John Leis

Cryo-electron tomography of biological specimens

This paper describes the important considerations in cryo-electron tomography (CET) of biological specimens and identifies the areas where digital signal processing can make a decisive contribution.

An efficient unequal error protection scheme for 3-D video transmission

In this paper, we propose a new unequal error protection (UEP) scheme, called video packet partitioning for three-dimensional (3-D) video transmission. We also propose a new 3-D video transceiver structure that adopts various UEP schemes based on the packet partitioning. The proposed schemes are applied for the modern 3-D video techniques, i.e., multiview video coding (MVC) and color plus depth (VpD). The schemes for MVC and VpD are tested over cooperative multiinput multi-output-orthogonal division multiplexing (MIMOOFDM) systems. For channel adaptation, we propose switching operations between the proposed schemes to achieve a trade-off between the system complexity and performance. Experimental results show that the proposed schemes significantly achieve high video quality at different signal-to-noise ratios (SNRs) in the wireless channel with the lowest possible bandwidth and system complexity compared to the direct transmission schemes.

Quantitative Analysis of Ternary Vapor Mixtures Using a Microcantilever-Based Electronic Nose

The authors report the identification and quantification of the components of a ternary vapor mixture using a microcantilever-based electronic nose. An artificial neural network was used for pattern recognition. Dimethyl methyl phosphonate vapor in ppb concentrations and water and ethanol vapors in ppm concentrations were quantitatively identified either individually or in binary and ternary mixtures at varying concentrations.

Detection of Potentially Explosive Methane Levels Using a Solid-State Infrared Source

Detection of methane gas which may be approaching the concentration limit when explosive ignition could occur is an important industrial problem. Optical methods for gas detection are attractive, and near-infrared (IR) wavelengths are especially suited to the detection of hydrocarbon gases. Unfortunately, temperature-related drift of solid-state IR sources is problematic. A method for stabilizing the response of a near-IR solid-state gas detection system operating at 2350 nm is presented in this paper. The system employs a broadband LED source and a wideband photodetector. Because IR absorption in the gas cell is used as an indirect measure of gas concentration, it is necessary to stabilize the optical source power. We approach this problem by employing a novel two-frequency pulsed excitation method. Stable measurements suitable for detecting the presence of methane gas at a concentration of 50% of the lower explosive limit are experimentally demonstrated. The response of the system is validated against the HITRAN IR spectroscopy database, by incorporating the emitter and detector IR profiles. Good agreement between the derived gas concentration and theoretical predictions based on standard gas absorption models is demonstrated for 2.5% methane in air, which is a critical point for determining the presence of potentially explosive mixtures.

Face detection based on skin color modeling and modified Hausdorff distance

This paper presents a new face detection approach which is capable of detecting human faces from complex backgrounds. A new skin color modeling process is applied to the face segmentation process. Image enhancement is then used to improve the features of face candidates before feeding to the face object classifier which is based on a modified Hausdorff distance. The overall performance of the face detection system is evaluated and achieved a success rate of 87.5 %.

Two novel lossless algorithms to exploit index redundancy in VQ speech compression

We address the problem of speech compression at very low rates, with the short-term spectrum compressed to less than 20 bits per frame. Current techniques apply structured vector quantization (VQ) to the short-term synthesis filter coefficients to achieve rates of the order of 24 to 26 bits per frame. We show that temporal correlations in the VQ index stream can be introduced by dynamic codebook ordering, and that these correlations can be exploited by lossless coding approaches to reduce the number of bits per frame of the VQ scheme. The use of lossless coding ensures that no additional distortion is introduced, unlike other interframe techniques. We then detail two constructive algorithms which are able to exploit this redundancy. The first method is a delayed-decision approach, which dynamically adapts the VQ codebook to allow for efficient entropy coding of the index stream. The second is based on a vector sub-codebook approach, and does not incur any additional delay. Experimental results are presented for both methods to validate the approach.

