Abstract: We suggest a novel method to incorporate longterm
redundancy (LTR) in signal time domain compression
methods. The proposition is based on block-sorting and curve
simplification. The proposition is illustrated on the ECG
signal as a post-processor for the FAN method. Test
applications on the new so-obtained FAN+ method using the
MIT-BIH database show substantial improvement of the
compression ratio-distortion behavior for a higher quality
reconstructed signal.
Abstract: Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
Abstract: The development of information and communication
technology, the increased use of the internet, as well as the effects of
the recession within the last years, have lead to the increased use of
cloud computing based solutions, also called on-demand solutions.
These solutions offer a large number of benefits to organizations as
well as challenges and risks, mainly determined by data visualization
in different geographic locations on the internet. As far as the specific
risks of cloud environment are concerned, data security is still
considered a peak barrier in adopting cloud computing. The present
study offers an approach upon ensuring the security of cloud data,
oriented towards the whole data life cycle. The final part of the study
focuses on the assessment of data security in the cloud, this
representing the bases in determining the potential losses and the
premise for subsequent improvements and continuous learning.
Abstract: Insulation used in transformer is mostly oil pressboard insulation. Insulation failure is one of the major causes of catastrophic failure of transformers. It is established that partial discharges (PD) cause insulation degradation and premature failure of insulation. Online monitoring of PDs can reduce the risk of catastrophic failure of transformers. There are different techniques of partial discharge measurement like, electrical, optical, acoustic, opto-acoustic and ultra high frequency (UHF). Being non invasive and non interference prone, acoustic emission technique is advantageous for online PD measurement. Acoustic detection of p.d. is based on the retrieval and analysis of mechanical or pressure signals produced by partial discharges. Partial discharges are classified according to the origin of discharges. Their effects on insulation deterioration are different for different types. This paper reports experimental results and analysis for classification of partial discharges using acoustic emission signal of laboratory simulated partial discharges in oil pressboard insulation system using three different electrode systems. Acoustic emission signal produced by PD are detected by sensors mounted on the experimental tank surface, stored on an oscilloscope and fed to computer for further analysis. The measured AE signals are analyzed using discrete wavelet transform analysis and wavelet packet analysis. Energy distribution in different frequency bands of discrete wavelet decomposed signal and wavelet packet decomposed signal is calculated. These analyses show a distinct feature useful for PD classification. Wavelet packet analysis can sort out any misclassification arising out of DWT in most cases.
Abstract: A comparative study on the feasibility of producing instant high fibre plantain flour for diabetic fufu by blending soy residence with different plantain (Musa spp) varieties (Horn, false Horn and French), all sieved at 60 mesh, mixed in ratio of 60:40 was analyzed for their passing properties using standard analytical method. Results show that VIIIS60 had the highest peak viscosity (303.75 RVU), Trough value (182.08 RVU), final viscosity (284.50 RVU), and lowest in breakdown viscosity (79.58 RVU), set back value (88.17 RVU), peak time (4.36min), pasting temperature (81.18°C) and differed significantly (p
Abstract: The current research paper is an implementation of
Eigen Faces and Karhunen-Loeve Algorithm for face recognition.
The designed program works in a manner where a unique
identification number is given to each face under trial. These faces
are kept in a database from where any particular face can be matched
and found out of the available test faces. The Karhunen –Loeve
Algorithm has been implemented to find out the appropriate right
face (with same features) with respect to given input image as test
data image having unique identification number. The procedure
involves usage of Eigen faces for the recognition of faces.
Abstract: In this paper, an ultrasonic technique is proposed to
predict oil content in a fresh palm fruit. This is accomplished by
measuring the attenuation based on ultrasonic transmission mode.
Several palm fruit samples with known oil content by Soxhlet
extraction (ISO9001:2008) were tested with our ultrasonic
measurement. Amplitude attenuation data results for all palm samples
were collected. The Feedforward Neural Networks (FNNs) are
applied to predict the oil content for the samples. The Root Mean
Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN
model for predicting oil content percentage are 7.6186 and 5.2287
with the correlation coefficient (R) of 0.9193.
Abstract: Noise causes significant sensibility changes on a human. This study investigated the effect of five different noises on electroencephalogram (EEG) and subjective evaluation. Six human subjects were exposed to classic piano, ocean wave, alarm in army, ambulance, mosquito noise and EEG data were collected during the experimental session. Alpha band activity in the mosquito noise was smaller than that in the classic piano. Alpha band activity decreased 43.4 ± 8.2 % in the mosquito noise. On the other hand, Beta band activity in the mosquito noise was greater than that in the classic piano. Beta band activity increased 60.1 ± 10.7 % in the mosquito noise. The advances from this study may aid the product design process with human sensibility engineering. This result may provide useful information in designing a human-oriented product to avoid the stress.
