Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(20)
- Celik, Erkan(12)
- Mete, Suleyman(11)
- Serin, Faruk(10)
- ALMisned, Ghada(9)
- Güler, Ömer(8)
- Yucesan, Melih(8)
- Tekin, H.O.(7)
- Artuğer, Fırat(6)
- Utku, Anıl(6)
- Guler, Omer(5)
- Özkul, İskender(5)
- Şimşek, Telem(5)
- Acar, Ramazan(4)
- Basgoz, Oykum(4)
- Guler, Seval Hale(4)
- Şimşek, Tuncay(4)
- Bahceci, Ersin(3)
- Baykal, Duygu Sen(3)
- Başhan, Veysi(3)
- Canbay, Canan Aksu(3)
- Demirel, Hakan(3)
- Doğan, Gürkan(3)
- Ergen, Burhan(3)
- Gul, Ali Oktay(3)
- Güler, Seval Hale(3)
- Gülmez, Nihan(3)
- Karaduman, Oktay(3)
- Kavaz, Esra(3)
- Kaya, Sema Kayapinar(3)
- Onder Erguven, Gokhan(3)
- Yayla, Nihal(3)
- Yildirim, Nuran Cikcikoglu(3)
- Özkaynak, Fatih(3)
- Ak, M. Fatih(2)
- Albayrak, M. Gökhan(2)
- Aslan, Serpil(2)
- Aycin, Ejder(2)
- Can, Umit(2)
- Cemalgil, Selim(2)
Yayınlar
- MakaleYalnız künye2025Scopus SJRQ2Enhanced gastrointestinal disease classification using a convvit hybrid model on endoscopic images
Utku, Anıl
Endoscopy is a procedure that allows examination of the gastrointestinal system, including the stomach, esophagus, large intestine, and duodenum, with the help of an endoscope. Processing of endoscopic images is important for early detection and treatment of gastrointestinal diseases. In this study, hybrid ConvViT was developed using CNN and ViT to increase the classification accuracy of pathologies in gastrointestinal endoscopic images. CNNs are well-suited for capturing local spatial features through hierarchical convolutions, making them highly effective in detecting fine-grained textures and edge patterns. These capabilities complement the ViT’s global attention mechanism, which excels at modeling long-range dependencies in images. The motivation of this study is to increase the classification accuracy and reliability with the ConvViT model, which was developed by combining the practical features of CNN and ViT models, which are individually successful in different aspects of image processing. The ConvViT model was compared with VGG-16, ResNet-50, Inception-V3 and ViT. Comparable models were tested using a gastrointestinal endoscopic image dataset containing ulcers, polyps, inflammation, bleeding, and regular anatomical features. Experiments showed that ConvViT had better prediction performance than compared models, with 95.87% classification accuracy.
AtıfScopus5WoS2OpenAlex2
İncele - MakaleYalnız künye2025Scopus SJRQ2Chromium removal with walnut shells and oak branches, adsorption studies, and kinetics
Fırat, Tülay
This study investigates the chromium sorption properties of walnut shells (WS) and oak branches (OB), both of which were modified using NaOH and lactic acid treatments. The characterization of these adsorbents was carried out using Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), point of zero charge (pHpzc) analysis, and Brunauer–Emmett–Teller (BET) surface area measurements. According to BET results, WS exhibited higher surface area values compared to OB. The pH and pHpzc measurements revealed that acidic functional groups are more prevalent than basic ones on both adsorbents. Batch experiments were conducted to evaluate the chromium ion sorption capacities of WS and OB. To further understand the adsorption mechanism, the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherm models were analyzed, with the Langmuir and Freundlich models being widely recognized for describing adsorption in single-solute systems. The equilibrium data aligned best with the Langmuir isotherm, while the kinetic data were modeled using pseudo-first-order and pseudo-second-order kinetics. The maximum chromium sorption capacity for WS was determined to be 30.51 mg/g. The energy values calculated from the D-R equation for chromium adsorption onto WS and OB were 13.49 kJ/mol and 15.71 kJ/mol, respectively, indicating that the adsorption process is primarily driven by physical adsorption.
