Abstract: Partial combustion of biomass in the gasifier generates producer gas that can be used for heating purposes and as supplementary or sole fuel in internal combustion engines. In this study, the virgin biomass obtained from hingan shell is used as the feedstock for gasifier to generate producer gas. The gasifier-engine system is operated on diesel and on esters of vegetable oil of hingan in liquid fuel mode operation and then on liquid fuel and producer gas combination in dual fuel mode operation. The performance and emission characteristics of the CI engine is analyzed by running the engine in liquid fuel mode operation and in dual fuel mode operation at different load conditions with respect to maximum diesel savings in the dual fuel mode operation. It was observed that specific energy consumption in the dual fuel mode of operation is found to be in the higher side at all load conditions. The brake thermal efficiency of the engine using diesel or hingan oil methyl ester (HOME) is higher than that of dual fuel mode operation. A diesel replacement in the tune of 60% in dual fuel mode is possible with the use of hingan shell producer gas. The emissions parameters such CO, HC, NOx, CO2 and smoke are higher in the case of dual fuel mode of operation as compared to that of liquid fuel mode.
Abstract: In the semiconductor manufacturing process, large
amounts of data are collected from various sensors of multiple
facilities. The collected data from sensors have several different characteristics
due to variables such as types of products, former processes
and recipes. In general, Statistical Quality Control (SQC) methods
assume the normality of the data to detect out-of-control states of
processes. Although the collected data have different characteristics,
using the data as inputs of SQC will increase variations of data,
require wide control limits, and decrease performance to detect outof-
control. Therefore, it is necessary to separate similar data groups
from mixed data for more accurate process control. In the paper,
we propose a regression tree using split algorithm based on Pearson
distribution to handle non-normal distribution in parametric method.
The regression tree finds similar properties of data from different
variables. The experiments using real semiconductor manufacturing
process data show improved performance in fault detecting ability.
Abstract: 2007 is a jubilee year: in 1967, programming language SIMULA 67 was presented, which contained all aspects of what was later called object-oriented programming. The present paper contains a description of the development unto the objectoriented programming, the role of simulation in this development and other tools that appeared in SIMULA 67 and that are nowadays called super-object-oriented programming.
Abstract: A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Abstract: Evolutionary Programming (EP) represents a
methodology of Evolutionary Algorithms (EA) in which mutation is
considered as a main reproduction operator. This paper presents a
novel EP approach for Artificial Neural Networks (ANN) learning.
The proposed strategy consists of two components: the self-adaptive,
which contains phenotype information and the dynamic, which is
described by genotype. Self-adaptation is achieved by the addition of
a value, called the network weight, which depends on a total number
of hidden layers and an average number of neurons in hidden layers.
The dynamic component changes its value depending on the fitness
of a chromosome, exposed to mutation. Thus, the mutation step size
is controlled by two components, encapsulated in the algorithm,
which adjust it according to the characteristics of a predefined ANN
architecture and the fitness of a particular chromosome. The
comparative analysis of the proposed approach and the classical EP
(Gaussian mutation) showed, that that the significant acceleration of
the evolution process is achieved by using both phenotype and
genotype information in the mutation strategy.
Abstract: A novel approach to speech coding using the hybrid architecture is presented. Advantages of parametric and perceptual coding methods are utilized together in order to create a speech coding algorithm assuring better signal quality than in traditional CELP parametric codec. Two approaches are discussed. One is based on selection of voiced signal components that are encoded using parametric algorithm, unvoiced components that are encoded perceptually and transients that remain unencoded. The second approach uses perceptual encoding of the residual signal in CELP codec. The algorithm applied for precise transient selection is described. Signal quality achieved using the proposed hybrid codec is compared to quality of some standard speech codecs.
Abstract: Although oil-based drilling fluids are of paramount practical and economical interest, they represent a serious source of pollution, once released into the environment as drill cuttings. The aim of this study is to assess the capability of isolated microorganisms to degrade gasoil fuel. The commonly used physicochemical and biodegradation remediation techniques of petroleum contaminated soil were both investigated. The study revealed that natural biodegradation is favorable. Even though, the presence of heavy metals, the moisture level of (8.55%) and nutrient deficiencies put severe constrains on microorganisms- survival ranges inhibiting the biodegradation process. The selected strains were able to degrade the diesel fuel at significantly high rates (around 98%).
Abstract: Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.
Abstract: Spent petroleum catalyst from Korean petrochemical
industry contains trace amount of metals such as Ni, V and Mo.
Therefore an attempt was made to recover those trace metal using
bioleaching process. Different leaching parameters such as Fe(II)
concentration, pulp density, pH, temperature and particle size of
spent catalyst particle were studied to evaluate their effects on the
leaching efficiency. All the three metal ions like Ni, V and Mo
followed dual kinetics, i.e., initial faster followed by slower rate. The
percentage of leaching efficiency of Ni and V were higher than Mo.
The leaching process followed a diffusion controlled model and the
product layer was observed to be impervious due to formation of
ammonium jarosite (NH4)Fe3(SO4)2(OH)6. In addition, the lower
leaching efficiency of Mo was observed due to a hydrophobic coating
of elemental sulfur over Mo matrix in the spent catalyst.
Abstract: The square-lattice Ising model is the simplest system
showing phase transitions (the transition between the paramagnetic
phase and the ferromagnetic phase and the transition between the
paramagnetic phase and the antiferromagnetic phase) and critical
phenomena at finite temperatures. The exact solution of the squarelattice
Ising model with free boundary conditions is not known for
systems of arbitrary size. For the first time, the exact solution of
the Ising model on the square lattice with free boundary
conditions is obtained after classifying all )
spin configurations with the microcanonical transfer matrix. Also, the
phase transitions and critical phenomena of the square-lattice Ising
model are discussed using the exact solution on the square
lattice with free boundary conditions.
