Abstract: In this study, the designed dual stage membrane
bioreactor (MBR) system was conceptualized for the treatment of
cyanide and heavy metals in electroplating wastewater. The design
consisted of a primary treatment stage to reduce the impact of
fluctuations and the secondary treatment stage to remove the residual
cyanide and heavy metal contaminants in the wastewater under
alkaline pH conditions. The primary treatment stage contained
hydrolyzed Citrus sinensis (C. sinensis) pomace and the secondary
treatment stage contained active Aspergillus awamori (A. awamori)
biomass, supplemented solely with C. sinensis pomace extract from
the hydrolysis process. An average of 76.37%, 95.37%, 93.26 and
94.76% and 99.55%, 99.91%, 99.92% and 99.92% degradation
efficiency for total cyanide (T-CN), including the sorption of nickel
(Ni), zinc (Zn) and copper (Cu) were observed after the first and
second treatment stages, respectively. Furthermore, cyanide
conversion by-products degradation was 99.81% and 99.75 for both
formate (CHOO-) and ammonium (NH4
+) after the second treatment
stage. After the first, second and third regeneration cycles of the C.
sinensis pomace in the first treatment stage, Ni, Zn and Cu removal
achieved was 99.13%, 99.12% and 99.04% (first regeneration cycle),
98.94%, 98.92% and 98.41% (second regeneration cycle) and 98.46
%, 98.44% and 97.91% (third regeneration cycle), respectively.
There was relatively insignificant standard deviation detected in all
the measured parameters in the system which indicated
reproducibility of the remediation efficiency in this continuous
system.
Abstract: Recurrent event data is a special type of multivariate
survival data. Dynamic and frailty models are one of the approaches
that dealt with this kind of data. A comparison between these two
models is studied using the empirical standard deviation of the
standardized martingale residual processes as a way of assessing the
fit of the two models based on the Aalen additive regression model.
Here we found both approaches took heterogeneity into account and
produce residual standard deviations close to each other both in the
simulation study and in the real data set.
Abstract: In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.
Abstract: This frame work describes a computationally more
efficient and adaptive threshold estimation method for image
denoising in the wavelet domain based on Generalized Gaussian
Distribution (GGD) modeling of subband coefficients. In this
proposed method, the choice of the threshold estimation is carried out
by analysing the statistical parameters of the wavelet subband
coefficients like standard deviation, arithmetic mean and geometrical
mean. The noisy image is first decomposed into many levels to
obtain different frequency bands. Then soft thresholding method is
used to remove the noisy coefficients, by fixing the optimum
thresholding value by the proposed method. Experimental results on
several test images by using this method show that this method yields
significantly superior image quality and better Peak Signal to Noise
Ratio (PSNR). Here, to prove the efficiency of this method in image
denoising, we have compared this with various denoising methods
like wiener filter, Average filter, VisuShrink and BayesShrink.
Abstract: This policy participation action research explores the
roles of Thai government units during its 2010 fiscal year on how to
create value added to recycling business in the central part of
Thailand. The research aims to a) study how the government plays a
role to support the business, and its problems and obstacles on
supporting the business, b) to design a strategic action – short,
medium, and long term plans -- to create value added to the recycling
business, particularly in local full-loop companies/organizations
licensed by Wongpanit Waste Separation Plant as well as those
licensed by the Department of Provincial Administration. Mixed
method research design, i.e., a combination of quantitative and
qualitative methods is utilized in the present study in both data
collection and analysis procedures. Quantitative data was analyzed
by frequency, percent value, mean scores, and standard deviation,
and aimed to note trend and generalizations. Qualitative data was
collected via semi-structured interviews/focus group interviews to
explore in-depth views of the operators. The sampling included 1,079
operators in eight provinces in the central part of Thailand.
Abstract: In this article, a method has been offered to classify
normal and defective tiles using wavelet transform and artificial
neural networks. The proposed algorithm calculates max and min
medians as well as the standard deviation and average of detail
images obtained from wavelet filters, then comes by feature vectors
and attempts to classify the given tile using a Perceptron neural
network with a single hidden layer. In this study along with the
proposal of using median of optimum points as the basic feature and
its comparison with the rest of the statistical features in the wavelet
field, the relational advantages of Haar wavelet is investigated. This
method has been experimented on a number of various tile designs
and in average, it has been valid for over 90% of the cases. Amongst
the other advantages, high speed and low calculating load are
prominent.
Abstract: The paper presents a compressor anti-surge control
system, that results in maximizing compressor throughput with
pressure standard deviation reduction, increased safety margin
between design point and surge limit line and avoiding possible
machine surge. Alternative control strategies are presented.