Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Uzun, Sevda(62)
- Merdan, Mehmet(58)
- Duran, Celal(50)
- Ozdes, Duygu(47)
- Kaygusuz, Abdullah(43)
- Ashyralyyev, Charyyar(38)
- Karsli, Orhan(33)
- Öztürk, Serkan(32)
- Araz, Onur(31)
- Demir, Selim(29)
- Kulakaç, Nurşen(29)
- Dokuz, Abdurrahman(28)
- Arslan, Mehmet(27)
- Baltacı, Cemalettin(27)
- Maden, Nafiz(27)
- Sipahi, Ferkan(27)
- Topal, Fevzi(27)
- Turan, Ibrahim(27)
- Kandemir, Raif(25)
- Kurt, Kemal(24)
- Ozturk, Samet(24)
- Peker, Iskender(24)
- Vural, Alaaddin(24)
- Reis, Hatice Catal(23)
- Yücel, Cem(23)
- Aydin, Faruk(22)
- Baltaci, Cemalettin(22)
- Gücer, Mehmet Ali(22)
- Günen, Mehmet Akif(22)
- Kankal, Murat(22)
- Topal, Meryem(22)
- Karimullah, Suud Sarim(21)
- Uysal, Ibrahim(20)
- Kurnaz, Muammer(19)
- Tuncer, Metin(19)
- Yolcu, Halil(19)
- Çelik, Necati(19)
- Ürkek, Bayram(19)
- Şan, Murat(19)
- Aliyazicioglu, Yuksel(18)
Yayınlar
- MakaleAçık Erişim2024Scopus SJRQ3PRODUCTION OF DEEP-FRIED WHEAT CHIPS USING PURPLE WHEAT FLOUR: PHYSICOCHEMICAL, TEXTURAL, SENSORY PROPERTIES AND OPTIMIZATION
Kaya, Şemsettin; Yuksel, Ferhat
The aim of this study was to develop alternative and healthy deep-fried chips by fortifying wheat chips with purple wheat flour (PWF). The effect of process variables (PWF content: 0-100%, frying temp. and time: 170-190 °C and 40-60 s) on the physicochemical, textural, instrumental color, sensorial properties, and optimization of the chips were investigated using response surface methodology. The levels of PWF in the chips receipt dramatically reduced oil uptake (by 23%), whereas the protein content of chips increased of the end products. The instrumental hardness of the enriched chips increased while sensory firmness decreased with increasing PWF. Generally, the chips enriched with PWF received the highest overall acceptability score by the panelists. Higher desirability (optimization results) and the process variables were determined as a 0.73 and 92.72 g/100g PWF, 170 °C, 40 s, respectively. These findings show that PWF can be easily incorporated into products that involve deep-fried chips.
AtıfScopus1WoS1
İncele - MakaleAçık Erişim2024Scopus SJRQ2Performance of different fibre types in alkaline-activated concrete produced with industrial wastes: volcanic rock powder and blast furnace slag
Aksüt, Yavuz Selim; Külekçi, Gökhan; Çullu, Mustafa; Yetgin, Şükrü
The objective of the study is to determine the effects of different fibre types and ratios on the mechanical and physical properties of alkali-activated concrete (AAC) and to optimise important properties such as workability, unit weight, water absorption, compressive strength, modulus of elasticity and abrasion resistance of these concretes. Concrete samples were produced using steel and polyester fibres at ratios of 0.25%, 0.50%, 0.75% and 1%. The fibre ratios were varied, and various tests were conducted to determine the mechanical and physical properties of the concrete samples. The experiments clearly revealed the effects of fibre types and ratios on the performance of concrete. These results clearly demonstrate the effects of different fibre types and ratios on the mechanical and physical properties of AACs. Particularly noteworthy is the water-retaining property of polyester fibres, their effect on workability and their enhancing effect on abrasion resistance. The effects of steel fibres on compressive strength and modulus of elasticity are more pronounced, but they may present disadvantages in terms of workability and abrasion resistance. It is observed that mixed fibre usage provides a good balance in some properties. This study provides a roadmap for evaluating sustainable material options in the concrete industry and guiding future research.
