Skin cancer is one of the most prevalent and deadly malignancies, necessitating early and precise diagnosis to improve patient survival rates. While recent advancements in deep learning have produced robust computer-aided diagnosis (CAD) systems, the majority of these models rely exclusively on visual features extracted from dermoscopic or clinical images. Conversely, dermatologists synthesize visual cues with patient clinical metadata (e.g., age, gender, continuous bleeding, and itchiness) to reach an accurate diagnosis. Prior research attempting multimodal fusion has largely depended on black-box concatenation-based late-fusion strategies or simple neural compression modules, obscuring clinical reasoning. To bridge this gap toward Explainable Artificial Intelligence (XAI), we propose CrossMeta-ViT, a deep vision-transformer metadata-fusion framework designed for transparent skin lesion classification. The core contribution of this architecture is a Cross-Attention Fusion module. Instead of sequentially concatenating features, CrossMeta-ViT utilizes encoded patient tabular metadata as a Query (Q) to dynamically attend to visual image patches acting as Keys (K) and Values (V). This mechanism ensures that structural image features are selected and weighted under the direct guidance of the patient's clinical history. We evaluated the framework on the smartphone-captured PAD-UFES-20 dataset for binary classification (Benign vs. Malignant). Using 5-fold cross-validation, CrossMeta-ViT achieved a macro F1-score of 0.8723 ± 0.0009, malignant recall of 0.9927, specificity of 0.7651, and an AUC of 0.955, while the held-out single-split evaluation yielded an accuracy of 0.90. These results support the model as a recall-oriented and interpretable multimodal aid for telemedicine pre-triage rather than as a universally dominant classifier.
Dalbergia melanoxylon (African Blackwood/Mpingo) is a tree species known for its high density and hard structure and is widely used in producing musical instruments, luxury furniture, and handicrafts. The surface roughness of wood is determined by certain sanding factors. This study investigated the factors affecting the surface roughness of Dalbergia melanoxylon wood and determined optimal sanding conditions. Surface roughness was evaluated using Ra (average roughness), Rq (root mean square roughness), and Rz (maximum profile height) parameters, and differences between groups were statistically examined using analysis of variance. The results showed that the most influential factor for Ra and Rq was the sandpaper grit size, with contributions of 53.29% and 36.39%, respectively, while for Rz, the measurement direction was the most influential factor, with a contribution of 43.20%. The highest roughness values were obtained with 80 grit sandpaper, 15 s of sanding time, and measurements taken perpendicular to the grain, with Ra = 4.071, Rq = 5.668, and Rz = 35.207 µm. On the other hand, the lowest roughness values were obtained with 220 grit sandpaper, 60 s of sanding time, and measurements taken parallel to the grain, with Ra = 2.116 µm, Rq = 3.160 µm, and Rz = 22.668 µm. According to the Duncan test results, the combination with the lowest surface roughness was 220 grit sandpaper, 60 s of sanding time, and measurements taken parallel to the grain. In conclusion, for dense and hard-grained woods such as Dalbergia melanoxylon, fine sandpaper and longer sanding times are the most suitable conditions for optimizing surface quality. These findings provide an important reference for quality control processes and industrial applications of wooden decorative surfaces.
This study investigates wave dispersion in a heat-conducting thermoelastic medium by integrating nonlocal elasticity with generalized thermoelastic theories. A characteristic dispersion equation is derived to examine the influence of the nonlocal parameter, thermal relaxation time, and thermoelastic coupling on mechanical and thermal wave modes, with silicon used as the numerical example. The results indicate that increasing nonlocality leads to greater deviation from the local thermoelastic response, particularly at higher wave numbers, highlighting the significance of internal length-scale effects. For the selected parameter values, the Lord–Shulman and Green–Lindsay models exhibit similar dispersion trends, as elastic, inertial, and nonlocal effects dominate over the relatively small contribution of thermal relaxation time. Unlike earlier studies that focus on individual models or limiting cases, this work offers a unified comparison of coupled and uncoupled nonlocal thermoelastic formulations, including their local and classical limits. Several limiting or simplified cases are analyzed to provide deeper insight into the model, while future studies should validate the predicted wave speeds against experimental results or established reference models.
