Abstract: This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.
Abstract: Intelligent traffic surveillance technology is an issue in
the field of traffic data analysis. Therefore, we need the technology to
detect moving objects in real-time while there are variations in background and natural light. In this paper, we proposed a Weighted-Center Surround Difference
method for object detection in outdoor environments. The proposed system detects objects using the saliency map that is obtained by
analyzing the weight of each layers of Gaussian pyramid. In order to validate the effectiveness of our system, we implemented the proposed
method using a digital signal processor, TMS320DM6437.
Experimental results show that blurred noisy around objects was effectively eliminated and the object detection accuracy is improved.
Abstract: In this paper, a reliable cooperative multipath routing
algorithm is proposed for data forwarding in wireless sensor networks
(WSNs). In this algorithm, data packets are forwarded towards the
base station (BS) through a number of paths, using a set of relay
nodes. In addition, the Rayleigh fading model is used to calculate
the evaluation metric of links. Here, the quality of reliability is
guaranteed by selecting optimal relay set with which the probability
of correct packet reception at the BS will exceed a predefined
threshold. Therefore, the proposed scheme ensures reliable packet
transmission to the BS. Furthermore, in the proposed algorithm,
energy efficiency is achieved by energy balancing (i.e. minimizing
the energy consumption of the bottleneck node of the routing path)
at the same time. This work also demonstrates that the proposed
algorithm outperforms existing algorithms in extending longevity of
the network, with respect to the quality of reliability. Given this, the
obtained results make possible reliable path selection with minimum
energy consumption in real time.
Abstract: This paper presents the findings of an
experimental investigation to study the effect of alkali content
in geopolymer mortar specimens exposed to sulphuric acid.
Geopolymer mortar specimens were manufactured from Class F fly
ash by activation with a mixture of sodium hydroxide and sodium
silicate solution containing 5% to 8% Na2O. Durability of specimens
were assessed by immersing them in 10% sulphuric acid solution and
periodically monitoring surface deterioration and depth of
dealkalization, changes in weight and residual compressive strength
over a period of 24 weeks. Microstructural changes in the specimens
were studied with Scanning electron microscopy (SEM) and EDAX.
Alkali content in the activator solution significantly affects the
durability of fly ash based geopolymer mortars in sulphuric acid.
Specimens manufactured with higher alkali content performed better
than those manufactured with lower alkali content. After 24 weeks in
sulphuric acid, specimen with 8% alkali still recorded a residual
strength as high as 55%.
Abstract: This paper gives an overview of how an OWL
ontology has been created to represent template knowledge models
defined in CML that are provided by CommonKADS.
CommonKADS is a mature knowledge engineering methodology
which proposes the use of template knowledge model for knowledge
modelling. The aim of developing this ontology is to present the
template knowledge model in a knowledge representation language
that can be easily understood and shared in the knowledge
engineering community. Hence OWL is used as it has become a
standard for ontology and also it already has user friendly tools for
viewing and editing.
Abstract: This paper proposes a framework for product
development including hardware and software components. It
provides separation of hardware dependent software, modifications of
current product development process, and integration of software
modules with existing product configuration models and assembly
product structures. In order to decide the dependent software, the
framework considers product configuration modules and engineering
changes of associated software and hardware components. In order to
support efficient integration of the two different hardware and
software development, a modified product development process is
proposed. The process integrates the dependent software development
into product development through the interchanges of specific product
information. By using existing product data models in Product Data
Management (PDM), the framework represents software as modules
for product configurations and software parts for product structure.
The framework is applied to development of a robot system in order to
show its effectiveness.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique are dependent on the initialization of cluster centers. In this article we propose a new algorithm to initialize the clusters. The proposed algorithm is based on finding a set of medians extracted from a dimension with maximum variance. The algorithm has been applied to different data sets and good results are obtained.
Abstract: A challenging problem in radar signal processing is to
achieve reliable target detection in the presence of interferences. In
this paper, we propose a novel algorithm for automatic censoring of
radar interfering targets in log-normal clutter. The proposed
algorithm, termed the forward automatic censored cell averaging
detector (F-ACCAD), consists of two steps: removing the corrupted
reference cells (censoring) and the actual detection. Both steps are
performed dynamically by using a suitable set of ranked cells to
estimate the unknown background level and set the adaptive
thresholds accordingly. The F-ACCAD algorithm does not require
any prior information about the clutter parameters nor does it require
the number of interfering targets. The effectiveness of the F-ACCAD
algorithm is assessed by computing, using Monte Carlo simulations,
the probability of censoring and the probability of detection in
different background environments.
