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.     

Interference impacts on 60 ghz real-time online video streaming in wireless smart tv platforms

In this paper we provide a method for computing and estimating the impact of interference on real-time online 1080p@30Hz and 1080p@60Hz high-definition video streaming in 60 GHz wireless smart TV platforms. The analysis involves two different interference scenarios: 1) downlink interference from deployed 60 GHz access points to the associated mobile ad-hoc devices, and 2) uplink interference from randomly deployed 60 GHz ad-hoc mobile devices to their associated access points. With these interference scenarios, the interference impact on the quality of main 1080p@30Hz and 1080p@60Hz wireless high-definition video streaming with various simulation settings are measured and estimated in terms of signal-to-interference-plus-noise ratio.     

A novel part-based approach to mean-shift algorithm for visual tracking

Visual tracking is one of the most important problems considered in computer vision. To improve the performance of the visual tracking, a part-based approach will be a good solution. In this paper, a novel method of visual tracking algorithm named part-based mean-shift (PBMS) algorithm is presented. In the proposed PBMS, unlike the standard mean-shift (MS), the target object is divided into multiple parts and the target is tracked by tracking each individual part and combining the results. For the part-based visual tracking, the objective function in the MS is modified such that the target object is represented as a combination of the parts and iterative optimization solution is presented. Further, the proposed PBMS provides a systematic and analytic way to determine the scale of the bounding box for the target from the perspective of the objective function optimization. Simulation is conducted with several benchmark problems and the result shows that the proposed PBMS outperforms the standard MS.

     

Note: Interpolation for evaluation of a two-dimensional spatial profile of plasma densities at low gas pressures

An interpolation algorithm for the evaluation of the spatial profile of plasma densities in a cylindrical reactor was developed for low gas pressures. The algorithm is based on a collisionless two-dimensional fluid model. Contrary to the collisional case, i.e., diffusion fluid model, the fitting algorithm depends on the aspect ratio of the cylindrical reactor. The spatial density profile of the collisionless fitting algorithm is presented in two-dimensional images and compared with the results of the diffusion fluid model.     

A high performance parallel DCT with OpenCL on heterogeneous computing environment

A noteworthy thing in desktop PCs is that they can provide a great opportunity to increase the performance of processing multimedia data by exploiting task- and data-parallelism with multi-core CPU and many-core GPU. This paper presents a high performance parallel implementation of 2D DCT on this heterogeneous computing environment. For this purpose, Intel TBB (threading building blocks) and OpenCL (Open Compute Language) are utilized for task- and data-parallelism, respectively. The simulation result shows that the parallel DCT implementations far the serial ones in processing speed. Especially, OpenCL implementation shows a linear speedup, a typical SIMD characteristic as the increase of 2D data sets.     

A finite memory filtering for end-to-end available bandwidth estimation

In this paper, a finite memory filter is proposed to estimate the available bandwidth through real-time tracking unknown parameters of the sloping straight line while removing undesired system and measurement noises. The finite memory filter is developed under a weighted least square criterion using only the most recent finite probe-packet measurements on the window. The proposed finite memory filtering based available bandwidth estimate is shown to have several inherent properties such as unbiasedness, deadbeat, and robustness. A guideline for choosing appropriate window length is described as it can significantly affect the estimation performance. Finally, computer simulations show that the proposed finite memory filtering based approach can be comparable with the Kalman filtering based approach with infinite memory structure for constantly or slowly changing available bandwidth and outperform that for dynamically changing available bandwidth.     

Color segmentation robust to brightness variations by using B-spline curve modeling

Color segmentation takes a great attention because color is an effective and robust visual cue for characterizing an object from the others. However, color segmentation suffers from color variations incurred by irregular illumination changes. We propose a reliable color modeling approach in hue–saturation–intensity (HSI) color space while considering intensity information by adopting the B-spline curve fitting to make a mathematical model for statistical characteristics of a color with respect to intensity. It is based on the fact that color distribution of a single-colored object is not invariant with respect to brightness variations even in the HS (hue–saturation) plane. The statistical characteristics contain the mean and standard deviation of hue and saturation with respect to intensity. They are mathematically expressed as four bar graphs. In order to fit the bar graphs to continuous curves, we use B-spline curve fitting procedure. From several experimental results, we verify that the proposed algorithm is successfully applied to color segmentation under various illumination conditions.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Optimal infinite scheduling for multi-priced timed automata

This paper is concerned with the derivation of infinite schedules for timed automata that are in some sense optimal. To cover a wide class of optimality criteria we start out by introducing an extension of the (priced) timed automata model that includes both costs and rewards as separate modelling features. A precise definition is then given of what constitutes optimal infinite behaviours for this class of models. We subsequently show that the derivation of optimal non-terminating schedules for such double-priced timed automata is computable. This is done by a reduction of the problem to the determination of optimal mean-cycles in finite graphs with weighted edges. This reduction is obtained by introducing the so-called corner-point abstraction, a powerful abstraction technique of which we show that it preserves optimal schedules. This work has been mostly done while visiting CISS at Aalborg University in Denmark and has been supported by CISS and by ACI Cortos, a program of the French Ministry of Research.