Abstract: Recent research on seeds of bio-diesel plants like
Jatropha curcas, constituting 40-50% bio-crude oil indicates its
potential as one of the most promising alternatives to conventional
sources of energy. Also, limited studies on utilization of de-oiled cake
have revealed that Jatropha bio-waste has good potential to be used as
organic fertilizers produced via aerobic and anaerobic treatment.
However, their commercial exploitation has not yet been possible. The
present study aims at developing appropriate bio-processes and
formulations utilizing Jatropha seed cake as organic fertilizer, for
improving the growth of Polianthes tuberose L. (Tuberose). Pot
experiments were carried out by growing tuberose plants on soil
treated with composted formulations of Jatropha de-oiled cake, Farm
Yard Manure (FYM) and inorganic fertilizers were also blended in
soil. The treatment was carried out through soil amendment as well as
foliar spray. The growth and morphological parameters were
monitored for entire crop cycle.
The growth Length and number of leaves, spike length, rachis
length, number of bulb per plant and earliness of sprouting of bulb and
yield enhancement were comparable to that achieved under inorganic
fertilizer. Furthermore, performance of inorganic fertilizer also showed
an improvement when blended with composted bio-waste. These
findings would open new avenues for Jatropha based bio-wastes to be
composted and used as organic fertilizers for commercial floriculture.
Abstract: We present a novel construction of 16-QAM codewords of length n = 2k . The number of constructed codewords is 162×[4k-1×k-k+1] . When these constructed codewords are utilized as a code in OFDM systems, their peak-to-mean envelope power ratios (PMEPR) are bounded above by 3.6 . The principle of our scheme is illustrated with a four subcarrier example.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: We demonstrate the synthesis of intermediary views
within a sequence of color encoded, materials discriminating, X-ray
images that exhibit animated depth in a visual display. During the
image acquisition process, the requirement for a linear X-ray detector
array is replaced by synthetic image. Scale Invariant Feature
Transform, SIFT, in combination with material segmented morphing
is employed to produce synthetic imagery. A quantitative analysis of
the feature matching performance of the SIFT is presented along with
a comparative study of the synthetic imagery. We show that the total
number of matches produced by SIFT reduces as the angular
separation between the generating views increases. This effect is
accompanied by an increase in the total number of synthetic pixel
errors. The trends observed are obtained from 15 different luggage
items. This programme of research is in collaboration with the UK
Home Office and the US Dept. of Homeland Security.
Abstract: In this report we present a rule-based approach to
detect anomalous telephone calls. The method described here uses
subscriber usage CDR (call detail record) data sampled over two
observation periods: study period and test period. The study period
contains call records of customers- non-anomalous behaviour.
Customers are first grouped according to their similar usage
behaviour (like, average number of local calls per week, etc). For
customers in each group, we develop a probabilistic model to describe
their usage. Next, we use maximum likelihood estimation (MLE) to
estimate the parameters of the calling behaviour. Then we determine
thresholds by calculating acceptable change within a group. MLE is
used on the data in the test period to estimate the parameters of the
calling behaviour. These parameters are compared against thresholds.
Any deviation beyond the threshold is used to raise an alarm. This
method has the advantage of identifying local anomalies as compared
to techniques which identify global anomalies. The method is tested
for 90 days of study data and 10 days of test data of telecom
customers. For medium to large deviations in the data in test window,
the method is able to identify 90% of anomalous usage with less than
1% false alarm rate.
Abstract: The interaction of tunneling or mining with
groundwater has become a very relevant problem not only due to the
need to guarantee the safety of workers and to assure the efficiency of
the tunnel drainage systems, but also to safeguard water resources
from impoverishment and pollution risk. Therefore it is very
important to forecast the drainage processes (i.e., the evaluation of
drained discharge and drawdown caused by the excavation). The aim
of this study was to know better the system and to quantify the flow
drained from the Fontane mines, located in Val Germanasca (Turin,
Italy). This allowed to understand the hydrogeological local changes
in time. The work has therefore been structured as follows: the
reconstruction of the conceptual model with the geological,
hydrogeological and geological-structural study; the calculation of
the tunnel inflows (through the use of structural methods) and the
comparison with the measured flow rates; the water balance at the
basin scale. In this way it was possible to understand what are the
relationships between rainfall, groundwater level variations and the
effect of the presence of tunnels as a means of draining water.
Subsequently, it the effects produced by the excavation of the mining
tunnels was quantified, through numerical modeling. In particular,
the modeling made it possible to observe the drawdown variation as a
function of number, excavation depth and different mines linings.
