Abstract: The equilibrium, thermodynamics and kinetics of the
biosorption of Cd (II) and Pb(II) by a Spore Forming Bacillus (MGL
75) were investigated at different experimental conditions. The
Langmuir and Freundlich, and Dubinin-Radushkevich (D-R)
equilibrium adsorption models were applied to describe the
biosorption of the metal ions by MGL 75 biomass. The Langmuir
model fitted the equilibrium data better than the other models.
Maximum adsorption capacities q max for lead (II) and cadmium (II)
were found equal to 158.73mg/g and 91.74 mg/g by Langmuir model.
The values of the mean free energy determined with the D-R equation
showed that adsorption process is a physiosorption process. The
thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°),
and entropy (ΔS°) changes were also calculated, and the values
indicated that the biosorption process was exothermic and
spontaneous. Experiment data were also used to study biosorption
kinetics using pseudo-first-order and pseudo-second-order kinetic
models. Kinetic parameters, rate constants, equilibrium sorption
capacities and related correlation coefficients were calculated and
discussed. The results showed that the biosorption processes of both
metal ions followed well pseudo-second-order kinetics.
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: In this paper, we consider the problem of logic simplification for a special class of logic functions, namely complementary Boolean functions (CBF), targeting low power implementation using static CMOS logic style. The functions are uniquely characterized by the presence of terms, where for a canonical binary 2-tuple, D(mj) ∪ D(mk) = { } and therefore, we have | D(mj) ∪ D(mk) | = 0 [19]. Similarly, D(Mj) ∪ D(Mk) = { } and hence | D(Mj) ∪ D(Mk) | = 0. Here, 'mk' and 'Mk' represent a minterm and maxterm respectively. We compare the circuits minimized with our proposed method with those corresponding to factored Reed-Muller (f-RM) form, factored Pseudo Kronecker Reed-Muller (f-PKRM) form, and factored Generalized Reed-Muller (f-GRM) form. We have opted for algebraic factorization of the Reed-Muller (RM) form and its different variants, using the factorization rules of [1], as it is simple and requires much less CPU execution time compared to Boolean factorization operations. This technique has enabled us to greatly reduce the literal count as well as the gate count needed for such RM realizations, which are generally prone to consuming more cells and subsequently more power consumption. However, this leads to a drawback in terms of the design-for-test attribute associated with the various RM forms. Though we still preserve the definition of those forms viz. realizing such functionality with only select types of logic gates (AND gate and XOR gate), the structural integrity of the logic levels is not preserved. This would consequently alter the testability properties of such circuits i.e. it may increase/decrease/maintain the same number of test input vectors needed for their exhaustive testability, subsequently affecting their generalized test vector computation. We do not consider the issue of design-for-testability here, but, instead focus on the power consumption of the final logic implementation, after realization with a conventional CMOS process technology (0.35 micron TSMC process). The quality of the resulting circuits evaluated on the basis of an established cost metric viz., power consumption, demonstrate average savings by 26.79% for the samples considered in this work, besides reduction in number of gates and input literals by 39.66% and 12.98% respectively, in comparison with other factored RM forms.
Abstract: Selection of the best possible set of suppliers has a
significant impact on the overall profitability and success of any
business. For this reason, it is usually necessary to optimize all
business processes and to make use of cost-effective alternatives for
additional savings. This paper proposes a new efficient context-aware
supplier selection model that takes into account possible changes of
the environment while significantly reducing selection costs. The
proposed model is based on data clustering techniques while
inspiring certain principles of online algorithms for an optimally
selection of suppliers. Unlike common selection models which re-run
the selection algorithm from the scratch-line for any decision-making
sub-period on the whole environment, our model considers the
changes only and superimposes it to the previously defined best set
of suppliers to obtain a new best set of suppliers. Therefore, any recomputation
of unchanged elements of the environment is avoided
and selection costs are consequently reduced significantly. A
numerical evaluation confirms applicability of this model and proves
that it is a more optimal solution compared with common static
selection models in this field.
Abstract: Evaluation and survey of curriculum quality as one of the most important components of universities system is necessary for different levels in higher education. The main purpose of this study was to survey of the curriculum quality of Actuarial science field. Case: University of SHahid Beheshti and Higher education institute of Eco insurance (according to viewpoint of students, alumni, employers and faculty members). Descriptive statistics (mean, tables, percentage, and frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criteria considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. Content, teaching and learning methods, space and facilities, assessment of learning criteria were relatively desirable level, objectives and time criterions were desirable level. The quality of curriculum of Actuarial Science field was relatively desirable level.
Abstract: Spatial trends are one of the valuable patterns in geo
databases. They play an important role in data analysis and
knowledge discovery from spatial data. A spatial trend is a regular
change of one or more non spatial attributes when spatially moving
away from a start object. Spatial trend detection is a graph search
problem therefore heuristic methods can be good solution. Artificial
immune system (AIS) is a special method for searching and
optimizing. AIS is a novel evolutionary paradigm inspired by the
biological immune system. The models based on immune system
principles, such as the clonal selection theory, the immune network
model or the negative selection algorithm, have been finding
increasing applications in fields of science and engineering.
