Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.
Abstract: Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.
Abstract: To create a solution for a specific problem in machine
learning, the solution is constructed from the data or by use a search
method. Genetic algorithms are a model of machine learning that can
be used to find nearest optimal solution. While the great advantage of
genetic algorithms is the fact that they find a solution through
evolution, this is also the biggest disadvantage. Evolution is inductive,
in nature life does not evolve towards a good solution but it evolves
away from bad circumstances. This can cause a species to evolve into
an evolutionary dead end. In order to reduce the effect of this
disadvantage we propose a new a learning tool (criteria) which can be
included into the genetic algorithms generations to compare the
previous population and the current population and then decide
whether is effective to continue with the previous population or the
current population, the proposed learning tool is called as Keeping
Efficient Population (KEP). We applied a GA based on KEP to the
production line layout problem, as a result KEP keep the evaluation
direction increases and stops any deviation in the evaluation.
Abstract: In this paper comparison of Reflector Antenna
analyzing techniques based on wave and ray nature of optics is
presented for an offset reflector antenna using GRASP (General
Reflector antenna Analysis Software Package) software. The results
obtained using PO (Physical Optics), PTD (Physical theory of
Diffraction), and GTD (Geometrical Theory of Diffraction) are
compared. The validity of PO and GTD techniques in regions around
the antenna, caustic behavior of GTD in main beam, and deviation of
GTD in case of near-in sidelobes of radiation pattern are discussed.
The comparison for far-out sidelobes predicted by PO, PO + PTD
and GTD is described. The effect of Direct Radiations from feed
which results in feed selection for the system is addressed.
Abstract: This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.
Abstract: The purpose of this research is to study motivation
factors and also to study factors relation to job performance to
compare motivation factors under the personal factor classification
such as gender, age, income, educational level, marital status, and
working duration; and to study the relationship between Motivation
Factors and Job Performance with job satisfactions. The sample
groups utilized in this research were 400 Suan Sunandha Rajabhat
University employees. This research is a quantitative research using
questionnaires as research instrument. The statistics applied for data
analysis including percentage, mean, and standard deviation. In
addition, the difference analysis was conducted by t value computing,
one-way analysis of variance and Pearson’s correlation coefficient
computing. The findings of the study results were as follows the
findings showed that the aspects of job promotion and salary were at
the moderate levels. Additionally, the findings also showed that the
motivations that affected the revenue branch chiefs’ job performance
were job security, job accomplishment, policy and management, job
promotion, and interpersonal relation.
Abstract: The electrolyte stirring method of anodization etching
process for manufacturing porous silicon (PS) is reported in this work.
Two experimental setups of nature air stirring (PS-ASM) and
electrolyte stirring (PS-ESM) are employed to clarify the influence of
stirring mechanisms on electrochemical etching process. Compared to
traditional fabrication without any stirring apparatus (PS-TM), a large
plateau region of PS surface structure is obtained from samples with
both stirring methods by the 3D-profiler measurement. Moreover, the
light emission response is also improved by both proposed electrolyte
stirring methods due to the cycling force in electrolyte could
effectively enhance etch-carrier distribution while the electrochemical
etching process is made. According to the analysis of statistical
calculation of photoluminescence (PL) intensity, lower standard
deviations are obtained from PS-samples with studied stirring methods,
i.e. the uniformity of PL-intensity is effectively improved. The
calculated deviations of PL-intensity are 93.2, 74.5 and 64,
respectively, for PS-TM, PS-ASM and PS-ESM.
Abstract: The aim of this study is to discuss the relationship between tourist awareness of environmental issues and their own recreational behaviors in the Taipei Guandu Wetland. A total of 392 questionnaires were gathered for data analysis using descriptive statistics, t-testing, one-way analysis of variance (ANOVA) and least significant difference (LSD) post hoc comparisons. The results showed that most of the visitors there enjoying the beautiful scenery are 21 to 30 years old with a college education. The means and standard deviations indicate that tourists express a positive degree of cognition of environmental issues and recreational behaviors. They suggest that polluting the environment is harmful to the natural ecosystem and that the natural resources of ecotourism are fragile, as well as expressing a high degree of recognition of the need to protect wetlands. Most of respondents are cognizant of the regulations proposed by the Guandu Wetland administration which asks that users exercise self-control and follow recommended guidelines when traveling the wetland. There were significant differences in the degree of cognition related to the variables of age, number of visits and reasons for visiting. We found that most respondents with relatively high levels of education would like to learn more about the wetland and are supportive of its conservation.
