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Analysis Of Agricultural Remote Sensing Data Driven By Artificial Intelligence On Crop Growth Patterns And Economic Benefits Of Grain, Yang Wang

Turkish Journal of Agriculture and Forestry

To address the shortcomings of conventional agricultural statistical and monitoring methods on a regional scale, this paper proposes the use of artificial intelligence-driven remote sensing data for analysing crop growth patterns and the economic benefits of grain. Winter wheat data from three stations in a single province from 2011 to 2020 was used, with the leaf area index (LAI) used as the key crop growth indicator value. The simulated annealing algorithm was used to assimilate the LAI and remote sensing leaf area index (MODIS-LAI), simulated by the World Food Study (WOFOST) simulation model, to carry out simulation analysis of winter …

Nitrogen Transport Patterns And Vegetation Community Optimization In Urban Green Space Soils Using Multifactor Coupling Analysis, Shujian Yang, Baoxi Yu, Zheng He, Baochang Liu, Chang Liu

Turkish Journal of Agriculture and Forestry

As vital components of urban ecosystems, urban green spaces directly affect soil fertility and plant growth through nitrogen transport dynamics. This study addresses the existing methodological gaps in understanding nitrogen cycling within urban green spaces, particularly the unclear interaction mechanisms between vegetation structure and soil physicochemical characteristics. The study was conducted in the Green Expo Park located in Nanjing, China. Using a stratified sampling approach, physicochemical indicators of soil layers were measured and combined with community parameters—including leaf area index, vegetation coverage, and plant density—to identify key drivers through correlation and multiple regression analyses. The regulatory mechanisms of soil physicochemical …

Mitigation Of Salinity Stress In Carnation Plants Through Zinc Oxide Nanoparticles: Growth, Physiological, And Biochemical Responses, Adel A. Rezk, Ishtiaq Ahmad, Maryam, Muhammad Saleem, Othman Al-Dossary, Hossam S. El-Beltagi, Mohammed Aldaej, Bader Y. Alsubaie, Hati̇ce Gülen, Tarek Shalaby, Riaz Ahmad

Turkish Journal of Agriculture and Forestry

Carnation (Dianthus caryophyllus L.) growth and floral yield are severely reduced when grown in soils with excessive salinity. Mitigation of adverse effects from salinity-induced stress is necessary for sustainable carnation cultivation. Although various approaches have been developed, the use of zinc oxide nanoparticles (ZnO-NPs) to ameliorate these effects remains scarcely explored. The current study explored the potential of ZnO-NPs to alleviate salinity-induced stress by examining their effects on morphophysiological and biochemical traits. A controlled pot experiment was conducted using a factorial design with three concentrations of sodium chloride (0, 50, and 100 mM) and three of ZnO-NPs (0, 50, and …

Housing System And Gender Effect On Carcass And Meat Quality Characteristics In Turkish Pekin Ducks, Hasan Önder, Uğur Şen, Mi̇ne Yilmaz, Si̇bel Bozkurt, Eli̇f Ci̇lavdaroğlu, Di̇lek Gökçek, Ahmet Uçar, Kadi̇r Erensoy, Burcu Kurnaz

Turkish Journal of Veterinary & Animal Sciences

Improving meat quality is one of the most important aims for scientists and breeders. This study aimed to evaluate the effects of housing system (indoor vs. free-range) and gender on carcass and meat quality traits in Pekin ducks. The animal material consisted of 20 male and 20 female birds in each housing system. Our results show cold carcass weights of 3174.10 ± 80.65 g and 2672.60 ± 59.63 g for male and female birds in the indoor housing system and 2821.10 ± 50.53 g and 2306.90 ± 43.32 g for male and female birds in the free-range housing system. The …

Effects Of Preslaughter Fasting On Ph And Bacterial Contamination In Akkaraman And Anatolian Merino Sheep, Sai̇m Boztepe, Özcan Şahi̇n, Talha Demi̇rci̇, Gi̇zem Coşkun, İbrahi̇m Ayteki̇n, İsmai̇l Keski̇n

Turkish Journal of Veterinary & Animal Sciences

The present study investigates the effects of the preslaughter fasting on pH and bacterial contamination in Akkaraman and Anatolian Merino sheep. Included in the study were 10 Akkaraman and 10 Anatolian Merino sheep (n = 20) that were fasted for 24 h prior to slaughter, and a further 10 Akkaraman and 10 Anatolian Merino sheep (n = 20) that continued to be fed until slaughter as a control group. The total mesophilic aerobic bacteria (TMAB) measured at 0 and 24 h in the fasting Akkaraman and Anatolian Merino sheep were 4.87/4.79 and 4.75/5.57 log CFU/g, respectively, and the corresponding Enterobacteriaceae …

Cover And Contents

Turkish Journal of Medical Sciences

No abstract provided.

