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Finite Difference Method for Advanced Volterra Integro-Differential Equation with Delay
No full textThe aim of this paper is to introduce a numerical method for advanced Volterra delay integro-differential equation with initial condition. A finite difference scheme on a uniform mesh using the trapezoidal formula is developed to numerically solve this problem. Additionally, demonstrated that this approach yields second-order convergence in the discrete maximum norm. The proposed method is validated through the presentation of numerical results
Power Production by Using the Hydroelectric Power Plants and Cost Effect on Electricity Market in Türkiye
No full textPower production through hydroelectric power plants is one of the important methods to produce electricity because of the use of alternative resources while considering the climate issues in our current world. On the other hand, growing economies demand energy in the sectors; therefore, energy demand increases correlatively with sustainable economic growth. In this context, increasing power generation, reducing carbon emissions, and reducing energy generation costs by protecting energy reliability are the main objectives in an energy market. Since the climate issues, these aims require the utilization of the renewable energy source maximum at present. Accordingly, this study mainly aims at the economic analysis of the power generation from hydroelectricity in the electricity market for Türkiye by comprehending the contribution of hydroelectric power plants. Since the 2050 roadmap of hydroelectricity might be beneficial to form the scenarios as realistic as possible by considering the hydroelectric capacity in Türkiye, the long-range energy alternative planning (LEAP) model is used to analyze the cost-effectiveness by applying the scenarios. In this way, the acquired data regarding the energy demands and costs in the energy market for the different scenarios are used to make future predictions and aspects in Turkey. © 2025 Elsevier B.V., All rights reserved
Synthesis, Dielectric and Magnetic Characterization and Properties of Nano Magnetic Particles by using Microwave Technique
Get PDFA microwave-induced combustion method has been utilized to prepare nano-sized powders of hexagonal ferrites using urea and glycine as fuel. The dielectric and magnetic properties of these products were investigated experimentally, the dielectric properties were investigated with the RF LCR device, the magnetic properties were investigated with the Electron Spin Resonance (ESR) and Vibration Sample Magnetometer (VSM) spectrometer, and the crystalline structure was investigated with the X-ray diffraction (XRD) device
Lise öğrencilerinin sürdürülebilir kalkınmaya yönelik tutumları ile sürdürülebilir kalkınmaya yönelik farkındalık düzeyleri arasındaki ilişkinin incelenmesi
Get PDFThe objective of this study is to examine the relationship between attitudes towards sustainable development among high school students and their awareness levels regarding sustainable development. A total of 519 students from years 9 to 12 in a northwestern Turkish province participated voluntarily in the study. The data collection tools employed in the study were the "Attitude Scale towards Sustainable Development" and the "Sustainable Development Awareness Determination Questionnaire". The relational screening method was utilised to ascertain the relationships between the variables in the study. The findings indicated that the attitudes of high school students towards sustainable development and their awareness levels in this regard were moderate. Following the execution of correlation analyses to examine the relationships between the attitude levels of high school students towards sustainable development and their awareness levels and its sub-dimensions, a moderately significant positive correlation was identified between attitude and awareness scores (.477). Furthermore, a highly significant positive correlation was identified between the participants' total attitude scores and their sub-dimensions (.869, .803, .876). In addition to these findings, a highly significant positive correlation was identified between the participants' awareness scores and their sub-dimensions. Furthermore, a moderately significant positive correlation was identified between the participants' attitude sub-scores and their awareness sub-scores. In view of these findings, it is recommended that environmental education topics be incorporated more extensively in curriculum curricula, in accordance with the 2030 sustainable development goals.Bu araştırmanın amacı, lise öğrencilerinin sürdürülebilir kalkınmaya yönelik tutumları ile sürdürülebilir kalkınmaya yönelik farkındalık düzeyleri arasındaki ilişkinin incelenmesidir. Araştırma doğrultusunda Türkiye’nin kuzeybatı bölgesinde bulunan bir ilin 9, 10, 11 ve 12. sınıflardan 519 lise öğrencisi gönüllü olarak çalışmaya katılmıştır. Araştırmanın veri toplama araçları olarak “Sürdürülebilir Kalkınmaya Yönelik Tutum Ölçeği” ve “Sürdürülebilir Kalkınma Farkındalıklarını Belirleme Anketi” kullanılmıştır. Çalışmada değişkenler arasındaki ilişkileri belirlemek amacıyla ilişkisel tarama yöntemi kullanılmıştır. Elde edilen bulgulara göre; lise öğrencilerinin sürdürülebilir kalkınmaya yönelik tutumları ile sürdürülebilir kalkınmaya yönelik farkındalık düzeylerinin orta düzeyde olduğu tespit edilmiştir. Lise öğrencilerinin sürdürülebilir kalkınmaya yönelik tutum düzeyleri ile sürdürülebilir kalkınmaya yönelik farkındalık düzeyleri ve alt boyutları arasındaki ilişkilerin incelenmesi için yapılan korelasyon analizleri sonrasında tutum ile farkındalık puanları arasında pozitif yönde orta düzeyde anlamlı korelasyon olduğu bulunmuştur ( .477). Bunun yanında katılımcıların tutum toplam puanları ile alt boyutları arasında pozitif yönde yüksek düzeyde anlamlı korelasyon olduğu tespit edilmiştir ( .869, .803, .876). Bu bulgulara ilave olarak katılımcıların farkındalık puanları ile alt boyutları arasında pozitif yönde yüksek düzeyde anlamlı korelasyon olduğu tespit edilmiştir. Bunların yanında katılımcıların tutum alt puanları ile farkındalık alt puanları arasında pozitif yönde orta düzeyde anlamlı korelasyon olduğu bulunmuştur. Bu bulgular ışığında çevre eğitimi konularının 2030 sürdürülebilir kalkınma hedefleriyle de ilişkili bir biçimde ders öğretim programlarında daha geniş yer bulması önerisinde bulunulabilir
Boundary calculations for transformations associated with the hermite-hadamard inequalities
Get PDFBu tezde, ikinci mertebeden diferansiyellenebilen sınırlı fonksiyonlar için orta nokta tipi ve yamuk tipi eşitsizlikleri incelenmiştir. İkinci türevinin alt ve üst sınırları olan fonksiyonlar yardımıyla yeni integral eşitsizlikleri sunulmuştur. Hermite-Hadamard integral eşitsizliğinin iki özel dönüşümle ilişkilendirilmesi ve bu dönüşümlerin sınırlarının hesaplanması üzerine odaklanılmıştır. Ayrıca, Bullen eşitsizliğinin iki ters eşitsizliği, aritmetik ortalama ve logaritmik ortalamaya ilişkin çeşitli uygulamalar sunulmuştur. Anahtar Sözcükler: Hermite-Hadamard Eşitsizliği, Konveks Fonksiyonlar, OrtalamalarIn this thesis, midpoint type and trapezoid type inequalities for second order differentiable bounded functions are investigated. New integral inequalities are presented by means of functions with lower and upper bounds of their second derivatives. Focus is placed on the association of the Hermite-Hadamard integral inequality with two special transformations and the computation of the bounds of these transformations. Also, two inverse inequalities of Bullen's inequality, various applications of the arithmetic mean and the logarithmic mean are presented
Comparison of Automation-Supported and Conventional Methods for Measuring Energy Consumption in Computer Numerical Control Machining
