Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(20)
- Celik, Erkan(12)
- Mete, Suleyman(11)
- Serin, Faruk(10)
- ALMisned, Ghada(9)
- Güler, Ömer(8)
- Yucesan, Melih(8)
- Tekin, H.O.(7)
- Artuğer, Fırat(6)
- Utku, Anıl(6)
- Guler, Omer(5)
- Özkul, İskender(5)
- Şimşek, Telem(5)
- Acar, Ramazan(4)
- Basgoz, Oykum(4)
- Guler, Seval Hale(4)
- Şimşek, Tuncay(4)
- Bahceci, Ersin(3)
- Baykal, Duygu Sen(3)
- Başhan, Veysi(3)
- Canbay, Canan Aksu(3)
- Demirel, Hakan(3)
- Doğan, Gürkan(3)
- Ergen, Burhan(3)
- Gul, Ali Oktay(3)
- Güler, Seval Hale(3)
- Gülmez, Nihan(3)
- Karaduman, Oktay(3)
- Kavaz, Esra(3)
- Kaya, Sema Kayapinar(3)
- Onder Erguven, Gokhan(3)
- Yayla, Nihal(3)
- Yildirim, Nuran Cikcikoglu(3)
- Özkaynak, Fatih(3)
- Ak, M. Fatih(2)
- Albayrak, M. Gökhan(2)
- Aslan, Serpil(2)
- Aycin, Ejder(2)
- Can, Umit(2)
- Cemalgil, Selim(2)
Yayınlar
- Kitap BölümüYalnız künye2024Possible Interaction of PVC with Micro-and Nano-fillers
Guler, Seval Hale; Simsek, Tuncay; Guler, Omer; Dikici, Burak
Undoubtedly, polyvinyl chloride (PVC) is one of the most produced synthetic polymers globally and is used in all areas of life. Its general structure consists of hydrocarbon and chloride as well known. The main reasons for its widespread use in our life are low production cost, high mechanical strength, and chemical stability. The PVCs have significant problems such as low thermal resistance or weak impact strength. Thus, nowadays, the current studies are noteworthy on the PVC-matrix composites reinforced with micro-/nano-based fillers. The primary purpose of this studies improves the mechanical, physical, or chemical properties of PVC. Of course, the essential feature of a composite structure is the matrix/reinforcement interface and its interactions. In addition to the production method, the selection of matric and reinforcement fillers is the main factor affecting the adhesion and interactions between the interface. In this chapter, an overview of the possible interaction of PVC with micro- and nano-fillers is presented.
AtıfScopus4OpenAlex5
İncele - MakaleYalnız künye2024Scopus SJRQ2Process optimization and modeling of Pb(II) ions adsorption on a new and reusable biocomposite material using experimental design approach
Ince, Muharrem; Kaplan Ince, Olcay; Alp Kavlo, Hevidar
This research paper aimed to establish the optimal conditions for lead (Pb(II)) ions from industrial wastewater (IW) using response surface methodology and central composite design (CCD) approach. A fixed-bed column study was designed by using a novel and reusable biocomposite material, Amanita vaginata (A. vaginata) immobilized on Amberlite XAD-4 resin (A&XAD-4@AV), to find out biosorption behavior of Pb(II) ions. Various experimental variables such as optimum pH value, biocomposite material amount, flow rate, and Pb(II) ions initial concentration were investigated, which significantly affected the Pb(II) ions removal efficiency. The maximum Pb(II) removal efficiency of A&XAD-4@AV biocomposite material was determined as 11.2 mg g−1 under optimum conditions. The reusability of A&XAD-4@AV biocomposite material was found to be suitable. For checking model adequacy, a regression model was derived using CCD to predict the responses and analysis of variance (ANOVA) and lack of fit test was performed. It was observed that the quadratic model, which was controlled and proposed, originated from experimental design data. The ANOVA showed a high coefficient of determination (R2 = 0.9896, R2Adj = 0.9800, R2Pred = 0.9633). Finally, developed and optimized method was applied effectively to wastewater for determining Pb(II) ions levels. The current study indicated that the prepared A&XAD-4@AV is an efficient material to remove of Pb(II) ions from IW.
