Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Shooting a Water Slug Into an Air Column with and without Vent(Amer Soc Mechanical Engineers, 2025-07-20) Bozkus, Zafer; Dincer, Ali Ersin; Tijsseling, Arris S.; van de Ven, FonsCompressed air is used to shoot a single water slug into an upward sloping pipe with elbow and orifice at its upper end. The experiment concerns a 12 m long pipe of 0.1 m diameter connected to a 0.5 m3 air vessel. The 10 to 50 kg heavy slugs are initially at rest in the lower part of the system. Because the upper end is closed by a flange with orifice, the water slug is expected not to hit the upstream elbow. It causes - like a piston - a fast compression of the air column ahead of it. Sometimes the slug bounces back and forth, which results in a pressure oscillation of serious amplitude. Numerical simulations based on an elementary mathematical model are normally used to interpret the pressure measurements, not all of which are fully understood. Lessons learned are summarised, and suggestions for improved experiments and enhanced simulations are given. The research is of importance, for example, for steam lines where liquid condensates may collect in lower parts after power failure. Start-up of the system will then lead to rapid slug acceleration and potentially damaging impact on elbows, orifices, and machinery.Book Part Design and Analysis of a Solar-Assisted Combined Cooling, Heating, and Power System for Smart Cities: Case Study From Doha(IGI Global, 2025-08-22) Akroot, A.; Almohammedi, A.A.; Talal, W.The rising demand for sustainable and energy-efficient solutions in urban areas has driven interest in renewable systems for smart cities. This chapter presents a solar-assisted combined cooling, heating, and power (SA-CCHP) system designed for Doha, Qatar, where high solar radiation and cooling needs prevail. Powered solely by a parabolic trough collector (PTC) field, the system delivers net power from 1200 kW in winter to 195 kW in summer, with cooling loads of ~2100-3400 kW and heating loads of ~90)00-14500 kW. Increasing the superheating degree at the ORC turbine inlet enhances power and heating but reduces cooling, while raising the pressure ratio (A) from 0.5 to 0.8 boosts net output and efficiency, cutting CO2 emissions from 0.22 to 0.13 kg/kWh. Overall energy efficiency rises from 85% to 90% and exergy efficiency from 76% to 78.5%, while costs decline from $40/hr to $36/hr, confirming both environmental and economic viability. The study demonstrates the feasibility of solar-powered CCHP systems as scalable models for achieving clean energy goals in smart cities. © 2026, IGI Global Scientific Publishing. All rights reserved.Conference Object Fully Flexible, Low-Cost, Environmentally Friendly Yarn-Based Inp/Ag Nw Photodetectors for UV-Visible Light Detection(SPIE, 2025-08-01) Savaş, M.; Akrema, A.; Ocal, S.K.; Erdem, T.We report the fabrication and investigate of a novel photodetector using a heterostructure of InP quantum dots (QDs) and silver nanowires (Ag NWs) incorporated into yarn. This device is simple, scalable, low-cost, flexible, and functions under ambient conditions. Ag NWs and red-emitting InP QDs were separately synthesized via chemical methods and mixed in a specific ratio to coat functional yarns, which were then knitted into fabrics. The photodetector benefits from the excellent electrical conductivity of Ag NWs and the strong optical absorption of InP QDs. It shows enhanced photoelectric response in both UV and visible regions. At 405 nm illumination, the device achieves a photoresponsivity of 5.8 mA W-1 and a detectivity of 2 × 1010 Jones-values comparable to or exceeding those of similar devices. The enhanced performance is attributed to efficient charge transfer enabled by favorable band alignment between Ag NWs and InP QDs, along with synergistic effects from nanostructure dimensionality and quantum confinement. The device's combination of flexibility, sensitivity, and cost-efficiency makes it a strong candidate for wearable UV-visible photodetectors. © 2025 SPIE. All rights reserved.Conference Object Minimising the Cycle Time with Assembly Line Balancing and Worker Assignment: A Case Study in a Medical Device Manufacturer Company(ISRES Publishing, 2025-10-27) Kayser, A.; Sipahi, G.; Sevimli, O.; Toplu, N.; Turan, S.; Satic, U.In this research, we considered the mixed-model assembly line balancing and worker assignment problems of a medical device manufacturer in Türkiye. We combined these problems into a single integer programming model where multiple types of products can be assembled simultaneously on a single assembly line, and workers are assigned to workstations based on their abilities while ensuring the balance and efficiency of the assembly line. Our proposed approach seeks to minimise the cycle time and ability-based assignment costs on the assembly line. We used the Gurobi solver to find the optimal solution for the proposed problem. Our approach provides higher efficiency