AtıfScopus4WoS3OpenAlex4İncele - MakaleAçık Erişim2024Scopus SJRQ2L0-Norm based Image Pansharpening by using population-based algorithms
Günen, Mehmet Akif; Pérez-Delgado, María-Luisa; Beşdok, Erkan
Earth observation satellites capture panchromatic images at high spatial resolution and multispectral images at lower resolution to optimize the use of their onboard energy sources. This results in a technical necessity to synthesize high-resolution multispectral images from these data. Pansharpening techniques aim to combine the spatial detail of panchromatic images with the spectral information of multispectral images. However, due to the discrete nature of these images and their varying local statistical properties, many pansharpening methods suffer from numerical artifacts such as chromatic and spatial distortions. This paper introduces the L0-Norm-based pansharpening method (L0pan), which addressed these challenges by maximizing the number of similar pixels between the synthesized pansharpened image and the original panchromatic and multispectral images. L0pan was optimized using a population-based colony search algorithm, enabling it to effectively balance both chromatic fidelity and spatial resolution. Extensive experiments across nine different datasets and comparison with nine other pansharpening methods using ten quality metrics demonstrated that L0pan significantly outperformed its counterparts. Notably, the colony search algorithm yielded the best overall results, highlighting the algorithm’s strength in refining pansharpening accuracy. This study contributed to the advancement of pansharpening techniques, offering a method that preserved both chromatic and spatial details more effectively than existing approaches.
AtıfScopus7OpenAlex5İncele - MakaleAçık Erişim2024Scopus SJRQ2Impact of Preoperative Progressive Relaxation Exercises on Postoperative Pain, Comfort, and Recovery : A Randomized Controlled Trial
Kulakaç, Nurşen; Sayılan, Aylin Aydın
This randomized controlled trial aimed to investigate the impact of preoperative progressive relaxation exercises on postoperative pain, comfort, and quality of recovery. The study was conducted between June and November 2023, involving 68 patients undergoing surgical intervention and hospitalized in the surgical clinic. Data were collected using the Personal Information Form, the Visual Analog Scale (VAS)-Pain, the Perianesthesia Comfort Scale, and the Quality of Recovery Questionnaire. At the sixth postoperative hour, no significant difference was observed in pain levels between the experimental and control groups (P > .05). However, the VAS scores for the experimental group at the 12th and 24th postoperative hours were significantly lower than those of the control group (P < .001). Furthermore, 24 hours postoperatively, the experimental group demonstrated significantly higher quality of recovery (P < .001) and comfort levels (P < .001) than the control group. This study concludes that patients engaged in relaxation exercises exhibited lower VAS scores and higher levels of recovery and comfort.
AtıfScopus2WoS1OpenAlex3
İncele - MakaleAçık Erişim2024EVALUATION OF CONSUMERS’ USE OF SMART ROBOTIC VACUUM CLEANERS UNDER EXTENDED EXPECTATIONCONFIRMATION MODEL; [VREDNOVANJE PROVEDENO MEĐU POTROŠAČIMA PAMETNIH ROBOTSKIH USISAVAČA U OKVIRU PROŠIRENOGA MODELA POTVRDE OČEKIVANJA]
Avci, Ibrahim; Kocan, Mahmut; Kirmizibiber, Ahmet
Purpose – The present research study extends the Expectation-Confirmation Model (ECM) by focusing on satisfaction, continuance intention, and recommendation intention among smart robotic vacuum cleaner users. The impacts of battery life concern and perceived privacy factors on satisfaction and continuance intention of the smart robotic vacuum cleaner were investigated by adding the variables of battery life concern, perceived privacy, and recommendation intention in the ECM. Design/methodology/approach – The participants of this study consisted of smart robotic vacuum cleaner users in Turkey. The snowball sampling method, as one of the non-random sampling methods, was used to reach the participants; data was collected using an online survey created with Google Forms, asking the participants to share the survey link with people around them who have smart robotic vacuum cleaners. A total of 218 smart robotic vacuum cleaner users participated in the