Fast similarity join for multi-dimensional data

The efficient processing of multidimensional similarity joins is important for a large class of applications. The dimensionality of the data for these applications ranges from low to high. Most existing methods have focused on the execution of high-dimensional joins over large amounts of disk-based data. The increasing sizes of main memory available on current computers, and the need for efficient processing of spatial joins suggest that spatial joins for a large class of problems can be processed in main memory. In this paper, we develop two new in-memory spatial join algorithms, the Grid-join and EGO*-join, and study their performance. Through evaluation, we explore the domain of applicability of each approach and provide recommendations for the choice of a join algorithm depending upon the dimensionality of the data as well as the expected selectivity of the join. We show that the two new proposed join techniques substantially outperform the state-of-the-art join algorithm, the EGO-join.     

Mobile information services enabled by mobile publishing (MIS-MP)

Mobile users and devices want to discover and share a growing range of information as the processing and storage capabilities of mobile devices grow. For example, users want to discover nearby networks, and location-based or time-sensitive user information contents. A mobile device may want to discover neighboring networks and the parameters required to access these networks so that it can intelligently decide which networks to use next, and use its existing network connection to authenticate with selected neighboring networks before it moves into the coverage areas of the selected networks. This can significantly reduce handoff delays. Existing service discovery frameworks are not effective for such neighboring network discovery or for discovering dynamic, location- or time-sensitive user information contents. This paper describes and evaluates a new approach—Mobile Information Services enabled by Mobile Publishing (MIS-MP)—for real time collection, discovery, and sharing of network and user information. With MIS-MP, mobiles take full advantage of the wealth of information they can accumulate during their routine mobility and use of networks to help each other to discover the information they want when and where they want it. This is accomplished by mobiles publishing the information they collect about the networks they visited, and the user information contents they learned or used, to make the information available to other mobiles. This paper presents analytical models and simulation results to evaluate the feasibility and performance of MIS-MP. It also describes a testbed implementation of MIS-MP and some of the lessons we learned. Tao Zhang is Director of Mobile Networking Research Group at Telcordia Technologies, Piscataway, New Jersey, USA. He develops and directs research and advanced development programs in mobile networking and applications, including mobility and applications across heterogeneous radio networks, mobile information services, vehicular networking, mobile peer-to-peer applications, sensor networking and applications, and collaborative networking .Dr. Zhang’s work has led to several new commercial products. He co-authored the book “IP-Based Next Generation Wireless Networks” published by John Wiley & Sons in 2004. He initiated the International Conference on Collaborative Computing: Networking, Applications, and Worksharing (CollaborateCom), and has been serving in various roles for it. Dr. Zhang holds 4 U.S. patents, with over 25 more pending. He received the 2000 Telcordia CEO Award (for most exceptional teams and individuals who have achieved a significant business success) and 2002 SAIC’s Executive Science and Technology Council Publication Prize. Eric van den Berg received his Ph.D. in Applied Mathematics from Cornell University in 1999. After obtaining his degree, he joined Telcordia Technologies, where he is a Research Scientist in Applied Research Department. His research interests include traffic modeling and performance analysis of IP- and wireless networks. He received the 2000 Telcordia CEO Award (for most exceptional individuals and teams who have achieved a significant business success) and the 2002 SAIC Executive Science and Technology Council Publication Prize. Sunil Madhani is a Distinguished MTS with Motorola where he manages the IP Realization team in Mobile Device Technology Office. He aims at working on unconventional and disruptive IP technologies. His current research focus is on convergent networks, dynamic mobility management and fast handoff in secured/seamless wireless LAN/WAN roaming. His past research includes registration/configuration protocols in wireless environment, application layer mobility management, secured Mobile IP, managed DOS attack sensor and TCP/IP boosters. Sunil Madhani holds MS (2002) in Engineering Management & System from Columbia University and MS (1997) in Computer Science from State University of New York.     

Text extraction and document image segmentation using matched wavelets and MRF model.

In this paper, we have proposed a novel scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estim ating globally matched wavelet filters using a collection of groundtruth images. We have extended our text extraction scheme for the segmentation of document images into text, background, and picture components (which include graphics and continuous tone images). Multiple, two-class Fisher classifiers have been used for this purpose. We also exploit contextual information by using a Markov random field formulation-based pixel labeling scheme for refinement of the segmentation results. Experimental results have established effectiveness of our approach.     

Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

Linear retrieval,validation and mapping of the sea surface temperature over western mid-latitude North Pacific using Seasat SMMR data

Abstract

The Scanning Multichannel Microwave Radiometer (SMMR) aboard the Seasat satellite measured emitted radiation in both horizontal and vertical polarizations at microwave frequencies of 6.6, 1069, 18.0, 21.0 and 37.0 GHz. Retrieval algorithms, for sea surface temperature (SST) determination, from subsets of one to three SMMR channels, are obtained by a two-step statistical technique. The technique first selects the best subsets of a given size defined by an R2 criterion (coefficient of determination), of a given size by the application of an efficient leaps and bounds technique on a statistical data base. It then performs a regression analysis on the selected subsets. The statistical data base employed a large (600) set of seasonally and geographically diverse atmospheric and surface parameters for radiative transfer calculations. The results of the study of one to three-channel subset retrieval algorithms indicate the possibility of using 6.6 V, 6.6 H and 18 V channels for SST determinatidn from Seasat-SMMR data. A comparison of SMMR-SST derived from three channels mentioned above and expendable bathythermograph (XBT) measurements over the North Pacific provided an r.m.s. difference of ～ 1.4 K which is comparable to the accuracy obtained from a five-channel subset (6 6 V, 6-6 H, 10-69 H, 180V, 21 OH) retrieval algorithm. The retrieval technique has the ability to recognize severe noise in brightness temperature measurements which may lead to unacceptable parameter retrieval. This may be achieved by setting up a quality control criteria either using different subsets of the same size or of different sizes. The three-channel retrieval compares within ～ 1.2 K with Chester's algorithm, which is being used at the Jet Propulsion Laboratory for geophysical processing.

