Abstract: In recent times there has been a growing interest in the
development of quasi-two-dimensional niobium pentoxide (Nb2O5)
as a semiconductor for the potential electronic applications such as
capacitors, filtration, dye-sensitised solar cells and gas sensing
platforms. Therefore once the purpose is established, Nb2O5 can be
prepared in a number of nano- and sub-micron-structural
morphologies that include rods, wires, belts and tubes. In this study
films of Nb2O5 were prepared on gold plated silicon substrate using
spin-coating technique and subsequently by mechanical exfoliation.
The reason this method was employed was to achieve layers of less
than 15nm in thickness. The sintering temperature of the specimen
was 800oC. The morphology and structural characteristics of the
films were analyzed by Atomic Force Microscopy (AFM), Raman
Spectroscopy, X-ray Photoelectron Spectroscopy (XPS).
Abstract: In this paper, we present a new learning algorithm for
anomaly based network intrusion detection using improved self
adaptive naïve Bayesian tree (NBTree), which induces a hybrid of
decision tree and naïve Bayesian classifier. The proposed approach
scales up the balance detections for different attack types and keeps
the false positives at acceptable level in intrusion detection. In
complex and dynamic large intrusion detection dataset, the detection
accuracy of naïve Bayesian classifier does not scale up as well as
decision tree. It has been successfully tested in other problem
domains that naïve Bayesian tree improves the classification rates in
large dataset. In naïve Bayesian tree nodes contain and split as
regular decision-trees, but the leaves contain naïve Bayesian
classifiers. The experimental results on KDD99 benchmark network
intrusion detection dataset demonstrate that this new approach scales
up the detection rates for different attack types and reduces false
positives in network intrusion detection.
Abstract: The main idea behind in network aggregation is that,
rather than sending individual data items from sensors to sinks,
multiple data items are aggregated as they are forwarded by the
sensor network. Existing sensor network data aggregation techniques
assume that the nodes are preprogrammed and send data to a central
sink for offline querying and analysis. This approach faces two major
drawbacks. First, the system behavior is preprogrammed and cannot
be modified on the fly. Second, the increased energy wastage due to
the communication overhead will result in decreasing the overall
system lifetime. Thus, energy conservation is of prime consideration
in sensor network protocols in order to maximize the network-s
operational lifetime. In this paper, we give an energy efficient
approach to query processing by implementing new optimization
techniques applied to in-network aggregation. We first discuss earlier
approaches in sensors data management and highlight their
disadvantages. We then present our approach “Energy Efficient
Indexed Aggregation" (EEIA) and evaluate it through several
simulations to prove its efficiency, competence and effectiveness.
Abstract: In this paper an open agent-based modular framework
for personalized and adaptive curriculum generation in e-learning
environment is proposed. Agent-based approaches offer several
potential advantages over alternative approaches. Agent-based
systems exhibit high levels of flexibility and robustness in dynamic
or unpredictable environments by virtue of their intrinsic autonomy.
The presented framework enables integration of different types of
expert agents, various kinds of learning objects and user modeling
techniques. It creates possibilities for adaptive e-learning process.
The KM e-learning system is in a process of implementation in
Varna Free University and will be used for supporting the
educational process at the University.
Abstract: Numerous divergence measures (spectral distance, cepstral
distance, difference of the cepstral coefficients, Kullback-Leibler
divergence, distance given by the General Likelihood Ratio, distance
defined by the Recursive Bayesian Changepoint Detector and the
Mahalanobis measure) are compared in this study. The measures are
used for detection of abrupt spectral changes in synthetic AR signals
via the sliding window algorithm. Two experiments are performed;
the first is focused on detection of single boundary while the second
concentrates on detection of a couple of boundaries. Accuracy of
detection is judged for each method; the measures are compared
according to results of both experiments.
Abstract: This paper propose the robust character segmentation method for license plate with topological transform such as twist,rotation. The first step of the proposed method is to find a candidate region for character and license plate. The character or license plate
must be appeared as closed loop in the edge image. In the case of
detecting candidate for character region, the evaluation of detected
region is using topological relationship between each character. When
this method decides license plate candidate region, character features
in the region with binarization are used. After binarization for the detected candidate region, each character region is decided again. In
this step, each character region is fitted more than previous step. In the
next step, the method checks other character regions with different
scale near the detected character regions, because most license plates
have license numbers with some meaningful characters around them.
The method uses perspective projection for geometrical normalization.
If there is topological distortion in the character region, the method
projects the region on a template which is defined as standard license
plate using perspective projection. In this step, the method is able to
separate each number region and small meaningful characters. The
evaluation results are tested with a number of test images.
