Abstract: This research studied recycled wastes by Recyclable Material Bank project of 17 universities of Thailand for evaluation of reducing greenhouse gasses emission compared with landfilling activity during January 2011 to December 2011. The results showed that the projects collected total amount of recyclable wastes about 1,626.917 metric ton. The office paper has the largest amount among these recycled wastes (55.61 % of total recycled wastes). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables and metal, respectively. The project reduced greenhouse gasses emission equivalent to about 5,263.481 metric ton of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gasses emission is office paper which is 73.45% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metal, mixed recyclables and glass, respectively.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
three feature selection methods are evaluated: Random Selection,
Information Gain (IG) and Support Vector Machine feature selection
(called SVM_FS). We show that the best results were obtained with
SVM_FS method for a relatively small dimension of the feature
vector. Also we present a novel method to better correlate SVM
kernel-s parameters (Polynomial or Gaussian kernel).
Abstract: Mechanical buckling analysis of rectangular plates
with central circular cutout is performed in this paper. The finiteelement
method is used to study the effects of plate-support
conditions, aspect ratio, and hole size on the mechanical buckling
strength of the perforated plates subjected to linearly varying loading.
Results show that increasing the hole size does not necessarily reduce
the mechanical buckling strength of the perforated plates. It is also
concluded that the clamped boundary condition increases the
mechanical buckling strength of the perforated plates more than the
simply-supported boundary condition and the free boundary
conditions enhance the mechanical buckling strength of the
perforated plates more effectively than the fixed boundary conditions.
Furthermore, for the bending cases, the critical buckling load of
perforated plates with free edges is less than perforated plates with
fixed edges.
Abstract: The main objective of this study was to remove and recover Ni, Cu and Fe from a mixed metal system using sodium hypophosphite as a reducing agent and nickel powder as seeding material. The metal systems studied consisted of Ni-Cu, Ni-Fe and Ni-Cu-Fe solutions. A 5 L batch reactor was used to conduct experiments where 100 mg/l of each respective metal was used. It was found that the metals were reduced to their elemental form with removal efficiencies of over 80%. The removal efficiency decreased in the order Fe>Ni>Cu. The metal powder obtained contained between 97-99% Ni and was almost spherical and porous. Size enlargement by aggregation was the dominant particulate process.
Abstract: Although lots of research work has been done for
human pose recognition, the view-point of cameras is still critical
problem of overall recognition system. In this paper, view-point
insensitive human pose recognition is proposed. The aims of the
proposed system are view-point insensitivity and real-time processing.
Recognition system consists of feature extraction module, neural
network and real-time feed forward calculation. First, histogram-based
method is used to extract feature from silhouette image and it is
suitable for represent the shape of human pose. To reduce the
dimension of feature vector, Principle Component Analysis(PCA) is
used. Second, real-time processing is implemented by using Compute
Unified Device Architecture(CUDA) and this architecture improves
the speed of feed-forward calculation of neural network. We
demonstrate the effectiveness of our approach with experiments on
real environment.
Abstract: In this paper, a neural network tuned fuzzy controller
is proposed for controlling Multi-Input Multi-Output (MIMO)
systems. For the convenience of analysis, the structure of MIMO
fuzzy controller is divided into single input single-output (SISO)
controllers for controlling each degree of freedom. Secondly,
according to the characteristics of the system-s dynamics coupling, an
appropriate coupling fuzzy controller is incorporated to improve the
performance. The simulation analysis on a two-level mass–spring
MIMO vibration system is carried out and results show the
effectiveness of the proposed fuzzy controller. The performance
though improved, the computational time and memory used is
comparatively higher, because it has four fuzzy reasoning blocks and
number may increase in case of other MIMO system. Then a fuzzy
neural network is designed from a set of input-output training data to
reduce the computing burden during implementation. This control
strategy can not only simplify the implementation problem of fuzzy
control, but also reduce computational time and consume less
memory.
Abstract: This paper describes the implementation and testing
of a multichannel active noise control system (ANCS) based on the
filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is
derived from the well-known filtered-x LMS (FXLMS) algorithm
with the aim to improve the rate of convergence of the multichannel
FXLMS algorithm and to reduce its computational load. Laboratory
setup and techniques used to implement this system efficiently are
described in this paper. Experiments performed in order to test the
performance of the FILMS algorithm are discussed and the obtained
results presented.
