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: Unified Speech Audio Coding (USAC), the latest MPEG standardization for unified speech and audio coding, uses a speech/audio classification algorithm to distinguish speech and audio segments of the input signal. The quality of the recovered audio can be increased by well-designed orchestra/percussion classification and subsequent processing. However, owing to the shortcoming of the system, introducing an orchestra/percussion classification and modifying subsequent processing can enormously increase the quality of the recovered audio. This paper proposes an orchestra/percussion classification algorithm for the USAC system which only extracts 3 scales of Mel-Frequency Cepstral Coefficients (MFCCs) rather than traditional 13 scales of MFCCs and use Iterative Dichotomiser 3 (ID3) Decision Tree rather than other complex learning method, thus the proposed algorithm has lower computing complexity than most existing algorithms. Considering that frequent changing of attributes may lead to quality loss of the recovered audio signal, this paper also design a modified subsequent process to help the whole classification system reach an accurate rate as high as 97% which is comparable to classical 99%.
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: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.
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: In this paper, the problem of reducing switching
activity in on-chip buses at the stage of high-level synthesis is
considered, and a high-level low power bus binding based on dynamic
bit reordering is proposed. Whereas conventional methods use a fixed
bit ordering between variables within a bus, the proposed method
switches a bit ordering dynamically to obtain a switching activity
reduction. As a result, the proposed method finds a binding solution
with a smaller value of total switching activity (TSA). Experimental
result shows that the proposed method obtains a binding solution
having 12.0-34.9% smaller TSA compared with the conventional
methods.
Abstract: An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.
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: The aim of the study was to identify seat belt wearing
factor among road users in Malaysia. Evidence-based approach
through in-depth crash investigation was utilised to determine the
intended objectives. The objective was scoped into crashes
investigated by Malaysian Institute of Road Safety Research
(MIROS) involving passenger vehicles within 2007 and 2010. Crash
information of a total of 99 crash cases involving 240 vehicles and
864 occupants were obtained during the study period. Statistical test
and logistic regression analysis have been performed. Results of the
analysis revealed that gender, seat position and age were associated
with seat belt wearing compliance in Malaysia. Males are 97.6%
more likely to wear seat belt compared to females (95% CI 1.317 to
2.964). By seat position, the finding indicates that frontal occupants
were 82 times more likely to be wearing seat belt (95% CI 30.199 to
225.342) as compared to rear occupants. It is also important to note
that the odds of seat belt wearing increased by about 2.64% (95% CI
1.0176 to 1.0353) for every one year increase in age. This study is
essential in understanding the Malaysian tendency in belting up
while being occupied in a vehicle. The factors highlighted in this
study should be emphasized in road safety education in order to
increase seat belt wearing rate in this country and ultimately in
preventing deaths due to road crashes.
Abstract: This paper presents an application of 5S lean technology to a production facility. Due to increased demand, high product variety, and a push production system, the plant has suffered from excessive wastes, unorganized workstations, and unhealthy work environment. This has translated into increased production cost, frequent delays, and low workers morale. Under such conditions, it has become difficult, if not impossible, to implement effective continuous improvement studies. Hence, the lean project is aimed at diagnosing the production process, streamlining the workflow, removing/reducing process waste, cleaning the production environment, improving plant layout, and organizing workstations. 5S lean technology is utilized for achieving project objectives. The work was a combination of both culture changes and tangible/physical changes on the shop floor. The project has drastically changed the plant and developed the infrastructure for a successful implementation of continuous improvement as well as other best practices and quality initiatives.
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: This paper presents a wrap-around view system with 4
smart cameras module and remote motion mobile robot control equipped with smart camera module system. The two-level scheme for
remote motion control with smart-pad(IPAD) is introduced on this
paper. In the low-level, the wrap-around view system is controlled or operated to keep the reference points lying around top view image
plane. On the higher level, a robot image based motion controller is utilized to drive the mobile platform to reach the desired position or
track the desired motion planning through image feature feedback. The
design wrap-around view system equipped on presents such advantages as follows: 1) a satisfactory solution for the FOV and affine
problem; 2) free of any complex and constraint with robot pose. The performance of the wrap-around view equipped on mobile robot
remote control is proven by experimental results.
Abstract: Due to the environmental and price issues of current
energy crisis, scientists and technologists around the globe are
intensively searching for new environmentally less-impact form of
clean energy that will reduce the high dependency on fossil fuel.
