Effects of solid retention time on the performance of submerged anoxic/oxic membrane bioreactor.

In this study, four similar bench-scale submerged Anoxic/Oxic Membrane Bioreactors (MBR) were used simultaneously to investigate the effects of solids retention time (SRT) on organic and nitrogen removal in MBR for treating domestic wastewater. COD removal efficiencies in all reactors were consistently above 94% under steady state conditions. Complete conversion of NH(4+)-N to NO(3-)-N was readily achieved over a feed NH(4+)-N concentration range of 30 to 50 mg/L. It was also observed that SRT did not significantly affect the nitrification in the MBR systems investigated. The average denitrification efficiencies for the 3, 5, 10 and 20 days SRT operations were 43.9, 32.6, 47.5 and 66.5%, respectively. In general, the average effluent nitrogen concentrations, which were mainly nitrate, were about 22.2, 27.6, 21.7 and 13.9 mg/L for the 3, 5, 10 and 20 days SRT systems, respectively. The rate of membrane fouling at 3 days SRT operation was more rapid than that observed at 5 days SRT. No fouling was noted in the 10 days and 20 days SRT systems during the entire period of study.     

Thermal challenges in next generation electronic systems - summary of panel presentations and discussions

The presentations made, as well as the discussions, in the panels at the workshop, Thermal Challenges in Next Generation Electronic Systems (THERMES), are summarized in this paper. The panels dealt with diverse topics including thermal management roadmaps, microscale cooling systems, numerical modeling from the component to system levels, hardware for future high performance and Internet computing architectures, and transport issues in the manufacturing of electronic packages. The focus of the panels was to identify barriers to further progress in each area that require the attention of the research community.     

Predictive fine granularity successive elimination for fast optimal block-matching motion estimation.

Given the number of checking points, the speed of block motion estimation depends on how fast the block matching is. In this paper, a new framework, fine granularity successive elimination (FGSE), is proposed for fast optimal block matching in motion estimation. The FGSE features providing a sequence of nondecreasing fine-grained boundary levels to reject a checking point using as little computation as possible, where block complexity is utilized to determine the order of partitioning larger sub-blocks into smaller subblocks in the creation of the fine-grained boundary levels. It is shown that the well-known successive elimination algorithm (SEA) and multilevel successive elimination algorithm (MSEA) are just two special cases in the FGSE framework. Moreover, in view that two adjacent checking points (blocks) share most of the block pixels with just one pixel shifting horizontally or vertically, we develop a scheme to predict the rejection level for a candidate by exploiting the correlation of matching errors between two adjacent checking points. The resulting predictive FGSE algorithm can further reduce computation load by skipping some redundant boundary levels. Experimental results are presented to verify substantial computational savings of the proposed algorithm in comparison with the SEA/MSEA.     

Optimization techniques for curved path computing

Participating media with an inhomogeneous index of refraction make light follow curved paths. Simulating this in a global illumination environment has usually been neglected due to the complexity of the calculations involved, sacrificing accurate physical simulations for efficient visual results. This paper aims to simulate non-linear media in a more reasonable time than previous works without losing physical correctness. Accuracy is achieved by solving the Eikonal equation of geometrical optics, which describes the path followed by a light beam that traverses a non-linear medium. This equation is used in the context of a photon mapping extension.     

Face detection based on skin color likelihood

We propose a face detection method based on skin color likelihood via a boosting algorithm which emphasizes skin color information while deemphasizing non-skin color information. A stochastic model is adapted to compute the similarity between a color region and the skin color. Both Haar-like features and Local Binary Pattern (LBP) features are utilized to build a cascaded classifier. The boosted classifier is implemented based on skin color emphasis to localize the face region from a color image. Based on our experiments, the proposed method shows good tolerance to face pose variation and complex background with significant improvements over classical boosting-based classifiers in terms of total error rate performance.     

Effect of dispersity on the Tll (>Tg) transition in polystyrene

The presence of a high temperature (>T_g) relaxation in amorphous polystyrene has been investigated further. In the previous work,¹ the techniques of differential thermal analysis (DTA) and torsional braid analysis (TBA) were employed to study polystyrene as a function of “monodisperse” molecular weight. The occurrence of the T_ll transition appeared to be associated with the attainment of a critical viscosity level with also corresponded with a free volume level. An entanglement network developed at a critical value of molecular weight, M_c, giving a break in the T_ll-versus-M plots. The present work deals with the influence of dispersity on the T_ll transition, below and above M_c. A series of binary blends of “monodisperse” anionically polymerized polystyrenes with systematic changes in M?_n and heterogeneity index (M?_w/M?_n) was tested by TBA. The results show that when both components have molecular weights below M_c, single and average values of T_g and T_ll are observed which are linearly related to M?_n^?1, as predicted by free volume arguments. Although a single T_g is observed when one component has a molecular weight above and the other has a molecular weight below M_c, the components appear to undergo the T_ll relaxation independently. The results indicate that both the glass transition and the T_ll transition are basically governed by the same type of molecular motion but at different length ranges.     