study between March 1 and May 1, 2023. Findings and implications – Structural equation modeling (SEM) was used as the data analysis technique in the study. While the ECM was confirmed as a result of the SEM analysis, an important finding was that consumers with battery life concerns intend to continue using the smart robotic vacuum cleaner despite a negative relationship between battery life concern and satisfaction. While the effect of perceived privacy on continuance intention was not significant, satisfaction was found to have a significant effect on continuance intention. Given that rtificial intelligence-related businesses face fierce competition, organizations that wish to prosper in this environment must excel in a variety of areas, ranging from product design to marketing and from sales policies to post-sales assistance. Considering the findings, determining the factors that affect the satisfaction and intention to continue using robot vacuum cleaners will be a guide for smart robot vacuum cleaner manufacturers and marketers. At the same time, the fact that the issue has been investigated within the framework of a model will also make significant contributions to the literature. Limitations – Different factors influence smart robotic vacuum cleaner users’ satisfaction and desire to continue using them, but only battery-life concerns and perceived privacy variables were incorporated into the ECM model in this research study. Another limitation is connected to the research sample. Because the snowball sampling method was employed to obtain data for the research, its findings cannot be generalized as they cover only smart robotic vacuum cleaner users who participated in the survey. Originality/value – The ECM employed in the study was expanded by including the variables of battery-life concern, perceived privacy, and recommendation intention. A general lack of information among potential consumers regarding artificial intelligence and smart robotic vacuum cleaners, which is highly fascinating and a source of curiosity, as well as the lack of research on this issue in the literature, underscore the significance of this research study. By integrating and expanding the ECM for application to consumers using smart robotic vacuum cleaners, this study adds a fresh viewpoint to the literature.
AtıfOpenAlex1İncele - MakaleAçık Erişim2024Scopus SJRQ4Changes in acute and late toxicity and patient-reported health-related quality of life following radiotherapy in women with breast cancer: A 1-year longitudinal study
Uslu, Gonca Hanedan; Aydin, Aydanur; Gürsoy, Ayla
Objective: The objective of this study was to investigate the frequency of acute and late toxicities, as well as changes in the quality of life (QOL) for breast cancer patients following radiotherapy (RT). Materials and Methods: A total of 108 breast cancer women were recruited for this prospective study. Data were collected at various intervals; prior to, and 1, 3, 6 months, and 1 year after radiation therapy. The primary outcomes were toxicity radiation therapy oncology group/European Organization for Research and Treatment of Cancer (EORTC) criteria. Our secondary outcome was QOL, measured using EORTC QLQ-C30 and Edmonton Symptom Assessment Scale. We employed Friedman's two-way analysis to evaluate the changes in QOL over the course of 1 year. Results: The early toxicities that are most commonly experienced include pharyngeal, skin, and mucous membrane toxicity. Late toxicities frequently involve skin and submucosal toxicity. To measure patient functionality, all functional subscale scores except for the patient's emotional state increased over time compared to pre-RT. Symptoms of the patients, which were included in the QOL symptom scale, decreased during the follow-up period, except for fatigue; however, changes in pain, insomnia, and loss of appetite did not significantly change. We identified the analogous symptom profiles in Edmonton. Although patients' overall health scores declined in the 1 st and 3 rd months after radiotherapy (RT), they rebounded at 6 and 12 months. Conclusion: For breast cancer patients, RT did not adversely affect functional capacity or exacerbate symptoms, but persistent fatigue did increase during the observation period. Health-care professionals ought to devise strategies to assist patients with skin toxicity and fatigue.
