[AISWorld] Contents of IJIIT 15(1) - International Journal of Intelligent Information Technologies (IJIIT)

[Vijayan Sugumaran]

The contents of the latest issue of:
International Journal of Intelligent Information Technologies (IJIIT)
Volume 15, Issue 1, January - March 2019
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

eHR Cloud Transformation: Implementation Approach and Success Factors

Robert-Christian Ziebell (Universitat Politècnica de València, Valencia,
Spain), Jose Albors-Garrigos (Universitat Politècnica de València, Valencia,
Spain), Martin Schultz (HAW Hamburg, Hamburg, Germany), Klaus Peter
Schoeneberg (Beuth University of Applied Sciences Berlin, Berlin, Germany),
M. Rosario Perello-Marin (Universitat Politècnica de València, Valencia,
Spain)

The article covers process models for HR IT projects and in particular for
HR transformation projects. Based on the authors' experience, an applied
process model for HR transformation projects in a cloud-based environment is
derived. The article identifies findings applicable to the fields of
organisation, business, and IT as well as decisions and critical success
factors in the specific context of cloud-based HR solutions.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/ehr-cloud-transformation/221351
<https://www.igi-global.com/article/ehr-cloud-transformation/221351> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=221351
<https://www.igi-global.com/viewtitlesample.aspx?id=221351> 

ARTICLE 2

SVM-Based Traffic Data Classification for Secured IoT-Based Road Signaling
System

Suresh Sankaranarayanan (SRM Institute of Science and Technology, Chennai,
India), Srijanee Mookherji (SRM Institute of Science and Technology,
Chennai, India)

The traffic controlling systems at present are microcontroller-based, which
is semi-automatic in nature where time is the only parameter that is
considered. With the introduction of IoT in traffic signaling systems,
research is being done considering density as a parameter for automating the
traffic signaling system and regulate traffic dynamically. Security is a
concern when sensitive data of great volume is being transmitted wirelessly.
Security protocols that have been implemented for IoT networks can protect
the system against attacks and are purely based on standard cryptosystem.
They cannot handle heterogeneous data type. To prevent the issues on
security protocols, the authors have implemented SVM machine learning
algorithm for analyzing the traffic data pattern and detect anomalies. The
SVM implementation has been done for the UK traffic data set between
2011-2016 for three cities. The implementation been carried out in Raspberry
Pi3 processor functioning as an edge router and SVM machine learning
algorithm using Python Scikit Libraries.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/svm-based-traffic-data-classification-for-secured
-iot-based-road-signaling-system/221352
<https://www.igi-global.com/article/svm-based-traffic-data-classification-fo
r-secured-iot-based-road-signaling-system/221352> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=221352
<https://www.igi-global.com/viewtitlesample.aspx?id=221352> 

ARTICLE 3

A Multi-Stage Fuzzy Model for Assessing Applicants for Faculty Positions in
Universities

Raghda Hraiz (PSUT, Amman, Jordan), Mariam Khader (SUT, Amman, Jordan),
Adnan Shaout (The University of Michigan, Dearborn, USA)

Assessing applicants for faculty positions in universities involves many
issues. Each issue may involve a judgment based on uncertain or imprecise
data. The uncertainty in data may exist in the interpretation made by the
evaluator. This issue might lead to improper decision making. Modeling such
a system using fuzzy logic will provide a more efficient model for handling
imprecision. This article presents a fuzzy system for modeling the
assessment of applicants for employment at academic universities. This
system will utilize a multi-stage fuzzy model for measuring and evaluating
the applicants. Utilizing fuzzy logic for applicants' evaluation will help
administrators in choosing the best candidates for faculty positions. The
fuzzy system was developed using jFuzzyLogic Java library. The reliability
of the proposed system was proved by evaluating real-world case studies to
prove its effectiveness to mimic human judgment. Moreover, the developed
system has been evaluated by comparing it with a traditional mathematical
method to prove the credibility and fairness of the proposed fuzzy system.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/a-multi-stage-fuzzy-model-for-assessing-applicant
s-for-faculty-positions-in-universities/221353
<https://www.igi-global.com/article/a-multi-stage-fuzzy-model-for-assessing-
applicants-for-faculty-positions-in-universities/221353> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=221353
<https://www.igi-global.com/viewtitlesample.aspx?id=221353> 

ARTICLE 4

Energy Efficient Load Balancing in Cloud Data Center Using Clustering
Technique

N. Thilagavathi (Anna University, Chennai, India), D. Divya Dharani (Anna
University, Chennai, India), R. Sasilekha (Anna University, Chennai, India),
Vasundhara Suruliandi (Anna University, Chennai, India), V. Rhymend
Uthariaraj (Anna University, Chennai, India)

Cloud computing has seen tremendous growth in recent days. As a result of
this, there has been a great increase in the growth of data centers all over
the world. These data centers consume a lot of energy, resulting in high
operating costs. The imbalance in load distribution among the servers in the
data center results in increased energy consumption. Server consolidation
can be handled by migrating all virtual machines in those underutilized
servers. Migration causes performance degradation of the job, based on the
migration time and number of migrations. Considering these aspects, the
proposed clustering agent-based model improves energy saving by efficient
allocation of the VMs to the hosting servers, which reduces the response
time for initial allocation. Middle VM migration (MVM) strategy for server
consolidation minimizes the number of VM migrations. Further, randomization
of extra resource requirement done to cater to real-time scenarios needs
more resource requirements than the initial requirement. Simulation results
show that the proposed approach reduces the number of migrations and
response time for user request and improves energy saving in the cloud
environment.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/energy-efficient-load-balancing-in-cloud-data-cen
ter-using-clustering-technique/221354
<https://www.igi-global.com/article/energy-efficient-load-balancing-in-cloud
-data-center-using-clustering-technique/221354> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=221354
<https://www.igi-global.com/viewtitlesample.aspx?id=221354> 

ARTICLE 5

Institutionalization of Business Intelligence for the Decision-Making
Iteration

Shaheb Ali (School of Business IT and Logistics, RMIT University, Melbourne,
Australia), Rafiqul Islam (School of Computing and Mathematics, Charles
Sturt University, Albury Campus, Australia), Ferdausur Rahman (Department of
Accounting, Military Institute of Science and Technology, Dhaka, Bangladesh)

Business intelligence (BI) institutionalization has become a growing
research area within the information systems (IS) discipline because of the
decision-making iteration in businesses. Studies on BI application in
improving decision support are not new. However, research on BI
institutionalization seems sparse. BI institutionalization may positively
contribute to a managerial role in using BI application repetitively for the
decision-making iteration in businesses. This article aims to carry out an
integrative literature review and report consolidated views of the body of
knowledge. The study adopted a qualitative content analysis to generate
themes about BI routinization in the decision-making iteration. Eighty-eight
research articles were selected for the study. However, 57 articles were
finally included for review. The findings suggest information management
capability as the key necessity for BI application and its alignment with
the organizational standard for BI institutionalization.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/institutionalization-of-business-intelligence-for
-the-decision-making-iteration/221355
<https://www.igi-global.com/article/institutionalization-of-business-intelli
gence-for-the-decision-making-iteration/221355> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=221355
<https://www.igi-global.com/viewtitlesample.aspx?id=221355> 

  _____  

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

Co-Director, Center for Data Science and Big Data Analytics

School of Business Administration

Oakland University

Rochester, MI 48309

Phone: 248-370-4649

Fax: 248-370-4275

Email: sugumara at oakland.edu <mailto:sugumara at oakland.edu> 

=============================================