Empirical Innovation of Computational Dual‐Loop Models for Identifying Vehicle Classifications against Varied Traffic Conditions

Clarifying traffic flow phases is a primary requisite for applying length‐based vehicle classifications with dual‐loop data under various traffic conditions. One challenge lies in identifying traffic phases using variables that could be directly calculated from the dual‐loop data. This article presents an innovative approach and associated algorithm for identifying traffic phases through a hybrid method that incorporates level of service method and K‐means clustering method. The “phase representative variables” are identified to represent traffic characteristics in the traffic flow phase identification algorithm. The traffic factors influencing the vehicle classification accuracy under non‐free traffic conditions are successfully identified using video‐based vehicular trajectory data, and the innovative length‐based vehicle classification models are then developed. The result of the concept‐of‐evidence test with use of sample data indicates that compared with the existing model, the accuracy of the estimated vehicle lengths is increased from 42% to 92% under synchronized and stop‐and‐go conditions. The results also foster a better understanding of the traffic stream characteristics and associated theories to lay out a good foundation for further development of relevant microscopic simulation models with other sensing traffic data sources.     

Is there more to complicated grief than depression and posttraumatic stress disorder? A test of incremental validity.

There is growing interest in complicated grief reactions as a possible new diagnostic category for inclusion in the Diagnostic and Statistical Manual of Mental Disorders. However, no research has yet shown that complicated grief has incremental validity (i.e., predicts unique variance in functioning). The authors addressed this issue in 2 studies by comparing grief, depression, and posttraumatic stress disorder (PTSD) symptoms with different measures of functioning (interviewer ratings, friend ratings, self-report, and autonomic arousal). The 1st study (N = 73) used longitudinal data collected at 4 and 18 months postloss, and the 2nd study (N = 447) used cross-sectional data collected 2.5-3.5 years postloss. With depression and PTSD controlled, grief emerged as a unique predictor of functioning, both cross-sectionally and prospectively. The findings provide convergent support for the incremental validity of complicated grief as an independent marker of bereavement-related psychopathology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Adapted waveform “de-noising” for medical signals andimages

Our goal is to describe tools for adapting methods of analysis to various tasks occurring in harmonic and numerical analysis and signal processing. By choosing an orthonormal basis, in which space and frequency are suitably localized, one can achieve both understanding of structure and efficiency in computation. In fact, the search for computational efficiency is intimately related to efficiency in representation (i.e., compression) and to pattern extraction, or structural understanding     

An object detection strategy for uncooled infrared imagery

Abstract

An overall strategy for the very difficult problem of object detection using uncooled infrared (UCIR) sensors is discussed. The UCIR sensors are based on micro-bolometer technology and thus differ significantly from cooled infrared sensors that employ photon-counting detectors. As such, UCIR imagery tends to be very low contrast, since the sensor operates over a broad spectral band; and blurry, because of the long integration times. Ideally, the UCIR imagery would be preprocessed using an appropriate image reconstruction/restoration algorithm. If the sources of image degradation are understood and lend themselves to accurate modelling, the image reconstruction can be solved as an inverse problem. Most often this is not the case and the problem is solved using minimization approaches, such as blind deconvolution. Because image reconstruction/restoration approaches tend to be very throughput intensive, they are rarely performed in a tactical environment. More typically, a detection algorithm is applied directly to the UCIR imagery. In this paper, Local Singular Value Decomposition (LSVD) is evaluated for anomaly detection. LSVD uses local statistics to identify anomalous regions and is very good at identifying local texture differences; it appears to work quite well on UCIR imagery. Target detection results are presented for a simulated data set.     

