Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

On the Scalability-Performance Tradeoffs in MPLS and IP Routing

MPLS (Multi-Protocol Label Switching) has recently emerged to facilitate the engineering of network traffic. This can be achieved by directing packet flows over paths that satisfy multiple requirements. MPLS has been regarded as an enhancement to traditional IP routing, which has the following problems: (1) all packets with the same IP destination address have to follow the same path through the network; and (2) paths have often been computed based on static and single link metrics. These problems may cause traffic concentration, and thus degradation in quality of service. In this paper, we investigate by simulations a range of routing solutions and examine the tradeoff between scalability and performance. At one extreme, IP packet routing using dynamic link metrics provides a stateless solution but may lead to routing oscillations. At the other extreme, we consider a recently proposed Profile-based Routing (PBR), which uses knowledge of potential ingress-egress pairs as well as the traffic profile among them. Minimum Interference Routing (MIRA) is another recently proposed MPLS-based scheme, which only exploits knowledge of potential ingress-egress pairs but not their traffic profile. MIRA and the more conventional widest-shortest path (WSP) routing represent alternative MPLS-based approaches on the spectrum of routing solutions. We compare these solutions in terms of utility, bandwidth acceptance ratio as well as their scalability (routing state and computational overhead) and load balancing capability. While the simplest of the per-flow algorithms we consider, the performance of WSP is close to dynamic per-packet routing, without the potential instabilities of dynamic routing.

An Online Distributed Algorithm for Inferring Policy Routing Configurations

We present an online distributed algorithm, the Causation Logging Algorithm (CLA), in which Autonomous Systems (ASes) in the Internet individually report route oscillations/flaps they experience to a central Internet Routing Registry (IRR). The IRR aggregates these reports and may observe what we call causation chains where each node on the chain caused a route flap at the next node along the chain. A chain may also have a causation cycle. The type of an observed causation chain/cycle allows the IRR to infer the underlying policy routing configuration (i.e., the system of economic relationships and constraints on route/path preferences). Our algorithm is based on a formal policy routing model that captures the propagation dynamics of route flaps under arbitrary changes in topology or path preferences. We derive invariant properties of causation chains/cycles for ASes which conform to economic relationships based on the popular Gao-Rexford model. The Gao-Rexford model is known to be safe in the sense that the system always converges to a stable set of paths under static conditions. Our CLA algorithm recovers the type/property of an observed causation chain of an underlying system and determines whether it conforms to the safe economic Gao-Rexford model. Causes for nonconformity can be diagnosed by comparing the properties of the causation chains with those predicted from different variants of the Gao-Rexford model.

Consciousness CLEARS the Mind

A full understanding of consciouness requires that we identify the brain processes from which conscious experiences emerge. What are these processes, and what is their utility in supporting successful adaptive behaviors? Adaptive Resonance Theory (ART) predicted a functional link between processes of Consciousness, Learning, Expectation, Attention, Resonance, and Synchrony (CLEARS), includes the prediction that "all conscious states are resonant states." This connection clarifies how brain dynamics enable a behaving individual to autonomously adapt in real time to a rapidly changing world. The present article reviews theoretical considerations that predicted these functional links, how they work, and some of the rapidly growing body of behavioral and brain data that have provided support for these predictions. The article also summarizes ART models that predict functional roles for identified cells in laminar thalamocortical circuits, including the six layered neocortical circuits and their interactions with specific primary and higher-order specific thalamic nuclei and nonspecific nuclei. These prediction include explanations of how slow perceptual learning can occur more frequently in superficial cortical layers. ART traces these properties to the existence of intracortical feedback loops, and to reset mechanisms whereby thalamocortical mismatches use circuits such as the one from specific thalamic nuclei to nonspecific thalamic nuclei and then to layer 4 of neocortical areas via layers 1-to-5-to-6-to-4.

Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

Spiking Dynamics during Perceptual Grouping in the Laminar Circuits of Visual Cortex

Grouping of collinear boundary contours is a fundamental process during visual perception. Illusory contour completion vividly illustrates how stable perceptual boundaries interpolate between pairs of contour inducers, but do not extrapolate from a single inducer. Neural models have simulated how perceptual grouping occurs in laminar visual cortical circuits. These models predicted the existence of grouping cells that obey a bipole property whereby grouping can occur inwardly between pairs or greater numbers of similarly oriented and co-axial inducers, but not outwardly from individual inducers. These models have not, however, incorporated spiking dynamics. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity to inducer configurations occur despite irregularities in spike timing across all the interacting cells. Other models have demonstrated spiking dynamics in laminar neocortical circuits, but not how perceptual grouping occurs. The current model begins to unify these two modeling streams by implementing a laminar cortical network of spiking cells whose intracellular temporal dynamics interact with recurrent intercellular spiking interactions to quantitatively simulate data from neurophysiological experiments about perceptual grouping, the structure of non-classical visual receptive fields, and gamma oscillations.

