International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Wikicfp
Friday, 26 October 2018
Wednesday, 24 October 2018
7th International Conference on Soft Computing, Artificial Intelligence and Applications (SCAI 2018)
7th
International Conference on Soft Computing, Artificial Intelligence and
Applications (SCAI 2018)
December 22~ 23,
2018, Sydney, Australia
Scope & Topics
7th International
Conference on Soft Computing, Artificial Intelligence and Applications ( SCAI
2018) Will Provide An Excellent International Forum For Sharing
Knowledge And Results In Theory, Methodology And Applications Of Artificial
Intelligence, Soft Computing. The Conference Looks For Significant
Contributions To All Major Fields Of The Artificial Intelligence, Soft
Computing In Theoretical And Practical Aspects. The Aim Of The Conference Is To
Provide A Platform To The Researchers And Practitioners From Both Academia As
Well As Industry To Meet And Share Cutting-Edge Development In The Field.
Authors Are Solicited To Contribute To
The Conference By Submitting Articles That Illustrate Research Results,
Projects, Surveying Works And Industrial Experiences That Describe Significant
Advances In The Following Areas, But Are Not Limited To.
Topics of Interest
- · Soft Computing
- · Fuzzy Systems
- · Neural Networks
- · Machine Learning
- · Probabilistic Reasoning
- · Evolutionary Computing
- · Pattern Recognition
- · Hybrid Intelligent Systems
- Software Agents
- Morphic
Computing
- Image
Processing
- E-commerce,
e-medicine
- Rough Sets
- Symbolic
Machine Learning
- Wavelet
- Signal or Image
Processing
- Vision
Recognition
- Biomedical
Engineering
- Telecommunications
- Reactive
Distributed AI
- Nano &
Micro-systems
- Data
Visualization
- Artificial
Intelligence
- AI Algorithms
- Artificial
Intelligence Tools & Applications
- Automatic
Control
- Bioinformatics
- Natural
Language Processing
- CAD Design
& Testing
- Computer Vision
and Speech Understanding
- Data Mining and
Machine Learning Tools
- Fuzzy Logic
- Heuristic and
AI Planning Strategies and Tools
- Computational
Theories of Learning
- Hybrid
Intelligent Systems
- Information
Retrieval
- Intelligent
System Architectures
- Knowledge
Representation
- Knowledge-based
Systems
- Mechatronics
- Multimedia
& Cognitive Informatics
- Neural Networks
- Parallel
Processing
- Pervasive
Computing and Ambient Intelligence
- Programming
Languages
- Reasoning and
Evolution
- Recent Trends
and Developments
- Robotics
- Semantic Web
Techniques and Technologies
- Soft Computing
Theory and Applications
- Software &
Hardware Architectures
- Web
Intelligence Applications & Search
- Trainer
Paper Submission
Authors are invited to submit papers
through the Conference Submission System by October 28, 2018. Submissions must be original and
should not have been published previously or be under consideration for
publication while being evaluated for this conference. The proceedings of the
conference will be published by Computer
Science Conference Proceedings in Computer Science & Information
Technology (CS & IT) series
(Confirmed).
Selected Papers From The Conference SCAI 2018, After Further Revisions,
Will Be Published In The Following International Journals.
Important Dates
Submission
Deadline: October 28, 2018
Authors Notification: November 20, 2018
Registration & Camera-Ready Paper Due : November 25, 2018
Contact Us
Monday, 22 October 2018
International Journal on Soft Computing ( IJSC )
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijscjournal@airccse.org
Submission Link : http://coneco2009.com/submissions/imagination/home.html
Wednesday, 17 October 2018
INVESTIGATING SOAP AND XML TECHNOLOGIES IN WEB SERVICE
INVESTIGATING SOAP AND XML TECHNOLOGIES
IN WEB SERVICE
Mehdi Zekriyapanah Gashti
Department of Computer Engineering
Payame Noor University
I.R of IRAN
ABSTRACT
In this paper, Investigating SOAP and XML technologies in web service is studied. The reason for using
XML technology to transmit data and also the need for application of existing communicative structure in
SOAP technology in web pages with WSDL technology are investigated uniquely. And also the need for
searchable address giving for web service which is available in UDDI technology and the advantages of
using it are explained for programmers.
