Over 10 mio. titler Fri fragt ved køb over 499,- Hurtig levering Forlænget returret til 31/01/25

Food and Feed Safety Systems and Analysis

Forfatter: info mangler
Bog
  • Format
  • Bog, paperback
  • Engelsk

Beskrivelse

Food and Feed Safety Systems and Analysis discusses the integration of food safety with recent research developments in food borne pathogens. The book covers food systems, food borne ecology, how to conduct research on food safety and food borne pathogens, and developing educational materials to train incoming professionals in the field. Topics include data analysis and cyber security for food safety systems, control of food borne pathogens and supply chain logistics. The book uniquely covers current food safety perspectives on integrating food systems concepts into pet food manufacturing, as well as data analyses aspects of food systems.

Læs hele beskrivelsen
Detaljer
  • SprogEngelsk
  • Sidetal424
  • Udgivelsesdato16-10-2017
  • ISBN139780128118351
  • Forlag Academic Press Inc
  • FormatPaperback
Størrelse og vægt
  • Vægt860 g
  • coffee cup img
    10 cm
    book img
    19,1 cm
    23,5 cm

    Findes i disse kategorier...

    Se andre, der handler om...

    Data mining Information theory Explanation Cognitive neuroscience Machine learning Resonance Positron-Emission Tomography Principal components analysis Logistic distribution Statistical mechanics Survival Analysis Kolmogorov complexity Magnetic resonance imaging Alpha rhythm Cognitive science Natural selection Attention Hippocampus Power series Neuroscience Case-control method Bias Causality Big data gestalt Alzheimer's disease Cognitive Aging Axon Observational Data Synapse Restricted Boltzmann Machine Naive bayes Longitudinal data Mixed logit Chi Square Maximum entropy Delayed recall Proportional hazards Dendrite Polynomial Random effects Linear Decision maker Prediction Logistic regression Information gain Panel data Interactive learning Minimum Description Length Rule» Hypothesis testing Wald test Propensity score Normalization Discrete choice Multilayer perceptron Quadratic Maximum Likelihood Hierarchical Bayes Genetic algorithm Back-propagation Neuron 'predictive analytics' Imputation Mutual Information Shannon Entropy Causal reasoning Unsupervised learning Supervised learning Fixed effects Taylor series Quasi-Experiment Ensemble learning Cross-Sectional Data Decision bias Binary variables Calculus Ratiocinator Analytic science Binary spikes Binding by synchrony Boltzmann entropy Bayes' Bayesian networks Cell body Beta Waves Boltzmann Machine Causal analytics Cluster-specific effects Bayesian probabilities Conditional logistic regression Dummy coded missing status variables Entorhinal Cortex Errors-in-variables regression Crystallized Intelligence cubic EEG left temporal slowing Electroencephalography (EEG)Gamma waves Fluid intelligence Dummy code Explicit RELR correlated observations Graded potentials Hebbian learning High-dimensional learning High Dimension Data Generalized estimating equations (GEE)Implicit RELR Delta waves Hopfield Network Integrate-and-fire Implicit learning and memory Kullback-Leibler divergence (KL learning)Likelihood ratio test Law of Pragnanz Intercept Correction Magnetoencephalography (MEG)Theta waves Extreme value error Even polynomial features Local Field Potentials Explicit learning and memory Extreme value type 1 distribution K-means cluster analysis Medial Temporal Lobe Frequentist probabilities Neural loss Logit error Odd polynomial features Offset regression Neuromorphic Hierarchical integration model of perception Nonlinear effect Neural impulse Hidden Units Quartic Immediate recall Ratio variables Implicit RELR Prior weight RELR sequential online learning Gumbel Distribution Randomized controlled experiment Reduced error logistic regression (RELR)Stable information theory Interval variables Simple model of neural dynamics Small sample size learning RELR's outcome score matching Student's t Spearman Correlation Simpson's Paradox Theory of neuronal group selection Self-organized map Interaction effect Transitional Model Jaynes principle Standardized Regression Coefficients Most likely inference Low Birth Weight Multicollinearity Update weight Synaptic sprouting Matched sample Matching experiment Welch's t Outcome score matching Posterior weight Neural Darwinism Probit regression Pseudo-observations Ranked variables RELR's causal machine learning Pearson correlation seasonal effects Negative error Ordinal Variables Tops�e distance Positive error Predementia Alzheimer's disease RELR error model assumptions Standardized variables Synaptic pruning Wechsler Logical Memory test
    Machine Name: SAXO080