Abstract: This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.
Abstract: Modes of occurrence of Pb, As, Cr, Co, Cu, and Ni in bituminous coal and lignite were determined by means of sequential extraction using NH4OAc, HCl, HF and HNO3 extraction solutions. Elemental affinities obtained were then evaluated in relation to volatility of these elements during the combustion of these coals in two circulating fluidised-bed power stations. It was found out that higher percentage of the elements bound in silicates brought about lower volatility, while higher elemental proportion with monosulphides association (or bound as exchangeable ion) resulted in higher volatility. The only exception was the behavior of arsenic, whose volatility depended on amount of limestone added during the combustion process (as desulphurisation additive) rather than to its association in coal.
Abstract: We present a theory for optimal filtering of infinite sets of random signals. There are several new distinctive features of the proposed approach. First, we provide a single optimal filter for processing any signal from a given infinite signal set. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.
Abstract: The purpose of this paper is to discuss the influence of
resistance characteristic on the high conductive concrete considering
the various voltage and environment. The four-electrode method is
applied to the tailor-made high conductive concrete with appropriate
proportion. The curve of resistivity with the changes of voltage and
environment is plotted and the changes of resistivity are explored. The
result based on the methods reveals that resistivity is less affected by
the temperature factor, and the four-electrode method would be an
applicable measurement method on a site inspection.
Abstract: This study used Item Analysis, Exploratory Factor
Analysis (EFA) and Reliability Analysis (Cronbach-s α value) to
exam the Questions which selected by the Delphi method based on the
issue of “Socio-technical system (STS)" and user-centered
perspective. A structure questionnaire with seventy-four questions
which could be categorized into nine dimensions (healthcare
environment, organization behaviour, system quality, medical data
quality, service quality, safety quality, user usage, user satisfaction,
and organization net benefits) was provided to evaluate EMR of the
Taiwanese healthcare environment.
Abstract: Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.
Abstract: Exponentially weighted moving average control chart (EWMA) is a popular chart used for detecting shift in the mean of parameter of distributions in quality control. The objective of this paper is to compare the efficiency of control chart to detect an increases in the mean of a process. In particular, we compared the Maximum Exponentially Weighted Moving Average (MaxEWMA) and Maximum Generally Weighted Moving Average (MaxGWMA) control charts when the observations are Exponential distribution. The criteria for evaluate the performance of control chart is called, the Average Run Length (ARL). The result of comparison show that in the case of process is small sample size, the MaxEWMA control chart is more efficiency to detect shift in the process mean than MaxGWMA control chart. For the case of large sample size, the MaxEWMA control chart is more sensitive to detect small shift in the process mean than MaxGWMA control chart, and when the process is a large shift in mean, the MaxGWMA control chart is more sensitive to detect mean shift than MaxEWMA control chart.
Abstract: This study assessed fish marketing as panacea towards
sustainable agriculture in Ogun State, Nigeria. Multi-stage sampling
technique was used in the selection of 150 fish marketers for this
study. Descriptive statistics were used for the objectives while
Product Pearson Moment Correlation was used to test the hypothesis.
Result of the findings revealed that the mean age of the respondents
was 38.60 years. Majority (93.33%) of the respondents had
acceptable levels of formal education. Many (44.00%) of the
respondents had spent 1-5 years in fish marketing. The average
quantity of fish sold in a day was 94.10kg. However, efficient fish
marketing were hindered by inadequate processing equipment,
storage rooms and ice holding facilities (86.67%). There was a
significant relationship between socio-economic characteristics and
profit realized from fish marketing (p < 0.05). It was recommended
that storage and warehousing facilities should be provided to the fish
marketers in the study area.
Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: This research study aims to identify the impact of two
factors –growth and competitive strategies- on a set of building
production innovation strategies. It was conducted a questionery
survey to collect data from construction professionals and it was
asked them the importance level of predicted innovation strategies for
corporate strategies. Multiple analysis of variance (MANOVA) was
employed to see the main and interaction effects of corporate
strategies on building innovation strategies. The results indicate that
growth strategies such as entering in a new a market or new project
types has a greater effect on innovation strategies rather than
competitive strategies such as cost leadership or differentiation
strategies. However the interaction effect of competitive strategies
and growth strategies on innovation strategies is much bigger than
the only effect of competitive strategies. It was also analyzed the
descriptive statistics of innovation strategies for different competitive
and growth strategy types.
Abstract: Simulation model is an easy way to build up models
to represent real life scenarios, to identify bottlenecks and to enhance
system performance. Using a valid simulation model may give
several advantages in creating better manufacturing design in order to
improve the system performances. This paper presents result of
implementing a simulation model to design hard disk drive
manufacturing process by applying line balancing to improve both
productivity and quality of hard disk drive process. The line balance
efficiency showed 86% decrease in work in process, output was
increased by an average of 80%, average time in the system was
decreased 86% and waiting time was decreased 90%.