Abstract: In Thailand, both the 1997 and the current 2007 Thai Constitutions have mentioned the establishment of independent organizations as a new mechanism to play a key role in proposing policy recommendations to national decision-makers in the interest of collective consumers. Over the last ten years, no independent organizations have yet been set up. Evidently, nobody could point out who should be key players in establishing provincial independent consumer bodies. The purpose of this study was to find definitive stakeholders in establishing and developing independent consumer bodies in a Thai context. This was a cross-sectional study between August and September 2007, using a postal questionnaire with telephone follow-up. The questionnaire was designed and used to obtain multiple stakeholder assessment of three key attributes (power, interest and influence). Study population was 153 stakeholders associated with policy decision-making, formulation and implementation processes of civil-based consumer protection in pilot provinces. The population covered key representatives from five sectors (academics, government officers, business traders, mass media and consumer networks) who participated in the deliberative forums at 10 provinces. A 49.7% response rate was achieved. Data were analyzed, comparing means of three stakeholder attributes and classification of stakeholder typology. The results showed that the provincial health officers were the definitive stakeholders as they had legal power, influence and interest in establishing and sustaining the independent consumer bodies. However, only a few key representatives of the provincial health officers expressed their own paradigm on the civil-based consumer protection. Most provincial health officers put their own standpoint of building civic participation at only a plan-implementation level. For effective policy implementation by the independent consumer bodies, the Thai government should provide budgetary support for the operation of the provincial health officers with their paradigm shift as well as their own clarified standpoint on corporate governance.
Abstract: Security risk models have been successful in estimating the likelihood of attack for simple security threats. However, modeling complex system and their security risk is even a challenge. Many methods have been proposed to face this problem. Often difficult to manipulate, and not enough all-embracing they are not as famous as they should with administrators and deciders. We propose in this paper a new tool to model big systems on purpose. The software, takes into account attack threats and security strength.
Abstract: Most parts of the world such as Iran are facing the excessive consumption of fertilizers, that are used to achieve high yield, but increase the cost of production of fertilizer and degradation of soil and water resources. This experiment was carried out to study the effect of PGPR and planting pattern on yield and yield components of rice (Oryza sativa L.) using split plot based on randomized complete block design with three replications in Ilam province, Iran. Bio-fertilizer including Azotobacter, Nitroxin and control treatment (without consumption) were designed as a main plot and planting pattern including 15 × 10, 15 × 15 and 15 × 20 and the number of plant in hill including 3, 4 and 5 plants in hill were considered as a sub-plots. The results showed that the effect of bio-fertilizers, planting pattern and the number of plants in hill were significant affect on yield and yield components. Interaction effect between bio-fertilizer and planting pattern had important difference on the number spikelet of panicle and harvest index. Interaction effect between bio-fertilizer and the number of plants in hill were significant affect on the number of spikelet per panicle. The maximum grain yield was obtained by inoculation with Nitroxin, planting pattern of 15 × 15 and 4 plants in hill with mean of 1110.6 g.m-2, 959.9 g.m-2 and 928.4 g.m-2, respectively.
Abstract: The neural stimulation has been gaining much interest in neuromodulation research and clinical trials. For efficiency, there is a need for variable electrical stimulation such as current and voltage stimuli as well as wireless framework. In this regard, we develop the wireless neural stimulator capable of voltage and current stimuli. The system consists of ZigBee which is a wireless communication module and stimulus generator. The stimulus generator with 8-bits resolution enable both mono-polar and bi-polar waveform in voltage (-3.3~3.3V) and current(-330~330µA) stimulus mode which is controllable. The experimental results suggest that the proposed neural stimulator can play a role as an effective approach for neuromodulation.
Abstract: The counting process of cell colonies is always a long
and laborious process that is dependent on the judgment and ability
of the operator. The judgment of the operator in counting can vary in
relation to fatigue. Moreover, since this activity is time consuming it
can limit the usable number of dishes for each experiment. For these
purposes, it is necessary that an automatic system of cell colony
counting is used. This article introduces a new automatic system of
counting based on the elaboration of the digital images of cellular
colonies grown on petri dishes. This system is mainly based on the
algorithms of region-growing for the recognition of the regions of
interest (ROI) in the image and a Sanger neural net for the
characterization of such regions. The better final classification is
supplied from a Feed-Forward Neural Net (FF-NN) and confronted
with the K-Nearest Neighbour (K-NN) and a Linear Discriminative
Function (LDF). The preliminary results are shown.