Abstract: This paper presents a new method for estimating the mean curve of impulse voltage waveforms that are recorded during impulse tests. In practice, these waveforms are distorted by noise, oscillations and overshoot. The problem is formulated as an estimation problem. Estimation of the current signal parameters is achieved using a fast and accurate technique. The method is based on discrete dynamic filtering algorithm (DDF). The main advantage of the proposed technique is its ability in producing the estimates in a very short time and at a very high degree of accuracy. The algorithm uses sets of digital samples of the recorded impulse waveform. The proposed technique has been tested using simulated data of practical waveforms. Effects of number of samples and data window size are studied. Results are reported and discussed.
Abstract: Reinforced concrete crash barriers used in road traffic
must meet a number of criteria. Crash barriers are laid lengthwise,
one behind another, and joined using specially designed steel locks.
While developing BSV reinforced concrete crash barriers (type
ŽPSV), experiments and calculations aimed to optimize the shape of
a newly designed lock and the reinforcement quantity and
distribution in a crash barrier were carried out. The tension carrying
capacity of two parallelly joined locks was solved experimentally.
Based on the performed experiments, adjustments of nonlinear
properties of steel were performed in the calculations. The obtained
results served as a basis to optimize the lock design using a
computational model that takes into account the plastic behaviour of
steel and the influence of the surrounding concrete [6]. The response
to the vehicle impact has been analyzed using a specially elaborated
complex computational model, comprising both the nonlinear model
of the damping wall or crash barrier and the detailed model of the
vehicle [7].
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.
Abstract: Solution to unsteady Navier-Stokes equation by Splitting method in physical orthogonal algebraic curvilinear coordinate system, also termed 'Non-linear grid system' is presented. The linear terms in Navier-Stokes equation are solved by Crank- Nicholson method while the non-linear term is solved by the second order Adams-Bashforth method. This work is meant to bring together the advantage of Splitting method as pressure-velocity solver of higher efficiency with the advantage of consuming Non-linear grid system which produce more accurate results in relatively equal number of grid points as compared to Cartesian grid. The validation of Splitting method as a solution of Navier-Stokes equation in Nonlinear grid system is done by comparison with the benchmark results for lid driven cavity flow by Ghia and some case studies including Backward Facing Step Flow Problem.
Abstract: In this paper, we study the application of Extreme
Learning Machine (ELM) algorithm for single layered feedforward
neural networks to non-linear chaotic time series problems. In this
algorithm the input weights and the hidden layer bias are randomly
chosen. The ELM formulation leads to solving a system of linear
equations in terms of the unknown weights connecting the hidden
layer to the output layer. The solution of this general system of
linear equations will be obtained using Moore-Penrose generalized
pseudo inverse. For the study of the application of the method we
consider the time series generated by the Mackey Glass delay
differential equation with different time delays, Santa Fe A and
UCR heart beat rate ECG time series. For the choice of sigmoid,
sin and hardlim activation functions the optimal values for the
memory order and the number of hidden neurons which give the
best prediction performance in terms of root mean square error are
determined. It is observed that the results obtained are in close
agreement with the exact solution of the problems considered
which clearly shows that ELM is a very promising alternative
method for time series prediction.
Abstract: The physical methods for RNA secondary structure prediction are time consuming and expensive, thus methods for computational prediction will be a proper alternative. Various algorithms have been used for RNA structure prediction including dynamic programming and metaheuristic algorithms. Musician's behaviorinspired harmony search is a recently developed metaheuristic algorithm which has been successful in a wide variety of complex optimization problems. This paper proposes a harmony search algorithm (HSRNAFold) to find RNA secondary structure with minimum free energy and similar to the native structure. HSRNAFold is compared with dynamic programming benchmark mfold and metaheuristic algorithms (RnaPredict, SetPSO and HelixPSO). The results showed that HSRNAFold is comparable to mfold and better than metaheuristics in finding the minimum free energies and the number of correct base pairs.
Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: This paper presents an overview of the Ocean wave kinetic energy harvesting system. Energy harvesting is a concept by which energy is captured, stored, and utilized using various sources by employing interfaces, storage devices, and other units. Ocean wave energy harvesting in which the kinetic and potential energy contained in the natural oscillations of Ocean waves are converted into electric power. The kinetic energy harvesting system could be used for a number of areas. The main applications that we have discussed in this paper are to how generate the energy from Ocean wave energy (kinetic energy) to electric energy that is to eliminate the requirement for continual battery replacement.