Neural Control of Interlimb Coordination and Gait Timing in Bipeds and Quadrupeds

1) A large body of behavioral data conceming animal and human gaits and gait transitions is simulated as emergent properties of a central pattern generator (CPG) model. The CPG model incorporates neurons obeying Hodgkin-Huxley type dynamics that interact via an on-center off-surround anatomy whose excitatory signals operate on a faster time scale than their inhibitory signals. A descending cornmand or arousal signal called a GO signal activates the gaits and controL their transitions. The GO signal and the CPG model are compared with neural data from globus pallidus and spinal cord, among other brain structures. 2) Data from human bimanual finger coordination tasks are simulated in which anti-phase oscillations at low frequencies spontaneously switch to in-phase oscillations at high frequencies, in-phase oscillations can be performed both at low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, and a "seagull effect" of larger errors occurs at intermediate phases. When driven by environmental patterns with intermediate phase relationships, the model's output exhibits a tendency to slip toward purely in-phase and anti-phase relationships as observed in humans subjects. 3) Quadruped vertebrate gaits, including the amble, the walk, all three pairwise gaits (trot, pace, and gallop) and the pronk are simulated. Rapid gait transitions are simulated in the order--walk, trot, pace, and gallop--that occurs in the cat, along with the observed increase in oscillation frequency. 4) Precise control of quadruped gait switching is achieved in the model by using GO-dependent modulation of the model's inhibitory interactions. This generates a different functional connectivity in a single CPG at different arousal levels. Such task-specific modulation of functional connectivity in neural pattern generators has been experimentally reported in invertebrates. Phase-dependent modulation of reflex gain has been observed in cats. A role for state-dependent modulation is herein predicted to occur in vertebrates for precise control of phase transitions from one gait to another. 5) The primary human gaits (the walk and the run) and elephant gaits (the amble and the walk) are sirnulated. Although these two gaits are qualitatively different, they both have the same limb order and may exhibit oscillation frequencies that overlap. The CPG model simulates the walk and the run by generating oscillations which exhibit the same phase relationships. but qualitatively different waveform shapes, at different GO signal levels. The fraction of each cycle that activity is above threshold quantitatively distinguishes the two gaits, much as the duty cycles of the feet are longer in the walk than in the run. 6) A key model properly concerns the ability of a single model CPG, that obeys a fixed set of opponent processing equations to generate both in-phase and anti-phase oscillations at different arousal levels. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases.

Frequency-Dependent Phase Transitions in the Coordination of Human Bimanual Tasks

The 2-channel Ellias-Grossberg neural pattern generator of Cohen, Grossberg, and Pribe [1] is shown to simulate data from human bimanual coordination tasks in which anti-phase oscillations at low frequencies spontaneously switch to in-phase oscillations at high frequencies, in-phase oscillations can be performed at both low and high frequencies, phase fluctuations occur at the anti-phase to in-phase transition, and a "seagull effect" of larger errors occurs at intermediate phases.

Quadruped Gait Transitions from a Neural Pattern Generator with Arousal Modulated Interactions

A four-channel neural pattern generator is described in which both the frequency and the relative phase of oscillations are controlled by a scalar arousal or GO signal. The generator is used to simulate quadruped gaits; in particular, rapid transitions are simulated in the order - walk, trot, pace, and gallop - that occurs in the cat. Precise switching control is achieved by using an arousal dependent modulation of the model's inhibitory interactions. This modulation generates a different functional connectivity in a single network at different arousal levels.

From Synapse to Self: Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

How do our brains transform the "blooming buzzing confusion" of daily experience into a coherent sense of self that can learn and selectively attend to important information? How do local signals at multiple processing stages, none of which has a global view of brain dynamics or behavioral outcomes, trigger learning at multiple synaptic sites when appropriate, and prevent learning when inappropriate, to achieve useful behavioral goals in a continually changing world? How does the brain allow synaptic plasticity at a remarkably rapid rate, as anyone who has gone to an exciting movie is readily aware, yet also protect useful memories from catastrophic forgetting? A neural model provides a unified answer by explaining and quantitatively simulating data about single cell biophysics and neurophysiology, laminar neuroanatomy, aggregate cell recordings (current-source densities, local field potentials), large-scale oscillations (beta, gamma), and spike-timing dependent plasticity, and functionally linking them all to cognitive information processing requirements.