Abstract: In this work, we present a reliable framework to solve boundary value problems with particular significance in solid mechanics. These problems are used as mathematical models in deformation of beams. The algorithm rests mainly on a relatively new technique, the Variational Iteration Method. Some examples are given to confirm the efficiency and the accuracy of the method.
Abstract: Copper based composites reinforced with WC and Ti
particles were prepared using planetary ball-mill. The experiment
was designed by using Taguchi technique and milling was carried out
in an air for several hours. The powder was characterized before and
after milling using the SEM, TEM and X-ray for microstructure and
for possible new phases. Microstructures show that milled particles
size and reduction in particle size depend on many parameters. The
distance d between planes of atoms estimated from X-ray powder
diffraction data and TEM image. X-ray diffraction patterns of the
milled powder did not show clearly any new peak or energy shift, but
the TEM images show a significant change in crystalline structure of
corporate on titanium in the composites.
Abstract: This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Abstract: Alcohol and water extracts of Cymbopogon citratus
was investigated for anti-bacterial properties and phytochemical
constituents. The extract was screened against four gram-negative
bacteria Escherichia coli, Klebsiella pneumoniae, Pseudomonas
aeruginosa, Proteus vulgaris) and two grampositive bacteria Bacillus
subtilis and Staphylococcus aureus at four different concentrations
(1:1, 1:5, 1:10 and 1:20) using disc diffusion method. The antibacterial
examination was by disc diffusion techniques, while the
photochemical constituents were investigated using standard
chemical methods. Results showed that the extracts inhibited the
growth of standard and local strains of the organisms used. The
treatments were significantly different (P = 0.05). The minimum
inhibitory concentration of the extracts against the tested
microorganisms ranged between 150mg/ml and 50mg/ml. The
alcohol extracts were found to be generally more effective than the
water extract. The photochemical analysis revealed the presence of
alkaloids and phenol but absence of cardiac and cyanogenic
glycosides. The presence of alkaloid and phenols were inferred as
being responsible for the anti-bacterial properties of the extracts.
Abstract: The cup method is applied for the measurement of water vapor transport properties of porous materials worldwide. However, in practical applications the experimental results are often used without taking into account some secondary effects which can play an important role under specific conditions. In this paper, the effect of temperature on water vapor transport properties of cellular concrete is studied, together with the influence of sample thickness. At first, the bulk density, matrix density, total open porosity and sorption and desorption isotherms are measured for material characterization purposes. Then, the steady state cup method is used for determination of water vapor transport properties, whereas the measurements are performed at several temperatures and for three different sample thicknesses.
Abstract: In the world of Peer-to-Peer (P2P) networking
different protocols have been developed to make the resource sharing
or information retrieval more efficient. The SemPeer protocol is a
new layer on Gnutella that transforms the connections of the nodes
based on semantic information to make information retrieval more
efficient. However, this transformation causes high clustering in the
network that decreases the number of nodes reached, therefore the
probability of finding a document is also decreased. In this paper we
describe a mathematical model for the Gnutella and SemPeer
protocols that captures clustering-related issues, followed by a
proposition to modify the SemPeer protocol to achieve moderate
clustering. This modification is a sort of link management for the
individual nodes that allows the SemPeer protocol to be more
efficient, because the probability of a successful query in the P2P
network is reasonably increased. For the validation of the models, we
evaluated a series of simulations that supported our results.
Abstract: Software project effort estimation is frequently seen
as complex and expensive for individual software engineers.
Software production is in a crisis. It suffers from excessive costs.
Software production is often out of control. It has been suggested that
software production is out of control because we do not measure.
You cannot control what you cannot measure. During last decade, a
number of researches on cost estimation have been conducted. The
metric-set selection has a vital role in software cost estimation
studies; its importance has been ignored especially in neural network
based studies. In this study we have explored the reasons of those
disappointing results and implemented different neural network
models using augmented new metrics. The results obtained are
compared with previous studies using traditional metrics. To be able
to make comparisons, two types of data have been used. The first
part of the data is taken from the Constructive Cost Model
(COCOMO'81) which is commonly used in previous studies and the
second part is collected according to new metrics in a leading
international company in Turkey. The accuracy of the selected
metrics and the data samples are verified using statistical techniques.
The model presented here is based on Multi-Layer Perceptron
(MLP). Another difficulty associated with the cost estimation studies
is the fact that the data collection requires time and care. To make a
more thorough use of the samples collected, k-fold, cross validation
method is also implemented. It is concluded that, as long as an
accurate and quantifiable set of metrics are defined and measured
correctly, neural networks can be applied in software cost estimation
studies with success