Abstract: This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the given environment. The suggested method is applied to the control of KUKA™,, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of MatLab™, and RecurDyn™,.
Abstract: In this paper a novel approach for generalized image
retrieval based on semantic contents is presented. A combination of
three feature extraction methods namely color, texture, and edge
histogram descriptor. There is a provision to add new features in
future for better retrieval efficiency. Any combination of these
methods, which is more appropriate for the application, can be used
for retrieval. This is provided through User Interface (UI) in the
form of relevance feedback. The image properties analyzed in this
work are by using computer vision and image processing algorithms.
For color the histogram of images are computed, for texture cooccurrence
matrix based entropy, energy, etc, are calculated and for
edge density it is Edge Histogram Descriptor (EHD) that is found.
For retrieval of images, a novel idea is developed based on greedy
strategy to reduce the computational complexity. The entire system
was developed using AForge.Imaging (an open source product),
MATLAB .NET Builder, C#, and Oracle 10g. The system was tested
with Coral Image database containing 1000 natural images and
achieved better results.
Abstract: One of the ubiquitous routines in medical practice is searching through voluminous piles of clinical documents. In this paper we introduce a distributed system to search and exchange clinical documents. Clinical documents are distributed peer-to-peer. Relevant information is found in multiple iterations of cross-searches between the clinical text and its domain encyclopedia.
Abstract: A number of automated shot-change detection
methods for indexing a video sequence to facilitate browsing and
retrieval have been proposed in recent years. This paper emphasizes
on the simulation of video shot boundary detection using one of the
methods of the color histogram wherein scaling of the histogram
metrics is an added feature. The difference between the histograms of
two consecutive frames is evaluated resulting in the metrics. Further
scaling of the metrics is performed to avoid ambiguity and to enable
the choice of apt threshold for any type of videos which involves
minor error due to flashlight, camera motion, etc. Two sample videos
are used here with resolution of 352 X 240 pixels using color
histogram approach in the uncompressed media. An attempt is made
for the retrieval of color video. The simulation is performed for the
abrupt change in video which yields 90% recall and precision value.
Abstract: Nowadays social media are important tools for web
resource discovery. The performance and capabilities of web searches
are vital, especially search results from social research paper
bookmarking. This paper proposes a new algorithm for ranking
method that is a combination of similarity ranking with paper posted
time or CSTRank. The paper posted time is static ranking for
improving search results. For this particular study, the paper posted
time is combined with similarity ranking to produce a better ranking
than other methods such as similarity ranking or SimRank. The
retrieval performance of combination rankings is evaluated using
mean values of NDCG. The evaluation in the experiments implies
that the chosen CSTRank ranking by using weight score at ratio 90:10
can improve the efficiency of research paper searching on social
bookmarking websites.
Abstract: Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.
Abstract: This paper describes a feasibility study that is
included with the research, development and testing of a micro
communications sonobuoy deployable by Maritime Fixed wing
Unmanned Aerial Vehicles (M-UAV) and rotor wing Quad Copters
which are both currently being developed by the University of
Adelaide. The micro communications sonobuoy is developed to act
as a seamless communication relay between an Autonomous
Underwater Vehicle (AUV) and an above water human operator
some distance away. Development of such a device would eliminate
the requirement of physical communication tethers attached to
submersible vehicles for control and data retrieval.
Abstract: In this paper, a model for an information retrieval
system is proposed which takes into account that knowledge about
documents and information need of users are dynamic. Two
methods are combined, one qualitative or symbolic and the other
quantitative or numeric, which are deemed suitable for many
clustering contexts, data analysis, concept exploring and
knowledge discovery. These two methods may be classified as
inductive learning techniques. In this model, they are introduced to
build “long term" knowledge about past queries and concepts in a
collection of documents. The “long term" knowledge can guide
and assist the user to formulate an initial query and can be
exploited in the process of retrieving relevant information. The
different kinds of knowledge are organized in different points of
view. This may be considered an enrichment of the exploration
level which is coherent with the concept of document/query
structure.
Abstract: Relational databases are often used as a basis for persistent storage of ontologies to facilitate rapid operations such as search and retrieval, and to utilize the benefits of relational databases management systems such as transaction management, security and integrity control. On the other hand, there appear more and more OWL files that contain ontologies. Therefore, this paper proposes to extract ontologies from OWL files and then store them in relational databases. A prerequisite for this storing is transformation of ontologies to relational databases, which is the purpose of this paper.
Abstract: This study investigates the use of genetic algorithms
in information retrieval. The method is shown to be applicable to
three well-known documents collections, where more relevant
documents are presented to users in the genetic modification. In this
paper we present a new fitness function for approximate information
retrieval which is very fast and very flexible, than cosine similarity
fitness function.
