Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Araz, Onur(15)
- Ozturk, Samet(14)
- Ozyurt, E.(9)
- Turk, Veysel(9)
- Reis, Hatice Catal(7)
- Beder, Murat(6)
- Erdogdu, Ferruh(6)
- Peker, Iskender(6)
- Erol, Ismail(5)
- Kaygusuz, Abdullah(5)
- Ozturk, Kasif Furkan(5)
- Wang, Y.C.(5)
- Akpinar, Adem(4)
- Akçay, Serhatcan Berk(4)
- Coskun, Eda(4)
- Kankal, Murat(4)
- Kaya, Selim(4)
- Liu, Shuxiang(4)
- Ozden, Talat(4)
- Seferoğlu, Mehmet Tevfik(4)
- Varol, Temel(4)
- Öztürk, Serkan(4)
- Akinoglu, Bulent G.(3)
- Alemdag, Selcuk(3)
- Arslan, Mehmet(3)
- Cakir, Tufan(3)
- Gurocak, Zulfu(3)
- Gücer, Mehmet Ali(3)
- Günen, Mehmet Akif(3)
- Kaya, Ali(3)
- Mert, Behic(3)
- Mızrak, Sefa(3)
- Saydam Eker, Çiğdem(3)
- Tasci, Caner(3)
- Çelik, Necati(3)
- Ünlü, Ramazan(3)
- Şan, Murat(3)
- Akpinar, A.(2)
- Akpinar, Merve(2)
- Aksa, Hüseyin Can(2)
Yayınlar
- MakaleYalnız künye2023SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data
Özdemir, Samed; Yavuzdoğan, Ahmet; Bilgilioğlu, Burhan Baha; Akbulut, Zeynep
Decentralized solar PhotoVoltaic (PV) is one of the most promising energy sources for cities and individuals pursuing energy self-sufficiency. Especially, the already available rooftop surfaces are a major contributor to push for rooftop mounted PV systems. However, accurate PV potential estimation of individual buildings is still a challenging task since many parameters must be considered such as meteorological factors, panel technology, geographical location, available roof surface area, surface azimuth and tilt angle. In this study, we created an efficient approach that can be used for roof surface's PV potential estimation based on point cloud data and capable of processing various scales from single building to city scale. In the proposed approach, each roof surface's features were utilized for PV potential estimation by employing the PVGIS database. PV potential estimation was carried out on daily, monthly, and annual periods to provide a better estimation. Also, we developed a flexible and easy to use open-source plugin based on the QGIS software for rooftop mounted PV potential estimation capable of estimating every roof surface's PV potential. The method was tested on 80 buildings selected from ROOFN3D dataset. The proposed approach achieved an overall accuracy of 84% and an F1 score of 0.92.
- MakaleYalnız künye2023Hydrocarbon reservoir depth identification in the eastern black sea basin: Implications from euler deconvolution and gravity tensor invariants
Doğru, Fikret; Maden, Nafiz
The Black Sea Basin (BSB) consisting of Eastern Black Sea (EBS) and Western Black Sea (WBS) basins which separated by the Mid Black Sea High (MBSH) is formed by the collision of Eurasia and Arabian-African Plates. Petroleum and gas hydrate contents of the BSB have been discussed by using different geological and geophysical research. In this study, the gravity gradient tensor and invariant data based on the Bouguer gravity anomaly of the EBS basin were evaluated to define the hydrocarbon reservoirs. Afterwards, Euler deconvolution technique is applied to the invariant to reveal the depth of subsurface bodies. Furthermore, the significant invariant anomalies are compared with known oil seepage and petroleum wells. The depth values of oil trace closest to the known Sürmene and Hopa drill holes were computed as 4809 m, and 4455 m according to the structural index values of SI = 2.
