Bayesian Programming Multi-Target Tracking: an Automotive Application

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. In particular, target tracking is still challenging in urban trafc situations, because of the large number of rapidly maneuvering targets. The goal of this paper is to present an original way to perform target position and velocity, based on the occupancy grid framework. The main interest of this method is to avoid the decision problem of classical multi-target tracking algorithms. Obtained occupancy grids are combined with danger estimation to perform an elementary task of obstacle avoidance with an electric car

Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge

FEEDFORWARD ARTIFICIAL NEURAL NETWORK DESIGN UTILISING SUBTHRESHOLD MODE CMOS DEVICES

This thesis reviews various previously reported techniques for simulating artificial neural networks and investigates the design of fully-connected feedforward networks based on MOS transistors operating in the subthreshold mode of conduction as they are suitable for performing compact, low power, implantable pattern recognition systems. The principal objective is to demonstrate that the transfer characteristic of the devices can be fully exploited to design basic processing modules which overcome the linearity range, weight resolution, processing speed, noise and mismatch of components problems associated with weak inversion conduction, and so be used to implement networks which can be trained to perform practical tasks. A new four-quadrant analogue multiplier, one of the most important cells in the design of artificial neural networks, is developed. Analytical as well as simulation results suggest that the new scheme can efficiently be used to emulate both the synaptic and thresholding functions. To complement this thresholding-synapse, a novel current-to-voltage converter is also introduced. The characteristics of the well known sample-and-hold circuit as a weight memory scheme are analytically derived and simulation results suggest that a dummy compensated technique is required to obtain the required minimum of 8 bits weight resolution. Performance of the combined load and thresholding-synapse arrangement as well as an on-chip update/refresh mechanism are analytically evaluated and simulation studies on the Exclusive OR network as a benchmark problem are provided and indicate a useful level of functionality. Experimental results on the Exclusive OR network and a 'QRS' complex detector based on a 10:6:3 multilayer perceptron are also presented and demonstrate the potential of the proposed design techniques in emulating feedforward neural networks

Tracking Target Signal Strengths on a Grid using Sparsity

Multi-target tracking is mainly challenged by the nonlinearity present in the measurement equation, and the difficulty in fast and accurate data association. To overcome these challenges, the present paper introduces a grid-based model in which the state captures target signal strengths on a known spatial grid (TSSG). This model leads to \emph{linear} state and measurement equations, which bypass data association and can afford state estimation via sparsity-aware Kalman filtering (KF). Leveraging the grid-induced sparsity of the novel model, two types of sparsity-cognizant TSSG-KF trackers are developed: one effects sparsity through $\ell_1$-norm regularization, and the other invokes sparsity as an extra measurement. Iterative extended KF and Gauss-Newton algorithms are developed for reduced-complexity tracking, along with accurate error covariance updates for assessing performance of the resultant sparsity-aware state estimators. Based on TSSG state estimates, more informative target position and track estimates can be obtained in a follow-up step, ensuring that track association and position estimation errors do not propagate back into TSSG state estimates. The novel TSSG trackers do not require knowing the number of targets or their signal strengths, and exhibit considerably lower complexity than the benchmark hidden Markov model filter, especially for a large number of targets. Numerical simulations demonstrate that sparsity-cognizant trackers enjoy improved root mean-square error performance at reduced complexity when compared to their sparsity-agnostic counterparts.Comment: Submitted to IEEE Trans. on Signal Processin

Chromosome Association of Minichromosome Maintenance Proteins in Drosophila Mitotic Cycles

Minichromosome maintenance (MCM) proteins are essential DNA replication factors conserved among eukaryotes. MCMs cycle between chromatin bound and dissociated states during each cell cycle. Their absence on chromatin is thought to contribute to the inability of a G2 nucleus to replicate DNA. Passage through mitosis restores the ability of MCMs to bind chromatin and the ability to replicate DNA. In Drosophila early embryonic cell cycles, which lack a G1 phase, MCMs reassociate with condensed chromosomes toward the end of mitosis. To explore the coupling between mitosis and MCM–chromatin interaction, we tested whether this reassociation requires mitotic degradation of cyclins. Arrest of mitosis by induced expression of nondegradable forms of cyclins A and/or B showed that reassociation of MCMs to chromatin requires cyclin A destruction but not cyclin B destruction. In contrast to the earlier mitoses, mitosis 16 (M16) is followed by G1, and MCMs do not reassociate with chromatin at the end of M16. dacapo mutant embryos lack an inhibitor of cyclin E, do not enter G1 quiescence after M16, and show mitotic reassociation of MCM proteins. We propose that cyclin E, inhibited by Dacapo in M16, promotes chromosome binding of MCMs. We suggest that cyclins have both positive and negative roles in controlling MCM–chromatin association

Chromosome Association of Minichromosome Maintenance Proteins in Drosophila Endoreplication Cycles

