Adaptive Chip-Level Channel Estimation for IMT-DS System: DL and UL

In this paper, chip-level adaptive channel estimation has been explored by using LMS algorithm for wideband CDMA channel estimation. The expression for the optimum step-size is modified for fading channel estimation problem. In addition, a new method is proposed to obtain channel estimates with known pilot symbols which is found to give better results than other methods. For slow fading channels, like pedestrian channel, LMS estimator with no update mode is found to give satisfactory results. For fast fading channels, like vehicular channel, a common decision directed technique of channel estimation is modified to be used at chip-level in the downlink (DL). A novel despreader-respreader based channel estimator has been proposed to obtain uplink channel estimates at chip level which resolves the deficiencies of conventional methods. The performance of Rake receiver with proposed channel estimation schemes for IMT-DS system – a 3G mobile communication standard – is evaluated in terms of BER. S. Faisal A. Shah received the B.S. degree from NED University of Engineering and Technology, Karachi, Pakistan, in 1998 and the M.S. degree from King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 2001, both in Electrical Engineering. From 2001 to 2004, he was a Lecturer in Electrical & Electronics Engineering Department, University of Sharjah, UAE. In September 2004, he joined the Electrical and Computer Engineering Department of University of Minnesota, USA, as a research assistant where he is currently pursuing the Ph.D. degree in Electrical Engineering. His research interests include ultra-wideband communication systems, adaptive signal processing and its application to wireless communication systems. Asrar U.H. Sheikh graduated from the University of Engineering and Technology, Lahore, Pakistan with first class honours and received his M.Sc. and Ph.D. degrees from the University of Birmingham, England, in 1966 and 1969 respectively. After completing teaching assignments in several countries, he returned to Birmingham as a Research Fellow in 1975. He worked at Carleton University from 1981 to 1997, first as Associate Professor and later as a Professor and Associate Chairman for Graduate Studies. He was the Founder Director of PCS Research Laboratory at Carleton University. Before taking position of Bugshan/Bell Lab Chair in Telecommunications at King Fahd University of Petroleum and Minerals in April 2000, he was a Professor and Associate Head of the Department of Electronic and Information Engineering at Hong Kong Polytechnic University, where he was founding director of Wireless Information Systems Research (WISR) Centre. At KFUPM he established Telecommunications Research Laboratory. Professor Sheikh is the author of a recently published book, Wireless Communications - Theory & Techniques published by Kluwer Academic Publishers, Orwell, Mass., USA. He has published over 230 papers in international journals and conference proceedings. He also authored or co-authored 30 technical reports. Dr. Sheikh is a co-recipient of Paul Adorian Premium from IERE (London) for his work on impulsive noise characterization. He was awarded teaching achievement awards in 1984 and 1986, and Research Achievement Award in 1994, all by Carleton University. Dr. Sheikh is actively involved in several international conferences mainly as a member of Technical Program Committees. He has organized and chaired many technical sessions at several international conferences. He Chaired the Technical Program of VTC'98. He is an editor of IEEE Transaction on Wireless Communications, a Technical Associate Editor of IEEE Communication Magazine. He is on the Editorial Board of Wireless Personal Communications, and Wireless Communications and Mobile Computing. He was a co-guest editor of the Special Issue of WPC on Interference. Dr. Sheikh is also on the reviewer panels of many IEEE and IEE Transactions and Journals. Dr. Sheikh has been consultant to many private companies and government agencies. His current interests are in signal processing in communications, mitigation of interference, spread spectrum and 3G and beyond systems. His other interests include helping developing countries in education and research. He had assignments under UNDP's sustained Development Program. He is a Fellow of the IEEE and a Fellow of the IEE. Dr. Sheikh is listed in Marquis Who's Whos in the world and Who's Who in Science and Engineering.     

THRESHOLD STRESS INTENSITY BEHAVIOUR OF CRACKED STEEL STRUCTURAL COMPONENTS

Abstract— The effects of stress variables on the fatigue design of steel structural components (SAE 1010 steel) in the threshold region are investigated. The threshold and the closure threshold stress intensity ranges both decreased linearly as the stress ratio is increased. The threshold and opening threshold stress intensities also decreased linearly as the magnitude of compressive peak stress is increased. Crack opening stress measurements using a mechanical extensometer showed that the crack is not fully closed throughout the stress cycle at the threshold level. The crack opening stress is found to be independent of the crack length up to a certain crack length depending on the loading conditions. It is also found that the threshold stress intensity consists of two components: opening or closure stress intensity required to overcome crack closure, and intrinsic stress intensity range required to grow the crack. Linear relationships are obtained for the intrinsic stress intensity range as a function of stress ratio or compressive peak stress.     

On the interaction between knowledge and social commitments in multi-agent systems

Both knowledge and social commitments have received considerable attention in Multi-Agent Systems (MASs), specially for multi-agent communication. Plenty of work has been carried out to define their semantics. However, the relationship between social commitments and knowledge has not been investigated yet. In this paper, we aim to explore such a relationship from the semantics and model checking perspectives with respect to CTLK logic (an extension of CTL logic with modality for reasoning about knowledge) and CTLC logic (an extension of CTL with modalities for reasoning about commitments and their fulfillments). To analyze this logical relationship, we simply combine the two logics in one new logic named CTLKC. The purpose of such a combination is not to advocate a new logic, but only to express and figure out some reasoning postulates merging both knowledge and commitments as they are currently defined in the literature. By so doing, we identify some paradoxes in the new logic showing that simply combining current versions of commitment and knowledge logics results in a logical language that violates some fundamental intuitions. Consequently, we propose CTLKC⁺, a new logic that fixes the identified paradoxes and allows us to reason about social commitments and knowledge simultaneously in a consistent manner. Furthermore, we address the problem of model checking CTLKC⁺ by reducing it to the problem of model checking GCTL^?, a generalized version of CTL^? with action formulae. By doing so, we directly benefit from CWB-NC, the model checker of GCTL^?. Using this reduction, we also prove that the computational complexity of model checking CTLKC⁺ is still PSPACE-complete for concurrent programs as the complexity of model checking CTLK and CTLC separately.     

