RD-TDMA: A Randomized and Distributed TDMA Scheduling for Correlated Contention in WSNs

In wireless sensor networks (WSNs), contention occurs when two or more nodes in a proximity simultaneously try to access the channel. The contention causes collisions, which are very likely to occur when traffic is correlated. The excessive collision not only affects the reliability and the QoS of the application, but also the lifetime of the network. It is well-known that random access mechanisms do not efficiently handle correlated-contention, and therefore, suffer from high collision rate. Most of the existing TDMA scheduling techniques try to find an optimal or a sub-optimal schedule. Usually, the situation of correlated-contention persists only for a short duration, and therefore, it is not worthwhile to take a long time to generate an optimal or a sub-optimal schedule. We propose a randomized distributed TDMA scheduling (RD-TDMA) algorithm to quickly generate a feasible schedule (not necessarily optimal) to handle correlated-contention in WSNs. In RD-TDMA, a node in the network negotiates a slot with its neighbors using the message exchange mechanism. The proposed protocol has been simulated using the Castalia simulator to evaluate its runtime performance. Simulation results show that the RD-TDMA algorithm considerably reduces the time required to schedule.

A survey on compressed domain video analysis techniques

Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.

Theoretical and Experimental Evaluation of Pulsating Torque Produced by Induction Motor Drives Controlled With Advanced Bus-Clamping Pulsewidth Modulation

This paper investigates possible reduction of pulsating torque in open-loop and vector-controlled induction motor drives through deployment of certain advanced bus-clamping pulsewidth modulation (ABCPWM) method. Toward this goal, a simple and machine-independent method is proposed to analyze the torque harmonic spectrum of a voltage source inverter fed induction motor, operated with any real-time pulsewidth modulation (PWM) method. The analytically evaluated torque harmonic spectra, pertaining to conventional space vector PWM (CSVPWM), bus-clamping PWM (BCPWM), and ABCPWM, are validated through simulation and experimental results. Theoretical and experimental studies bring out the superiority of the ABCPWM in terms of torque harmonics over CSVPWM and BCPWM. The magnitude of the dominant torque harmonic with the ABCPWM scheme is shown to be significantly lower than that with CSVPWM, over a wide range of speed. The rms torque ripple (i.e., total rms value of all harmonic torques) is lower with ABCPWM than with BCPWM over the entire range of speed.

Investigation Into Harmful Patterns Over Multitrack Shingled Magnetic Detection Using the Voronoi Model

Two-dimensional magnetic recording 2-D (TDMR) is a promising technology for next generation magnetic storage systems based on a systems-level framework involving sophisticated signal processing at the core. The TDMR channel suffers from severe jitter noise along with electronic noise that needs to be mitigated during signal detection and recovery. Recently, we developed noise prediction-based techniques coupled with advanced signal detectors to work with these systems. However, it is important to understand the role of harmful patterns that can be avoided during the encoding process. In this paper, we investigate the Voronoi-based media model to study the harmful patterns over multitrack shingled recording systems. Through realistic quasi-micromagnetic simulation studies, we identify 2-D data patterns that contribute to high media noise. We look into the generic Voronoi model and present our analysis on multitrack detection with constrained coded data. We show that the 2-D constraints imposed on input patterns result in an order of magnitude improvement in the bit-error rate for the TDMR systems. The use of constrained codes can reduce the complexity of 2-D intersymbol interference (ISI) signal detection, since the lesser 2-D ISI span can be accommodated at the cost of a nominal code rate loss. However, a system must be designed carefully so that the rate loss incurred by a 2-D constraint does not offset the detector performance gain due to more distinguishable readback signals.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

On the Geometrically Dependent Quasi-Saturation and g(m) Reduction in Advanced DeMOS Transistors

This paper reveals an early quasi-saturation (QS) effect attributed to the geometrical parameters in shallow trench isolation-type drain-extended MOS (STI-DeMOS) transistors in advanced CMOS technologies. The quasi-saturation effect leads to serious g(m) reduction in STI-DeMOS. This paper investigates the nonlinear resistive behavior of the drain-extended region and its impact on the particular behavior of the STI-DeMOS transistor. In difference to vertical DMOS or lateral DMOS structures, STI-DeMOS exhibits three distinct regions of the drain extension. A complete understanding of the physics in these regions and their impact on the QS behavior are developed in this paper. An optimization strategy is shown for an improved g(m) device in a state-of-the-art 28-nm CMOS technology node.

Nano-hardness Techniques and Its Applications in Mechanical Property Measurements for Surface Engineering

结合纳米硬度技术测量各类薄膜和块体材料表层的纳米压痕硬度、弹性模量、断裂韧性、膜厚、微结构的弯曲变形,采用纳米划痕硬度技术测量各类薄膜和块体材料的粗糙度、临界附着力、摩擦系数、划痕横剖面.纳米硬度计是检测材料表层微米乃至几十纳米力学性能的先进仪器,可广泛应用于表面工程中的质量检测.

Development of the 2003 CU-HTK conversational telephone speech transcription system

This paper describes the development of the 2003 CU-HTK large vocabulary speech recognition system for Conversational Telephone Speech (CTS). The system was designed based on a multi-pass, multi-branch structure where the output of all branches is combined using system combination. A number of advanced modelling techniques such as Speaker Adaptive Training, Heteroscedastic Linear Discriminant Analysis, Minimum Phone Error estimation and specially constructed Single Pronunciation dictionaries were employed. The effectiveness of each of these techniques and their potential contribution to the result of system combination was evaluated in the framework of a state-of-the-art LVCSR system with sophisticated adaptation. The final 2003 CU-HTK CTS system constructed from some of these models is described and its performance on the DARPA/NIST 2003 Rich Transcription (RT-03) evaluation test set is discussed.