[AISWorld] Contents of IJIIT 14(1) - International Journal of Intelligent Information Technologies (IJIIT)
Vijayan Sugumaran
sugumara at oakland.edu
Thu Oct 12 10:12:43 EDT 2017
The contents of the latest issue of:
International Journal of Intelligent Information Technologies (IJIIT)
Volume 14, Issue 1, January - March 2018
Indexed by: Compendex (Elsevier Engineering Index), INSPEC, SCOPUS, Web of
Science Emerging Sources Citation Index (ESCI)
For a complete list of indexing and abstracting services that include this
journal, please reference the bottom of this announcement.
Published: Quarterly in Print and Electronically
ISSN: 1548-3657; EISSN: 1548-3665;
Published by IGI Global Publishing, Hershey, USA
www.igi-global.com/ijiit
<https://www.igi-global.com/journal/international-journal-intelligent-inform
ation-technologies/1089>
Editor-in-Chief: Vijayan Sugumaran (Oakland University, USA)
Note: The International Journal of Intelligent Information Technologies
(IJIIT) has an Open Access option, which allows individuals and institutions
unrestricted access to its published content. Unlike traditional
subscription-based publishing models, open access content is available
without having to purchase or subscribe to the journal in which the content
is published. All IGI Global manuscripts are accepted based on a
double-blind peer review editorial process.
ARTICLE 1
Intelligent Techniques for Providing Effective Security to Cloud Databases
Ar Arunarani (Anna University, Department of Computer Science and
Engineering, Chennai, India), D Manjula Perkinian (Anna University,
Department of Computer Science and Engineering, Chennai, India)
Cloud databases have been used in a spate of web-based applications in
recent years owing to their capacity to store big data efficiently. In such
a scenario, access control techniques implemented in relational databases
are so modified as to suit cloud databases. The querying features of cloud
databases are designed with facilities to retrieve encrypted data. The
performance with respect to retrieval and security needs further
improvements to ensure a secured retrieval process. In order to provide an
efficient secured retrieval mechanism, a rule- and agent-based intelligent
secured retrieval model has been proposed in this paper that analyzes the
user, query and contents to be retrieved so as to effect rapid retrieval
with decryption from the cloud databases. The major advantage of this
retrieval model is in terms of its improved query response time and enhanced
security of the storage and retrieval system. From the experiments conducted
in this work, proposed model increased storage and access time and, in
addition, intensified the security of the data stored in cloud databases.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/intelligent-techniques-for-providing-effective-se
curity-to-cloud-databases/190651
<https://www.igi-global.com/article/intelligent-techniques-for-providing-eff
ective-security-to-cloud-databases/190651>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=190651
<https://www.igi-global.com/viewtitlesample.aspx?id=190651>
ARTICLE 2
Word Sense Based Hindi-Tamil Statistical Machine Translation
Vimal Kumar K. (Jaypee Institute of Information Technology, Department of
Computer Science and Engineering and Information Technology, Noida, India),
Divakar Yadav (Jaypee Institute of Information Technology, Department of
Computer Science and Engineering and Information Technology, Noida, India)
Corpus based natural language processing has emerged with great success in
recent years. It is not only used for languages like English, French,
Spanish, and Hindi but also is widely used for languages like Tamil, Telugu
etc. This paper focuses to increase the accuracy of machine translation from
Hindi to Tamil by considering the word's sense as well as its
part-of-speech. This system works on word by word translation from Hindi to
Tamil language which makes use of additional information such as the
preceding words, the current word's part of speech and the word's sense
itself. For such a translation system, the frequency of words occurring in
the corpus, the tagging of the input words and the probability of the
preceding word of the tagged words are required. Wordnet is used to identify
various synonym for the words specified in the source language. Among these
words, the one which is more relevant to the word specified in source
language is considered for the translation to target language. The
introduction of the additional information such as part-of-speech tag,
preceding word information and semantic analysis has greatly improved the
accuracy of the system.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/word-sense-based-hindi-tamil-statistical-machine-
translation/190652
<https://www.igi-global.com/article/word-sense-based-hindi-tamil-statistical
-machine-translation/190652>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=190652
<https://www.igi-global.com/viewtitlesample.aspx?id=190652>
ARTICLE 3
Clustering-Based Color Image Segmentation Using Local Maxima
Kalaivani Anbarasan (Department of Computer Science and Engineering,
Saveetha School of Engineering, Saveetha University, Tamil Nadu, India), S.