AtıfScopus1WoS1OpenAlex1
İncele - MakaleYalnız künye2024Scopus SJRQ2Factors Affecting the Setting Times of Pumice Based Alkali-Activated Hybrid Cements
Balun, Bilal; Karataş, Mehmet
The environmental impacts of ordinary Portland cement (OPC) production have led researchers to produce alternative binders. Binders with aluminosilicate structure, such as pumice, can be used to produce one of these alternatives, alkali-activated cements. In addition, alkali-activated hybrid cements have become a type of material that combines the positive aspects of geopolymers and Portland cement. Especially in the activation of low CaO containing materials such as pumice with alkalis, the use of a small amount of OPC ensures that the alkali-activated materials can both be produced under ambient conditions and improves its strength properties. In this study, setting times of pumiced based alkali-activated hybrid cements were evaluated based on OPC amount (0%, 5%, 10%, 15% and 20%), alkaline solution/binder ratio (0.47, 0.50 and 0.53) and sodium silicate/potassium hydroxide (1, 2 and 3) ratio. In experiments carried out under ambient conditions, the silica module (2.0) of the sodium silicate solution was kept constant. As a result of the experimental studies, the increase in the OPC amount and the sodium silicate ratio shortened the setting times of the pumiced based alkali-activated hybrid materials while the alkali solution/binder ratio increased the setting times. It was determined that the factor most affects the setting times was the OPC amount. The setting time of the OPC-free pumice-based alkali-activated binders without OPC takes more than one day. As a result, increasing the amount of OPC up to 20% significantly reduced the setting times. A decreasing trend was observed in compressive strengths with increasing setting times.
AtıfScopus5WoS4OpenAlex5İncele - MakaleYalnız künye2024Scopus SJRQ1A comprehensive risk assessment framework for mooring risks at hydrocarbon berths using fuzzy rule-based Bayesian network and multi-attribute decision-making
Demirel, Hakan; Başhan, Veysi; Yucesan, Melih; Gul, Muhammet
Mooring operations -especially at hydrocarbon berths- are critical components of the marine and offshore industry. They usually involve securing the berths of ships carrying valuable cargo and ensuring the safety of personnel, assets, and the environment. For this purpose, a comprehensive risk assessment framework for mooring operations at hydrocarbon berths is proposed in this study. This framework helps evaluate risks using a rule-based Bayesian network. In the assessment of mooring risks, four risk parameters of severity, occurrence, detection, and maintenance are considered to construct the BN structure of each mooring risk. These parameters are weighted with the aid of the fuzzy Best Worst Method. Hereafter, a fuzzy rule-based system is constructed by incorporating BN to determine a risk priority score. The framework also develops mitigation strategies to maintain effective risk management for safe and secure maritime transportation. Sensitivity analyzes and comparison studies were conducted to test the validity of the proposed comprehensive risk management framework. The study reveals that the most critical risk is associated with Technical Failures (Q1) in the cluster pertaining to the automation of Quick Release Hooks. This risk stems from technical malfunctions in automation systems, encompassing sensors and control mechanisms, potentially resulting in the unintended release of mooring lines. The second highest priority risk is linked to Human Error (M1) in the mooring risks cluster, attributed to human errors such as inadequate training, miscommunication, and procedural mistakes during mooring operations, posing risks of accidents and damage to ships and infrastructure. Conversely, the least significant risk, Redundancy (Q5), focuses on redundancy. This risk is associated with automation and underscores the importance of implementing redundancy mechanisms to ensure the safe continuation of mooring operations in the face of system failures. In conclusion, the proposed comprehensive risk assessment framework offers a systematic approach to evaluate and prioritize mooring risks at hydrocarbon berths. The study’s findings emphasize the critical importance of addressing technical malfunctions in the automation of Quick Release Hooks and human errors during mooring operations. By identifying the most significant risks and developing mitigation strategies, this framework contributes to enhancing the safety and security of maritime transportation, particularly in the context of hydrocarbon berths.