Abstract: Since polymerase chain reaction (PCR) has been
invented, it has emerged as a powerful tool in genetic analysis. The
PCR products are closely linked with thermal cycles. Therefore, to
reduce the reaction time and make temperature distribution uniform in
the reaction chamber, a novel oscillatory thermal cycler is designed.
The sample is placed in a fixed chamber, and three constant isothermal
zones are established and lined in the system. The sample is oscillated
and contacted with three different isothermal zones to complete
thermal cycles. This study presents the design of the geometric
characteristics of the chamber. The commercial software
CFD-ACE+TM is utilized to investigate the influences of various
materials, heating times, chamber volumes, and moving speed of the
chamber on the temperature distributions inside the chamber. The
chamber moves at a specific velocity and the boundary conditions
with time variations are related to the moving speed. Whereas the
chamber moves, the boundary is specified at the conditions of the
convection or the uniform temperature. The user subroutines compiled
by the FORTRAN language are used to make the numerical results
realistically. Results show that the reaction chamber with a rectangular
prism is heated on six faces; the effects of various moving speeds of
the chamber on the temperature distributions are examined. Regarding
to the temperature profiles and the standard deviation of the
temperature at the Y-cut cross section, the non-uniform temperature
inside chamber is found as the moving speed is larger than 0.01 m/s.
By reducing the heating faces to four, the standard deviation of the
temperature of the reaction chamber is under 1.4×10-3K with the range
of velocities between 0.0001 m/s and 1 m/s. The nature convective
boundary conditions are set at all boundaries while the chamber moves
between two heaters, the effects of various moving velocities of the
chamber on the temperature distributions are negligible at the assigned
time duration.
Abstract: Various intelligences and inspirations have been
adopted into the iterative searching process called as meta-heuristics.
They intelligently perform the exploration and exploitation in the
solution domain space aiming to efficiently seek near optimal
solutions. In this work, the bee algorithm, inspired by the natural
foraging behaviour of honey bees, was adapted to find the near
optimal solutions of the transportation management system, dynamic
multi-zone dispatching. This problem prepares for an uncertainty and
changing customers- demand. In striving to remain competitive,
transportation system should therefore be flexible in order to cope
with the changes of customers- demand in terms of in-bound and outbound
goods and technological innovations. To remain higher service
level but lower cost management via the minimal imbalance scenario,
the rearrangement penalty of the area, in each zone, including time
periods are also included. However, the performance of the algorithm
depends on the appropriate parameters- setting and need to be
determined and analysed before its implementation. BEE parameters
are determined through the linear constrained response surface
optimisation or LCRSOM and weighted centroid modified simplex
methods or WCMSM. Experimental results were analysed in terms
of best solutions found so far, mean and standard deviation on the
imbalance values including the convergence of the solutions
obtained. It was found that the results obtained from the LCRSOM
were better than those using the WCMSM. However, the average
execution time of experimental run using the LCRSOM was longer
than those using the WCMSM. Finally a recommendation of proper
level settings of BEE parameters for some selected problem sizes is
given as a guideline for future applications.
Abstract: To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Abstract: In this study, the Scots pine (Pinus sylvestris L.) C
needles (i.e. the current-year-needles) were used as bioindicators in
determining the aerial distribution pattern of sulphur emissions
around industrial point sources at Kemi, Northern Finland. The
average sulphur concentration in the C needles was 897 mg/kg
(d.w.), with a standard deviation of 118 mg/kg (d.w.) and range 740 –
1350 mg/kg (d.w.). According to results in this study, Scots pine
needles (Pinus sylvestris L.) appear to be an ideal bioindicators for
identifying atmospheric sulphur pollution derived from industrial
plants and can complement the information provided by plant
mapping studies around industrial plants.
