has been developed to
optimize biasing conditions for obtaining maximum linearity among
lattice-matched, pseudomorphic and metamorphic HEMT types as
well as enhancement and depletion HEMT modes. A nonlinear
current-voltage model has been simulated based on extracted data to
study and select the most appropriate type and mode of HEMT in
terms of a given gate-source biasing voltage within the device so as
to employ the circuit for the highest possible output current or
voltage linear swing. Simulation results can be used as a basis for the
selection of optimum gate-source biasing voltage for a given type
and mode of HEMT with regard to a circuit design. The
consequences can also be a criterion for choosing the optimum type
or mode of HEMT for a predetermined biasing condition.
Abstract: The increasing recognition of the need for education to be closely aligned with team playing, project based learning and problem solving approaches has increase the interest in collaborative learning among university and college instructors. Using online collaboration learning in learning can enhance the outcome and achievement of students as well as improve their communication, critical thinking and personnel skills. The current research aims at examining the effect of OCL on the student's achievement at Kingdom of Bahrain. Numbers of objectives were set to achieve the aim of the research include: investigating the current situation regarding the collaborative learning and OCL at the Kingdom of Bahrain by identifying the advantages and effectiveness of OCL as a learning tool over traditional learning, examining the factors that affect OCL as well as examining the impact of OCL on the student's achievement. To achieve these objectives, quantitative method was adopted. Two hundred and thirty one questionnaires were distributed to students in different local and private universities at Kingdom of Bahrain. The findings of the research show that most of the students prefer to use FTFCL in learning and that OCL is already adopted in some universities especially in University of Bahrain. Moreover, the most factors affecting the adopted OCL are perceived readiness, and guidance and support.
Abstract: Pyrite (FeS2) is a promising candidate for cathode
materials in batteries because of it`s high theoretical capacity, low
cost and non-toxicity. In this study, nano size iron disulfide thin film
was prepared on graphite substrate through a new method as battery
cathode. In this way, acetylene black and poly vinylidene fluoride
were used as electron conductor and binder, respectively. Fabricated
thin films were analyzed by XRD and SEM. These results and
electrochemical data confirm improvement of battery discharge
capacity in comparison with commercial type of pyrite.
Abstract: This paper presents a method of reducing the feedback
delay time of DWA(Data Weighted Averaging) used in sigma-delta
modulators. The delay time reduction results from the elimination of
the latch at the quantizer output and also from the falling edge
operation. The designed sigma-delta modulator improves the timing
margin about 16%. The sub-circuits of sigma-delta modulator such as
SC(Switched Capacitor) integrator, 9-level quantizer, comparator, and
DWA are designed with the non-ideal characteristics taken into
account. The sigma-delta modulator has a maximum SNR (Signal to
Noise Ratio) of 84 dB or 13 bit resolution.