and results in a 76% increase in productivity without requiring additional work hours or workers. © 2025 Published by ISRES Publishing.Conference Object Scheduling in Flexible Flow Shop Environments with Re-Entrant Jobs and Heterogeneous Workers(ISRES Publishing, 2025-10-27) Bekli, S.; Kayisoglu, B.In many industries, manufacturing is organized as a flexible flow shop (FFS), which has gotten the researchers' attention. The scheduling studies, particularly those on FFS scheduling, are concerned with homogeneous workers with the same skill set or heterogeneous workers who can only perform one specific type of operation on the production lines. Moreover, jobs are mainly assumed to go through an operation once. Yet, in real-life production, workers might have different skill sets with varying processing times. Furthermore, certain jobs may require revisiting the same machine multiple times, i.e., re-entrant jobs. We study an FFS environment with re-entrant jobs, considering worker flexibility. We propose a mixed integer linear programming model to find the optimal sequences of jobs to be processed by the multiskilled workers assigned to the production system, ensuring each re-entrant job waits for a predefined time window before reprocessing on the same operation. The objective of the model is to minimize makespan. We tested the proposed model on a dataset taken from a real production system of a PVC windows and doors production facility. © 2025 Published by ISRES Publishing.Article Citation - WoS: 1Citation - Scopus: 1Numerical Analysis and Experimental Comparison of Stress and Stiffness Parameters of Steel Reinforced Geopolymer Concrete Columns(Elsevier Sci Ltd, 2026-01) Ozbayrak, Ahmet; Kucukgoncu, Hurmet; Aslanbay, Huseyin Hilmi; Aslanbay, Yuksel Gul; Altun, FatihDespite extensive research, Geopolymer concrete (GPC) lacks reinforced concrete construction and design specifications. Developing such specifications requires comprehensive studies to promote the use of GPC, which is known for its superior performance and environmental benefits compared to ordinary Portland cement concrete (OPC). This study numerically investigated and compared the behavior and strength of fly ash-based geopolymer-reinforced concrete columns with the experimental results. Comparisons with OPC were made based on existing specifications. Herein, FEM analyses were conducted on 16 GPC and 4 OPC columns under eccentric axial compressive loads. Parameters such as eccentricity, reinforcement ratio, curing method, and activation solution ratios were varied. According to average numerical results, the GPC columns have 7% more moment capacity and 30% more curvature values than OPC. Moreover, GPC columns absorbed more energy than OPC columns. Also, GPC columns have higher axial load and bending moment carrying capacities than OPC for numerical results. Error analysis between FEM and experimental data revealed a strong correlation, with MAPE values of 8.88% (axial load) and 7.20% (moment) for GPC columns, confirming the reliability of the numerical model. ACI 318 and Eurocode 2 specifications were deemed applicable for GPC columns, provided axial loads are limited per TEC 2018.Article Citation - WoS: 4Citation - Scopus: 3Multifaceted Effects of the Dielectric Component Within Plasmon-Assisted Light-Emitting Structures(American Chemical Society, 2025-10-23) Kulakovich, O.; Muravitskaya, A.; Ramanenka, A.; Efimova, T.; Krukov, V.; Mutlugün, E.; Gaponenko, S.Plasmon-enhanced photoluminescence of molecular probes and semiconductor nanocrystals is a rapidly developing field that promises enhanced sensitivity in chemical and biomedical analyses, as well as higher efficiency of light-emitting devices and single-photon sources. The dielectric component, or spacer, is typically used to control the distance between the emitter and the plasmonic nanoparticle in order to decrease undesirable nonradiative energy transfer to the metal and achieve high enhancement efficiency. While most research focuses on the shape and organization of the plasmonic nanoparticles, less attention is given to the role of the dielectric component in plasmon-enhancing structures. Meanwhile, the dielectric shell or environment critically modulates near-field enhancement, far-field scattering, charge and energy exchange between the emitter and the plasmonic structure, and the general environmental stability of the structure. In this review, we discuss all mentioned topics and therefore consider both the optical and chemical influence of the widely used spacers and dielectric layers on plasmon-enhanced photoluminescence efficiency. Investigating the role of individual components in plasmon-assisted light-emitting structures is critical for optimizing device performance and for advancing the integration of plasmonic architectures in optoelectronic and sensing applications. This review challenges the passive interpretation of dielectrics, revealing them as one of the key players in plasmonic structures, mediating