Results 61 to 70 of about 4,354,487 (343)

Aspects Relating to the Perspective and Management Strategies of the Balanced Scorecard Method [PDF]

open access: yesOvidius University Annals: Economic Sciences Series, 2019
This article aims to highlight the way in which the Balanced Scorecard management system achieves the measured performances and the strategic objectives for each perspective, together with their graphical presentation showing the relationship between ...
Ioana Cristina Circa (Buzduga)
doaj  

Deformable Part Models are Convolutional Neural Networks

open access: yes, 2014
Deformable part models (DPMs) and convolutional neural networks (CNNs) are two widely used tools for visual recognition. They are typically viewed as distinct approaches: DPMs are graphical models (Markov random fields), while CNNs are "black-box" non ...
Darrell, Trevor   +3 more
core   +1 more source

The graphical brain: Belief propagation and active inference

open access: yesNetwork Neuroscience, 2017
This paper considers functional integration in the brain from a computational perspective. We ask what sort of neuronal message passing is mandated by active inference—and what implications this has for context-sensitive connectivity at microscopic and ...
Karl J. Friston   +2 more
semanticscholar   +1 more source

A critical review of recent trends, and a future perspective of optical spectroscopy as PAT in biopharmaceutical downstream processing

open access: yesAnalytical and Bioanalytical Chemistry, 2020
As competition in the biopharmaceutical market gets keener due to the market entry of biosimilars, process analytical technologies (PATs) play an important role for process automation and cost reduction.
Laura Rolinger   +2 more
semanticscholar   +1 more source

Structural insights into lacto‐N‐biose I recognition by a family 32 carbohydrate‐binding module from Bifidobacterium bifidum

open access: yesFEBS Letters, EarlyView.
Bifidobacterium bifidum establishes symbiosis with infants by metabolizing lacto‐N‐biose I (LNB) from human milk oligosaccharides (HMOs). The extracellular multidomain enzyme LnbB drives this process, releasing LNB via its catalytic glycoside hydrolase family 20 (GH20) lacto‐N‐biosidase domain.
Xinzhe Zhang   +5 more
wiley   +1 more source

A graphical method of presenting property rights, building types, and residential behaviors: A case study of Xiaoxihu historic area, Nanjing

open access: yesFrontiers of Architectural Research, 2022
One of the main reasons for the decline of urban historic areas in China is the co-existence of multiple property rights. It also deeply affects conservation and regeneration practice.
Yinan Dong   +2 more
doaj   +1 more source

Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI Channels Using Graphical Models

open access: yes, 2011
In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models.
Chockalingam, A.   +4 more
core   +1 more source

Cold chemistry: a few-body perspective on impurity physics of a single ion in an ultracold bath [PDF]

open access: yes, 2020
Impurity physics is a traditional topic in condensed matter physics that nowadays is being explored in the field of ultracold gases. Among the different classes of impurities, we focus on charged impurities in an ultracold bath.
J. P'erez-R'ios
semanticscholar   +1 more source

The Caenorhabditis elegans DPF‐3 and human DPP4 have tripeptidyl peptidase activity

open access: yesFEBS Letters, EarlyView.
The dipeptidyl peptidase IV (DPPIV) family comprises serine proteases classically defined by their ability to remove dipeptides from the N‐termini of substrates, a feature that gave the family its name. Here, we report the discovery of a previously unrecognized tripeptidyl peptidase activity in DPPIV family members from two different species.
Aditya Trivedi, Rajani Kanth Gudipati
wiley   +1 more source

Characterizing the Shape of Activation Space in Deep Neural Networks

open access: yes, 2019
The representations learned by deep neural networks are difficult to interpret in part due to their large parameter space and the complexities introduced by their multi-layer structure.
Gebhart, Thomas   +2 more
core   +1 more source

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