- MakaleYalnız künye2023Microwave decontamination processing of tahini and process design considerations using a computational approach
Topcam, Huseyin; Coskun, Eda; Son, Ezgi; Kutuk, Dilay; Aytac, S. Aykut; Mert, Behic; Ozturk, Samet; Erdogdu, Ferruh
Tahini, as a low moisture food product, is linked to several outbreaks of Salmonella recently even though a high temperature roasting (of sesame seeds) through its production is involved. Therefore, a final decontamination approach might be required for safety. Considering its higher oil content and lower thermophysical properties, conventional approaches are not easy to apply while preserving the quality attributes. Therefore, microwave heating was used for decontamination purpose. For this purpose, a computational mathematical model was developed first to determine the temperature distribution of tahini during microwave heating, and microbial inactivation studies for Salmonella enteritidis (ATCC 13076) were carried out. Changes in color and peroxide values were evaluated, and the experimentally validated model was further used to design an industrial process to achieve a 5-log cycle reduction as an efficient decontamination processing. The target temperature over 80 °C within the sample was demonstrated to achieve such a process, and industrial scale process conditions were presented for 262 kg/h process capacity.
- MakaleYalnız künye2023Optimum tuned tandem mass dampers for suppressing seismic-induced vibrations considering soil-structure interaction
Araz, Onur; Noroozinejad Farsangi, Ehsan
In recent studies, it has been stated that tuned tandem mass dampers (TTMD) will be a practical mechanical solution to reduce the dynamic responses of structures under seismic excitations. However, since TTMD is tuned based on the dominant frequency of the superstructure, ignoring the soil-structure interaction (SSI), it may cause a notable deterioration in the control performance of the control devices. Thus, a methodology for the optimum design of TTMD positioned on the top story of a high-rise building due to near-fault pulse-like ground motions considering potential SSI effects has been investigated in this paper. Firstly, the TTMD is located on the top story of a well-known 40-story shear building, and the equations of motion for soil-structure-TTMD interaction are derived. Based on the sequential quadratic programming (SQP), the tuning parameters of TTMD are then found for different support conditions in the frequency domain. The efficiency of SQP is also compared with two meta-heuristic algorithms (i.e., simulated annealing and pattern search algorithms). The effectiveness of optimum TTMD is tested using 30 near-fault pulse-like ground motions using time-domain analyses. Numerical results showed that the optimum TTMD is more effective in suppressing the maximum displacement and inter-story drift of the building, considering SSI. It is also found that the frequency content of the earthquake, as well as the pulse period of the earthquake and soil type, has a significant effect on the control performance of the TTMD.
- MakaleYalnız künye2023Trend analysis of precipitation using innovative approaches in northwestern Turkey
Körük, Ali Emre; Kankal, Murat; Yıldız, Mehmet Berkant; Akçay, Fatma; Şan, Murat; Nacar, Sinan
Precipitation is highly sensitive to climate change, and monitoring its trends over time is essential for understanding the effects of global warming on the Earth's water cycle. This study investigates the effects of climate change on monthly precipitation in the Susurluk Basin located in northwestern Turkey, using innovative trend analysis methods. Innovative Polygon Trend Analysis (IPTA) using star graphics and Improved Visualization for Innovative Trend Analysis (IV-ITA) techniques were used to analyze precipitation data from nine stations in the basin over 50 years (1970–2019), and the findings were compared to classical Mann-Kendall (MK) results. According to the trend analysis results, the MK method detected significant trends in only two months in the decreasing direction. In these decreasing trends observed at Simav and Keles stations in November, z values were calculated as −2.38 and −2.05, respectively. IPTA method detected increasing trends in 54 months and decreasing trends in 40 months; this means there is a change of more than 5% between two half series. The IV-ITA method indicated an increase of more than 40% in the low values for January, March, August, and September. In addition, there was an increasing trend of more than 40% in the high values observed in September at all stations. It was observed that mean precipitation heights increased from September to December and then decreased throughout the basin. It is predicted that decreases in precipitation during dry seasons may put intense pressure on agricultural water use and affect water quality. In addition, the increase in precipitation in spring months may increase flood events. It was determined that graphical innovative trend analysis methods are more effective in trend identification than MK, and these methods' results have much higher visual inspection and linguistic interpretation possibilities. Innovative methods allow for more flexible and in-depth analysis using different statistical parameters.