Abstract: A measurement system for pH array sensors is
introduced to increase accuracy, and decrease non-ideal effects
successfully. An array readout circuit reads eight potentiometric
signals at the same time, and obtains an average value. The deviation
value or the extreme value is counteracted and the output voltage is a
relatively stable value. The errors of measuring pH buffer solutions are
decreased obviously with this measurement system, and the non-ideal
effects, drift and hysteresis, are lowered to 1.638mV/hr and 1.118mV,
respectively. The efficiency and stability are better than single sensor.
The whole sensing characteristics are improved.
Abstract: Today, Genetic Algorithm has been used to solve
wide range of optimization problems. Some researches conduct on
applying Genetic Algorithm to text classification, summarization
and information retrieval system in text mining process. This
researches show a better performance due to the nature of Genetic
Algorithm. In this paper a new algorithm for using Genetic
Algorithm in concept weighting and topic identification, based on
concept standard deviation will be explored.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: Graph coloring is an important problem in computer
science and many algorithms are known for obtaining reasonably
good solutions in polynomial time. One method of comparing
different algorithms is to test them on a set of standard graphs where
the optimal solution is already known. This investigation analyzes a
set of 50 well known graph coloring instances according to a set of
complexity measures. These instances come from a variety of
sources some representing actual applications of graph coloring
(register allocation) and others (mycieleski and leighton graphs) that
are theoretically designed to be difficult to solve. The size of the
graphs ranged from ranged from a low of 11 variables to a high of
864 variables. The method used to solve the coloring problem was
the square of the adjacency (i.e., correlation) matrix. The results
show that the most difficult graphs to solve were the leighton and the
queen graphs. Complexity measures such as density, mobility,
deviation from uniform color class size and number of block
diagonal zeros are calculated for each graph. The results showed that
the most difficult problems have low mobility (in the range of .2-.5)
and relatively little deviation from uniform color class size.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: One of the purposes of the robust method of
estimation is to reduce the influence of outliers in the data, on the
estimates. The outliers arise from gross errors or contamination from
distributions with long tails. The trimmed mean is a robust estimate.
This means that it is not sensitive to violation of distributional
assumptions of the data. It is called an adaptive estimate when the
trimming proportion is determined from the data rather than being
fixed a “priori-.
The main objective of this study is to find out the robustness
properties of the adaptive trimmed means in terms of efficiency, high
breakdown point and influence function. Specifically, it seeks to find
out the magnitude of the trimming proportion of the adaptive
trimmed mean which will yield efficient and robust estimates of the
parameter for data which follow a modified Weibull distribution with
parameter λ = 1/2 , where the trimming proportion is determined by a
ratio of two trimmed means defined as the tail length. Secondly, the
asymptotic properties of the tail length and the trimmed means are
also investigated. Finally, a comparison is made on the efficiency of
the adaptive trimmed means in terms of the standard deviation for the
trimming proportions and when these were fixed a “priori".
The asymptotic tail lengths defined as the ratio of two trimmed
means and the asymptotic variances were computed by using the
formulas derived. While the values of the standard deviations for the
derived tail lengths for data of size 40 simulated from a Weibull
distribution were computed for 100 iterations using a computer
program written in Pascal language.
The findings of the study revealed that the tail lengths of the
Weibull distribution increase in magnitudes as the trimming
proportions increase, the measure of the tail length and the adaptive
trimmed mean are asymptotically independent as the number of
observations n becomes very large or approaching infinity, the tail
length is asymptotically distributed as the ratio of two independent
normal random variables, and the asymptotic variances decrease as
the trimming proportions increase. The simulation study revealed
empirically that the standard error of the adaptive trimmed mean
using the ratio of tail lengths is relatively smaller for different values
of trimming proportions than its counterpart when the trimming
proportions were fixed a 'priori'.
Abstract: This paper proposes a new performance characterization for the test strategy intended for second order filters denominated Transient Analysis Method (TRAM). We evaluate the ability of the addressed test strategy for detecting deviation faults under simultaneous statistical fluctuation of the non-faulty parameters. For this purpose, we use Monte Carlo simulations and a fault model that considers as faulty only one component of the filter under test while the others components adopt random values (within their tolerance band) obtained from their statistical distributions. The new data reported here show (for the filters under study) the presence of hard-to-test components and relatively low fault coverage values for small deviation faults. These results suggest that the fault coverage value obtained using only nominal values for the non-faulty components (the traditional evaluation of TRAM) seem to be a poor predictor of the test performance.