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- Gutes, A., et al.
(författare)
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A flow injection voltammetric electronic tongue applied to paper mill industrial waters
- 2006
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Ingår i: Sensors and actuators. B, Chemical. - : Elsevier BV. - 0925-4005 .- 1873-3077. ; 115:1, s. 390-395
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Tidskriftsartikel (refereegranskat)abstract
- A voltammetric electronic tongue with automated operation based on the flow injection (FIA) technique was applied to the characterization of wastewaters coming from the paper mill industry. A metallic multielectrode array - formed by platinum, gold and rhodium electrodes - was employed as the detection system, while the measurements were based on large amplitude pulse voltammetry (LAPV). LAPV consisted in scans of pulses from to 0 to 1.8 V at 0.2 V steps. Five current values were recorded for each pulse, so a set of 300 current values (three electrodes × 20 pulses × five values) was recorded for each sample. Samples were first discriminated using Principal Component Analysis (PCA), while Artificial Neural Networks were used for the characterization and prediction of chemical oxygen demand, conductivity and pH. The system may be used for the quick identification and monitoring of the quality of used waters in these industrial facilities. © 2005 Elsevier B.V. All rights reserved.
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| 2. |
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| 3. |
- Hellstrom-Lindberg, E., et al.
(författare)
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A validated decision model for treating the anaemia of myelodysplastic syndromes with erythropoietin + granulocyte colony-stimulating factor : Significant effects on quality of life
- 2003
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Ingår i: British Journal of Haematology. - : Wiley. - 0007-1048 .- 1365-2141. ; 120, s. 1037-
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Tidskriftsartikel (refereegranskat)abstract
- We have published previously a prototype of a decision model for anaemic patients with myelodysplastic syndromes (MDS), in which transfusion need and serum erythropoietin (S-Epo) were used to define three groups with different probabilities of erythroid response to treatment with granulocyte colony-stimulating factor (G-CSF) + Epo. S-Epo = 500 U/l and a transfusion need of < 2 units/month predicted a high probability of response to treatment, S-Epo > 500 U/l and =2 units/month for a poor response, whereas the presence of only one negative prognostic marker predicted an intermediate response. A total of 53 patients from a prospective study were included in our evaluation sample. Patients with good or intermediate probability of response were treated with G-CSF + Epo. The overall response rate was 42% with 28.3% achieving a complete and 13.2% a partial response to treatment. The response rates were 61% and 14% in the good and intermediate predictive groups respectively. The model retained a significant predictive value in the evaluation sample (P < 0.001). Median duration of response was 23 months. Scores for global health and quality of life (QOL) were significantly lower in MDS patients than in a reference population, and fatigue and dyspnoea was significantly more prominent. Global QOL improved in patients responding to treatment (P = 0.01). The validated decision model defined a subgroup of patients with a response rate of 61% (95% confidence interval 48-74%) to treatment with G-CSF + Epo. The majority of these patients have shown complete and durable responses.
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| 4. |
- Jonsson, A., et al.
(författare)
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Electronic nose for microbial quality classification of grains
- 1997
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Ingår i: International Journal of Food Microbiology. - : Elsevier. - 0168-1605 .- 1879-3460. ; 35:2, s. 187-193
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Tidskriftsartikel (refereegranskat)abstract
- The odour of grains is in many countries the primary criterion of fitness for consumption. However, smelling of grain for quality grading should be avoided since inhalation of mould spores or toxins may be hazardous to the health and determinations of the off-odours are subjective. An electronic nose, i.e. a gas sensor array combined with a pattern recognition routine might serve as an alternative. We have used an electronic nose consisting of a sensor array with different types of sensors. The signal pattern from the sensors is collected by a computer and further processed by an artificial neural network (ANN) providing the pattern recognition system. Samples of oats, rye and barley with different odours and wheat with different levels of ergosterol, fungal and bacterial colony forming units (cfu) were heated in a chamber and the gas in the chamber was led over the sensory array. The ANN could predict the odour classes of good, mouldy, weakly and strongly musty oats with a high degree of accuracy. The ANN also indicated the percentage of mouldy barley or rye grains in mixtures with fresh grains. In wheat a high degree of correlation between ANN predictions and measured ergosterol as well as with fungal and bacterial cfu was observed. The electronic nose can be developed to provide a simple and fast method for quality classification of grain and is likely to find applications also in other areas of food mycology.
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| 6. |
- Wide, Peter, et al.
(författare)
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An air-quality sensor system with fuzzy classification
- 1997
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Ingår i: Measurement Science and Technology. - : Institute of Physics (IOP). - 0957-0233 .- 1361-6501. ; 8:2, s. 138-148
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Tidskriftsartikel (refereegranskat)abstract
- sensor system for the measurement of air quality is presented and evaluated. It is based on the approach of mimicking the advantages of human olfactory sensing, using gas sensor measurements and fuzzy sensor fusion. Signals from four sensitive metal - oxide - semiconductor field-effect transistors (MOSFET), each with a unique selectivity profile, are used. Each sensor exhibits information which is extracted by signal analysis and used to determine a crisp air-quality profile. The resulting crisp profile is unique, representing a distinct air quality and serves as a basis for the determining of a fuzzy quality profile. A fuzzy measurement profile is then matched pair-wise to the different fuzzy quality profiles. The matches are processed with help of a fuzzy fusion technique to determine the most representative crisp air-quality profile. Preliminary experiments show that the performance of the proposed fuzzy sensor clustering system is very promising. Environmental air-quality tests inside and outside a car driving in different cities during different seasons resulted in an artificial system determining air-quality opinions. The sensor opinions are classified with reference to three air-quality references (clean, medium and polluted air) and appear to be in accordance with human opinions obtained simultaneously.
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