Particularly hydrogen can be produced from biomass via thermochemical
processes including pyrolysis and gasification due to the
economic advantage and can be further enhanced through in-situ
carbon dioxide removal using calcium oxide. This work focuses on
the synthesis and development of the flowsheet for the enhanced
biomass gasification process in PETRONAS-s iCON process
simulation software. This hydrogen prediction model is conducted at
operating temperature between 600 to 1000oC at atmospheric
pressure. Effects of temperature, steam-to-biomass ratio and
adsorbent-to-biomass ratio were studied and 0.85 mol fraction of
hydrogen is predicted in the product gas. Comparisons of the results
are also made with experimental data from literature. The
preliminary economic potential of developed system is RM 12.57 x
106 which equivalent to USD 3.77 x 106 annually shows economic
viability of this process.
Abstract: A study was undertaken to assess the potential of an
Algal Turf Scrubber to remove nitrogen from aquaculture effluent to
reduce environmental pollution. High total ammonia nitrogen
concentrations were introduced to an Algal Turf Scrubber developed
under varying hydraulic surface loading rates of African catfish
(Clarius gariepinus) effluent in a recirculating aquaculture system.
Nutrient removal rates were not affected at total suspended solids
concentration of up to 0.04g TSS/l (P > 0.05). Nitrogen removal
rates 0.93-0.99g TAN/m²/d were recorded at very high loading rates
3.76-3.81 g TAN/m²/d. Total ammonia removal showed ½ order
kinetics between 1.6 to 2.3mg/l Total Ammonia Nitrogen
concentrations. Nitrogen removal increased with its loading, which
increased with hydraulic surface loading rate. Total Ammonia
Nitrogen removal by Algal turf scrubber was higher than reported
values for fluidized bed filters and trickling filters. The algal turf
scrubber also effectively removed nitrate thereby reducing the need
for water exchange.
Abstract: This paper attempts to establish the fact that Multi
State Network Classification is essential for performance
enhancement of Transport protocols over Satellite based Networks. A
model to classify Multi State network condition taking into
consideration both congestion and channel error is evolved. In order
to arrive at such a model an analysis of the impact of congestion and
channel error on RTT values has been carried out using ns2. The
analysis results are also reported in the paper. The inference drawn
from this analysis is used to develop a novel statistical RTT based
model for multi state network classification.
An Adaptive Multi State Proactive Transport Protocol consisting
of Proactive Slow Start, State based Error Recovery, Timeout Action
and Proactive Reduction is proposed which uses the multi state
network state classification model. This paper also confirms through
detail simulation and analysis that a prior knowledge about the
overall characteristics of the network helps in enhancing the
performance of the protocol over satellite channel which is
significantly affected due to channel noise and congestion.
The necessary augmentation of ns2 simulator is done for
simulating the multi state network classification logic. This
simulation has been used in detail evaluation of the protocol under
varied levels of congestion and channel noise. The performance
enhancement of this protocol with reference to established protocols
namely TCP SACK and Vegas has been discussed. The results as
discussed in this paper clearly reveal that the proposed protocol
always outperforms its peers and show a significant improvement in
very high error conditions as envisaged in the design of the protocol.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Wireless mobile communications have experienced
the phenomenal growth through last decades. The advances in
wireless mobile technologies have brought about a demand for high
quality multimedia applications and services. For such applications
and services to work, signaling protocol is required for establishing,
maintaining and tearing down multimedia sessions. The Session
Initiation Protocol (SIP) is an application layer signaling protocols,
based on request/response transaction model. This paper considers
SIP INVITE transaction over an unreliable medium, since it has been
recently modified in Request for Comments (RFC) 6026. In order to
help in assuring that the functional correctness of this modification is
achieved, the SIP INVITE transaction is modeled and analyzed using
Colored Petri Nets (CPNs). Based on the model analysis, it is
concluded that the SIP INVITE transaction is free of livelocks and
dead codes, and in the same time it has both desirable and
undesirable deadlocks. Therefore, SIP INVITE transaction should be
subjected for additional updates in order to eliminate undesirable
deadlocks. In order to reduce the cost of implementation and
maintenance of SIP, additional remodeling of the SIP INVITE
transaction is recommended.
Abstract: This paper describes a complex energy signal model
that is isomorphic with digital human fingerprint images. By using
signal models, the problem of fingerprint matching is transformed
into the signal processing problem of finding a correlation between
two complex signals that differ by phase-rotation and time-scaling. A
technique for minutiae matching that is independent of image
translation, rotation and linear-scaling, and is resistant to missing
minutiae is proposed. The method was tested using random data
points. The results show that for matching prints the scaling and
rotation angles are closely estimated and a stronger match will have a
higher correlation.