Abstract: The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia and to measure the positive effect, if any, of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Abstract: In the Equivalent Transformation (ET) computation
model, a program is constructed by the successive accumulation of
ET rules. A method by meta-computation by which a correct ET
rule is generated has been proposed. Although the method covers a
broad range in the generation of ET rules, all important ET rules
are not necessarily generated. Generation of more ET rules can be
achieved by supplementing generation methods which are specialized
for important ET rules. A Specialization-by-Equation (Speq) rule is
one of those important rules. A Speq rule describes a procedure in
which two variables included in an atom conjunction are equalized
due to predicate constraints. In this paper, we propose an algorithm
that systematically and recursively generate Speq rules and discuss
its effectiveness in the synthesis of ET programs. A Speq rule is
generated based on proof of a logical formula consisting of given
atom set and dis-equality. The proof is carried out by utilizing some
ET rules and the ultimately obtained rules in generating Speq rules.
Abstract: Avionic software architecture has transit from a
federated avionics architecture to an integrated modular avionics
(IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in
Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the
executable model have been brought up, however with less
consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic
interaction order sequence. In this paper, we proposed an
AADL-based model-driven design methodology to fulfill the purpose
to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the
mapping rules between the AADL653 elements and the elements in
Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our
approach. Finally, we give the related work and future research directions.
Abstract: Psoriasis is a chronic inflammatory skin condition
which affects 2-3% of population around the world. Psoriasis Area
and Severity Index (PASI) is a gold standard to assess psoriasis
severity as well as the treatment efficacy. Although a gold standard,
PASI is rarely used because it is tedious and complex. In practice,
PASI score is determined subjectively by dermatologists, therefore
inter and intra variations of assessment are possible to happen even
among expert dermatologists. This research develops an algorithm to
assess psoriasis lesion for PASI scoring objectively. Focus of this
research is thickness assessment as one of PASI four parameters
beside area, erythema and scaliness. Psoriasis lesion thickness is
measured by averaging the total elevation from lesion base to lesion
surface. Thickness values of 122 3D images taken from 39 patients
are grouped into 4 PASI thickness score using K-means clustering.
Validation on lesion base construction is performed using twelve
body curvature models and show good result with coefficient of
determinant (R2) is equal to 1.
Abstract: In this paper, application of artificial neural networks
in typical disease diagnosis has been investigated. The real procedure
of medical diagnosis which usually is employed by physicians was
analyzed and converted to a machine implementable format. Then
after selecting some symptoms of eight different diseases, a data set
contains the information of a few hundreds cases was configured and
applied to a MLP neural network. The results of the experiments and
also the advantages of using a fuzzy approach were discussed as
well. Outcomes suggest the role of effective symptoms selection and
the advantages of data fuzzificaton on a neural networks-based
automatic medical diagnosis system.
Abstract: The most common domestic birds live in Turkey are: crows (Corvus corone), pigeons (Columba livia), sparrows (Passer domesticus), starlings (Sturnus vulgaris) and blackbirds (Turdus merula). These birds give damage to the agricultural areas and make dirty the human life areas. In order to send away these birds, some different materials and methods such as chemicals, treatments, colored lights, flash and audible scarers are used. It is possible to see many studies about chemical methods in the literatures. However there is not enough works regarding audible bird scarers are reported in the literature. Therefore, a solar powered bird scarer was designed, manufactured and tested in this experimental investigation. Firstly, to understand the sensitive level of these domestic birds against to the audible scarer, many series preliminary studies were conducted. These studies showed that crows are the most resistant against to the audible bird scarer when compared with pigeons, sparrows, starlings and blackbirds. Therefore the solar powered audible bird scarer was tested on crows. The scarer was tested about one month during April- May, 2007. 18 different common known predators- sounds (voices or calls) of domestic birds from Falcon (Falco eleonorae), Falcon (Buteo lagopus), Eagle (Aquila chrysaetos), Montagu-s harrier (Circus pygargus) and Owl (Glaucidium passerinum) were selected for test of the scarer. It was seen from the results that the reaction of the birds was changed depending on the predators- sound type, camouflage of the scarer, sound quality and volume, loudspeaker play and pause periods in one application. In addition, it was also seen that the sound from Falcon (Buteo lagopus) was most effective on crows and the scarer was enough efficient.
Abstract: In the paper an effective context based lossless coding
technique is presented. Three principal and few auxiliary contexts are
defined. The predictor adaptation technique is an improved CoBALP
algorithm, denoted CoBALP+. Cumulated predictor error combining
8 bias estimators is calculated. It is shown experimentally that
indeed, the new technique is time-effective while it outperforms the
well known methods having reasonable time complexity, and is
inferior only to extremely computationally complex ones.
Abstract: To study the effect of suitable methods for
propagation of True Potato Seed (TPS) progenies, transplant and
selection of the best progenies, a factorial experiment base on a
randomized complete block design was carried out in the research
field of Sahneh region, Kermanshah, Iran during 2009-2010. Five
selective progenies from CIP (International Potato Center) including
CIP.994013, CIP.994002, CIP.994014, CIP.888006, and
CIP.994001 and two transplant preparation methods (Paper pot
preparation for mechanical cultivation and preparation in transplant
trays for manual cultivation) were studied in three replications.