AtıfScopus11WoS11OpenAlex13İncele - DüzeltmeAçık Erişim2024Scopus SJRQ2Correction to: Detection of hateful twitter users with graph convolutional network model (Earth Science Informatics, (2023), 16, 1, (329-343), 10.1007/s12145-023-00940-w)
Utku, Anıl; Can, Umit; Aslan, Serpil
In this article the affiliation details for Serpil Aslan were incorrectly given as ‘Software Engineering Department, Turgut Üzal University, 44210 Malatya, Turkey’ but should have been ‘Department of Software Engineering, Faculty of Engineering and Natural Sciences, Malatya Turgut Ozal University, Malatya, Turkey.’ The original article has been corrected.
AtıfScopus1OpenAlex2İncele - MakaleAçık Erişim2024Scopus SJRQ1Spread patterns of COVID-19 in European countries: hybrid deep learning model for prediction and transmission analysis
Utku, Anıl; Akcayol, M. Ali
The COVID-19 pandemic has profoundly impacted healthcare systems and economies worldwide, leading to the implementation of travel restrictions and social measures. Efforts such as vaccination campaigns, testing, and surveillance have played a crucial role in containing the spread of the virus and safeguarding public health. There needs to be more research exploring the transmission dynamics of COVID-19, particularly within European nations. Therefore, the primary objective of this research was to examine the spread patterns of COVID-19 across various European countries. Doing so makes it possible to implement preventive measures, allocate resources, and optimize treatment strategies based on projected case and mortality rates. For this purpose, a hybrid prediction model combining CNN and LSTM models was developed. The performance of this hybrid model was compared against several other models, including CNN, k-NN, LR, LSTM, MLP, RF, SVM, and XGBoost. The empirical findings revealed that the CNN-LSTM hybrid model exhibited superior performance compared to alternative models in effectively predicting the transmission of COVID-19 within European nations. Furthermore, examining the peak of case and death dates provided insights into the dynamics of COVID-19 transmission among European countries. Chord diagrams were drawn to analyze the inter-country transmission patterns of COVID-19 over 5-day and 14-day intervals.
AtıfScopus6WoS3OpenAlex7İncele - MakaleAçık Erişim2024Scopus SJRQ1A new hybrid approach for grapevine leaves recognition based on ESRGAN data augmentation and GASVM feature selection
Doğan, Gürkan; Imak, Andaç; Ergen, Burhan; Sengur, Abdulkadir
Grapevine leaf is a commodity that is collected only once a year and has a high return on investment due to its export. However, only certain types of grapevine leaves are consumed. Therefore, it is extremely important to distinguish the types of grapevine leaves. In particular, performing this process automatically on industrial machines will reduce human errors, workload, and thus cost. In this study, a new hybrid approach based on a convolutional neural network is proposed that can automatically distinguish the types of grapevine leaves. In the proposed approach, firstly, the overfitting of network models is prevented by applying data augmentation techniques. Second, new synthetic images were created with the ESRGAN technique to obtain detailed texture information. Third, the top blocks of the MobileNetV2 and VGG19 CNN models were replaced with the newly designed top block, effectively extracting features with the data. Fourthly, the GASVM algorithm was adapted and used to create a subset of the features to eliminate the ineffective and unimportant ones from the obtained features. Finally, SVM classification was performed with the feature subset consisting of 314 features, and approximately 2% higher accuracy and MCC score were obtained compared to the approaches in the literature.
AtıfScopus8WoS6OpenAlex9İncele - MakaleYalnız künye2024Scopus SJRQ2A new S-box generator algorithm based on chaos and cellular automata
Artuğer, Fırat
S-boxes are very important structures for encryption algorithms. For S-boxes to be strong, they should not be as linear as possible. Obtaining an S-box with high nonlinearity is a difficult problem. For this reason, it has attracted the attention of researchers for many years. In this study, cellular automata logic was used to overcome this problem. A chaotic tent map was used for the initial population. Then, in this weak S-box, the elements were replaced with their neighbors, and the nonlinearity value was checked. When this value increased, the S-box was transferred to the next generation. With the proposed algorithm, an S-box structure with a nonlinearity value of 110.5 was obtained. This value surpasses most studies in the literature. In addition, it has been proven because of the analysis that the proposed S-box also provides other performance criteria.