Abstract: This presentation reviews recent advances in superalloys and thermal barrier coating (TBC) for application in hot sections of energy-efficient gas-turbine engines. It has been reviewed that in the modern combined-cycle gas turbines (CCGT) applying single-crystal energy materials (SC superalloys) and thermal barrier coatings (TBC), and – in one design – closed-loop steam cooling, thermal efficiency can reach more than 60%. These technological advancements contribute to profitable and clean power generation with reduced emission. Alternatively, the use of advanced superalloys (e.g. GTD-111 superalloy, Allvac 718Plus superalloy) and advanced thermal barrier coatings (TBC) in modern gas-turbines has been shown to yield higher energy-efficiency in power generation.
Abstract: This manuscript presents, palmprint recognition by
combining different texture extraction approaches with high accuracy.
The Region of Interest (ROI) is decomposed into different frequencytime
sub-bands by wavelet transform up-to two levels and only the
approximate image of two levels is selected, which is known as
Approximate Image ROI (AIROI). This AIROI has information of
principal lines of the palm. The Competitive Index is used as the
features of the palmprint, in which six Gabor filters of different
orientations convolve with the palmprint image to extract the orientation
information from the image. The winner-take-all strategy
is used to select dominant orientation for each pixel, which is
known as Competitive Index. Further, PCA is applied to select highly
uncorrelated Competitive Index features, to reduce the dimensions of
the feature vector, and to project the features on Eigen space. The
similarity of two palmprints is measured by the Euclidean distance
metrics. The algorithm is tested on Hong Kong PolyU palmprint
database. Different AIROI of different wavelet filter families are also
tested with the Competitive Index and PCA. AIROI of db7 wavelet
filter achievs Equal Error Rate (EER) of 0.0152% and Genuine
Acceptance Rate (GAR) of 99.67% on the palm database of Hong
Kong PolyU.
Abstract: Increasing concerns over climate change have limited
the liberal usage of available energy technology options. India faces
a formidable challenge to meet its energy needs and provide adequate
energy of desired quality in various forms to users in sustainable
manner at reasonable costs. In this paper, work carried out with an
objective to study the role of various energy technology options
under different scenarios namely base line scenario, high nuclear
scenario, high renewable scenario, low growth and high growth rate
scenario. The study has been carried out using Model for Energy
Supply Strategy Alternatives and their General Environmental
Impacts (MESSAGE) model which evaluates the alternative energy
supply strategies with user defined constraints on fuel availability,
environmental regulations etc. The projected electricity demand, at
the end of study period i.e. 2035 is 500490 MWYr. The model
predicted the share of the demand by Thermal: 428170 MWYr,
Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr
in the base line scenario. Coal remains the dominant fuel for
production of electricity during the study period. However, the
import dependency of coal increased during the study period. In
baseline scenario the cumulative carbon dioxide emissions upto 2035
are about 11,000 million tones of CO2. In the scenario of high nuclear
capacity the carbon dioxide emissions reduced by 10 % when nuclear
energy share increased to 9 % compared to 3 % in baseline scenario.
Similarly aggressive use of renewables reduces 4 % of carbon
dioxide emissions.
Abstract: A wideband 2-1-1 cascaded ΣΔ modulator with a
single-bit quantizer in the two first stages and a 4-bit quantizer in the
final stage is developed. To reduce sensitivity of digital-to-analog
converter (DAC) nonlinearities in the feedback of the last stage,
dynamic element matching (DEM) is introduced. This paper presents
two modelling approaches: The first is MATLAB description and the
second is VHDL-AMS modelling of the proposed architecture and
exposes some high-level-simulation results allowing a behavioural
study. The detail of both ideal and non-ideal behaviour modelling are
presented. Then, the study of the effect of building blocks
nonidealities is presented; especially the influences of nonlinearity,
finite operational amplifier gain, amplifier slew rate limitation and
capacitor mismatch. A VHDL-AMS description presents a good
solution to predict system-s performances and can provide sensitivity
curves giving the impact of nonidealities on the system performance.
Abstract: Since 2005, an SRF module of CESR type serves as the
accelerating cavity at the Taiwan Light Source in the National
Synchrotron Radiation Research Center. A 500-MHz niobium cavity
is immersed in liquid helium inside this SRF module. To reduce heat
load, the liquid helium vessel is thermally shielded by
liquid-nitrogen-cooled copper layer, and the beam chambers are also
anchored with pipes of the liquid nitrogen flow in middle of the liquid
helium vessel and the vacuum vessel. A strong correlation of the
movement of the cavity-s frequency tuner with the temperature
variation of parts cooled with liquid nitrogen was observed. A
previous study on a spare SRF module with the niobium cavity cooled
by liquid nitrogen instead of liquid helium, satisfactory suppression of
the thermal oscillation was achieved by attaching a temporary buffer
tank for the vented shielding nitrogen flow from the SRF module. In
this study, a home-made buffer tank is designed and integrated to the
spare SRF module with cavity cooled by liquid helium. Design,
construction, integration, and preliminary test results of this buffer
tank are presented.