Get PDFOptimizing energy consumption in machining processes is critical for achieving sustainable manufacturing. This study introduces an Automation-Supported measurement approach that integrates a custom power analyzer with real-time data logging and visualization capabilities to accurately measure energy usage during CNC (computer numerical control) operations. Statistical comparisons were conducted using the independent samples t-test and Taguchi analysis to evaluate the effectiveness of the proposed method against traditional measurement techniques. The results revealed that there is a statistically significant difference (p < 0.05) in the current measurements across X, Z, and spindle motors between the proposed and conventional methods. The advanced method based on automation reduced the error rate in measuring spindle motor power consumption due to the selection of processing parameters from 34.17% to 2.7%. Additionally, Taguchi analysis demonstrated that the measurement method influenced the optimization of machining parameters, with S/N ratio improvements observed. These findings confirm that the proposed method enhances energy efficiency, reduces environmental impact, and supports sustainable manufacturing practices.TUBITAK (The Scientific and Technological Research Council of Turkey)[2200215]The work was supported by TUBITAK (The Scientific and Technological Research Council of Turkey) (Project No.: 2200215)
A Decision-Making Framework for Struggling with Digital Supply Chain Barriers through Industry 5.0 Technologies
Get PDFPurpose: The objective of this research is to determine and rank methods for overcoming implementation hurdles for Digital Supply Chains (DSCs) in the context of the Industry 5.0 (I5.0) framework. Methodology: First, twenty-three DSC barriers hindering the digitalization of the manufacturing supply chain and nine Industry 5.0 technologies to overcome them were defined with an extensive literature review and expert opinions. The importance weights of the identified criteria were calculated using the Full Consistency Method (FUCOM). Multi-Attribute Ideal-Real Comparative Analysis (MAIRCA), Multi-Attributive Border Approximation Area Comparison (MABAC) and Additive Ratio Assessment (ARAS) method were used to rank the Industry 5.0 (I5.0) technologies. The results were compared with each other using different ranking methods. Sensitivity analysis was performed for all ranking methods to monitor the consistency of the results. Findings: The results showed that “high initial investment”, “issues with data” and “complexity in integrating systems” are the most important DSC barriers to overcome first. To overcome these barriers, “virtual training” and “blockchain” technologies seem to be the most important I5.0 innovations that should be addressed primarily. Originality/Value: By identifying the critical barriers to DSC and prioritizing the I5.0 technologies needed to overcome them, this study provides a solid framework for future research and practical applications in the Digital Transformation (DT) journey of companies. © 2025 Elsevier B.V., All rights reserved
Mitosis detection from breast histopathology images with transformer architectures
Get PDFMeme kanseri kadınlarda en sık görülen kanser türüdür. Histopatolojik görüntü analizinde, mitoz hücrelerinin tespiti ve sayısı, kanser derecesinin ve saldırganlığının prognozunda önemli bir biyo belirteçtir. Mitozun patolog tarafından manuel olarak tespit edilmesi uzun ve zorlu bir süreçtir. Derin öğrenme mimarilerindeki gelişmelerle birlikte, çok sayıda otomatik mitoz tespit yöntemi önerilmiştir. Ancak çoğu mitoz tespit yöntemi, görüntü alanları arasında zayıf genelleştirme yeteneğine sahiptir. Bu tez çalışmasının amacı, meme histopatolojisi görüntülerinden mitoz tespiti sorunlarına çözüm getirecek, yüksek doğrulukta, objektif ve hızlı sonuçlar elde edilmesini sağlayacak yeni bir yöntem geliştirmektir. Bu amaçla son zamanlarda medikal alanda üstün başarılar gösteren dönüştürücü mimarisine dayalı üç farklı otomatik mitoz tespit yöntemi önerilmiştir. Önerilen ilk model, mitozun tespiti için DETR'in geliştirilmiş bir versiyonudur ve Mi-DETR olarak adlandırılmıştır. Mi-DETR modeli, CSPResNeXt omurgası, katman azaltma sctratejisi ve CIoU kayıp fonksiyonu ile optimize edilmiştir. Önerilen ikinci modelde, mitozun segmentasyonu için SegFormer mimarisi kullanılmıştır. Deneylerde kullanılan ICPR14 ve TUPAC16 veri setleri, mitoz segmentasyonu için SAM modeli ile segmentasyon veri setlerine