AtıfScopus3WoS3OpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ1Hybrid GA-ConvLSTM for data-driven prediction of climate variables: a case study of the most biodiverse cities in India
Utku, Anıl; Akyol, Sinem
Climate variables affect ecosystems’ structure, sustainability, and biodiversity. Monitoring and analysis of climate variables are essential for the management of ecosystems and the conservation of biodiversity. Temperature affects the distributions, habitats, and phonological events of living things in ecosystems. Humidity is essential for meeting plants’ water needs and the habitat’s quality and health. Dew point is essential for water quality, balance, plant health, and microclimate. Wind speed is essential for pollinating plants, microhabitats, and the health of living things. For such reasons, accurate prediction of climate variables using artificial intelligence methods can effectively predict the future of ecosystems and biodiversity and develop future strategic plans. This study aimed to predict the climate variables of temperature, humidity, dew point, and wind speed of Bhubaneshwar, Dehradun, Guwahati, Mysore, and Nagpur, among the cities with the highest biodiversity in India. It aimed to determine the long-term impacts of climate change on managing ecosystems and biodiversity protection. The hyperparameters of the ConvLSTM model, developed using CNN and LSTM, were optimized with a genetic algorithm, and the GA-ConvLSTM hybrid model was created. GA-ConvLSTM was tested with XGBoost, SVM, ANFIS, CNN, LSTM, and base ConvLSTM using approximately 15 years of hourly, up-to-date, and real-time climate variable data of cities. This work is one of the pioneering studies using GA to optimize deep learning hybrid models for multi-city climate prediction through extensive long-term high-resolution datasets. The experimental results reveal that GA-ConvLSTM outperforms conventional models, producing an R2 score exceeding 0.9 for each city across all climate variables. GA-ConvLSTM produced temperature predictions with 0.833 RMSE and 0.995 R2 for Bhubaneswar, humidity predictions with 3.461 RMSE and 0.990 R2, dew point predictions with 0.632 RMSE and 0.995 R2, and wind speed predictions with 2.278 RMSE and 0.993 R2. The experimental findings confirm the improved performance over conventional models due to SVM and XGBoost failing to achieve these R2 values and high RMSE scores. The research meets three principal obstacles because of the combination of stochastic climate datasets and complex nonlinear patterns, which also encounter limitations in conventional methods for managing scale-dependency relationships and manual parameter adjustments. This approach delivers three main strengths because it combines CNN and LSTM networks through genetic programming while tracking temporal and spatial relationships and processing noisy data automatically, leading to improved results compared to other methods. Unlike other published models in the field, the hybrid model GA-ConvLSTM combines optimized CNN and LSTM elements with genetic algorithm elements. The proposed model received its first application in this research for multi-city climate prediction through training with 15 years of hourly data. Standard methods encounter challenges when detecting long-term dependencies, but GA-ConvLSTM successfully addresses this issue.
AtıfScopus1OpenAlex1İncele - MakaleYalnız künye2025Scopus SJRQ1Rainfall trends in the transboundary Euphrates-Tigris River Basin
Acar, Ramazan; Akbas, Ergun; Koycegiz, Cihangir; Esit, Musa
Climate change and anthropogenic factors have a significant impact on rainfall variability. In this study, the trends of monthly total precipitation in the transboundary Euphrates-Tigris River Basin (ETRB), where these effects are intensely observed, were analyzed by trend analysis methods with various perspectives. After decomposing the monthly total rainfall series (1964–2021) obtained from 18 stations representing 12 months of the year, statistical (Mann-Kendall, Wilcoxon, Onyutha), graphical (Innovative Polygon Trend Analysis, IPTA), Trend Polygon Star Concept, TPSC), sub-trend (Onyutha) and spatial trend analyses were performed. Based on the results, it was observed that rainfall in the basin has significant spatial and temporal variability. A monotonic strong decreasing trend was observed in cold months with high rainfall, while an increasing trend was observed in warm months with low rainfall. Extreme rainfall during the winter months has shifted towards the end of the cold months. Graphical and statistical analysis methods have shown strong consistency in identifying monotonic trends. However, the implementation of various methods provides specific insight (transition, sub-trend, etc.) into the temporal and spatial variability of rainfall. Sub-trend analysis shows that rainfall characteristics in the cold months show a significant change before and after the 1990–2000 period. In warmer months, this variability is significantly affected by local and global driving forces. The central and marginal parts of the ETRB have different rainfall characteristics. During cold months, the monotonic trend (decreasing) is significant in the central part. In warm months, the monotonic trend (increasing) increases its intensity in the eastern parts.
