This repository contains a sequence of 5 CPUs' Logisim designs. The designs are taught in the course CSE4117 at Marmara University. The Lecture notes can be found here. You may find this repo helpful if you are taking the course or if you are just learning Logisim.
Term Projects for Operating Systems Course coded using C and Shell in a Linux environment using Docker
Marmara University 3rd year course
PySpark/AI computational framework for 'AI and Big Data Analytics for Seismic Hazard Assessment: Marmara Region, Türkiye' (Lemenkova & Zülfikar, Data 2026, 11(6):131): distributed seismic waveform processing, STA/LTA detection, PhaseNet phase picking, magnitude estimation, EEW streaming and Gutenberg-Richter analysis.
Reproducible Python pipeline for multi-hazard (earthquake, tsunami, wind) risk assessment of the Marmara basin and Istanbul — generates the study's geospatial figures from open datasets.
Scripts and data for "Soil amplification and earthquake-induced collapse potential in Istanbul: A physics-guided machine-learning framework with physically interpretable features for Marmara basin effects and structural vulnerability". Lemenkova & Zülfikar, Geohazards & Remediation, 2026.
Reproducible R & Python workflow for fractal analysis of seismicity: box-counting (D0) and correlation (D2) dimensions, fault-network dimension, and maximum-likelihood Gutenberg–Richter b-value, with Mc selection and Gardner–Knopoff declustering. Case study: Marmara region, North Anatolian Fault Zone.
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