Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Güler, Ömer(32)
- Akkurt, Nevzat(27)
- Tekin, H.O.(27)
- ALMisned, Ghada(24)
- Gul, Muhammet(20)
- Yucesan, Melih(14)
- Xu, Qian(12)
- Baykal, Duygu Sen(11)
- Güler, Seval Hale(11)
- Taşgın, Yahya(10)
- Kavaz, E.(9)
- Kilic, G.(8)
- Zengin, Gokhan(8)
- Durmus, Hasan(7)
- Guler, Omer(7)
- Xiong, Yaxuan(7)
- Yılmaz, Demet(7)
- Özkul, İskender(7)
- Yayla, Nihal(6)
- Zhang, Hui(6)
- Alkarrani, Hessa(5)
- Baloglu, Ulas Baran(5)
- Celik, Erkan(5)
- Du, Yanping(5)
- Ilik, E.(5)
- Kanca, M. Sait(5)
- Kök, Mediha(5)
- Mahomoodally, Mohamad Fawzi(5)
- Ortiz-Barrios, Miguel(5)
- Qiang, Yujie(5)
- Yang, Gang(5)
- Zakaly, Hesham M.H.(5)
- Aghakhani, S.(4)
- Basgoz, Oykum(4)
- Birdogan, Selcuk(4)
- Caprioli, Giovanni(4)
- Etli, Serkan(4)
- Guler, Seval Hale(4)
- Kahraman, Gökhan(4)
- Liu, Lin(4)
Yayınlar
- MakaleYalnız künye2019Scopus SJRQ1Fabrication, characterization of poly(MA-co-NIPA)-graphene composites and optimization the dielectric properties using the response surface method (RSM)
Torğut, Gülben
Poly(Maleic anhydride-N-isopropyl acrylamide poly(MA-co-NIPA) copolymer was synthesized by Free radical polymerization method. Response surface methodology (RSM) was used for optimizing the dielectric constant (έ) and dielectric loss factor (ε՛՛). The aim of this study is to determine the quantitative relationship between selected parameters (frequency, applied voltage and graphene content) at room temperature. The importance of process parameters in the model is assessed by analysis of variance (ANOVA) investigation. Our results show that, with increasing the frequency the έ and ε՛՛ of the polymers decreases, whereas voltage has no significant effect on έ and ε՛՛ of the composites. With the incorporation of graphene into poly(MA-co-NIPA) the έ and ε՛՛ considerably increased by 244% and 387% respectively. The model predicted the maximum value of the έ (13) when the frequency was set at 4506, the voltage was set at 1.45, and the graphene content was set at 14.97 wt%. Also, the RSM indicated that maximum ε՛՛ (1969) was achieved at the frequency of 512, at the voltage of 20.44, and at the graphene content of 14.76 wt%. The morphology of composites was investigated by scanning electron microscopy (SEM). SEM results demonstrated that the poly(MA-co-NIPA)-graphene composites has interconnected and they form different morphologies with the increase of GNs content. ATR tests showed that no significant change in chemical bond and crystallization is found in composites.
AtıfScopus16WoS17OpenAlex21
İncele - MakaleYalnız künye2019Scopus SJRQ1Research of thermal performance by metallographic investigation of stator winding solder region in hydroelectric power plants
Kahraman, Gökhan; Taşgın, Yahya
Hydroelectric power plants are the most widely used renewable energy sources all over the world. In these plants, many studies have been conducted in order to produce energy continuously and efficiently. Among these studies, predictive maintenance methods, efforts to increase power by improving cooling conditions, and improving efficiency by improving the turbine wheel. In this paper, soldering at the junctions of the stator windings in the central generators has been investigated. Traditional solder (Cu–Zn) materials and silver alloy solders (Ag-Cu-Zn) have been investigated in terms of thermal and metallographic. Silver alloy soldering has been found to have lower electrical conductivity than conventional soldering. The winding temperatures measured on the generating generator show that silver alloy soldering is more efficient. Reducing the stator winding temperature in hydroelectric power plants allows more energy production and also reduces costs by preventing winding failures.