AtıfScopus12WoS10OpenAlex14İncele - MakaleAçık Erişim2025Scopus SJRQ2An investigation on microstructural, physical, and radiation shielding properties Yb2O3 oxide dispersion-strengthened 316L-SS alloys
ALMisned, Ghada; Yayla, Nihal; Albayrak, M. Gökhan; Güler, Ömer; Sen Baykal, Duygu; Alkarrani, Hessa; Susoy, Gulfem; Tekin, H.O.
Oxide dispersion-strengthened alloys have emerged as a highly effective solution to address the physical, structural, and shielding challenges faced by traditional alloys in nuclear environments. This study presents a comprehensive evaluation of the microstructural, mechanical, and radiation shielding properties of Yb2O3 oxide dispersion-strengthened 316L stainless steel composites at varying Yb2O3 concentrations such as 1%, 5%, 10%, and 20% by weight. XRD analysis revealed lattice distortions, with crystallite sizes decreasing from 11.2267 nm to 9.3351 nm. SEM/EDX analyses confirmed homogeneous Yb2O3 dispersion at lower concentrations, with agglomeration at 20% Yb2O3. The mass attenuation coefficient increased from 56.103 cm2/g to 65.919 cm2/g at 0.015 MeV, marking a 17.5% enhancement. HVL decreased by 40.68% at 0.2 MeV for the 20% Yb2O3 sample. Additionally, the 20% Yb2O3 composite showed nearly 33% lower transmission factor at 3.0 cm thickness and 0.662 MeV. It can be concluded that Yb2O3 reinforcement significantly enhances the microstructural, and gamma-ray attenuation properties of 316L-SS composites, positioning them as promising materials for advanced nuclear shielding and structural applications.
AtıfScopus5OpenAlex5İncele - MakaleYalnız künye2025Scopus SJRQ2Exploring the Grazing Land Footprint’s Stochastic Behavior in the Top Dairy and Meat-Producing Nations
Adali, Zafer; Yeter, Fatih; Çoban, Mustafa Necati; Sarı, Sacit
The Sustainable Development Goals (SDGs) are a set of influential and easily understood sustainability principles. SDG2 defines Zero Hunger, which is once again a key goal in the SDGs. A sustainable food system depends on the grazing land footprint, one of the elements of the ecological footprint. For food security to be maintained, the grazing land footprint has to be taken into consideration. In order to provide adequate global food systems and mitigate climate change, research on the stochastic features of grazing land footprint is crucial. The goal of this research is to look at the stochastic characteristics of the grazing land footprint in 13 nations that produce almost two-thirds of the world’s milk and meat. The study includes data for 13 nations over the years 1961–2022. Several unit root tests are conducted to provide more precise data about the effectiveness of the policy shocks, including whether or not they allow for repeated, smooth structural breakdowns. The results show that because the series is prone to following its long-term trends, shocks cannot lead it to diverge from those trends. Thus, any shocks brought on by policies cannot have a lasting effect on the series. However, the series includes a unit root. The unit root tests have made it clear that any policy shocks would have a long-lasting effect on the series and that policymakers may set a goal for the series. Policy suggestions have been provided for the investigated nations in conjunction with these results.