AtıfScopus2OpenAlex2İncele - MakaleAçık Erişim2024Scopus SJRQ1A study on effective data preprocessing and augmentation method in diabetic retinopathy classification using pre-trained deep learning approaches
İncir, Ramazan; Bozkurt, Ferhat
High glucose levels in the blood not only damage different tissues and organs of the body, but also cause adverse effects on the eye. This condition is called diabetic retinopathy (DR). DR can cause blurred vision, darkening of the field of vision, and severe vision loss. The number of people infected with the disease is increasing in our country and worldwide. The time-consuming physician check-ups and the presence of small lesions indicate the need to develop diagnostic systems. Deep learning-based applications have become the trend for diagnosing and grading diseases from images. This study aims to create a meaningful and sufficient dataset using effective data preprocessing and affine transformation techniques in diabetic retinopathy classification. In this study, classification was performed using seven different pre-trained deep learning architectures. An experimental study of each technique was performed on the EyePACS dataset. An overfitting problem was encountered in the experimental results with the original data set. Thus, data preprocessing and data augmentation processes were carried out in order to eliminate overfitting by considering the imbalance between classes in the dataset. The classification performance obtained from each architecture was observed according to performance metrics of precision, recall, F1 Score, accuracy, and loss. In this study, the best performance was achieved with 97.65% test accuracy with the proposed EfficientNetV2-M network model.
AtıfScopus32WoS21OpenAlex34İncele - BildiriAçık Erişim2024AN ANALYSIS OF NEIGHBOURHOOD TYPES FOR POINTNET++ IN SEMANTIC SEGMENTATION OF AIRBORNE LASER SCANNING DATA
Akbulut, Z.; Ozdemir, S.; Karsli, F.; Dihkan, M.; Isikdag, U.; Bayram, B.
The objective of the study is to conduct a comprehensive examination of how different neighbourhood types, namely spherical, cylindrical, and k-nearest neighbour (kNN), influence the feature extraction capabilities of the PointNet++ architecture in the semantic segmentation of Airborne Laser Scanning (ALS) point clouds. Two datasets are utilized for semantic segmentation analysis: the Dayton Annotated LiDAR Earth Scan (DALES) and the ISPRS 3D Semantic Labelling Benchmark datasets. In the experiments, the kNN method exhibited approximately 1% higher accuracy in weighted mean F1 and intersection over union (IoU) metrics compared to the spherical and cylindrical neighbourhood types on the DALES dataset. However, in the generalization experiment conducted on the ISPRS dataset, the spherical neighbourhood achieved the best results in these metrics, outperforming the cylindrical neighbourhood by a small margin. Notably, the kNN method was the least accurate, with a decrease in accuracy of approximately 1% in both weighted mean IoU and F1 scores. These findings suggest that the features extracted from spherical and cylindrical neighbourhood types are more generalizable compared to those from the kNN method.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2024Scopus SJRQ3Antioxidant Capacity, Oxidative Stability and Sensory Properties of Flavored Butter Using Dried Apricot Pulp
Bulut, M.; Gundogdu, E.
In this study, various concentrations of Dried Apricot Pulp (DAP) were added to butter at levels of 0, 15, 20, and 25%, and its effects on antioxidant capacity, oxidative stability, color, and sensory attributes were assessed during 45 days of storage. Butter samples were labeled as A0 (Control), A15, A20, and A25 corresponding to the respective levels of DAP incorporation. The addition of DAP resulted in significant reductions in pH, while titratable acidity (expressed as lactic acid %) and free fatty acids (FFA) content (mg KOH g-1 butter) increased in a dose-dependent manner (P< 0.05). Fortification with DAP delayed peroxide formation in the butter samples. Additionally, DAP supplementation significantly (P< 0.05) increased Total Phenolic Content (TPC), improved DPPH (2,2-Diphenyl-1-Picrylhydrazyl) scavenging activity, and increased Total Antioxidant Capacity (TAC) during storage. Panelists assigned higher sensory scores to the DAP-enhanced butters. These fortified butters exhibited lower fat content (ranging from 65.25 to 65.50%) compared to the control butter (73.75%). Notably, the total sugar content of samples A15, A20, and A25 was 3.69±0.06, 4.70±0.06, and 5.64±0.08, respectively. Overall, this study demonstrates the potential of all DAP ratios, particularly 25%, as rich sources of antioxidants. However, further formulation adjustments and comprehensive analyses are warranted for industrial and marketing applications.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2024Scopus SJRQ1Extraction of Water Bodies from High-Resolution Aerial and Satellite Images Using Visual Foundation Models
Ozdemir, Samed; Akbulut, Zeynep; Karsli, Fevzi; Kavzoglu, Taskin
