Servo controller design using neural networks

The dynamics of a physical plant may be difficult to express as concise mathematical equations. In practice there exist uncertainties that cannot be modeled with the system equations. Hence, robustness against system uncertainties is essential in a control system design. In this article, multilayered neural networks (MNNs) are used to compensate for model uncertainties of a dynamical system. Neural network models are used along with a classical linear servo controller derived from the linear state space equations. These models are trained so that system uncertainties are compensated. The design of a servo system indicates the enhanced performance of the neural-network-based servo controller as compared to the classical servo controller.     

A Built-in-Self-Test Scheme for Segmented and Binary Weighted DACs

This paper describes a new Built-In-Self-Test(BIST) scheme for estimation of static non-linearity errors in segmented and binary weighted digital to analog converters (DACs). The BIST scheme comprises of a hierarchy of tests including tests for non-monotonicity, checks to detect if the DNL/INL errors exceed ±0.5 LSB and actual estimation of the DNL/INL. The BIST scheme has been experimentally verified on 10-bit segmented current steering DAC. The DAC, along with the additional circuits required for testing, was designed and fabricated using a 0.35 m process. Both simulation and experimental results are included in this paper. Errors estimated using the BIST scheme match well with measurements done on the fabricated device.     

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.     

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.     

Development of new encryption system using Brownian motion based diffusion

Multimedia Tools and Applications - A new cryptographic model is proposed incorporating intertwining logistic map based confusion process and two dimensional Brownian Motion based diffusion...     

Optimizing functionally graded nickel–zirconia coating profiles for thermal stress relaxation

The investigations on optimization of composite composition of nickel–zirconia for the functionally graded layered thermal barrier coating for the lowest but uniform stress field under thermal loading is presented. The procedure for obtaining temperature- and composition-dependent thermal and mechanical properties of various coating compositions is discussed. These material parameters were used in thermo-mechanical finite element stress analyses of a nickel substrate with the coating. The results showed that the Von-Mises stresses in the substrate and the interfaces were the lowest with the coating profile that followed a concave power law relationship with the index n ≈ 2.65.     

A study on dynamic rheological characterisation of electron beam crosslinked high vinyl styrene butadiene styrene block copolymer

Crosslinking of elastomers using electron beam radiation has several advantages over conventional method. It is accomplished much faster, in a more environmental friendly approach and in a much simpler manner. When fast moving electrons that are generated from electron accelerators are targeted on a polymer matrix, they primarily crosslink the polymer. However, in the process, some chain scission may also occur. In this work, a high vinyl (~50%) styrene–butadiene–styrene (S–B–S) block copolymer was used as the base polymer. Radiation doses were varied from 25 to 300 kGy. A detailed investigation was made to understand the effect of electron beam radiation on the rheological properties such as storage modulus, loss modulus, storage viscosity and complex viscosity of the block copolymer under strain and frequency sweeps performed in a Rubber Process Analyzer (RPA). Recyclability of the crosslinked S–B–S polymer was also explored by RPA and mechanical studies.