Abstract: This paper presents modern vibration signalprocessing
techniques for vehicle gearbox fault diagnosis, via the
wavelet analysis and the Squared Envelope (SE) technique. The
wavelet analysis is regarded as a powerful tool for the detection of
sudden changes in non-stationary signals. The Squared Envelope
(SE) technique has been extensively used for rolling bearing
diagnostics. In the present work a scheme of using the Squared
Envelope technique for early detection of gear tooth pit. The pitting
defect is manufactured on the tooth side of a fifth speed gear on the
intermediate shaft of a vehicle gearbox. The objective is to
supplement the current techniques of gearbox fault diagnosis based
on using the raw vibration and ordered signals. The test stand is
equipped with three dynamometers; the input dynamometer serves as
the internal combustion engine, the output dynamometers introduce
the load on the flanges of output joint shafts. The gearbox used for
experimental measurements is the type most commonly used in
modern small to mid-sized passenger cars with transversely mounted
powertrain and front wheel drive; a five-speed gearbox with final
drive gear and front wheel differential. The results show that the
approaches methods are effective for detecting and diagnosing
localized gear faults in early stage under different operation
conditions, and are more sensitive and robust than current gear
diagnostic techniques.
Abstract: The vast amount of information hidden in huge
databases has created tremendous interests in the field of data
mining. This paper examines the possibility of using data clustering
techniques in oral medicine to identify functional relationships
between different attributes and classification of similar patient
examinations. Commonly used data clustering algorithms have been
reviewed and as a result several interesting results have been
gathered.
Abstract: This paper attempts to model and design a simple
fuzzy logic controller with Variable Reference. The Variable
Reference (VR) is featured as an adaptability element which is
obtained from two known variables – desired system-input and actual
system-output. A simple fuzzy rule-based technique is simulated to
show how the actual system-input is gradually tuned in to a value
that closely matches the desired input. The designed controller is
implemented and verified on a simple heater which is controlled by
PIC Microcontroller harnessed by a code developed in embedded C.
The output response of the PIC-controlled heater is analyzed and
compared to the performances by conventional fuzzy logic
controllers. The novelty of this work lies in the fact that it gives
better performance by using less number of rules compared to
conventional fuzzy logic controllers.
Abstract: This article outlines a hybrid method, incorporating
multiple techniques into an evaluation process, in order to select
competitive suppliers in a supply chain. It enables a purchaser to do
single sourcing and multiple sourcing by calculating a combined
supplier score, which accounts for both qualitative and quantitative
factors that have impact on supply chain performance.
Abstract: An automatic method for the extraction of feature points for face based applications is proposed. The system is based upon volumetric feature descriptors, which in this paper has been extended to incorporate scale space. The method is robust to noise and has the ability to extract local and holistic features simultaneously from faces stored in a database. Extracted features are stable over a range of faces, with results indicating that in terms of intra-ID variability, the technique has the ability to outperform manual landmarking.
Abstract: The Malaysian government is promoting
entrepreneurship development skills amongst farmers through informal
courses. These courses will concentrate on teaching managerial skills as
inevitable means for small farms to succeed by making farmers more
creative and innovative. Therefore it is important to assess the effect of
informal agri-entrepreneurial training in developing entrepreneurship
among the farmers in Malaysia. Seven hundred and ninety six farmers
(796) farmers were interviewed via structured questionnaire to define
their opinion on whether the current informal educational and training
establishments are sufficient to teach and develop entrepreneurial
skills. Factor analysis and logic regression analysis were used to
determine the motivating factors and predict their impact on the
development of entrepreneurial skills. The result from the factor analysis
led us to investigate the association between these factors and farmers-
opinions about the development of entrepreneurial skills and traits
through participating in informal entrepreneurship training or education.
The outcome has shown us that the importance of informal training to
promote entrepreneurship among farmers is crucial. The training should
be intensified to encourage farmers to not only focus on the modern
technologies but also on the fundamental changes in their attitude towards
agriculture as a business.
DOA:
KMO: Kaiser- Meyer- Olkin Test
MOA: Ministry of Agriculture
NMP: Ninth Malaysia Plan
NAP: Third National Agricultural Policy (2000-2010)
Abstract: Adjacent Hall microsensors, comprising a silicon
substrate and four contacts, providing simultaneously two supply inputs and two differential outputs, are characterized. The voltage
related sensitivity is in the order of 0.11T-1, and a cancellation method for offset compensation is used, achieving residual offset in
the micro scale which is also compared to a single Hall plate.