Water, indispensable for life and central to ecosystems, human activities, and climate dynamics, requires rapid and accurate monitoring. This is vital for sustaining ecosystems, enhancing human welfare, and effectively managing land, water, and biodiversity on both the local and global level. In the rapidly evolving domain of remote sensing and deep learning, this study focuses on water body extraction and classification through the use of recent deep learning models of visual foundation models (VFMs). Specifically, the Segment Anything Model (SAM) and Contrastive Language-Image Pre-training (CLIP) models have shown promise in semantic segmentation, dataset creation, change detection, and instance segmentation tasks. A novel two-step approach involving segmenting images via the Automatic Mask Generator method of the SAM and the zero-shot classification of segments using CLIP is proposed, and its effectiveness is tested on water body extraction problems. The proposed methodology was applied to both remote sensing imagery acquired from LANDSAT 8 OLI and very high-resolution aerial imagery. Results revealed that the proposed methodology accurately delineated water bodies across complex environmental conditions, achieving a mean intersection over union (IoU) of 94.41% and an F1 score of 96.97% for satellite imagery. Similarly, for the aerial imagery dataset, the proposed methodology achieved a mean IoU of 90.83% and an F1 score exceeding 94.56%. The high accuracy achieved in selecting segments predominantly classified as water highlights the effectiveness of the proposed model in intricate environmental image analysis.
AtıfScopus19WoS13OpenAlex16İncele - MakaleAçık Erişim2024Scopus SJRQ2Elevation-dependent growth trends of Picea orientalis (L.) Peterm forests in the Fırtına Creek Basin (Rize/Turkey)
Işık, Fatih; Bahadır, Muhammet; Zeybek, Halil İbrahim; Hatipoğlu, İlter Kutlu
Changes in climatic conditions have ecological and economic consequences or impact for trees and forest stands. In this respect, it is crucial to understand the radial growth trends of trees, their ecological response across elevation gradients, and the possible impacts of climate change on the species. In this study, Picea orientalis (L.) Peterm, located in the Fırtına Creek Basin in the northern part of the Eastern Black Sea Mountains in northeastern Turkey, was investigated along different elevation gradients in the context of climate-growth response. In the study, six site chronologies along an elevation gradient from 900 m to 2050 m were developed. Dendroclimatological methods were applied to assess the elevation-dependent radial growth characteristics of trees. In total, 200 increment cores were collected from 98 living trees. The relationships between climate and tree ring growth along the elevation gradient showed a positive relationship between growth and temperature at upper elevations (1700–1900 m) and a positive relationship between growth and precipitation at middle elevations (1400–1600 m). In particular, January–April mean temperatures and May rainfall were positively correlated with tree-ring growth. At lower elevations (900–1100 m), the correlation coefficients between climate and growth are insignificant because, at these altitudes, the species have optimum ecological conditions. It was also found that mean temperatures between 0 °C and 2 °C in January–April and total precipitation between 60 and 100 mm in January–February positively affect tree growth. However, if these thresholds are exceeded, it is possible that growth may be adversely affected. This research underscores the complex interplay between climate variables and tree growth along elevation gradients, highlighting the need for adaptive management strategies in the face of changing climatic conditions.
AtıfScopus4OpenAlex2İncele - MakaleYalnız künye2024Scopus SJRQ2The Effect of Video-Based Simulation Training on Nursing Students' Motivation and Academic Achievement A Mixed Study
Koçan, Sema; Kulakaç, Nurşen; Aktug, Cemile; Demirel, Sevgül
This study was conducted to determine the effect of video-based simulation education on nursing students' motivation and academic achievement. The research was designed in a mixed model. A quasi-experimental method with a pretest-posttest control group was used for the quantitative part, and the descriptive phenomenology approach was used as the qualitative research method. The sample of the study consisted of second-year nursing students in two state universities in eastern Turkey. The data were collected with the Student Information Form, the Academic Achievement Test, and the Motivation Resources and Problems Scale using Google Forms Web application. Qualitative data were collected through online semistructured interview forms and focus group interviews. According to the results, the posttest academic achievement and Motivation Resources and Problems Scale mean scores of the students in the intervention group were significantly higher than those of the control group (P < .05). In the analysis of the qualitative, three main themes emerged: We felt fortunate that it increased information retention,” “We felt like we were in real practice environment,” and “It made us feel that we were nurses.” The results showed the use of video-based simulation can be suggested as a strategy to promote classroom teaching and engage students.