Lateritic soils are widely used in tropical pavement construction but often exhibit high fines, plasticity, and moisture susceptibility that undermine long-term performance. This study synthesizes engineering, chemical, and microstructural evidence from a lateritic soil stabilized using stone dust (SD) and bamboo leaf ash (BLA) to assess (i) moisture-related durability indicators and (ii) mechanistic–empirical (M–E) performance implications relevant to cyclic traffic loading. Lateritic soil was treated with SD (0–30% at 5% intervals) and with combined SD-BLA blends (BLA: 3 to 9%; SD: 5 to 20%) and tested for Atterberg limits, compaction (BSL/WAS/BSH), soaked and unsoaked CBR, UCS, and shear strength. XRF confirmed the pozzolanic character of SD and BLA (SiO₂+Al₂O₃+Fe₂O₃ = 85.51% for SD; 66.71% for BLA), while XRD/SEM evidenced microfabric densification and cementitious bonding in stabilized blends. The combined SD–BLA blend provided the best overall performance, with an optimum at 10% SD + 3% BLA (by dry soil mass), reducing plasticity (PI down to ~10%) and increasing strength. Moisture durability improved substantially: under British Standard Heavy (BSH) compaction, soaked California bearing ratio (CBR) increased from ~18% (natural) to ~65.48% (SD-BLA optimum) and the CBR retention ratio (soaked/unsoaked) improved from ~0.44 to ~0.71. For M-E interpretation, resilient modulus was conservatively estimated from CBR using a standard correlation, indicating a marked increase in wet-condition stiffness and reduced rutting susceptibility, thereby improving seasonal performance of subbase layers. These results support SD-BLA as a low-carbon stabilizer system for lateritic pavement layers, while highlighting the need for follow-on repeated-load and wet-dry cycling to fully quantify cyclic durability.
This study investigated the regression analysis of tropical soil (TS) stabilised with calcium chloride salt (CCS) using the Standard Proctor Method (SPM) to assess its suitability as a pavement construction material. Laboratory tests, including Atterberg limits (liquid limit, plastic limit, and plasticity index) and compaction parameters (maximum dry density, MDD; optimum moisture content, OMC), were conducted on both natural and stabilised soils in accordance with British Standard Light specifications. CCS was applied at concentrations ranging from 4% to 16%. Results were evaluated using analysis of variance (ANOVA) and regression analysis. Findings indicated that increasing CCS content increased the coarseness of the lateritic soil. MDD initially decreased from 1.63 Mg/m³ (untreated) to 1.45 Mg/m³ at 4% CCS, then increased to 1.97 Mg/m³ at 16% CCS, while OMC rose from 19.47% at 4% CCS and declined progressively at higher CCS. Regression analyses confirmed significant differences across most test parameters, except for the plasticity index, which showed no variation. High coefficient values were recorded across treatments. The study concludes that CCS effectively improves the engineering properties of tropical soils and recommends close monitoring of CCS content and liquid limit parameters during pavement design for low-traffic road applications.
Vector calculus concepts such as vector fields, divergence, and curl are often difficult for students to understand because they involve abstract multidimensional structures and spatial interpretation processes. In traditional instructional approaches, these concepts are generally presented through symbolic notation and static visual representations, which may limit the interpretation of the dynamic behavior of three-dimensional mathematical structures. This study addresses the design, development, and expert evaluation of a Matlab-based interactive learning object for the three-dimensional examination of vector calculus concepts. The proposed system integrates symbolic computation, numerical evaluation, and three-dimensional graphical visualization within a single computational environment. Using a selected vector field example, the study examines vector direction, magnitude, divergence, curl, and parameter-dependent graphical transformations. In addition, two independent experts evaluated the developed learning object in terms of mathematical accuracy, visual clarity, usability, reproducibility, and instructional suitability. The overall expert-review mean was 4.50/5.00, and both experts evaluated the learning object as suitable in its current form. However, this study is not an effectiveness study in which learning outcomes are experimentally measured. Therefore, the impact of the proposed learning object on students' learning outcomes should be further examined through future user studies, pilot implementations, and classroom-based experimental research.