Ten-day and monthly average SMMR-SST contour maps are produced using three-channel retrieval for the period 7 July-6 August 1978 over the western North Pacific, 20^°-50^° N, 140^°-180^° E. These contour maps are compared against similar maps obtained from Chester's algorithm and ship's observations. All the SMMR-SST maps show the major climatological features and are in reasonable agreement with ship's SST maps.     

Relationships between vegetation indices and root zone soil moisture under maize and soybean canopies in the US Corn Belt: a comparative study using a close-range sensing approach

Understanding the relationships between root zone soil moisture and vegetation spectral signals will enhance our ability to manage water resources and monitor drought-related stress in vegetation. In this article, the relationships between vegetation indices (VIs) and in situ soil moisture under maize and soybean canopies were analysed using close-range reflectance data acquired at a rainfed cropland site in the US Corn Belt. Because of the deep rooting depths of maize plants, maize-based VIs exhibited significant correlations with soil moisture at a depth of 100 cm (P < 0.01) and kept soil moisture memory for a long period of time (45 days). Among the VIs applied to maize, the chrolophyll red-edge index (CI_red-edge) correlated best with the concurrent soil moisture at 100 cm depth (P < 0.01) for up to 20 day lag periods. The same index showed a significant correlation with soil moisture at a 50 cm depth for lag periods from 10 (P < 0.05) to 60 days (P < 0.01). VIs applied to soybean resulted in statistically significant correlations with soil moisture at the shallower 10 and 25 cm depths, and the correlation coefficients declined with increasing depths. As opposed to maize, soybean held a shorter soil moisture memory as the correlations for all VIs versus soil moisture at 10 cm depth were strongest for the 5 day lag period. Wide dynamic range VI and normalized difference VI performed better in characterizing soil moisture at the 10 and 25 cm depths under soybean canopies when compared with enhanced VI and CI_red-edge.     

A critical assessment of the Q-W relation and a parametrization relation for computing latent heat fluxes over the Indian Ocean

Ten years (1982–1991) of upper air and ocean surface observations over the Indian Ocean from Sagar Kanya and Monex–79 data have been used to examine the relationship between the precipitable water (W) and surface level humidity (Q) on an instantaneous scale. Our analysis of Q and W over the Indian Ocean shows that Q is correlated with Won an instantaneous scale with r=O·44, which is a statistically significant correlation. A regression between Q and W has been fitted and it has been found that a fifth order polynomial yields a lowest root-mean-square (rms) error of I-4gkg- 1 when compared with observed Q using an independent observation. The validity of earlier derived global relation between Q and W has been examined over the Indian Ocean. It has been found that Liu's global Q-W relation gave a large rms error of 4·1 gkg ^-1 when compared with the observed instantaneous Q values over the Indian Ocean. The usefulness of the above derived Q-W relation and an earlier derived relation between the monthly mean Q and W has been examined for the estimation of latent heat fluxes (LHF) over the Indian Ocean using an independent observation. The LHF estimated from the bulk aerodynamic method using all quantities available from ship observations, called the direct method (M1), has been compared with the LHF computed by using a derived Q-W relation (M2). The rms error between MI versus M2 is found to be 56 Wm^-2. The LHF estimated by Liu's Q -W relation, when compared with MI gave an rms error of 155Wm ^-2, which is suggestive of its unsuitability for the estimation of LHF over the Indian Ocean on an instantaneous basis. The difference between the sea surface humidity (Q,) and surface level humidity (Q) has been parametrized in terms of sea surface temperature (SST) and W, both obtainable from satellite sensors. This relation has then been used to compute LHF (M3) and was compared with MI, where it was found that M1 versus M3 gave an rms error of 58Wm^-2. Thus, this study indicates that methods M2 and M3 are found to be more consistent and accurate in nature, and also suggests that it can be further applied to the LHF estimation using satellite based microwave/IR measurements for Wand SST on an instantaneous basis.     

Regioselectivity in Hydroformylation of Aryl Olefins Using Novel Rhodium Polyether Phosphinite Catalysts

Polyethylene glycol based diphosphinite ligands and their Wilkinson type Rh-polymeric carbonyl complexes were prepared for homogeneous hydroformylation of styrenes. The effect of reaction variables such as temperature, pressure, P/Rh ratio, Substrate/Rh ratio, phosphine and phosphinite ligands on the activity and selectivity performance were discussed in detail. The catalyst showed a high rate of reaction, TON and tunable regioselectivity depending upon reaction conditions as compared to conventional Rh-phosphine based catalysts.