Mining predecessor–successor rules from DAG data

Data mining extracts implicit, previously unknown, and potentially useful information from databases. Many approaches have been proposed to extract information, and one of the most important ones is finding association rules. Although a large amount of research has been devoted to this subject, none of it finds association rules from directed acyclic graph (DAG) data. Without such a mining method, the hidden knowledge, if any, cannot be discovered from the databases storing DAG data such as family genealogy profiles, product structures, XML documents, task precedence relations, and course structures. In this article, we define a new kind of association rule in DAG databases called the predecessor–successor rule, where a node x is a predecessor of another node y if we can find a path in DAG where x appears before y. The predecessor–successor rules enable us to observe how the characteristics of the predecessors influence the successors. An approach containing four stages is proposed to discover the predecessor–successor rules. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 621–637, 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.     

Synthesis of Rice Processing Plants. I. Development of Simplified Models

This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.     

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.     

High-performance MIM capacitor using ALD high-k HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectrics

For the first time, we successfully fabricated and demonstrated high performance metal-insulator-metal (MIM) capacitors with HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectric using atomic layer deposition (ALD) technique. Our data indicates that the laminate MIM capacitor can provide high capacitance density of 12.8 fF//spl mu/m/sup 2/ from 10 kHz up to 20 GHz, very low leakage current of 3.2 /spl times/ 10/sup -8/ A/cm/sup 2/ at 3.3 V, small linear voltage coefficient of capacitance of 240 ppm/V together with quadratic one of 1830 ppm/V/sup 2/, temperature coefficient of capacitance of 182 ppm//spl deg/C, and high breakdown field of /spl sim/6 MV/cm as well as promising reliability. As a result, the HfO/sub 2/-Al/sub 2/O/sub 3/ laminate is a very promising candidate for next generation MIM capacitor for radio frequency and mixed signal integrated circuit applications.     

Hydrogen annealing effect on DC and low-frequency noise characteristics in CMOS FinFETs

The hydrogen annealing process has been used to improve surface roughness of the Si-fin in CMOS FinFETs for the first time. Hydrogen annealing was performed after Si-fin etch and before gate oxidation. As a result, increased saturation current with a lowered threshold voltage and a decreased low-frequency noise level over the entire range of drain current have been attained. The low-frequency noise characteristics indicate that the oxide trap density is reduced by a factor of 3 due to annealing. These results suggest that hydrogen annealing is very effective for improving device performance and for attaining a high-quality surface of the etched Si-fin.     

Bio-layer management in anaerobic membrane bioreactors for wastewater treatment.

Membrane separation technology represents an alternative way to achieve biomass retention in anaerobic bioreactors for wastewater treatment. Due to high biomass concentrations of anaerobic reactors, cake formation is likely to represent a major cause of flux decline. In the presented research, experiments are performed on the effect of biomass concentration and level of gas sparging on the hydraulic capacity of a submerged anaerobic membrane bioreactor. Both parameters significantly affected the hydraulic capacity, with biomass exerting the most pronounced effect. After 50 days of continuous operation the critical flux remained virtually unchanged, despite an increase in membrane resistance, suggesting that biomass characteristics and hydraulic conditions determine the bio-layer formation rather than the membrane's fouling level. The concept of bio-layer management is introduced to describe the programmed combination of actions performed in order to control the formation of biomass layer over membranes.