Tekstil üretiminde kumaş yüzeyinde oluşan kusurlar, ürün kalitesini düşürmekte ve üretim maliyetlerini artırmaktadır. İnsan gözlemine dayalı geleneksel kalite kontrol yöntemlerinin hız ve tutarlılık açısından sınırlı olması nedeniyle bu çalışmada, kumaş kusurlarının çevrim içi belirlenmesi ve konveyör sistemine durdurma komutu iletilmesi amacıyla Edge AI tabanlı laboratuvar ölçekli bir prototip geliştirilmiştir. Sistem; Raspberry Pi 5, yüksek çözünürlüklü kamera, L298N motor sürücüsü, DC motorlu konveyör mekanizması ve YOLOv8n nesne tespit modelinden oluşmaktadır. Model; leke, yırtık, boya, iplik ve kusursuz kumaş olmak üzere beş sınıf üzerinde eğitilmiştir. Veri seti, beş farklı kumaş örneğinden üç ayrı çekim oturumunda elde edilen 750 özgün görüntüden oluşturulmuştur. Ardışık görüntülerden kaynaklanabilecek veri sızıntısı riskini azaltmak amacıyla veri seti, artırma işlemlerinden önce grup bazlı olarak eğitim, doğrulama ve test kümelerine ayrılmış; veri artırma yalnızca eğitim kümesine uygulanmıştır. Eğitim ve model seçimi süreçlerinde kullanılmayan test kümesinde model %96,36 kesinlik, %96,00 duyarlılık, %96,00 mAP@0.5 ve %42,15 mAP@0.5:0.95 değerlerine ulaşmıştır. Sonuçlar, geliştirilen sistemin kontrollü laboratuvar koşullarında kumaş kusuru tespiti ile olay tetiklemeli konveyör kontrolünün bütünleştirilmesi açısından uygulanabilir bir ön prototip sunduğunu göstermektedir. Bununla birlikte, sistemin endüstriyel üretim ortamlarında kullanılabilmesi için daha geniş ve çeşitli veri setleriyle doğrulanması, farklı aydınlatma koşulları ve bant hızlarında test edilmesi ve mekanik durma süresi ile durma mesafesinin ayrıca ölçülmesi gerekmektedir.
LDH yapıları, esnek ve uyarlanabilir özelliklere sahip olması sayesinde belirli bir uygulama için modifiye edilebilmektedir. Bu çalışmada, CuFeV-LDH yapısı sentezlenmiş ve XRD, FTIR, FE-SEM ve BET gibi analiz yöntemleri ile karakterize edilerek yapısı ortaya koyulmuştur. XRD sonucu malzemenin yüksek kristal yapıya sahip olduğunu göstermiştir. FE-SEM sonucuna göre yapının nano boyutlu küresel taneciklerden oluştuğu ve elementlerin homojen dağılıma sahip olduğu belirlenmiştir. BET sonucuna göre ise CuFeV-LDH’nin yüzey alanı 238.59 m² g⁻¹ olarak bulunmuştur. Üretilen bu malzeme kullanılarak Fenton benzeri katalitik oksidasyon yöntemi ile metilen mavisi giderim performansı incelenmiştir. Metilen mavisi giderim deneyleri üç farklı katalizör miktarı (0.5, 1, 1.5 g/L) varlığında gerçekleştirilmiştir. Katalizör miktarı için optimum değer olarak 1g/L belirlenmiş ve kinetik çalışmalar bu değer sabit tutularak gerçekleştirilmiştir. Metilen mavisi giderim performansı 45oC de, 1g/L katalizör ve 100 mM H2O2 varlığında % 85’e ulaşmıştır. Kinetik çalışma analizleri sonucu, reaksiyonun birinci ve ikinci dereceden kinetik modele uyduğunu göstermiştir. CuFeV-LDH katalizörünün Fenton benzeri sistemler için önemli bir potansiyele sahip olduğunu göstermektedir.