Abstract: In order to monitor the water table depth on soil profile
salinity buildup, a field study was carried out during 2006-07. Wheat
(Rabi) and Sorghum (Kharif) fodder were sown in with three
treatments. The results showed that watertable depth lowered from
1.15m to 2.89 m depth at the end of experiment. With lower of
watertable depth, pH, ECe and SAR decreased under crops both
without and with gypsum and increased in fallowing. Soil moisture
depletion was directly proportional to lowering of watertable. With the
application of irrigation water (58cm) pH, ECe and SAR were reduced
in cropped plots, reduction was higher in gypsum applied plots than
non-gypsum plots. In case of fallowing, there was increase in pH, EC,
while slight reduction occurred in SAR values. However, soil salinity
showed an increasing upward trend under fallowing and its value in
0-30 cm soil layer was the highest amongst the treatments.
Abstract: Owing to the stringent environmental legislations,
CO2 capture and sequestration is one of the viable solutions to reduce
the CO2 emissions from various sources. In this context, Ionic liquids
(ILs) are being investigated as suitable absorption media for CO2
capture. Due to their non-evaporative, non-toxic, and non-corrosive
nature, these ILs have the potential to replace the existing solvents
like aqueous amine solutions for CO2 separation technologies. Thus,
the present work aims at studying the important aspects such as the
interactions of CO2 molecule with different anions (F-, Br-, Cl-, NO3
-,
BF4
-, PF6
-, Tf2N-, and CF3SO3
-) that are commonly used in ILs
through molecular modeling. In this, the minimum energy structures
have been obtained using Ab initio based calculations at MP2
(Moller-Plesset perturbation) level. Results revealed various degrees
of distortion of CO2 molecule (from its linearity) with the anions
studied, most likely due to the Lewis acid-base interactions between
CO2 and anion. Furthermore, binding energies for the anion-CO2
complexes were also calculated. The implication of anion-CO2
interactions to the solubility of CO2 in ionic liquids is also discussed.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.
Abstract: Dealing with hundreds of features in character
recognition systems is not unusual. This large number of features
leads to the increase of computational workload of recognition
process. There have been many methods which try to remove
unnecessary or redundant features and reduce feature dimensionality.
Besides because of the characteristics of Farsi scripts, it-s not
possible to apply other languages algorithms to Farsi directly. In this
paper some methods for feature subset selection using genetic
algorithms are applied on a Farsi optical character recognition (OCR)
system. Experimental results show that application of genetic
algorithms (GA) to feature subset selection in a Farsi OCR results in
lower computational complexity and enhanced recognition rate.
Abstract: Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.
Abstract: The most widely used semiconductor memory types
are the Dynamic Random Access Memory (DRAM) and Static
Random Access memory (SRAM). Competition among memory
manufacturers drives the need to decrease power consumption and
reduce the probability of read failure. A technology that is relatively
new and has not been explored is the FinFET technology. In this
paper, a single cell Schmitt Trigger Based Static RAM using FinFET
technology is proposed and analyzed. The accuracy of the result is
validated by means of HSPICE simulations with 32nm FinFET
technology and the results are then compared with 6T SRAM using
the same technology.
Abstract: Existing experiences indicate that one of the most
prominent reasons that some ERP implementations fail is related to
selecting an improper ERP package. Among those important factors
resulting in inappropriate ERP selections, one is to ignore preliminary
activities that should be done before the evaluation of ERP packages.
Another factor yielding these unsuitable selections is that usually
organizations employ prolonged and costly selection processes in
such extent that sometimes the process would never be finalized
or sometimes the evaluation team might perform many key final
activities in an incomplete or inaccurate way due to exhaustion, lack
of interest or out-of-date data. In this paper, a systematic approach
that recommends some activities to be done before and after the
main selection phase is introduced for choosing an ERP package. On
the other hand, the proposed approach has utilized some ideas that
accelerates the selection process at the same time that reduces the
probability of an erroneous final selection.
Abstract: This paper presents a vocoder to obtain high quality synthetic speech at 600 bps. To reduce the bit rate, the algorithm is based on a sinusoidally excited linear prediction model which extracts few coding parameters, and three consecutive frames are grouped into a superframe and jointly vector quantization is used to obtain high coding efficiency. The inter-frame redundancy is exploited with distinct quantization schemes for different unvoiced/voiced frame combinations in the superframe. Experimental results show that the quality of the proposed coder is better than that of 2.4kbps LPC10e and achieves approximately the same as that of 2.4kbps MELP and with high robustness.