Abstract: Human-related information security breaches within organizations are primarily caused by employees who have not been made aware of the importance of protecting the information they work with. Information security awareness is accordingly attracting more attention from industry, because stakeholders are held accountable for the information with which they work. The authors developed an Information Security Retrieval and Awareness model – entitled “ISRA" – that is tailored specifically towards enhancing information security awareness in industry amongst all users of information, to address shortcomings in existing information security awareness models. This paper is principally aimed at expounding a prototype for the ISRA model to highlight the advantages of utilizing the model. The prototype will focus on the non-technical, humanrelated information security issues in industry. The prototype will ensure that all stakeholders in an organization are part of an information security awareness process, and that these stakeholders are able to retrieve specific information related to information security issues relevant to their job category, preventing them from being overburdened with redundant information.
Abstract: The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,
April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.
Abstract: Accurate loss minimization is the critical component
for efficient electrical distribution power flow .The contribution of
this work presents loss minimization in power distribution system
through feeder restructuring, incorporating DG and placement of
capacitor. The study of this work was conducted on IEEE
distribution network and India Electricity Board benchmark
distribution system. The executed experimental result of Indian
system is recommended to board and implement practically for
regulated stable output.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.
Abstract: This paper proposes a low power SRAM based on
five transistor SRAM cell. Proposed SRAM uses novel word-line
decoding such that, during read/write operation, only selected cell
connected to bit-line whereas, in conventional SRAM (CV-SRAM),
all cells in selected row connected to their bit-lines, which in turn
develops differential voltages across all bit-lines, and this makes
energy consumption on unselected bit-lines. In proposed SRAM
memory array divided into two halves and this causes data-line
capacitance to reduce. Also proposed SRAM uses one bit-line and
thus has lower bit-line leakage compared to CV-SRAM.
Furthermore, the proposed SRAM incurs no area overhead, and has
comparable read/write performance versus the CV-SRAM.
Simulation results in standard 0.25μm CMOS technology shows in
worst case proposed SRAM has 80% smaller dynamic energy
consumption in each cycle compared to CV-SRAM. Besides, energy
consumption in each cycle of proposed SRAM and CV-SRAM
investigated analytically, the results of which are in good agreement
with the simulation results.
Abstract: To reduce the carbon dioxide emission into the
atmosphere, adsorption is believed to be one of the most attractive
methods for post-combustion treatment of flue gas. In this work,
activated carbon (AC) was modified by polyethylenimine (PEI) via
impregnation in order to enhance CO2 adsorption capacity. The
adsorbents were produced at 0.04, 0.16, 0.22, 0.25, and 0.28 wt%
PEI/AC. The adsorption was carried out at a temperature range from
30 °C to 75 °C and five different gas pressures up to 1 atm. TG-DTA,
FT-IR, UV-visible spectrometer, and BET were used to characterize
the adsorbents. Effects of PEI loading on the AC for the CO2
adsorption were investigated. Effectiveness of the adsorbents on the
CO2 adsorption including CO2 adsorption capacity and adsorption
temperature was also investigated. Adsorption capacities of CO2 were
enhanced with the increase in the amount of PEI from 0.04 to 0.22
wt% PEI before the capacities decreased onwards from0.25 wt% PEI
at 30 °C. The 0.22 wt% PEI/AC showed higher adsorption capacity
than the AC for adsorption at 50 °C to 75 °C.
Abstract: With major technological advances and to reduce the
cost of training apprentices for real-time critical systems, it was
necessary the development of Intelligent Tutoring Systems for
training apprentices in these systems. These systems, in general, have
interactive features so that the learning is actually more efficient,
making the learner more familiar with the mechanism in question. In
the home stage of learning, tests are performed to obtain the student's
income, a measure on their use. The aim of this paper is to present a
framework to model an Intelligent Tutoring Systems using the UML
language. The various steps of the analysis are considered the
diagrams required to build a general model, whose purpose is to
present the different perspectives of its development.
Abstract: Information regarding early onset neonatal sepsis
(EONS) pathogens may vary between regions. Global perspectives
showed Group B Streptococcal (GBS) as the most common causative
pathogens, but the widespread use of intrapartum antibiotics has
changed the pathogens pattern towards gram negative
microorganisms, especially E. coli. Objective of this study is to
describe the pathogens isolated, to assess current treatment and risk
of EONS. Records of 899 neonates born in three General Hospitals
between 2009 until 2012 were retrospectively reviewed. Proven was
found in 22 (3%) neonates. The majority was isolated with gram
positive organisms, 17 (2.3%). All grams positive and most gram
negative organisms showed sensitivity to the tested antibiotics. Only
two rare gram negative organisms showed total resistant. Male was
possible risk of proven EONS. Although proven EONS remains
uncommon in Malaysia, nonetheless, the effect of intrapartum
antibiotics still required continuous surveillance.
Abstract: There is an urgent need to develop novel
Mycobacterium tuberculosis (Mtb) drugs that are active against drug
resistant bacteria but, more importantly, kill persistent bacteria. Our
study structured based on integrated analysis of metabolic pathways,
small molecule screening and similarity Search in PubChem
Database. Metabolic analysis approaches based on Unified weighted
used for potent target selection. Our results suggest that pantothenate
synthetase (panC) and and 3-methyl-2-oxobutanoate hydroxymethyl
transferase (panB) as a appropriate drug targets. In our study, we
used pantothenate synthetase because of existence inhibitors. We
have reported the discovery of new antitubercular compounds
through ligand based approaches using computational tools.