Synthesis, characterization and magnetic properties of polyaniline/γ-Fe2O3 composites

Conducting polyaniline/γ-Fe₂O₃ (PANI/FE) composites have been synthesized using an in situ deposition technique by placing fine-graded γ-Fe₂O₃ in a polymerization mixture of aniline. The composites are characterized by using scanning electron microscopy (SEM), X-ray diffraction (XRD) and infrared (IR) spectroscopy. The electrical properties such as d.c. and a.c. conductivities are studied by sandwitching the pellets of these composites between the silver electrodes. It is observed that the conductivity increases up to a composition of 20 wt.% of γ-Fe₂O₃ in polyaniline and decreases thereafter. The initial increase in conductivity is attributed to the extended chain length of polyaniline, where polarons possess sufficient energy to hop between favourable sites. Beyond 20 wt.% of γ-Fe₂O₃ in polyaniline, the blocking of charge carrier hop occurs, reducing conductivity values. The magnetic properties such as hysteresis characteristics and normalized a.c. susceptibility are also measured, which show a strong dependence on content of γ-Fe₂O₃ in polyaniline. Because of superparamagnetic behaviour of these composites, they may find extensive technological applications, especially for absorbing and shielding applications in microwave frequencies.     

TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 2: Surface dynamics and basin analysis

We present the analytical capability of TecDEM, a MATLAB toolbox used in conjunction with Global DEMs for the extraction of tectonic geomorphologic information. TecDEM includes a suite of algorithms to analyze topography, extracted drainage networks and sub-basins. The aim of part 2 of this paper series is the generation of morphometric maps for surface dynamics and basin analysis. TecDEM therefore allows the extraction of parameters such as isobase, incision, drainage density and surface roughness maps. We also provide tools for basin asymmetry and hypsometric analysis. These are efficient graphical user interfaces (GUIs) for mapping drainage deviation from basin mid-line and basin hypsometry. A morphotectonic interpretation of the Kaghan Valley (Northern Pakistan) is performed with TecDEM and the findings indicate a high correlation between surface dynamics and basin analysis parameters with neotectonic features in the study area.     

TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 1: Drainage network preprocessing and stream profile analysis

We present TecDEM, a software shell implemented in MATLAB that applies tectonic geomorphologic tasks to digital elevation models (DEMs). The first part of this paper series describes drainage partitioning schemes and stream profile analysis. The graphical user interface of TecDEM provides several options: determining flow directions, stream vectorization, watershed delineation, Strahler order labeling, stream profile generation, knickpoints selection, Concavity, Steepness and Hack indices calculations. The knickpoints along selected streams as well as stream profile analysis, and Hack index per stream profile are computed using a semi-automatic method. TecDEM was used to extract and investigate the stream profiles in the Kaghan Valley (Northern Pakistan). Our interpretations of the TecDEM results correlate well with previous tectonic evolution models for this region. TecDEM is designed to assist geoscientists in applying complex tectonic geomorphology tasks to global DEM data.     

View-invariant motion trajectory-based activity classification and recognition

Motion trajectories provide rich spatio-temporal information about an object's activity. The trajectory information can be obtained using a tracking algorithm on data streams available from a range of devices including motion sensors, video cameras, haptic devices, etc. Developing view-invariant activity recognition algorithms based on this high dimensional cue is an extremely challenging task. This paper presents efficient activity recognition algorithms using novel view-invariant representation of trajectories. Towards this end, we derive two Affine-invariant representations for motion trajectories based on curvature scale space (CSS) and centroid distance function (CDF). The properties of these schemes facilitate the design of efficient recognition algorithms based on hidden Markov models (HMMs). In the CSS-based representation, maxima of curvature zero crossings at increasing levels of smoothness are extracted to mark the location and extent of concavities in the curvature. The sequences of these CSS maxima are then modeled by continuous density (HMMs). For the case of CDF, we first segment the trajectory into subtrajectories using CDF-based representation. These subtrajectories are then represented by their Principal Component Analysis (PCA) coefficients. The sequences of these PCA coefficients from subtrajectories are then modeled by continuous density hidden Markov models (HMMs). Different classes of object motions are modeled by one Continuous HMM per class where state PDFs are represented by GMMs. Experiments using a database of around 1750 complex trajectories (obtained from UCI-KDD data archives) subdivided into five different classes are reported.     

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in removing almost exclusively the undesirable discrimination, while leaving the explainable differences unchanged, allowing for differences in decisions as long as they are explainable.     

Crown Structures for Vertex Cover Kernelization

Crown structures in a graph are defined and shown to be useful in kernelization algorithms for the classic vertex cover problem. Two vertex cover kernelization methods are discussed. One, based on linear programming, has been in prior use and is known to produce predictable results, although it was not previously associated with crowns. The second, based on crown structures, is newer and much faster, but produces somewhat variable results. These two methods are studied and compared both theoretically and experimentally with each other and with older, more primitive kernelization algorithms. Properties of crowns and methods for identifying them are discussed. Logical connections between linear programming and crown reductions are established. It is shown that the problem of finding an induced crown-free subgraph, and the problem of finding a crown of maximum size in an arbitrary graph, are solvable in polynomial time.