Local cosine transform — a method for the reduction of the blocking effect in JPEG

This paper presents the local cosine transform (LCT) as a new method for the reduction and smoothing of the blocking effect that appears at low bit rates in image coding algorithms based on the discrete cosine transform (DCT). In particular, the blocking effect appears in the JPEG baseline sequential algorithm.Two types of LCT were developed: LCT-IV is based on the DCT type IV, and LCT-II is based on DCT type II, which is known as the standard DCT. At the encoder side the image is first divided into small blocks of pixels. Both types of LCT have basis functions that overlap adjacent blocks. Prior to the DCT coding algorithm a preprocessing phase in which the image is multiplied by smooth cutoff functions (or bells) that overlap adjacent blocks is applied. This is implemented by folding the overlapping parts of the bells back into the original blocks, and thus it permits the DCT algorithm to operate on the resulting blocks. At the decoder side the inverse LCT is performed by unfolding the samples back to produce the overlapped bells. The purpose of the multiplication by the bell is to reduce the gaps and inaccuracies that may be introduced by the encoder during the quantization step.LCT-IV and LCT-II were applied on images as a preprocessing phase followed by the JPEG baseline sequential compression algorithm. For LCT-IV, the DCT type IV replaced the standard DCT as the kernel of the transform coding. In both cases, for the same low bit rates the blocking effect was smoothed and reduced while the image quality in terms of mean-square error became better. Subjective tests performed on a group of observers also confirm these results. Thus the LCT can be added as an optional step for improving the quality of existing DCT (JPEG) encoders. Advantages over other methods that attempt to reduce the blocking effect due to quantization are also described.     

Multilayered image representation: application to image compression

The main contribution of this work is a new paradigm for image representation and image compression. We describe a new multilayered representation technique for images. An image is parsed into a superposition of coherent layers: piecewise smooth regions layer, textures layer, etc. The multilayered decomposition algorithm consists in a cascade of compressions applied successively to the image itself and to the residuals that resulted from the previous compressions. During each iteration of the algorithm, we code the residual part in a lossy way: we only retain the most significant structures of the residual part, which results in a sparse representation. Each layer is encoded independently with a different transform, or basis, at a different bitrate, and the combination of the compressed layers can always be reconstructed in a meaningful way. The strength of the multilayer approach comes from the fact that different sets of basis functions complement each others: some of the basis functions will give reasonable account of the large trend of the data, while others will catch the local transients, or the oscillatory patterns. This multilayered representation has a lot of beautiful applications in image understanding, and image and video coding. We have implemented the algorithm and we have studied its capabilities.     

Data fusion and multicue data matching by diffusion maps

Data fusion and multicue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the recently introduced diffusion framework to address these tasks. Our contribution is three-fold: first, we present the Laplace-Beltrami approach for computing density invariant embeddings which are essential for integrating different sources of data. Second, we describe a refinement of the Nystrom extension algorithm called "geometric harmonics." We also explain how to use this tool for data assimilation. Finally, we introduce a multicue data matching scheme based on nonlinear spectral graphs alignment. The effectiveness of the presented schemes is validated by applying it to the problems of lipreading and image sequence alignment     

Adaptive wavelet packet basis selection for zerotree image coding

Image coding methods based on adaptive wavelet transforms and those employing zerotree quantization have been shown to be successful. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. A fast basis selection algorithm is developed; it uses a Markov chain based cost estimate of encoding the image using this structure. As a result, our adaptive wavelet zerotree image coder has a relatively low computational complexity, performs comparably to state-of-the-art image coders, and is capable of progressively encoding images.     

Does repressive coping promote resilience? Affective-autonomic response discrepancy during bereavement.

Traditional theories of coping emphasize the value of attending to and expressing negative emotion while recovering from traumatic life events. However, recent evidence suggests that the tendency to direct attention away from negative affective experience (i.e., repressive coping) may promote resilience following extremely aversive events (e.g., the death of a spouse). The current study extends this line of investigation by showing that both bereaved and nonbereaved individuals who exhibited repressive coping behavior--as measured by the discrepancy between affective experience and sympathetic nervous system response--had fewer symptoms of psychopathology, experienced fewer health problems and somatic complaints, and were rated as better adjusted by close friends than those who did not exhibit repressive coping. Results are discussed in terms of recent developments in cognitive and neuroimaging research suggesting that repressive coping may serve a protective function. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Graph laplacian tomography from unknown random projections

We introduce a graph Laplacian-based algorithm for the tomographic reconstruction of a planar object from its projections taken at random unknown directions. A Laplace-type operator is constructed on the data set of projections, and the eigenvectors of this operator reveal the projection orientations. The algorithm is shown to successfully reconstruct the Shepp-Logan phantom from its noisy projections. Such a reconstruction algorithm is desirable for the structuring of certain biological proteins using cryo-electron microscopy.