Abstract: This research presents a handwritten signature recognition based on angle feature vector using Artificial Neural Network (ANN). Each signature image will be represented by an Angle vector. The feature vector will constitute the input to the ANN. The collection of signature images will be divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested for recognition of the signature. When the signature is classified correctly, it is considered correct recognition otherwise it is a failure.
Abstract: Modern management in most fields is performance based; both planning and implementation of maintenance and operational activities are driven by appropriately defined performance indicators. Continuous real-time data collection for management is becoming feasible due to technological advancements. Outdated and insufficient input data may result in incorrect decisions. When using deterministic models the uncertainty of the object state is not visible thus applying the deterministic models are more likely to give false diagnosis. Constructing structured probabilistic models of the performance indicators taking into consideration the surrounding indicator environment enables to estimate the trustworthiness of the indicator values. It also assists to fill gaps in data to improve the quality of the performance analysis and management decisions. In this paper authors discuss the application of probabilistic graphical models in the road performance measurement and propose a high-level conceptual model that enables analyzing and predicting more precisely future pavement deterioration based on road utilization.
Abstract: In power system protection, the need to know the load
current together with the fault level detected by a relay is important.
This is due to the fact that the relay is required to isolate the
equipment being protected if a fault is present and keep the breaker
associated with it closed if the current level is lower than the
maximum load level. This is not an issue for a radial system. This is
not the same however in a looped power system. In a looped power
system, the isolation of an equipment system will contribute to a
topology change. The change in the power system topology will then
influence or change the maximum load current and the fault level
detected by each relay. In this paper, a method of data collection for
changing topology using matlab and sim-power will be presented.
The method will take into consideration the change in topology and
collect data for each possible topology.
Abstract: The benefits of eco-roofs is quite well known, however there remains very little research conducted for the implementation of eco-roofs in subtropical climates such as Australia. There are many challenges facing Australia as it moves into the future, climate change is proving to be one of the leading challenges. In order to move forward with the mitigation of climate change, the impacts of rapid urbanization need to be offset. Eco-roofs are one way to achieve this; this study presents the energy savings and environmental benefits of the implementation of eco-roofs in subtropical climates. An experimental set-up was installed at Rockhampton campus of Central Queensland University, where two shipping containers were converted into small offices, one with an eco-roof and one without. These were used for temperature, humidity and energy consumption data collection. In addition, a computational model was developed using Design Builder software (state-of-the-art building energy simulation software) for simulating energy consumption of shipping containers and environmental parameters, this was done to allow comparison between simulated and real world data. This study found that eco-roofs are very effective in subtropical climates and provide energy saving of about 13% which agrees well with simulated results.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
we present three feature selection methods: Information Gain,
Support Vector Machine feature selection called (SVM_FS) and
Genetic Algorithm with SVM (called GA_SVM). We show that the
best results were obtained with GA_SVM method for a relatively
small dimension of the feature vector.
Abstract: The goal of a network-based intrusion detection
system is to classify activities of network traffics into two major
categories: normal and attack (intrusive) activities. Nowadays, data
mining and machine learning plays an important role in many
sciences; including intrusion detection system (IDS) using both
supervised and unsupervised techniques. However, one of the
essential steps of data mining is feature selection that helps in
improving the efficiency, performance and prediction rate of
proposed approach. This paper applies unsupervised K-means
clustering algorithm with information gain (IG) for feature selection
and reduction to build a network intrusion detection system. For our
experimental analysis, we have used the new NSL-KDD dataset,
which is a modified dataset for KDDCup 1999 intrusion detection
benchmark dataset. With a split of 60.0% for the training set and the
remainder for the testing set, a 2 class classifications have been
implemented (Normal, Attack). Weka framework which is a java
based open source software consists of a collection of machine
learning algorithms for data mining tasks has been used in the testing
process. The experimental results show that the proposed approach is
very accurate with low false positive rate and high true positive rate
and it takes less learning time in comparison with using the full
features of the dataset with the same algorithm.
Abstract: Advances in processors architecture, such as multicore,
increase the size of complexity of parallel computer systems.
With multi-core architecture there are different parallel languages
that can be used to run parallel programs. One of these languages is
OpenMP which embedded in C/Cµ or FORTRAN. Because of this
new architecture and the complexity, it is very important to evaluate
the performance of OpenMP constructs, kernels, and application
program on multi-core systems. Performance is the activity of
collecting the information about the execution characteristics of a
program. Performance tools consists of at least three interfacing
software layers, including instrumentation, measurement, and
analysis. The instrumentation layer defines the measured
performance events. The measurement layer determines what
performance event is actually captured and how it is measured by the
tool. The analysis layer processes the performance data and
summarizes it into a form that can be displayed in performance tools.
In this paper, a number of OpenMP performance tools are surveyed,
explaining how each is used to collect, analyse, and display data
collection.