Res-Mnd: Motor Neuron Disease Detection Using Res4net–Convolutional Block Attention Module ​, Shuriya Balusamy, Rakesh Sivalingam, Shobana Rooben, Sony Helen

Turkish Journal of Medical Sciences

Background/aim: Motor neuron diseases (MNDs) are progressive neurological disorders that cause muscle weakness and wasting as a result of ongoing neurodegeneration. MNDs require comprehensive diagnostic approaches that integrate clinical symptoms, laboratory findings, and multimodal imaging data.

Materials and methods: In this study, a novel residual network for motor neuron disease detection (RES-MND) framework is proposed for detecting MNDs using multimodal imaging data. Initially, the input multimodal images, including MRI, CT, PET, and DTI, are preprocessed using adaptive dynamic histogram equalization and the total variation bilateral filter. The preprocessed multimodal images are processed through Res4Net-CBAM for feature extraction to enhance image …

Sun-Macerated Hypericum Perforatum Oleates In Fixed Oils: Analytical Characterization And Comparative Wound-Healing Activity, Ci̇han Çapar, Esra Akkol, Ayli̇n Yaba, Ayhan Parmaksiz, Engi̇n Sümer, Erdem Yeşi̇lada

Turkish Journal of Medical Sciences

Background/aim: Hypericum perforatum L. oleates prepared in fixed oils have long been used for wound management due to their anti-inflammatory, antibacterial, and tissue-regenerative properties. The bioactivity of these oleates is mainly attributed to hypericin, hyperforin, and pseudohypericin. This study aimed to comparatively evaluate the wound-healing potential of H. perforatum oleates prepared in different fixed oils, including Olea europaea L. (olive), Sesamum indicum L. (sesame), Helianthus annuus L. (sunflower), and Nigella sativa L. (black seed).Materials and methodsFixed oils were characterized by GC–MS, while oleuropein in olive oil and thymoquinone in black seed oil were quantified by HPLC, and sesamin and sesamol …

Serum Phosphoproteome Alterations Associated With Cardiac Troponin I Levels In Acute Myocardial Infarction ​, Merve Öztuğ, Meltem Aşicioğlu, Konca Altinkaynak, Evren Kilinç

Turkish Journal of Medical Sciences

Background/aim: Acute myocardial infarction (AMI) triggers systemic biochemical responses, including dynamic changes in the phosphorylation status of circulating proteins. However, the phosphoproteomic profile of serum in the context of AMI remains insufficiently characterized. This study aimed to investigate serum phosphoproteomic alterations associated with AMI and to explore potential correlations with markers of cardiac injury.

Materials and methods: A comparative phosphoproteomic analysis was performed on serum samples obtained from eight patients with AMI and pooled healthy control samples. High-abundance serum proteins were depleted, and phosphopeptides were enriched using TiO2 phosphopeptide enrichment kit. Samples were analyzed by liquid chromatography–tandem mass spectrometry using …

Comprehensive Profiling Of Gut Microbiota In Postmenopausal Osteoporosis ​, Gülsemi̇n Ertürk Çeli̇k, Sedat Yildiz, Münevver Aksoy Bektaş, Yaprak Engi̇n-Üstün

Turkish Journal of Medical Sciences

Background/aim: Osteoporosis is a multifactorial skeletal disease that predominantly affects postmenopausal women and is characterized by reduced bone mass and an increased risk of fractures. Growing evidence suggests that the gut microbiota plays a pivotal role in bone metabolism through immunological, endocrine, and metabolic pathways, forming the basis of the so-called gut– bone axis. This study aimed to characterize gut microbiota composition in postmenopausal women with osteoporosis compared with healthy controls.

