Fakülteler
https://hdl.handle.net/20.500.12508/16
Faculties2024-03-29T14:14:19ZA multi-objective approach to home health care routing problem with team formation
https://hdl.handle.net/20.500.12508/3049
A multi-objective approach to home health care routing problem with team formation
Bektur, Gülçin; Nenbhard, David
Home health care (HHC) services provide the elderly, disabled, and those with chronic diseases health services in their homes. The demand for HHC services has increased due to the growth of the elderly population, the increase in hospital occupancy rates during the pandemic, and developments in medical device technologies. In this study, team formation is taken into consideration in a multi-period and multi-objective HHC assignment, scheduling and routing problem. The team and the assigned patients to this team must be compatible with skill levels and operational requirements. The objective functions are minimization of total completion time and maximum working time overall caregivers. To evaluate our approach, an HHC service unit in a state hospital is adopted as the operational scenario, and we propose a multi-objective mathematical model to solve the problem. In this model, HHC teams are formed, the patients are assigned to the teams, and the route of each team is determined in an integrated manner. The variable neighborhood search algorithm is modified to solve the multi-objective optimization model and is improved with a local search algorithm. The proposed algorithm has been compared with the state-of-the-art multi-objective algorithms in the literature over test problems. Current results show that the model to be an effective means of estimating and predicting system behavior in this complex environment.
2023-01-01T00:00:00ZTrainable Self-Guided Filter for Multi-Focus Image Fusion
https://hdl.handle.net/20.500.12508/3047
Trainable Self-Guided Filter for Multi-Focus Image Fusion
Karacan, Levent
Cameras are limited in their ability to capture all-in-focus images due to their limited depth of field. This results in blurriness for objects too far in front of or behind the focused point. To overcome this limitation, multi-focus image fusion (MFIF) approaches have been proposed. Although recent MFIF methods have shown promising results for this task, they still need to be improved in terms of artifacts and color degradation. Motivated by these observations, in this paper, we propose a new Generative Adversarial Network (GAN)-based MFIF model to improve fusion quality by predicting more accurate focus maps thanks to a trainable guided filter we incorporated. The proposed model comprises an encoder-decoder network, and a trainable self-guided filtering (TSGF) module that is specifically designed to enhance spatial consistency in the predicted focus map and to eliminate the requirements of post-processing in existing GAN-based methods. The encoder-decoder network first predicts raw focus maps, which are then passed to the TSGF to produce the final focus maps. To train the proposed model effectively, we define three objectives: L1 loss, GAN loss, and Focal Frequency Loss (FFL) in the frequency domain. L1 loss is defined on ground-truth and predicted focus maps, whereas GAN loss and FFL are defined on ground-truth all-in-focus images and fused images. Experimental results show that the proposed approach outperforms the existing GAN-based methods and achieves highly competitive performance with state-of-the-art methods in terms of standard quantitative image fusion metrics and visual quality on three MFIF benchmark datasets.
2023-01-01T00:00:00ZOxidative Stress and Biochemical Alterations in Patients with Head and Multiple Organ Traumas
https://hdl.handle.net/20.500.12508/3044
Oxidative Stress and Biochemical Alterations in Patients with Head and Multiple Organ Traumas
Akyuva, Yener; Nur, Gökhan; Deveci, Hacı Ahmet; Güler, Songül Kocabaş
AIM: To evaluate paraoxonase (PON), total antioxidant status (TAS), total oxidant status (TOS), high-density lipoproteins (HDL), CRP, AST, ALT, GGT, ALP levels in patients with head and multiple organ traumas.MATERIAL and METHODS: The study included 29 male patients undergoing treatment for head and multiple organ traumas. Blood sample analysis was performed on the first, third, and seventh days after trauma.RESULTS: The mean age, duration of hospitalization in the intensive care unit, and intubation period of the study sample was 45 years (range: 9 to 81 years), 4.29 days, and 2.94 days, respectively. One patient died, and 13 underwent surgical intervention. Comparison of PON, TAS, TOS, and CRP levels showed statistically significant differences between the first day and the third and seventh days, although no such differences were seen in HDL levels. A moderately positive correlation was observed between CRP/ AST, CRP/ALT and CRP/GGT, while a moderately negative correlation was seen between CRP/ALP.CONCLUSION: The findings of this study suggest that some oxidative parameters may play a significant role in the prognosis and follow-up of intensive care patients. Moreover, biochemical markers can provide important information about patient response to trauma.
2023-01-01T00:00:00ZComparative Economic Assessment of On-Grid Solar Power System Applications Having Limited Areas: A Case Study on a Shore Facility
https://hdl.handle.net/20.500.12508/3043
Comparative Economic Assessment of On-Grid Solar Power System Applications Having Limited Areas: A Case Study on a Shore Facility
Gülmez, Yiğit; Konur, Olgun; Yüksel, Onur; Korkmaz, Süleyman Aykut
The objective of this study is to assess the economic feasibility of installing high-efficiency solar panels in a yacht marina in the cesme district of Izmir, Turkiye. In this aim, the facility's energy demand from the grid is reduced. The study compares ten different PV panel modules with various installation configurations, including fixed, horizontal, vertical, and two-axis. The most cost-effective option is determined with novel comparative economic indicators involving the costs associated with purchasing electricity from the grid. The PVGIS online tool is used to simulate energy production from solar panel systems and determine the ideal quantity of solar panels that can be deployed within the designated regions. New economic indicators, Relative Levelized Energy Cost (RLEC), and Relative Payback Period (RPBP) are proposed in the study to compare the economic performance of the different solar panel sets. The results indicate that the facility can compensate for 14.44% of its energy demand with the two-axis configuration. Module 5 yielded the best relative economic performance with an RLEC of 0.090 $/kWh. The best Payback Period (PBP) is obtained from fixed module 7, while the best RPBP is achieved with fixed module 5 at 7.113 years, which shows the importance of using comparative economic indicators for suitable energy systems.
2023-01-01T00:00:00Z