Metal Dusting of Fe–Cr and Fe–Ni–Cr Alloys Under Cyclic Conditions

Metal dusting is the disintegration of alloys into carbon and metal particles during high-temperature exposure to carbon-bearing gases. Model Fe–Cr and Fe–Ni–Cr alloys were studied to test the hypothesis that M₃C formation is necessary for metal dusting to occur. The alloys were exposed to a 68% CO–26% H₂–6% H₂O gas mixture at 680°C (a_c=2.9) under thermal cycling conditions. Equilibrium calculations predicted the formation of M₃C at the surface of Fe–25Cr, but not Fe–60Cr. All compositions were expressed in w/o, weight percent. Alloys of Fe–25Cr with 2.5, 5, 10, and 25 w/o nickel additions were also exposed to the same conditions to study the role of nickel in destabilizing the precipitation of M₃C and, hence, altering the resistance to metal dusting. Metal dusting was observed on all the alloys except Fe–60Cr. For Fe–25Cr, Fe–25Cr–2.5Ni, and Fe–25Cr–5Ni, the carbonization and dusting process was localized, and its incidence decreased in Fe–25Cr–2.5Ni, consistent with the increased destabilization of M₃C precipitation. However, Fe–25Cr–10Ni and Fe–25Cr–25Ni both underwent extensive dusting in the absence of protective Cr₂O₃ formation. The carbon deposits formed consisted of carbon filaments, which contained particles at their tips. These were shown by electron diffraction to be exclusively Fe₃C in Fe–25Cr, Fe–25Cr–2.5Ni, and Fe–25Cr–5Ni, and a mixture of austenite and (Fe,Ni)₃C in Fe–25Cr–10Ni and Fe–25Cr–25Ni.     

Object tracking based on an online learning network with total error rate minimization

This paper presents a visual object tracking system which is tolerant to external imaging factors such as illumination, scale, rotation, occlusion and background changes. Specifically, an integration of an online version of total-error-rate minimization based projection network with an observation model of particle filter is proposed to effectively distinguish between the target object and the background. A re-weighting technique is proposed to stabilize the sampling of particle filter for stochastic propagation. For self-adaptation, an automatic updating scheme and extraction of training samples are proposed to adjust to system changes online. Our qualitative and quantitative experiments on 16 public video sequences show convincing performances in terms of tracking accuracy and computational efficiency over competing state-of-the-art algorithms.     

Remote flood monitoring system based on plastic optical fibres and wireless motes

This paper summarises an effort in the development of a remote flood monitoring system based on plastic optical fibre (POF) sensors and a wireless mote network. The wireless mote, comprising of a network of MICA2DOT™ units, was used as a platform to monitor and record the signal from the POF sensors and transmit this information to a base station wirelessly. A prototype of the integrated wireless POF sensor unit has been constructed, rendering it possible to deploy the autonomous unit remotely at multiple monitoring points as required. A flood monitoring simulation was carried out in a 24 m × 10 m × 0.9 m wave basin where four of these wireless optical fibre mote sensors were used to detect the rising water level in the basin. The novelty of the work lies in the successful integration of the wireless platform to a POF-based liquid level sensor and the subsequent demonstration of the prototype of the system for the purposes of flood monitoring applications.The sensing principle of the POF sensor developed here is well-known and is based on the loss of total internal reflection of the optical signal as the sensor probe comes in contact with the liquid. Compared to optical fibre-based sensors reported previously in the literature, the probe profile used in this study differs in terms of its simplicity in design, while exhibiting an excellent signal intensity loss ratio without the need for additional attachments to the probe such as optical prisms. The tests carried out showed that the POF sensor is capable of detecting a variety of fluids. Exhibiting good signal stability, the sensor also detects the liquid level reliably when the liquid rises or falls to the predetermined level. The responsiveness of the optical fibre sensor was evaluated by simulating different rates at which the liquid rises by immersing the sensor tip into the liquid and vice-versa at various speeds ranging from 1 mm/min to 500 mm/min.