Abstract: Lignocellulosic materials are considered the most
abundant renewable resource available for the Bioethanol
Production. Water Hyacinth is one of potential raw material of the
world-s worst aquatic plant as a feedstock to produce Bioethanol.
The purposed this research is obtain reduced of matter for
biodegradation lignin in Biological pretreatment with White Rot
Fungi eg. Phanerochaete Chrysosporium using Solid state
Fermentation methods. Phanerochaete Chrysosporium is known to
have the best ability to degraded lignin, but simultaneously it can also
degraded cellulose and hemicelulose. During 8 weeks incubation,
water hyacinth occurred loss of weight reached 34,67%, while loss
of lignin reached 67,21%, loss of cellulose reached 11,01% and loss
of hemicellulose reached 36,56%. The kinetic of losses lignin using
regression linear plot, the results is obtained constant rate (k) of
reduction lignin is -0.1053 and the equation of reduction of lignin
is y = wo - 0, 1.53 x
Abstract: The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.
Abstract: Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Abstract: An important step in studying the statistics of
fingerprint minutia features is to reliably extract minutia features from
the fingerprint images. A new reliable method of computation for
minutiae feature extraction from fingerprint images is presented. A
fingerprint image is treated as a textured image. An orientation flow
field of the ridges is computed for the fingerprint image. To
accurately locate ridges, a new ridge orientation based computation
method is proposed. After ridge segmentation a new method of
computation is proposed for smoothing the ridges. The ridge skeleton
image is obtained and then smoothed using morphological operators
to detect the features. A post processing stage eliminates a large
number of false features from the detected set of minutiae features.
The detected features are observed to be reliable and accurate.
Abstract: Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
Abstract: We present a new method for the fully automatic 3D
reconstruction of the coronary artery centerlines, using two X-ray
angiogram projection images from a single rotating monoplane
acquisition system. During the first stage, the input images are
smoothed using curve evolution techniques. Next, a simple yet
efficient multiscale method, based on the information of the Hessian
matrix, for the enhancement of the vascular structure is introduced.
Hysteresis thresholding using different image quantiles, is used to
threshold the arteries. This stage is followed by a thinning procedure
to extract the centerlines. The resulting skeleton image is then pruned
using morphological and pattern recognition techniques to remove
non-vessel like structures. Finally, edge-based stereo correspondence
is solved using a parallel evolutionary optimization method based on
f symbiosis. The detected 2D centerlines combined with disparity
map information allow the reconstruction of the 3D vessel
centerlines. The proposed method has been evaluated on patient data
sets for evaluation purposes.
Abstract: IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.
Abstract: Several models have been introduced so far for single
electron box, SEB, which all of them were restricted to DC response
and or low temperature limit. In this paper we introduce a new time
dependent, high temperature analytical model for SEB for the first
time. DC behavior of the introduced model will be verified against
SIMON software and its time behavior will be verified against a
newly published paper regarding step response of SEB.
Abstract: In this paper the design of maximally flat linear phase
finite impulse response (FIR) filters is considered. The problem is
handled with totally two different approaches. The first one is
completely deterministic numerical approach where the problem is
formulated as a Linear Complementarity Problem (LCP). The other
one is based on a combination of Markov Random Fields (MRF's)
approach with messy genetic algorithm (MGA). Markov Random
Fields (MRFs) are a class of probabilistic models that have been
applied for many years to the analysis of visual patterns or textures.
Our objective is to establish MRFs as an interesting approach to
modeling messy genetic algorithms. We establish a theoretical result
that every genetic algorithm problem can be characterized in terms of
a MRF model. This allows us to construct an explicit probabilistic
model of the MGA fitness function and introduce the Ising MGA.
Experimentations done with Ising MGA are less costly than those
done with standard MGA since much less computations are involved.
The least computations of all is for the LCP. Results of the LCP,
random search, random seeded search, MGA, and Ising MGA are
discussed.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: Bluetooth is a personal wireless communication
technology and is being applied in many scenarios. It is an emerging
standard for short range, low cost, low power wireless access
technology. Current existing MAC (Medium Access Control)
scheduling schemes only provide best-effort service for all masterslave
connections. It is very challenging to provide QoS (Quality of
Service) support for different connections due to the feature of
Master Driven TDD (Time Division Duplex). However, there is no
solution available to support both delay and bandwidth guarantees
required by real time applications. This paper addresses the issue of
how to enhance QoS support in a Bluetooth piconet. The Bluetooth
specification proposes a Round Robin scheduler as possible solution
for scheduling the transmissions in a Bluetooth Piconet. We propose
an algorithm which will reduce the bandwidth waste and enhance the
efficiency of network. We define token counters to estimate traffic of
real-time slaves. To increase bandwidth utilization, a back-off
mechanism is then presented for best-effort slaves to decrease the
frequency of polling idle slaves. Simulation results demonstrate that
our scheme achieves better performance over the Round Robin
scheduling.