AtıfScopus2WoS2OpenAlex8İncele - MakaleAçık Erişim2025Scopus SJRQ1ADAMTS-1, a multifunctional proteinase, in the uterus of both estrous cycle rats and ovariectomized rats can be regulated via hormones
Parlak Ak, Tuba; Yaman, Mine; Bayrakdar, Ali; Bulmus, Ozgur
Remodeling of the extracellular matrix (ECM) throughout the estrous cycle is one of the most striking features of the uterus. A disintegrin and metalloprotease with thrombospondin type I motifs (ADAMTS-1) is a metalloproteinase responsible for the degradation of some proteoglycans, which are ECM components. In this study, ADAMTS-1 distribution was analyzed in the uterus of ovariectomized rats administered 17β-estradiol (E2) and progesterone (P4) and in the uterus at different estrous stages. Ovariectomized (OVX) rats were subjected to single and combined E2 (0.2 mg/kg) and P4 (10 mg/kg) hormone replacement therapies. E2 was administered for 3 consecutive days, followed by E2, P4, or E2 + P4 for 4 consecutive days. The serum level of E2 decreased from the proestrus phase to the diestrus phase, but that of P4 was the highest in the estrus phase. During the estrus phase, the serum level of luteinizing hormone (LH) was the lowest and that of follicle-stimulating hormone (FSH) was the highest. P4 level increased significantly in the OVX + P4 and OVX + E2 + P4 groups compared with the OVX group. The serum levels of LH and FSH decreased in the OVX + E2 and OVX + P4 groups compared with the OVX group, and were the lowest in the OVX + E2 + P4 group. ADAMTS-1 immunoreactivity in luminal, glandular, and stromal cells of the uterus decreased from proestrus to diestrus. When immunoreactivity in hormone replacement groups was compared, weak immunoreactivity was observed in the OVX group. ADAMTS-1 immunoreactivity gradually increased in OVX + P4 and OVX + E2 groups, and was particularly notable in luminal, glandular, and stromal cells in the OVX + E2 + P4 group. ADAMTS-1 distribution was affected by the estrous cycle process and hormone replacement therapy in the OVX procedure.
AtıfScopus1OpenAlex1İncele - MakaleYalnız künye2025Scopus SJRQ1The Extraction of Rare-Earth Elements (REEs) from Spent Nickel–Metal Hydride (Ni–MH) Batteries by Bifunctional Ionic Liquids (Bif-ILs): Process Optimization and Kinetics Modeling
Erust, Ceren
The cathode material of nickel–metal hydride (Ni–MH) batteries includes nickel, cobalt, and rare-earth elements (REEs) such as La, Ce, Nd, and Pr, which are among the critical raw materials (CRMs). Ionic liquids as the environmentally friendly approaches are proposed by various investigations for the extraction of critical metals from spent Ni–MH batteries. In this study, three different Bifunctional Ionic Liquids (Bif-ILs) were designed for comparative studies, namely Aliquat 336–Cyanex 272 (AL–CY), Aliquat 336–PC88A (AL–PC), and Aliquat 336–D2EHPA (AL–D2). The extraction results indicated that temperature has a direct effect on the extraction of critical metals in the presence of all Bif-ILs. Among three types of Bif-ILs, AL–D2 has an optimal extraction power (La: 98.8%, Ce: 94.2%, Nd: 99.2%, and Pr: 98.4%) after precipitation of 99.99% of Ni and Co. Furthermore, kinetics modeling is used for reaction mechanisms investigation. Results indicated that the mixed controlled model by shrinking core model (diffusion controlled and chemical reaction controlled) was the best model fitted to all data (coefficient of determination (R2) > 0.90). according to the Arrhenius equation, activation energies for all REEs in the presence of all Bif-ILs are between 13 and 42 kJ/mol that reflects a mixed controlled reaction.
AtıfScopus2OpenAlex2İncele - MakaleYalnız künye2025Scopus SJRQ3In Vitro Control of Anisakis Larvae Using Nanoemulsified Thyme, Garlic, and Grape Seed Essential Oils Combined with Brines
Cadun, Aslı; Pekmezci, Gökmen Zafer; Şen Yılmaz, Evren Burcu; Bulat, Fevziye Nihan; Demirtaş, Nida; Çaklı, Atilla; Inci, Abdullah; Yıldırım, Alparslan; Karademir, Gupse Kübra; Erdem, Omer Alper
Introduction: Anisakiasis is a zoonotic parasitic disease transmitted through consumption of fish, with increasing global cases. While thorough cooking kills Anisakis larvae, thermo-stable allergens can still cause allergic reactions. Traditional Mediterranean seafood methods such as marinating, salting, and brining, which lack heat treatment, pose a high risk of anisakiasis. Materials and methods: This study investigated the antilarval effects of nanoemulsions made from thyme, garlic, and grape seed essential oils combined with brines on Anisakis L3 larvae in vitro. Results: Larvae were collected from mackerel, chub mackerel, anchovy, horse mackerel, and sardine, with 1746 larvae examined, mostly Anisakis type I and molecularly identified as A. pegreffii. Thyme oil’s main components, carvacrol and thymol, showed strong antimicrobial and antioxidant effects and superior larvicidal activity at lower doses compared to garlic and grape seed oils. Garlic oil, rich in organosulfur compounds, was more effective in Lakerda samples. High salt brine alone inactivated larvae within 24 h. The thyme oil nanoemulsion had droplet sizes below 90 nm, enhancing stability, whereas garlic and grape seed oils had larger droplets. Conclusion: These results indicate that nanoemulsified essential oils, especially thyme oil, are promising natural agents to control Anisakis larvae in traditional sea-food products.