Materials and methods: Forty postmenopausal women aged 55–65 years were classified into osteoporosis (n = 20) and healthy control (n = 20) groups based on dual-energy X-ray absorptiometry T-scores. …

Long-Term Measurements Of Global Solar Radiation In Osmaniye, Türkiye (2014–2023), Muhi̇tti̇n Şahan, Hali̇de Şahan, Ramazan Kaya

Turkish Journal of Physics

This paper presents the horizontal solar radiation data for Osmaniye (37◦04′N, 36◦22′E), located in Mediterranean region of Türkiye, over the period 2014–2023. Solar radiation variability, recorded at 1-min intervals, was evaluated in terms of hourly, daily, monthly, seasonal, and annual averages. Over the 10-year periods, the mean daily total and daily average global radiations received on a horizontal surface were 1,360,000 W/m2 and 371.47 W/m2, respectively. The monthly averaged daily global radiation (averaged over the 10-year period) ranged from 202.94 W/m2 in December to 496.86 W/m2 in July. The seasonal average values of solar radiations were 452.14 W/m2 in summer, …

Two-Dimensional Inverse Scattering Solution Using Nurbs Expansion And A Deep Learning Method, Meisam Shafaee

Turkish Journal of Physics

This paper presents a novel framework for solving two-dimensional (2D) inverse scattering problems by integrating nonuniform rational B-spline (NURBS) parameterization with convolutional neural networks (CNNs). Tra ditional pixel/voxel-based deep learning methods often suffer from high dimensionality and discretization artifacts, while purely geometric approaches lack robust inversion mechanisms. To address these limitations, we propose a hybrid frame work where the relative permittivity profile of an unknown scatterer is compactly represented as a NURBS surface, parameterized by a sparse set of control points and weights. This approach reduces the problem dimensionality over 16 times. On the other hand, using NURBS expansion ensures …

From Stability To Spintronics: A Comprehensive High-Throughput Investigation Of 2d Mf4 Lieb Lattices, Uğur Yorulmaz

Turkish Journal of Physics

The research on two-dimensional (2D) materials which have intrinsic magnetism and exotic electronic struc tures is an important quest in condensed matter physics. The Lieb lattice offers a unique platform for studying strongly correlated electron phenomena. In this work, we systematically investigated the structural, dynamical, mechanical, electronic, and magnetic properties of monolayer transition metal tetrafluorides (MF4, where M = Ag, Cd, Cr, Cu, Fe, Hf, Mn, Mo, Nb, Ni, Pd, Pt, Rh, Ru, Sc, Ta, Ti, V, W, and Y) arranged in a 2D Lieb lattice, using first-principles calculations based on density functional theory (DFT) with Hubbard (U) corrections. Our …

Artificial Intelligence In Mycology: A Systematic Review Of Species Identification, Biotechnological Assessment, And Explainable Deep Learning Methods, Fati̇h Eki̇nci̇, Mehmet Serdar Güzel, Ilgaz Akata

Turkish Journal of Botany

This review offers a comprehensive analysis of the expanding role of artificial intelligence (AI) in mycological research. It highlights how AI supports the identification of fungal taxa at both microscopic and macroscopic levels, facilitates the detection of toxic species, contributes to ecological mapping, aids in discovering new fungal bioproducts, and enhances precision agriculture practices. Advanced techniques such as convolutional neural networks, you only look once, U-shaped network (UNet), and residual network have demonstrated strong performance in classification, segmentation, and object detection tasks. Additionally, explainable AI (XAI) methods like gradient-weighted class activation mapping (Grad-CAM), local interpretable model-agnostic explanations (LIME), and SHapley …

Nonnative Crayfish In Türkiye: Presence Records, Invasion Pathways, And Ecological Risks, Muzaffer Mustafa Harlioğlu

Turkish Journal of Zoology

The globalization of trade, aquaculture, and the ornamental pet industry has accelerated the transboundary movement of nonnative crayfish species, with significant ecological consequences. Türkiye, a biodiversity-rich country bridging Europe and Asia, has increasingly become a point of concern due to the rising presence of alien crayfish taxa introduced primarily via the aquarium trade and scientific research. This study investigates the presence records of nonnative crayfish species in Türkiye, identifies their likely introduction pathways, and outlines potential future outspread routes across the major freshwater basins of the country. Species such as Procambarus clarkii, Cherax quadricarinatus, C. albertisii, and Cambarellus patzcuarensis have …