- MakaleAçık Erişim2023A comparative study of evolutionary computation and swarm-based methods applied to color quantization
Pérez-Delgado, María-Luisa; Günen, Mehmet Akif
Color Quantization (CQ) is a complex and hard problem because selecting the best set of colors from many available colors and using that set to obtain a good quality image is an NP-complete problem. The use of evolutionary computation and swarm-based methods to solve search and optimization problems has increased dramatically in recent years. This article compares some of these methods in order to solve the CQ problem. The following methods were used to generate CQ images: Particle swarm optimization, Artificial bee colony, Adaptive differential evolution, Success-history based adaptive differential evolution (with and without linear population size reduction), Cuckoo search, Firefly algorithm and Shuffled-frog leaping algorithm. For the first two methods, two variants were considered. Thus, a total of ten metaheuristics were compared with four classical CQ methods (Variance-based, Median-cut, Binary splitting and Wu's methods) applying them to a set of benchmark images and considering four different palette sizes (32, 64, 128, and 256 colors). Three error measures were considered to compare the methods: the mean squared error, the mean absolute error and the peak signal-to-noise ratio. Some of the swarm-based methods analyzed include a recently proposed CQ method using ants. Although they have a slow computational speed in the experimental studies, the ant-based methods are significantly better than all other methods according to the Wilcoxon signed rank test. In general, despite their speed, classical methods underperform the other ten methods both qualitatively and quantitatively.
- MakaleYalnız künye2023Immunogenic evaluation of multi-epitope peptide-loaded PCPP microparticles as a vaccine candidate against Toxoplasma Gondii
Yilmaz-Ozturk, Rabia; Calik, Hilal; Yaman, Serkan; Ustun-Karatop, Eslin; Cakir-Koc, Rabia
Toxoplasmosis is a major health problem and socioeconomic burden, affecting around 30–50% of the global population. Poly(dicarboxylatophenoxy)phosphazene (PCPP) polymer was chosen as adjuvant for the immunogenic peptide antigen. Peptide-loaded PCPP microparticles were synthesized via the coacervation method and the characterization studies of microparticles were conducted to determine their size, charge, morphology, encapsulation efficacy, and loading capacity. To evaluate in vivo efficacy of the vaccine candidate, Balb/c mice were immunized with the formulations. Brain and spleen tissues were isolated from animals to investigate cytokine levels, lymphocyte proliferation, and brain cyst formation. As a result, antibody and cytokine responses in groups immunized with peptide-loaded PCPP microparticles were found to be significantly higher when compared to the control group. In conclusion, our novel multi-epitope peptide-loaded PCPP microparticle-based vaccine formulation demonstrated considerable humoral and cellular immune responses against T. gondii and protected mice against T. gondii infection during Toxoplasmosis.
- MakaleYalnız künye2023Detection of forest fire using deep convolutional neural networks with transfer learning approach[Formula presented]
Reis, Hatice Catal; Turk, Veysel
Forest fires caused by natural causes such as climate change, temperature increase, lightning strikes, volcanic activity or human effects are among the world's most dangerous, deadly, and destructive disasters. Detection, prevention, and extinguishing forest fires is challenging. In addition, forest fires can cause habitat destruction that cannot be controlled in time and cause great material and moral losses. Therefore, fast and accurate Detection of forest fires is vital in emergency response. Here, in solving the problem, the transfer learning method from deep learning sub-topics can be used, which allows the application of pre-trained networks to a new problem. The Fire Luminosity Airborne-based Machine learning Evaluation dataset (consisting of forest fire images) obtained by Unmanned Aerial Vehicle was used in this study. In the Detection of forest fire images in the dataset, InceptionV3, DenseNet121, ResNet50V2, NASNetMobile, VGG-19 deep learning algorithms, transfer learning techniques that can produce more successful results than networks trained from scratch, and hybrid proposed with Support Vector Machine, Random Forest, Bidirectional Long Short-Term Memory, Gated Recurrent Unit algorithms methods have been applied. In the classification study with the Fire Luminosity Airborne-based Machine learning Evaluation dataset in performance measurement, 97.95% accuracy was obtained from the DenseNet121 model, which was started with random weights. In the transfer learning study using ImageNet weights, satisfactory results were obtained with 99.32% accuracy in the DenseNet121 model. We anticipate that working in forest fire detection and response can be entirely satisfactory.