- MakaleAçık Erişim2025Scopus SJRQ2A novel additive for enhancing biomass energy production from agro-industrial wastes: synthesis of hydrophobic nanoporous silica aerogel and its effect on methane production
Gulsen Akbay, Habibe Elif; Basgoz, Oykum; Guler, Omer
Anaerobic digestion (AD) is one of the most preferred processes for the treatment of organic waste. However, additional processes such as co-digestion, pretreatment, and additive addition continue to be explored to remove the limits on the applicability of AD. This study investigated the effects of hydrophobic nanoporous silica aerogel (NpSA) synthesized from waste rice husks on the anaerobic co-digestion (AnCD) of the mixture consisting of sewage sludge and fruit processing industry wastes. All bioreactors containing NpSA-free, 0.1 g, 0.2 g, 0.5 g, and 1 g NpSA (0.03–0.3 gNpSA/gVSadded) were operated in a mesophilic-batch process. Biogas and methane yields increased from 346 mL/gVS (NpSA-free) to 387 mL/gVS and from 231 mL/gVS (NpSA-free) to 288 mL/gVS, respectively, with 0.1 g NpSA addition. NpSA additive increased biogas production in all bioreactors compared to the blank. However, biogas production rate and methane content increased faster at lower doses of NpSA. Maximum soluble chemical oxygen demand (sCOD), protein, carbohydrate, and volatile solid (VS) reductions were between 45–71%, 35–54%, 44–65%, and 34–91% for NpSA added mixtures, respectively. The hydrophobic NpSA additive was effective in improving the AnCD performance and biogas/methane production. Experimental results fit the kinetic models frequently preferred in such AD processes. In addition, the possible energy and financial potential of the produced methane were also discussed, and it was determined that the direct sale of methane gas produced by the addition of NpSA in the global market could provide 1.4 $/Lmixture more financial gain than the mixture NpSA-free.
AtıfWoS1İncele - MakaleYalnız künye2025Scopus SJRQ2Heat transfer and condensation analysis of the walls of a house built with natural andesite stone
Işik, Erdem; Kahraman, Gökhan; Atalar, Aydın
The use of natural stones in buildings is increasingly popular due to both their decorative appearance and their thermal performance. Proper use of these stones in buildings is crucial for energy conservation and preventing condensation within structural components. This study investigated heat transfer and condensation in the wall of a house made from natural andesite stone in Iğdır, Turkey, under steady-state conditions and different wall combinations. Samples were created from natural stones extracted from two different elevations in the foothills of Mount Ararat, with measured thermal conductivity values of 1.73 W/m·K (higher elevation– Haverage) and 1.31 W/m·K (lower elevation– Laverage). In the wall model using a 3-cm thick insulation board between two natural stones from the higher elevation, condensation occurred on the outer surface of the insulation layer. This can negatively impact the durability and thermal performance of the structure, and such design should be avoided. The highest heat flux of 18.27 W/m² was observed in the non-insulated wall made of higher elevation stones, while the lowest heat flux of 6.68 W/m² occurred in the model using a 3-cm insulation board between two lower elevation stones. No condensation risk was found in this configuration. The difference between the worst and best cases in terms of heat flux was approximately threefold, emphasizing the importance of proper material selection and insulation design. These findings provide guidance for energy-efficient building design using natural stone.