Abstract: We created the tool, which combines the powerful
GENESIS (GEneral NEural SImulation System) simulation language
with the up-to-date visualisation and internet techniques. Our
solution resides in the connection between the simulation output from
GENESIS, which is converted to the data-structure suitable for
WWW browsers and VRML (Virtual Reality Modelling Language)
viewers. The selected GENESIS simulations are once exported into
the VRML code, and stored in our neurovisualisation portal
(webserver). There, the loaded models, demonstrating mainly the
spread of electrical signal (action potentials, postsynaptic potentials)
along the neuronal membrane (axon, dendritic tree, neuron) could be
displayed in the client-s VRML viewer, without interacting with
original GENESIS environment. This enables the visualisation of
basic neurophysiological phenomena designed for GENESIS
simulator on the independent OS (operation system).
Abstract: This study assessed the productivity and performance of the barangays in the Heritage City of Vigan in terms of the barangays- resource requirements, management of resources, produced goods and services, and outcomes of service delivery. The descriptive research design was used in the study employing the input-process-output-outcomes model. Findings of this study showed that the barangays were strong in terms of resource requirements which enabled them to produce goods and services. The barangays were also strong in terms of management of resources in development planning. They also showed great potential along fiscal administration, and had a moderately high capability in organization and management. However, the barangays appeared to be most wanting in the area of barangay legislation, but they were strong in community mobilization and they had strong linkages with POs, NGOs and educational institutions. In the delivery of social services, the barangays favored the maintenance of day care centers. However, the barangays seem to be weak in the delivery of economic services. They fared well along providing protective services such as in establishing a Barangay Disaster Coordinating Council and organizing a group of Barangay Tanod. In terms of environmental services, the barangays performed garbage collection and disposal; however, garbage still found their way in the streets in some barangays. The services delivered had effected an improved status of the barangays. However, the barangays are still facing some problems.
Abstract: This paper discusses the Urdu script characteristics,
Urdu Nastaleeq and a simple but a novel and robust technique to
recognize the printed Urdu script without a lexicon. Urdu being a
family of Arabic script is cursive and complex script in its nature, the
main complexity of Urdu compound/connected text is not its
connections but the forms/shapes the characters change when it is
placed at initial, middle or at the end of a word. The characters
recognition technique presented here is using the inherited
complexity of Urdu script to solve the problem. A word is scanned
and analyzed for the level of its complexity, the point where the level
of complexity changes is marked for a character, segmented and
feeded to Neural Networks. A prototype of the system has been
tested on Urdu text and currently achieves 93.4% accuracy on the
average.
Abstract: A study was conducted to formally characterize
notebook computer performance under various environmental and
usage conditions. Software was developed to collect data from the
operating system of the computer. An experiment was conducted to
evaluate the performance parameters- variations, trends, and
correlations, as well as the extreme value they can attain in various
usage and environmental conditions. An automated software script
was written to simulate user activity. The variability of each
performance parameter was addressed by establishing the empirical
relationship between performance parameters. These equations were
presented as baseline estimates for performance parameters, which
can be used to detect system deviations from normal operation and
for prognostic assessment. The effect of environmental factors,
including different power sources, ambient temperatures, humidity,
and usage, on performance parameters of notebooks was studied.
Abstract: A word recognition architecture based on a network
of neural associative memories and hidden Markov models has been
developed. The input stream, composed of subword-units like wordinternal
triphones consisting of diphones and triphones, is provided
to the network of neural associative memories by hidden Markov
models. The word recognition network derives words from this input
stream. The architecture has the ability to handle ambiguities on
subword-unit level and is also able to add new words to the
vocabulary during performance. The architecture is implemented to
perform the word recognition task in a language processing system
for understanding simple command sentences like “bot show apple".
Abstract: We developed a vision interface immersive projection system, CAVE in virtual rea using hand gesture recognition with computer vis background image was subtracted from current webcam and we convert the color space of the imag Then we mask skin regions using skin color range t a noise reduction operation. We made blobs fro gestures were recognized using these blobs. Using recognition, we could implement an effective bothering devices for CAVE. e framework for an reality research field vision techniques. ent image frame age into HSV space. e threshold and apply from the image and ing our hand gesture e interface without
Abstract: A biocompatible ferrofluid have been prepared by coprecipitation
of FeCl2.4H2O and FeCl3.6H2O under ultrasonic
irradiation and with NaOH as alkaline agent. Cystein was also used
as capping agent in the solution. Magnetic properties of the produced
ferrofluid were then determined by VSM test and magnetite
nanoparticles were characterized by XRD and TEM techniques. The
effect of surfactant to Fe ion weight ratio was also studied during this
project by using two different amount of Dextran. Results showed the
presence of a biocompatible superparamagnetic ferrofluid including
magnetite nanoparticles with particle size ranging under 20 nm. The
increase in the surfactant content results in the narrowing of the size
distribution and reduction of the particle size and more solution
stability.