The need for cutting-edge and environmentally shielding materials to reduce radiation exposure has grown along with the use of nuclear energy due to scientific and industrial developments. The gamma attenuation characteristics of samarium oxide (Sm2O3)-doped photopolymer composites created for additive manufacturing applications are examined in this work. This study involved the theoretical design of resin structures that contained 0%, 10%, 20%, and 50% Sm2O3 by weight. The GAMOS Monte Carlo simulation code was used to examine the materials' radiation interaction parameters at gamma energies ranging from 81 keV to 1408 keV. The results showed that as the dopant concentration increased, the linear attenuation coefficient (LAC) and mass attenuation coefficient (MAC) increased significantly, while the half-value layer (HVL) thickness decreased. Specifically, at the low energy level of 81 keV, the Sm50 sample containing 50% Sm2O3 exhibited the highest radiation attenuation performance compared to the undoped sample. Consequently, samarium-doped composites produced using 3D printing technology offer high potential for lightweight and lead-free radiation shielding equipment with complex geometries.
Bu çalışmada SCGA590 kalite otomotiv çeliği, diğer kaynak parametreleri sabit tutularak üç farklı akım (8 kA, 10 kA ve 12 kA) ve iki farklı zaman değerlerinde (100 ms ve 200 ms) nokta direnç kaynak yöntemiyle birleştirilmiştir. Farklı parametrelerde elde edilen numunelerin mikroyapısı detaylı olarak incelenmiş ve mikro sertlik deneyleri yapılmıştır. Kaynak işleminde meydana gelen yüksek sıcaklık ve sonrasında gerçekleşen hızlı soğuma mikroyapıda bölgesel değişimlere sebep olmuştur. Bu doğrultuda kaynaklı birleşimde esas metal, ısının tesiri altındaki bölge ve kaynak metali olmak üzere 3 farklı bölge tespit edilmiştir. Mikroyapı sebebiyle sertlik değerleri esas metalden kaynak metaline doğru artış göstermiştir. En yüksek sertlik değerine (621 HV), 10 kA kaynak akımı 200 ms kaynak süresi parametrelerinde elde edilen numunede ulaşılmıştır.
Bu çalışmada, çökelme sertleşmesi uygulanabilir martenzitik çeliklerden Corrax malzemesinin farklı ısıl işlemler sonrası oluşan mikroyapı ve sertlik değerleri incelenmiş ve işlenebilirlik performansı kuru ve kaplamasız takım kullanılarak yapılan tornalama deneyleri ile değerlendirilmiştir. Corrax malzemesi uygulanan farklı sıcaklıktaki ısıl işlemlere göre sertlik değeri 50 HRC değerine kadar çıkmış, bu sıcaklıktan daha yüksek sıcaklıkta ise (600℃) yapılan yaşlandırma işlemi ile sertlik değerlerinde aşırı yaşlandırmaya bağlı düşüş görülmüştür. İşlenebilirlik testlerinde ise, en yüksek kesme kuvveti değeri A6 numunesinde elde edilmiştir ve bu durum yaşlandırma esnasında meydana gelen dönüşmüş östenit ile ilişkilendirilmiştir. En düşük kesme kuvveti değerleri genel olarak A0 numunesinde elde edilirken, en yüksek kesme kuvveti A6 numunesinde ölçülmüştür. En düşük yüzey pürüzlülük değerleri ise genel olarak A6 numunesinde ölçülmüştür. Genel olarak yaşlandırma işlemleri kesme kuvvetlerinin artmasına neden olurken, çalışmanın en dikkat çekici sonucu en yüksek kesme kuvvetinin, en sert malzeme yerine A6 numunesinde ölçülmüş olmasıdır ve bu durum kalıntı östenitin, işleme esnasında oluşan deformasyon ile martenzite dönüşmesi ile ilişkilendirilmiştir.