- MakaleYalnız künye2025Scopus SJRQ2Using Meta-Heuristic Optimization Algorithms to Determine Baseflow and Comparing Their Temporal Performance
Acar, Ramazan; Sapliogu, Kemal
Accurate and simple determination of baseflow is an extremely important issue. In this study, the baseflow levels of Göksu station number 1805 in the Seyhan basin were determined by calibrating the Lyne and Hollick, Chapman, Chapman and Maxwell methods available in the literature using meta-heuristic optimization methods. The meta-heuristic algorithms used for calibration in the study were run thirty times each. Thus the reliability, the reliability of the algorithms was tested with the standard deviations obtained. The study also measured the temporal performance of the algorithms. In addition, the baseflows of Göksu station were determined and their percentage rates were found separately according to all three methods and intuitive methods, and the results obtained were compared. By examining the results obtained in this section, the average baseflow rate of the basin was also determined. Furthermore, each phase of the study was repeated over a five-year period, with the objective of measuring its sustainability. Consequently, it has been demonstrated that the method can be employed over extended periods.
AtıfOpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ2Multifunctional properties and microstructural correlations of NiCoMnTi-Based high entropy alloys with focus on magnetic, thermodynamic, and radiation shielding characteristics
Özkul, İskender; Karaduman, Oktay; Şimşek, Tuncay; Şimşek, Telem; Canbay, Canan Aksu; Güler, Ömer; ALMisned, Ghada; Baykal, Duygu Sen; Tekin, Huseyin Ozan
High-entropy alloys (HEAs) are a novel class of materials known for their complex compositions and exceptional multifunctional properties. In this study, NiCoMnTi-based HEAs were modified with Fe, Cr, and Cu as fifth elements to systematically investigate their structural, magnetic, thermodynamic, and nuclear radiation shielding characteristics. The alloys were synthesized via arc melting and characterized using XRD, SEM-EDS, VSM, and theoretical modeling methods. The findings reveal that each additional element uniquely alters the alloy’s properties. The Fe-containing alloy exhibited a well-defined lamellar microstructure, the highest saturation magnetization (10.79 emu/g), and a Curie temperature near 450 K, along with strong gamma-ray shielding performance across both low and high energy ranges. The Cr-containing alloy demonstrated soft magnetic behavior, featuring the lowest coercivity (29.64 Oe) and the highest fast neutron removal cross-section. In contrast, the Cu-containing alloy enhanced low-energy photon attenuation due to its higher atomic number but exhibited limited magnetic homogeneity. Despite these differences, all samples displayed stable thermodynamic behavior and comparable buildup factor trends. Overall, the addition of Fe led to a synergistic improvement in both magnetic and radiation shielding capabilities of the NiCoMnTi-based HEA system.
AtıfScopus3OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ2Comprehensive evaluation of thermal, structural, magnetic, and radiation shielding properties of CuAlNi and CuAlNi-X (X = Co, CoFe, CoFeMn, CoFeMnCr) high-temperature shape memory alloys
Özkul, İskender; Karaduman, Oktay; Şimşek, Telem; Şimşek, Tuncay; Canbay, Canan Aksu; Güler, Ömer; Şan, Mert Hüseyin; ALMisned, Ghada; Tekin, H.O.
This study investigates the thermal, structural, magnetic, and radiation shielding properties of CuAlNi-based high-temperature shape memory alloys (HTSMAs) enhanced through sequential alloying with Co, Fe, Mn, and Cr. Five different variants were produced, designated as CRef (reference CuAlNi alloy), CCo (CuAlNiCo), CFe (CuAlNiCoFe), CMn (CuAlNiCoFeMn), and CCr (CuAlNiCoFeMnCr). Differential scanning calorimetry (DSC) confirmed the presence of reversible martensitic transformations in all alloys, with Co and Mn additions significantly enhancing thermal stability. Structural analyses using X-ray diffraction (XRD) and microscopy showed significant grain refinement and phase transitions, while magnetic measurements highlighted the strong ferromagnetic response of CCo (CuAlNiCo) and the increased coercivity of CMn (CuAlNiCoFeMn) due to domain-pinning effects. Moreover, radiation shielding analyses demonstrated the critical influence of density and elemental composition, with CRef exhibiting superior linear attenuation coefficients (LAC), effective atomic number (Zeff), and energy absorption buildup factor (EBF) performance, attributed to its optimized Cu fraction and high density (7.1296 g/cm3). In contrast, CMn (CuAlNiCoFeMn) showed the weakest shielding properties due to reduced density and Mn content. Among the samples, CRef emerged as the superior alloy, demonstrating exceptional multifunctionality across all evaluated parameters, while CCr (CuAlNiCoFeMnCr) displayed synergistic properties, combining shape memory behavior with competitive shielding efficiency. It can be concluded that CuAlNi-based HTSMAs hold significant potential as multifunctional materials, particularly for nuclear safety and aerospace engineering applications, where adaptive functionality and radiation protection are critical.
