62 citations · 107 across the 26 of their papers we have counts for
8 papers · 1 filter
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…
Few-shot learning for sentence pair classification and its applications in software engineering
Robert Kraig Helmeczi, Mucahit Cevik, Savas Yıldırım
Few-shot learning-the ability to train models with access to limited data-has become increasingly popular in the natural language processing (NLP) domain, as large language models…
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…
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting
Ozan Ozyegen, Juyoung Wang, Mucahit Cevik
Despite the high performance of neural network-based time series forecasting methods, the inherent challenge in explaining their predictions has limited their applicability in cert…
A Concurrent CNN-RNN Approach for Multi-Step Wind Power Forecasting
Syed Kazmi, Berk Gorgulu, Mucahit Cevik +1
Wind power forecasting helps with the planning for the power systems by contributing to having a higher level of certainty in decision-making. Due to the randomness inherent to met…
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…
Transfer learning for conflict and duplicate detection in software requirement pairs
Garima Malik, Savas Yildirim, Mucahit Cevik
Consistent and holistic expression of software requirements is important for the success of software projects. In this study, we aim to enhance the efficiency of the software devel…