Bu çalışmada, Magnetherm prosesi ile farklı magnezyum kaynakları ve farklı redükleyicilerle metalik magnezyum üretimi gerçekleştirilmiştir. Magnezyum kaynağı olarak magnezyum oksit (MgO) ve dolomit (CaO·MgO); redükleyici ajan olarak alüminyum talaşları (Al), ferosilisyum (FeSi) ve kalsiyum karbür (CaC2) kullanılmıştır. Bu çalışmada aynı deney parametrelerinde farklı magnezyum kaynağı kullanarak farklı redükleyici kullanımının redüksiyon verimi ve geri kazanım verimi üzerindeki etkisi araştırılmıştır. Deneyler, 1,5 dakikalık deney süresi ve 600 amperlik akım değerinde, Al- CaO·MgO, FeSi-MgO, FeSi-CaO·MgO, CaC2-MgO ve CaC2-CaO·MgO sistemlerinde gerçekleştirilmiştir. FactSage programı kullanılarak termodinamik modelleme yapılmış ve sonuçlar deneysel bulgularla karşılaştırılmıştır. Üretilen magnezyumlar toz formunda elde edilmiş ve magnezyum tozları ile cüruflara çeşitli analizler uygulanmıştır. Magnezyum tozları ve cüruflara XRD ve karbon tayini; magnezyum tozlarına atomik absorbsiyon analizi (AAS); cüruflara ise XRF analizi yapılmıştır. Deney sonuçlarına göre, en yüksek redüksiyon verimi %98,17 ile FeSi-CaO·MgO redüksiyonunda, en yüksek geri kazanım verimi ise %93,75 ile Al- CaO·MgO redüksiyonunda elde edilmiştir.
Bu çalışmada, kahve telvesi ve yumurta akı kullanılarak yeni nesil biyosıvalar geliştirilmiş ve bu malzemelerin gözeneklilik özellikleri ile ısı yalıtım performansları analiz edilmiştir. Kahve telvesi, lifli ve gözenekli yapısı sayesinde düşük yoğunluk ve düşük ısı iletim katsayısı sağlamaktadır. Yumurta akı ise bağlayıcı ve güçlendirici özellikleriyle malzemenin yapısal dayanıklılığını artırmıştır. Çalışmada, köpürtülmüş ve köpürtülmemiş yumurta akı kullanılarak altı farklı numune hazırlanmış ve SEM görüntüleri üzerinden gözenek dağılımları incelenmiştir. Segmentasyon analizleri sonucunda, köpürtülmüş yumurta akı içeren numunelerde gözeneklilik oranlarının %65–85 arasında olduğu, bunun da ısı yalıtım performansını belirgin şekilde iyileştirdiği görülmüştür. Buna karşın, köpürtülmemiş yumurta akı ile hazırlanan numunelerde gözeneklilik oranı düşük kalmış ve yalıtım performansı zayıflamıştır. Elde edilen bulgular, kahve telvesi ve yumurta akı karışımının biyobazlı ve çevre dostu bir yalıtım malzemesi olarak kullanılabileceğini ortaya koymaktadır. Özellikle köpürtülmüş yumurta akı ile hazırlanan numuneler, geleneksel çimento esaslı sıvalara kıyasla daha yüksek gözeneklilik ve düşük ısıl iletkenlik gösterebileceği sergilemiştir. Bu sonuçlar, biyosıvaların sürdürülebilir yapı malzemeleri arasında yer alabileceğini göstermektedir. Çalışma ayrıca döngüsel ekonomi ilkelerine katkı sağlayarak atık yönetimi, enerji verimliliği ve karbon emisyonlarının azaltılmasına yönelik stratejik bir çözüm sunmaktadır.
