Abstract: XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.
Abstract: Main goal of preventive healthcare problems are at
decreasing the likelihood and severity of potentially life-threatening
illnesses by protection and early detection. The levels of
establishment and staffing costs along with summation of the travel
and waiting time that clients spent are considered as objectives
functions of the proposed nonlinear integer programming model. In
this paper, we have proposed a bi-objective mathematical model for
designing a network of preventive healthcare facilities so as to
minimize aforementioned objectives, simultaneously. Moreover, each
facility acts as M/M/1 queuing system. The number of facilities to be
established, the location of each facility, and the level of technology
for each facility to be chosen are provided as the main determinants
of a healthcare facility network. Finally, to demonstrate performance
of the proposed model, four multi-objective decision making
techniques are presented to solve the model.
Abstract: The security of computer networks plays a strategic
role in modern computer systems. Intrusion Detection Systems (IDS)
act as the 'second line of defense' placed inside a protected
network, looking for known or potential threats in network traffic
and/or audit data recorded by hosts. We developed an Intrusion
Detection System using LAMSTAR neural network to learn patterns
of normal and intrusive activities, to classify observed system
activities and compared the performance of LAMSTAR IDS with
other classification techniques using 5 classes of KDDCup99 data.
LAMSAR IDS gives better performance at the cost of high
Computational complexity, Training time and Testing time, when
compared to other classification techniques (Binary Tree classifier,
RBF classifier, Gaussian Mixture classifier). we further reduced the
Computational Complexity of LAMSTAR IDS by reducing the
dimension of the data using principal component analysis which in
turn reduces the training and testing time with almost the same
performance.
Abstract: Tolerance is a tool for achieving a social cohesion, particularly, among individuals and groups with different values. The aim is to study the characteristics of the ethnic tolerance, the inhabitants of Latvia. The ethnic tolerance is taught as a set of conscious and unconscious orientations of the individual in social interaction and inter-ethnic communication. It uses the tools of empirical studies of the ethnic tolerance which allows to identify the explicitly and implicitly levels of the emotional component of Latvia's residents. Explicit measurements were made using the techniques of self-report which revealed the index of the ethnic tolerance and the ethnic identity of the participants. The implicit component was studied using methods based on the effect of the emotional priming. During the processing of the results, there were calculated indicators of the positive and negative implicit attitudes towards members of their own and other ethnicity as well as the explicit parameters of the ethnic tolerance and the ethnic identity of Latvia-s residents. The implicit measurements of the ratio of neighboring ethnic groups against each other showed a mutual negative attitude whereas the explicit measurements indicate a neutral attitude. The data obtained contribute to a further study of the ethnic tolerance of Latvia's residents.
Abstract: Imaging is defined as the process of obtaining
geometric images either two dimensional or three dimensional by scanning or digitizing the existing objects or products. In this research, it applied to retrieve 3D information of the human skin
surface in medical application. This research focuses on analyzing
and determining volume of leg ulcers using imaging devices. Volume
determination is one of the important criteria in clinical assessment of leg ulcer. The volume and size of the leg ulcer wound will give the
indication on responding to treatment whether healing or worsening.
Different imaging techniques are expected to give different result (and accuracies) in generating data and images. Midpoint projection
algorithm was used to reconstruct the cavity to solid model and compute the volume. Misinterpretation of the results can affect the
treatment efficacy. The objectives of this paper is to compare the
accuracy between two 3D data acquisition method, which is laser
triangulation and structured light methods, It was shown that using models with known volume, that structured-light-based 3D technique
produces better accuracy compared with laser triangulation data
acquisition method for leg ulcer volume determination.
Abstract: A lot of research made during these last 15 years
showed that the quantification of the springback has a significant role
in the industry of sheet metal forming. These studies were made with
the objective of finding techniques and methods to minimize or
completely avoid this permanent physical variation. Moreover, the
use of steel and aluminum alloys in the car industry and aviation
poses every day the problem of the springback. The determination in
advance of the quantity of the springback allows consequently the
design and manufacture of the tool. The aim of this paper is to study
experimentally the influence of the blank holder force BHF and the
radius of curvature of the die on the springback and their influence on
the strain in various zone of specimen.
The original of our purpose consist on tests which are ensured by
adapting a U-type stretching-bending device on a tensile testing
machine, where we studied and quantified the variation of the
springback according to displacement.