Abstract: This work proposes a set of actions to assist redesign
procedure in existing products of Electric and Electronic Equipment
(EEE). The aim is to improve their environmental behavior after their
withdrawal in the End-of-Life (EOL) phase. In the beginning data
collection takes place. Then follows selection and implementation of
the optimal EOL Treatment Strategy (EOL_TS) and its results-
evaluation concerning the environment. In parallel, product design
characteristics that can be altered are selected based on their
significance for the environment in the EOL stage. All results from
the previous stages are combined and possible redesign actions are
formulated for further examination and afterwards configuration in
the design stage. The applied method to perform these tasks is Lean
Thinking (LT). At the end, results concerning the application of the
proposed method on a distribution transformer are presented.
Abstract: This paper analysis performance of disbursement
procedure of public works project in Thailand. The results of
research were summarised based on contracts, submitted invoice,
inspection dated, copies of disbursement dated between client and
their main contractor and interviewed with persons involved in
central and local government projects during 1994-2008 in Thailand.
The data collection was to investigate the disbursement procedure
related to performance in disbursement during construction period
(Planned duration of contract against Actual execution date in each
month). A graphical presentation of a duration analysis of the
projects illustrated significant disbursement formation in each
project. It was established that the shortage of staff, the financial
stability of clients, bureaucratic, method of disbursement and
economics situation has play major role on performance of
disbursement to their main contractors.
Abstract: Abovepresented work deals with the new scope of application of information and communication technologies for the improvement of the election process in the biased environment. We are introducing a new concept of construction of the information-communication system for the election participant. It consists of four main components: Software, Physical Infrastructure, Structured Information and the Trained Stuff. The Structured Information is the bases of the whole system and is the collection of all possible events (irregularities among them) at the polling stations, which are structured in special templates, forms and integrated in mobile devices.The software represents a package of analytic modules, which operates with the dynamic database. The application of modern communication technologies facilities the immediate exchange of information and of relevant documents between the polling stations and the Server of the participant. No less important is the training of the staff for the proper functioning of the system. The e-training system with various modules should be applied in this respect. The presented methodology is primarily focused on the election processes in the countries of emerging democracies.It can be regarded as the tool for the monitoring of elections process by the political organization(s) and as one of the instruments to foster the spread of democracy in these countries.
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: In analyzing large scale nonlinear dynamical systems,
it is often desirable to treat the overall system as a collection of
interconnected subsystems. Solutions properties of the large scale
system are then deduced from the solution properties of the
individual subsystems and the nature of the interconnections. In this
paper a new approach is proposed for the stability analysis of large
scale systems, which is based upon the concept of vector Lyapunov
functions and the decomposition methods. The present results make
use of graph theoretic decomposition techniques in which the overall
system is partitioned into a hierarchy of strongly connected
components. We show then, that under very reasonable assumptions,
the overall system is stable once the strongly connected subsystems
are stables. Finally an example is given to illustrate the constructive
methodology proposed.
Abstract: In this study, any possible differences between mathematics beliefs and anxiety of prospective elementary mathematics teachers have been investigated according to their gender. In this purpose, 1st, 2nd, 3rd and 4th grade students from a Government University in Turkey were selected as a sample. Mathematics Teaching Anxiety Scale (MATAS) and Beliefs About Mathematics Survey (BAMS) has been used as data collection tools. As a result of the study, it has been observed that prospective male teachers have more instrumentalist approach in learning mathematics than females according to their mathematical beliefs. On the other hand, females have more mathematics teaching anxiety than males especially, for subject knowledge in mathematics and selfconfidence.
Abstract: Mobile ad hoc network is a collection of mobile
nodes communicating through wireless channels without any existing
network infrastructure or centralized administration. Because of the
limited transmission range of wireless network interfaces, multiple
"hops" may be needed to exchange data across the network. In order
to facilitate communication within the network, a routing protocol is
used to discover routes between nodes. The primary goal of such an
ad hoc network routing protocol is correct and efficient route
establishment between a pair of nodes so that messages may be
delivered in a timely manner. Route construction should be done
with a minimum of overhead and bandwidth consumption. This paper
examines two routing protocols for mobile ad hoc networks– the
Destination Sequenced Distance Vector (DSDV), the table- driven
protocol and the Ad hoc On- Demand Distance Vector routing
(AODV), an On –Demand protocol and evaluates both protocols
based on packet delivery fraction, normalized routing load, average
delay and throughput while varying number of nodes, speed and
pause time.
