Psychology and Education Journal <h2><strong>PSYCHOLOGY AND EDUCATION (ISSN: 1553-6939)<br /></strong></h2> <div class="row" style="border: 1px solid grey; padding: 5px; text-align: justify;">Dear Authors and Researchers,<br />We would like to inform you that the U.S. ISSN Center at the Library of Congress has confirmed that the correct ISSN number of the Journal <strong>Psychology and Education</strong> is ISSN 1553-6939. This ISSN is to be used instead of ISSN 0033-3077 which is the ISSN that belongs to the former title, “<strong>Psychology</strong>.” Each time a journal undergoes a major change of title a new ISSN is assigned. <strong>Psychology and Education</strong> also has been assigned a Linking ISSN (ISSN-L). The ISSN-L is available for use when there is a need to identify and link to a continuing resource without regard to format, for example in services such as OpenURL, library catalogues, search engines or knowledge bases. The next issue of <strong>Psychology and Education</strong> will be published with ISSN 1553-6969. But the previous ISSN will be also available in the ISSN Portal to retrieve the record for <strong>Psychology</strong> because it remains the identifier for the former title <strong>Psychology</strong> and the articles published under that title.</div> <div class="row"> <p style="text-align: justify;"> </p> <p style="text-align: justify;"><strong>Psychology and Education</strong> <strong>(ISSN: 1553-6939)</strong> is a quality journal devoted to basic research, theory, and techniques and arts of practice in the general field of psychology and education. <strong>Psychology and Education</strong> is published bimonthly. There are numerous papers on important aspects of psychology and education which can find no place in the professional literature. This journal is dedicated to filling this void.<br />Preparation of manuscripts: In formal aspects, the manuscripts should follow closely the general directions given in the Publication Manual of the American Psychological Association (6th Edition). EXCEPTIONS: All data in photographs, tables, drawings, figures and graphs must be simplified and stated in the RESULTS section of the paper. All papers must be formatted in MSWord, typed, Times New Roman font #12, double-spaced, with 1 inch margins, and submitted electronically or printed manuscript in original copy. Manuscripts must be accompanied by an abstract of about 70-100 words. The manuscript and abstract should conform to the American Psychological Association Manual Style, 6th Edition.<br />Given the present trends in the publishing industry and to reach the global audience without any restrictions, we have opted to move the journal from subscription-based to Gold open access.<br />A shift in this mode has certain benefits:</p> <ul> <li>Increased usage and citation</li> <li>Easy compliance with institutional and funder mandates</li> <li>Retention of copyright by authors</li> <li>Greater public engagement</li> <li>Faster impact</li> </ul> <p style="text-align: justify;"><strong>Psychology and Education</strong>, the Editor, nor the Board of Editors (individually or collectively), assumes no responsibility for statements of fact or opinion in the papers printed. Authors are responsible for obtaining copyright permissions. Advertising rates supplied on request. Books for review should be sent to the Editor.<br />Articles in <strong>Psychology and Education</strong> are listed in PsycINFO, American Psychological Association (APA), Scopus,, and shared with other websites, and numerous gratis copies are mailed to the Library of Congress, EBSCO subscription services, and universities in developing countries overseas.</p> </div> en-US Wed, 15 Sep 2021 04:55:51 +0000 OJS 60 A New Methodology for Noise Removal and Segmentation in Microarray Images <p>Microarray technology allows the simultaneous monitoring of thousands of genes in parallel. Based on the gene expression measurements, microarray technology have proven powerful in gene expression profiling for discovering new types of diseases and for predicting the type of a disease. Enhancement, Gridding, Segmentation and Intensity extraction are important steps in microarray image analysis. This paper presents a noise removal method in microarray images based on Bi-dimensional Variational Mode Decomposition (BVMD). VMD is a signal processing method which decomposes any input signal into discrete number of sub-signals (called Variational Mode Functions) with each mode chosen to be its band width in spectral domain. First the noisy image is processed using BVMD to produce BVMFs. Then Discrete Wavelet Transform (DWT) thresholding technique is applied to each BVMF for denoising. The denoised microarray image is reconstructed by the summation of BVMFs. The filtered image is segmented using fuzzy local information c- means clustering algorithm. This method is named as BVMD and DWT thresholding method. The proposed method is compared with DWT thresholding and BEMD and DWT thresholding methods. The qualitative and quantitative analysis shows that BVMD and DWT thresholding method produces better noise removal than other two methods and produces better segmentation quality.</p> Vinta Surendra reddy, Dr. Mohini Prashar Copyright (c) 2021 Wed, 15 Sep 2021 00:00:00 +0000