In this paper, we develop a novel immunological algorithm based
on clonal selection algorithm (CSA) for spatial trend detection. We
are created neighborhood graph and neighborhood path, then select
spatial trends that their affinity is high for antibody. In an
evolutionary process with artificial immune algorithm, affinity of
low trends is increased with mutation until stop condition is satisfied.
Abstract: For numerical prediction of the NOX in the exhaust of
a compression ignition engine a model was developed by considering
the parameter equivalence ratio. This model was validated by
comparing the predicted results of NOX with experimental ones. The
ultimate aim of the work was to access the applicability, robustness
and performance of the improved NOX model against other NOX
models.
Abstract: DNA shuffling is a powerful method used for in vitro
evolute molecules with specific functions and has application in areas
such as, for example, pharmaceutical, medical and agricultural
research. The success of such experiments is dependent on a variety
of parameters and conditions that, sometimes, can not be properly
pre-established. Here, two computational models predicting DNA
shuffling results is presented and their use and results are evaluated
against an empirical experiment. The in silico and in vitro results
show agreement indicating the importance of these two models and
motivating the study and development of new models.
Abstract: A general stochastic spatial MIMO channel model is
proposed for evaluating various MIMO techniques in this paper. It can
generate MIMO channels complying with various MIMO
configurations such as smart antenna, spatial diversity and spatial
multiplexing. The modeling method produces the stochastic fading
involving delay spread, Doppler spread, DOA (direction of arrival),
AS (angle spread), PAS (power azimuth Spectrum) of the scatterers,
antenna spacing and the wavelength. It can be applied in various
MIMO technique researches flexibly with low computing complexity.
Abstract: This study aimed to detect and to identify the main
strains of airborne microorganisms present in the Shanghai Metro
system. Samples were collected using agar plates exposed to the air
and microorganisms were identified using catalase, plasma coagulase
and hymolytic analysis. The results show that the concentration of
mildew present within a newly opened metro line was significantly
higher than for other lines. Differences among underground and
elevated stations can be attributed to differences in passenger flow and
the environment surrounding the stations. Additionally, the
investigation indicated that bacteria reached maximum levels at
different times on weekdays and weekends. The bacteria in the Metro
stations were identified as primarily Gram positive, consisting mainly
of coagulase-negative staphylococcus strains (CNS).
Abstract: The use of renewable energy sources becomes more
necessary and interesting. As wider applications of renewable energy
devices at domestic, commercial and industrial levels has not only
resulted in greater awareness, but also significantly installed
capacities. In addition, biomass principally is in the form of woods,
which is a form of energy by humans for a long time. Gasification is
a process of conversion of solid carbonaceous fuel into combustible
gas by partial combustion. Many gasifier models have various
operating conditions; the parameters kept in each model are different.
This study applied experimental data, which has three inputs, which
are; biomass consumption, temperature at combustion zone and ash
discharge rate. One output is gas flow rate. For this paper, neural
network was used to identify the gasifier system suitable for the
experimental data. In the result,neural networkis usable to attain the
answer.
Abstract: In July 2012, an indoor/outdoor monitoring
programme was undertaken in two university sports facilities: a
fronton and a gymnasium. Comfort parameters (temperature, relative
humidity, CO and CO2) and total volatile organic compounds
(VOCs) were continuously monitored. Concentrations of NO2,
carbonyl compounds and individual VOCs were obtained. Low
volume samplers were used to collect particulate matter (PM10). The
minimum ventilation rates stipulated for acceptable indoor air quality
were observed in both sports facilities. It was found that cleaning
activities may have a large influence on the VOC levels. Acrolein
was one of the most abundant carbonyl compounds, showing
concentrations above the recommended limit. Formaldehyde was
detected at levels lower than those commonly reported for other
indoor environments. The PM10 concentrations obtained during the
occupancy periods ranged between 38 and 43μgm-3 in the fronton and
from 154 to 198μgm-3 in the gymnasium.
Abstract: In this paper we study the use of a new code called
Random Diagonal (RD) code for Spectral Amplitude Coding (SAC)
optical Code Division Multiple Access (CDMA) networks, using
Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose
index of reflection varies periodically along its length. RD code is
constructed using code level and data level, one of the important
properties of this code is that the cross correlation at data level is
always zero, which means that Phase intensity Induced Phase (PIIN)
is reduced. We find that the performance of the RD code will be
better than Modified Frequency Hopping (MFH) and Hadamard code
It has been observed through experimental and theoretical simulation
that BER for RD code perform significantly better than other codes.
Proof –of-principle simulations of encoding with 3 channels, and 10
Gbps data transmission have been successfully demonstrated together
with FBG decoding scheme for canceling the code level from SAC-signal.