dönüştürülmüştür. Mitozun hassas segmentasyonu için MiT-B0'dan MiT-B5'e kadar farklı kodlayıcılar denenmiştir ve ince ayarlar yapılmıştır. Önerilen üçüncü model mitozun tespiti ve segmentasyonu için DETR'in ve SegFormer'ın güçlü yönlerini birleştiren hibrit Mi-SegDeTr yöntemi önerilmiştir. Tüm deneylerde ICPR14 ve TUPAC16 meme histopatolojisi veri setleri kullanılmıştır. Sonuç olarak, önerilen Mi-DETR modeli ile ICPR14 veri setinde 0,921 ve TUPAC16 veri setinde 0,950 F1-Skoru elde edilmiştir. SegFormer modeli ile ICPR14 veri setinde 0,8962 ve TUPAC16 veri setinde 0,8272 F1-Skoru elde edilmiştir. Son olarak Mi-SegDeTr modeli ile ICPR14 veri setinde segmentasyon için 0,9044, tespit için 0,9658 ve TUPAC16 veri setinde segmentasyon için 0,9189, tespit için 0,9684 F1-Skoru elde edilmiştir. Her iki veri seti üzerinde elde edilen sonuçlar, önerilen Mi-SegDeTr modelinin son teknoloji mitoz tespit yöntemleri ile yarışabilecek kadar iyi performans gösterdiğini ortaya koymuştur.Breast cancer is the most common type of cancer among women. In histopathological image analysis, the detection and count of mitotic cells serve as a crucial biomarker for grading cancer and predicting its aggressiveness. Manual identification of mitotic cells by pathologists is a time-consuming and challenging process. With advancements in deep learning architectures, numerous automated mitosis detection methods have been proposed. However, most mitosis detection methods have poor generalization ability across image fields. This thesis aims to develop a novel method that addresses the challenges of mitosis detection in breast histopathology images, providing high accuracy, objectivity, and rapid results. For this purpose, three different automated mitosis detection methods based on the transformer architecture, which has recently demonstrated remarkable success in medical applications, have been proposed. The first proposed model is an enhanced version of DETR for mitosis detection, referred to as Mi-DETR. The Mi-DETR model is optimized with a CSPResNeXt backbone, a layer reduction strategy, and the CIoU loss function. In the second proposed model, the SegFormer architecture is utilized for mitosis segmentation. The ICPR14 and TUPAC16 datasets used in the experiments were converted into segmentation datasets with the SAM model for mitosis segmentation. Various encoders, ranging from MiT-B0 to MiT-B5, were tested and fine-tuned for precise mitosis segmentation. The third proposed model, a hybrid method called Mi-SegDeTr, combines the strengths of DETR and SegFormer for both mitosis detection and segmentation. All experiments were conducted using the ICPR14 and TUPAC16 breast histopathology datasets. As a result, the proposed Mi-DETR model achieved F1-scores of 0.921 on the ICPR14 dataset and 0.950 on the TUPAC16 dataset. The SegFormer model yielded F1-scores of 0.8962 on the ICPR14 dataset and 0.8272 on the TUPAC16 dataset. Finally, the Mi-SegDeTr model achieved F1-scores of 0.9044 for segmentation and 0.9658 for detection on the ICPR14 dataset, and 0.9189 for segmentation and 0.9684 for detection on the TUPAC16 dataset. The results obtained on both datasets demonstrate that the proposed Mi-SegDeTr model performs competitively with state-of-the-art mitosis detection methods
Investigation of Gait Characteristics and Kinematic Deviations in Rare Genetic Disorders with Instrumented Gait Analysis
Get PDFBackground: Dravet Syndrome (DS), Helsmoortel-Van Der Aa Syndrome (HVDAS) and Tuberous Sclerosis Complex (TSC) are rare genetic syndromes, sharing intellectual disability (ID) and motor delay. In DS, two distinct gait patterns, crouch and non-crouch, have been described using instrumented 3D gait analysis (i3DGA). This cross-sectional study measures gait in participants with TSC and HVDAS. The findings are compared to the known crouch and non-crouch gait patterns observed in DS and to typical gait. Methods: Participants (6-22 years) with DS (n = 37; 19 crouch and 18 non-crouch), HVDAS (n = 12) or TSC (n = 8) were compared with typically developing (TD) peers (n = 33). All participants underwent i3DGA (Plugin Gait model