Abstract: During the past several years, face recognition in video
has received significant attention. Not only the wide range of
commercial and law enforcement applications, but also the availability
of feasible technologies after several decades of research contributes
to the trend. Although current face recognition systems have reached a
certain level of maturity, their development is still limited by the
conditions brought about by many real applications. For example,
recognition images of video sequence acquired in an open
environment with changes in illumination and/or pose and/or facial
occlusion and/or low resolution of acquired image remains a largely
unsolved problem. In other words, current algorithms are yet to be
developed. This paper provides an up-to-date survey of video-based
face recognition research. To present a comprehensive survey, we
categorize existing video based recognition approaches and present
detailed descriptions of representative methods within each category.
In addition, relevant topics such as real time detection, real time
tracking for video, issues such as illumination, pose, 3D and low
resolution are covered.
Abstract: Machine Translation (MT) between the Thai and English languages has been a challenging research topic in natural language processing. Most research has been done on English to Thai machine translation, but not the other way around. This paper presents a Thai to English Machine Translation System that translates a Thai sentence into interlingua of a Thai LFG tree using LFG grammar and a bottom up parser. The Thai LFG tree is then transformed into the corresponding English LFG tree by pattern matching and node transformation. Finally, an equivalent English sentence is created using structural information prescribed by the English LFG tree. Based on results of experiments designed to evaluate the performance of the proposed system, it can be stated that the system has been proven to be effective in providing a useful translation from Thai to English.
Abstract: The research on two-wheels balancing robot has
gained momentum due to their functionality and reliability when
completing certain tasks. This paper presents investigations into the
performance comparison of Linear Quadratic Regulator (LQR) and
PID-PID controllers for a highly nonlinear 2–wheels balancing robot.
The mathematical model of 2-wheels balancing robot that is highly
nonlinear is derived. The final model is then represented in statespace
form and the system suffers from mismatched condition. Two
system responses namely the robot position and robot angular
position are obtained. The performances of the LQR and PID-PID
controllers are examined in terms of input tracking and disturbances
rejection capability. Simulation results of the responses of the
nonlinear 2–wheels balancing robot are presented in time domain. A
comparative assessment of both control schemes to the system
performance is presented and discussed.
Abstract: To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.
Abstract: the present paper, using the technique of differential subordination, we obtain certain results for analytic functions defined by a multiplier transformation in the open unit disc E = { z : IzI < 1}. We claim that our results extend and generalize the existing results in this particular direction
Abstract: Sign language recognition has been a topic of research since the first data glove was developed. Many researchers have attempted to recognize sign language through various techniques. However none of them have ventured into the area of Pakistan Sign Language (PSL). The Boltay Haath project aims at recognizing PSL gestures using Statistical Template Matching. The primary input device is the DataGlove5 developed by 5DT. Alternative approaches use camera-based recognition which, being sensitive to environmental changes are not always a good choice.This paper explains the use of Statistical Template Matching for gesture recognition in Boltay Haath. The system recognizes one handed alphabet signs from PSL.
Abstract: Pomegranate and pomegranate juices (PJs) have taken
great attention for their health benefits in the last years. As there is an
increasing concern about potential health benefits of ellagic acid, it is
of great interest to evaluate alterations in ellagic acid concentration of
commercial PJs. The purpose of this study is to analyze total
phenolic, free and total ellagic acid content of six commercial PJs
sold in Turkish markets using HPLC.
The results showed that some commercial PJs had markedly high
total phenolic and ellagic acid content. Total phenolic substances of
commercial PJs range from 796.71 to 4608.91 mg GAE/l. Free
amount of ellagic acid in commercial PJs range from 27.64 to 111.78
mg/l. Samples are hydrolyzed with concentrated HCl at 93oC for 2
and 24 hour and influences of temperature and time parameters on
hydrolization were investigated. Thermal processing for
pasteurization increased ellagic acid via ellagitannins hydrolysis.