Abstract: Lighting upgrades involve relatively lower costs which
allow the benefits to be spread more widely than is possible with any
other energy efficiency measure. In order to popularize the adoption of
CFL in Taiwan, the authority proposes to implement a new energy efficient lamp comparative label system. The current study was
accordingly undertaken to investigate the factors affecting the performance and the deviation of actual and labeled performance of
commercially available integrated CFLs. In this paper, standard test
methods to determine the electrical and photometric performances of
CFL were developed based on CIE 84-1989 and CIE 60901-1987,
then 55 selected CFLs from market were tested. The results show that
with higher color temperature of CFLs lower efficacy are achieved. It
was noticed that the most packaging of CFL often lack the information of Color Rendering Index. Also, there was no correlation between
price and performance of the CFLs was indicated in this work. The results of this paper might help consumers to make more informed
CFL-purchasing decisions.
Abstract: The purpose of this study is to analyze the islands
tourist travel information sources, as well as for the satisfaction of the
tourist destination services. This study used questionnaires to the
island of Taiwan to the Penghu Islands to engage in tourism activities
tourist adopt the designated convenience sampling method, a total of
889 valid questionnaires were collected. After statistical analysis, this
study found that: 1. tourists to the Penghu Islands travel information
source for “friends and family came to Penghu". 2. Tourists feel the
service of the outlying islands of Penghu, the highest feelings of
“friendly local residents". 3. There are different demographic variables
affect the tourist travel information source and service satisfaction.
Based on the findings of this study not only for Penghu's tourism
industry with the unit in charge of the proposed operating and
suggestions for future research to other researchers.
Abstract: A hardware efficient, multi mode, re-configurable
architecture of interleaver/de-interleaver for multiple standards,
like DVB, WiMAX and WLAN is presented. The interleavers
consume a large part of silicon area when implemented by using
conventional methods as they use memories to store permutation
patterns. In addition, different types of interleavers in different
standards cannot share the hardware due to different construction
methodologies. The novelty of the work presented in this paper is
threefold: 1) Mapping of vital types of interleavers including
convolutional interleaver onto a single architecture with flexibility
to change interleaver size; 2) Hardware complexity for channel
interleaving in WiMAX is reduced by using 2-D realization of the
interleaver functions; and 3) Silicon cost overheads reduced by
avoiding the use of small memories. The proposed architecture
consumes 0.18mm2 silicon area for 0.12μm process and can
operate at a frequency of 140 MHz. The reduced complexity helps
in minimizing the memory utilization, and at the same time
provides strong support to on-the-fly computation of permutation
patterns.
Abstract: Querying a data source and routing data towards sink
becomes a serious challenge in static wireless sensor networks if sink
and/or data source are mobile. Many a times the event to be observed
either moves or spreads across wide area making maintenance of
continuous path between source and sink a challenge. Also, sink can
move while query is being issued or data is on its way towards sink.
In this paper, we extend our already proposed Grid Based Data
Dissemination (GBDD) scheme which is a virtual grid based
topology management scheme restricting impact of movement of
sink(s) and event(s) to some specific cells of a grid. This obviates the
need for frequent path modifications and hence maintains continuous
flow of data while minimizing the network energy consumptions.
Simulation experiments show significant improvements in network
energy savings and average packet delay for a packet to reach at sink.
Abstract: We board the problem of creating a seismic alert
system, based upon artificial neural networks, trained by using the
well-known back-propagation and genetic algorithms, in order to emit
the alarm for the population located into a specific city, about an
eminent earthquake greater than 4.5 Richter degrees, and avoiding
disasters and human loses. In lieu of using the propagation wave, we
employed the magnitude of the earthquake, to establish a correlation
between the recorded magnitudes from a controlled area and the city,
where we want to emit the alarm. To measure the accuracy of the
posed method, we use a database provided by CIRES, which contains
the records of 2500 quakes incoming from the State of Guerrero
and Mexico City. Particularly, we performed the proposed method to
generate an issue warning in Mexico City, employing the magnitudes
recorded in the State of Guerrero.
