DSpace Arşivi :: Ana Sayfa

İstanbul Gelişim Üniversitesi Kurumsal Açık Erişim Arşivi

DSpace@Gelişim, İstanbul Gelişim Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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A Comprehensive Survey on Handover Management Techniques Toward Seamless Mobility in 5G and Beyond Heterogeneous Networks
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2026) Khan, Sajjad Ahmad; Tashan, Waheeb; Shayea, Ibraheem; Kucik, Kerem; Aldırmaz Çolak, Sultan; Chaudhry, Shehzad Ashraf; Yahya, Khalid
Handover failures and service interruptions remain critical challenges to seamless mobility in Fifth Generation and beyond (B5G) heterogeneous cellular networks (HetNets). In these environments, ultra-dense deployments and coexisting Radio Access Technologies (RATs) dramatically increase the complexity of mobility control. User Equipment (UE) frequently switches between macro cells, small cells, and different RATs. These frequent switches introduce risks of service disruption, excessive signaling overhead, and degraded user experience. Therefore, Handover Management (HOM) has become one of the most critical functions in modern mobile networks. This paper presents a comprehensive survey of HOM techniques designed to support seamless mobility in B5G HetNets. The survey begins by reviewing the handover mechanisms defined in recent Third Generation Partnership Project (3GPP) releases, from Release 15 through Release 18. Their operational principles and practical limitations in dense multi-tier cellular architectures are discussed. The survey then examines existing mobility optimization methods, including parameter tuning, mobility robustness optimization, and coordinated mobility control. Particular attention is given to intelligent Mobility Management (MM) approaches based on Machine Learning (ML). These approaches enable predictive mobility analysis, adaptive handover parameter adjustment, and context-aware decision-making in large-scale radio access networks. The role of Software Defined Networking (SDN) in enabling centralized and programmable handover control is also analyzed, along with joint SDN and ML frameworks that support self-optimizing network behavior. The survey further examines how emerging technologies may shape future MM frameworks. These technologies include Integrated Sensing and Communication (ISAC), Reconfigurable Intelligent Surfaces (RIS), Non-Terrestrial Networks (NTN), and Integrated Access and Backhaul (IAB) architectures. Several open challenges are also discussed. These include the scalability of mobility prediction algorithms in dense deployments, security management during handover procedures, and latency constraints for Ultra-Reliable Low-Latency Communication (URLLC) services. Finally, the survey outlines important research directions for future mobility-aware network architectures in B5G and Sixth Generation (6G) cellular systems. This survey reveals that while ML-based and SDN-assisted approaches offer significant gains in handover robustness, critical gaps remain in real-time deployment, scalability, and security-aware mobility design for next-generation networks.
Hydrothermal assessment of a hybrid geometry-optimized microchannel and internal jet-impingement cooling architecture for advanced chips
(PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, 2026) Alshehery, Sultan; Dobrota, Dan; Stoica, Augustin; Sawwan, Hussain; Saeidlou, Salman; Maleki, Nemat Mashoofi; Mahariq, Ibrahim
The increasing power density of modern electronic chips demands advanced cooling solutions capable of high heat removal and temperature uniformity. This study experimentally investigates a hybrid cooling architecture integrating microchannel cold plates with internal jet impingement. In this design, water jets are delivered through small-nozzle tubes that are strategically distributed along the microchannel to provide localized heattransfer enhancement. Three microchannel geometries—rectangular, arc-shaped, and sinusoidal—are evaluated under heat loads of 500–1000 W and flow rates of 1–4 l/min. Results indicate that the sinusoidal geometry achieves the highest overall hydrothermal efficiency, with jet integration yielding substantial performance gains. At 4 l/min and 1000 W, the hybrid sinusoidal design enhances the Nusselt number by 37.3% and reduces thermal resistance by 21.8%, while lowering the average surface temperature by up to 16 ◦C compared to a conventional plain cold plate. The thermal enhancement factor reaches 1.278, despite an associated pressure drop penalty. Furthermore, the hybrid design reduces the minimum flow rate required for safe operation and enhances energy reuse capability, achieving up to an 11% increase in the Energy Reuse Factor (ERF) compared to the traditional plain cooling block.
