Bacterial strains in an activated sludge aerobic reactor from a coke wastewater were found to be able to utilize thiocyanate as carbon source when the thiocyanate-containing wastewater was deprived of carbon source. This study showed that three thiocyanate-oxidizing bacterial strains, Burkholderia sp., Chryseobacterium sp., and Ralstonia sp. were isolated from the activated sludge of a coke wastewater treatment plant as evidenced by the fact that complete decomposition of thiocyanate was achieved either by coculture or individual pure culture. The thiocyanate biodegradation by the coculture occurred with an optimal pH range between 6.5 and 8.5 and an optimal temperature range between 30°C and 40°C. The biodegradation kinetics of thiocyanate was well fitted with the Andrew-Haldane model, which demonstrated a distinct substrate concentration-inhibited bacterial growth pattern. The effects of different types of additional carbon, nitrogen or sulfur sources on thiocyanate biodegradation were also investigated. Analysis of the end-products indicated that thiocyanate degradation by these strains should proceed via two pathways.

Quality control of the coking wastewater treatment requires real time monitoring and regulation of the concentrations of thiocyanate,since it is one of the major constituents of wastewater effluents.A method for multi -site and multi-frequency sampling and analysis was proposed for this purpose.Experimental results showed that the spectrophotometric method of ferric iron-thiocyanate complex had the advantages of rapid determination,high sensitivity and long-term stability in terms of its application for determining thiocyanate.This method had a lower detection limit of 0.1mg/L and an upper detection limit of 34.8mg/L.The measurement errors were small with deviances less than 2.6%.It was found to be applicable to the determination of thiocyanate contained in the diluted coking wastewater samples where the influence of other ions on color reaction could be eliminated.In such a case,a good repeatability and a high recovery rate were obtained.

Few studies have been devoted to the real-time analysis of the variation in cyanide concentration in a coking wastewater treatment plant,although this is important for the design of such a plant.This work presented a method to allow high-efficiency removal of cyanide,based on the analysis of the data collected from a real A/O1/H/O2 coking wastewater treatment plant(Shaogang,Guangdong).The results showed that the biodegradation rate of cyanide was much slower than that of phenols present in the biological system,and the degradation rate of metal-complexed cyanide was much slower than that associated with uncomplexed cyanide.The effective removal of carbon and nitrogen in the A/O1/H/O2 biological system was responsible for achieving high-efficiency biodegradation of cyanide.In addition,this work demonstrated that the high-efficiency treatment of coking wastewater could be realized by taking into account the synergetic effect of biodegradation kinetics for different components and the optimization of operating conditions.

A novel biological fluidized bed was designed and developed to deal with high-concentration refractory organic industrial wastewater. From 12 successful projects, three cases of dyeing wastewater treatment projects with the scale of 1200, 2000 and 13000 m3/d respectively were selected to analyze the principle of treating refractory organic wastewater with fluidized bed technology and discuss the superiority of self-developed biological fluidized bed from the aspects of technical and economic feasibility. In the three cases, when the hydraulic retention time (HRT) of biological system were 23, 34 and 21. 8 h, and the volume loading of influents (COD) were 1.75, 4.75 and 2.97 kg/(m3 x d), the corresponding COD removal were 97.3%, 98.1% and 95.8%. Furthermore the operating costs of projects were 0.91, 1.17 and 0.88 yuan per ton of water respectively. The index of effluent all met the 1st grade of Guangdong Province wastewater discharge standard. Results showed that the biological fluidized bed had characteristics of shorter retention time, greater oxygen utilization rate, faster conversion rate of organic pollutants and less sludge production, which made it overcome the shortcomings of traditional methods in printing and dyeing wastewater treatment. Considering the development of technology and the combination of ecological security and recycling resources, a low-carbon wastewater treatment process was proposed.

