62 citations · 85 across the 17 of their papers we have counts for
19 papers
Assessing the impact of emergency department short stay units using length-of-stay prediction and discrete event simulation
Mucahit Cevik, Can Kavaklioglu, Fahad Razak +2
Accurately predicting hospital length-of-stay at the time a patient is admitted to hospital may help guide clinical decision making and resource allocation. In this study we aim to…
Prediction of the 2023 Turkish Presidential Election Results Using Social Media Data
Aysun Bozanta, Fuad Bayrak, Ayse Basar
Social media platforms influence the way political campaigns are run and therefore they have become an increasingly important tool for politicians to directly interact with citizen…
Data Augmentation for Conflict and Duplicate Detection in Software Engineering Sentence Pairs
Garima Malik, Mucahit Cevik, Ayşe Başar
This paper explores the use of text data augmentation techniques to enhance conflict and duplicate detection in software engineering tasks through sentence pair classification. The…
Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning
Davood Pirayesh Neghab, Mucahit Cevik, M. I. M. Wahab
The complexity and ambiguity of financial and economic systems, along with frequent changes in the economic environment, have made it difficult to make precise predictions that are…
Adaptive Fine-tuning for Multiclass Classification over Software Requirement Data
Savas Yildirim, Mucahit Cevik, Devang Parikh +1
The analysis of software requirement specifications (SRS) using Natural Language Processing (NLP) methods has been an important study area in the software engineering field in rece…
ADPTriage: Approximate Dynamic Programming for Bug Triage
Hadi Jahanshahi, Mucahit Cevik, Kianoush Mousavi +1
Bug triaging is a critical task in any software development project. It entails triagers going over a list of open bugs, deciding whether each is required to be addressed, and, if…
Interpretable Time Series Clustering Using Local Explanations
Ozan Ozyegen, Nicholas Prayogo, Mucahit Cevik +1
This study focuses on exploring the use of local interpretability methods for explaining time series clustering models. Many of the state-of-the-art clustering models are not direc…
Improved -GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning
Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar
Generative Adversarial Networks (GANs) have gained significant attention in several computer vision tasks for generating high-quality synthetic data. Various medical applications i…
Supervised Semantic Similarity-based Conflict Detection Algorithm: S3CDA
Garima Malik, Mucahit Cevik, Ayse Basar +1
Identifying conflicting requirements is a key challenge in software requirement engineering, often overlooked in automated solutions. Most existing approaches rely on handcrafted r…
Time Series Clustering for Grouping Products Based on Price and Sales Patterns
Aysun Bozanta, Sean Berry, Mucahit Cevik +4
Developing technology and changing lifestyles have made online grocery delivery applications an indispensable part of urban life. Since the beginning of the COVID-19 pandemic, the…
VARGAN: Variance Enforcing Network Enhanced GAN
Sanaz Mohammadjafari, Mucahit Cevik, Ayse Basar
Generative adversarial networks (GANs) are one of the most widely used generative models. GANs can learn complex multi-modal distributions, and generate real-like samples. Despite…
Text Classification for Predicting Multi-level Product Categories
Hadi Jahanshahi, Ozan Ozyegen, Mucahit Cevik +4
In an online shopping platform, a detailed classification of the products facilitates user navigation. It also helps online retailers keep track of the price fluctuations in a cert…
DABT: A Dependency-aware Bug Triaging Method
Hadi Jahanshahi, Kritika Chhabra, Mucahit Cevik +1
In software engineering practice, fixing a bug promptly reduces the associated costs. On the other hand, the manual bug fixing process can be time-consuming, cumbersome, and error-…
Predicting the Number of Reported Bugs in a Software Repository
Hadi Jahanshahi, Mucahit Cevik, Ayşe Başar
The bug growth pattern prediction is a complicated, unrelieved task, which needs considerable attention. Advance knowledge of the likely number of bugs discovered in the software s…
A Deep Reinforcement Learning Approach for the Meal Delivery Problem
Hadi Jahanshahi, Aysun Bozanta, Mucahit Cevik +5
We consider a meal delivery service fulfilling dynamic customer requests given a set of couriers over the course of a day. A courier's duty is to pick-up an order from a restaurant…
Does chronology matter in JIT defect prediction? A Partial Replication Study
Hadi Jahanshahi, Dhanya Jothimani, Ayşe Başar +1
Just-In-Time (JIT) models detect the fix-inducing changes (or defect-inducing changes). These models are designed based on the assumption that past code change properties are simil…
Moving from Cross-Project Defect Prediction to Heterogeneous Defect Prediction: A Partial Replication Study
Hadi Jahanshahi, Mucahit Cevik, Ayşe Başar
Software defect prediction heavily relies on the metrics collected from software projects. Earlier studies often used machine learning techniques to build, validate, and improve bu…
Wayback Machine: A tool to capture the evolutionary behaviour of the bug reports and their triage process in open-source software systems
Hadi Jahanshahi, Mucahit Cevik, José Navas-Sú +2
The issue tracking system (ITS) is a rich data source for data-driven decision-making. Different characteristics of bugs, such as severity, priority, and time to fix, provide a cle…
An empirical study on using CNNs for fast radio signal prediction
Ozan Ozyegen, Sanaz Mohammadjafari, Karim El mokhtari +3
Accurate radio frequency power prediction in a geographic region is a computationally expensive part of finding the optimal transmitter location using a ray tracing software. We em…