Stage-Specific Growth Characteristics Of The Calanoid Copepod Invader Sinodiaptomus Sarsi​, Leonid Svetlichny, Kami̇l Mert Eryalçin, Melek İşi̇ni̇bi̇li̇r Okyar

Turkish Journal of Zoology

The population dynamics of the Asian invasive copepod Sinodiaptomus sarsi were  studied for four years after its introduction into an artificial pond in Kyiv (Ukraine) in  2020. The growth and development parameters of this species were measured under  laboratory conditions. From its first appearance in spring 2020, the abundance  of copepodite stages and adults increased from 3.5–5.2 individuals (ind.)  m–3 to 1057.8 ind. m–3 in June 2024, suggesting the successful establishment  of S. sarsi populations in this region. A characteristic feature of S.  sarsi development in ponds is a male-biased sex ratio in the later copepodite stages.  The sex ratio …

Geochemistry Of The Upper Jurassic–Lower Cretaceous Limestone Of The Bilecik Formation In The Dümrek Area (Eskişehir, Western Central Anatolia): Implications For Depositional Environment And Paleotemperature, Asuman Kahya, Meti̇n Bağci

Turkish Journal of Earth Sciences

Upper Jurassic–Lower Cretaceous limestones of the Bilecik Formation are exposed near the village of Dümrek (Eskişehir Province) within the Sakarya Zone. Mineralogical analyses reveal that these limestones are predominantly composed of calcite and include intraclasts, fossil shell fragments, ooids, and peloids, cemented by sparry and micritic calcite. The U/Th, Ni/Co, V/(V+Ni), V/Cr, and Ce/Ce* ratios indicate that these carbonates were deposited in an oxic environment. Furthermore, the Mn/Sr ratios imply no diagenetic alteration, indicating preservation of the original geochemical signature. The PAAS-normalized REE+Y patterns of these limestones display depletion in light rare earth elements, a pronounced positive La anomaly (La/La* …

Neotectonics Of The Malatya Basin, Se Türkiye; Implications Of The Reactivations Of The Faults Of The Basin During 6 February 2023 Earthquakes Of The East Anatolian Fault System, Yaşar Ergun Gökten, Doğan Kalafat

Turkish Journal of Earth Sciences

The Malatya Basin (MB) is a fault-controlled superimposed sedimentary basin situated in the SE of Anatolia, near and to the north of the East Anatolian Fault System (EAFS). The rock units ranging from the Permo–Carboniferous to the Upper Miocene form the basin’s basement. The thickening of the Upper Cretaceous–Upper Miocene sequence toward the Malatya Fault (MF), the basin’s northwestern boundary, indicates a dip-slip-dominated character for the MF and its control on the first-step sedimentation of the basin. The MF changes its character from dip-slip normal to the strike-slip in the Late Pliocene, and today presents a 1700-m left lateral offset, …

Numerical Study Of Porosity Effects On Temperature And Fluid Flow In Black Sea Gas Hydrates, Bahar Güvem, Doğa Doğan

Turkish Journal of Earth Sciences

Numerical temperature and fluid flow simulations were conducted using ANSYS Fluent to investigate the influence of porosity variations on the temperature distribution within the gas hydrate layer. The study was carried out in the Black Sea region, where the gas hydrate deposits are of particular interest due to their potential for energy resources. The simulations explored various porosity levels within the hydrate layer to observe their effect on thermal behavior and fluid dynamics. The results revealed that porosity plays a significant role in modulating the temperature distribution within the gas hydrate layer, with lower porosity models exhibiting higher temperatures compared …

Effects Of Seismic Filters On Pretrained Cnn Models For Fault Detection: Application To The Delft 3d Seismic Volume, The Netherlands, Süleyman Alemdar, Ertan Pekşen

