Advanced treatment by chemical oxidation of pulp and paper effluent from a plant manufacturing hardboard from waste paper.

This study attempts to evaluate the applicability of chemical oxidation processes to polish biologically treated effluent of a plant manufacturing hardboard from waste paper to comply with the discharge limit of 120 mg l(-1) chemical oxygen demand (COD). In the first step, a chemically assisted settling was applied. The optimum results were obtained with alum plus lime with the alum dose of 200 mg l(-1). In the second step, chemically assisted settling effluent was fed into an activated sludge system and over 80% COD removal was achieved. In the last step of the experimental study, a series of ozone oxidation and Fenton oxidation methods were tested to remove residual COD. Ozone oxidation provided 80% COD removal. An ozone dose of 40 mg min(-1) with a reaction time of two hours was found to be optimum. Catalytic ozonation by using ferric iron, as well as high pH ozonation, Fenton process and H2O2/O3 oxidation did not prove to be more efficient than plain ozonation under these study conditions.

The effect of the textile industry dye bath additive EDTMPA on colour removal characteristics by ozone oxidation.

In this study, the effects of the phosphonic acid based sequestering agent EDTMPA used in the textile dye baths on colour and organic matter removal by ozone oxidation was experimentally investigated. Procion Navy HEXL dyestuff that has been commonly used for the reactive dyeing of cellulose fibers was selected as the model component. The organic matter oxidation by ozone was determined to obey the pseudo-first order kinetics as they are treated singly or in combination. COD removal rates obtained from pseudo-first order reaction kinetics showed that oxidation of Navy HEXL alone (0.0947 L/min) was faster than that of EDTMPA (0.0171 L/min) and EDTMPA with dye (0.0155 L/min) at pH 3.0. It was also found that reaction rates of single EDTMPA removal and EDTMPA and dye mixture removal increased as the reaction pH was increased from 3.0 to 10.5.

Nitrogen removal from tannery wastewater by protein recovery.

Nitrogen removal from wastewaters has gained importance in recent years. In this paper protein precipitation and recovery potential of leather tanning industry wastewaters were experimentally evaluated. A protein profile for all sources was prepared. Liming was determined to be the most important protein source. Composite samples were made up to assess the protein precipitation applications. Isoelectric pH precipitation yielded around 50% protein removal between the optimum pH interval of 2.1-3.8. FeCl3 proved to be a very effective means of protein removal providing over 60% efficiency. Polyelectrolyte precipitation did not yield satisfactory results. Magnesium ammonium phosphate precipitation followed by acid precipitation of protein provided 85% ammonia removal in addition to 50% protein removal.

Assessment of magnesium ammonium phosphate precipitation for the treatment of leather tanning industry wastewaters.

Magnesium ammonium phosphate (MAP) precipitation has a potential for ammonium removal from industrial wastewaters. Application basis of this recent method of treatment has not been fully determined. In this study application of MAP precipitation to leather tanning wastewaters has been experimentally evaluated. Five alternative places of MAP precipitation in leather tanning wastewater treatment scheme tested were; instead of plain settling, after plain settling, after polyelectrolyte added plain settling, within the chemical precipitation and after biological treatment. Among these alternatives MAP application instead of plain settling and within the chemical precipitation were found to be most favourable and efficient by reducing the nitrogen load to the level of nutrient requirement in the biological stage. pH 9.0-9.5 and stoichiometric magnesium and phosphate doses were determined to be optimum conditions for MAP precipitation.

Assessment of source-based nitrogen removal alternatives in leather tanning industry wastewater.

Nitrogen is an important parameter of leather tanning wastewaters. Magnesium ammonium phosphate (MAP) precipitation is a chemical treatment alternative for ammonia removal. In this study, a detailed source-based wastewater characterisation of a bovine leather tannery was made and nitrogen speciation as well as other basic pollutant parameter values was evaluated. This evaluation has led to definition of alternatives for source-based MAP treatment. MAP precipitation experiments conducted on these alternatives have yielded over 90% ammonia removal at pH 9.5 and using stoichiometric doses. Among the alternatives tested liming-deliming and bating-washing was found to be the most advantageous providing 71% ammonia removal.

Factors affecting colour removal from reactive dye bath by ozonation.

A reactive dye bath sample containing a mixture of dyes was ozonated and colour removal was obtained in a relatively short time of 30 min at 605 mgl-1 of ozone utilisation. The factors affecting ozonation were assessed by comparing the results of dye bath and synthetic samples. Results from dye bath and synthetic dye solution ozonation were found to be significantly different. NaCl and Na2CO3 were determined to have a slight effect only on the initial rate of ozonation. However, the effect of the chelating agent in terms of both time and ozone dose was significant and explained the differences between the results of the dye bath and dye solution ozonation.

ECG beat classification by a novel hybrid neural network.

This paper presents a novel hybrid neural network structure for the classification of the electrocardiogram (ECG) beats. Two feature extraction methods: Fourier and wavelet analyses for ECG beat classification are comparatively investigated in eight-dimensional feature space. ECG features are determined by dynamic programming according to the divergence value. Classification performance, training time and the number of nodes of the multi-layer perceptron (MLP), restricted Coulomb energy (RCE) and a novel hybrid neural network are comparatively presented. In order to increase the classification performance and to decrease the number of nodes, the novel hybrid structure is trained by the genetic algorithms (GAs). Ten types of ECG beats obtained from the MIT-BIH database and from a real-time ECG measurement system are classified with a success of 96% by using the hybrid structure.

Detection of ECG waveforms by neural networks.

In this study, ECG waveform detection was performed by using artificial neural networks (ANNs). Initially, the R peak of the QRS complex is detected, and then feature vectors are formed by using the amplitudes of the significant frequency components of the DFT spectrum. Grow and Learn (GAL) and Kohonen networks are comparatively investigated to detect four different ECG waveforms. The comparative performance results of GAL and Kohonen networks are reported.