Results 101 to 110 of about 14,317,493 (293)

Decision problem for infinite duration semi-Markov process [PDF]

, 2014
In the paper there are presented basic concepts and some results of the theory of semi-Markov decision processes. The optimization problem for the infinite duration SM process is connsider in the paper.
Grabski, F.
core  

The risk probability optimal problem for infinite discounted semi-Markov decision processes [PDF]

summary:This paper investigates the risk probability minimization problem for infinite horizon semi-Markov decision processes (SMDPs) with varying discount factors.
Wen, Xian, Cui, Jinhua, Huo, Haifeng
core   +1 more source

Bridging Human and Plant Adaptations for Climate Resilience

PLANTS, PEOPLE, PLANET, EarlyView.
Climate change is transforming agriculture through both gradual shifts and increasingly unpredictable extremes, challenging farmers' ability to protect crops and livelihoods. This study brings together farmer experiences and plant adaptation strategies to explore how people and plants respond to similar climate pressures.
Nicola Favretto, Heng Lim Tan, Gemma Brain, Daphne Ezer   +3 more
wiley   +1 more source

Semi‐mechanistic population PK/PD model to aid clinical understanding of myelodysplastic syndromes following treatment with Venetoclax and Azacitidine

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 448-459, March 2025.
Abstract Myelodysplastic syndromes (MDS) represent a group of bone marrow disorders involving cytopenias, hypercellular bone marrow, and dysplastic hematopoietic progenitors. MDS remains a challenge to treat due to the complex interplay between disease‐induced and treatment‐related cytopenias.
Neha Thakre, Corinna Maier, Jiuhong Zha, Benjamin Engelhardt, Johannes E. Wolff, Sven Mensing   +5 more
wiley   +1 more source

The Shared Experience Actor–Critic (SEAC) Approach for Allocating Radio Resources and Mitigating Resource Collisions in 5G-NR-V2X Mode 2 Under Aperiodic Traffic Conditions

Sensors
5G New Radio (NR)-V2X, standardized by 3GPP Release 16, includes a distributed resource allocation Mode, known as Mode 2, that allows vehicles to autonomously select transmission resources using either sensing-based semi-persistent scheduling (SB-SPS) or
Sawera Aslam, Daud Khan, KyungHi Chang
doaj   +1 more source

Wide sense one-dependent processes with embedded Harris chains and their applications in inventory management [PDF]

In this paper we consider stochastic processes with an embedded Harris chain. The embedded Harris chain describes the dependence structure of the stochastic process.
Bazsa, E.M., Iseger, P. den
core  

Semi-Markov model structure.

, 2016
Semi-Markov model structure.
Paul Sutcliffe (493515), Matthew Costa (3325197), Hema Mistry (3325194), Karoline Freeman (493517), Ngianga-Bakwin Kandala (590375), Ruth Pulikottil-Jacob (3325200), Martin Connock (159426), Amy Grove (493520), Aileen Clarke (470453)   +8 more
core   +1 more source

Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry   +4 more
wiley   +1 more source

Brown–Proschan Repair Policy for Repairable Systems Using the Discrete Weibull Failure Distribution and Markov Chains

Quality and Reliability Engineering International, EarlyView.
ABSTRACT A repairable system operates under a maintenance strategy involving scheduled preventive maintenance (PM) and corrective repair actions following failures. This study develops an exact analytical methodology using Markov chains with discrete states and time to calculate the expected number of failures E[N(t)]$\mathop {\mathbb {E}}[N(t)]$ under
Danilo G. O. Valadares, Roberto C. Quinino, Linda L. Ho, Frederico R. B. Cruz   +3 more
wiley   +1 more source

Semi-markov conditional random fields for information extraction

We describe semi-Markov conditional random fields (semi-CRFs), a con- ditionally trained version of semi-Markov chains. Intuitively, a semi- CRF on an input sequence x outputs a “segmentation” of x, in which labels are assigned to segments (i.e ...
Sarawagi, Sunita, W, William, Semi-markov, Cohen   +2 more
core   +1 more source