- MakaleYalnız künye2023Fixed-time neuro-sliding mode controller design for quadrotor UAV transporting a suspended payload
Bingöl, Özhan; Güzey, Hacı Mehmet
This study develops a fixed-time neuro-sliding mode controller to enhance the transient response and robustness of a quadrotor that is subjected to external disturbances and parameter uncertainties along with the dynamics of a suspended payload. A simple neural network with a fixed-time adaptive law is used to estimate unknown dynamics; therefore, no previous knowledge of dynamics is required to develop controllers. The neural network component will also help to eliminate the chattering effect of the sliding mode controller through its learning structure. Fixed-time convergence to desired trajectories is proven by detailed theoretical analysis based on the Lyapunov stability theorem, and to show the proposed controller's effective performance, thorough numerical simulations are run.
- MakaleAçık Erişim2023Performance analysis of digitally controlled nonlinear systems considering time delay issues
Yanarateş, Cağfer; Okur, Serkan; Altan, Aytaç
In this paper, a comprehensive investigation into discretization, effective sample time selection considering delays in the system, and time and frequency domain analysis of a DC-DC buck converter, which plays a vital role in photovoltaic (PV) systems, is conducted to enhance the understanding of their dynamic behavior, optimize control algorithms, improve system efficiency, and ensure reliable power conversion in photovoltaic applications. To effectively address the non-linear behavior and enhance digital control of a buck converter by selecting the best sample time, several approaches can be employed. These include accurate modeling and identification of non-linear elements, development of advanced control algorithms that account for non-linearities, implementation of adaptive control techniques, and utilization of feedback mechanisms to compensate for deviations from linearity. By considering and mitigating the non-linear behavior, digital control systems can achieve improved accuracy, stability, and transient behavior in regulating the buck converter's output waveforms (voltage or current). The results of the study demonstrated that the trapezoidal integration method which is also known as bilinear approximation, or Tustin's approach outperformed other commonly used discretization methods, such as first-order hold (FOH), zero-order hold (ZOH), impulse response matching (impulse invariant), and matched pole-zero (MPZ) technique, in dual-domain (both time and frequency) analysis. The key finding highlighting the superiority of the bilinear approximation was its ability to achieve the closest match in the frequency domain bridging the continuous-time and discrete systems. This finding emphasizes the significance of the bilinear approach in preserving the frequency characteristics of the original continuous-time system during discretization. By employing this method, the discrete system closely approximated the behavior of its continuous-time counterpart, ensuring accurate frequency-domain representation.
- MakaleYalnız künye2023Excessive groundwater withdrawal and resultant land subsidence in the Küçük Menderes River Basin, Turkey as estimated from InSAR-SBAS and GNSS measurements
Yalvaç, Sefa; Alemdağ, Selçuk; Zeybek, Halil İbrahim; Yalvaç, Murat
Küçük Menderes River Basin (KMRB) is located in the western part of Turkey in the city of İzmir. The basin hosts about half a million people and 90% of the population makes their living from farming and animal husbandry. Most of the water needs for agricultural irrigation, animal husbandry, and drinking are met from groundwater resources in the basin. Since the water pumped from the aquifers cannot be naturally recharged by surface waters and precipitation, the groundwater level is rapidly receding and a decrease of up to 150 meters has been observed in the historical groundwater level time series since the 1990s. For this reason, land subsidence occurred in the basin and as a result of this, crustal surface cracks have formed and infrastructure and superstructure facilities have been endangered. To prevent loss of life and property that may occur in the future, it has become necessary to estimate the magnitude and the expansion zone of the land subsidence by carrying out geodetic monitoring studies in the region. In this study, the analyzes performed by Interferometric Synthetic Aperture Radar-Small Baseline Subset (InSAR-SBAS) and Global Navigation Satellite System (GNSS) methods to monitor land subsidence in the KMRB are presented. For this purpose, monthly 74 SAR images from 2017 to the end of 2022 were evaluated according to the SBAS procedure in the GMTSAR academic analysis software. In order to, both validate the InSAR-SBAS results and convert the deformation rate in the Line of Sight (LOS) to the ellipsoid normal direction, 3 periods of GNSS campaign were performed between 2021 and 2023 in 5 different GNSS stations and evaluated with the GAMIT/GLOBK software. According to the analyses, the land subsidence rate of up to −165 mm/year has been estimated in the KMRB, especially in the district centers of Bayındır and Ödemiş. In addition, unlike many studies, different rates and propagation of subsidence were determined in different parts of the basin depending on the aquifer type and precipitation. Monthly time series of the deformations were created and the behavior of the deformations and its relationship with the groundwater withdrawal and the lithological structure in the region was scrutinized. Thus, the spatio-temporal behaviour of the land subsidence and the associated geological factors were revealed.
