Results 61 to 70 of about 8,464,096 (315)

Modeling and Non-Linear Self-Tuning Robust Trajectory Control of an Autonomous Underwater Vehicle [PDF]

open access: yesModeling, Identification and Control, 1988
A non-linear self-tuning algorithm is demonstrated for an autonomous underwater vehicle. Tighter control is achieved by a non-linear parameter identification algorithm which reduces the parameter uncertainty bounds.
Thor Inge Fossen, Jens G. Balchen
doaj   +1 more source

Fine Tuning in General Gauge Mediation [PDF]

open access: yes, 2009
We study the fine-tuning problem in the context of general gauge mediation. Numerical analyses toward for relaxing fine-tuning are presented. We analyse the problem in typical three cases of the messenger scale, that is, GUT ($2\times10^{16}$ GeV ...
A Birkedal   +74 more
core   +2 more sources

Time after time – circadian clocks through the lens of oscillator theory

open access: yesFEBS Letters, EarlyView.
Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo   +2 more
wiley   +1 more source

A SARIMA APPROACH WITH PARAMETER OPTIMIZATION FOR ENHANCING FORECAST ACCURACY FOR NATIVE CHICKEN EGG PRODUCTION

open access: yesBarekeng
This study aims to accurately forecast monthly native chicken egg production using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model with parameter optimization.
Rendra Gustriansyah   +3 more
doaj   +1 more source

Confronting brane inflation with Planck and pre-Planck data

open access: yes, 2013
In this paper, we compare brane inflation models with the Planck data and the pre-Planck data (which combines WMAP, ACT, SPT, BAO and H0 data). The Planck data prefer a spectral index less than unity at more than 5\sigma confidence level, and a running ...
Huang, Qing-Guo, Ma, Yin-Zhe, Zhang, Xin
core   +1 more source

Structural instability impairs function of the UDP‐xylose synthase 1 Ile181Asn variant associated with short‐stature genetic syndrome in humans

open access: yesFEBS Letters, EarlyView.
The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li   +2 more
wiley   +1 more source

A Parameter Self-Tuning Rule Based on Spatial–Temporal Scale for Active Disturbance Rejection Control and Its Application in Flight Test Chamber Systems

open access: yesAerospace
Active disturbance rejection control (ADRC) emerges as a promising control approach due to its partial model-based characteristics and strong disturbance rejection capabilities.
Zhuang Xu   +5 more
doaj   +1 more source

The (Glg)ABCs of cyanobacteria: modelling of glycogen synthesis and functional divergence of glycogen synthases in Synechocystis sp. PCC 6803

open access: yesFEBS Letters, EarlyView.
We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee   +3 more
wiley   +1 more source

Explore the Principles of Prompt Tuning and the Progress of Research [PDF]

open access: yesITM Web of Conferences
Prompt Tuning is a lightweight fine-tuning method that demonstrates efficient task adaptation and parameter efficiency for pre-trained language models (PLMs). Prompt Tuning highlights an important contribution to the advancement of NLP technology.
Zheng Tongxin
doaj   +1 more source

Hyper-parameter Tuning for Quantum Support Vector Machine

open access: yesAdvances in Electrical and Computer Engineering, 2022
In recent years, the positive effect of quantum techniques on machine learning methods have been studied. Especially in training big data, quantum computing is beneficial in terms of speed.
DEMIRTAS, F., TANYILDIZI, E.
doaj   +1 more source

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