AtıfScopus5WoS3OpenAlex4İncele - MakaleAçık Erişim2024Scopus SJRQ2The novel numerical solutions for time-fractional Fornberg-Whitham equation by using fractional natural transform decomposition method
Alkan, Aslı; Anaç, Halil
The time-fractional partial differential equations were solved by the fractional natural transform decomposition method. Fractional derivatives are Caputo sense. The Fornberg-Whitham equation is a generalization of the Korteweg-de Vries (KdV) equation, which describes the propagation of long waves in shallow water. It includes higher-order dispersion terms, making it applicable to a wider range of dispersive media the fractional natural transform decomposition method (FNTDM) was also used to examine applications, and the solutions obtained by this method have been compared to those obtained by the variational iteration method, fractional variational iteration method, and homotopy perturbation method. In addition, the MAPLE package drew graphs of the solutions of nonlinear time-fractional partial differential equations, taking into account physics. The method described in this study exhibited a notable degree of computational precision and straightforwardness when used to the analysis and resolution of intricate phenomena pertaining to fractional nonlinear partial differential equations within the domains of science and technology.
AtıfScopus10WoS6OpenAlex13İncele - MakaleAçık Erişim2024Scopus SJRQ4Economic Evaluation of Thermal and Mechanical Activation Energies in Plaster Production
Şener, Muhammed; Uysal, Turan; Erdemoğlu, Murat
Plaster is among the most needed raw materials in the world. In this study, thermal activation provided by calcination and mechanical activation methods provided by intensive milling in the plaster production process were evaluated in terms of activation energy. In this context, the energies of laboratory-scale thermal and mechanical activation processes were calculated and these activation methods were evaluated economically and the ideal activation methods were determined. Although the mechanical activation method creates additional investment and operating costs, it reduces the calcination temperature by 13 °C, thus provides lower energy costs. Addition of a mechanical activator mill before thermal activation in plaster production as a more economical and more environmentally friendly method was proposed.
AtıfScopus1İncele - MakaleAçık Erişim2024Scopus SJRQ1Optimizing Memristor-Based Synaptic Devices for Enhanced Energy Efficiency and Accuracy in Neuromorphic Machine Learning
Gökgöz, Baki; Aydin, Tolga; Gül, Fatih
The traditional Von Neumann computing architecture, which necessitates data transfer between external memory and the processor, incurs significant energy and time costs when running deep learning (DL) and machine learning (ML) architectures. The primary issue with the energy and time efficiency of this architecture stems from the frequent and intensive data transfers between memory and the processor. Therefore, memristive synaptic devices are utilized to overcome this energy and time inefficiency while performing cognitive tasks. The fundamental working principle of memristive devices is to reduce the need for data transfer by combining memory and processing in the same location, thereby significantly decreasing both energy consumption and the time required for operations. However, to achieve the desired level of efficiency in terms of energy and time consumption from neuromorphic systems, the performance of these systems needs to be further improved with respect to accuracy and test error rates for classification applications. Achieving high accuracy performance in such deep learning or machine learning models necessitates optimization processes not only at the hardware level but also at the algorithmic level. In this context, this paper presents a comprehensive examination and comparison of the frequently used SGD and its momentum variants for deep learning and machine learning applications