Survey on production quality of electrodialysis reversal and reverse osmosis on municipal wastewater desalination

Water shortage has become an emerging environmental issue. Reclamation of the effluent from municipal wastewater treatment plant (WWTP) is feasible for meeting the growth of water requirement from industries. In this study, the results of a pilot-plant setting in Futian wastewater treatment plant (Taichung, Taiwan) were presented. Two processes, sand filter - ultrafiltration - reverse osmosis (SF-UF-RO) and sand filter - electrodialysis reversal (SF-EDR), were operated in parallel to evaluate their stability and filtrate quality. It has been noticed that EDR could accept inflow with worse quality and thus required less pretreatment compared with RO. During the operation, EDR required more frequent chemical cleaning (every 3 weeks) than RO did (every 3 months). For the filtrate quality, the desalination efficiency of SF-EDR ranged from 75 to 80% in continuous operation mode, while the conductivity ranged from 100 to 120 μS/cm, with turbidity at 0.8 NTU and total organic carbon at 1.3 mg/L. SF-EDR was less efficient in desalinating the multivalent ions than SF-UF-RO was. However for the monovalent ions, the performances of the two processes were similar to each other. Noticeably, total trihalomethanes in SF-EDR filtrate was lower than that of SF-UF-RO, probably because the polarization effects formed on the concentrated side of the EDR membrane were not significant. At the end of this study, cost analysis was also conducted to compare the capital requirement of building a full-scale wastewater reclamation plant using the two processes. The results showed that using SF-EDR may cost less than using SF-UF-RO, if the users were to accept the filtrate quality of SF-EDR.     

Note on “Unrelated parallel-machine scheduling with deteriorating maintenance activities”

In this note, we prove that both problems studied by Cheng et al. [Cheng, T. C. E., Hsu, C.-J., & Yang, D.-L. (2011). Unrelated parallel-machine scheduling with deteriorating maintenance activities. Computers and Industrial Engineering, 60, 602–605] can be solved in O(n^m+3) time no matter what the processing time of a job after a maintenance activity is greater or less than its processing time before the maintenance activity, where m is the number of machines and n is the number of jobs.     

Recovery of online service: Perceived justice and transaction frequency

Recovery of online service is an issue in need of study. The current study empirically examines (1) the relationships among perceived justice, satisfaction with recovery of online service and repurchase intention of online service/failure encounters; and (2) the moderating effects of transaction frequency on these relationships. The current study collects 187 self-administered questionnaires to gather customers’ perceptions of actual online service/failure encounters. Research findings demonstrate that distributive justice, interactional justice and procedural justice can positively lead to satisfaction with recovery of online service and repurchase intention toward online service. These results further show that customers with low transaction frequency tend to focus more on interactional justice to establish their satisfaction with recovery of online service. On the other hand, customers with high transaction frequency focus more on procedural justice.     

Slip and fall event detection using Bayesian Belief Network

This paper proposes a method to detect slip-only events and fall events based on the motion activity measure and human silhouette shape variations. Here, we also apply the Bayesian Belief Network (BBN) to model the causality of the events before and after the fall and slip-only events. The motion measure is obtained by analyzing the energy of the motion active (MA) area in the integrated spatiotemporal energy (ISTE) map. Unlike the motion history image (MHI), the ISTE map can be applied to detect fall and slip-only events. The contributions of this study are: (a) proposing the ISTE map; (b) detecting the fall parallel to the optical axis; (c) application to non-fixed frame rate video; (d) identifying the slip-only event; and (e) using BBN to model the causality of the slip or fall events with other events. Early identification of a slip-only event can help prevent falls and injuries. In the experiments, we demonstrate that our method is effective in detecting both fall and slip-only events.     

Extending UML to model Web 2.0‐based context‐aware applications

Web 2.0 Mashups offer entirely new opportunities for context‐aware application (CAA) developers by integrating Web 2.0 technologies to facilitate interoperability among heterogeneous context‐aware systems. From a software engineering perspective, a visualized approach for Web 2.0‐based CAA modeling is crucial. Current CAA development, however, cannot provide a conceptual model for Web 2.0‐based CAA. Therefore, the development efficiency and potential for reuse are decreased. The UML is a general purpose modeling language with potential for use in many application domains. However, UML often lacks elements needed to model concepts in specific domains, such as Web 2.0‐based CAA modeling. To address the above issues, this study presents the Web 2.0‐based CAA UML profile, a UML profile for modeling Web 2.0‐based CAA. Copyright © 2011 John Wiley & Sons, Ltd.     