AtıfScopus6WoS8OpenAlex7İncele - MakaleAçık Erişim2024Scopus SJRQ1A new CNN-based semantic object segmentation for autonomous vehicles in urban traffic scenes
Doğan, Gürkan; Ergen, Burhan
Semantic segmentation is the most important stage of making sense of the visual traffic scene for autonomous driving. In recent years, convolutional neural networks (CNN)-based methods for semantic segmentation of urban traffic scenes are among the trending studies. However, the methods developed in the studies carried out so far are insufficient in terms of accuracy performance criteria. In this study, a new CNN-based semantic segmentation method with higher accuracy performance is proposed. A new module, the Attentional Atrous Feature Pooling (AAFP) Module, has been developed for the proposed method. This module is located between the encoder and decoder in the general network structure and aims to obtain multi-scale information and add attentional features to large and small objects. As a result of experimental tests with the CamVid data set, an accuracy value of approximately 2% higher was achieved with a mIoU value of 70.59% compared to other state-of-art methods. Therefore, the proposed method can semantically segment objects in the urban traffic scene better than other methods.
AtıfScopus19WoS10İncele - MakaleAçık Erişim2024Scopus SJRQ2Innovative Al6061-gadolinium oxide ods alloys: fabrication and comprehensive characterization of microstructural, physical, mechanical, and radiation shielding properties
ALMisned, Ghada; Yayla, Nihal; Albayrak, M. Gökhan; Güler, Ömer; Baykal, Duygu Sen; Tekin, H.O.
This study explores the development and comprehensive characterization of Al6061-Gd₂O₃ composites, designed to enhance radiation shielding and mechanical properties for critical applications in environments exposed to ionizing radiation. The purpose of this research is to assess the effectiveness of Gd2O3 as a reinforcing material for Al6061, with the aim of creating a dual-function composite that combines structural integrity with superior gamma-ray and neutron attenuation capabilities. Using X-ray diffraction (XRD) and scanning electron microscopy (SEM), we analyzed the microstructural effects of varying Gd2O3 content, observing homogeneous dispersion at low concentrations and clustering at higher levels. Mechanical properties demonstrated that increased Gd2O3 content reduces the elastic modulus, indicating a trade-off between stiffness and shielding efficiency. Radiation shielding parameters, including Transmission Factor (TF), mass attenuation coefficient (MAC), and Fast Neutron Removal Cross Section (FNRCS), were evaluated through Phy-X/PSD and PHITS Monte Carlo simulations. Results indicate that Gd2O3 reinforcement significantly improves gamma-ray and neutron shielding, particularly at higher concentrations, making the composite viable for non-structural applications prioritizing radiation protection. The findings from this study highlight the potential of Gd2O3-reinforced Al6061 composites to serve as effective shielding materials in environments where radiation exposure is a primary concern.
AtıfScopus4OpenAlex5İncele - MakaleAçık Erişim2024Scopus SJRQ2Enhanced impedance, electrical conductivity, dielectric properties for colloidal starch-g-poly (methyl methacrylate) supported with semiconductor cadmium sulfide
Torğut, Gülben; Gürler, Nedim
In this study, starch-graft-poly (methyl methacrylate) (starch-g-PMMA) composites doped with different amounts (5, 10, and 15 wt%) of cadmium sulfide (CdS) particles were fabricated for electrical measurements using in-situ polymerization technique. The structural characterization of the samples was studied. The dielectric and conductivity properties of the composites were investigated using impedance analyzer depending on the frequency (100 Hz–20 kHz) at room temperature. Spectroscopy revealed that the dielectric constant (ε′), dielectric loss (ε′′), and real (Z) components of impedance are found to decrease with increasing frequency for both starch-g-PMMA and starch-g-PMMA (5, 10, and 15 wt%) composites. On the contrary, the AC conductivity (σac) of samples increased with increasing frequency. In addition, ε′ and ε′′ values of starch-g-PMMA were lower than composites that added CdS. When the CdS content increased from 0 to 15%, ε′ increased from 5.62 to 15.10 at 100 Hz. AC conductivity was improved after adding the CdS particles. The maximum conductivity value for starch-g-PMMA15%CdS is found to be 3.07 × 10–7 at 100 Hz. When the dielectric properties of composites are evaluated, it is concluded that it is an exciting material for electronic applications in technology.