The need for energy has significantly increased in recent decades as a result of rapid urbanization, excessive energy consumption and population growth. This leads to environmental problems such as climate change, water and air pollution. Predicting energy consumption can reduce these problems and helps energy management and efficacity. In this paper, we investigate the performance of several machine learning methods, such as linear regression, K-Nearest neighbor, support vector regressor, random forest, gradient boosting, and stacking to predict energy consumption in Tetouan city, in Morocco. To evaluate the performance of these models, evaluation metrics such as MAE, RMSE, and R2 were used. Stacking method provided outstanding performance and the best result with accuracy of 98.13%, 98.11% and 99.05% in zone 1, 2, 3, respectively.
In this study, metallic magnesium was produced using the Magnetherm process with different magnesium sources and various reducing agents. Magnesium oxide (MgO) and dolomite (CaO·MgO) were used as magnesium sources, while aluminum chips (Al), ferrosilicon (FeSi), and calcium carbide (CaC2) served as reducing agents. The effects of using different magnesium sources and reductants under identical experimental parameters on both reduction efficiency and recovery yield were investigated. The experiments were carried out for 1.5 minutes at a current of 600 A in the Al- CaO·MgO, FeSi-MgO, FeSi-CaO·MgO, CaC2-MgO, and CaC2-CaO·MgO systems. Thermodynamic modeling was performed using the FactSage software, and the results were compared with experimental findings. The produced magnesium was obtained in powder form, and various analyses were performed on both magnesium powders and slags. XRD and carbon determination tests were applied to the magnesium powders and slags; atomic absorption spectroscopy (AAS) was used for the magnesium powders; and XRF analysis was conducted on the slags. According to the experimental results, the highest reduction efficiency was obtained in the FeSi-CaO·MgO system with 98.17%, while the highest recovery yield was achieved in the Al- CaO·MgO system with 93.75%.
In this study, SCGA590 automotive steel was joined using the resistance spot welding method with three different currents (8 kA, 10 kA, and 12 kA) and two different time values (100 ms and 200 ms), while keeping other welding parameters constant. The microstructure of the specimens obtained under different parameters was examined in detail, and microhardness tests were performed. The high temperature generated during the welding process and the subsequent rapid cooling caused regional changes in the microstructure. Accordingly, three distinct regions were identified in the welded joint: the base metal, the heat-affected zone, and the weld metal. Due to the microstructure, the hardness values increased from the base metal to the weld metal. The highest hardness value (621 HV) was achieved in the sample obtained with welding current parameters of 10 kA and a welding time of 200 ms.
With the technological advancements, global urbanization, and dynamic socio-economic progress, the demand for strategic raw materials (SRMs) is expected to increase in the coming years, making raw material assessment both inevitable and indispensable. The comprehensive criticality assessment of these materials inherently involves a multitude of parameters, raw materials, and constantly changing variables. European Union (EU) has systematically conducted assessments of critical raw materials (CRMs) on a triennial basis since 2011. This paper focuses on the final report on CRMs for the EU, where SRMs including Bismuth, Boron, Cobalt, Gallium, Germanium, Lithium, Magnesium, Manganese, Natural Graphite, Copper, Silicon, Titanium, Tungsten, and Nickel were first added to the list. In this context, the Entropy and CRITIC (Criteria Importance Through Inter-criteria Correlation) methods were applied for subjective weighting using real data, while SWARA (Stepwise Weight Assessment Ratio Analysis) and AHP (Analytical Hierarchy Process) were used to incorporate the assessments of participating experts. These methods were employed to determine the weights of the main criteria, including supply risk (SR), economic importance (EI), main supplier share, evaluation of materials linked with sector share and value-added, substitution (EI and SR), and import reliance in the criticality matrix. Across all applied methodologies, the computational results consistently converge to demonstrate that supply risk, value-added, and import reliance are most profoundly associated with the comprehensive assessment of SRMs. The findings guide policymakers in developing countries in tailoring their own criticality assessments based on the most essential criteria.