Design of an adaptive self-organizing fuzzy neural network controller for uncertain nonlinear chaotic systems

Though the control performances of the fuzzy neural network controller are acceptable in many previous published papers, the applications are only parameter learning in which the parameters of fuzzy rules are adjusted but the number of fuzzy rules should be determined by some trials. In this paper, a Takagi–Sugeno-Kang (TSK)-type self-organizing fuzzy neural network (TSK-SOFNN) is studied. The learning algorithm of the proposed TSK-SOFNN not only automatically generates and prunes the fuzzy rules of TSK-SOFNN but also adjusts the parameters of existing fuzzy rules in TSK-SOFNN. Then, an adaptive self-organizing fuzzy neural network controller (ASOFNNC) system composed of a neural controller and a smooth compensator is proposed. The neural controller using the TSK-SOFNN is designed to approximate an ideal controller, and the smooth compensator is designed to dispel the approximation error between the ideal controller and the neural controller. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived based on the Lyapunov stability theory, thus not only the system stability can be achieved but also the convergence of tracking error can be speeded up. Finally, the proposed ASOFNNC system is applied to a chaotic system. The simulation results verify the system stabilization, favorable tracking performance, and no chattering phenomena can be achieved using the proposed ASOFNNC system.     

Adaptive dynamic CMAC neural control of nonlinear chaotic systems with L2 tracking performance

The advantage of using cerebellar model articulation control (CMAC) network has been well documented in many applications. However, the structure of a CMAC network which will influence the learning performance is difficult to select. This paper proposes a dynamic structure CMAC network (DSCN) which the network structure can grow or prune systematically and their parameters can be adjusted automatically. Then, an adaptive dynamic CMAC neural control (ADCNC) system which is composed of a computation controller and a robust compensator is proposed via second-order sliding-mode approach. The computation controller containing a DSCN identifier is the principal controller and the robust compensator is designed to achieve L₂ tracking performance with a desired attenuation level. Moreover, a proportional–integral (PI)-type adaptation learning algorithm is derived to speed up the convergence of the tracking error in the sense of Lyapunov function and Barbalat’s lemma, thus the system stability can be guaranteed. Finally, the proposed ADCNC system is applied to control a chaotic system. The simulation results are demonstrated that the proposed ADCNC scheme can achieve a favorable control performance even under the variations of system parameters and initial point.     

Segmenting customers by transaction data with concept hierarchy

The segmentation of customers is crucial for an organization wishing to develop appropriate promotion strategies for different clusters. Clustering customers provides an in-depth understanding of their behavior. However, previous studies have paid little attention to the similarity of different items in transaction. Lack of categories and concept levels of items, results from item-based segmentation methods are not as good as expected. Through employing a concept hierarchy of items, this study proposes a segmentation methodology to identify similarities between customers. First, the dissimilarity between transaction sequences is defined. Second, we adopt hierarchical clustering method to segment customers by their transaction data with concept hierarchy of consumed items. After segmentation, three cluster validation indices are used for optimizing the number of clusters of customers. Through the compassion of normalized index, the segmentation method proposed by this study rendered better results than other traditional methods.     

Organoclay effect on transverse compressive strength of glass/epoxy nanocomposites

This research focuses on the fabrication of glass fiber/epoxy nanocomposites containing organoclay as well as understanding the organoclay effect on the transverse compressive strength of nanocomposites. To demonstrate the organoclay effect, three different loadings of organoclay were dispersed, respectively, in the epoxy resin using a mechanical mixer followed by sonication. The corresponding glass/epoxy nanocomposites were produced by impregnating dry glass fiber with organoclay epoxy compound through a vacuum hand lay-up procedure. Unidirectional block specimens were employed for transverse compression tests on a hydraulic MTS machine. Experimental observations indicate that glass/epoxy nanocomposites containing organoclay exhibit higher transverse compressive strength than conventional composites. Furthermore, the failure mechanisms for all tested specimens were found to be fiber and matrix debonding. Therefore, results indicate that the increasing characteristic in transverse failure stress may be ascribed to the enhanced fiber/matrix adhesion modified by the organoclay.     

The effect of substrate temperature on the microstructure and tunnelling magnetoresistance of FeCo–Al2O3 nanogranular films

A series of FeCo–Al₂O₃ granular films were prepared with a magnetron controlled sputtering system. The magnetic–transport properties and microstructure of films sputtered at various substrate temperatures were characterized by conventional four probes method, SQUID magnetometer, analytical electron microscope and transmission electron microscope, respectively. The results indicate that the tunnelling magnetoresistance reaches the peak value of about 6.9% for FeCo (41 vol.%)-Al₂O₃ granular films sputtered at 300 K, while for FeCo granular films sputtered at 473 K, the 6% peak value in tunnelling magnetoresistance vs. volume fraction curve displaces toward the lower FeCo content of about 35 vol.%. Meanwhile, FeCo (30vol.%)-Al₂O₃ granular films sputtered both at room temperature and at 473 K behave as superparamagnetic and the susceptibility of this film increases with increasing substrate temperature. Based on the feature of microstructure of FeCo (41vol.%)-Al₂O₃ granular films sputtered at both room temperature and 823 K, the evolution sequence of two-stage phase separation is suggested. In addition, the effect of the microstructure on tunnelling magnetoresistance has been discussed.