Effect of multi-directional forging in a closed die after extrusion on Gd and Y added AZ61 Mg alloy
(SAGE PUBLICATIONS INC, 2455 TELLER RD, THOUSAND OAKS, CA 91320, 2026) Özdamar, Osman; Yetmez, Mehmet; Kocaman, Engin; Türen, Yunus; Özyiğit, Hamdi Alper
In this study, 0.5 and 1 wt.% Gadolinium (Gd) and Yttrium (Y) rare earth elements were added to the AZ61 magnesiumalloy. The alloys were exposed to extrusion at 375 degrees C, followed by multi-directional forging in a closed die at 400 degrees C. Themicrostructural changes and mechanical properties of the alloy were examined. The addition of rare earth elements and theapplied mechanical processes led to a significant reduction in grain size in the AZ61 cast alloy. The addition of Gd and Ypromoted the formation of the Al2(Y,Gd) intermetallic structure, which contributed to heterogeneous nucleation andincreased hardness. The extrusion and multi-directional forging processes further contributed to afine-grained, equiaxedmicrostructure. As a result of the grain refinement, notable improvements in the mechanical properties were observed.In mechanical tests, samples with 0.5% Gd and 0.5% Y achieved the highest tensile strength (290 MPa) and hardness values(113 HV). In contrast, a slight decrease was observed with 1% additions, indicating that the optimal rare earth elementcontent is 0.5%.
Synthesis, X-Ray Analysis, Anticancer Activity, Computational, and in Silico Studies of New Thiophene Pyrazole Conjugates
(WILEY-V C H VERLAG GMBH, POSTFACH 101161, 69451 WEINHEIM, GERMANY, 2026) Muhsinah, Abdullatif Bin; Kheder, Nabila A.; Elhaty, Ismail A. M.; Mabkhot, Yahia N.
A convenient synthesis of two new thiophene-appended pyrazoles, 8a and 8b, from thiophene derivative 3 is reported. The structures of the synthesized compounds were confirmed by infrared, nuclear magnetic resonance, and mass spectroscopy analysis, while compound 8a was further confirmed by single-crystal X-ray diffraction and computational studies. The crystal structure of 8a revealed a nonplanar conformation stabilized by N─H···O hydrogen bonding and a weak C─H···O/N contacts. Hirshfeld surface analysis of 8a showed that H···H contacts dominate the packing, accounting for 52.8%. Density functional theory calculations showed a highest occupied molecular orbital–lowest unoccupied molecular orbital gap of 3.999 eV, indicating a moderate electronic stability with charge transfer ability. The in vitro antitumor activity of the synthesized compounds was evaluated against liver (HepG2), breast (MCF-7), and colorectal (HCT-116) cancer cell lines, using the sulforhodamine B (SRB) assay. Compound 3 showed the highest activity against MCF-7 (IC50 = 2.2 ± 0.3 μg/mL), while the thiophene pyrazole hybrid 8b demonstrates greater activity than 8a against all tested cell lines. In silico evaluation indicated that 8b showed the most balanced safety and drug likeness profile.
Istanbul Gelisim University School of Foreign Languages: Monthly Bulletin (May 2026)
(İstanbul Gelişim Üniversitesi / Istanbul Gelisim University, 2026) Istanbul Gelisim University School of Foreign Languages
Artificial Intelligence in Language Learning: 5 Lesser-Known Facts Artificial Intelligence (AI) is increasingly reshaping the field of language learning, offering tools that go far beyond traditional classroom methods. While most people are familiar with translation apps or grammar checkers, AI’s role in language acquisition is far more complex and, in some cases, surprising. Below are five lesser-known facts that highlight how AI is transforming the way languages are learned and understood. 1. AI can detect how you learn, not just what you learn. Modern language-learning systems use learner modeling to analyze patterns in mistakes, response time, and revision behavior. This allows AI to identify whether a learner is more visual, repetitive, or context-based, and then adjust exercises accordingly. 2. Some AI systems simulate “forgetting curves.” Inspired by cognitive psychology, AI platforms often replicate the human memory decay process. They schedule vocabulary review sessions at scientifically optimized intervals, ensuring that words are revisited just before they are likely to be forgotten.