Abstract: Excessive ductility demand on shorter piers is a
common problem for irregular bridges subjected to strong ground
motion. Various techniques have been developed to reduce the
likelihood of collapse of bridge due to failure of shorter piers. This
paper presents the new approach to improve the seismic behavior of
such bridges using Nitinol shape memory alloys (SMAs).
Superelastic SMAs have the ability to remain elastic under very large
deformation due to martensitic transformation. This unique property
leads to enhanced performance of controlled bridge compared with
the performance of the reference bridge. To evaluate the effectiveness
of the devices, nonlinear time history analysis is performed on a RC
single column bent highway bridge using a suite of representative
ground motions. The results show that this method is very effective in
limiting the ductility demand of shorter pier.
Abstract: A bond graph model of a two degrees of freedom
PUMA is described. System inversion gives the system input
required to generate a given system output. In order to get the system
inversion of the PUMA manipulator, a linearization of the nonlinear
bond graph is obtained. Hence, the bicausality of the linearized bond
graph of the PUMA manipulator is applied. Thus, the bicausal bond
graph provides a systematic way of generating the equations of the
system inversion. Simulation results to verify the calculated input for
a given output are shown.
Abstract: According to the majority and to stereotypes in a simple everyman religious processes in the world in general, and Kazakhstan in particular, have only negative trends. The main reason for the author's opinion is seen in the fact that the media in the pursuit of ratings and sensation, more inclined to highlight the negative aspects of events in the country and the world of processes forgetting or casually mentioning the positive initiatives and achievements. That is why the article is mainly revealed positive trends in mind that the problems of fanaticism, terrorism and the confrontation of society on various issues, a lot has been written and detailed. This article describes the stages in the development of relations between religion and state, as well as institutionalization, networking and assistance in the correct orientation of religious activities in the country.
Abstract: In the context of spectrum surveillance, a method to
recover the code of spread spectrum signal is presented, whereas the
receiver has no knowledge of the transmitter-s spreading sequence.
The approach is based on a genetic algorithm (GA), which is forced to
model the received signal. Genetic algorithms (GAs) are well known
for their robustness in solving complex optimization problems.
Experimental results show that the method provides a good
estimation, even when the signal power is below the noise power.
Abstract: An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).
Abstract: The study aimed to investigate characteristics of
vegetative tissue for taxonomic purpose and possibly trend of waste
application in industry. Stems and branches of 15 species in Solanum
found in Thailand were prepared for fiber and examined by light
microscopy. Microstructural characteristic data of fiber i.e. fiber
length and width, fiber lumen diameter and fiber cell wall thickness
were recorded. The longest average fiber cell length (>3.9 mm.) were
obtained in S. lycopersicum L. and S. tuberosum L. Fiber cells from
S. lycopersicum also revealed the widest average diameter of whole
cell and its lumen at >45.5 μm and >29 μm respectively. However
fiber cells with thickest wall of > 9.6 μm were belonged to the
ornamental tree species, S. wrightii Benth. The results showed that
the slenderness ratio, Runkel ratio, and flexibility coefficient, with
potentially suitable for feedstock in paper industry fell in 4 exotic
species, i.e. Solanumamericanum L., S. lycopersicum, S.
seaforthianum Andr., and S. tuberosum L
Abstract: Functional near infrared spectroscopy (fNIRS) is a
practical non-invasive optical technique to detect characteristic of
hemoglobin density dynamics response during functional activation of
the cerebral cortex. In this paper, fNIRS measurements were made in
the area of motor cortex from C4 position according to international
10-20 system. Three subjects, aged 23 - 30 years, were participated in
the experiment.
The aim of this paper was to evaluate the effects of different motor
activation tasks of the hemoglobin density dynamics of fNIRS signal.