DC/DC converter 3D assembly for autonomous sensor nodes

This paper reports on the design and the manufacturing of an integrated DCDC converter, which respects the specificity of sensor node network: compactness, high efficiency in acquisition and transmission modes, and compatibility with miniature Lithium batteries. A novel integrated circuit (ASIC) has been designed and manufactured to provide regulated Voltage to the sensor node from miniaturized, thin film Lithium batteries. Then, a 3D integration technique has been used to integrate this ASIC in a 3 layers stack with high efficiency passives components, mixing the wafer level technologies from two different research institutions. Electrical results have demonstrated the feasibility of this integrated system and experiments have shown significant improvements in the case of oscillations in regulated voltage. However, stability of this output voltage toward the input voltage has still to be improved.

Two closely coupled lasers, dynamics & applications

The dynamics of two mutually coupled identical single-mode semi-conductor lasers are theoretically investigated. For small separation and large coupling between the lasers, symmetry-broken one-colour states are shown to be stable. In this case the light output of the lasers have significantly different intensities whilst at the same time the lasers are locked to a single common frequency. For intermediate coupling we observe stable two-colour states, where both single-mode lasers lase simultaneously at two optical frequencies which are separated by up to 150 GHz. For low coupling but possibly large separation, the frequency of the relaxation oscillations of the freerunning lasers defines the dynamics. Chaotic and quasi-periodic states are identified and shown to be stable. For weak coupling undamped relaxation oscillations dominate where each laser is locked to three or more odd number of colours spaced by the relaxation oscillation frequency. It is shown that the instabilities that lead to these states are directly connected to the two colour mechanism where the change in the number of optical colours due to a change in the plane of oscillation. At initial coupling, in-phase and anti-phase one colour states are shown to emerge from “on” uncoupled lasers using a perturbation method. Similarly symmetry-broken one-colour states come from considering one free-running laser initially “on” and the other laser initially “off”. The mechanism that leads to a bi-stability between in-phase and anti-phase one-colour states is understood. Due to an equivariant phase space symmetry of being able to exchange the identical lasers, a symmetric and symmetry-broken variant of all states mentioned above exists and is shown to be stable. Using a five dimensional model we identify the bifurcation structure which is responsible for the appearance of symmetric and symmetry-broken one-colour, symmetric and symmetry-broken two-colour, symmetric and symmetry-broken undamped relaxation oscillations, symmetric and symmetry-broken quasi-periodic, and symmetric and symmetry-broken chaotic states. As symmetry-broken states always exist in pairs, they naturally give rise to bi-stability. Several of these states show multistabilities between symmetric and symmetry-broken variants and among states. Three memory elements on the basis of bi-stabilities in one and two colour states for two coupled single-mode lasers are proposed. The switching performance of selected designs of optical memory elements is studied numerically.

A microscopic study of structural and electronic properties of functionalized silicon surfaces based on first-principles