Abstract: The objective of this study is to determine the thermal comfort among worker at Malaysian automotive industry. One critical manual assembly workstation had been chosen as a subject for the study. The human subjects for the study constitute operators at Body Assembly Station of the factory. The environment examined was the Relative Humidity (%), Airflow (m/s), Air Temperature (°C) and Radiant Temperature (°C) of the surrounding workstation area. The environmental factors were measured using Babuc apparatus, which is capable to measure simultaneously those mentioned environmental factors. The time series data of fluctuating level of factors were plotted to identify the significant changes of factors. Then thermal comfort of the workers were assessed by using ISO Standard 7730 Thermal sensation scale by using Predicted Mean Vote (PMV). Further Predicted percentage dissatisfied (PPD) is used to estimate the thermal comfort satisfaction of the occupant. Finally the PPD versus PMV were plotted to present the thermal comfort scenario of workers involved in related workstation. The result of PMV at the related industry is between 1.8 and 2.3, where PPD at that building is between 60% to 84%. The survey result indicated that the temperature more influenced comfort to the occupants
Abstract: This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.
Abstract: In this study we focus on improvement performance
of a cue based Motor Imagery Brain Computer Interface (BCI). For
this purpose, data fusion approach is used on results of different
classifiers to make the best decision. At first step Distinction
Sensitive Learning Vector Quantization method is used as a feature
selection method to determine most informative frequencies in
recorded signals and its performance is evaluated by frequency
search method. Then informative features are extracted by packet
wavelet transform. In next step 5 different types of classification
methods are applied. The methodologies are tested on BCI
Competition II dataset III, the best obtained accuracy is 85% and the
best kappa value is 0.8. At final step ordered weighted averaging
(OWA) method is used to provide a proper aggregation classifiers
outputs. Using OWA enhanced system accuracy to 95% and kappa
value to 0.9. Applying OWA just uses 50 milliseconds for
performing calculation.
Abstract: The overall objective of this paper is to retrieve soil
surfaces parameters namely, roughness and soil moisture related to
the dielectric constant by inverting the radar backscattered signal
from natural soil surfaces.
Because the classical description of roughness using statistical
parameters like the correlation length doesn't lead to satisfactory
results to predict radar backscattering, we used a multi-scale
roughness description using the wavelet transform and the Mallat
algorithm. In this description, the surface is considered as a
superposition of a finite number of one-dimensional Gaussian
processes each having a spatial scale. A second step in this study
consisted in adapting a direct model simulating radar backscattering
namely the small perturbation model to this multi-scale surface
description. We investigated the impact of this description on radar
backscattering through a sensitivity analysis of backscattering
coefficient to the multi-scale roughness parameters.
To perform the inversion of the small perturbation multi-scale
scattering model (MLS SPM) we used a multi-layer neural network
architecture trained by backpropagation learning rule. The inversion
leads to satisfactory results with a relative uncertainty of 8%.
Abstract: Acetaminophen (Paracetamol) tablets are popular OTC products among patients as analgesics and antipyretics. Paracetamol is marketed by a lot of suppliers around the world. The aim of the present investigation was to compare between many types of paracetamol tablets obtained from different suppliers (six brands produced by different pharmaceutical companies in middle east countries, and Panadol® manufactured in Ireland), by different quality control tests according to USP pharmacopeia.Using Non official tests-hardness and friability; official tests- disintegration, dissolution, and drug content. Additionally, evaluate the influence of temperatures 4°C, 25°C and 40°C at 75% relative humidity on the stability of the same brands in their original packaging has been conducted for two months. The results revealed that all paracetamol tablet brands complied with the official USP specifications. In conclusion, paracetamol tablets preferred to be stored at 25°C. All the tested brands being biopharmaceutically and chemically equivalent.
Abstract: This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.
Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: A sensitive and specific method for quantitative
determination of aflatoxins(B1, B2, G1,G2), deoxynivalenol,
fumonisin(B1,B2), ochratoxin A, zearalenone, T-2 and HT-2 in
roasted and ground grains using liquid chromatography combined
with tandem mass spectrometry. A double extraction using a
phosphate buffer solution followed by methanol was applied to
achieve effective co extraction of 11 mycotoxins. A multitoxin
immunoaffinity column for all these mycotoxins was used to clean up
the extract. The LODs of mycotoxins were 0.1~6.1 μg/kg, LOQs were
0.3~18.4 μg/kg. Forty seven samples collected from Seoul (Korea) for
mycotoxin contamination monitoring. The results showed that the
occurrence of zearalenone and deoxynivalenol were frequent.
Zearalenone was detected in all samples and deoxynivalenol was
detected in 80.9 % samples in the range 0.626 ~ 29.264 μg/kg and N.D
~ 48.332 μg/kg respectively. Fumonisins and ochratoxin A were
detected in 46.8% samples and 17 % samples respectively, aflatoxins
and T-2/HT-2 toxins were not detected all samples.
Abstract: There is a paucity of data on the prevalence of alcohol
use and related problems among foreign students in Belarus. We
therefore screen for the prevalence of alcohol related problems
among the general foreign students- population in Minsk, Belarus.
Participants were 135 male university foreign students (average age –
21) from three major universities in Minsk, Belarus. All respondents
were administered questionnaire, containing the AUDIT, CAGE,
MAST and other alcohol related questions. Overall, 62.2% (n=84)
alcohol users and 31.1% (n=42) problem drinkers were identified on
the AUDIT. There was a significant increase (from 39.3% to 60.7%)
of the total alcohol users after arrival in Belarus (¤ç2 = 7.714, p