https://turcomat.org/index.php/turkbilmat/issue/feed Turkish Journal of Computer and Mathematics Education (TURCOMAT) 2024-09-04T09:48:42+00:00 Ms Shivani Agrawal editor@turcomat.org 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) ISSN: 3048-4855</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>ISSN</strong> <strong>:</strong> 3048-4855 | <strong>Publisher:</strong> <a href="https://nnpub.org" 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="https://turcomat.org/public/site/images/admin_turcomat/black-and-white-simple-company-cover-journal.png" alt="" width="200" height="259" /><br /> <p style="background-color: white; padding: 10px;"><strong>Citation Analysis: </strong><br /><br /><a href="https://scholar.google.co.in/citations?hl=en&amp;user=mELVS0AAAAAJ&amp;view_op=list_works&amp;sortby=pubdate" target="_blank" rel="noopener"><strong>Google Scholar</strong></a><br /><strong>Citations: 22264<br />h-index: 58<br />i10 -index: 577</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="https://turcomat.org/index.php/turkbilmat ">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: September-December 2024 Issue of TURCOMAT</p> <ul class="list-group"> <li class="list-group-item"> Submission Deadline: December 31, 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> https://turcomat.org/index.php/turkbilmat/article/view/14761 A Review on Breast Cancer Prediction Using Machine Learning and Deep Learning Techniques 2024-09-04T09:48:42+00:00 Mounika potta mounikapotta@gmail.com B. Narayanan narayanan.bk@gmail.com Kavitha Rani Balmuri phdknr1@gmail.com <p>Breast cancer is one of the most prevalent and chronic disease that affect women. To overcome this disease, effective medical treatment is required.&nbsp; Early detection of the disease plays an important role for suitable medication and survival of patient. To identify the breast cancer in the patients, standard imaging technique mammography is used. Due to the subtle and varied nature of cancer tissues interpreting mammogram images can be a challenge to doctors. Machine learning (ML) and Deep Learning (DL) techniques offer promising solutions that provide efficient breast cancer detection from mammograms. In this review paper a comprehensive review of ML and DL algorithms and their applications in mammogram image analysis are presented. Various supervised and unsupervised learning techniques, such as convolutional neural networks (CNNs), support vector machines (SVMs), random forests, and other popular ML and DL models are discussed in paper. The integration of these DL methods that are efficiently used in image preprocessing techniques, feature extraction, and classification strategies. The overall survey focusses on various performance metrics, datasets, and benchmarks used in existing studies. Further the strengths and limitations of different approaches used by various researchers are identified. By understating current research trends this paper aims to contribute to the ongoing development of more accurate and reliable breast cancer detection systems using advanced ML techniques.</p> 2024-09-04T00:00:00+00:00 Copyright (c) 2024 Mounika potta, B. Narayanan, Kavitha Rani Balmuri https://turcomat.org/index.php/turkbilmat/article/view/14722 ADVANCED AUTONOMOUS SURVEILLANCE ROBOT FOR ENHANCED MONITORING AND INDIVIDUAL IDENTIFICATION 2024-08-01T17:18:10+00:00 Moeen Ul Islam 20-41862-1@student.aiub.edu Debanjon Dutta Purkaystha 20-42375-1@student.aiub.edu Antu Das Gupta 20-42657-1@student.aiub.edu Sopan Saha 20-42450-1@student.aiub.edu Durjoy Banik muhibulhb@aiub.edu Muhibul Haque Bhuyan muhibulhb@aiub.edu <p>The primary objective is to detect and identify suspicious activities and potential threats in a precise manner while prioritizing human safety leveraging surveillance technology and machine learning. The implementation of this system involves coding in Python using the OpenCV library. It utilizes Wi-Fi connectivity as a means of communication. The robot is equipped with a Raspberry Pi along with a USB web camera, which captures video footage and employs object detection algorithms to identify unknown individuals. When a person or an object is detected, the system sends an email to the dedicated email addresses including an image of the unrecognized individual. The proposed system is designed as a unified unit responsible for monitoring the environment for hazardous conditions and delivering real-time video feedback. The proposed system is simulated and tested in real-time to observe its functionality, and it is observed that the system works properly as per given input conditions.</p> 2024-09-09T00:00:00+00:00 Copyright (c) 2024 Moeen Ul Islam, Debanjon Dutta Purkaystha,Antu Das Gupta, Sopan Saha, Durjoy Banik, Muhibul Haque Bhuyan