AtıfScopus2WoS2OpenAlex2İncele - MakaleAçık Erişim2019Scopus SJRQ1Surface morphology, spectroscopy, optical and conductivity properties of transparent poly(9-vinylcarbazole) thin films modified with graphene oxide
Aydin, Handan; Gündüz, Bayram; Aydin, Cihat
In this work, we synthesized the graphene oxide by Hummers method and prepared poly-N-vinylcarbazole (PVK)/graphene oxide (GO) nanocomposites. We investigated the SEM images, FTIR and UV spectroscopy and ac conductivity properties of PVK:wt% (0, 1, 5, 10, 15%) GO nanocomposites thin films. The PVK and PVK/GO nanocomposites are dominant in near ultraviolet region. The absorption band edge of the films of the PVK/GO nanocomposites varies from 3.077 to 3.175 eV, while the allowed optical band gap of the 0, 1, 5, 10 and 15% wt. GO + PVK nanocomposites varies from 2.97 to 3.30 eV. The optical band gap and refractive indices of the PVK can be changed with increasing the percentage by weight of graphene oxide. The single oscillator energy varies from 3.358 to 3.670 eV, while the dispersion energy varies from 6.404 to 6.970 eV. The graphene oxide has an important effect on the ac conductivity of the PVK. Obtained results show that the PVK material modified with graphene oxide is promising for electronic, optical and optoelectronic technology.
AtıfScopus20WoS20OpenAlex22İncele - MakaleAçık Erişim2019Scopus SJRQ2Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals
Yildirim, Ozal; Talo, Muhammed; Ay, B.; Baloglu, Ulas Baran; Aydin, G.; Acharya, U. Rajendra
In this study, a deep-transfer learning approach is proposed for the automated diagnosis of diabetes mellitus (DM), using heart rate (HR) signals obtained from electrocardiogram (ECG) data. Recent progress in deep learning has contributed significantly to improvement in the quality of healthcare. In order for deep learning models to perform well, large datasets are required for training. However, a difficulty in the biomedical field is the lack of clinical data with expert annotation. A recent, commonly implemented technique to train deep learning models using small datasets is to transfer the weighting, developed from a large dataset, to the current model. This deep learning transfer strategy is generally employed for two-dimensional signals. Herein, the weighting of models pre-trained using two-dimensional large image data was applied to one-dimensional HR signals. The one-dimensional HR signals were then converted into frequency spectrum images, which were utilized for application to well-known pre-trained models, specifically: AlexNet, VggNet, ResNet, and DenseNet. The DenseNet pre-trained model yielded the highest classification average accuracy of 97.62%, and sensitivity of 100%, to detect DM subjects via HR signal recordings. In the future, we intend to further test this developed model by utilizing additional data along with cloud-based storage to diagnose DM via heart signal analysis.
AtıfScopus145OpenAlex152
İncele - MakaleAçık Erişim2019Scopus SJRQ1Al-doped ZnO as a multifunctional nanomaterial: Structural, morphological, optical and low-temperature gas sensing properties
Aydın, Handan; Yakuphanoglu, Fahrettin; Aydın, Cihat
In this study, zinc oxide thin films doped with Al at different atomic ratios (0.1%, 0.5%, 1%, 2%, 5%) were prepared using sol-gel spin coating method. Crystal structure, surface morphology, optical properties of the films and their response to ammonia gas were examined. XRD results showed that the ZnO thin films had a hexagonal polycrystalline structure. It was concluded from the calculation of the crystal size and lattice constant of the films that the produced samples were a nanomaterial. Scanning electron microscope (SEM) and atomic force microscope (AFM) images of the samples revealed that the morphology was composed of nanostructured particles and a cluster structure made of the combination of these particles. The optical band gap (Eg) of the prepared films were found within the range of 3.251 eV–3.342 eV by using the optical absorption method. Characteristics of susceptibility against ammonia gas were evaluated depending on the Al dopant. The obtained results showed that the gas response along with the structural, morphological, and optical properties of ZnO thin films changed with Al dopant. The produced thin film samples can be used as a sensor for the detection of ammonia gas in various industrial branches.
AtıfScopus66WoS59OpenAlex76İncele - MakaleYalnız künye2019Scopus SJRQ1Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry
Gul, Muhammet; Ak, M. Fatih; Guneri, Ali Fuat
Introduction: Underground mining is considered one of the most hazardous industries and is often associated with serious work-related fatalities; this paper addresses job-related hazards and associated risks. Method: A risk assessment approach is proposed (Pythagorean fuzzy environment) and a case study is carried out in an underground copper and zinc mine. Results: Results of the study demonstrate that hazards can be categorized into different risk levels via compromised solutions of the fuzzy approach. Conclusion: The study provides a theoretical contribution by suggesting a Pythagorean fuzzy numbers-based VlseKriterijumska Optimizacija I Kompromisno Resenje (PFVIKOR) approach. Moreover, it contributes to improving overall safety levels of underground mining by considering and advising on the potential hazards of risk management. Practical applications: The proposed approach will improve the existing safety risk assessment mechanism in underground copper and zinc mining.
