KOSE Erkan

Makale/Derleme | 2023 | Operations Research and Decisions Vol. 33, No. 4 (2023) DOI: 10.37190/ord230407. 33 ( 4 ) , pp.119 - 131

Abstract The impact of COVID-19 on the transportation costs of a large-scale company has been examined. Before the pandemic, shift personnel were transported to the factory by shuttles, and after a quick shift change, other shift personnel were transported back to their homes. However, with the implementation of laws mandating the reduction of shuttle seat capacities, transportation costs have risen significantly. To address this issue, a new simultaneous pickup and delivery model is proposed as an alternative to the separate transportation of shift workers. The results of this study indicate that the proposed model provides a subst . . .antial advantage in terms of both the number of vehicles used and the total distance traveled, leading to a significant reduction in costs. This research underscores the importance of effective operations research practices for the profitability of companies, particularly in extraordinary circumstances such as the COVID-19 pandemic Daha fazlası Daha az

Erkan KÖSE

Bildiri | 2023 | 42. Yöneylem Araştırması ve Endüstri Mühendisliği Ulusal Kongresi , pp.90 - 90

Artan yakıt fiyatları i¸sletmeler i¸cin personel ta¸sıma maliyetlerini ¨onemli sorunlardan birisi haline getirmi¸stir. Bu maliyetlerin d¨u¸s¨ur¨ulmesi ve kaybedilen s¨urelerin en aza indirilmesi gerekmektedir. Bu ¸calı¸smada, Kayseri’de faaliyet g¨osteren orta ¨ol¸cekli bir firmada, personel servisleri i¸cin optimal rotalar belirlenmeye ¸calı¸sılmı¸stır. Mevcut durumda firma iki vardiya halinde ¸calı¸smaktadır. Gece ve g¨und¨uz vardiyasında ¸calı¸sanlar i¸cin servis planlaması ayrı-ayrı yapılmaktadır. G¨und¨uz vardiyasında ¸calı¸sanlar i¸sletmeye ta¸sınmakta, onlar i¸si devraldıktan sonra gece vardiyasında ¸calı¸sanlar evlerine ta¸s . . .ınmaktadır. Bu durum personel servislerinin kat ettikleri toplam mesafeyi dolayısı ile de ula¸sım maliyetlerini arttırmaktadır. Ula¸stırma maliyetlerini azaltabilmek amacıyla fabrikada i¸sleri kesintisiz olarak y¨ur¨utebilmek i¸cin asgari sayıda personelin i¸slere atanması, geri kalan personelin e¸s zamanlı olarak toplanıp-da˘gıtılması amacıyla yeni bir matematiksel model ¨onerilmi¸stir. Matematiksel model ilk ¨once fabrikada faaliyetleri y¨ur¨utecek asgari sayıda personel atamasını yapmakta daha sonra geri kalan personelin e¸s zamanlı olarak toplanıp da˘gıtıldı˘gı optimal rotayı belirlemektedir. Elde edilen sonu¸clar ¨onerilen matematiksel modelin faaliyetlerin kesintisiz y¨ur¨ut¨ulmesinde herhangi bir aksaklı˘ga sebep olmaksızın ula¸stırma maliyetlerinde ¨onemli ¨ol¸c¨ude tasarruf sa˘glanabilece˘gini g¨ostermi¸stir Daha fazlası Daha az

Zeki ORALHAN | Burcu ORALHAN

Bildiri | 2023 | 3rd International Conference on Design, Research and Development , pp.39 - 39

Sports has emerged as one of the world's major industries. Thus, athlete health is one of the most critical elements influencing the sector's profits and losses. When potential injuries or poor performance are expected, the risks can be reduced by assessing the players' physical health state and performance. Although traditional methods can only provide limited forecasts, machine learning approaches will allow us to take steps to improve athlete performance and avoid potential injury concerns. In this work, modeling was used to forecast athlete injury and poor performance risks using a rule-based expert system technique. The propose . . .d method has been implemented into software. With the model fed on the athletes' simultaneous data, it was able to take immediate action in the event of an injury or poor performance. This reduces the existing hazards for the invested sportsmen and allows them to perform better. In the study, the fuzzy logic approach was used for modeling, and an accuracy rate of 75.2% was obtained Daha fazlası Daha az

Beril DEMİRCAN

Makale/Derleme | 2023 | BMC Oral Health23 , pp.1 - 9

Aim This study aimed to evaluate the stress distribution caused by secondary trauma forces after regenerative endodontic treatment (RET) using different thicknesses of coronary barrier material with three-dimensional finite element analysis(FEA). Method A control model was created using the tomography image of the immature maxillary central tooth with computer software.Study models were created with the modulus of elasticity and Poisson’s ratio of the materials used in RET.Enamel, dentin, cementum, periodontal ligament, cortical, and cancellous bone were modeled. Coronary barrier materials were applied in 3 mm and 5 mm thicknesses ( . . .Model 1: control model, model 2:3 mm/Calcium Enriched Mixture(CEM), model 3:3 mm/Mineral Trioxide Aggregate(MTA), model 4:3 mm/Biodentin, model 5:5 mm/CEM, model 6:5 mm/MTA, model 7:5 mm/Biodentin). For the trauma force simulation, 300 N force in the horizontal direction was applied to the buccal surface of the tooth in the first scenario. For the second scenario, maximum bite force simulation, a force of 240 N in the oblique direction was applied to the palatal surface of the tooth. FEA was performed with Algor Fempro. The resulting stresses were recorded as Von Mises, maximum, and minimum principal stresses. Results Lower stress values were obtained in 5 mm models compared to 3 mm models. However, the difference between them was insignificant. Lower stress values were obtained in all RET models compared to the control model. The lowest stress values in dental tissues and bone tissue were obtained in the CEM models. Conclusion This is the first study in which the stress caused by different thicknesses of CEM on dental tissues was evaluated with FEA. RET strengthens immature teeth biomechanically. CEM and Biodentin are more successful materials in stress distribution than MTA. Considering the cost of treatment, 3 mm material thickness is ideal for RET since there is no significant difference between the stress values resulting from the use of 5 mm and 3 mm coronary barrier material Daha fazlası Daha az

Zeki ORALHAN | Burcu ORALHAN

Bildiri | 2023 | 3 rd International Conference on Design, Research and Development , pp.37 - 37

The paper presents a deep learning model for improving customer loyalty management in the business-to-business (B2B) field. In industries where technology is continuously evolving and competition is fierce, it is critical to maintain client loyalty and improve customer satisfaction. To generate a competitive advantage, the project aims to construct a deep learning-supported model to meet these objectives. The research is covered methodologies involving artificial intelligence algorithms such as deep learning to analyze customer behavior and preferences. Customer data was obtained from ERP systems. Afterwards, deep learning models CN . . .N, RNN and LSTM architectures were applied for modelling. The developed B2B-DL model has achieved high success in predicting customer behavior and offering customized offers. Improvements in customer loyalty management will bring great benefits to companies by causing customer satisfaction rates to increase significantly and customer loss to be reduced. Therefore, the study is showed that the use of deep learning methods in the B2B industry can play an important role in customer loyalty management. In the study, LSTM architecure was achieved the best performance with the accurate valuse as %8 Daha fazlası Daha az