Abstract: A novel sponge submerged membrane bioreactor
(SSMBR) was developed to effectively remove organics and
nutrients from wastewater. Sponge is introduced within the SSMBR
as a medium for the attached growth of biomass. This paper evaluates
the effects of new and acclimatized sponges for dissolved organic
carbon (DOC) removal from wastewater at different mixed liquor
suspended solids- (MLSS) concentration of the sludge. It was
observed in a series of experimental studies that the acclimatized
sponge performed better than the new sponge whilst the optimum
DOC removal could be achieved at 10g/L of MLSS with the
acclimatized sponge. Moreover, the paper analyses the relationships
between the MLSSsponge/MLSSsludge and the DOC removal efficiency
of SSMBR. The results showed a non-linear relationship between the
biomass parameters of the sponge and the sludge, and the DOC
removal efficiency of SSMBR. A second-order polynomial function
could reasonably represent these relationships.
Abstract: In policy discourse of 1990s, more inclusive spaces
have been constructed for realizing full and meaningful participation
of common people in education. These participatory spaces provide
an alternative possibility for universalizing elementary education
against the backdrop of a history of entrenched forms of social and
economical exclusion; inequitable education provisions; and
shrinking role of the state in today-s neo-liberal times. Drawing on
case-studies of bottom-up approaches to school governance, the study
examines an array of innovative ways through which poor people
gained a sense of identity and agency by evolving indigenous
solutions to issues regarding schooling of their children. In the
process, state-s institutions and practices became more accountable
and responsive to educational concerns of the marginalized people.
The deliberative participation emerged as an active way of
experiencing deeper forms of empowerment and democracy than its
passive realization as mere bearers of citizen rights.
Abstract: In this paper, cloud resource broker using goalbased
request in medical application is proposed. To handle recent
huge production of digital images and data in medical informatics
application, the cloud resource broker could be used by medical
practitioner for proper process in discovering and selecting correct
information and application. This paper summarizes several
reviewed articles to relate medical informatics application with
current broker technology and presents a research work in applying
goal-based request in cloud resource broker to optimize the use of
resources in cloud environment. The objective of proposing a new
kind of resource broker is to enhance the current resource
scheduling, discovery, and selection procedures. We believed that
it could help to maximize resources allocation in medical
informatics application.
Abstract: This article proposes an Ant Colony Optimization
(ACO) metaheuristic to minimize total makespan for scheduling a set
of jobs and assign workers for uniformly related parallel machines.
An algorithm based on ACO has been developed and coded on a
computer program Matlab®, to solve this problem. The paper
explains various steps to apply Ant Colony approach to the problem
of minimizing makespan for the worker assignment & jobs
scheduling problem in a parallel machine model and is aimed at
evaluating the strength of ACO as compared to other conventional
approaches. One data set containing 100 problems (12 Jobs, 03
machines and 10 workers) which is available on internet, has been
taken and solved through this ACO algorithm. The results of our
ACO based algorithm has shown drastically improved results,
especially, in terms of negligible computational effort of CPU, to
reach the optimal solution. In our case, the time taken to solve all 100
problems is even lesser than the average time taken to solve one
problem in the data set by other conventional approaches like GA
algorithm and SPT-A/LMC heuristics.
Abstract: Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
Abstract: Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
Abstract: Unified Theory of Acceptance and Use of Technology
(UTAUT) model has demonstrated the influencing factors for generic
information systems use such as tablet personal computer (TPC) and
mobile communication. However, in the context of digital library
system, there has been very little effort to determine factors affecting
the intention to use digital library based on the UTAUT model. This
paper investigates factors that are expected to influence the intention
of postgraduate students to use digital library based on modified
UTAUT model. The modified model comprises of constructs
represented by several latent variables, namely performance
expectancy (PE), effort expectancy (EE), information quality (IQ)
and service quality (SQ) and moderated by age, gender and
experience in using digital library. Results show that performance
expectancy, effort expectancy and information quality are positively
related to the intention to use digital library, while service quality is
negatively related to the intention to use digital library. Age and
gender have shown no evidence of any significant interactions, while
experience in using digital library significantly interacts with effort
expectancy and intention to use digital library. This has provided the
evidence of a moderating effect of experience in the intention to use
digital library. It is expected that this research will shed new lights
into research of acceptance and intention to use the library in a digital
environment.
Abstract: Highly ordered TiO2 nanotube (TNT) arrays were
fabricated onto a pre-treated titanium foil by anodic oxidation with a
voltage of 20V in phosphoric acid/sodium fluoride electrolyte. A pretreatment
of titanium foil involved washing with acetone,
isopropanol, ethanol and deionized water. Carbon doped TiO2
nanotubes (C-TNT) was fabricated 'in-situ' with the same method in
the presence of polyvinyl alcohol and urea as carbon sources. The
affects of polyvinyl alcohol concentration and oxidation time on the
composition, morphology and structure of the C-TN were studied by
FE-SEM, EDX and XRD techniques. FESEM images of the
nanotubes showed uniform arrays of C-TNTs. The density and
microstructures of the nanotubes were greatly affected by the content
of PVA. The introduction of the polyvinyl alcohol into the electrolyte
increases the amount of C content inside TiO2 nanotube arrays
uniformly. The influence of carbon content on the photo-current of
C-TNT was investigated and the I-V profiles of the nanotubes were
established. The preliminary results indicated that the 'in-situ'
doping technique produced a superior quality nanotubes compared to
post doping techniques.