AtıfScopus184WoS156OpenAlex180İncele - MakaleYalnız künye2018Scopus SJRQ1A new Fine-Kinney-based risk assessment framework using FAHP-FVIKOR incorporation
Gul, Muhammet; Guven, Busra; Guneri, Ali Fuat
The most crucial step of a risk assessment process that follows identifying the scope of assessment and hazards is the initial risk assessment, particularly with a risk scoring system. The Fine–Kinney method is a comprehensive method for quantitative evaluations to aid in controlling hazards. In this risk assessment method, the risk value is calculated by considering the parameters of the consequence of an accident (C), the exposure or frequency of occurrence of a hazard event that could lead to an accident (E) and the probability of a hazardous event (P). The classical Fine–Kinney method has a limitation in that it assigns an equal weight to these three parameters. Therefore, we propose a new risk assessment method incorporating a fuzzy analytic hierarchy process (FAHP) with fuzzy VIKOR (FVIKOR). FAHP was used in weighting these risk parameters derived from the Fine–Kinney method. The priority orders of hazards were determined by a FVIKOR method. The proposed method enables group decision-making in assessing hazards and uses relative importance among three risk parameters by pair-wise comparison of Buckley's FAHP. Owing to the difficulty in evaluating C, E and P, linguistic terms are used in the proposed method. In addition, a case study of the evaluation of risks in the arms industry is used to illustrate the proposed method. A comparison with the classical method and fuzzy technique for order preference by similarity of an ideal solution (FTOPSIS) is discussed. The results show that the proposed method is effective in helping stakeholders to determine the risk control policies to validate the effectiveness of their risk controls.
AtıfScopus106WoS84OpenAlex124İncele - MakaleYalnız künye2018Scopus SJRQ2Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Yıldırım, Özal; Pławiak, Paweł; Tan, Ru-San; Acharya, U. Rajendra
This article presents a new deep learning approach for cardiac arrhythmia (17 classes) detection based on long-duration electrocardiography (ECG) signal analysis. Cardiovascular disease prevention is one of the most important tasks of any health care system as about 50 million people are at risk of heart disease in the world. Although automatic analysis of ECG signal is very popular, current methods are not satisfactory. The goal of our research was to design a new method based on deep learning to efficiently and quickly classify cardiac arrhythmias. Described research are based on 1000 ECG signal fragments from the MIT - BIH Arrhythmia database for one lead (MLII) from 45 persons. Approach based on the analysis of 10-s ECG signal fragments (not a single QRS complex) is applied (on average, 13 times less classifications/analysis). A complete end-to-end structure was designed instead of the hand-crafted feature extraction and selection used in traditional methods. Our main contribution is to design a new 1D-Convolutional Neural Network model (1D-CNN). The proposed method is 1) efficient, 2) fast (real-time classification) 3) non-complex and 4) simple to use (combined feature extraction and selection, and classification in one stage). Deep 1D-CNN achieved a recognition overall accuracy of 17 cardiac arrhythmia disorders (classes) at a level of 91.33% and classification time per single sample of 0.015 s. Compared to the current research, our results are one of the best results to date, and our solution can be implemented in mobile devices and cloud computing.
AtıfScopus801OpenAlex854İncele - MakaleYalnız künye2018Scopus SJRQ1A comparative outline for quantifying risk ratings in occupational health and safety risk assessment
Gul, Muhammet; Ak, M. Fatih
The concept of risk assessment has been introduced as an examination of safety in the workplace to enable assessments as to whether sufficient precautions have been taken or if more should be done to prevent potential harm. Hazardous industries have faced serious fatalities related to work, workplaces, and workers as a consequence of their high-risk processes. Therefore, in this work, a novel and comparative methodology for quantifying risk ratings in occupational health and safety risk assessment is proposed. A 5 × 5 risk matrix is initially determined, and the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is then applied to rank identified hazards. As a novelty to the knowledge, two parameters of the 5 × 5 matrix method, likelihood and severity, are subjectively assessed by occupational health and safety experts, and then importance levels for these parameters are determined using the Pythagorean fuzzy analytic hierarchy process (PFAHP). In the proposed approach, analysts use linguistic terms and Pythagorean fuzzy sets, which provide greater independence in their evaluations. An outline that enables comparison of the results of this study with the circumcenter of centroids method and the fuzzy AHP-fuzzy VIKOR integrated method in quantifying risk ratings is also provided. In order to present the practicality of this work, a case study in an underground copper and zinc mine is carried out.