Abstract: This paper presents a digital engineering library – the
Digital Mechanism and Gear Library, DMG-Lib – providing a multimedia collection of e-books, pictures, videos and animations in the domain of mechanisms and machines. The specific characteristic
about DMG-Lib is the enrichment and cross-linking of the different
sources. DMG-Lib e-books not only present pages as pixel images
but also selected figures augmented with interactive animations. The
presentation of animations in e-books increases the clearness of the
information.
To present the multimedia e-books and make them available in the
DMG-Lib internet portal a special e-book reader called StreamBook
was developed for optimal presentation of digitized books and to
enable reading the e-books as well as working efficiently and individually with the enriched information. The objective is to support different user tasks ranging from information retrieval to
development and design of mechanisms.
Abstract: This study aims to segment objects using the K-means
algorithm for texture features. Firstly, the algorithm transforms color
images into gray images. This paper describes a novel technique for
the extraction of texture features in an image. Then, in a group of
similar features, objects and backgrounds are differentiated by using
the K-means algorithm. Finally, this paper proposes a new object
segmentation algorithm using the morphological technique. The
experiments described include the segmentation of single and multiple
objects featured in this paper. The region of an object can be
accurately segmented out. The results can help to perform image
retrieval and analyze features of an object, as are shown in this paper.
Abstract: Sharing consistent and correct master data among
disparate applications in a reverse-logistics chain has long been
recognized as an intricate problem. Although a master data
management (MDM) system can surely assume that responsibility,
applications that need to co-operate with it must comply with
proprietary query interfaces provided by the specific MDM system. In
this paper, we present a RFID-ready MDM system which makes
master data readily available for any participating applications in a
reverse-logistics chain. We propose a RFID-wrapper as a part of our
MDM. It acts as a gateway between any data retrieval request and
query interfaces that process it. With the RFID-wrapper, any
participating applications in a reverse-logistics chain can easily
retrieve master data in a way that is analogous to retrieval of any other
RFID-based logistics transactional data.
Abstract: Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.
Abstract: Pattern recognition and image recognition methods are commonly developed and tested using testbeds, which contain known responses to a query set. Until now, testbeds available for image analysis and content-based image retrieval (CBIR) have been scarce and small-scale. Here we present the one million images CEA-List Image Collection (CLIC) testbed that we have produced, and report on our use of this testbed to evaluate image analysis merging techniques. This testbed will soon be made publicly available through the EU MUSCLE Network of Excellence.
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: This article describes Uruk, the virtual museum of
Iraq that we developed for visual exploration and retrieval of image
collections. The system largely exploits the loosely-structured
hierarchy of XML documents that provides a useful representation
method to store semi-structured or unstructured data, which does not
easily fit into existing database. The system offers users the
capability to mine and manage the XML-based image collections
through a web-based Graphical User Interface (GUI). Typically, at an
interactive session with the system, the user can browse a visual
structural summary of the XML database in order to select interesting
elements. Using this intermediate result, queries combining structure
and textual references can be composed and presented to the system.
After query evaluation, the full set of answers is presented in a visual
and structured way.
Abstract: This paper presents the design and implementation of
the WebGD, a CORBA-based document classification and retrieval
system on Internet. The WebGD makes use of such techniques as Web,
CORBA, Java, NLP, fuzzy technique, knowledge-based processing
and database technology. Unified classification and retrieval model,
classifying and retrieving with one reasoning engine and flexible
working mode configuration are some of its main features. The
architecture of WebGD, the unified classification and retrieval model,
the components of the WebGD server and the fuzzy inference engine
are discussed in this paper in detail.
Abstract: PARIS (Personal Archiving and Retrieving Image
System) is an experiment personal photograph library, which includes
more than 80,000 of consumer photographs accumulated within a
duration of approximately five years, metadata based on our proposed
MPEG-7 annotation architecture, Dozen Dimensional Digital Content
(DDDC), and a relational database structure. The DDDC architecture
is specially designed for facilitating the managing, browsing and
retrieving of personal digital photograph collections. In annotating
process, we also utilize a proposed Spatial and Temporal Ontology
(STO) designed based on the general characteristic of personal
photograph collections. This paper explains PRAIS system.
Abstract: In this paper, we propose a new model of English-
Vietnamese bilingual Information Retrieval system. Although there
are so many CLIR systems had been researched and built, the accuracy of searching results in different languages that the CLIR
system supports still need to improve, especially in finding bilingual documents. The problems identified in this paper are the limitation of
machine translation-s result and the extra large collections of document to be found. So we try to establish a different model to overcome these problems.