Abstract: The separation efficiency of a hydrocyclone has
extensively been considered on the rigid particle assumption. A
collection of experimental studies have demonstrated their
discrepancies from the modeling and simulation results. These
discrepancies caused by the actual particle elasticity have generally
led to a larger amount of energy consumption in the separation
process. In this paper, the influence of particle elasticity on the
separation efficiency of a hydrocyclone system was investigated
through the Finite Element (FE) simulations using crude oil droplets
as the elastic particles. A Reitema-s design hydrocyclone with a
diameter of 8 mm was employed to investigate the separation
mechanism of the crude oil droplets from water. The cut-size
diameter eter of the crude oil was 10 - Ðçm in order to fit with the
operating range of the adopted hydrocylone model. Typical
parameters influencing the performance of hydrocyclone were varied
with the feed pressure in the range of 0.3 - 0.6 MPa and feed
concentration between 0.05 – 0.1 w%. In the simulation, the Finite
Element scheme was applied to investigate the particle-flow
interaction occurred in the crude oil system during the process. The
interaction of a single oil droplet at the size of 10 - Ðçm to the flow
field was observed. The feed concentration fell in the dilute flow
regime so the particle-particle interaction was ignored in the study.
The results exhibited the higher power requirement for the separation
of the elastic particulate system when compared with the rigid
particulate system.
Abstract: We have proposed an information filtering system
using index word selection from a document set based on the
topics included in a set of documents. This method narrows
down the particularly characteristic words in a document set
and the topics are obtained by Sparse Non-negative Matrix
Factorization. In information filtering, a document is often
represented with the vector in which the elements correspond
to the weight of the index words, and the dimension of the
vector becomes larger as the number of documents is
increased. Therefore, it is possible that useless words as index
words for the information filtering are included. In order to
address the problem, the dimension needs to be reduced. Our
proposal reduces the dimension by selecting index words
based on the topics included in a document set. We have
applied the Sparse Non-negative Matrix Factorization to the
document set to obtain these topics. The filtering is carried out
based on a centroid of the learning document set. The centroid
is regarded as the user-s interest. In addition, the centroid is
represented with a document vector whose elements consist of
the weight of the selected index words. Using the English test
collection MEDLINE, thus, we confirm the effectiveness of
our proposal. Hence, our proposed selection can confirm the
improvement of the recommendation accuracy from the other
previous methods when selecting the appropriate number of
index words. In addition, we discussed the selected index
words by our proposal and we found our proposal was able to
select the index words covered some minor topics included in
the document set.
Abstract: Recently, a vehicular ad-hoc networks(VANETs) for
Intelligent Transport System(ITS) have become able safety and convenience services surpassing the simple services such as
an electronic toll collection system. To provide the proper services,
VANET needs infrastructure over the country infrastructure. Thus, we have to spend a huge sum of
human resources. In this reason, several studies have been made on the
usage of cellular networks instead of new protocols
this study is to assess a performance evaluation of the
cellular network for VANET. In this paper, the result of a
for the suitability of cellular networks for VANET
experiment, The LTE(Long Term Evolution) of cellular networks found to be most suitable among the others cellular networks
Abstract: In this paper we present a novel error model for
packet loss and subsequent error description. The proposed model
simulates the error performance of wireless communication link. The
model is designed as two independent Markov chains, where the first
one is used for packet generation and the second one generates
correctly and incorrectly transmitted bits for received packets from
the first chain. The statistical analyses of real communication on the
wireless link are used for determination of model-s parameters. Using
the obtained parameters and the implementation of the generator, we
collected generated traffic. The obtained results generated by
proposed model are compared with the real data collection.
Abstract: Electro-hydraulic power steering (EHPS) system for
the fuel rate reduction and steering feel improvement is comprised of
ECU including the logic which controls the steering system and BL
DC motor and produces the best suited cornering force, BLDC motor,
high pressure pump integrated module and basic oil-hydraulic circuit
of the commercial HPS system.
Electro-hydraulic system can be studied in two ways such as
experimental and computer simulation. To get accurate results in
experimental study of EHPS system, the real boundary management is
necessary which is difficult task. And the accuracy of the experimental
results depends on the preparation of the experimental setup and
accuracy of the data collection. The computer simulation gives
accurate and reliable results if the simulation is carried out considering
proper boundary conditions. So, in this paper, each component of
EHPS was modeled, and the model-based analysis and control logic
was designed by using AMESim
Abstract: XML is a markup language which is becoming the
standard format for information representation and data exchange. A
major purpose of XML is the explicit representation of the logical
structure of a document. Much research has been performed to
exploit logical structure of documents in information retrieval in
order to precisely extract user information need from large
collections of XML documents. In this paper, we describe an XML
information retrieval weighting scheme that tries to find the most
relevant elements in XML documents in response to a user query.
We present this weighting model for information retrieval systems
that utilize plausible inferences to infer the relevance of elements in
XML documents. We also add to this model the Dempster-Shafer
theory of evidence to express the uncertainty in plausible inferences
and Dempster-Shafer rule of combination to combine evidences
derived from different inferences.