AtıfScopus194WoS153OpenAlex211İncele - MakaleYalnız künye2018Scopus SJRQ1Transmission line fault location using traveling wave frequencies and extreme learning machine
Akmaz, Düzgün; Mamiş, Mehmet Salih; Arkan, Müslüm; Tağluk, Mehmet Emin
In this research, a new approach was proposed for determining the fault location in transmission lines. Traveling wave frequencies and an extreme learning machine (ELM) were used to determine fault location. Transient signals in the time domain were transformed to the frequency domain using the fast Fourier transform (FFT) and the traveling wave frequencies were detected from the transient frequency spectrum. In order to detect the location of fault, traveling wave frequency was used initially to predict the fault location. The prediction of this fault location was tested for many different fault conditions and was found to be adversely affected by only the source inductance value. This is due to the negative effect of source inductance on wave velocity. Regression feature of ELM was used in order to improve the prediction of fault location and to minimize the negative effect of source inductance. For ELM regression training, values of the fault distance estimated from the traveling-wave frequencies and the source inductance values were used as ELM input data, and the actual distance values were used as ELM output data. After ELM regression training, ELM predicted a new fault location using the input data. The Alternative Transients Program (ATP/EMTP) was used to model J. Marti frequency dependent line model, and the MATLAB program was used to perform fault-detection algorithms. Simulation results show that the proposed method is very successful against many variables such as different fault resistances, source inductances, transmission line characteristics, transmission line lengths.
AtıfScopus104WoS74OpenAlex101İncele - MakaleAçık Erişim2018Scopus SJRQ1Artificial neural networks and adaptive neuro-fuzzy inference systems approaches to forecast the meteorological data for HVAC: The case of cities for Turkey
Işık, Erdem; Inallı, Mustafa
Limited energy resources and increasing need for energy due to population growth seem to lead researchers to focus on these issues. Forecast of meteorological data has significant importance in design of thermal systems. In this study, forecasting of meteorological data used in thermal system design was performed for fifty cities to represent the entire Turkey. Data obtained from General Directorate of Meteorology (MGM) were modelled by artificial neural networks and adaptive-network based fuzzy inference systems. Matlab software was used for modeling and forecasting of prospective data with high sensitivity in thermal systems. Surfer and ArcGIS software were used to create humidity, temperature, solar radiation maps for Turkey. Root mean square error (RMSE), mean absolute error and (MAE), coefficient of variation (COV) and the coefficient of determination (R2) were used to validate the result of the proposed approaches. The results were satisfactory with respect to RMSE, MAE, COV and R2 to forecast the meteorological data. Annual solar power potential maps for Turkey were also proposed and compared with MGM results. The results of the proposed approaches are compatible with the result of the MGM. The Turkey policy maker(s) from MGM can easily use these approaches if a software is constructed.
AtıfScopus66WoS52OpenAlex68İncele - MakaleAçık Erişim2018Scopus SJRQ1New zircon U-Pb LA-ICP-MS ages and Hf isotope data from the Central Pontides (Turkey): Geological and geodynamic constraints
Çimen, Okay; Göncüoğlu, M. Cemal; Simonetti, Antonio; Sayit, Kaan
The Central Pontides in northern Anatolia is located on the accretionary complex formed by the closure of Neotethyan Intra-Pontide Ocean between the southern Eurasian margin (Istanbul-Zonguldak Terrane) and the Cimmerian Sakarya Composite Terrane. Among other components of the oceanic lithosphere, it comprises not yet well-dated felsic igneous rocks formed in arc-basin as well as continent margin settings. In-situ U-Pb age results for zircons from the arc-basin system (öangaldağ Metamorphic Complex) and the continental arc (Devrekani Metadiorite and Granitoid) yield ages of 176 ± 6 Ma, 163 ± 9 Ma and 165 ± 3 Ma, respectively. Corresponding in-situ average (initial) 176Hf/177Hf initial ratios are 0.28261 ± 0.00003, 0.28267 ± 0.00002 and 0.28290 ± 0.00004 for these units and indicative of a subduction-modified mantle source. The new U-Pb ages and Hf isotope data from these oceanic and continental arc units together with regional geological constraints support the presence of a multiple subduction system within the Intra-Pontide Ocean during the Middle Jurassic.
