Abstract: Parsing is important in Linguistics and Natural
Language Processing to understand the syntax and semantics of a
natural language grammar. Parsing natural language text is
challenging because of the problems like ambiguity and inefficiency.
Also the interpretation of natural language text depends on context
based techniques. A probabilistic component is essential to resolve
ambiguity in both syntax and semantics thereby increasing accuracy
and efficiency of the parser. Tamil language has some inherent
features which are more challenging. In order to obtain the solutions,
lexicalized and statistical approach is to be applied in the parsing
with the aid of a language model. Statistical models mainly focus on
semantics of the language which are suitable for large vocabulary
tasks where as structural methods focus on syntax which models
small vocabulary tasks. A statistical language model based on Trigram
for Tamil language with medium vocabulary of 5000 words has
been built. Though statistical parsing gives better performance
through tri-gram probabilities and large vocabulary size, it has some
disadvantages like focus on semantics rather than syntax, lack of
support in free ordering of words and long term relationship. To
overcome the disadvantages a structural component is to be
incorporated in statistical language models which leads to the
implementation of hybrid language models. This paper has attempted
to build phrase structured hybrid language model which resolves
above mentioned disadvantages. In the development of hybrid
language model, new part of speech tag set for Tamil language has
been developed with more than 500 tags which have the wider
coverage. A phrase structured Treebank has been developed with 326
Tamil sentences which covers more than 5000 words. A hybrid
language model has been trained with the phrase structured Treebank
using immediate head parsing technique. Lexicalized and statistical
parser which employs this hybrid language model and immediate
head parsing technique gives better results than pure grammar and
trigram based model.
Abstract: A concrete structure is designed and constructed for its
purpose of use, and is expected to maintain its function for the target
durable years from when it was planned. Nevertheless, as time elapses
the structure gradually deteriorates and then eventually degrades to the
point where the structure cannot exert the function for which it was
planned. The performance of concrete that is able to maintain the level
of the performance required over the designed period of use as it has
less deterioration caused by the elapse of time under the designed
condition is referred to as Durability. There are a number of causes of
durability degradation, but especially chloride damage, carbonation,
freeze-thaw, etc are the main causes. In this study, carbonation, one of
the main causes of deterioration of the durability of a concrete
structure, was investigated via a microstructure analysis technique.
The method for the measurement of carbonation was studied using the
existing indicator method, and the method of measuring the progress
of carbonation in a quantitative manner was simultaneously studied
using a FT-IR (Fourier-Transform Infrared) Spectrometer along with
the microstructure analysis technique.
Abstract: Grid environments include aggregation of
geographical distributed resources. Grid is put forward in three types
of computational, data and storage. This paper presents a research on
data grid. Data grid is used for covering and securing accessibility to
data from among many heterogeneous sources. Users are not worry
on the place where data is located in it, provided that, they should get
access to the data. Metadata is used for getting access to data in data
grid. Presently, application metadata catalogue and SRB middle-ware
package are used in data grids for management of metadata. At this
paper, possibility of updating, streamlining and searching is provided
simultaneously and rapidly through classified table of preserving
metadata and conversion of each table to numerous tables.
Meanwhile, with regard to the specific application, the most
appropriate and best division is set and determined. Concurrency of
implementation of some of requests and execution of pipeline is
adaptability as a result of this technique.
Abstract: Installation of power compensation equipment in
some cases places additional buses into the system. Therefore, a total
number of power flow equations and voltage unknowns increase due
to additional locations of installed devices. In this circumstance, power flow calculation is more complicated. It may result in a
computational convergence problem. This paper presents a power flow calculation by using Newton-Raphson iterative method together
with the proposed load transfer technique. This concept is to eliminate additional buses by transferring installed loads at the new buses to existing two adjacent buses. Thus, the total number of power
flow equations is not changed. The overall computational speed is
expectedly shorter than that of solving the problem without applying the load transfer technique. A 15-bus test system is employed for test
to evaluate the effectiveness of the proposed load transfer technique. As a result, the total number of iteration required and execution time
is significantly reduced.
Abstract: This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.
Abstract: Dynamic characteristics of a four-lobe journal bearing
of micropolar fluids are presented. Lubricating oil containing
additives and contaminants is modelled as micropolar fluid. The
modified Reynolds equation is obtained using the micropolar
lubrication theory and solving it by using finite difference technique.
The dynamic characteristics in terms of stiffness, damping
coefficients, the critical mass and whirl ratio are determined for
various values of size of material characteristic length and the
coupling number. The results show compared with Newtonian fluids,
that micropolar fluid exhibits better stability.
