Turkish Journal of Computer and Mathematics Education (TURCOMAT) 2024-05-20T05:42:54+00:00 Ms Shivani Agrawal Open Journal Systems <h2 class="py-3 bg-white text-dark" style="background-color: white; padding: 10px;">Turkish Journal of Computer and Mathematics Education (TURCOMAT)</h2> <p style="background-color: white; padding: 10px;"><strong>Period</strong> Tri-annual | <strong> Starting Year: </strong> 2009 |<strong>Format:</strong> Online | <strong>Language:</strong> ENGLISH | <strong>Publisher:</strong> <a href="" target="_blank" rel="noopener"><strong>NINETY NINE PUBLICATION</strong></a></p> <div class="row"> <div class="col-md-4"><img style="background-color: white; padding: 10px; display: block; margin-left: auto; margin-right: auto;" src="" alt="" width="200" height="259" /><br /> <p style="background-color: white; padding: 10px;"><strong>Citation Analysis: </strong><br /><br /><a href=";user=mELVS0AAAAAJ&amp;view_op=list_works&amp;sortby=pubdate" target="_blank" rel="noopener"><strong>Google Scholar</strong></a><br /><strong>Citations: 18638 <br />h-index: 54<br />i10 -index: 438</strong></p> <p> </p> </div> <div class="col-md-8"> <p style="background-color: white; padding: 10px; text-align: justify;"><strong>Announcement:</strong>We are excited to announce that Turkish Journal of Computer and Mathematics Education (TURCOMAT) is now under the new management of <strong>Ninety Nine Publication</strong>, effective since November 2023. We are proud to launch our first issue with the new team, Volume 15, Issue 1, for the year 2024. This issue marks a new chapter in the journal's history and is now available on our website. For detailed information and to access the latest issue, please visit our <a href=" ">journal's website</a></p> <p style="background-color: white; padding: 10px; text-align: justify;">The Turkish Journal of Computer and Mathematics Education, known as TURCOMAT, is a globally acknowledged journal notable for its comprehensive peer-review process and open access availability. This journal publishes three issues a year, in the periods of January-April, May-August, and September-December. TURCOMAT primarily focuses on sharing scholarly research in the fields of mathematics education and computer science. For more detailed insights into its areas of interest, readers are encouraged to refer to the journal's focus and scope section.</p> </div> </div> <div class="row"> <div class="jumbotron" style="padding: 10px; margin-bottom: 5px;"> <p>Call for Papers: May-August 2024 Issue of TURCOMAT</p> <ul class="list-group"> <li class="list-group-item"> Submission Deadline: August 30, 2024</li> <li class="list-group-item">Publication Model: Continuous</li> <li class="list-group-item">Scope: Encourages exchange of ideas in mathematics and computer science, covering both theoretical and applied research.</li> <li class="list-group-item">Focus Areas: Mathematical theories, computational algorithms, data science, and their applications in various domains.</li> <li class="list-group-item">Submission Encouragement: Innovative, interdisciplinary research and comprehensive reviews contributing to mathematical and computational sciences.</li> <li class="list-group-item">Journal Characteristics: International, scholarly, refereed, and editor-organized.</li> <li class="list-group-item">TURCOMAT's Evolution: Dynamic, adapting to changes and developments in the field.</li> <li class="list-group-item">Participation Invitation: Enthusiastic call for manuscripts for future issues, highlighting enjoyment in engaging with new authors and their research.</li> </ul> <p> </p> </div> </div> DETECTION OF FRAUDULENT PHONE CALLS DETECTION IN MOBILE APPLICATIONS 2024-05-20T05:36:15+00:00 Dr K. BHARGAVI B. MITHILA SHIVANI <p><span class="fontstyle0">The primary challenge faced over the course of this decade-long endeavour is the difficulty in devising effective features without direct access to telephony network infrastructure. we conducted an extensive three-month measurement study using these call logs, which encompassed a staggering 9 billion records. Based on the insights gleaned from this study, we identified and designed 29 features that could be used by machine learning algorithms to predict malicious calls. Fraudulent phone calls or scams and spam s via telephone or mobile phone have become a common threat to individuals and organizations. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful tools in detecting and analyzing fraud or malicious calls. This paper presents an overview of AI-based fraud or spam detection and analysis techniques, along with its challenges and potential solutions. The novel fraud call detection approach is proposed that achieved high accuracy and precision. The outcomes revealed that the most effective approach could reduce unblocked malicious calls by up to 90%, while maintaining a precision rate exceeding 93.79% for benign call traffic. Moreover, our analysis demonstrated that these models could be implemented efficiently without incurring significant latency overhead.</span></p> 2024-05-20T00:00:00+00:00 Copyright (c) 2024