AtıfScopus39OpenAlex32İncele - MakaleYalnız künye2018Scopus SJRQ1An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: The case of ship loader
Celik, Erkan; Akyuz, Emre
Duration of cargo operation (loading or discharging) is of paramount importance for ship owners and port managers since idle time at terminal significantly boost to the cost of providing shipping service. Hence, it is important to choose the appropriate shiploader type for handling bulk materials. This paper aims to present a comprehensive multi-criteria decision making (MCDM) method extended by interval type-2 fuzzy sets (IT2FSs) for selecting appropriate shiploader type in maritime transportation. The proposed approach incorporates Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under IT2FSs environment to overcome more of the uncertainty of experts’ judgement and expression in decision-making. The proposed approach adopts a sensitivity analysis to investigate the impact of key performance indicator (KPI) under numerous conditions. Besides its robust theoretical background, this paper prompts practical benefits to decision-makers (port owners or port managers) who make investment decision for appropriate shiploader type in dry bulk cargo shipment.
AtıfScopus165WoS148OpenAlex172İncele - MakaleYalnız künye2018Scopus SJRQ2A novel wavelet sequences based on deep bidirectional LSTM network model for ECG signal classification
Yildirim, Özal
Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems.
AtıfScopus807WoS607OpenAlex837İncele - MakaleAçık Erişim2017Scopus SJRQ1Application of AHP and VIKOR methods under interval type 2 fuzzy environment in maritime transportation
Soner, Omer; Celik, Erkan; Akyuz, Emre
The aim of this paper is to provide not only a hybrid theoretical methodology in multiple-attribute decision making problems but also a practical application in maritime transportation industry. The proposed hybrid approach integrates Analytic Hierarchy Process (AHP) method into VlseKriterijumska Optimizacijia I Kompromisno Resenje, (VIKOR) technique under interval type-2 fuzzy (IT2F) environment. While AHP and VIKOR provides a comprehensive framework to solve multiple-attribute decision making (MADM) problems in maritime transportation industry, the IT2F enables to deal with much uncertainty during linguistic assessment of decision-makers. The proposed approach is demonstrated with a hatch cover design selection problem since it has utmost importance in structure of bulk carrier ships to prevent water ingress and protect cargo form the external damages. Besides its robust theoretical insight, the paper has practical contribution to the naval engineers, classification societies and ship owners who have difficulty in deciding appropriate hatch cover type during construction of the ship.
AtıfScopus117WoS103OpenAlex122İncele - BildiriAçık Erişim2017Economic Analysis of Hybrid Renewable Energy Systems with V2G Integration Considering Battery Life
Baloglu, Ulas Baran; Demir, Yakup; Caetano, N.S.; Faculty of Engineering University of Porto (FEUP), LEPABE, Rua Dr. Roberto Frias, Porto; Polytechnic Institute of Porto (IPP), CIETI, School of Engineering (ISEP), Rua Dr. Antonio Bernardino de Almeida 431, Porto; Felgueiras, M.C.; Forment, M.A.
Hybrid renewable energy systems considered as candidate solutions for environmental problems. Solar energy and wind energy are important components of these systems, but both of them cause fluctuations in the grid. Batteries of Electric Vehicles (EVs) can be connected to the grid to create an ancillary resource. These systems known as Vehicle to Grid (V2G) and they could be the most suitable solution to the fluctuation problems of renewable resources. In this paper, economic analysis of V2G is investigated from various perspectives. The findings of this study indicate that battery aging costs of a V2G system can be minimized with an intelligent energy management system, and these systems are both economically and environmentally better alternatives to fossil-fuelled generators.
AtıfScopus15WoS13OpenAlex16İncele - MakaleYalnız künye2017Scopus SJRQ1Biodegradation of hydroxyapatite coated Rex-734 alloy with silver and selenium/chitosan substitutions: In vitro analysis
Aksakal, B.; Say, Y.; Buyukpinar, Ç.; Bakirdere, S.
Hydroxyapatite (HA) based bioceramic coatings; such as single-HA, double layered with Silver-Ag, Selenium-Se and Chitosan substitutions on Rex-734 alloy were executed by using the sol-gel method. Surface morphologies and adhesion strengths of the obtained coatings were investigated and coating material weight losses and metal ion releases from the substrates were determined in SBF (Simulated Body Fluid) environment. The coatings were characterized by SEM, EDS, XRD and adhesion strengths between the substrate and bioceramic coatings were measured with adhesion tests. SEM analyses revealed that crack-free surface morphologies were obtained in all bioceramic coatings. The coatings were kept in SBF for immersion periods from one to four weeks and the weight loss (%) in coatings and changes in ion release rates were determined. HA/Ag double layered coatings applied on the Rex-734 alloy increased the adhesion strength and accordingly reduced the weight losses (%) of coating materials in SBF. Se/Chitosan double layered coatings were found to decrease the adhesion strength and increase the weight losses (%) in SBF. Additionally, all bioceramic coatings were observed to prevent the elemental ion release by physical barrier effect for the release of metal ions during the four weeks immersion period in SBF.
