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Your search keyword '"Eriksson, Lennart"' showing total 550 results
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550 results on '"Eriksson, Lennart"'

3. Falling Angel – A Wrist Worn Fall Detection System Using K-NN Algorithm

Author

Rahman, Hamidur, Sandberg, Johan, Eriksson, Lennart, Heidari, Mohammad, Arwald, Jan, Eriksson, Peter, Begum, Shahina, Lindén, Maria, Ahmed, Mobyen Uddin, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Coulson, Geoffrey, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert Y., Series editor, Ahmed, Mobyen Uddin, editor, Begum, Shahina, editor, and Raad, Wasim, editor

Published
2016
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7. Characterizing a Bioprocess with Advanced Data Analytics: Modeling at various stages of the data analytics continuum aids scale comparison of a bioreactor

Author

Eriksson, Lennart and McCready, Chris

Subjects
Data mining -- Usage, Biological products industry -- Technology application, Data warehousing/data mining, Technology application, Biotechnology industry, Business, Pharmaceuticals and cosmetics industries
Abstract

Advanced data analytics tools are used by industry to find the golden nuggets in historical data, to aid in process development, to fine-tune production, and to achieve long-term improvements in [...]

Published
2018

18. An Introduction to Some Basic Chemometric Tools

Author

Eriksson, Lennart, Johansson, Erik, Trygg, Johan, Eriksson, Lennart, Johansson, Erik, and Trygg, Johan

Abstract

Design of experiments (DOE) and multivariate data analysis (MVDA) are two strong links in a chain of chemometrics and data analytics. DOE and MVDA can be applied well in aquatic toxicology and can be used independently of one another, but when used in conjunction they equip the researcher with high quality data and model results with a faithful interpretation. Two example aquatic toxicity datasets are used to describe the benefits of DOE and MVDA in aquatic toxicology. The popular data analytical tools principal components analysis (PCA) and partial least squares (PLS) are outlined in detail and exemplified. A modification of PLS called orthogonal partial least squares (OPLS) is introduced and it is shown how it can simplify model interpretation. When using chemometrics to establish quantitative structure-activity relationships (QSAR), a central questions is that of whether to derive a single-response QSAR model involving a single Y-variable, or a multi-response QSAR covering multiple responses. It is demonstrated how an initial PCA model on a matrix of response data can be used to figure out when a multi-response QSAR model might be a viable alternative to several single-response QSAR models.

Published
2021
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20. Block‐wise Exploration of Molecular Descriptors with Multi‐block Orthogonal Component Analysis (MOCA).

Author

Schmidt, Sebastian, Schindler, Michael, and Eriksson, Lennart

Subjects
FEATURE selection, STRUCTURE-activity relationships, DATA structures, PLANT protection, MACHINE learning, DESCRIPTOR systems
Abstract

Data tables for machine learning and structure‐activity relationship modelling (QSAR) are often naturally organized in blocks of data, where multiple molecular representations or sets of descriptors form the blocks. Multi‐block Orthogonal Component Analysis (MOCA), a new analytical tool, can be used to explore such data structures in a single model, identifying principal components that are unique to a single block or joint over multiple blocks. We applied MOCA to two sets of 550 and 300 molecules and up to 9213 molecular descriptors organized in 11 blocks. The MOCA models reveal relationships between the blocks and overarching trends across the whole dataset. Based on the MOCA joint components, we propose a quantitative metric for the redundancy of blocks, useful for a priori block‐wise feature selection or evaluation of new molecular representations. The second data set includes 7 ecotoxicological study endpoints for crop protection chemicals, for which we (re‐)discovered some general trends and linked them to molecular properties. Using a single MOCA model we estimated the predictive potential of each block and the model‐ability of the target block. [ABSTRACT FROM AUTHOR]

Published
2022
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34. QSAR Model Validation

Author

Johansson, Erik, Eriksson, Lennart, Sandberg, Maria, Wold, Svante, Gundertofte, Klaus, editor, and Jørgensen, Flemming Steen, editor

Published
2000
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50. Multivariate characterization and modeling of polychlorinated dibenzo-p-dioxins and dibenzofurans

Author

Tysklind, Mats, Lundgren, Kjell, Rappe, Christoffer, Eriksson, Lennart, Jonsson, Jorgen, Sjostrom, Michael, and Ahlborg, Ulf G.

Subjects
Dibenzofurans -- Research, Dioxin -- Research, Environmental issues, Science and technology
Abstract

A multivariate physicochemical characterization of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) was conducted. Some 136 PCDDs and PCDFs congeners with four to eight chlorine atoms were analyzed, and multivariate quantitative structure-activity relationships were developed. Size-related chemical variables and substitution patterns were identified.

Published
1992

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