- MakaleAçık Erişim2023Understanding university students WHO do not want to volunteer in disasters: A qualitative study from Türkiye
Demirbilek, Ömer; Öztürk, Serkan
A functional and sufficient volunteer community is needed to reduce the damage of disasters and to have a rapid response and recovery process. Most of the volunteering studies in disasters in the literature focus on the positive side of the volunteering process, but there are many negative points that prevent individuals from volunteering in disasters. In this research, it is aimed to discover why university students, who are one of the most valuable groups in volunteering in disasters, do not volunteer in disasters. The research was conducted with a phenomenological design. Maximum variation and criterion sampling were used to decide the study group. The study group consists of thirteen university students with distinctive characteristics. The interview method was used as the data collection technique, and the semi-structured interview form developed by the researchers was used as the data collection tool. Thematic analysis was conducted with the MAXQDA 2020 qualitative analysis program on the obtained data. As a result of the data analysis, seven themes appeared, consisting of İnformation, Economy, Interpersonal Bonds, Uncertainties, Individual Characteristics, Perceptions of Volunteering, Promotion and Advertising Activities. Finding the negative aspects of volunteering that distracts young people from volunteering will be one of the best preparations for future disasters.
- MakaleAçık Erişim2023Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements
Bowler, Alexander; Ozturk, Samet; di Bari, Vincenzo; Glover, Zachary J.; Watson, Nicholas J.
In manufacturing environments, real-time monitoring of yoghurt fermentation is required to maintain an optimal production schedule, ensure product quality, and prevent the growth of pathogenic bacteria. Ultrasonic sensors combined with machine learning models offer the potential for non-invasive process monitoring. However, methods are required to ensure the models are robust to changing ultrasonic measurement distributions as a result of changing process conditions. As it is unknown when these changes in distribution will occur, domain adaptation methods are needed that can be applied to newly acquired data in real-time. In this work, yoghurt fermentation processes are monitored using non-invasive ultrasonic sensors. Furthermore, a transmission based method is compared to an industrially-relevant non-transmission method which does not require the sound wave to travel through the fermenting yoghurt. Three machine learning algorithms were investigated including fully-connected neural networks, fully-connected neural networks with long short-term memory layers, and convolutional neural networks with long short-term memory layers. Three real-time domain adaptation strategies were also evaluated, namely; feature alignment, prediction alignment, and feature removal. The most accurate method (mean squared error of 0.008 to predict pH during fermentation) was non-transmission based and used convolutional neural networks with long short-term memory layers, and a combination of all three domain adaption methods.
- MakaleAçık Erişim2023Near-infrared spectroscopy and machine learning for classification of food powders during a continuous process
Ozturk, Samet; Bowler, Alexander; Rady, Ahmed; Watson, Nicholas J.
In food production environments, the wrong powder material is occasionally loaded onto a production line which impacts food safety, product quality, and production economics. The aim of this study was to assess the potential of using Near Infrared (NIR) spectroscopy combined with Machine Learning to classify food powders under motion conditions. Two NIR sensors with different wavelength ranges were compared and the ML models were tasked with classifying between 25 food powder materials. Eleven different spectra pre-processing methods, three feature selection methods, and five algorithms were investigated to find the optimal ML pipeline. It was found that pre-processing the spectra using autoencoders followed by using support vector machines with the all spectral wavelengths from both sensors was most accurate. The results were improved further using under-sampling and boosting. Overall, this method achieved 99.52, 97.12, 94.08, and 91.68% accuracy for the static, 0.017, 0.036 and 0.068 m s-1 sample speeds. The models were also validated using an independent test sets.