AtıfScopus9WoS8OpenAlex10İncele - Kitap BölümüAçık Erişim2024Scopus SJRQ4Heavy Metals in Cetraria islandica: Health Risk Assessment
Topal, Murat; Arslan Topal, E. Işıl; Öbek, Erdal; Aslan, Ali
In this chapter, potential human health risk of the heavy metals associated with usage of Cetraria islandica were evaluated. Heavy metals (lead, cadmium, manganese, chromium, copper, zinc, and nickel) were determined in Cetraria islandica. Highest and lowest heavy metal values were 87 ± 4.3 mg/kg for manganese (Mn) and 0.12 ± 0.01 mg/kg for cadmium (Cd). When potential health risk was assessed, the doses of exposure for man, woman, and child followed the order of bread > tea > dermal. Risk of health for bread and tea were child > woman > man. Also, risk of health for dermal was woman > child > man. Non-carcinogenic risk was woman > child > man for dermal way. Non-carcinogenic risks were child > woman > man for dietary. Highest total hazard index (THI) was 6.33 for chromium (Cr), lowest THI was 0.22 for zinc (Zn). THIs were zinc < copper < cadmium < nickel < lead < manganese < chromium. The THIs were higher than 1 for chromium, manganese and lead. Total highest carcinogenic value was 1.73E−03 for Ni and minimum was 1.19 E−05 for lead. Carcinogenic risks for bread (cadmium, nickel and chromium) were high. As a result, it was determined that Cetraria islandica may cause cancer risk if consumed as additive in bread. It was determined that if Cetraria islandica was consumed as tea and cream, there would be no risk of cancer and could not adversely affect human health.
- MakaleAçık Erişim2024Scopus SJRQ2A novel convolutional neural network model with hybrid attentional atrous convolution module for detecting the areas affected by the flood
Şener, Abdullah; Doğan, Gürkan; Ergen, Burhan
Natural disasters are sudden and unexpected events that occur as a result of natural processes and often have a significant impact on people, animals, and plants, often resulting in material and emotional losses. Two of the most devastating disasters are floods and tsunamis. After these disasters, search and rescue operations to identify flooded areas are very important to save the lives of affected people and to ensure the health and safety of rescue workers. In this study, a novel semantic segmentation model called Flood Area Segmentation Network (FASegNet) was proposed to guide search and rescue teams in disaster areas to speed up search and rescue operations after natural disasters such as floods, high tides, and tsunamis. The obtained results were compared with common image segmentation models used in various fields. It was found that the developed model achieved higher accuracy rates with fewer parameters. When tested with the "Flood Area" and "Water Body" datasets without pretraining and data augmentation, FASegNet achieved mIoU accuracy of 84.3% and 84.5% respectively.
AtıfScopus23WoS21OpenAlex23İncele - MakaleAçık Erişim2024Scopus SJRQ1Optimization and Kinetic Study of Manganese Leaching from Pyrolusite Ore in Hydrochloric Acid Solutions with Oxalic Acid
Karacahan, Mehmet Kayra
The leaching behavior of pyrolusite minerals was examined in hydrochloric acid solutions, including oxalic acid, to evaluate the influence of various experimental conditions. The optimum parameters for the leaching process were found in the first stage, and the process's kinetics were assessed in the second. The concentrations of oxalic acid, hydrochloric acid, and temperature were chosen as independent variables in the optimization experiments, with the central composite design used to analyze the experimental data. The optimum concentrations for oxalic acid, hydrochloric acid, and temperature were determined to be 0.75 mol/L, 1.2 mol/L, and 60 °C, respectively. The leaching rate was determined to be 97.4% for 120 min of response time in optimum situations. The kinetic assessment experiments studied the effects of solid/liquid ratio, particle size, stirring speed, and temperature on the manganese leaching rate from pyrolusite. In the studies, the leaching rate was shown to rise with increasing temperature and stirring speed, as well as with decreasing particle size and solid/liquid ratio. The kinetic analysis revealed that the leaching kinetics matched the mixed kinetic model, and a mathematical model for the leaching process was developed. This process's activation energy was determined to be 29.05 kJ/mol. Graphical Abstract: (Figure presented.)