Minichromosome maintenance (MCM) proteins are essential eukaryotic DNA replication factors. The binding of MCMs to chromatin oscillates in conjunction with progress through the mitotic cell cycle. This oscillation is thought to play an important role in coupling DNA replication to mitosis and limiting chromosome duplication to once per cell cycle. The coupling of DNA replication to mitosis is absent in Drosophila endoreplication cycles (endocycles), during which discrete rounds of chromosome duplication occur without intervening mitoses. We examined the behavior of MCM proteins in endoreplicating larval salivary glands, to determine whether oscillation of MCM–chromosome localization occurs in conjunction with passage through an endocycle S phase. We found that MCMs in polytene nuclei exist in two states: associated with or dissociated from chromosomes. We demonstrate that cyclin E can drive chromosome association of DmMCM2 and that DNA synthesis erases this association. We conclude that mitosis is not required for oscillations in chromosome binding of MCMs and propose that cycles of MCM–chromosome association normally occur in endocycles. These results are discussed in a model in which the cycle of MCM–chromosome associations is uncoupled from mitosis because of the distinctive program of cyclin expression in endocycles

Identification of morphological differences between avian influenza A viruses grown in chicken and duck cells

Although wild ducks are considered to be the major reservoirs for most influenza A virus subtypes, they are typically resistant to the effects of the infection. In contrast, certain influenza viruses may be highly pathogenic in other avian hosts such as chickens and turkeys, causing severe illness and death. Following in vitro infection of chicken and duck embryo fibroblasts (CEF and DEF) with low pathogenic avian influenza (LPAI) viruses, duck cells die more rapidly and produce fewer infectious virions than chicken cells. In the current study, the morphology of viruses produced from CEF and DEF cells infected with low pathogenic avian H2N3 was examined. Transmission electron microscopy showed that viruses budding from duck cells were elongated, while chicken cells produced mostly spherical virions; similar differences were observed in viral supernatants. Sequencing of the influenza genome of chicken- and duck-derived H2N3 LPAI revealed no differences, implicating host cell determinants as responsible for differences in virus morphology. Both DEF and CEF cells produced filamentous virions of equine H3N8 (where virus morphology is determined by the matrix gene). DEF cells produced filamentous or short filament virions of equine H3N8 and avian H2N3, respectively, even after actin disruption with cytochalasin D. These findings suggest that cellular factors other than actin are responsible for the formation of filamentous virions in DEF cells. The formation of elongated virions in duck cells may account for the reduced number of infectious virions produced and could have implications for virus transmission or maintenance in the reservoir host

Cell Wall Stress Depolarizes Cell Growth via Hyperactivation of Rho1

Cells sense and physiologically respond to environmental stress via signaling pathways. Saccharomyces cerevisiae cells respond to cell wall stress by transiently depolarizing the actin cytoskeleton. We report that cell wall stress also induces a transient depolarized distribution of the cell wall biosynthetic enzyme glucan synthase FKS1 and its regulatory subunit RHO1, possibly as a mechanism to repair general cell wall damage. The redistribution of FKS1 is dependent on the actin cytoskeleton. Depolarization of the actin cytoskeleton and FKS1 is mediated by the plasma membrane protein WSC1, the RHO1 GTPase switch, PKC1, and a yet-to-be defined PKC1 effector branch. WSC1 behaves like a signal transducer or a stress-specific actin landmark that both controls and responds to the actin cytoskeleton, similar to the bidirectional signaling between integrin receptors and the actin cytoskeleton in mammalian cells. The PKC1-activated mitogen-activated protein kinase cascade is not required for depolarization, but rather for repolarization of the actin cytoskeleton and FKS1. Thus, activated RHO1 can mediate both polarized and depolarized cell growth via the same effector, PKC1, suggesting that RHO1 may function as a rheostat rather than as a simple on-off switch

The functions and consequences of force at kinetochores

Chromosome segregation requires the generation of force at the kinetochore—the multiprotein structure that facilitates attachment of chromosomes to spindle microtubules. This force is required both to move chromosomes and to signal the formation of proper bioriented attachments. To understand the role of force in these processes, it is critical to define how force is generated at kinetochores, the contributions of this force to chromosome movement, and how the kinetochore is structured and organized to withstand and respond to force. Classical studies and recent work provide a framework to dissect the mechanisms, functions, and consequences of force at kinetochores.National Institute of General Medical Sciences (U.S.) (Grant GM088313

Role of replication protein A as sensor in activation of the S-phase checkpoint in Xenopus egg extracts

Uncoupling between DNA polymerases and helicase activities at replication forks, induced by diverse DNA lesions or replication inhibitors, generate long stretches of primed single-stranded DNA that is implicated in activation of the S-phase checkpoint. It is currently unclear whether nucleation of the essential replication factor RPA onto this substrate stimulates the ATR-dependent checkpoint response independently of its role in DNA synthesis. Using Xenopus egg extracts to investigate the role of RPA recruitment at uncoupled forks in checkpoint activation we have surprisingly found that in conditions in which DNA synthesis occurs, RPA accumulation at forks stalled by either replication stress or UV irradiation is dispensable for Chk1 phosphorylation. In contrast, when both replication fork uncoupling and RPA hyperloading are suppressed, Chk1 phosphorylation is inhibited. Moreover, we show that extracts containing reduced levels of RPA accumulate ssDNA and induce spontaneous, caffeine-sensitive, Chk1 phosphorylation in S-phase. These results strongly suggest that disturbance of enzymatic activities of replication forks, rather than RPA hyperloading at stalled forks, is a critical determinant of ATR activation