in memristor-based neuromorphic computing systems. The study thoroughly investigates the performance of critical metrics such as the learning properties, energy efficiency, and accuracy rates of the nano-scale titanium dioxide (TiO2) based synaptic device. The experimental results for the MNIST dataset showed AdaDelta 89.48%, AdaGrad 79.00%, Adam 79.13%, AdaMax 79.68%, Momentum 88.55%, Nadam 81.20%, RMSprop 84.91% and SGD 89.47% accuracy. The experimental results for the CIFAR dataset showed AdaDelta 90.51%, AdaGrad 82.08%, Adam 83.10%, AdaMax 81.76%, Momentum 91.25%, Nadam 82.45%, RMSprop 88.11% and SGD 90.21% accuracy. 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
AtıfScopus11WoS8OpenAlex13İncele - MakaleYalnız künye2024Scopus SJRQ2Effects of combining phosphorus (P) and zinc (Zn) fertilization on P-Zn distribution and yield in safflower
Korkmaz, Kursat; Kılıç, Rahman; Akgün, Mehmet; Kara, Şevket Metin
The interaction of P and Zn is a crucial factor affecting plant growth and yield. The aim of this study was to investigate the combined effects of P and Zn on P-Zn distribution in safflower tissues and seed yield. A two-year study was conducted in farmer fields in northeastern Turkey during 2014 and 2015 years. P applications consisted of four levels (0, 3, 6 and 9 kg P2O5 da−1) that were allotted to the main plots. Sub-plots were composed of three Zn levels (0, 0.5 and 1 kg Zn da−1). The results showed that P and Zn applications had a significant effect on the P and Zn concentration of straw, head, seed, and yield. P concentration in straw, head, and seed increased significantly with increasing P and Zn levels. Zn concentration decreased with high P levels compared to the control, while it increased with increasing Zn levels regardless of P application. At low P levels, yield did not respond to Zn treatments; however, at high P doses, Zn application resulted in a dramatic increase in yield compared to the control. In order to increase seed yield, instead of P and Zn sole application, their combined application was very effective, and doses of 9 kg P2O5 da−1 and 0.5 kg Zn da−1 showed the optimum performance. In conclusion, this study revealed that in P- and Zn-deficient soil, P treatments increased seed yield remarkably, but the combined application of P and Zn resulted in even higher yield increases.
AtıfScopus3WoS3OpenAlex8İncele - MakaleAçık Erişim2024Scopus SJRQ1Enhancing brain tumor classification through ensemble attention mechanism
CELIK, Fatih; CELIK, Kemal; CELIK, Ayse
Brain tumors pose a serious threat to public health, impacting thousands of individuals directly or indirectly worldwide. Timely and accurate detection of these tumors is crucial for effective treatment and enhancing the quality of patients’ lives. The widely used brain imaging technique is magnetic resonance imaging, the precise identification of brain tumors in MRI images is challenging due to the diverse anatomical structures. This paper introduces an innovative approach known as the ensemble attention mechanism to address this challenge. Initially, the approach uses two networks to extract intermediate- and final-level feature maps from MobileNetV3 and EfficientNetB7. This assists in gathering the relevant feature maps from the different models at different levels. Then, the technique incorporates a co-attention mechanism into the intermediate and final feature map levels on both networks and ensembles them. This directs attention to certain regions to extract global-level features at different levels. Ensemble of attentive feature maps enabling the precise detection of various feature patterns within brain tumor images at both model, local, and global levels. This leads to an improvement in the classification process. The proposed system was evaluated on the Figshare dataset and achieved an accuracy of 98.94%, and 98.48% for the BraTS 2019 dataset which is superior to other methods. Thus, it is robust and suitable for brain tumor detection in healthcare systems.
