Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

Mode Matching Analysis of a Tapered Coaxial Tip in a Parallel-Plate Waveguide

A tapered coaxial tip in a parallel plate waveguide is investigated. A boundary-value problem of electromagnetic scattering from a tapered coaxial monopole is solved rigorously based on the Fourier transform, eigenfunction expansion, and mode matching. Scattering parameters are represented in a series and computed to understand the behavior of the scattering in terms of the coaxial tip geometry.     

Corrosion resistance of austenitic stainless steel separator for molten carbonate fuel cell

STS310S and SC-STS310S (simultaneously co-deposited chromium and aluminum onto 310S austenitic stainless steel substrate by pack-cementation process) were used as separator materials on the cathode side of a molten carbonate fuel cell. With the STS310S, corrosion proceeded via three steps; a formation step of unstable corrosion product, a protection step against corrosion until breakaway, and an advance step of corrosion after breakaway. The final corrosion product was LiFeO₂ and the loss of mass was 6.5 mg/cm² after a corrosion test of 480 hr at 650°C. The SC-STS310S showed more effective corrosion resistance, however, than did common STS310S. There was especially no corrosion loss on the SC-STS310S after the 480 hr corrosion test. It is anticipated that it will be very useful as an alternative separator on the cathode side off the MCFC in the future.     

Inductive semimodules and the vector modules over them

The notion of an inductive semimodule over an ordered *-semiring is introduced and some related properties are investigated. Inductive semimodules are extensions of several important algebraic structures such as Kleene modules, Kleene algebras and inductive *-semirings. We prove that an inductive semimodule over an ordered *-semiring K is a Kleene module if and only if K is a Kleene algebra. Moreover, we establish that the vector module of an inductive semimodule over an ordered Conway semiring is again an inductive semimodule over the matrix semiring. Consequently, in an inductive semimodule over an ordered Conway semiring, least solutions to linear inequation systems can be denoted by linear expressions, avoiding the least fixed point operator. In addition, we also introduce a related notion called weak inductive semimodules, and propose several open problems on them.

Memory effects of all‐solution‐processed oxide thin‐film transistors using ZnO nanoparticles

Abstract— Non‐volatile memory effects of an all‐solution‐processed oxide thin‐film transistor (TFT) with ZnO nanoparticles (NPs) as the charge‐trapping layer are reported. The device was fabricated by using a soluble MgInZnO active channel on a ZrHfO^x gate dielectric. ZnO NPs were used as the charge‐trapping site at the gate‐insulator—channel interface, and Al was used for source and drain electrodes. Transfer characteristics of the device showed a large clockwise hysteresis, which can be used to demonstrate its memory function due to electron trapping in the ZnO NP charge‐trapping layer. This memory effect has the potential to be utilized as a memory application on displays and disposable electronics.     

Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Response to ‘Comments on: A cohesion measure for object‐oriented classes’

Indicating that CBMC does not satisfy the monotonic property in terms of the number of interactions, Xu and Zhou proposed an augmented definition of CBMC by adopting cut set instead of glue methods. The augmented CBMC clearly satisfies the monotonic property. However, CBMC is designed to overcome the problem with respect to the number of interactions and, therefore, focuses on the interaction pattern, especially, member connectivity. Consequently, it does not make sense to mention the monotonic property of CBMC with respect to interaction number. Moreover, the notion of glue methods allows several interpretations on the design quality of a class. However, that meaningful interpretation is not possible for the augmented definition due to the removal of the notion of glue methods. Copyright © 2001 John Wiley & Sons, Ltd.