AtıfScopus17WoS15OpenAlex18İncele - MakaleYalnız künye2024Scopus SJRQ3Ochratoxin a levels in Turkish coffee: a probabilistic health risk assessment via Monte Carlo simulation
Sevim, Sumeyra; Macit, Arife; Kizil, Mevlude
Throughout history, Turkish coffee has been the most widely consumed type of coffee in Turkey. Therefore, the goal of this study was to determine the amount of ochratoxin A (OTA) present in Turkish coffee and to analyze any potential health hazards. A total of 41 Turkish coffees were collected and analyzed for OTA activity using a competitive enzyme immunoassay (ELISA). Furthermore, dietary exposure and health risk assessments for the Turkish population were calculated based on analytical results and coffee consumption data from the Turkish Nutrition and Health Survey 2019 (TNHS-2019) in three age categories (15–18, 19–64, and 65 + years). Nine of the samples contained more than 2.5 μg/kg OTA, with an average of 5.24 μg/kg. The OTA concentration in 3 samples exceeded the permissible maximum limit (5 μg/kg) established by Turkish legislation, and the mean concentration was 8.41 μg/kg. A margin of exposure (MOE) approach was used for risk characterization, considering both non-neoplastic and neoplastic consequences. There were no concerns about health risks because MOEs were more than 10,000 for all categories. Although the levels of OTA analyzed in Turkish coffee did not pose a risk to individuals in the three age categories, emphasis should be placed on minimizing and controlling OTA concentrations in Turkish coffee. Additionally, it is also necessary to consider other food sources that could contribute to OTA exposure.
AtıfScopus2WoS2OpenAlex2
İncele - MakaleYalnız künye2024Scopus SJRQ1A novel algorithm based on DNA coding for substitution box generation problem
Artuğer, Fırat
Substitution boxes are very important for cryptographic structures. But getting an 8-bit strong s-box is a difficult problem. To address this problem, a new approach is proposed in this study. DNA chains are used in the proposed approach. First of all, a weak s-box is obtained with the help of a chaotic map. Then, a DNA chain is formed with the same chaotic map. In this study, 2000-long DNA chains were produced. Then, two random values consisting of four components are determined from these DNA chains, and these values are addressed to the s-box structure. By changing the places of these values, the s-box structure is improved up to a certain iteration. In this study, 10,000 iterations were examined, and three different strong s-boxes were obtained by using three different DNA chains. The nonlinearity values of these s-box structures were observed as 110.25, 110.5, and 110.75, respectively. The proposed study has proven to work effectively with effective results in three different chains. In addition, it has been proven as a result of the analysis that the proposed s-box structures also have other cryptographic features. The proposed algorithm has surpassed many s-box generation philosophies in the literature. In addition, the proposed algorithm will provide serious gains to cryptographic structures that will be developed in the future.
AtıfScopus21WoS22OpenAlex24İncele - MakaleAçık Erişim2024Scopus SJRQ2Photoresponse, thermal and electrical behaviors of MXene-based polysulfone nanocomposite
Demirelli, Kadir; Barim, Esra; Çelik, Aytekin; Yegin, Mustafa; Aksoy, Yunus; Hanay, Özge; Hasar, Halil
The Ti3C2Tx MXene nanosheet was prepared by 40% (v/v) hydrofluoric acid etching at 20 °C for 48 h and delamination of bulk MAX Ti3AlC2 precursor material. A 2D nanomaterial MXene Ti3C2Tx as a nanofiller was introduced to polysulfone (PSulfone) matrix. MXene and PSulfone/MXene nanocomposite systems were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscope, Fourier-transform infrared and thermogravimetric analysis instruments. Dielectric and electrical characterization of PSulfone/MXene nanocomposite was carried out. The electrical resistance of Ti3C2Tx MXene from measurement current (I)–voltage (V) was measured as 116 Ω. Pure PSulfone matrix exhibits typical insulator behavior, and MXene exhibits a good conductor behavior. But, when MXene was added to the pure PSulfone matrix, the resistance of the MXene/PSulfone nanocomposite increased moderately compared to that of pure MXene. In spite of the excess of surface functional groups, MXene showed surprisingly good electron transport across the surface, while in the case of PSulfone/MXene nanocomposite, the insulating behavior of PSulfone significantly reduced the electron transport of MXene. The semiconductor behavior of PSulfone/Ti3C2Tx MXene nanocomposite indicates that MXene provides efficient charge carrier transfer in the nanocomposite system. By comparing the TGA results between the PSulfone and different weight ratios of PSulfone/Ti3C2Tx MXene nanocomposites, it was determined that MXene nanosheets had a significant effect in slightly accelerating the thermal degradation of PSulfone. Optical conductivity was investigated by preparing a film of PSulfone/MXene nanocomposite on an interdigital contact. It was observed that the optical current values changed depending on the increasing illumination intensity. Considering current–voltage measurements, the photocurrent generation potential of PSulfone/MXene nanocomposite shows that it can be used in photodevice production.