Turkish Journal of Earth Sciences

Accurate mapping of faults from 3D seismic volumes is critical for identifying structural traps, assessing reservoir compartmentalization, and guiding drilling decisions. This study evaluates how common seismic conditioning filters affect both the visual quality of a production Delft 3D poststack time-migrated volume and the outputs of two pretrained 3D CNN fault detectors: UNet3D and FaultNet. Seven filters were applied independently—AJAX, DeSmile, SimpleDenoise, Dip-Steered Median Filter (DSMF), Edge-Preserving Smoother (EPS), Fault Enhancement, and Ridge Enhancement—and results were inspected across inline, crossline, time-slice, and full-cube perspectives. The analysis is image-driven, supported by high-resolution comparison figures and view-specific interpretations.Filters that suppress incoherent noise …

Integrated Dinsar And Hvsr Microtremor Analysis For Understanding Ground Deformation And Site Effects: Case Study Of The Bawean Earthquake (M6.5), Joshua Purba, Muhammad Fikri Hayqal Hiola, Ramadhan Priadi, Riska Yulinda, Iham Ilham, Rosa Amelia

Turkish Journal of Earth Sciences

This study investigates the seismic hazards of Bawean Island following a recent M6.5 earthquake using an integrated approach combining differential interferometric synthetic aperture radar (DInSAR) and horizontal-to-vertical spectral ratio (HVSR) methodologies. The DInSAR analysis revealed ground deformation characterized by subsidence up to 10 cm and uplift up to 8 cm, correlating with the region’s strike-slip fault dynamics. HVSR analysis provided insights into site amplification effects, identifying zones with low Vs30 values (153.77–454.72 m/s), high amplification factors (A0), and elevated seismic vulnerability index values (Kg). The dominant frequency (f0) on Bawean Island ranges from 0.64 to 17.76 Hz, with most areas …

Burdigalian–Langhian Flora Of The Çan–Etili (Çanakkale) Basin, Compared With Those Of Western Türkiye, Sari̇ye Duygu Durak, Mehmet Serkan Akki̇raz

Turkish Journal of Earth Sciences

A palaeofloristic study was carried out on Lower–Middle Miocene deposits of western Türkiye (Çan–Etili Basin). The sediments of the Çan–Etili Basin, which were obtained from measured sections, were deposited in a continental environment. The palaeovegetation of the Çan–Etili Basin (Kazım Oğlak and Keçiağılı successions) during the Early–Middle Miocene was mainly made up of evergreen and deciduous mixed forests (Castanea–Castanopsis, Cyrillaceae–Clethraceae, Engelhardia, Quercus evergreen-type, Quercus deciduous-type), riparian vegetation with high quantities of Alnus and conifers such as Pinus haploxylon-type, Pinus diploxylon-type, and undifferentiated Pinaceae. The reconstructed palaeoclimate data from the palaeoflora (pollen and leaves) imply a warm and temperate climate, with …

Enhanced Antenna Selection Techniques For Energy-Efficient Code Index Modulation Aided Spatial Modulated Wireless Communication Systems, Fati̇h Çögen, Burak Ahmet Özden, Erdoğan Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an integrated multiple-input multiple-output (MIMO) transceiver framework, termed CIM-HQAM-SM, which combines code index modulation (CIM) and spatial modulation (SM) with energy-efficient hexagonal quadrature amplitude modulation (HQAM). In the proposed bit mapping, the information bits jointly select (i) the active transmit-antenna index, (ii) the Walsh–Hadamard spreading-code indices for the in-phase and quadrature branches, and (iii) an HQAM symbol. Hence, the payload is conveyed through the constellation symbol as well as through antenna and code indices. For the considered Rayleigh-fading scenarios and matched spectral-efficiency settings, the proposed framework offers BER improvements over conventional SM and quadrature SM (QSM), while …

An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra

Turkish Journal of Electrical Engineering and Computer Sciences

Computational Psychiatry represents a burgeoning realm within scientific inquiry, delving into the intricate interplay of neurobiology within the brain. The escalating prevalence of mental illness underscores the urgency to confront this challenge. Among the prevalent disorders, Schizophrenia and Bipolar Disorder loom large, affecting a significant portion of the population at some point in their lives. However, pinpointing psychiatric disorders poses a formidable challenge. Genetic predispositions significantly influence the development of mental illnesses, with intriguing overlaps observed among certain disorders. This convergence complicates accurate diagnosis. Here, a deep learning approach is considered for significant gene biomarker identification and classification of Schizophrenia …

Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents SENTISEC, a hybrid LLM-based threat detection framework designed to classify security logs by integrating keyword heuristics, domain-adapted sentiment scoring, and Retrieval-Augmented Generation (RAG). The system achieves an overall accuracy of 93.67%, with 91.46% macro recall, 89.07% macro F1, and 95.15% threat recall, while maintaining a low false-positive rate of 1.68%. Its methodology incorporates strict keyword and IOC matching, a domain-tuned DistilBERT sentiment module, hybrid BM25–MiniLM retrieval enhanced with BGE reranking, adaptive quantile-based threshold calibration, and SHAP-based explainability. Comparative evaluations against keyword-only, sentiment-only, classical machine-learning models, and DistilBERT-only baselines show that SENTISEC consistently improves both true-positive and true-negative …

Optimal Network Reconfiguration Based On Discrete Metaheuristic Techniques For Reduction Of Power Loss And Carbon Emission In Distribution Networks, Asad Ali, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hussain Shareef, Hasmaini Mohamad, Munir Azam Muhammad

Turkish Journal of Electrical Engineering and Computer Sciences

Power distribution systems play a crucial role in transmitting electrical power from generation sources to end users. During transmission, significant power losses occur in the form of heat as the current flowing along the lines/cables has resistance. To minimize power losses, distribution network reconfiguration (DNR) has been widely adopted. This paper proposes optimal DNR based on metaheuristic techniques with discrete mutation feature targeting active power loss reduction, which subsequently lowers carbon emissions and operational costs. Through the discrete mutation feature, computational time to find optimal solution has been reduced significantly with fewer iterations compared to conventional mutation techniques. The proposed …

Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid, Dushmanta Kumar Das, Samaniba Imchen

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining smart grid stability is crucial for the reliable operation of decentralized electricity networks, especially as the energy sector becomes more complex. The process of ensuring grid stability begins with collecting consumer data and comparing it to power supply requirements. Ultimately, consumers receive a report showing their energy use and pricing details. However, this process is time-consuming and can be improved by leveraging artificial intelligence to predict smart grid stability more efficiently. Specifically, an optimized Long Short-Term Memory (LSTM) network is proposed to predict smart grid stability, addressing the challenges associated with traditional data collection and evaluation methods. Simulations from …

Reducing Complexity In Versatile Video Coding Intra-Coding Through Machine Learning-Based Optimization Of Partitioning And Prediction, Amina Kessentini, Amna Maraoui, Imen Werda, Fatma Ezahra Sayadi

Turkish Journal of Electrical Engineering and Computer Sciences

The escalating demand for high-resolution multimedia content has necessitated more efficient video compression solutions. The Versatile Video Coding (VVC) standard, despite achieving remarkable compression gains, introduces significant computational complexity, primarily due to its exhaustive Rate-Distortion Optimization (RDO) process. To address this, we propose an intelligent approach leveraging supervised machine learning techniques to streamline the VVC encoding process. Specifically, we introduce a Lightweight Neural Network (LNN) for efficient coding unit partitioning decisions and a Decision Tree (DT) classifier for optimizing the intra prediction process. This dual-method framework, tailored for All Intra coding configuration, significantly reduces encoder complexity while maintaining compression performance …

Designing Risk-Aware Mixed-Mode Evacuation Strategies For Tsunamis: Insights From İstanbul, Vedat Bayram, Doruk Ergez, Ada Arikanoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

​Tsunamis pose severe and time-critical risks to densely populated coastal cities, where limited warning times and infrastructure constraints demand carefully coordinated evacuation strategies. This study develops an integrated, risk-aware optimization framework that jointly considers vertical and horizontal sheltering options together with mixed pedestrian-vehicular evacuation dynamics. The proposed mixed-integer second-order cone programming (MISOCP) model simultaneously determines vertical shelter location, evacuee assignment, road-use designation for pedestrians and vehicles, and route selection under congestion, capacity, and budget constraints. Vehicle travel times incorporate congestion effects through a convex flow-dependent function, while pedestrian routing ensures convergent and conflict free evacuation paths. A risk-minimization objective accounts …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.