http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/15591 2026-04-23T06:58:42Z 2026-04-23T06:58:42Z Caner, Mustafa Buyruk, Ertan http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/16602 2026-02-02T11:47:21Z 2025-01-01T00:00:00Z

EXPERIMENTAL INVESTIGATION OF THE PERFORMANCE OF A SHELL AND TUBE HEAT EXCHANGER WITH HELICALLY COILED CORRUGATED TUBE Caner, Mustafa; Buyruk, Ertan The study involved a series of experiments to examine the heat transfer behaviour of shell-and-tube heat exchangers with a helically coiled corrugated tube. Experimental investigations were conducted to analyse the performance of the heat exchangers, with a focus on the impact of tube- and shell-side flow rates, as well as shell inlet temperature, on effectiveness. Throughout the experiments, the tube inlet water temperature was kept at 20 °C, whereas the shell inlet temperature was set to 50, 60 or 70 °C. The tube flow rate was set to 1, 2 or 3 L/min, while the shell flow rate was set to 2, 3 or 4 L/min. A total of 27 tests were performed with these combinations. The results show that effectiveness increases significantly with an increase in the shell side flow rate and hot inlet water temperature, whereas an increase in the tube side flow rate reduces effectiveness. The highest effectiveness value (ε = 0.603) was obtained at a shell side flow rate of 4 L/min, a tube side flow rate of 1 L/min and a shell side inlet temperature of 70 °C. The maximum heat transfer was measured as 3290 W at an inlet temperature of 70 °C and a flow rate of 4 L/min on the shell side and 3 L/min on the tube side. The experimental data obtained provide a reliable basis for validating numerical models and designing highly efficient, compact heat exchangers.

2025-01-01T00:00:00Z Bıyık, Hilal Kaya, Duygu Akbal, Ayhan http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/16601 2026-02-02T11:31:49Z 2025-01-01T00:00:00Z

AUTOMATIC DIAGNOSIS OF SKIN DISEASES WITH CONVOLUTIONAL NEURAL NETWORKS ON MULTI-CLASS VISUAL DATA Bıyık, Hilal; Kaya, Duygu; Akbal, Ayhan The automatic diagnosis of skin diseases is of great importance, especially in cases requiring early detection, as it accelerates clinical processes and reduces the margin of error. In this study, a classification model based on Convolutional Neural Network (CNN) architectures was developed on a multi-class visual dataset containing three different skin disease categories. To enhance the model’s performance, data augmentation techniques were applied, and the images were resized to 224×224 pixels. Using a transfer learning approach, the model was trained with preprocessing ResNet-18, AlexNet, DenseNet-201 architectures. The hyperparameters used during the training process were carefully selected, and the model's training and validation accuracies were monitored. According to the results obtained, the ResNet-18 model demonstrated strong performance with an accuracy of 87.19% on the test set. These findings indicate that deep learning-based architectures can be effectively applied in the multi-class diagnosis of skin diseases.

2025-01-01T00:00:00Z Kaya, Mustafa Fırat, Mehmet Çelikezen, Fatih Çağlar http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/16600 2026-02-02T11:25:23Z 2025-01-01T00:00:00Z

PHYTOCHEMICAL PROFILING AND IN VITRO ANTI-SARS-COV-2 EVALUATION OF VERBASCUM ZERDUST: INTEGRATION OF ACE2-SPIKE INHIBITION ASSAY AND COMPUTATIONAL APPROACHES Kaya, Mustafa; Fırat, Mehmet; Çelikezen, Fatih Çağlar Plants have long been used to protect and maintain human health. Due to the increasing costs and side effects of synthetic drugs, interest in herbal products is increasing day by day. For this reason, research continues in laboratories around the world to discover new drug active ingredients of natural origin. In the present study, the COVID-19 Spike ACE2 binding inhibition capacity of Verbascum zerdust Fırat was studied using commercial kits. In addition, the plant content was determined by HPLC-DAD analysis and the interaction of the components in the plant content with the 7U0N protein was determined by molecular docking analysis. In addition, the ADME profiles of the molecules detected in the plant content were determined using the SwissADME web tool. According to the results obtained, Verbascum zerdust showed the highest inhibition value at 0.001µl concentration (15.38%). In molecular docking analysis, catechin carbohydrate showed the highest binding affinity to the 7U0N complex (∆G= -8.3 kcal/mol). Among the molecules detected in the plant extract, catechin hydrate, resveretrol, quercetin and tcinamic acid fully complied with the Lipinski, Ghose, Veber, Egan and Muegge criteria. In conclusion, the results obtained indicate that Verbascum zerdust plant can be used in the treatment of COVID-19.

2025-01-01T00:00:00Z Loyinmi, Adedapo Chris Adeleke, Emmanuel Oyeyemi Ijaola, Alani Lateef Oluwatoyin, Olowofeso http://dspace.beu.edu.tr:8080/xmlui/handle/123456789/16599 2026-02-02T11:21:23Z 2025-01-01T00:00:00Z

MODELLING THE TRANSMISSION DYNAMICS OF LASSA HEMORRHAGIC FEVER WITH MITIGATING MEASURES USING FRACTIONAL ORDER DERIVATIVES Loyinmi, Adedapo Chris; Adeleke, Emmanuel Oyeyemi; Ijaola, Alani Lateef; Oluwatoyin, Olowofeso This study proposes a fractional-order model, formulated in the sense of the Caputo fractional derivative, to investigate the transmission dynamics of Lassa hemorrhagic fever. A necessary qualitative analysis was conducted to assess the validity of the model. The fundamental number of reproduction (R0), was estimated using the next generation matrix approach and was found to be less than unity (1) through the stability analysis. The Jacobi and Lyapunov approach was utilized to construct the stability analysis at Infection free and Endemic Equilibrium respectively. The fractional order model is analyzed using a modified Adams-Bashforth technique. Additionally, the numerical simulations were done to validate the effect of various parameters on the model as a whole. The estimator-corrector graphical solutions indicate that the fractional order β, which is the saturation factor impact the dynamics of the model when varied. The results indicate that saturation of infectious individuals in the system helps flatten the infection transmission curve thereby achieving a disease free community in the long run.

2025-01-01T00:00:00Z