https://journals.tultech.eu/index.php/ijitis/issue/feedInternational Journal of Innovative Technology and Interdisciplinary Sciences2024-09-27T13:18:00+02:00Mr. Alireza AldaghiAlireza.Aldaghi@tultech.euOpen Journal Systems<p>The <strong>International Journal of Innovative Technology and Interdisciplinary Sciences (IJITIS) (ISSN 2613-7305)</strong> is a reputable open-access, quarterly multidisciplinary journal that serves as a platform for the publication of reviews, regular research papers, short communications, and special issues on specific subjects, all presented in the English language. With a focus on fostering academic exchange and disseminating original research, IJITIS showcases the latest advancements and achievements in scientific research from Estonia and beyond to a global audience. Our journal welcomes original and innovative contributions across various fields of technology, innovation in the sciences, and interdisciplinary studies. We encourage submissions that provide valuable insights through analytical, computational modeling, and experimental research results. IJITIS is guided by an esteemed international board of editors comprised of distinguished local and foreign scientists and researchers. Notably, we actively seek manuscripts that introduce new research proposals and ideas, and we offer the option for authors to submit supplementary material such as electronic files or software to enhance the transparency and reproducibility of their work.</p>https://journals.tultech.eu/index.php/ijitis/article/view/177An application with meta-methods (MetaRF) based on random forest classifier2024-06-05T10:07:28+02:00Burcu Durmuşburcudrmz@windowslive.comÖznur İşçi Günerioznur.isci@mu.edu.tr<p>Meta classifiers are an area of intense study in the field of machine learning to improve classification performance. On the other hand, Random Forest is an important classifier in terms of providing fast and effective results. In this study, a meta-ensemble classifier called MetaRF based on the Random Forest basic learner is presented to use and combine the advantages of meta classifiers. For experimental results, the Random Forest base learner and eight meta-learners (AdaBoost, MultiBoostAB, Bagging, Stacking, UltraBoost, FeatureselectedClassifier, RandomSubSpace, FilteredClassifier) were used for ensemble classification on five datasets from the UCI Machine Learning Repository. Experimental results are promising in terms of accuracy rates, precision, recall and F-measure values. The method designed in the study is recommended to be used in machine learning studies and meta-classifier applications.</p>2024-09-28T00:00:00+02:00Copyright (c) 2024 Authorshttps://journals.tultech.eu/index.php/ijitis/article/view/190A Scan Line Survey for Early Detection of Landslide Potential in Hard Rock Slopes2024-07-22T22:25:37+02:00Javid Hussainjavid.bangash@mails.ucas.ac.cnXiaodong Fuxiadongfuu@whrsm.ac.cnNafees Alinafeesalii@mails.ucas.ac.cnJian Chenjianchenn@whrsm.ac.cnSayed Muhammad Iqbaliqbalkazmii35@mails.ucas.ac.cn<p>Discontinuity surveys involve collecting rock data through fieldwork and are an important characteristic of evaluating the quality of rock masses in rock engineering. The characteristics of a rock mass, such as strength, deformability, and permeability, are considerably influenced by its discontinuities. Landslides and slope collapse in hard rocks demonstrate distinct qualities in comparison with those occurring in soft geological formations. The primary purpose of the investigation is to employ a scan line survey technique to assess and estimate the frequency of landslides in the Warcha Sandstone outcrop located in Karuli Piran village, Chakwal district, Pakistan. Scan line approach and physical classification of rock types are frequently utilized to identify controlling factors. We carried out a systematic investigation of the stability of the Warcha Sandstone cliff to recognize potential failure modes. The outcomes highlight a potential risk of vertical cliff instability through toppling, with the expected failure direction identified from northeast to southwest. A comprehensive physical inspection estimate underscores the gravity of the situation, indicating that a probable landslide could lead to substantial damage and road blockage. It is recommended to promptly implement precautionary measures, such as controlled blasting to remove the high-risk toppling region or to enhance resistance to stabilize the slope.</p>2024-10-06T00:00:00+02:00Copyright (c) 2024 Authors