Results showed that different progenies had no significant effect on
plant height (cm) and tuber yield (t ha-1), whereas had a significant
effect on number of tubers per unit area (m2). There was significant
difference between transplant preparation methods for plant height
and tuber yield. The interaction effect of progenies and transplant
preparation method was not significant for these traits. CIP.888006
progeny and paper pot preparation method produced the highest
tuber yields. Also CIP.994002 and CIP.994014 progenies considered
as the best progenies under paper pot preparation method due to high
yields.
Abstract: This paper presents the development of a wavelet
based algorithm, for distinguishing between magnetizing inrush
currents and power system fault currents, which is quite adequate,
reliable, fast and computationally efficient tool. The proposed
technique consists of a preprocessing unit based on discrete wavelet
transform (DWT) in combination with an artificial neural network
(ANN) for detecting and classifying fault currents. The DWT acts as
an extractor of distinctive features in the input signals at the relay
location. This information is then fed into an ANN for classifying
fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz
laboratory transformer connected to a 380 V power system were
simulated using ATP-EMTP. The DWT was implemented by using
Matlab and Coiflet mother wavelet was used to analyze primary
currents and generate training data. The simulated results presented
clearly show that the proposed technique can accurately discriminate
between magnetizing inrush and fault currents in transformer
protection.
Abstract: Adsorption of CS2 vapors has been studied on
different types of activated carbons obtained from different source
raw materials. The activated carbons have different surface areas and
are associated with varying amounts of the carbon-oxygen surface
groups. The adsorption of CS2 vapors is not directly related to surface
area, but is considerably influenced by the presence of carbonoxygen
surface groups. The adsorption decreases on increasing the
amount of carbon-oxygen surface groups on oxidation and increases
when these surface groups are eliminated on degassing. The
adsorption is maximum in case of the 950°-degassed carbon sample
which is almost completely free of any associated oxygen. The
kinetic data as analysed by Empirical diffusion model and Linear
driving force mass transfer model indicate that the adsorption does
not involve Fickian diffusion but may be considered as a pseudo first
order mass transfer process. The activation energy of adsorption and
isosteric enthalpies of adsorption indicate that the adsorption does not
involve interaction between CS2 and carbon-oxygen surface groups,
but hydrophobic interactions between CS2 and C-C atoms in the
carbon lattice.
Abstract: Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.
Abstract: Today, design requirements are extending more and
more from electronic (analogue and digital) to multidiscipline design.
These current needs imply implementation of methodologies to make
the CAD product reliable in order to improve time to market, study
costs, reusability and reliability of the design process.
This paper proposes a high level design approach applied for the
characterization and the optimization of Switched-Current Sigma-
Delta Modulators. It uses the new hardware description language
VHDL-AMS to help the designers to optimize the characteristics of
the modulator at a high level with a considerably reduced CPU time
before passing to a transistor level characterization.
Abstract: In this paper we have numerically analyzed terahertzrange
wavelength conversion using nondegenerate four wave mixing
(NDFWM) in a SOA integrated DFB laser (experiments reported
both in MIT electronics and Fujitsu research laboratories). For
analyzing semiconductor optical amplifier (SOA), we use finitedifference
beam propagation method (FDBPM) based on modified
nonlinear SchrÖdinger equation and for distributed feedback (DFB)
laser we use coupled wave approach. We investigated wavelength
conversion up to 4THz probe-pump detuning with conversion
efficiency -5dB in 1THz probe-pump detuning for a SOA integrated
quantum-well
Abstract: One of the most important power quality issues is voltage flicker. Nowadays this issue also impacts the power system all over the world. The fact of the matter is that the more and the larger capacity of wind generator has been installed. Under unstable wind power situation, the variation of output current and voltage have caused trouble to voltage flicker. Hence, the major purpose of this study is to analyze the impact of wind generator on voltage flicker of power system. First of all, digital simulation and analysis are carried out based on wind generator operating under various system short circuit capacity, impedance angle, loading, and power factor of load. The simulation results have been confirmed by field measurements.
Abstract: In recent years, the number of the cases of information
leaks is increasing. Companies and Research Institutions make various
actions against information thefts and security accidents. One of the
actions is adoption of the crime prevention system, including the
monitoring system by surveillance cameras. In order to solve
difficulties of multiple cameras monitoring, we develop the automatic
human tracking system using mobile agents through multiple
surveillance cameras to track target persons. In this paper, we develop
the monitor which confirms mobile agents tracing target persons, and
the simulator of video picture analysis to construct the tracking
algorithm.
Abstract: The history of technology and banking is examined as
it relates to risk and technological determinism. It is proposed that
the services that banks offer are determined by technology and that
banks must adopt new technologies to be competitive. The adoption
of technologies paradoxically forces the adoption of other new
technologies to protect the bank from the increased risk of
technology. This cycle will lead to bank examiners and regulators to
focus on human behavior, not on the ever changing technology.
Abstract: An approach for experimental measurement of the
dynamic characteristics of linear electromagnet actuators is
presented. It uses accelerometer sensor to register the armature
acceleration. The velocity and displacement of the moving parts can
be obtained by integration of the acceleration results. The armature
movement of permanent magnet linear actuator is acquired using this
technique. The results are analyzed and the performance of the
supposed approach is compared with the most commonly used
experimental setup where the displacement of the armature vs. time
is measured instead of its acceleration.
Abstract: In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Abstract: The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.