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Predicting student attrition is an intriguing yet challenging problem for any academic institution. Classimbalanced data is a common in the field of student retention, mainly because a lot of students register but fewer students drop out. Classification techniques for imbalanced dataset can yield deceivingly high prediction accuracy where the overall(More)
In this paper, we apply the Augmented-neural-networks (AugNN) approach for solving the classical bin-packing problem (BPP). AugNN is a meta-heuristic that combines a priorityrule heuristic with the iterative learning approach of neural networks, to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also(More)
In the recent past, there have been several initiatives by major network providers such as Turk Telekom lead the industry towards network capacity distribution in Turkey. In this study, we use a monopoly pricing model to examine the optimal pricing strategies for “payper-volume” and “pay-per-time” based leasing of data networks. Traditionally, network(More)
Treatment of patients with metastatic breast cancer is one of the most difficult problems of clinical oncology. Chemotherapy is one of the main methods of treatment of patients with metastatic breast cancer. Long experience of the world's cancer centers, advances in clinical oncology recent decades, the synthesis of anticancer drugs with new mechanisms of(More)
Information Technologies (IT) and business processes should be considered together to get the best results in business life. Therefore their integration and reflections on each other are very important in managing institutional changes due to changes in the IT world. Change is a very sensitive concept that must be managed very carefully. In this article, a(More)