AtıfScopus12WoS11OpenAlex12İncele - MakaleYalnız künye2017Scopus SJRQ1Mechanical and fracture characteristics of self-compacting concretes containing different percentage of plastic waste powder
Gesoglu, Mehmet; Güneyisi, Erhan; Hansu, Osman; Etli, Serkan; Alhassan, Mahammed
This study addresses the mechanical and fracture properties of self-compacting concretes (SCCs) containing plastic waste (PW) powder in varying amounts used as a cement replacement material. Partial amount of cement was replaced by PW powder at 5%, 10%, 15%, 20% and 25% by weight so as to design six SCC mixtures with a constant slump flow of 700 ± 30 mm, total binder content of 550 kg/m3 and water-to-binder (w/b) ratio of 0.35. Mechanical characteristics of SCCs were tested for compressive and splitting tensile strengths, net flexural strength as well as modulus of elasticity at 28 day. Moreover, failure characteristics of the concrete were monitored via three-point bending test on the notched beams. The findings indicated that mechanical properties of PVC powder modified SCCs decreased while the concretes became less brittle.
AtıfScopus125WoS96OpenAlex136İncele - MakaleYalnız künye2017Scopus SJRQ1A cause and effect relationship model for location of temporary shelters in disaster operations management
Celik, Erkan
The aim of the location of temporary shelter directly is to focus on helping the sufferers and injured people on disaster areas during and after a disaster. Facility location (location of temporary shelters) decisions play a critical role and affect directly performance of relief operations in disaster operations management (DOM). In this paper, a proactive decision-making tool by integrating decision-making trail and evaluation laboratory (DEMATEL) method with interval type-2 fuzzy sets (IT2FSs) is proposed to locate of temporary location in DOM. While DEMATEL method enables to analyse cause and effect relationship in decision-making process, the IT2FSs overcome ambiguity and vagueness of linguistic assessment of decision-makers through the DEMATEL. 14 different criteria for location of temporary shelters are considered by 9 disaster operation managers for evaluating the cause and effect factors. Beside the theoretical contribution of the proposed method, it provides practical benefits to disaster operation managers to perceive cause and effect relationship on location of temporary shelters.
AtıfScopus38WoS29OpenAlex41İncele - MakaleYalnız künye2017Scopus SJRQ1The effect of Zirconia/Yttria/Silver substitutions on mechanostructure and cell viability of the synthesized bioceramic bone grafts
Aksakal, Bunyamin; Demirel, Mehtap
Hydroxyapatite (HA) based biografts were synthesized by substitution of Zirconia (Zr), Yttria (Y2O3) and Silver (Ag) using the sol-gel method. Fabricated bone grafts (H40ZrYt and H50Yt10) were compared with a control biograft. The effects of Zr and Y2O3 and Ag additions on the morphological, mechanical and cell viability of the synthesized biografts were analyzed. The biografts were characterized by X-ray Diffractometer (XRD) and Scanning Electron Microscope (SEM). All biografts were then embedded into the drilled holes (D=3.2 mm) in rabbit femurs. The rabbits were then sacrificed after twelve weeks. Three-point bending (3-PB) tests were conducted on defected and grafted regions. Flexural strength values were found to be 347, 149 and 180 MPa, for the H40ZrYt, H50Yt10 and the control/commercial graft, respectively. Cell viability results indicated that the percentage viability ratios slightly increased after the substitution of Ag into the H50Yt10 biograft at 0.1 and 0.3 µg/ml concentrations and into the H40ZrYt biograft at a 0.1 µg/ml concentration. Although the cell viability was a bit lower in the H50Yt10 graft, the H40ZrYt graft achieved better results compared to the counterpart grafts. Furthermore, the hardness of both of the novel fabricated grafts were found to be higher than the control/commercial graft, however, as the flexture strength of H40ZrYt was higher but H50Yt10 was lower than the control/commercial graft.
AtıfScopus11WoS10OpenAlex13İncele