| 1. |
- Alander, E. M., et al.
(författare)
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Characterization of paracetamol agglomerates by image analysis and strength measurement
- 2003
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Ingår i: Powder Technology. - : Elsevier BV. - 0032-5910 .- 1873-328X. ; 130:1-3, s. 298-306
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Tidskriftsartikel (refereegranskat)abstract
- Paracetamol is crystallized in different solvents and techniques are developed and used to characterize the product. The product particles from three different solvent compositions: ethylene glycol, acetone and an acetone-water mixture (30-70 wt.%) have been examined. Product properties visually observed are quantified by image analysis and evaluation of measured image descriptors with Principal Component Analysis (PCA). The agglomerate strength has been determined by crushing single agglomerates. Depending on the solvent, the content of single crystals and agglomerates differ. Agglomerates differ by the number and size of crystals grown together, as well as by the strength.
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| 2. |
- Alander, E. M., et al.
(författare)
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Mechanisms of crystal agglomeration of paracetamol in acetone-water mixtures
- 2005
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Ingår i: Industrial & Engineering Chemistry Research. - : American Chemical Society (ACS). - 0888-5885 .- 1520-5045. ; 44:15, s. 5788-5794
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Tidskriftsartikel (refereegranskat)abstract
- The mechanisms governing the influence of the solvent composition on the agglomeration in a crystallization process have been investigated. Narrowly sieved paracetamol crystals were suspended in supersaturated acetone-water solutions, and were allowed to grow at isothermal conditions, after which the agglomeration was recorded. In all experiments the same sieve size fraction was used as well as the same magma density. In each experiment the supersaturation was kept constant. Experiments were performed in different solvent compositions at different supersaturation, crystal growth rate, solution viscosity, and agitation rate. For a statistically sufficient number of particles from each experiment, the number of crystals in each product particle was determined by image analysis and multivariate data evaluation. From the resulting number distributions of crystals per product particle, parameters defining the degree of agglomeration were extracted. The experimental results clearly establish that there is an influence of the solvent composition on the degree of agglomeration, which cannot be explained by differences in crystal growth rate, or differences in solution viscosity. The degree of agglomeration is found to decrease with increasing solvent polarity. It is, suggested that the mechanism by which the solvent influence relates to the crystal-solvent interaction and the physicochemical. adhesion forces between crystals in the solution.
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| 3. |
- Alander, Jarmo, et al.
(författare)
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Near infrared wavelength relevance detection of ultraviolet radiation-induced erythema
- 2008
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Ingår i: Journal of Near Infrared Spectroscopy. - : SAGE Publications. - 0967-0335 .- 1751-6552. ; 16:3, s. 233-241
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Tidskriftsartikel (refereegranskat)abstract
- The acute effects of sun-bathing on the near-infrared absorption spectra of human skin were studied by exposing the shoulders of a male test subject to bright Finnish high summer mid-day sun. The spectra were measured before, immediately after and for several days after exposure. Four different spectral. processing and classification methods were applied to the data set to identify differences caused by exposure to the sun. The spectrophotometer and measuring procedure were found to cause some systematic errors, calling for further development, even though they could, to a large extent, be compensated for computationally. Spectral regions indicating ultraviolet radiation-induced erythema were Located and the degree of erythema could be predicted correctly but the signal is weak. This paper discusses promising wavelength selection methods to study the dermal effects of exposure to the sun, as well as difficulties and remedies of near infrared spectroscopic measurements of the skin.
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| 4. |
- Koljonen, Janne, et al.
(författare)
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A review of genetic algorithms in near infrared spectroscopy and chemometrics : past and future
- 2008
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Ingår i: Journal of Near Infrared Spectroscopy. - : SAGE Publications. - 0967-0335 .- 1751-6552. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Global optimisation and search problems are abundant in science and engineering, including spectroscopy and its applications. Therefore, it is hardly surprising that general optimisation and search methods such as genetic algorithms (GAs) have also found applications in the area of near infrared INIRI spectroscopy. A brief introduction to genetic algorithms, their objectives and applications in NIR spectroscopy, as well as in chemometrics, is given. The most popular application for GAs in NIR spectroscopy is wavelength, or more generally speaking, variable selection. GAs are both frequently used and convenient in multi-criteria optimisation; for example, selection of pre-processing methods, wavelength inclusion, and selection of Latent variables can be optimised simultaneously. Wavelet transform has recently been applied to pre-processing of NIR data. In particular, hybrid methods of wavelets and genetic algorithms have in a number of research papers been applied to pre-processing, wavelength selection and regression with good success. In all calibrations and, in particular, when optimising, it is essential to validate the model and to avoid over-fitting. GAs have a Large potential when addressing these two major problems and we believe that many future applications will emerge. To conclude, optimisation gives good opportunities to simultaneously develop an accurate calibration model and to regulate model complexity and prediction ability within a considered validation framework.
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| 5. |
- Nordling, Torbjörn E. M., 1979-, et al.
(författare)
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Genetic Algorithms as a Tool for Wavelength Selection
- 2004
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Ingår i: Proceedings of the 11th Finnish Artificial Intelligence Conference (STeP 2004) in Vantaa (Finland), Volume 3. ; , s. 99-113
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Konferensbidrag (refereegranskat)abstract
- This work is a careful implementation of a genetic algorithm (GA) for pre-selection of wavelengths, combined with partial least squares regression (PLS) for modelling of near-infrared (NIR) data. We show that NIR spectro- metry can be used for concentration measurements when background noise has not been limited and no chemical properties of the substances are known. We use an alternative brute force approach working for any convergent GA. It works by generating many solutions, preferably by using different GA parameters, and then constructing the final solution by only including variables found in a majority of all solutions. The proposed method is based on three assumptions: existence of data, varying measurement noise and selection of data wavelengths that are more fruitful than noise.
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| 6. |
- Nordling, Torbjörn E. M., 1979-, et al.
(författare)
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Wavelength selection by genetic algorithms in near infrared spectra for melanoma diagnosis
- 2005
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Ingår i: IFMBE Proceedings, Volume 11, 3rd European Medical & Biological Engineering Conference (EMBEC’05) in Prague (Czech Republic).
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Konferensbidrag (refereegranskat)abstract
- Early, reliable and fast diagnosis of melanoma is particularly important as the number of cases is increasing. In this paper, the potential of using near infrared spectroscopy for melanoma diagnosis is studied. The classification task is complicated by a low signal-to-noise ratio and the high dimensionality of the spectral data. Thus pre-selection of wavelength variables is required. Atypical naevi samples of patients were clinically classified, using the ABCD rule, and their near infrared spectra recorded. A nonlinear clustering model for spectral based classification was calibrated to the spectra and pathologist?s classification using a genetic algorithm. The genetic algorithm optimized the spectral based classification by selecting wavelengths correlated to melanoma. Some wavelength selections allowed correct classification of all samples in our dataset. The small size of the dataset and uncertainty in the clinical classification, however, limit the conclusions that can be drawn. Evidence for the existence of spectral regions that contain information needed for melanoma diagnosis is presented.
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