A threshold insensitive method for locating the forest canopy top with waveform lidar

Lidars have the unique ability to make direct, physical measurements of forest height and vertical structure in much denser canopies than is possible with passive optical or short wavelength radars. However the literature reports a consistent underestimate of tree height when using physically based methods, necessitating empirical corrections. This bias is a result of overestimating the range to the canopy top due to background noise and failing to correctly identify the ground.This paper introduces a method, referred to as “noise tracking”, to avoid biases when determining the range to the canopy top. Simulated waveforms, created with Monte-Carlo ray tracing over geometrically explicit forest models, are used to test noise tracking against simple thresholding over a range of forest and system characteristics. It was found that noise tracking almost completely removed the bias in all situations except for very high noise levels and very low (< 10%) canopy covers. In all cases noise tracking gave lower errors than simple thresholding and had a lower sensitivity to the initial noise threshold.Finite laser pulses spread out the measured signal, potentially overriding the benefit of noise tracking. In the past laser pulse length has been corrected by adding half that length to the signal start range. This investigation suggests that this is not always appropriate for simple thresholding and that the results for noise tracking were more directly related to pulse length than for simple thresholding. That this effect has not been commented on before may be due to the possible confounding impacts of instrument and survey characteristics inherent in field data. This method should help improve the accuracy of waveform lidar measurements of forests, whether using airborne or spaceborne instruments.     

Rule chaining in fuzzy expert systems

A fuzzy expert system must do rule chaining differently than a nonfuzzy expert system. In particular, any rule that can fire with a particular linguistic variable in its consequent must fire before any rule whose antecedent conditions depend upon the resultant fuzzy set value of the consequent linguistic variable is allowed to fire. The dependent rules would be considered in a chain with the fuzzy rules which generate or assert the needed fuzzy linguistic variable. A recent paper by J. Pan et al. (1998) points out that a version of the FuzzyCLIPS expert system shell does not operate with chained fuzzy rules as one would expect. They introduce FuzzyShell which is described as the only known shell to have the expected fuzzy rule chaining performance. We show several approaches to obtaining the desired behavior in FuzzyCLIPS. Further, a potential pitfall with the FuzzyShell approach to dealing with chaining is pointed out     

Issues in representation of molecular structure the development of molecular connectivity.

Significant issues in the representation of molecular structure and the development of the molecular connectivity paradigm are presented. In the molecular connectivity paradigm, molecular structure is represented directly. Kier and Hall developed the method by creating ways to encode electronic information based on the paradigm developed from the Randi? branching index. The simple and valence delta values were created to encode atomic and valence-state electronic information through counts of sigma, pi, and lone pair electrons. A family of indices was created to provide a wide range of structure information. The key aspects of the development are presented and discussed in such a way as to reveal, at least in part, the imaginative thinking involved in the process. Possible future roles for molecular connectivity chi indices are discussed.     

Generating Test Sets from Non-Deterministic Stream X-Machines

X-machines were proposed by Holcombe as a possible specification language and since then a number of further investigations have demonstrated that the model is intuitive and easy to use as well as general enough to cater for a wide range of applications. In particular (generalised) stream X-machines have been found to be extremely useful as a specification method and most of the theory developed so far has concentrated on this particular class of X-machines. Furthermore, a method for testing systems specified by stream X-machines exists and is proved to detect all faults of the implementation provided that the system meets certain initial requirements. However, this method can only be used to generate test sequences from deterministic X-machine specifications. In this paper we present the theoretical basis for a method for generating test sets from non-deterministic generalised stream X-machines. Received November 1999 / Accepted in revised form September 2000     

Micromachined Accelerometers With Optical Interferometric Read-Out and Integrated Electrostatic Actuation

A micromachined accelerometer device structure with diffraction-based optical detection and integrated electrostatic actuation is introduced. The sensor consists of a bulk silicon proof mass electrode that moves vertically with respect to a rigid diffraction grating backplate electrode to provide interferometric detection resolution of the proof-mass displacement when illuminated with coherent light. The sensor architecture includes a monolithically integrated electrostatic actuation port that enables the application of precisely controlled broadband forces to the proof mass while the displacement is simultaneously and independently measured optically. This enables several useful features such as dynamic self-characterization and a variety of force-feedback modalities, including alteration of device dynamics in situ. These features are experimentally demonstrated with sensors that have been optoelectronically integrated into sub-cubic-millimeter volumes using an entirely surface-normal, rigid, and robust embodiment incorporating vertical cavity surface emitting lasers and integrated photodetector arrays. In addition to small form factor and high acceleration resolution, the ability to self-characterize and alter device dynamics in situ may be advantageous. This allows periodic calibration and in situ matching of sensor dynamics among an array of accelerometers or seismometers configured in a network.     

Performance evaluation for DRED discrete-time queueing network analytical model

Due to the rapid development in computer networks, congestion becomes a critical issue. Congestion usually occurs when the connection demands on network resources, i.e. buffer spaces, exceed the available ones. We propose in this paper a new discrete-time queueing network analytical model based on dynamic random early drop (DRED) algorithm to control the congestion in early stages. We apply our analytical model on two-queue nodes queueing network. Furthermore, we compare between the proposed analytical model and three known active queue management (AQM) algorithms, including DRED, random early detection (RED) and adaptive RED, in order to figure out which of them offers better quality of service (QoS). We also experimentally compare the queue nodes of the proposed analytical model and the three AQM methods in terms of different performance measures, including, average queue length, average queueing delay, throughput, packet loss probability, etc., aiming to determine the queue node that offers better performance.     

Application of autoregressive spectral analysis to cepstral estimation of mean scatterer spacing

The problem of estimation of mean scatterer spacing in an object containing regularly spaced structures is addressed. An autoregressive (AR) spectral estimation method is compared with a conventional fast Fourier transform (FFT)-based approach for this task. Regularly spaced structures produce a periodicity in the power spectrum of ultrasonic backscatter. This periodicity is manifested as a peak in the cepstrum. A phantom was constructed for comparison of the two methods. It contained regularly spaced nylon filaments. It also contained randomly positioned glass spheres that produced incoherent backscatter. In an experiment in which this target was interrogated using broadband ultrasound, the AR spectral estimate offered considerable improvement over the FFT when the analysis gate length was on the order of the structural dimension. Advantages included improved resolution, reduction in bias and variance of scatterer spacing estimates, and greater resistance to ringing artifacts. Data were also acquired from human liver in vivo. AR spectral estimates on human data exhibited a decreased dependence on gate length. These results offer promise for enhanced spatial resolution and accuracy in ultrasonic tissue characterization and nondestructive evaluation of materials.     

Christopher Strachey: Recollections of His Influence

My early research was inspired by the mathematical semantics of Scott and Strachey. Two such topics, recounted in this paper, were the fixed-point analysis of pointer loops and the expressibility of a style of functional programming introduced by Barron and Strachey.     

Three-dimensional moment invariants

Recognition of three-dimensional objects independent of size, position, and orientation is an important and difficult problem of scene analysis. The use of three-dimensional moment invariants is proposed as a solution. The generalization of the results of two-dimensional moment invariants which had linked two-dimensional moments to binary quantics is done by linking three-dimensional moments to ternary quantics. The existence and number of nth order moments in two and three dimensions is explored. Algebraic invariants of several ternary forms under different orthogonal transformations are derived by using the invariant property of coefficients of ternary forms. The result is a set of three-dimensional moment invariants which are invariant under size, orientation, and position change. This property is highly significant in compressing the data which are needed in three-dimensional object recognition. Empirical examples are also given.