Abstract: This paper proposed a novel model for short term load
forecast (STLF) in the electricity market. The prior electricity
demand data are treated as time series. The model is composed of
several neural networks whose data are processed using a wavelet
technique. The model is created in the form of a simulation program
written with MATLAB. The load data are treated as time series data.
They are decomposed into several wavelet coefficient series using
the wavelet transform technique known as Non-decimated Wavelet
Transform (NWT). The reason for using this technique is the belief
in the possibility of extracting hidden patterns from the time series
data. The wavelet coefficient series are used to train the neural
networks (NNs) and used as the inputs to the NNs for electricity load
prediction. The Scale Conjugate Gradient (SCG) algorithm is used as
the learning algorithm for the NNs. To get the final forecast data, the
outputs from the NNs are recombined using the same wavelet
technique. The model was evaluated with the electricity load data of
Electronic Engineering Department in Mandalay Technological
University in Myanmar. The simulation results showed that the
model was capable of producing a reasonable forecasting accuracy in
STLF.
Abstract: In this article, by using fuzzy AHP and TOPSIS
technique we propose a new method for project selection problem.
After reviewing four common methods of comparing alternatives
investment (net present value, rate of return, benefit cost analysis
and payback period) we use them as criteria in AHP tree. In this
methodology by utilizing improved Analytical Hierarchy Process
by Fuzzy set theory, first we try to calculate weight of each
criterion. Then by implementing TOPSIS algorithm, assessment of
projects has been done. Obtained results have been tested in a
numerical example.
Abstract: Public health surveillance system focuses on outbreak detection and data sources used. Variation or aberration in the frequency distribution of health data, compared to historical data is often used to detect outbreaks. It is important that new techniques be developed to improve the detection rate, thereby reducing wastage of resources in public health. Thus, the objective is to developed technique by applying frequent mining and outlier mining techniques in outbreak detection. 14 datasets from the UCI were tested on the proposed technique. The performance of the effectiveness for each technique was measured by t-test. The overall performance shows that DTK can be used to detect outlier within frequent dataset. In conclusion the outbreak detection technique using anomaly-based on frequent-outlier technique can be used to identify the outlier within frequent dataset.
Abstract: The present study has been carried out with a view to calculate the coastal vulnerability index (CVI) to know the high and low sensitive areas and area of inundation due to future SLR. Both conventional and remotely sensed data were used and analyzed through the modelling technique. Out of the total study area, 8.26% is very high risk, 14.21% high, 9.36% medium, 22.46% low and 7.35% in the very low vulnerable category, due to costal components. Results of the inundation analysis indicate that 225.2 km² and 397 km² of the land area will be submerged by flooding at 1m and 10m inundation levels. The most severely affected sectors are expected to be the residential, industrial and recreational areas. As this coast is planned for future coastal developmental activities, measures such as industrializations, building regulation, urban growth planning and agriculture, development of an integrated coastal zone management, strict enforcement of the Coastal Regulation Zone (CRZ) Act, monitoring of impacts and further research in this regard are recommended for the study area.
Abstract: In this paper, hybrid FDMA-TDMA access technique in a cooperative distributive fashion introducing and implementing a modified protocol introduced in [1] is analyzed termed as Power and Cooperation Diversity Gain Protocol (PCDGP). A wireless network consists of two users terminal , two relays and a destination terminal equipped with two antennas. The relays are operating in amplify-and-forward (AF) mode with a fixed gain. Two operating modes: cooperation-gain mode and powergain mode are exploited from source terminals to relays, as it is working in a best channel selection scheme. Vertical BLAST (Bell Laboratories Layered Space Time) or V-BLAST with minimum mean square error (MMSE) nulling is used at the relays to perfectly detect the joint signals from multiple source terminals. The performance is analyzed using binary phase shift keying (BPSK) modulation scheme and investigated over independent and identical (i.i.d) Rayleigh, Ricean-K and Nakagami-m fading environments. Subsequently, simulation results show that the proposed scheme can provide better signal quality of uplink users in a cooperative communication system using hybrid FDMATDMA technique.
Abstract: Selection of a project among a set of possible
alternatives is a difficult task that the decision maker (DM) has to
face. In this paper, by using a fuzzy TOPSIS technique we propose a
new method for a project selection problem. After reviewing four
common methods of comparing investment alternatives (net present
value, rate of return, benefit cost analysis and payback period) we
use them as criteria in a TOPSIS technique. First we calculate the
weight of each criterion by a pairwise comparison and then we utilize
the improved TOPSIS assessment for the project selection.