July 23 ~ 24, 2022, Toronto, Canada
Webpage URL: https://www.itcse2022.org/caiml/index
Submission Deadline: July 02, 2022 (Final Call)
Contact us:
Here's where you can reach us: caiml@itcse2022.org (or) caimlconf@yahoo.com
Submission URL:
https://www.itcse2022.org/submission/index.php
#softcomputing #chaostheory #bioinformatics #robotics #machinelearning #FuzzyLogic
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Website URL: https://airccse.org/journal/ijsc/ijsc.html
Submission Deadline: July 09, 2022
Contact Us: ijscjournal@yahoo.com or ijsc@aircconline.com
Paper Submission URL - http://coneco2009.com/submissions/imagination/home.html
ISSN: 2229 - 6735 [Online]; 2229 - 7103 [Print]
https://airccse.org/journal/ijsc/ijsc.html
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field
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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 |
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Rough Sets ●
Symbolic machine learning, ●
Wavelet ●
Signal or Image
Processing ●
Vision Recognition ●
Biomedical Engineering ●
Telecommunications ●
Reactive Distributed AI ●
Nano & Micro-systems ●
Data Visualization |
Paper
Submission
Authors are invited to submit papers for this journal through E-mail: ijsc@aircconline.com or through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
·
Submission Deadline : July 09, 2022
·
Notification
: August 09, 2022
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Final Manuscript Due
: August 17, 2022
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Publication Date : Determined
by the Editor-in-Chief
Here's where you can reach us: ijscjournal@yahoo.com or ijsc@aircconline.com Submission
System http://coneco2009.com/submissions/imagination/home.html
Google scholar: https://scholar.google.co.in/citations?user=4BpotHUAAAAJ&hl=en
Academia: https://independent.academia.edu/IjscJournal
Mehdi Zekriyapanah Gashti, Payame Noor University, 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: https://airccse.org/journal/ijsc/papers/3412ijsc02.pdf
https://airccse.org/journal/ijsc/current2012.html
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Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com
Submission System http://coneco2009.com/submissions/imagination/home.html
3rd International Conference on Advanced Machine Learning (AMLA 2022)
August 20 ~ 21, 2022, Chennai, India
https://csit2022.org/amla/index
Submission Deadline : June 25, 2022
Submission URL: https://csit2022.org/submission/index.php
Contact Us: Here's where you can reach us : amla@csit2022.org or amlaconf@yahoo.com
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
Website URL:
https://airccse.org/journal/ijsc/ijsc.html
Submission Deadline : June 25, 2022
Contact Us: ijscjournal@yahoo.com or ijsc@aircconline.com
Paper Submission URL - http://coneco2009.com/submissions/imagination/home.html
Wikicfp: http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=145683
Ghazali Osman1, Muhammad Suzuri Hitam2 and Mohd Nasir Ismail1, 1Universiti Teknologi MARA, Malaysia and 2Universiti Malaysia Terengganu, Malaysia
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: https://airccse.org/journal/ijsc/papers/3412ijsc01.pdf
https://airccse.org/journal/ijsc/current2012.html
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Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com
Submission System http://coneco2009.com/submissions/imagination/home.html
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
https://airccse.org/journal/ijsc/ijsc.html
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Current Issue
May 2022, Volume 13, Number 1/2
Spatio-Temporal Characterization with Wavelet Coherence: Anexus between Environment and Pandemic
Iftikhar U. Sikder1 and James J. Ribero2, 1Cleveland State University, USA, 2IBA, University of Dhaka, Bangladesh
ABSTRACT
Identifying spatio-temporal synchrony in a complex, interacting and oscillatory coupled-system is a challenge. In particular, the characterization of statistical relationships between environmental or biophysical variables with the multivariate data of pandemic is a difficult process because of the intrinsic variability and non-stationary nature of the time-series in space and time. This paper presents a methodology to address these issues by examining the bivariate relationship between Covid-19 and temperature time-series in the time-localized frequency domain by using Singular Value Decomposition (SVD) and continuous cross-wavelet analysis. First, the dominant spatio-temporal trends are derived by using the eigen decomposition of SVD. The Covid-19 incidence data and the temperature data of the corresponding period are transformed into significant eigen-state vectors for each spatial unit. The Morlet Wavelet transformation is performed to analyse and compare the frequency structure of the dominant trends derived by the SVD. The result provides cross-wavelet transform and wavelet coherence measures in the ranges of time period for the corresponding spatial units. Additionally, wavelet power spectrum and paired wavelet coherence statistics and phase difference are estimated. The result suggests statistically significant coherency at various frequencies providing insight into spatio-temporal dynamics. Moreover, it provides information about the complex conjugate dynamic relationships in terms phases and phase differences.
KEYWORDS
Wavelet analysis, Cross-wavelet power, Wavelet coherence, Covid-19, Singular Value Decomposition
Original Source URL: https://aircconline.com/ijsc/V13N2/13222ijsc01.pdf
https://airccse.org/journal/ijsc/current2022.html
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Contact Us
Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com
#softcomputing #neuralnetworks #fuzzylogic #computationalintelligence #computingtechniques
International Journal on Soft Computing ( IJSC )
ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]
https://airccse.org/journal/ijsc/ijsc.html
Contact Us
Here's where you can reach us: ijscjournal@yahoo.com or ijsc@aircconline.com
Submission Deadline : June 11, 2022
Submission System: http://coneco2009.com/submissions/imagination/home.html
Hemalatha N.1,Rajesh M. K.2 and Narayanan N. K.3,1St. Aloysius College, India, 2Central Plantation Crops Research Institute, India and 3Kannur University, 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: https://airccse.org/journal/ijsc/papers/4113ijsc02.pdf
https://airccse.org/journal/ijsc/current2013.html
International Journal on Soft Computing (IJSC) ISSN: 2229 - 6735 [Online]; 2229 - 7103 [Print] https://airccse.org/journal/ijsc/ijsc.html He...