- DüzeltmeAçık Erişim2023Corrigendum to Understanding university students WHO do not want to volunteer in disasters: A qualitative study from Türkiye [Int. J. Disaster Risk Reduc. 96 (2023) 103994] (International Journal of Disaster Risk Reduction (2023) 96, (S2212420923004740), (10.1016/j.ijdrr.2023.103994))
Demirbilek, Ömer; Öztürk, Serkan
The authors would like to add the below sentence in the Acknowledgment section. This study was produced from a doctoral thesis. The authors would like to apologise for any inconvenience caused. Ömer Demirbilek completed his undergraduate and graduate education in disaster management. He is currently pursuing his doctorate in disaster management. He works as a lecturer in the Disaster Management Department of Sinop University. Her areas of interest are disaster education, management, and volunteering in disasters. He has works published in international books and journals.
- MakaleYayıncıda açık erişim2022Technical potential of rooftop solar photovoltaic for Ankara
Kutlu, Elif Ceren; Durusoy, Beyza; Ozden, Talat; Akinoglu, Bulent G.
Turkey, which has immense solar potential, has recently shifted towards solar energy and new renewable energy deployment regulations, including implementation and commercializing rooftop PV technologies. Thus, these require a detailed assessment to determine the power source's capability and convince the policymakers. To the authors' best knowledge, there is no available data or a city-based study for the rooftop PV potential in Turkey. Here, we present the first city-based rooftop PV potential study in Ankara. The technical PV potential calculations are sensitive to the suitable area ratio, module efficiency, and module area assumptions. This study proposes a new, free, reliable, and open-source model for estimating the rooftop PV potential, and it is adaptable to every roof type. The suitable roof area for PV panels is calculated using Helioscope software. Five different modules with different efficiencies and module sizes are modelled in Helioscope. The results showed that Ankara's total technical PV potentials for residential, public, and commercial buildings are 1.15 TWh/year, 55 GWh/year, and 26.8 GWh/year, respectively. Best results are obtained by Mono-Si Halfcut (M2) and Thin Film (M5) modules in residentials, M2 and Mono-Si Bifacial Modules (M3) in Public and Commercial Buildings.
- MakaleAçık Erişim2022Continuous flow microwave processing of peanut butter: A (hypothetical) computational process design study with experimental validation
Coskun, Eda; Ozturk, Samet; Topcam, Huseyin; Karatas, Ozan; Li, Rui; Wang, Shaojin; Mert, Behic; Erdogdu, Ferruh
The increase in foodborne pathogen cases in low moisture foods has raised a significant food safety concern for food industry. One of the most significant outbreaks related with these food products was observed in 2008–2009 due to Salmonella problem in peanut butter. This issue was recently observed again for a multinational case. Challenges of conventional thermal processing due to the lower thermal conductivity – diffusivity value and higher viscosity, microwave (MW) heating might be an efficient processing while the non-uniform heating is a challenging drawback. Therefore, the objective of this study was to develop a mathematical model for MW processing of peanut butter and present industrial scale designs for continuous flow processing. For this purpose, the mathematical model was first experimentally validated using a lab-scale system and validated with experimental data. Following this, continuous flow MW process design studies were carried out with different holding tube configurations to obtain a temperature increase to enable decontamination and improve the temperature uniformity. These design simulations provided a better understanding to enhance the process efficiency of high viscosity low moisture peanut butter samples and for design and optimization of continuous flow MW processing.
- Derleme MakaleYalnız künye2022Comprehensive review on distributed maximum power point tracking: Submodule level and module level MPPT strategies
Başoğlu, Mustafa Engin
Maximum power point tracking (MPPT) procedure in photovoltaic (PV) systems can be realized with many different methods. Especially in arrays consisting of PV modules (PVMs) connected in series; the maximum power point (MPP) may change due to partial shading conditions (PSC), aging, degradation, fabrication production differences etc. In addition, even in small power systems containing a single PVM, the difference in shading and irradiation between submodules affects the maximum power potential of the PVM. In this study, power electronics-based power processing methods in distributed MPPT (DMPPT) systems are emphasized. Power electronics-based hardware MPPT solutions are examined in two groups as full power processing (FPP) and differential power processing (DPP). In addition, commercially available power optimizers have been examined under many criteria. The literature on the subject has been analyzed in a broad perspective, and it has been comprehensively evaluated according to criteria such as power processing level, converter configuration, MPPT algorithm, MPPT application level and control approaches. This study is an important guide for scientists and hardware engineers doing academic studies on the subject. This study, which examines the topologies and control approaches used in application-oriented studies, has the feature of triggering future studies. The features that commercial power optimizers should have and the examination of the products in the market within the framework of some criteria is one of the original aspects of the study. It is expected that this study will contribute to the PV industry in building applied and building integrated studies, where extreme shading scenario occurs.