Chitrakala (Anna University, Department of Computer Science and Engineering,
Chennai, India,)
Color image segmentation has contributed significantly to image analysis and
retrieval of relevant images. Color image segmentation helps the end user
subdivide user input images into unique homogenous regions of similar
pixels, based on pixel property. The success of image analysis is largely
owing to the reliability of segmentation. The automatic segmentation of a
color image into accurate regions without over-segmentation is a tedious
task. Our paper focuses on segmenting color images automatically into
multiple regions accurately, based on the local maxima of the GLCM texture
property, with pixels spatially clustered into identical regions. A novel
Clustering-based Image Segmentation using Local Maxima (CBIS-LM) method is
presented. Our proposed approach generates reliable, accurate and
non-overlapping multiple regions for the given user input image. The
segmented regions can be automatically annotated with distinct labels which,
in turn, help retrieve relevant images based on image semantics.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/clustering-based-color-image-segmentation-using-l
ocal-maxima/190653
<https://www.igi-global.com/article/clustering-based-color-image-segmentatio
n-using-local-maxima/190653>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=190653
<https://www.igi-global.com/viewtitlesample.aspx?id=190653>
ARTICLE 4
An Efficient Kinetic Range Query for One Dimensional Axis Parallel Segments
T. Hema (Anna University, Department of Computer Science and Engineering,
Chennai, India), K. S. Easwarakumar (Anna University, Department of Computer
Science and Engineering, Chennai, India)
We present a kinetic data structure named Kinetic Interval Graph (KI-Graph)
for performing efficient range search on moving one dimensional
axis-parallel segments. This finds applications in Artificial Intelligence
such as robotic motion. The structure requires O(n) storage. The time taken
per update when a critical event occurs is O (1) thereby improving
responsiveness when compared to the kinetic segment trees, while the overall
updates across all segments at a time instance is at most n/2. Also, range
query is performed efficiently in ?(k) time, where k segments are reported.
To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/an-efficient-kinetic-range-query-for-one-dimensio
nal-axis-parallel-segments/190654
<https://www.igi-global.com/article/an-efficient-kinetic-range-query-for-one
-dimensional-axis-parallel-segments/190654>
To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=190654
<https://www.igi-global.com/viewtitlesample.aspx?id=190654>
_____
For full copies of the above articles, check for this issue of the
International Journal of Intelligent Information Technologies (IJIIT) in
your institution's library. This journal is also included in the IGI Global
aggregated "InfoSci-Journals" database: www.igi-global.com/isj
<https://www.igi-global.com/e-resources/infosci-databases/infosci-journals/>
.
_____
CALL FOR PAPERS
Mission of IJIIT:
The advent of the World Wide Web has sparked renewed interest in the area of
intelligent information technologies. There is a growing interest in
developing intelligent technologies that enable users to accomplish complex
tasks in web-centric environments with relative ease, utilizing such
technologies as intelligent agents, distributed computing in heterogeneous
environments, and computer supported collaborative work. The mission of the
International Journal of Intelligent Information Technologies (IJIIT) is to
bring together researchers in related fields such as information systems,
distributed AI, intelligent agents, and collaborative work, to explore and
discuss various aspects of design and development of intelligent
technologies. This journal provides a forum for academics and practitioners
to explore research issues related to not only the design, implementation
and deployment of intelligent systems and technologies, but also economic
issues and organizational impact. Papers related to all aspects of
intelligent systems including theoretical work on agent and multi-agent
systems as well as case studies offering insights into agent-based problem
solving with empirical or simulation based evidence are welcome.
Indices of IJIIT:
* ACM Digital Library
* Australian Business Deans Council (ABDC)
* Bacon's Media Directory
* Burrelle's Media Directory
* Cabell's Directories
* Compendex (Elsevier Engineering Index)
* CSA Illumina
* DBLP
* DEST Register of Refereed Journals
* Gale Directory of Publications & Broadcast Media
* GetCited
* Google Scholar
* INSPEC
* JournalTOCs
* Library & Information Science Abstracts (LISA)
* MediaFinder
* Norwegian Social Science Data Services (NSD)
* SCOPUS
* The Index of Information Systems Journals
* The Standard Periodical Directory
* Ulrich's Periodicals Directory
* Web of Science
* Web of Science Emerging Sources Citation Index (ESCI)
Coverage of IJIIT:
The International Journal of Intelligent Information Technologies (IJIIT)
encourages quality research dealing with (but not limited to) the following
topics:
* Agent-based auction, contracting, negotiation, and ecommerce
* Agent-based control and supply chain
* Agent-based simulation and application integration
* Cooperative and collaborative systems
* Distributed intelligent systems and technologies
* Human-agent interaction and experimental evaluation
* Implementation, deployment, diffusion, and organizational impact
* Integrating business intelligence from internal and external sources
* Intelligent agent and multi-agent systems in various domains
* Intelligent decision support systems
* Intelligent information retrieval and business intelligence
* Intelligent information systems development using design science
principles
* Intelligent Web mining and knowledge discovery systems
* Manufacturing information systems
* Models, architectures and behavior models for agent-oriented information
systems
* Multimedia information processing
* Privacy, security, and trust issues
* Reasoning, learning and adaptive systems
* Semantic Web, Web services, and ontologies
Interested authors should consult the journal's manuscript submission
guidelines
www.igi-global.com/calls-for-papers/international-journal-intelligent-inform
ation-technologies/1089
<http://www.igi-global.com/calls-for-papers/international-journal-intelligen
t-information-technologies/1089>
===========================================
Vijayan Sugumaran, Ph.D.
Professor of Management Information Systems
Chair, Department of Decision and Information Sciences
School of Business Administration
Oakland University
Rochester, MI 48309
Phone: 248-370-4649
Fax: 248-370-4275
Email: <mailto:sugumara at oakland.edu> sugumara at oakland.edu
===========================================
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