AtıfScopus42WoS21OpenAlex42İncele - MakaleAçık Erişim2024Scopus SJRQ1Damage assessment of Siverek Castle during the Kahramanmaraş Earthquakes (Mw 7.7 and Mw 7.6) on 06 February 2023: Remediation and strengthening proposals
Nasery, Mohammad Manzoor; Çelik, Muhammet; Şadoğlu, Erol
On February 6, 2023, two significant earthquakes with magnitudes (Mw) of 7.7 and 7.6 struck Turkey, occurring nine hours apart. In addition to the tragic loss of over 50,000 lives in the earthquakes centered in Kahramanmaraş, hundreds of thousands of engineering structures, such as residences, schools, hospitals, historical landmarks, highways, and more, were severely damaged. This study assesses the damages and risk scenario following the Kahramanmaraş earthquakes concerning Siverek Castle. In addition, remediation and strengthening proposals, required to eliminate the damage and the possible risk, have been developed. The initial stage involved observational damage assessments on the castle and surrounding slopes as part of field studies, identifying five different types of damage and potential risks. Subsequently, a precise 3D digital model of the damaged castle and its slopes was generated using the digital photogrammetry method. Additionally, geological and geophysical studies were conducted in the field to determine the characteristics of the mound structure, historical castle walls, soil and rock on the slope. Non-destructive, geophysical methods consisting Vertical Electrical Sounding (VES), Seismic Refraction Method (SRM) and Multichannel Analysis of Surface Waves (MASW) measurements were specifically employed in the area with historical remnants. To verify the obtained data, five boreholes were drilled in the lower parts of the slope, and experimental studies were conducted to determine the soil and rock material properties of the slope. In the numerical studies, a total of 54 2D stability analyses were performed under static, long-term static, and dynamic conditions. Additionally, 1000 different probabilistic rockfall analyses were conducted, both in 2D and 3D, to calculate the run-out distance, bounce height, velocity, and kinetic energies of the blocks that fell or were about to fall during the earthquake. In the final stage of the study, remediation and strengthening recommendations were prepared for the strengthening of the fortification walls and slopes where failures occurred, and stability analyses were conducted. Consequently, a design proposal recommending five distinct approaches to remediate and strengthen the castle and slopes impacted by the Kahramanmaraş earthquakes was endorsed by the relevant authorities, and construction has commenced. When the remediation and strengthening works are completed, the security of the cultural heritage will be ensured, and it is planned to be opened to visitors.
AtıfScopus21WoS19OpenAlex20İncele - MakaleAçık Erişim2024THE DIALECTIC OF ISLAMIC LITERACY AND ADAT CONSERVATION: REMOTE COMMUNITY RECEPTION OF HADITHS IN THE KHUTBAH NAGA MANUSCRIPT OF WEST PAPUA
Al Abza, M. Thohar; Zulfadli; Hasbillah, Ahmad ’Ubaydi; Syibromalisi, Arif; Karimullah, Suud Sarim
This study seeks to explore the pattern of hadith reception in the da’wah practices within the Muslim community of Lilinta, Raja Ampat. In particular, it aims to explore how the hadith text, articulated in Arabic, continues to influence local behaviors, beliefs and customs, despite the community’s lack of cognitive understanding of the language. Employing the living hadith approach and adopting Stuart Hall’s reception theory, this study reveals that Lilinta community demonstrates a habitus pattern of ‘negotiation’ in hadith reception. This study found that while on the one hand the redaction of the hadith was not literally understood by the local Muslims, but the essence of hadith was practiced as cultural doctrines. The pattern of hadith transformation suggests that the hadith and its practices co-exist on divergent paths. Practice transpires through doctrinal channels, while the narrative remains misunderstood. This communalpractical living hadith, grounded in habitus rather than cognition, culminates in robust, albeit static traditions. This study concludes that hadith effectively molds the behavior and beliefs of the Lilinta community when viewed from the practiced behaviors over cognitive understanding.
AtıfScopus4OpenAlex5İncele - MakaleAçık Erişim2024Scopus SJRQ2A new species of Buresilia (Opiliones, Phalangiidae) from Turkey
Kurt, Kemal; Kurt, Pinar
A new harvestman species, Buresilia gumushanensis sp. nov. (Opiliones: Phalangiidae), is described based on male specimens collected from Gümüşhane province, Turkey. Detailed descriptions, diagnostic features and pictures of the new species are provided, together with mitochondrial cytochrome c oxidase subunit I (COI) sequences. The phylogenetic tree constructed using the COI gene region revealed the phylogenetic position of the genus Buresilia within the family Phalangiidae. In addition, the new species is compared with known species of the genus Buresilia.