Abstract: For the past thirty years the Malaysian economy has been said to contribute well to the progress of the nations. However, the intensification of global economy activity and the extensive use of Information Communication Technologies (ICTs) in recent years are challenging government-s effort to further develop Malaysian society. The competition posed by the low wage economies such as China and Vietnam have made the government realise the importance of engaging in high-skill and high technology industries. It is hoped this will be the basis of attracting more foreign direct investment (FDI) in order to help the country to compete in globalised world. Using Vision 2020 as it targeted vision, the government has decided to engage in the use of ICTs and introduce many policies pertaining to it. Mainly based on the secondary analysis approach, the findings show that policy pertaining to ICTs in Malaysia contributes to economic growth, but the consequences of this have resulted in greater division within society. Although some of the divisions such as gender and ethnicity are narrowing down, the gap in important areas such as regions and class differences is becoming wider. The widespread use of ICTs might contribute to the further establishment of democracy in Malaysia, but the increasing number of foreign entities such as FDI and foreign workers, cultural hybridisation and to some extent cultural domination are contributing to neocolonialism in Malaysia. This has obvious consequences for the government-s effort to create a Malaysian national identity. An important finding of this work is that there are contradictions within ICT policy between the effort to develop the economy and society.
Abstract: Ethanol has become more attractive in fuel industry
either as fuel itself or an additive that helps enhancing the octane
number and combustibility of gasoline. This research studied a
pressure swing adsorption using cassava-based adsorbent prepared
from mixture of cassava starch and cassava pulp for dehydration of
ethanol vapor. The apparatus used in the experiments consisted of
double adsorption columns, an evaporator, and a vacuum pump. The
feed solution contained 90-92 %wt of ethanol. Three process
variables: adsorption temperatures (110, 120 and 130°C), adsorption
pressures (1 and 2 bar gauge) and feed vapor flow rate (25, 50 and 75
% valve opening of the evaporator) were investigated. According to
the experimental results, the optimal operating condition for this
system was found to be at 2 bar gauge for adsorption pressure, 120°C
for adsorption temperature and 25% valve opening of the evaporator.
Production of 1.48 grams of ethanol with concentration higher than
99.5 wt% per gram of adsorbent was obtained. PSA with cassavabased
adsorbent reported in this study could be an alternative method
for production of nearly anhydrous ethanol. Dehydration of ethanol
vapor achieved in this study is due to an interaction between free
hydroxyl group on the glucose units of the starch and the water
molecules.
Abstract: Ontology-based modelling of multi-formatted
software application content is a challenging area in content
management. When the number of software content unit is huge and
in continuous process of change, content change management is
important. The management of content in this context requires
targeted access and manipulation methods. We present a novel
approach to deal with model-driven content-centric information
systems and access to their content. At the core of our approach is an
ontology-based semantic annotation technique for diversely
formatted content that can improve the accuracy of access and
systems evolution. Domain ontologies represent domain-specific
concepts and conform to metamodels. Different ontologies - from
application domain ontologies to software ontologies - capture and
model the different properties and perspectives on a software content
unit. Interdependencies between domain ontologies, the artifacts and
the content are captured through a trace model. The annotation traces
are formalised and a graph-based system is selected for the
representation of the annotation traces.
Abstract: In this paper optimal capacitor placement problem has
been formulated in a restructured distribution network. In this
scenario the distribution network operator can consider reactive
energy also as a service that can be sold to transmission system. Thus
search for optimal location, size and number of capacitor banks with
the objective of loss reduction, maximum income from selling
reactive energy to transmission system and return on investment for
capacitors, has been performed. Results is influenced with economic
value of reactive energy, therefore problem has been solved for
various amounts of it. The implemented optimization technique is
genetic algorithm. For any value of reactive power economic value,
when reverse of investment index increase and change from zero or
negative values to positive values, the threshold value of selling
reactive power has been obtained. This increasing price of economic
parameter is reasonable until the network losses is less than loss
before compensation.
Abstract: In this work we introduce an efficient method to limit
the impact of the hiding process on the quality of the cover speech.
Vector quantization of the speech spectral information reduces drastically
the number of the secret speech parameters to be embedded
in the cover signal. Compared to scalar hiding, vector quantization
hiding technique provides a stego signal that is indistinguishable from
the cover speech. The objective and subjective performance measures
reveal that the current hiding technique attracts no suspicion about the
presence of the secret message in the stego speech, while being able
to recover an intelligible copy of the secret message at the receiver
side.