Abstract: This paper presents an information retrieval model on
XML documents based on tree matching. Queries and documents are
represented by extended trees. An extended tree is built starting from
the original tree, with additional weighted virtual links between each
node and its indirect descendants allowing to directly reach each
descendant. Therefore only one level separates between each node
and its indirect descendants. This allows to compare the user query
and the document with flexibility and with respect to the structural
constraints of the query. The content of each node is very important to
decide weither a document element is relevant or not, thus the content
should be taken into account in the retrieval process. We separate
between the structure-based and the content-based retrieval processes.
The content-based score of each node is commonly based on the
well-known Tf × Idf criteria. In this paper, we compare between
this criteria and another one we call Tf × Ief. The comparison
is based on some experiments into a dataset provided by INEX1 to
show the effectiveness of our approach on one hand and those of
both weighting functions on the other.
Abstract: Use of the Internet and the World-Wide-Web
(WWW) has become widespread in recent years and mobile agent
technology has proliferated at an equally rapid rate. In this scenario
load balancing becomes important for P2P systems. Beside P2P
systems can be highly heterogeneous, i.e., they may consists of peers
that range from old desktops to powerful servers connected to
internet through high-bandwidth lines. There are various loads
balancing policies came into picture. Primitive one is Message
Passing Interface (MPI). Its wide availability and portability make it
an attractive choice; however the communication requirements are
sometimes inefficient when implementing the primitives provided by
MPI. In this scenario we use the concept of mobile agent because
Mobile agent (MA) based approach have the merits of high
flexibility, efficiency, low network traffic, less communication
latency as well as highly asynchronous. In this study we present
decentralized load balancing scheme using mobile agent technology
in which when a node is overloaded, task migrates to less utilized
nodes so as to share the workload. However, the decision of which
nodes receive migrating task is made in real-time by defining certain
load balancing policies. These policies are executed on PMADE (A
Platform for Mobile Agent Distribution and Execution) in
decentralized manner using JuxtaNet and various load balancing
metrics are discussed.
Abstract: Online Communities are an example of sociallyaware,
self-organising, complex adaptive computing systems.
The multi-agent systems (MAS) paradigm coordinated by
self-organisation mechanisms has been used as an effective
way for the simulation and modeling of such systems. In this
paper, we propose a model for simulating an online health
community using a situated multi-agent system approach,
governed by the co-evolution of the social and spatial
organisations of the agents.
Abstract: This paper examines the modeling and analysis of a
cruise control system using a Petri net based approach, task graphs,
invariant analysis and behavioral properties. It shows how the
structures used can be verified and optimized.
Abstract: In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.
Abstract: Tandem mass spectrometry (MS/MS) is the engine
driving high-throughput protein identification. Protein mixtures possibly
representing thousands of proteins from multiple species are
treated with proteolytic enzymes, cutting the proteins into smaller
peptides that are then analyzed generating MS/MS spectra. The
task of determining the identity of the peptide from its spectrum
is currently the weak point in the process. Current approaches to de
novo sequencing are able to compute candidate peptides efficiently.
The problem lies in the limitations of current scoring functions. In this
paper we introduce the concept of proteome signature. By examining
proteins and compiling proteome signatures (amino acid usage) it is
possible to characterize likely combinations of amino acids and better
distinguish between candidate peptides. Our results strongly support
the hypothesis that a scoring function that considers amino acid usage
patterns is better able to distinguish between candidate peptides. This
in turn leads to higher accuracy in peptide prediction.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: Bootstrapping has gained popularity in different tests of hypotheses as an alternative in using asymptotic distribution if one is not sure of the distribution of the test statistic under a null hypothesis. This method, in general, has two variants – the parametric and the nonparametric approaches. However, issues on reliability of this method always arise in many applications. This paper addresses the issue on reliability by establishing a reliability measure in terms of quantiles with respect to asymptotic distribution, when this is approximately correct. The test of hypotheses used is Ftest. The simulated results show that using nonparametric bootstrapping in F-test gives better reliability than parametric bootstrapping with relatively higher degrees of freedom.
Abstract: Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.
Abstract: A DC servomotor position control system using a Fuzzy Logic Sliding mode Model Following Control or FLSMFC approach is presented. The FLSMFC structure consists of an integrator and variable structure system. The integral control is introduced into it in order to eliminated steady state error due to step and ramp command inputs and improve control precision, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a DC servomotor drives. Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, excellent control effects and avoids the chattering phenomenon.
Abstract: This paper presents the development of a hybrid
thermal model for the EVO Electric AFM 140 Axial Flux Permanent
Magnet (AFPM) machine as used in hybrid and electric vehicles. The
adopted approach is based on a hybrid lumped parameter and finite
difference method. The proposed method divides each motor
component into regular elements which are connected together in a
thermal resistance network representing all the physical connections
in all three dimensions. The element shape and size are chosen
according to the component geometry to ensure consistency. The
fluid domain is lumped into one region with averaged heat transfer
parameters connecting it to the solid domain. Some model parameters
are obtained from Computation Fluid Dynamic (CFD) simulation and
empirical data. The hybrid thermal model is described by a set of
coupled linear first order differential equations which is discretised
and solved iteratively to obtain the temperature profile. The
computation involved is low and thus the model is suitable for
transient temperature predictions. The maximum error in temperature
prediction is 3.4% and the mean error is consistently lower than the
mean error due to uncertainty in measurements. The details of the
model development, temperature predictions and suggestions for
design improvements are presented in this paper.
