Investigation on sulphonated zinc oxide nanorod incorporated sulphonated poly (1,4-phenylene ether ether sulfone) nanocomposite membranes for improved performance of microbial fuel cell

Hydrothermally prepared zinc oxide nanorods are sulphonated (S–ZnO NR) and incorporated into 15% Sulphonated Poly (1,4-Phenylene Ether Ether Sulfone) (SPEES) to improve the hydrophilicity, water uptake and ion transfer capacity. Water uptake and ion transfer capacity increased to 34.6 ± 0.6% and 2.0 ± 0.05 meq g^?1 from 29.8 ± 0.3% and 1.4 ± 0.04 meq g^?1 by adding 7.5 wt% S–ZnO NR to SPEES. Morphological studies show the prepared S–ZnO NR is well dispersed in the polymer matrix. SPEES +7.5 wt% S–ZnO NR membrane exhibits optimum performance after three-weeks of continual operation in a fabricated microbial fuel cell (MFC) to produce a maximum power density of 142 ± 1.2 mW m^?2 with a reduced biofilm compared to plain SPEES (59 ± 0.8 mW m^?2), unsulphonated filler incorporated SPEES (SPEES + 7.5 wt% ZnO, 68 ± 1.1 mW m^?2) and Nafion (130 ± 1.5 mW m^?2) thereby suggesting its suitability as a sustainable and improved cation exchange membrane (CEM) for MFCs.     

Impact of power-supply noise on timing in high-frequency microprocessors

This paper analyzes the impact of power-supply noise on the performance of high-frequency microprocessors. First, delay models that take this noise into account are proposed for device-dominated and interconnect-dominated timing paths. For typical circuits, it is shown that the peak of the noise is largely irrelevant and that the average supply voltage during switching is more important. It is then argued that global differential noise can potentially have a greater timing impact than common-mode noise. Finally, realistic values for the model parameters are measured on a 2.53-GHz Pentium4 microprocessor using a 130-nm technology. These values imply that the power-supply noise present on the system board reduces clock frequency by 6.7%. The model suggests that the frequency penalty associated with this power-supply noise will steadily increase and reach 7.6% for the 90-nm technology generation.     

A general enthalpy method for modeling solidification processes

In the present work, a general implicit source-based enthalpy method is presented for the analysis of solidification systems. The proposed approach is both robust and efficient. The performance of the method is illustrated by application to a number of problems taken from recent metallurgical literature.     

Analysis of Caching and Replication Strategies for Web Applications

Developers often use replication and caching mechanisms to enhance Web application performance. The authors present a qualitative and quantitative analysis of state-of-the art replication and caching techniques used to host Web applications. Their analysis shows that selecting the best mechanism depends heavily on data workload and requires a careful review of the application's characteristics. They also propose a technique for Web practitioners to compare different mechanisms' performance on their own     

Evaluation of Localized Semantics: Data, Methodology, and Experiments

We present a new data set of 1014 images with manual segmentations and semantic labels for each segment, together with a methodology for using this kind of data for recognition evaluation. The images and segmentations are from the UCB segmentation benchmark database (Martin et al., in International conference on computer vision, vol. II, pp. 416–421, 2001). The database is extended by manually labeling each segment with its most specific semantic concept in WordNet (Miller et al., in Int. J. Lexicogr. 3(4):235–244, 1990). The evaluation methodology establishes protocols for mapping algorithm specific localization (e.g., segmentations) to our data, handling synonyms, scoring matches at different levels of specificity, dealing with vocabularies with sense ambiguity (the usual case), and handling ground truth regions with multiple labels. Given these protocols, we develop two evaluation approaches. The first measures the range of semantics that an algorithm can recognize, and the second measures the frequency that an algorithm recognizes semantics correctly. The data, the image labeling tool, and programs implementing our evaluation strategy are all available on-line (kobus.ca//research/data/IJCV_2007). We apply this infrastructure to evaluate four algorithms which learn to label image regions from weakly labeled data. The algorithms tested include two variants of multiple instance learning (MIL), and two generative multi-modal mixture models. These experiments are on a significantly larger scale than previously reported, especially in the case of MIL methods. More specifically, we used training data sets up to 37,000 images and training vocabularies of up to 650 words. We found that one of the mixture models performed best on image annotation and the frequency correct measure, and that variants of MIL gave the best semantic range performance. We were able to substantively improve the performance of MIL methods on the other tasks (image annotation and frequency correct region labeling) by providing an appropriate prior.     

An algorithm for recognizing palm polygons

A polygonP is said to be apalm polygon if there exists a pointxP such that the Euclidean shortest path fromx to any pointyP makes only left turns or only right turns. The set of all such pointsx is called thepalm kernel. In this paper we propose an O(E) time algorithm for recognizing a palm polygonP, whereE is the size of the visibility graph ofP. The algorithm recognizes the given polygonP as a palm polygon by computing the palm kernel ofP. If the palm kernel is not empty,P is a palm polygon.The extended abstract of this paper was reported at the Second Canadian Conference in Computational Geometry, pp. 246–251, 1990     

Energy and Trust Management Framework for MANET using Clustering Algorithm

In General, Mobile Ad-Hoc Network (MANET) has limited energy resources, and it cannot recharge itself. This research goal focuses on building a power management scheme that saves energy in the MANET. Due to power instability, there is a chance that cluster heads fail and function incorrectly in cluster-based routing. As a result, instability occurs with the cluster heads while collecting data and communicating with others effectively. This work focuses on detecting the unstable cluster heads, which are replaced by other nodes implementing the envisaged self-configurable cluster mechanism. A self-configurable cluster mechanism with a k-means protocol approach is proposed to designate cluster heads effectively. The proposed k-means procedure is based on periodic irregular cluster head rotations or altering the number of clusters. We also propose a trust management mechanism in this research to detect and avoid MANET vulnerabilities. Because of the continuously changing topology and limited resources (power, bandwidth, computing), the trust management algorithm should only use local data. Consequently, compared to traditional protocols, the proposed approach with the k-means procedure and its experimental results show lower power usage and provide an optimal system for trust management.

     

Extraction of S‐parameters from time domain reflectometry and transmission measurements using rational functions

The extraction of the broad band S‐parameter response from transient reflection and transmission measurements is discussed. The proposed method uses the generalized pencil‐of‐function method, recursive deconvolution, and calibration structures to obtain a response using rational functions. A low loss printed circuit board plane and a lossy thin film plane are characterized to capture the two‐port S‐parameters. The results are compared with network analyzer measurements. The effects of the measurement parameters such as the sampling interval, time window, and number of averages are shown. The effect of time jitter on the extracted frequency response is quantified through repeated measurements. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 74–85, 2003.