In this study, the effects of different heat treatment conditions on the microstructure, hardness, and machinability performance of precipitation-hardenable martensitic Corrax steel were investigated. Following various heat treatments, microstructural evolution and hardness variations were examined, while machinability performance was evaluated through dry turning experiments conducted with uncoated cutting tools. The results revealed that the hardness of the Corrax material increased up to 50 HRC depending on the applied heat treatment temperature; however, when aged at higher temperatures (600 °C), a decrease in hardness occurred due to over-aging. In the machinability tests, the highest cutting force was observed in the A6 specimen, which was attributed to the formation of reverted austenite during the aging process. Conversely, the lowest cutting force values were generally obtained in the A0 specimen. The lowest surface roughness values were also predominantly measured in the A6 specimen. Overall, the aging treatments led to an increase in cutting forces. The most remarkable finding of the study was that the maximum cutting force was not recorded in the hardest specimen but in the A6 condition, a phenomenon associated with the transformation of retained austenite into martensite under machining-induced deformation.
Among the advancing technology, energy management systems and power electronics studies are becoming more and more significant day by day. Therefore, the application areas of buck converters in industrial and consumer electronics are increasing day by day. In this study, a simple and effective real-time controller for buck converters is designed and implemented. The study aims to performance the dynamic performance of the system and reduce energy losses by using the advantages of real-time control. One of the most important objectives is to reduce complex programming processes by using a model-based approach. With this model-based approach, easy changes of the system are provided with a fast intervention to the changes in the system. With the developed TMS320F28379D based real-time control approach, the stability and response time of the buck converter are tested. Simulations and experimental studies have shown that the proposed hardware and software architecture provides stable, fast and accurate results in the control of buck converters. As a consequence, this study aims to contribute to the field of power electronics by providing an effective, simple and accessible control mechanism that improves energy conversion processes. In addition, since the results obtained can be used as a reference in the design of similar systems, it is expected to be useful for both academic and industrial applications. When the voltage control of the buck converter is made for 2 Volts, the voltage change, and the duty cycle reach the desired steady state in 1.75*10-3 seconds. The results show that the proposed control structure provides a suitable and reliable solution for industrial applications. Future studies on energy efficiency and control systems will open the door to innovative designs in this field.
Bu araştırma, farklı coğrafi konumlardan kaynaklanan yoğun trafiği kullanarak sistemleri çökerten siber saldırılar olan DDoS saldırılarının, ağ performansını nasıl etkilediğini incelemeyi amaçlamıştır. Volumetrik, protokol ve uygulama katmanındaki DDoS saldırılarının, ağ üzerindeki etkileri simülasyonlarla incelenmiş ve bu saldırıların sistemlerin işlem gücünü ve bant genişliğini nasıl tükettiği detaylı olarak analiz edilmiştir. Özellikle çoklu kaynaklı saldırıların, tespit ve savunma sistemlerini zorlaması üzerine odaklanan bu çalışma, Ddosphere simülasyon aracıyla desteklenmiştir. Elde edilen sonuçlar, ağ yöneticileri ve siber güvenlik uzmanlarına, ağ performansını artırmak ve DDoS saldırılarına karşı daha etkili savunma stratejileri geliştirmek için değerli bilgiler sunmaktadır. Bu çalışma, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu'nun desteklediği "DDOS Tabanlı Siber Saldırı Test Modülü" projesi kapsamında Virgosol tarafından yürütülmüştür.