AtıfScopus24OpenAlex27İncele - MakaleAçık Erişim2024Scopus SJRQ2Physical and shielding properties of Er2O3 rare earth oxide compound content on PCL/PEG blend
Taşgin, Yahya; Pekdemir, Mustafa Ersin; Yilmaz, Mücahit; Kanca, Muhammed Sait; Kök, Mediha
Rare earth elements (RRE), due to their unique magnetic, electrical, and optical properties, are an important group of elements demanded in many application areas from machine technology to the health industry. In this study, new composites were obtained by mixing Erbium oxide (Er2O3), one of the rare earth element oxides, into PCL–PEG blend, which is also an important material group, in different ratios. The characteristic functional groups of the obtained polymer blend/Er2O3 nanocomposites were determined by the ATR-IR, and as the erbium oxide ratio increased, characteristic peaks of the polymers in the blend as well as characteristic signals of the Er–O–Er bond were found. When the thermal behavior of the obtained composites was examined, it was observed that the polymer blend exhibited miscible blend properties and the melting temperature of the polymer blend increased as the Er2O3 ratio increased. In addition, it was determined that the thermal stability of the composite increased significantly. X-ray measurements of composites at room temperature support other measurement results. It was determined that the presence of Er-RRE oxide increased the crystal structure feature in the polymer blend composite. Gamma radiation shielding capabilities of polymer materials containing different erbium ratios were investigated by calculating shielding parameters such as half value layer (HVL), radiation protection efficiency (RPE), and mean free path (MFP). Cs-137 and Co-60 radioactive sources were used as gamma sources. According to the obtained measurement results, Erbium oxide increased the absorption property of the polymer composite material. Graphical abstract: [Figure not available: see fulltext.].
AtıfScopus26WoS28OpenAlex29İncele - MakaleAçık Erişim2024Scopus SJRQ2Strong s-box construction approach based on Josephus problem
Artuğer, Fırat
There are two basic requirements for symmetric encryption algorithms. The first of these is diffusion. The second and most important is confusion. In these algorithms, this requirement is usually met by s-box structures. Therefore, s-box structures must be strong. So, a cryptographically good s-box will make the encryption algorithm difficult to crack. However, obtaining a strong s-box is a rather difficult problem. In this study, Josephus circle logic is used to solve this problem. Initially, with a random s-box structure, the elements are replaced according to their Josephus positions, and the s-box is made stronger. In the proposed algorithm, according to the Josephus logic, the elements that kill each other are replaced and this process continues until one element remains. The last 30 surviving elements are replaced with all elements. In this way, three different s-boxes were obtained. In two of them, the nonlinearity value was 110.5, and in one of them, the nonlinearity value was 110.75. Fixed points in the proposed s-box structures were identified and eliminated. In addition, it has been proven because of the analysis that the obtained s-box structures also meet other cryptographic requirements. In addition to leaving behind most studies in the literature, the proposed method will also provide strong s-box structures for encryption algorithms to be built in the future.
AtıfScopus15OpenAlex12İncele - MakaleAçık Erişim2023Scopus SJRQ1COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model
Baskak, Dilber; Ozbey, Sumeyye; Yucesan, Melih; Gul, Muhammet
The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the “COVID-19 safe campus” evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers’ evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.
AtıfScopus4WoS3OpenAlex2İncele