AtıfScopus2OpenAlex2İncele - DüzeltmeAçık Erişim2025Scopus SJRQ1Correction: Median-Linear model for solar radiation estimation by comparison with ANFIS and Angström-Prescott methods (Modeling Earth Systems and Environment, (2025), 11, 5, (352), 10.1007/s40808-025-02554-1)
Acar, Ramazan; Saplıoğlu, Kemal; Güçlü, Yavuz Selim
The Funding information section was missing from this article and should have read ‘This research was supported by the Scientific Research Projects Coordination Unit of Istanbul Technical University under Project Number MGA-2025-46432’.The original article has been corrected.
- MakaleAçık Erişim2025Scopus SJRQ1New comparative approach to multi-level thresholding: chaotically initialized adaptive meta-heuristic optimization methods
Serbet, Fatmanur; Kaya, Turgay
One method aimed at enhancing the performance of meta-heuristic optimization techniques is the incorporation of chaotic systems. Instead of irregular distributions in the search space, chaotic distributions are employed in the initial population of optimization algorithms to improve the efficiency of the search process. This approach enables search agents distributed in a chaotic manner to effectively explore the search space. The initial populations of both the well-established PSO algorithm and the enhanced WSO algorithm, which incorporates advanced search techniques, are distributed in the search space according to the characteristics of Logistic, Chebyshev, Circle, Sine, and Piecewise chaotic maps in this study. The original PSO and WSO algorithms, as well as the resulting chaotically initialized PSO and chaotically initialized WSO algorithms, were tested using 23 benchmark functions. Subsequently, the Otsu method was integrated into the tested optimization algorithms to obtain multi-level thresholding values. These algorithms were applied to five different test images with a manually determined number of thresholds. The results obtained were presented in the study and evaluated using statistical tests.
AtıfScopus13OpenAlex12İncele - MakaleAçık Erişim2025Scopus SJRQ2Innovative image encryption approach based on bitwise XOR high nonlinear S-boxes and random permutation
Artuğer, Fırat
With today's developing technologies, the need for new image encryption algorithms to encrypt images is inevitable. In this study, an innovative image encryption algorithm is proposed. The proposed algorithm first XORs each layer of the image with a unique and strong new key. Each layer is then subjected to a random permutation process. Each of the encrypted layers obtained here is finally passed through a new s-box structure with a high nonlinearity value. After these processes, all layers are combined to obtain an encrypted image. Thus, XOR and s-box confusion meet the criteria, while random permutation meets the diffusion criteria. In this study, both key and s-box structures were originally obtained with a chaotic Gaussian map. The outputs of the chaotic map were converted into bit sequences and five different sequences with a length of 1 million were obtained. All these arrays have successfully passed all NIST SP 800-22 tests. On the other hand, the proposed s-box structures surpassed many studies with nonlinearity values of 108, 108.5, and 108.75. The images were successfully encrypted with the proposed algorithm, and the encrypted images successfully completed tests such as NPCR-UACI, information entropy, histogram analysis, and correlation analysis. It is thought that this study will make many contributions to the fields of s-box development, random number generation, and image encryption.
