Akademische Ressourcen durchsuchen

Fachgebiete / Stichwörter: HEYMAN, DANIEL P; MCGRAW-HILL; 003 H618s

Abstract In this paper, two models are presented for Multiprocessor Stochastic Systems (MSS). The first one is the Generalized Semi-Markov Process (GSMP), the second is the Generalized Stochastic Petri Net (GSPN). These ...

Barndorff‑Nielsen and Shephard (2001) proposed a class of stochastic volatility models in which the volatility process is the Ornstein‑Uhlenbeck process driven by a Levy process without gaussian component. Parameter ...

This book is aimed at covering the bases on random variables, random vectors and stochastic processes, necessary to be able to address the study of stochastic models based mainly on random and stochastic differential equ...

Abstract Here, we review mathematical models of epigenetic memory, focusing on chromatin modifications as key mechanisms to achieve long-term maintenance of epigenetic states. After reviewing the main stochastic modeling...

Diffusivity in supercooled liquids was observed to exhibit a non-Arrhenius behavior near the glass-transition temperature. This process, which occurs where the activation energy depends on the temperature, suggests the p...

We study the irreversible growth of magnetic thin films under the influence of spatially periodic fields by means of extensive Monte Carlo simulations. We find first-order pseudo-phase transitions that separate a dynamic...

Abstract This study applies a stochastic framework to quantify Potentially Toxic Elements (PTEs) and related risks in soils of the Maluwe–Tinga–Wasipe corridor in the Savannah Region of Ghana. A total of 729 B-horizo...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

Foundation models (FMs) represent a significant evolution in artificial intelligence (AI), impacting diverse fields. Within radiology, this evolution offers greater adaptability, multimodal integration, and improved gene...

The stochastic fundamental diagram (SFD), which describes the stochasticity of the macroscopic relations of traffic flow, plays a crucial role in understanding the uncertainty of traffic flow evolution and developing rob...

Several studies have reported about sustainability issues of the National Health Insurance Fund (NHIF) due to a mismatch between assets and liabilities. Despite these studies, no study has worked on the asset and liabili...

Reconstructing the early spatiotemporal dynamics of emerging infectious diseases (EIDs) is essential for effective public health response but remains difficult due to reporting delays, heterogeneous surveillance systems,...

Accurately modelling radiation interactions within canopy layers and soil backgrounds is crucial for biophysical variables retrieval across regional or global scales. However, terrain relief introduces significant uncert...

Abstract Differentially private stochastic gradient descent is a standard algorithm for training deep models on sensitive data, but under tight privacy budgets it must add large noise to every step, which slows convergen...

An essential aspect of the current theory of adaptive speciation is the maintenance of phenotypic variation and the evolution of stationary stable phenotypic diversity, a phenomenon known as evolutionary branching. Theor...

Mutualistic networks are highly dynamic, characterized by high temporal turnover of species and interactions. Yet, we have a limited understanding of how the internal structure of these networks and the roles species pla...

Parameter calibration of the traffic assignment models is vital to travel demand analysis and management. As an extension of the conventional traffic assignment, boundedly rational activity-travel assignment (BR-ATA) com...

This study was conducted to potentially optimize the sustainable culture of Mozambique tilapia (Oreochromis mossambicus) in a periphyton-based aquaculture system with supplemental feeding to aqua dams using stochastic si...

Mathematical models play an important role in epidemiology. The inclusion of a spatial component in epidemiological models is especially important to understand and address many relevant ecological and public health ques...

The paper presents the analysis of the spatial and spatio‑temporal tendencies and dependence in matters related to the situation in the labour market of the Kujawsko‑Pomorskie Voivodeship across municipalities in the...

Forecasting vaccine demand and determining inventory policies are critical challenges in healthcare supply chains, where uncertainty poses significant operational risks. This study proposes a two-step data-driven framewo...

Abstract Heterogeneous graphs are widely employed in applications such as social networks, recommendation systems, and bioinformatics. However, node attributes in real-world heterogeneous graphs are often missing or corr...