The chaotic concept based on deterministic dynamics is an important
feature in biological signal analysis. This paper employs the chaotic
properties which is a novel method of nonlinear analysis, to analyze
and to quantify the chaotic property in the time series of the
hemoglobin dynamics of the various motor imagery tasks of fNIRS
signal. Usually, hemoglobin density in the human brain cortex is
found to change slowly in time. An inevitable noise caused by various
factors is to be included in a signal. So, principle component analysis
method (PCA) is utilized to remove high frequency component. The
phase pace is reconstructed and evaluated the Lyapunov spectrum, and
Lyapunov dimensions. From the experimental results, it can be
conclude that the signals measured by fNIRS are chaotic.
Abstract: In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.
Abstract: In this note first we define the notions of intuitionistic
fuzzy dual positive implicative hyper K-ideals of types
1,2,3,4 and intuitionistic fuzzy dual hyper K-ideals. Then we
give some classifications about these notions according to the
level subsets. Also by given some examples we show that these
notions are not equivalent, however we prove some theorems
which show that there are some relationships between these
notions. Finally we define the notions of product and antiproduct
of two fuzzy subsets and then give some theorems
about the relationships between the intuitionistic fuzzy dual
positive implicative hyper K-ideal of types 1,2,3,4 and their
(anti-)products, in particular we give a main decomposition
theorem.
Abstract: Power transformers are among the most important and
expensive equipments in the electric power systems. Consequently
the transformer protection is an essential part of the system
protection. This paper presents a new method for locating
transformer winding faults such as turn-to-turn, turn-to-core, turn-totransformer
body, turn-to-earth, and high voltage winding to low
voltage winding. In this study the current and voltage signals of input
and output terminals of the transformer are measured, which the
Fourier transform of measured signals and harmonic analysis
determine the fault's location.
Abstract: In the current context of globalization, accountability has become a key subject of real interest for both, national and international business areas, due to the need for comparability and transparency of the economic situation, so we can speak about the harmonization and convergence of international accounting. The paper presents a qualitative research through content analysis of several reports concerning the roadmap for convergence. First, we develop a conceptual framework for the evolution of standards’ convergence and further we discuss the degree of standards harmonization and convergence between US GAAP and IAS/IFRS as to October 2012. We find that most topics did not follow the expected progress. Furthermore there are still some differences in the long-term project that are in process to be completed and other that were reassessed as a lower priority project.
Abstract: This research aims to study consumer acceptance of Tempeh from various raw materials (type of bean) and determine protein contents for comparison. Tempeh made from soybean, peanut, white kidney bean and sesame in the ratio: - soybean:sesame =1:0.1, soybean:white kidney:sesame =1:1:0.1, soybean:peanut:sesame =1:1:0.1 and peanut:white kidney bean: sesame =1:1:0.1. The study found that consumer is most satisfied with appearances on soybean mixed with white kidney and black sesame tempeh (3.98). The most satisfied tempeh with textures is soybean mixed with peanut and black sesame tempeh (4.00). The most satisfied tempeh with odor is peanut mixed with white kidney bean and black sesame tempeh (4.04). And the most satisfied tempeh with flavor is peanut mixed with white kidney bean and black sesame tempeh (4.2). The amount of protein in production, soybean tempeh has the highest protein. When we add sesame seeds, it made the protein content slightly decreased (1.86 and 0.6 %). When we use peanut as raw material, the protein content decreased 15.3%. And when we use
white kidney bean as raw material, the protein content decreased (22.77- 26.11%).
Abstract: Automatic reusability appraisal is helpful in
evaluating the quality of developed or developing reusable software
components and in identification of reusable components from
existing legacy systems; that can save cost of developing the
software from scratch. But the issue of how to identify reusable
components from existing systems has remained relatively
unexplored. In this research work, structural attributes of software
components are explored using software metrics and quality of the
software is inferred by different Neural Network based approaches,
taking the metric values as input. The calculated reusability value
enables to identify a good quality code automatically. It is found that
the reusability value determined is close to the manual analysis used
to be performed by the programmers or repository managers. So, the
developed system can be used to enhance the productivity and
quality of software development.