Results 61 to 70 of about 796 (198)
From rights to runtime: Privacy engineering for agentic AI
AI Magazine, Volume 46, Issue 4, Winter 2025.Abstract Agentic AI shifts stacks from request‐response to plan‐execute. Systems no longer just answer; they act—planning tasks, calling tools, keeping memory, and changing external state. That shift moves privacy from policy docs into the runtime.
Keivan Navaie
wiley +1 more source
An integrated approach to solving retrial queue complexity
, 2018 Retrial queues have been proposed in literature as a means of managing lost traffic in wireless cellular networks. However, the retrial queue system has led to a more complex Markovic process in network analysis.
Nwakamma, P.A. +2 more
core +1 more source
Offline Learning for Acknowledgment Optimization in Massive LoRaWAN Networks
Internet Technology Letters, Volume 8, Issue 6, November/December 2025.ABSTRACT LoRaWAN faces critical limitations in large‐scale deployments due to spectrum contention, duty‐cycle restrictions, and energy constraints. These challenges impact the reliability and responsiveness of bidirectional communication particularly when conventional acknowledgment mechanisms are used.
Leila Aissaoui Ferhi
wiley +1 more source
The single server retrial queue with finite population: a BSDE approach
, 2012 This paper uses the block-structured state-dependent event (BSDE) approach to generalize the scalar version of the single server retrial queue with finite population.
López Herrero, María Jesús +1 more
core +1 more source
IEEE Access, 2019 In a cognitive radio (CR) system, excessive access services for secondary users (SUs) lead to a substantial increase in congestion and the retrial phenomenon, both of which degrade the performance of CR networks, especially in overload conditions.
Yu Zhang, Jinting Wang, Wei Wayne Li
doaj +1 more source
Heterogeneous Finite-Source Retrial Queues [PDF]
Journal of Mathematical Sciences, 2004 The paper considers a system with \(K\) different sources of primary calls, each consisting of a single request. When source \(i\) is free at time \(t\) (i.e., is not being served and not waiting for serving), it may generate a primary call during interval \((t,t + dt)\) with probability \(\lambda _i dt + o(dt)\).
Almási, B., Bolch, G., Sztrik, J.
openaire +1 more source
Cytometry Part B: Clinical Cytometry, Volume 108, Issue 5, Page 392-403, September 2025.Abstract Machine‐learning (ML) models in flow cytometry have the potential to reduce error rates, increase reproducibility, and boost the efficiency of clinical labs. While numerous ML models for flow cytometry data have been proposed, few studies have described the clinical deployment of such models.
Lauren M. Zuromski +10 more
wiley +1 more source
Analysis of an M/{Dn}/1 retrial queue
, 2007 We consider a single server retrial queueing system in which each customer (primary or retrial customer) has discrete service times taking on value Dj with probability pj,j=1,2,…, and ∑j=1∞pj=1.
Wu, Xiaoyong, Ke, Xiaowu
core +1 more source
AxiomsIn this article, we consider a make-to-stock queueing system with retrial customers. Upon their arrival, customers make a decision to either join the system or not based on a reward–cost function.
Yuejiao Wang, Chenguang Cai
doaj +1 more source
Engineering Reports, Volume 7, Issue 7, July 2025.Flow chart highlighting the service mechanism of MRP with impatience and working breakdown of the server. ABSTRACT The long‐term reliability of a machining system is essential for ensuring the uninterrupted operation of an automated manufacturing process.
Shreekant Varshney +4 more
wiley +1 more source