Abstract: Every commercial bank optimises its asset portfolio
depending on the profitability of assets and chosen or imposed
constraints. This paper proposes and applies a stylized model for
optimising banks' asset and liability structure, reflecting profitability
of different asset categories and their risks as well as costs associated
with different liability categories and reserve requirements. The level
of detail for asset and liability categories is chosen to create a
suitably parsimonious model and to include the most important
categories in the model. It is shown that the most appropriate
optimisation criterion for the model is the maximisation of the ratio
of net interest income to assets. The maximisation of this ratio is
subject to several constraints. Some are accounting identities or
dictated by legislative requirements; others vary depending on the
market objectives for a particular bank. The model predicts variable
amount of assets allocated to loan provision.
Abstract: Image synthesis is an important area in image processing.
To synthesize images various systems are proposed in
the literature. In this paper, we propose a bio-inspired system to
synthesize image and to study the generating power of the system, we
define the class of languages generated by our system. We call image
as array in this paper. We use a primitive called iso-array to synthesize
image/array. The operation is double splicing on iso-arrays. The
double splicing operation is used in DNA computing and we use
this to synthesize image. A comparison of the family of languages
generated by the proposed self restricted double splicing systems on
iso-arrays with the existing family of local iso-picture languages is
made. Certain closure properties such as union, concatenation and
rotation are studied for the family of languages generated by the
proposed model.
Abstract: In this paper, an improved technique for contingency
ranking using artificial neural network (ANN) is presented. The
proposed approach is based on multi-layer perceptrons trained by
backpropagation to contingency analysis. Severity indices in dynamic
stability assessment are presented. These indices are based on the
concept of coherency and three dot products of the system variables.
It is well known that some indices work better than others for a
particular power system. This paper along with test results using
several different systems, demonstrates that combination of indices
with ANN provides better ranking than a single index. The presented
results are obtained through the use of power system simulation
(PSS/E) and MATLAB 6.5 software.
Abstract: In Grid computing, a data transfer protocol called
GridFTP has been widely used for efficiently transferring a large volume
of data. Currently, two versions of GridFTP protocols, GridFTP
version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have
been proposed in the GGF. GridFTP v2 supports several advanced
features such as data streaming, dynamic resource allocation, and
checksum transfer, by defining a transfer mode called X-block mode.
However, in the literature, effectiveness of GridFTP v2 has not been
fully investigated. In this paper, we therefore quantitatively evaluate
performance of GridFTP v1 and GridFTP v2 using mathematical
analysis and simulation experiments. We reveal the performance
limitation of GridFTP v1, and quantitatively show effectiveness of
GridFTP v2. Through several numerical examples, we show that by
utilizing the data streaming feature, the average file transfer time of
GridFTP v2 is significantly smaller than that of GridFTP v1.
Abstract: In this paper, we present the design and experimental
evaluation of complementary energy path adiabatic logic (CEPAL)
based 1 bit full adder circuit. A simulative investigation on the
proposed full adder has been done using VIRTUOSO SPECTRE
simulator of cadence in 0.18μm UMC technology and its
performance has been compared with the conventional CMOS full
adder circuit. The CEPAL based full adder circuit exhibits the energy
saving of 70% to the conventional CMOS full adder circuit, at 100
MHz frequency and 1.8V operating voltage.
Abstract: In this paper a technique for increasing the
convergence rate of fractionally spaced channel equalizer is
proposed. Instead of symbol-spaced updating of the equalizer filter, a
mechanism has been devised to update the filter at a higher rate. This
ensures convergence of the equalizer filter at a higher rate and
therefore less time-consuming. The proposed technique has been
simulated and tested for two-ray modeled channels with various
delay spreads. These channels include minimum-phase and nonminimum-
phase channels. Simulation results suggest that that
proposed technique outperforms the conventional technique of
symbol-spaced updating of equalizer filter.
Abstract: The paper describes a new approach for fingerprint
classification, based on the distribution of local features (minute
details or minutiae) of the fingerprints. The main advantage is that
fingerprint classification provides an indexing scheme to facilitate
efficient matching in a large fingerprint database. A set of rules based
on heuristic approach has been proposed. The area around the core
point is treated as the area of interest for extracting the minutiae
features as there are substantial variations around the core point as
compared to the areas away from the core point. The core point in a
fingerprint has been located at a point where there is maximum
curvature. The experimental results report an overall average
accuracy of 86.57 % in fingerprint classification.