Soft Incremental Redundancy for Distributed Turbo Product Codes

In this paper, we propose a Distributed Turbo Product Code (DTPC) with soft information relaying over cooperative network using block Extended Bose Chaudhuri Hochquenghem (EBCH) codes as component codes. The source broadcasts extended EBCH coded frames to the destination and to a preassigned relay. After soft-decoding the received sequences and obtaining the Log-Likelihood Ratio (LLR) values, the relay constructs a product code by arranging the decoded bit sequences in rows and re-encoding them along the columns using a novel soft block encoding technique to obtain soft parity bits with different reliabilities that can be used as soft Incremental Redundancy (IR) for sources data which is forwarded to the destination. A modified turbo product decoder to cope with the data received over different channels and thus having different reliabilities is used at the destination. We compared the simulation results in Additive White Gaussian Noise (AWGN) channel using network scenarios with our previous work for Decode and Forward (DF) DTPC and with non-cooperative case. Results show O.5dB gain improvement over the non-cooperative Turbo Product Codes (TPC) at Bit Error Rate (BER) 10-4. In addition, the BER performance is less affected by the decoding errors at the relay.

Identification and quantification of components in ternary vapor mixtures using a microelectromechanical-system-based electronic nose

We report the experimental details on the successful application of the electronic nose approach to identify and quantify components in ternary vapor mixtures. Preliminary results have recently been presented [L. A. Pinnaduwage et al., Appl. Phys. Lett. 91, 044105 (2007)]. Our microelectromechanical-system-based electronic nose is composed of a microcantilever sensor array with seven individual sensors used for vapor detection and an artificial neural network for pattern recognition. A set of custom vapor generators generated reproducible vapor mixtures in different compositions for training and testing of the neural network. The sensor array was selected to be capable of generating different response patterns to mixtures with different component proportions. Therefore, once the electronic nose was trained by using the response patterns to various compositions of the mixture, it was able to predict the composition of “unknown” mixtures. We have studied two vapor systems: one included the nerve gas simulan...

Estimating gas concentration using a microcantilever-based electronic nose

This paper investigates the determination of the concentration of a chemical vapor as a function of several nonspecific microcantilever array sensors. The nerve agent dimethyl methyl phosphonate (DMMP) in parts-per-billion concentrations in binary and ternary mixtures is able to be resolved when present in a mixture containing parts-per-million concentrations of water and ethanol. The goal is to not only detect the presence of DMMP, but additionally to map the nonspecific output of the sensor array onto a concentration scale. We investigate both linear and nonlinear approaches - the linear approach uses a separate least-squares model for each component, and a nonlinear approach which estimates the component concentrations in parallel. Application of both models to experimental data indicate that both models are able to produce bounded estimates of concentration, but that the outlier performance favors the linear model. The linear model is better suited to portable handheld analyzer, where processing and memory resources are constrained.

A Temperature Compensation Technique for Near-Infrared Methane Gas Threshold Detection

Methane is the primary constituent of natural gas and is used in many industrial processes. Detection of the presence of methane is important, especially before it reaches explosive concentrations. Earlier sensor types are based on catalytic adsorption (which may limit the sensor lifetime) at elevated temperatures (requiring additional power and possibly compromising safety). Recently, optical sensors based on infrared (IR) absorption by hydrocarbon molecules have become an important research focus. One unsolved problem when using solid-state IR sources is that of optical flux variation due to heating. This paper introduces a novel power compensation approach for IR LEDs employed in gas detection, which accounts for variations in the optical flux of the source. The contribution of this paper is threefold. First, we propose the idea of compensating for emitted IR flux by means of pulsed junction voltage measurement and explain why this is effective. Second, we introduce a compensation algorithm which shows how to take advantage of this concept. Third, experimental results demonstrate that the discrimination algorithm is at least six times better than the uncompensated measurements. The convergence of the algorithm results in a stabilized measurement in less than 1 s.