Abstract: Rice husk is one of the alternative fuels for Thailand because of its high potential and environmental benefits. Nonetheless, the environmental profile of the electricity production from rice husk must be assessed to ensure reduced environmental damage. A 10 MW pilot plant using rice husk as feedstock is the study site. The environmental impacts from rice husk power plant are evaluated by using the Life Cycle Assessment (LCA) methodology. Energy, material and carbon balances have been determined for tracing the system flow. Carbon closure has been used for describing of the net amount of CO2 released from the system in relation to the amount being recycled between the power plant and the CO2 adsorbed by rice husk. The transportation of rice husk to the power plant has significant on global warming, but not on acidification and photo-oxidant formation. The results showed that the impact potentials from rice husk power plant are lesser than the conventional plants for most of the categories considered; except the photo-oxidant formation potential from CO. The high CO from rice husk power plant may be due to low boiler efficiency and high moisture content in rice husk. The performance of the study site can be enhanced by improving the combustion efficiency.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: The term hybrid composite refers to the composite
containing more than one type of fiber material as reinforcing fillers.
It has become attractive structural material due to the ability of
providing better combination of properties with respect to single fiber
containing composite. The eco-friendly nature as well as processing
advantage, light weight and low cost have enhanced the attraction
and interest of natural fiber reinforced composite. The objective of
present research is to study the mechanical properties of jute-coir
fiber reinforced hybrid polypropylene (PP) composite according to
filler loading variation. In the present work composites were
manufactured by using hot press machine at four levels of fiber
loading (5, 10, 15 and 20 wt %). Jute and coir fibers were utilized at a
ratio of (1:1) during composite manufacturing. Tensile, flexural,
impact and hardness tests were conducted for mechanical
characterization. Tensile test of composite showed a decreasing trend
of tensile strength and increasing trend of the Young-s modulus with
increasing fiber content. During flexural, impact and hardness tests,
the flexural strength, flexural modulus, impact strength and hardness
were found to be increased with increasing fiber loading. Based on
the fiber loading used in this study, 20% fiber reinforced composite
resulted the best set of mechanical properties.
Abstract: Series of tellurite glass of the system 78TeO2-10PbO-
10Li2O-(2-x)Nd2O3-xEr2O3, where x = 0.5, 1.0, 1.5 and 2.0 was
successfully been made. A study of upconversion luminescence of
the Nd3+/Er3+ co-doped tellurite glass has been carried out. From
Judd-Ofelt analysis, the experimental lifetime, exp. τ of the glass
serie are found higher in the visible region as they varies from
65.17ms to 114.63ms, whereas in the near infrared region (NIR) the
lifetime are varies from 2.133ms to 2.270ms. Meanwhile, the
emission cross section,σ results are found varies from 0.004 x 1020
cm2 to 1.007 x 1020 cm2 with respect to composition. The emission
spectra of the glass are found been contributed from Nd3+ and Er3+
ions by which nine significant transition peaks are observed. The
upconversion mechanism of the co-doped tellurite glass has been
shown in the schematic energy diagrams. In this works, it is found
that the excited state-absorption (ESA) is still dominant in the
upconversion excitation process as the upconversion excitation
mechanism of the Nd3+ excited-state levels is accomplished through a
stepwise multiphonon process. An efficient excitation energy transfer
(ET) has been observed between Nd3+ as a donor and Er3+ as the
acceptor. As a result, respective emission spectra had been observed.
Abstract: To evaluate the ability to predict xerostomia after
radiotherapy, we constructed and compared neural network and
logistic regression models. In this study, 61 patients who completed a
questionnaire about their quality of life (QoL) before and after a full
course of radiation therapy were included. Based on this questionnaire,
some statistical data about the condition of the patients’ salivary
glands were obtained, and these subjects were included as the inputs of
the neural network and logistic regression models in order to predict
the probability of xerostomia. Seven variables were then selected from
the statistical data according to Cramer’s V and point-biserial
correlation values and were trained by each model to obtain the
respective outputs which were 0.88 and 0.89 for AUC, 9.20 and 7.65
for SSE, and 13.7% and 19.0% for MAPE, respectively. These
parameters demonstrate that both neural network and logistic
regression methods are effective for predicting conditions of parotid
glands.
Abstract: In this study, active tendons with Proportional Integral
Derivation type controllers were applied to a SDOF and a MDOF
building model. Physical models of buildings were constituted with
virtual springs, dampers and rigid masses. After that, equations of
motion of all degrees of freedoms were obtained. Matlab Simulink
was utilized to obtain the block diagrams for these equations of
motion. Parameters for controller actions were found by using a trial
method. After earthquake acceleration data were applied to the
systems, building characteristics such as displacements, velocities,
accelerations and transfer functions were analyzed for all degrees of
freedoms. Comparisons on displacement vs. time, velocity vs. time,
acceleration vs. time and transfer function (Db) vs. frequency (Hz)
were made for uncontrolled and controlled buildings. The results
show that the method seems feasible.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in the form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studied with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.