AtıfScopus3OpenAlex3İncele - MakaleYalnız künye2024Scopus SJRQ2Activity of nanosized copper-boron alloys against Phytophthora species
Yiğit, Uğur; Türkkan, Muharrem; İlhan, Hasan; Şimşek, Tuncay; Güler, Ömer; Derviş, Sibel
This study aimed to evaluate the antifungal activity of copper-boron (Cu-B) nanoalloys against a range of Phytophthora species, including P. capsici, P. citrophthora, P. palmivora, P. cinnamomi, P. nicotianae, P. cactorum, P. plurivora, P. inundata, and P. megasperma. The nanoalloys were synthesized via mechanical alloying under an argon atmosphere, resulting in the formation of nanocrystalline Cu-B nanoalloys with irregular morphology and particle sizes ranging from 50 to 240 nm. At a concentration of 250 µg mL−1, the Cu-B nanoalloys demonstrated complete inhibition of mycelial growth, sporangium production, and zoospore germination in all tested Phytophthora species. The EC50 values for mycelial growth ranged from 28.02 to 120.17 µg mL−1, while for sporangium production and zoospore germination, they were below 10 µg mL−1. Furthermore, the nanoalloys exhibited fungicidal activity against specific Phytophthora species, such as P. capsici, P. citrophthora, P. inundata, and P. megasperma, at concentrations of 100, 250, 250, and 250 µg mL−1, respectively. Notably, the Cu-B nanoalloys displayed significant protective and curative effects on tuber rot severity in P. nicotianae-inoculated potatoes, resulting in reductions of 94.13% and 92.61% compared to the control, respectively, at a concentration of 10 µg mL−1 (P < 0.05). These findings highlight the potential of Cu-B nanoalloys as a promising fungicide for the management of plant diseases caused by Phytophthora spp.
AtıfScopus3WoS1OpenAlex2İncele - MakaleYayıncıda açık erişim2024Scopus SJRQ2Mechanical and electrical faults detection in induction motor across multiple sensors with CNN-LSTM deep learning model
Ertargin, Merve; Yildirim, Ozal; Orhan, Ahmet
The utilization of monitoring sensors in machinery has led to the mainstream adoption of fault detection and diagnosis in time series data across various industrial applications. Deep learning techniques, specifically in constructing fault diagnosis models by extracting insights from historical equipment fault data, are receiving widespread attention as crucial tools in ensuring the safety and reliability of motor systems. In this study, a CNN-LSTM-based deep learning model is proposed for the detection of electric motor faults. Three distinct sets of accelerometer sensor data are provided as input to the model, enabling a comprehensive evaluation of its performance across various sensor configurations. The model demonstrated a remarkable capacity for generalization, achieving impressive accuracy rates of 99.96% for Accelerometer-1, 98.88% for Accelerometer-2, and 99.37% for Accelerometer-3. This underscores the robustness and adaptability of the proposed CNN-LSTM model in effectively detecting electric motor faults regardless of the specific accelerometer sensor employed.
AtıfScopus47OpenAlex38İncele - BildiriYalnız künye2024Scopus SJRQ4Constructing the Criteria in Determining the Product Groups for Agriculture 4.0 Applications
Erdoğan, Melike; Konurhan, Zekeriya; Yücesan, Melih; Gül, Muhammet; Mirzazadeh, A.; Molamohamadi, Z.; Erdebilli, B.; Babaee Tirkolaee, E.; Weber, G.-W.
With Agriculture 4.0, the use of techniques such as sensors, robots, artificial intelligence, and machine learning in agriculture has started. It is aimed to increase productivity in agriculture by reducing food loss and waste through Agriculture 4.0. It is a critical decision to determine which products should be handled first for Turkey to benefit from the advantages of Agriculture 4.0 as soon as possible compared to developed countries in the field of agriculture. At this point, the problem of which factors should be addressed in the determination of product & product groups arises. To handle this, in this study, a multi-criteria analysis has been applied to prioritize the factors that should be considered in the determination of the critical fruit and vegetable group for export, which should be considered as a priority within the scope of Agriculture 4.0. In this context, a multi-criteria analysis has been carried out by adopting the Bayesian Best Worst Method BWM (B-BWM), which is an improved version of a pairwise comparison-based BWM method and applied to group decisions. As a result of the analysis, the most important and least important criteria to be used in determining which products or product groups are more suitable for Agriculture 4.0 applications in Turkey and which should be invested in priority have been determined.