Results 71 to 80 of about 266,359 (347)

D-optimal Factorial Designs under Generalized Linear Models [PDF]

open access: yes, 2013
Generalized linear models (GLMs) have been used widely for modelling the mean response both for discrete and continuous random variables with an emphasis on categorical response.
Mandal, Abhyuday, Yang, Jie
core  

Creating Shared Value as an Antecedent of Value Co‐Creation: B2B Relationships in the Agri‐Food Sector

open access: yesAgribusiness, EarlyView.
ABSTRACT This study analyzes the effects of value co‐creation and creation of shared value in agricultural input marketing. This study used a sample of 178 agricultural companies in Costa Rica. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM) with SMART PLS software. Our findings reveal the significant influence
Luis Ricardo Solís‐Rivera   +1 more
wiley   +1 more source

Effect of Tillage Systems on Growth and Yield of Bread Wheat Triticum aestivum L. and Associated Weeds [PDF]

open access: yesMesopotamia Journal of Agriculture
A factorial field experiment was implemented during the agricultural season 2023-2024 in two MRA locations, Sahleg and Kahreez villages. The factorial experiment included two factors. The 1st.
Salim Hommade Antar   +4 more
doaj   +1 more source

Sparse experimental design : an effective an efficient way discovering better genetic algorithm structures [PDF]

open access: yes, 2001
The focus of this paper is the demonstration that sparse experimental design is a useful strategy for developing Genetic Algorithms. It is increasingly apparent from a number of reports and papers within a variety of different problem domains that the ...
Braiden, P. M.   +4 more
core  

Regional Differences in U.S. Consumer Preferences for Native Woody Shrubs With Varying Aesthetic Characteristics

open access: yesAgribusiness, EarlyView.
ABSTRACT Native plants offer a variety of aesthetic (e.g., fall colour, fruit, flowers) and functional benefits (e.g., pollinator friendly, wildlife friendly, water management). How these benefits influence consumer choice and perceived value of native versus introduced plants is not well understood.
Alicia Rihn   +3 more
wiley   +1 more source

KL-Divergence Guided Two-Beam Viterbi Algorithm on Factorial HMMs [PDF]

open access: yes, 2014
This thesis addresses the problem of the high computation complexity issue that arises when decoding hidden Markov models (HMMs) with a large number of states.
Yeh, Raymond
core   +1 more source

Advanced Experiment Design Strategies for Drug Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang   +3 more
wiley   +1 more source

QCD and models on multiplicities in $e^+e^-$ and $p\bar p$ interactions

open access: yes, 2004
A brief survey of theoretical approaches to description of multiplicity distributions in high energy processes is given. It is argued that the multicomponent nature of these processes leads to some peculiar characteristics observed experimentally ...
A. B. Kaidalov   +38 more
core   +1 more source

Confounding in Factorial Experiments

open access: yesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1974
Summary Various methods of construction of confounded designs and determination of the confounded effects of a confounded design are available in the literature. An alternative method based on the theory of groups is given in this paper.
openaire   +2 more sources

Disentangling Coincident Cell Events Using Deep Transfer Learning and Compressive Sensing

open access: yesAdvanced Intelligent Systems, EarlyView.
Overlapping cells during detection distort single‐cell measurements and reduce diagnostic accuracy. A hybrid framework combining a fully convolutional neural network with compressive sensing to disentangle overlapping signals directly from raw time‐series data is presented.
Moritz Leuthner   +2 more
wiley   +1 more source

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