Surface modification of silicon with organic monolayers tethered to the surface by different linkers is an important process in realizing future (opto-)electronic devices. Understanding the role played by the nature of the linking group and the chain length on the adsorption structures and electronic properties of these assemblies is vital to advance this technology. This Thesis is a study of such properties and contributes in particular to a microscopic understanding of induced changes in the work function of experimentally studied functionalized silicon surfaces. Using first-principles density functional theory (DFT), at the first step, we provide predictions for chemical trends in the work function of hydrogenated silicon (111) surfaces modified with various terminations. For nonpolar terminating atomic species such as F, Cl, Br, and I, the change in the work function is directly proportional to the amount of charge transferred from the surface, thus relating to the difference in electronegativity of the adsorbate and silicon atoms. The change is a monotonic function of coverage in this case, and the work function increases with increasing electronegativity. Polar species such as −TeH, −SeH, −SH, −OH, −NH2, −CH3, and −BH2 do not follow this trend due to the interaction of their dipole with the induced electric field at the surface. In this case, the magnitude and sign of the surface dipole moment need to be considered in addition to the bond dipole to generally describe the change in work function. Compared to hydrogenated surfaces, there is slight increase in the work function of H:Si(111)-XH, where X = Te, Se, and S, whereas reduction is observed for surfaces covered with −OH, −CH3, and −NH2. Next, we study the hydrogen passivated Si(111) surface modified with alkyl chains of the general formula H:Si–(CH2)n–CH2 and H:Si–X–(CH2)n–CH3, where X = NH, O, S and n = (0, 1, 3, 5, 7, 9, 11), at half coverage. For (X)–Hexyl and (X)–Dodecyl functionalization, we also examined various coverages up to full monolayer grafting in order to validate the result of half covered surface and the linker effect on the coverage. We find that it is necessary to take into account the van der Waals interaction between the alkyl chains. The strongest binding is for the oxygen linker, followed by S, N, and C, irrespective of chain length. The result revealed that the sequence of the stability is independent of coverage; however, linkers other than carbon can shift the optimum coverage considerably and allow further packing density. For all linkers apart from sulfur, structural properties, in particular, surface-linker-chain angles, saturate to a single value once n > 3. For sulfur, we identify three regimes, namely, n = 0–3, n = 5–7, and n = 9–11, each with its own characteristic adsorption structures. Where possible, our computational results are shown to be consistent with the available experimental data and show how the fundamental structural properties of modified Si surfaces can be controlled by the choice of linking group and chain length. Later we continue by examining the work function tuning of H:Si(111) over a range of 1.73 eV through adsorption of alkyl monolayers with general formula -[Xhead-group]-(CnH2n)-[Xtail-group], X = O(H), S(H), NH(2). The work function is practically converged at 4 carbons (8 for oxygen), for head-group functionalization. For tail-group functionalization and with both head- and tail-groups, there is an odd-even effect in the behavior of the work function, with peak-to-peak amplitudes of up to 1.7 eV in the oscillations. This behavior is explained through the orientation of the terminal-group's dipole. The shift in the work function is largest for NH2-linked and smallest for SH-linked chains and is rationalized in terms of interface dipoles. Our study reveals that the choice of the head- and/or tail-groups effectively changes the impact of the alkyl chain length on the work function tuning using self-assembled monolayers and this is an important advance in utilizing hybrid functionalized Si surfaces. Bringing together the understanding gained from studying single type functionalization of H:Si(111) with different alkyl chains and bearing in mind how to utilize head-group, tail-group or both as well as monolayer coverage, in the final part of this Thesis we study functionalized H:Si(111) with binary SAMs. Aiming at enhancing work function adjustment together with SAM stability and coverage we choose a range of terminations and linker-chains denoted as –X–(Alkyl) with X = CH3, O(H), S(H), NH(2) and investigate the stability and work function of various binary components grafted onto H:Si(111) surface. Using binary functionalization with -[NH(2)/O(H)/S(H)]-[Hexyl/Dodecyl] we show that work function can be tuned within the interval of 3.65-4.94 eV and furthermore, enhance the SAM’s stability. Although direct Si-C grafted SAMs are less favourable compared to their counterparts with O, N or S linkage, regardless of the ratio, binary functionalized alkyl monolayers with X-alkyl (X = NH, O) is always more stable than single type alkyl functionalization with the same coverage. Our results indicate that it is possible to go beyond the optimum coverage of pure alkyl functionalized SAMs (50%) by adding a linker with the correct choice of the linker. This is very important since dense packed monolayers have fewer defects and deliver higher efficiency. Our results indicate that binary anchoring can modify the charge injection and therefore bond stability while preserving the interface electronic structure.

Independent individual addressing of multiple neutral atom qubits with a micromirror-based beam steering system

We demonstrate a scalable approach to addressing multiple atomic qubits for use in quantum information processing. Individually trapped 87Rb atoms in a linear array are selectively manipulated with a single laser guided by a microelectromechanical beam steering system. Single qubit oscillations are shown on multiple sites at frequencies of ≃3.5 MHz with negligible crosstalk to neighboring sites. Switching times between the central atom and its closest neighbor were measured to be 6-7 μs while moving between the central atom and an atom two trap sites away took 10-14 μs. © 2010 American Institute of Physics.

Plasmon-induced electrical conduction in molecular devices.

Metal nanoparticles (NPs) respond to electromagnetic waves by creating surface plasmons (SPs), which are localized, collective oscillations of conduction electrons on the NP surface. When interparticle distances are small, SPs generated in neighboring NPs can couple to one another, creating intense fields. The coupled particles can then act as optical antennae capturing and refocusing light between them. Furthermore, a molecule linking such NPs can be affected by these interactions as well. Here, we show that by using an appropriate, highly conjugated multiporphyrin chromophoric wire to couple gold NP arrays, plasmons can be used to control electrical properties. In particular, we demonstrate that the magnitude of the observed photoconductivity of covalently interconnected plasmon-coupled NPs can be tuned independently of the optical characteristics of the molecule-a result that has significant implications for future nanoscale optoelectronic devices.