- MakaleYalnız künye2022Alleviating the Impact of the Barriers to Circular Economy Adoption Through Blockchain: An Investigation Using an Integrated MCDM-based QFD With Hesitant Fuzzy Linguistic Term Sets
Erol, Ismail; Murat Ar, Ilker; Peker, Iskender; Searcy, Cory
Despite its clear potential to contribute to sustainability, there are many challenges to adopting circular economy (CE). These barriers impede the implementation of CE; however, research to address them is ongoing. For example, novel technologies have become a key enabler for easing the impact of CE adoption barriers. Blockchain is one disruptive technology that has the potential to address some of those barriers, notably technological, organizational, and ecological. Blockchain is particularly well suited to help address supply chain-oriented barriers to CE adoption. However, a review of the literature shows that while there are a limited number of conceptual studies that address the capabilities of blockchain to alleviate the impact of the barriers to CE, no previous study has focused on this vital subject using a decision tool based on expert data. To this end, this paper proposes an integrated decision framework involving Multi-Criteria Decision-Making (MCDM)-based Quality Function Deployment (QFD) method with Hesitant Fuzzy Linguistic Term Sets (HFLTS) to investigate the true potential of blockchain to address the CE adoption barriers. Our findings indicate that enhanced supply chain traceability management, improved collaboration and coordination in supply chain ecosystems, building higher levels of trust in supply chain ecosystems, and enhanced business models are the most significant functions of blockchain to help overcome the CE adoption barriers.
- MakaleAçık Erişim2022The image of nursing among nursing and other healthcare professional university students: A mixed-method study
Apaydin Cirik, Vildan; Gül, Uğur; Aksoy, Bahar
Aim: This study had three objectives: (1) determining the image of nursing in the eyes of undergraduate health sciences students; (2) identifying factors affecting that image; and (3) evaluating students’ views and experiences regarding that image. Background: If healthcare students perceive nursing positively, it may result in directing future generations to nursing, and improving nursing, and reducing the need for nurses. Design: This study adopted an explanatory sequential design with participant selection variant. The design involved data collection in two consecutive phases. Methods: A mixed-method design using quantitative data and qualitative interviews was used. In the quantitative phase, a descriptive and cross-sectional research method was used. The qualitative phase was based on phenomenological research. The quantitative portion was performed with 1556 participants in their second, third or fourth year during the 2019–2020 academic year. Students were from the nursing, emergency and disaster management, nutrition and dietetics, occupational health and safety, health management, and social work departments. The qualitative portion was performed with 29 participant volunteers. Participants were interviewed on the phone. The data were collected using an introductory information form, a nursing image scale, and semi-structured interviews. The quantitative data were analyzed using descriptive statistics and the independent-samples t-test, Mann-Whitney U test, one-way ANOVA, and stepwise linear regression. The quantitative data were analyzed using thematic analysis. Results: There were significant relationships between participants' nursing image scale total scores and their department (p < 0.001), education year (p = 0.014), age (p = 0.032) and desire to recommend the nursing profession (p < 0.001). Nursing image scale total score was significantly higher in nursing departments than in other departments. Second-year participants and 18–20-year-olds had higher total scores than fourth-year participants and 21–23-year-olds, respectively, and those who would recommend the nursing profession had higher total scores than those who would not recommend it (p < 0.05). Analysis of the qualitative data produced six main themes: perceptions of the nursing profession, perceived nursing figure, nurse knowledge, relationship with healthcare professionals, reason for preference and job gender. Conclusion: This study employed a mixed-method design involving both quantitative and qualitative stages. The results highlighted the image of nursing and its significance in the eyes of prospective healthcare professionals. Detecting nursing image early can increase professional training and improve the professional image of nursing. We should take into account the factors that negatively affect the image of nursing to plan nursing education better in the future.