Abstract: This paper examines the role of telecommunications in sustainable development of urban, rural and remote communities in the Northern Territory of Australia through the theoretical lens of Social Capital. Social Capital is a relatively new construct and is rapidly gaining interest among policy makers, politicians and researchers as a means to both describe and understand social and economic development. Increasingly, the concept of Social Capital, as opposed to the traditional economic indicators, is seen as a more accurate measure of well-being. Whilst the essence of Social Capital is quality social relations, the concept intersects with telecommunications and Information Communications Technology (ICT) in a number of ways. The potential of ICT to disseminate information quickly, to reach vast numbers of people simultaneously and to include the previously excluded, is immense. However, the exact nature of the relationship is not clearly defined. This paper examines the nexus between social relations of mutual benefit, telecommunications access and sustainable development. A mixed methodological approach was used to test the hypothesis that No relationship exists between Social Capital and access to telecommunications services and facilities. Four communities, which included two urban, a rural and a remote Indigenous community in the Northern Territory of Australia are the focus of this research paper.
Abstract: Microwave energy can be used for drying purpose. It is unique process. It is distinctly different from conventional drying process. It is advantageous over conventional drying / heating processes. When microwave energy is used for drying purpose, the process can be accelerated with a better control to achieve uniform heating, more conversion efficiency, selective drying and ultimately improved product quality of the output. Also, less floor space and compact system are the added advantages. Existing low power microwave drying system is to be modified with suitable applicator. Appropriate sensors are to be used to measure parameters like moisture, temperature, weight of sample. Suitable high tech controller is to be used to control microwave power continuously from minimum to maximum. Phase - controller, cycle - controller and PWM - controller are some of the advanced power control techniques. It has been proposed to work on turmeric using high-tech phase controller to control the microwave power conveniently. The drying of turmeric with microwave energy employing phase controller gives better results as formulated in this paper and hence new approach of processing turmeric will open future doors of profit making to allied industries and the farmers.
Abstract: The paper structures research approaches to the crisis
and its management. It focuses on approaches – psychological,
sociological, economic, ethical and technological. Furthermore, it
describes the basic features of models chosen according to those
approaches. By their comparison it shows how the crisis influences
organizations and individuals, and their mutual interaction.
Abstract: Evolvable Hardware (EHW) has been regarded as adaptive system acquired by wide application market. Consumer market of any good requires diversity to satisfy consumers- preferences. Adaptation of EHW is a key technology that could provide individual approach to every particular user. This situation raises a question: how to set target for evolutionary algorithm? The existing techniques do not allow consumer to influence evolutionary process. Only designer at the moment is capable to influence the evolution. The proposed consumer-triggered evolution overcomes this problem by introducing new features to EHW that help adaptive system to obtain targets during consumer stage. Classification of EHW is given according to responsiveness, imitation of human behavior and target circuit response. Home intelligent water heating system is considered as an example.
Abstract: The objective of this study is to evaluate the threshold
stress of the clay with sand subgrade soil. Threshold stress can be
defined as the stress level above which cyclic loading leads to
excessive deformation and eventual failure. The thickness
determination of highways formations using the threshold stress
approach is a more realistic assessment of the soil behaviour because
it is subjected to repeated loadings from moving vehicles. Threshold
stress can be evaluated by plastic strain criterion, which is based on
the accumulated plastic strain behaviour during cyclic loadings [1].
Several conditions of the all-round pressure the subgrade soil namely,
zero confinement, low all-round pressure and high all-round pressure
are investigated. The threshold stresses of various soil conditions are
determined. Threshold stress of the soil are 60%, 31% and 38.6% for
unconfined partially saturated sample, low effective stress saturated
sample, high effective stress saturated sample respectively.
Abstract: The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.
Abstract: Steganography, derived from Greek, literally means
“covered writing". It includes a vast array of secret communications
methods that conceal the message-s very existence. These methods
include invisible inks, microdots, character arrangement, digital
signatures, covert channels, and spread spectrum communications.
This paper proposes a new improved version of Least Significant Bit
(LSB) method. The approach proposed is simple for implementation
when compared to Pixel value Differencing (PVD) method and yet
achieves a High embedding capacity and imperceptibility. The
proposed method can also be applied to 24 bit color images and
achieve embedding capacity much higher than PVD.
Abstract: Accurate evaluation of damping ratios involving soilstructure interaction (SSI) effects is the prerequisite for seismic design of in-situ buildings. This study proposes a combined approach to identify damping ratios of SSI systems based on ambient excitation technique. The proposed approach is illustrated with main test process, sampling principle and algorithm steps through an engineering example, as along with its feasibility and validity. The proposed approach is employed for damping ratio identification of 82 buildings in Xi-an, China. Based on the experimental data, the variation range and tendency of damping ratios of these SSI systems, along with the preliminary influence factor, are shown and discussed. In addition, a fitting curve indicates the relation between the damping ratio and fundamental natural period of SSI system.
Abstract: The cost of developing the software from scratch can
be saved by identifying and extracting the reusable components from
already developed and existing software systems or legacy systems
[6]. But the issue of how to identify reusable components from
existing systems has remained relatively unexplored. We have used
metric based approach for characterizing a software module. In this
present work, the metrics McCabe-s Cyclometric Complexity
Measure for Complexity measurement, Regularity Metric, Halstead
Software Science Indicator for Volume indication, Reuse Frequency
metric and Coupling Metric values of the software component are
used as input attributes to the different types of Neural Network
system and reusability of the software component is calculated. The
results are recorded in terms of Accuracy, Mean Absolute Error
(MAE) and Root Mean Squared Error (RMSE).