Search Results - "Esbensen, Kim"

Principles of Proper Validation: use and abuse of re-sampling for validation by Esbensen, Kim H., Geladi, Paul

“…Validation in chemometrics is presented using the exemplar context of multivariate calibration/prediction. A phenomenological analysis of common validation…”
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Monitoring of anaerobic digestion processes: A review perspective by Madsen, Michael, Holm-Nielsen, Jens Bo, Esbensen, Kim H.

“…The versatility of anaerobic digestion (AD) as an effective technology for solving central challenges met in applied biotechnological industry and society has…”
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Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 2: Particular requirements for near infrared spectroscopy by Esbensen, Kim H, Abu-Khalaf, Nawaf

“…Non-representative sampling of materials, lots and processes intended for NIR analysis is often fraught with hidden contributions to the full Measurement…”
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Before reliable near infrared spectroscopic analysis - the critical sampling proviso. Part 1: Generalised theory of sampling by Esbensen, Kim H, Abu-Khalaf, Nawaf

“…Non-representative sampling of materials, lots and processes intended for near infrared (NIR) analysis is often contributing hidden additions to the full…”
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Revisiting Pierre Gy's formula (TOS) – A return to size-density classes for applications to contaminated soils, coated particular aggregates and mixed material systems by Dubé, Jean-Sébastien, Esbensen, Kim H.

“…For some real-world material systems, estimations of the incompressible sampling variance based on Gy's classical s2(FSE) formula from the Theory of Sampling…”
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Transition to circular economy requires reliable statistical quantification and control of uncertainty and variability in waste by Esbensen, Kim H, Velis, Costas

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Sampling of particulate materials with significant spatial heterogeneity - Theoretical modification of grouping and segregation factors involved with correct sampling errors: Fundamental Sampling Error and Grouping and Segregation Error by Minkkinen, Pentti O., Esbensen, Kim H.

“…There has been an extensive abuse of Gy's Formula during the entire history of applied TOS (Theory of Sampling), it being applied too liberally to almost any…”
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Materials properties: heterogeneity and appropriate sampling modes by Esbensen, Kim H

“…The target audience for this Special Section comprises parties related to the food and feed sectors, e.g., field samplers, academic and industrial scientists,…”
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Theory of sampling: four critical success factors before analysis by Wagner, Claas, Esbensen, Kim H

“…Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data,…”
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Evaluation of sampling systems in iron ore concentrating and pelletizing processes – Quantification of Total Sampling Error (TSE) vs. process variation by Engström, Karin, Esbensen, Kim H.

“…•Regular control of sampling variability through variographic characterization.•Variographic analysis of process data enable evaluation of sampling…”
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Adequacy and verifiability of pharmaceutical mixtures and dose units by variographic analysis (Theory of Sampling) – A call for a regulatory paradigm shift by Esbensen, Kim H., Román-Ospino, Andrés D., Sanchez, Adriluz, Romañach, Rodolfo J.

“…[Display omitted] In spite of intense efforts in the last 20 years, the current state of affairs regarding evaluation of adequacy of pharmaceutical mixing is…”
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Representative sampling for food and feed materials: a critical need for food/feed safety by Esbensen, Kim H, Paoletti, Claudia, Thiex, Nancy

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Representative sampling of large kernel lots I. Theory of Sampling and variographic analysis by Esbensen, Kim H., Paoletti, Claudia, Minkkinen, Pentti

“…► Kernel lot, trace constituents sampling errors outweighs analytical errors by factors 10–100. ► Contemporary kernel lots uniformity assumptions are…”
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FTIR Spectroscopy for Grape and Wine Analysis by Bauer, Rolene, Nieuwoudt, Hilhne, Bauer, Florian F, Kossmann, Jens, Koch, Klaus R, Esbensen, Kim H

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Variographic analysis: A new methodology for quality assurance of pharmaceutical blending processes by Sánchez-Paternina, Adriluz, Sierra-Vega, Nobel O., Cárdenas, Vanessa, Méndez, Rafael, Esbensen, Kim H., Romañach, Rodolfo J.

“…•Developed a NIR calibration model to predict low heterogeneity blends in 1-D sampling system.•Variographic characterization offers a possibility to not only…”
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Distributional assumptions in food and feed commodities- development of fit-for-purpose sampling protocols by Paoletti, Claudia, Esbensen, Kim H

“…Material heterogeneity influences the effectiveness of sampling procedures. Most sampling guidelines used for assessment of food and/or feed commodities are…”
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Representative sampling of large kernel lots II. Application to soybean sampling for GMO control by Minkkinen, Pentti, Esbensen, Kim H., Paoletti, Claudia

“…► KeLDA data are here re-interpreted w.r.t. the Theory of Sampling (TOS). ► KeLDA data subjected to proper variographic analysis and interpretation. ► Total…”
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Variographic Assessment of Total Process Measurement System Performance for a Complete Ore-to-Shipping Value Chain by Karin Engström, Kim H. Esbensen

“…Variographic characterisation has been shown to be a powerful tool to assess the performance of process measurement systems, using existing process data…”
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Representative sampling for reliable data analysis: Theory of Sampling by Petersen, Lars, Minkkinen, Pentti, Esbensen, Kim H.

“…The Theory of Sampling (TOS) provides a description of all errors involved in sampling of heterogeneous materials as well as all necessary tools for their…”
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Representative sampling of large kernel lots III. General considerations on sampling heterogeneous foods by Esbensen, Kim H., Paoletti, Claudia, Minkkinen, Pentti

“…► Definition of salient characteristics of “fit-for-purpose” sampling plans. ► Minimum no. of increments to counteract maximum heterogeneity kernel lots is 42…”
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