field enhancement, emission dynamics, and chemical stability simultaneously. © 2025 American Chemical SocietyArticle Citation - WoS: 1Citation - Scopus: 1An Ultra-Low Fabric Capacitive Glove for Real-Time Motion Tracking and Human–computer Interaction(Institute of Physics, 2025-11-04) Başıbüyük, Y.; Mutluç, M.N.; Şavur, Ö.; İçöz, K.This study presents the development of a wearable glove system that integrates ultra-low-cost, fabric-based capacitive sensors for motion detection and human–computer interaction. The system combines touch and bend sensors fabricated from commercially available silver-coated fabric and silicone acrylic tape, enabling real-time tracking of finger movements via measurable capacitance changes. The glove translates physical gestures into digital commands, facilitating intuitive control in virtual environments. Experimental evaluation demonstrated stable operation across a wide pressure range (10–200 g, equivalent to 1.25–25 kPa), with an unnormalized sensitivity of ∼0.00504 pF g−1 (∼0.0040 pF kPa−1), corresponding to a normalized sensitivity of ∼0.0067 kPa−1 when referenced to the baseline capacitance (C<inf>0</inf> ≈ 6 pF). The device exhibited high repeatability over 4000 loading cycles, and minimal signal variation (coefficient of variation, CV < 0.005). Integration with a Unity-based interface enabled low-latency gesture tracking in real time. Each sensor was fabricated for less than $0.05 using simple, scalable methods, without nanomaterials or cleanroom processing. Owing to its affordability, fabrication simplicity, and mechanical robustness, the proposed glove system provides a practical and scalable platform for wearable motion tracking, with strong potential in rehabilitation, assistive technologies, and interactive systems. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.Article Citation - WoS: 2Citation - Scopus: 2Measuring Eudaimonic and Hedonic Wellbeing: Development and Validation of the Holistic Wellbeing Measure(Routledge, 2025-10-09) Arslan, G.; Coşkun, M.The primary goal of this study was to develop a concise, theoretically grounded tool –the Holistic Wellbeing Measure (HWM)– that captures both hedonic and eudaimonic facets of wellbeing. Items for the HWM were generated through a careful review of existing wellbeing scales and literature, followed by expert consultation, pilot testing, and iterative refinement to ensure conceptual coverage, clarity, and face validity. Data were collected from three distinct samples: adolescents (n = 453), young adults (n = 361), and adults (n = 358). Exploratory and confirmatory factor analyses supported a two-factor structure, with 12 items reflecting independent but related hedonic and eudaimonic wellbeing dimensions. The measure demonstrated strong internal reliability and evidence of convergent, discriminant, and concurrent validity across all age groups. Regression analyses further indicated that the HWM contributed unique variance to the prediction of general health indicators (physical, social, and mental health) and psychological problems (depression, anxiety, and somatization), above the effects of gender, age, and psychological wellbeing. These results suggest that the HWM is a valid and reliable measure for assessing both aspects of wellbeing across age groups and can support strategies aimed at promoting overall mental health. © 2025 Taylor & Francis Group, LLC.Conference Object Enhancing Complex Disease Group Scoring with Mirgedinet: A Multi-Algorithm Machine Learning Framework Based on the GSM Approach(IEEE, 2025-06-25) Qumsiyeh, Emma; Bakir-Gungor, Burcu; Yousef, MalikIntegrating biological prior knowledge for disease gene associations has shown significant promise in discovering new biomarkers with potential translational applications. This work investigates the application of a multi-algorithm machine learning framework based on the Grouping-Scoring-Modeling (G-S-M) approach for improving the prediction of complex diseases. The study identifies the primary gene and miRNA interactions in various complex diseases with the help of miRGediNET, which is a machine-learning based tool that integrates data from three biological databases. Traditional methods have only focused on independence between features; the G-S-M method focuses on aggregating genes based on biological interactions, pinpointing the scoring of gene groups for a disease, and modeling its predictive capability using advanced machine learning algorithms. In this research paper, seven algorithms, including Support Vector Machine, Decision Tree, and CatBoost, were applied to eight datasets extracted from the GEO database. This framework proved very robust in ranking gene clusters, thus predicting critical biomarkers while doing 100-fold randomized cross-validation within the evaluation. The results indicate this approach's high potential for refining disease and supporting research for choosing the best algorithm that can provide biological insights and computational advances.