Co-digestion of manure and biowaste according to the EC animal by-products regulation and Finnish national regulations.

The objective of this study was to compare methane production and characteristics of digested material in anaerobic digestion concepts according to the Animal By-Products Regulation (ABP-Regulation) of the EC (hygienisation of biowaste for 1 hour at 70 degrees C, particle size < 12 mm) and Finnish national regulations (treatment temperature 55 degrees C, feeding interval 24 h, hydraulic retention time (HRT) 20 d, particle size < 40 mm) and with small variations in treatment methods for treating manure and biowaste. Moreover, the survival of three different salmonella bacteria in these processes was studied. Hygienisation of biowaste prior to digestion at 35 degrees C enhanced methane production by 14-18% compared to similar treatment without hygienisation. The differences in treatment temperature, HRT and hygienisation of biowaste prior to digestion did not significantly affect the characteristics of digested material. The concepts according to the ABP-Regulation and Finnish national regulations were effective in destroying salmonella bacteria to an undetectable level.     

Ring‐opening polymerization of lactones initiated by diphenylzinc–coinitiator systems

Diphenylzinc, alone or in combination with water and butanone as coinitiators, was used as a polymerization initiator system for a variety of lactones at varying temperatures. The resulting data indicate that the course of the polymerization is greatly influenced by the lactone structure, as well as by the molar ratio of coinitiator to diphenylzinc. When used alone, diphenylzinc exhibited high activity as an initiator in δ‐valerolactone polymerizations, although it was less efficient when used in the β‐butyrolactone and the β‐propiolactone polymerizations. Activity in the polymerization of β‐lactones was increased by adding small amounts of butanone or water. It was also observed that the diphenylzinc–butanone combination was more effective than the diphenylzinc–water mixture in the polymerizations of β‐butyrolactone and β‐propiolactone. Copyright © 2003 Society of Chemical Industry     

Nonlinearity analysis and optimization of HBTs for optical mixer designs

Two types of photo heterojunction bipolar transistor (HBT) to directly down-convert optical signals to electronic signals have been reported in the literature: a conventional photo-HBT in which light penetrates through the area of the base-collector junction and an HBT where light shines through the base-collector edge for higher conversion efficiency. Although the performance in relation to bias conditions has been published, the detailed analyses for identifying the parameters and bias conditions that provide optimum direct down-conversion have not been examined. This paper provides a full explanation of the operation of the down-conversion for both HBT configurations based on low-frequency analyses. Such information is useful for both understanding the nonlinear mechanisms involved and designing for maximum efficiency. In addition, a new circuit has been developed from the basic HBT down-conversion circuit that provides improved performance.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.     

Mass Transfer in a Flat Gas/Liquid Interface using non‐Newtonian Media

Gas/liquid mass transfer has been investigated using a stirred vessel gas/liquid contactor using non‐Newtonian media and carbon dioxide as absorbent and gas phase, respectively. The volumetric mass transfer coefficients at different operational variables have been determined. Non‐Newtonian media (liquid phase) were prepared as aqueous solutions of sodium carboxymethyl cellulose salt. The influence of the rheological properties, polymer concentration, stirring rate, and gas flow rate on mass transfer was studied for these liquid phases. Kinematic viscosity and density experimental data were used to calculate the average molecular weight corresponding to the polymer employed. The Ostwald model has been used to fit the rheological behavior of aqueous solutions of the polymer employed as absorbent phase. Reasonably good agreement was found between the predictions of the proposed models and the experimental data of mass transfer coefficients.     

An introduction of the condition class space with continuous value discretization and rough set theory

The granularity of an information system has an incumbent effect on the efficacy of the analysis from many machine learning algorithms. An information system contains a universe of objects characterized and categorized by condition and decision attributes. To manage the concomitant granularity, a level of continuous value discretization (CVD) is often undertaken. In the case of the rough set theory (RST) methodology for object classification, the granularity contributes to the grouping of objects into condition classes with the same condition attribute values. This article exposits the effect of a level of CVD on the subsequent condition classes constructed, with the introduction of the condition class space—the domain within which the condition classes exist. This domain elucidates the association of the condition classes to the related decision outcomes—reflecting the inexactness incumbent when a level of CVD is undertaken. A series of measures is defined that quantify this association. Throughout this study and without loss of generality, the findings are made through the RST methodology. This further offers a novel exposition of the relationship between all the condition attributes and the RST‐related reducts (subsets of condition attributes). © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 173–191, 2006.     

Fault detection for control of wastewater treatment plants.

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.     

Comparison of total and faecal coliforms as faecal indicator in eutrophicated surface water.

The aim of this study was to evaluate the use of total coliforms (TC) and faecal coliforms (FC) using a membrane filtration method for precise monitoring of faecal pollution in Korean surface water. The samples were collected in Korea from both main rivers and their tributaries. Presumptive TC * FC were enumerated. The ratios of presumptive FC to TC were not constant, but varied widely, and TC were difficult to enumerate because of overgrowth by background colonies. For FC this was not the case. Seven hundred and three purified strains of presumptive TC * FC and their background colonies were biotyped using API 20E. Among 272 presumptive TC, non-faecal related species, Aeromonas hydrophila dominated (34.6%) and E. coli accounted for only 5.1%. In contrast, E. coli made up 89% of the 209 presumptive FC. Furthermore, of 164 background colonies on Endo Agar LES, 54.9% was A. hydrophila, while background colonies on m-FC Agar were few (58 strains), and despite their atypical colony appearance, most of them were biotyped as enteric bacteria. These results reveal that the detection of FC rather than TC using m-FC Agar is more appropriate for faecal pollution monitoring in eutrophicated surface water located in a temperate region.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.