International Journal of Engineering Maths and Computer Science <h2 class="contentheading">Call for Papers 2017</h2><h2 style="text-align: justify;"><img style="float: left; padding: 0px 10px 0px 0px;" src="" alt="" width="167" height="200" border="0" /></h2><h2 style="text-align: justify;">Submission open for 2017</h2><p style="text-align: justify;"><strong><span style="line-height: 15.808px;"><br /></span></strong></p><p style="text-align: justify;"><strong>Acceptance Notification</strong> : within 3-4 days after submission</p><p style="text-align: justify;"><strong>Publication (Online) : </strong>within 1-2 days after Payment Approval</p><p style="text-align: justify;"><strong>Issue online :</strong> Monthly</p><p style="text-align: justify;"><span style="line-height: 1.3em;">Authors are invited to submit papers for the upcoming Issue<strong> </strong></span><strong>2017</strong><span style="line-height: 1.3em;">.</span></p><p style="text-align: justify;"><strong>The manuscript/ paper can be submitted online via Online Submission system</strong></p><p style="text-align: justify;"><strong><a title="Online Submission" href="/index.php/ijemcs/about/submissions#onlineSubmissions">online Submission</a></strong></p><h2 style="text-align: justify;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 1em; line-height: 1.3em;">or by directly</span> Email: <strong></strong></h2><p><strong>International Journal of Engineering Mathematics and Computer Sciences </strong>aims to publish high-quality <span class="il">papers</span> with a specific focus on teaching and learning within the Engineering, Mathematics and Computer Sciences discipline that are accessible and of interest to educators, researchers, and practitioners alike.</p><p>Depending on their special interests, those working in the field may draw on subject areas as diverse as statistics, educational theory and the cognitive sciences in addition to technical computing knowledge.</p><p><span class="il">Papers</span> may present work at different scales, from classroom-based empirical studies through evaluative comparisons of pedagogic approaches across institutions or countries and of different types from the practical to the theoretical.</p><p>The journal is not dedicated to any single research orientation. Studies based on qualitative data, such as case studies, historical analysis and theoretical, analytical or philosophical material, are equally highly regarded as studies based on quantitative data and experimental methods.</p><p>It is expected that all <span class="il">papers</span> should inform the reader of the methods and goals of the research; present and contextualize results, and draw clear conclusions.</p><p>Areas and subareas of interest include (but are not limited to):</p><p><em>Electrical, Telecommunication , Mechanical , Electromechanical System , Chemical , Agricultural Biological &amp; Biosystem, Environmental , Forestry, Materials, Water Resource, Mineral &amp; Metallurgical, Civil, Architecture &amp; Planning, Natural Sciences, Aerospace, Automotive, Naval Architectural, Biomechanical &amp; Biomedical, Geotechnical, Petroleum,<br /> Maths, Physics, Integrated, Aeronautical , Marine, Model, Nuclear, Ocean, Sound, Structural, advanced Mathematics, Pure Mathematics, Applied Mathematics, Methodology, Mathematical statement, General concepts, Mathematical objects, Equations named after people, about Mathematics, Statistics, Bio Statistics, Mathematical Economics, Financial Mathematics</em><em>…………………..and many more.</em></p><p><strong>Benefits to Authors:</strong></p><p style="line-height: 15.8079996109009px;"> </p><ul style="text-align: justify;"><li><span style="line-height: 1.3em;">Easy &amp; Rapid <span class="il">Paper</span> publication Process <br /></span></li><li><span style="line-height: 1.3em;">journal provides one <strong>"Hard copy of full <span class="il">Paper</span>" </strong>to Author and provides individual<strong> Soft Copy of " Publication <span style="line-height: 1.3em;"><strong>Certificate </strong></span>" to each Authors</strong> of <span class="il">paper</span>.</span></li><li><span style="line-height: 1.3em;"><strong>Full Color soft Copy of <span class="il">paper</span></strong> with Journal Cover Pages <span class="il">for</span> Printing</span></li><li><span style="line-height: 1.3em;">Open Access Journal Database </span><span style="line-height: 1.3em;"><span class="il">for</span></span><span style="line-height: 1.3em;"> High visibility and promotion of your research work.<br /></span></li><li><span style="line-height: 1.3em;">Inclusion in all Major Bibliographic open Journal Databases <br /></span></li></ul><p> </p><p><strong>Thanks &amp; Regards, </strong></p><p><strong>Editor in chief</strong></p><p><strong>Dr S Gandhi,</strong></p><p>Website: <a href="" target="_blank">Ijemcs | Innovative Journal</a></p> en-US International Journal of Engineering Maths and Computer Science Optimum Executive Body Has 5 Members Simple Mathematical Proof <p><strong>Abstract:  Mathematical proof:  Optimum executive body has 5 members.</strong></p><p>        Key Words: Executive body, optimization, mathematical proof, combinatorics</p> Vladimír Vrecion ##submission.copyrightStatement## 2017-04-22 2017-04-22 5 3 10.15520/.2017.vol5.iss3.21 ESTIMATION OF AUC AND ITS SIGNIFICANCE IN THE ASSESSMENT OF CLASSIFICATION MODELS <p>The performance of a diagnostic test when test results are measured on a binary or ordinal scale can be evaluated using the measures of sensitivity and specificity. In particular, when it is measured on a continuous scale, the assessment of the performance of a diagnostic test is always over the range of possible cut-off points for the predictor variable. This is achieved by the use of a receiver operating characteristic (ROC) curve which is a graph of sensitivity against 1-specificity across all possible decision cut-offs values from a diagnostic test result. This curve evaluates the diagnostic ability of tests to discriminate the true state of subjects especially in classification models. These tasks of assessing the predictive accuracy of classification models is always better achieved using a summary measure of accuracy across all possible ranges of cut-off values called the area under the receiver operating characteristic curve (AUC). In this paper, we propose a simple nonparametric method of calculating AUC from predicted probability of positive response to a condition which involves multiple prediction rules. This method is based on the non-parametric Mann-Whitney U statistic. The estimation methods for AUC and their significance was assessed using some classification models. The proposed method when applied on real data and compared with other existing methods of calculating AUC was shown to be better in assessing classification models. The method offers reliable statistical inferences and circumvents the difficulties of deriving the statistical moments of complex summary statistics seen in the parametric method. The proposed method as a non-parametric estimation is recommended for calculating the AUC.    </p> Okeh U.M ##submission.copyrightStatement## 2017-04-22 2017-04-22 5 3 10.15520/.2017.vol5.iss3.27