Abstract: State Dependent Riccati Equation (SDRE) approach is
a modification of the well studied LQR method. It has the capability of being applied to control nonlinear systems. In this paper the technique
has been applied to control the single inverted pendulum (SIP) which represents a rich class of nonlinear underactuated systems. SIP
modeling is based on Euler-Lagrange equations. A procedure is developed
for judicious selection of weighting parameters and constraint handling. The controller designed by SDRE technique here gives better results than existing controllers designed by energy based techniques.
Abstract: The ubiquitous payment problems within construction
industry of China are notoriously hard to be resolved, thus lead to a
series of impacts to the industry chain. Among of them, the most direct
result is affecting the normal operation of contractors negatively. A
wealth of research has already discussed reasons of the payment
problems by introducing a number of possible improvement strategies.
But the causalities of these problems are still far from harsh reality. In
this paper, the authors propose a model for cash flow system of
construction projects by introducing System Dynamics techniques to
explore causal facets of the payment problem. The effects of payment
arrears on both cash flow and profitability of project are simulated into
four scenarios by using data from real projects. Simulating results
show visible clues to help contractors quantitatively determining the
consequences for the construction project that arise from payment
delay.
Abstract: The link between urban planning and design principles and the built environment of an urban renewal area is of interest to the field of urban studies. During the past decade, there has also been increasing interest in urban planning and design; this interest is motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual activity and behavior. However, direct assessments and design techniques of the links between how urban planning design policies influence individuals are still rare in the field. Recent research efforts in urban design have focused on the idea that land use and design policies can be used to increase the quality of design projects for an urban renewal area-s built environment. The development of appropriate design techniques for the built environment is an essential element of this research. Quality function deployment (QFD) is a powerful tool for improving alternative urban design and quality for urban renewal areas, and for procuring a citizen-driven quality system. In this research, we propose an integrated framework based on QFD and an Analytic Network Process (ANP) approach to determine the Alternative Technical Requirements (ATRs) to be considered in designing an urban renewal planning and design alternative. We also identify the research designs and methodologies that can be used to evaluate the performance of urban built environment projects. An application in an urban renewal built environment planning and design project evaluation is presented to illustrate the proposed framework.
Abstract: The aim of this paper is to identify the most suitable
model for churn prediction based on three different techniques. The
paper identifies the variables that affect churn in reverence of
customer complaints data and provides a comparative analysis of
neural networks, regression trees and regression in their capabilities
of predicting customer churn.
Abstract: This paper presents a comparative study on
Vanadyl Phthalocyanine (VOPc) thin films deposited by thermal
evaporation and spin coating techniques. The samples
were prepared on cleaned glass substrates and annealed at
various temperatures ranging form 95oC to 155oC. To obtain
the morphological and structural properties of VOPc thin
films, X-ray diffraction (XRD) technique and atomic force
microscopy (AFM) have been implied. The AFM topographic
images show a very slight difference in the thermally grown
films, before and after annealing, however best results are
achieved for the spin-cast film annealed at 125oC. The XRD
spectra show no existence of the sharp peaks, suggesting the
material to be amorphous. The humps in the XRD patterns
indicate the presence of some crystallites.
Abstract: Component-Based software engineering provides an
opportunity for better quality and increased productivity in software
development by using reusable software components [10]. One of the
most critical aspects of the quality of a software system is its
performance. The systematic application of software performance
engineering techniques throughout the development process can help
to identify design alternatives that preserve desirable qualities such
as extensibility and reusability while meeting performance objectives
[1]. In the present scenario, software engineering methodologies
strongly focus on the functionality of the system, while applying a
“fix- it-later" approach to software performance aspects [3]. As a
result, lengthy fine-tunings, expensive extra hard ware, or even
redesigns are necessary for the system to meet the performance
requirements. In this paper, we propose design based,
implementation independent, performance prediction approach to
reduce the overhead associated in the later phases while developing a
performance guaranteed software product with the help of Unified
Modeling Language (UML).
Abstract: Sign language is used by the deaf and hard of hearing people for communication. Automatic sign language recognition is a challenging research area since sign language often is the only way of communication for the deaf people. Sign language includes different components of visual actions made by the signer using the hands, the face, and the torso, to convey his/her meaning. To use different aspects of signs, we combine the different groups of features which have been extracted from the image frames recorded directly by a stationary camera. We combine the features in two levels by employing three techniques. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, or by concatenating feature groups over time and using LDA to choose the most discriminant elements. At the model level, a late fusion of differently trained models can be carried out by a log-linear model combination. In this paper, we investigate these three combination techniques in an automatic sign language recognition system and show that the recognition rate can be significantly improved.
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: 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 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: 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: 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