Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
Browse
3 results
Search Results
Article Improving Last-Mile Delivery in Humanitarian Logistics by Solving a Two-Echelon Routing Problem with Portering and Infrastructure Disruptions(Springer India, 2026) Mutlu, Ismail Nurullah; Togrul, Ergul Kisa; Kazanc, H. Cansin Uzgoren; Kilic, Kaan; Soysal, Mehmet; Uzgören Kazanç, H. Cansın; Kısa Toğrul, ErgülOver time, catastrophes have increasingly caused significant material and human losses. Effective logistics management in humanitarian aid is crucial to minimizing these impacts. Infrastructure damage from disasters introduces uncertainties that must be considered when routing trucks for relief item delivery. This study proposes a Mixed Integer Programming model for the Two-Echelon Vehicle Routing Problem in Humanitarian Aid Logistics (2E-VRP-HAL) to minimize total travel time. An earthquake scenario in Kartal, Istanbul is used to demonstrate the model's accuracy and applicability while accounting for road closures. A diverse fleet, including trucks and pedestrians, addresses delivery challenges, with handover stations enabling access to unreachable areas. To address larger problem instances, a set partitioning approach is used to cluster demand points, followed by a MIP-based local search heuristic to refine the results. Numerical analysis shows up to 15.83% improvement in medium-sized instances and feasible results for larger cases where the model struggles. These findings highlight the potential of proposed decision support methods.Article Citation - Scopus: 1Randomised Comparison Between Navigation and Non-Navigation Camera Control Performance in a Surgical Simulation Task Using a Haptic Device Interface(Wolters Kluwer Medknow Publications, 2026) Cagiltay, Nergiz Ercil; Topalli, Damla; Tuner, Emre; Berker, MustafaIntroduction:Navigation skills for controlling the camera in the surgical field are critical for many minimally invasive surgery (MIS) procedures. Currently, endoscopes lack integrated navigation aids, making camera control a challenging task. This experimental study aims to investigate the effect of navigation guidance on the performance of beginners.Patients and Methods:A custom computer-based simulation environment was developed for this study, featuring two conditions - one with navigation guidance and one without - focussed on a camera-cleaning task. Participants (64 beginners) were randomly assigned to one of these groups and used two haptic devices to simulate the endoscope and surgical tools.Results:Participants in the guided condition performed significantly better than those in the unguided condition. Notably, female participants completed the task in significantly less time under the guided condition compared to the unguided one.Conclusion:These findings suggest that incorporating navigation aids into endoscope interfaces could improve user performance, especially for beginners. Medical device manufacturers should consider adding navigation features to enhance usability. In addition, simulation-based instructional systems should integrate navigation aids to better support surgical training.Article Citation - WoS: 1Citation - Scopus: 3Improving the Performance of a Mems-Imu System Based on a False State-Space Model by Using a Fading Factor Adaptive Kalman Filter(Sage Publications Ltd, 2024) Akbas, Eren Mehmet; Cifdaloz, Oguzhan; Ucuncu, MuratIn this study, we introduce a novel algorithm, the low error rate adaptive fading Kalman filter (LERAFKF), designed to predict system states in the presence of uncertainty in both the system matrix and the model. The purpose of developing the LERAFKF is to address challenges arising from measurement difficulties, system parameter uncertainties, and state-space model inaccuracies. Several studies have utilized the Kalman filter (KF) and extended Kalman filter (EKF) algorithms to handle uncertainties in system parameters, corrupted measurements with unknown covariances, and incorrectly defined system modeling. Our work distinguishes itself by proposing a new approach that achieves lower error and deviation rates by combining the current Kalman estimation algorithm and the fading factor adaptive filter. To achieve this goal, we transformed the KF into an adaptive KF by introducing a forgetting factor, and the algorithm was subsequently reconfigured to calculate an optimized forgetting factor. In this study, we conducted simulations and measurements using both linear and nonlinear systems. The linear system represents the motion of an object, and the simulation involved measurements from the inertial navigation system (INS) sensor, specifically the Pololu IMU01b three-axis inertial measurement unit (IMU) sensor. We employed the SDI33 system with 9 degrees of freedom (DoF) mounted on a three-axis rotary table for the nonlinear system. This system simulates a missile as a 4th-order nonlinear system. Our findings demonstrate that the proposed LERAFKF filter outperforms KF and EKF in estimating system states, particularly in measurement-related error scenarios. Mean square error analysis further confirmed that LERAFKF exhibited the lowest error values, showcasing superior performance over KF and EKF in linear and nonlinear systems.