KEYWORDS
XML, SOAP, WSDL, UDDI, OOP, Reliability
Original Source URL : http://airccse.org/journal/ijsc/papers/3412ijsc02.pdf
Tuesday, 16 October 2018
International Journal on Soft Computing ( IJSC )
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijscjournal@airccse.org
Friday, 12 October 2018
ENHANCED SKIN COLOUR CLASSIFIER USING RGB RATIO MODEL
ENHANCED SKIN COLOUR CLASSIFIER USING RGB
RATIO MODEL
Ghazali Osman1
, Muhammad Suzuri Hitam2
and Mohd Nasir Ismail3
1,3Faculty of Information Management
Universiti Teknologi MARA, Kelantan, Malaysia
1
ghaza936@kelantan.uitm.edu.my
3nasir733@kelantan.uitm.edu.my
2Department of Computer Science
Universiti Malaysia Terengganu, Malaysia
suzuri@umt.edu.my
ABSTRACT
Skin colour detection is frequently been used for searching people, face detection, pornographic filtering
and hand tracking. The presence of skin or non-skin in digital image can be determined by manipulating
pixels’ colour and/or pixels’ texture. The main problem in skin colour detection is to represent the skin
colour distribution model that is invariant or least sensitive to changes in illumination condition. Another
problem comes from the fact that many objects in the real world may possess almost similar skin-tone
colour such as wood, leather, skin-coloured clothing, hair and sand. Moreover, skin colour is different
between races and can be different from a person to another, even with people of the same ethnicity.
Finally, skin colour will appear a little different when different types of camera are used to capture the
object or scene. The objective in this study is to develop a skin colour classifier based on pixel-based using
RGB ratio model. The RGB ratio model is a newly proposed method that belongs under the category of an
explicitly defined skin region model. This skin classifier was tested with SIdb dataset and two benchmark
datasets; UChile and TDSD datasets to measure classifier performance. The performance of skin classifier
was measured based on true positive (TF) and false positive (FP) indicator. This newly proposed model
was compared with Kovac, Saleh and Swift models. The experimental results showed that the RGB ratio
model outperformed all the other models in term of detection rate. The RGB ratio model is able to reduce
FP detection that caused by reddish objects colour as well as be able to detect darkened skin and skin
covered by shadow.
KEYWORDS
Image processing, Skin colour detection, Skin colour classifier, Pixel-based classification, RGB ratio model
Original Source URL : http://airccse.org/journal/ijsc/papers/3412ijsc01.pdf
Tuesday, 9 October 2018
International Journal on Soft Computing ( IJSC )
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijscjournal@airccse.org
Submission Link : http://coneco2009.com/submissions/imagination/home.html
Thursday, 4 October 2018
AN INTEGRATIVE SYSTEM FOR PREDICTION OF NAC PROTEINS IN RICE USING DIFFERENT FEATURE EXTRACTION METHODS
AN INTEGRATIVE SYSTEM FOR PREDICTION
OF NAC PROTEINS IN RICE USING
DIFFERENT FEATURE EXTRACTION
METHODS
Hemalatha N. 1,*, Rajesh M. K. 2 and
Narayanan N. K. 3
1AIMIT, St. Aloysius College, Mangalore,
India 2Division of Crop Improvement, Central Plantation Crops
Research Institute, Kasaragod 671124, India 3School of
Information Science and Technology, Kannur University, Kannur, India.
ABSTRACT
The NAC gene family encodes a large family of plant-specific transcription factors with diverse roles in
various developmental processes and stress responses in plants. Creation of genome wide prediction tools
for NAC proteins will have a significant impact on gene annotation in rice. In the present study, NACSVM,
a tool for computational genome-scale prediction of NAC proteins in rice was developed integrating
compositional and evolutionary information of NAC proteins. Initially, support vector machine (SVM)-
based modules were developed using combinatorial presence of diverse protein features such as
traditional amino acid, dipeptide (i+1), tripeptide (i+2), four-parts composition and PSSM and an overall
accuracy of 79%, 93%, 93%, 79% and 100% respectively was achieved. Later, two hybrid modules were
developed based on amino acid, dipeptide and tripeptide composition, through which an overall accuracy
of 83% and 79% was achieved. NACSVM was also evaluated using position-specific iterated – basic local
alignment search tool which resulted in a lower accuracy of 50%. In order to benchmark NACSVM ,
the
tool was evaluated using independent data test and cross validation methods. The different statistical
analyses carried out revealed that the proposed algorithm is an useful tool for annotating NAC proteins in
genome of rice.
KEYWORDS
SVM, NAC, RBF, PSSM, ROC, AUC
Original Source URL : http://airccse.org/journal/ijsc/papers/4113ijsc02.pdf
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