Thiocyanate (SCN-) is one of the main contaminants in coking wastewater and has non-neglectable contribution to COD,chroma and NH+4-N value.The interactive inhibitory reaction of SCN-with other pollutants would affect the selection of treatment technology and the draining water quality control.In this study,the SCN-degradation kinetics was investigated using activated sludge of coking wastewater.Effects of phenol on SCN-degradation and SCN-on nitrification were also studied in order to assess the interaction of SCN-with other pollutants.Under specified culture condition,the degradation rate of SCN-reached up to 20.15 mg SCN-·(g MLSS)-1·h-1 and the sludge activity was not significantly affected by the initial concentration of SCN-.The SCN-degradation process follows the Michaelis-Menten model.Experiment results indicated that phenol has toxic inhibition on SCN-degradation,with 738 mg·L-1 phenol,the complete degradation time of 108 mg·L-1 SCN-was delayed from 1.5 h to 20 h.On the other hand,SCN-also inhibits the nitrification of NH+4,especially for the conversion of nitrite to nitrate,which resulted in the accumulation of NO-2.Hence,the inhibitory interactions of thiocyanate with phenol and ammonia make the treatment of coking wastewater more complicated and difficult.Thus,for the pollution control of coking wastewater,it should identify the interaction effects among main contaminants,consider the adaptation of sludge activity with pollutants concentrations from the point of co-substrate effect or poisonous effect,which would give help in establishing an optimized biological treatment technology.

Since the early 1970s, decision support systems (DSS) have evolved significantly. In this paper, the design and implementation of MSMiner, a developing platform for DSS, is introduced. The system is constructed on a data warehouse and integrated with a number of data mining algorithms. It is well suited for on-line analytical processing (OLAP). The characteristics of MSMiner include the ability to support multiple data sources and data mining strategies, additional organizational flexibility in regard to data and mining strategies, and the powerful expansibility of data mining tasks.

ERP systems for the manufacturing sector are commercially available and research on ERP systems for manufacturing enterprises is prevalent now. However, little attention has so far been paid on how to establish ERP systems for large scale engineering projects. An ERP system for a specific engineering project is usually not available commercially. In this paper, the methods and models for establishing an ERP system for a large-scale engineering project with unique features are discussed in systems engineering perspectives. First, the necessity for establishing ERP system is analysed; second, the methods and models for developing, implementing and maintaining the ERP system are discussed; third, the successful experiences of establishing the ERP system are illustrated and finally, a conclusion is provided. Copyright (c) 2006 John Wiley & Sons, Ltd.

As the Web has emerged as a large distributed data repository, individuals and organizations have been able to utilize the low-cost information and knowledge on the Internet when making business decisions. Because data in different data sources may be conflictive or untrue, researchers and practitioners must intensify efforts to develop appropriate techniques for its efficient use and management. In this paper, a logical framework is designed for identifying quality knowledge from different data sources, thus working towards the development of an agreed ontology. Our experimental results have demonstrated that the approach is promising, and that a minor data enhancement adjustment could bring higher effectiveness.

Mining group differences is useful in many applications, such as medical research, social network analysis and link discovery. The differences between groups can be measured from either statistical or data mining perspective. In this paper, we propose an empirical likelihood (EL) based strategy of building confidence intervals for the mean and distribution differences between two contrasting groups. In our approach we take into account the structure (semi-parametric) of groups, and experimentally evaluate the proposed approach using both simulated and real-world data. The results demonstrate that our approach is effective in building confidence intervals for group differences such as mean and distribution function.

ERP systems for manufacturing sector are commercially available and research on ERP systems for manufacturing enterprises is prevalent now. However, little attention has so far been paid on how to establish ERP systems for large scale engineering projects. An ERP system for a specific engineering project is usually not available commercially. In this paper, the methods and models for establishing an ERP system for a large-scale engineering project with unique features are discussed in systems engineering perspectives. First, the necessity for establishing ERP system is analyzed; second, the methods and models for developing the ERP system are discussed; finally, the relative conclusions are given.