processed with Vicon Nexus and MATLAB (R)) to investigate spatiotemporal and lower-limb kinematics. Results: All three genetic syndromes showed increased step width. Participants with HVDAS and DS, but not participants with TSC walked with decreased step length and velocity compared to TD. HVDAS demonstrated increased knee flexion during the stance phase, lack of hip extension during pre-swing, and increased ankle dorsiflexion during some phases of the gait cycle (p 0.05). Conclusion: The current study reveals differences in gait characteristics from typical functional gait in rare genetic disorders. DS-Crouch, DS-NonCrouch and HVDAS display a more impaired gait from a biomechanical perspective than TSC. The variability of clinical and genetic features might explain heterogeneity in gait deviations and should be further explored.Flemish Research CouncilUniversity of AntwerpUniversity Hospital of AntwerpResearch Foundation Flanders [FWO FKM 1805321N]University of Pennsylvania Orphan Disease Center [MDBR-23-003-STXBP1][T003116N]We would like to thank the patients for their participation. This study was supported by the Flemish Research Council (grant number T003116N), the University of Antwerp, the University Hospital of Antwerp and clinical gait lab of Heder. AJ is supported by a fellowship from the Research Foundation Flanders (FWO FKM 1805321N). LG was supported by a research grant from the University of Pennsylvania Orphan Disease Center in partnership with Lulu's Crew/STXBP1 Disorders (MDBR-23-003-STXBP1)
Enhancing Smart Grid Reliability Through Data-Driven Optimisation and Cyber-Resilient EV Integration
Get PDFThis study presents a novel cyber-resilient, data-driven optimisation framework for real-time energy management in electric vehicle (EV)-integrated smart grids. The proposed framework integrates a hybrid optimisation engine-combining genetic algorithms and reinforcement learning-with a real-time analytics module to enable adaptive scheduling under uncertainty. It accounts for dynamic electricity pricing, EV mobility patterns, and grid load fluctuations, dynamically reallocating charging demand in response to evolving grid conditions. Unlike existing GA/RL schedulers, this framework uniquely integrates adaptive optimisation with resilient forecasting under incomplete data and lightweight blockchain-inspired cyber-defence, thereby addressing efficiency, accuracy, and security simultaneously. To ensure secure and trustworthy EV-grid communication, a lightweight blockchain-inspired protocol is incorporated, supported by an intrusion detection system (IDS) for cyber-attack mitigation. Empirical evaluation using European smart grid datasets demonstrates a daily peak demand reduction of 9.6% (from 33 kWh to 29.8 kWh), with a 27% decrease in energy delivered at the original peak hour and a redistribution of demand that increases delivery at 19:00 h by nearly 25%. Station utilisation became more balanced, with weekly peak normalised utilisation falling from 1.0 to 0.7. The forecasting module achieved a mean absolute error (MAE) of 0.25 kWh and a mean absolute percentage error (MAPE) below 20% even with up to 25% missing data. Among tested models, CatBoost outperformed LightGBM and XGBoost with an RMSE of 0.853 kWh and R2 of 0.416. The IDS achieved 94.1% accuracy, an AUC of 0.97, and detected attacks within 50-300 ms, maintaining over 74% detection accuracy under 50% novel attack scenarios. The optimisation runtime remained below 0.4 s even at five times the nominal dataset scale. Additionally, the study outlines a conceptual extension to support location-based planning of charging infrastructure. This proposes the alignment of infrastructure roll-out with forecasted demand to enhance spatial deployment efficiency. While not implemented in the current framework, this forward-looking integration highlights opportunities for synchronising infrastructure development with dynamic usage patterns. Collectively, the findings confirm that the proposed approach is technically robust, operationally feasible, and adaptable to the evolving demands of intelligent EV-smart grid systems