An Optimal Medium Access Control with Partial Observations for Sensor Networks

We consider medium access control (MAC) in multihop sensor networks, where only partial information about the shared medium is available to the transmitter. We model our setting as a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain representing the available bandwidth, and in which the arrivals are controlled based on the partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state on which the control decisions are based. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results can be specifically applied for designing efficient and stable algorithms for medium access control in multiple-accessed systems, in particular for sensor networks

On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks

We consider sensor networks that measure spatio-temporal correlated processes. An important task in such settings is the reconstruction at a certain node, called the sink, of the data at all points of the field. We consider scenarios where data is time critical, so delay results in distortion, or suboptimal estimation and control. For the reconstruction, the only data available to the sink are the values measured at the nodes of the sensor network, and knowledge of the correlation structure: this results in spatial distortion of reconstruction. Also, for the sake of power efficiency, sensor nodes need to transmit their data by relaying through the other network nodes: this results in delay, and thus temporal distortion of reconstruction if time critical data is concerned. We study data gathering for the case of Gaussian processes in one- and two-dimensional grid scenarios, where we are able to write explicit expressions for the spatial and time distortion, and combine them into a single total distortion measure. We prove that, for various standard correlation structures, there is an optimal finite density of the sensor network for which the total distortion is minimized. Thus, when power efficiency and delay are both considered in data gathering, it is useless from the point of view of accuracy of the reconstruction to increase the number of sensors above a certain threshold that depends on the correlation structure characteristics

Power Control for Target Tracking in Sensor Networks

We consider the problem of a sensor network tracking a moving target that exhibits a Markov model of mobility. The sensor nodes have adjustable power levels and the precision of the measurement of the target location depends on both the relative distance from the target to the measuring sensor, and on the sensing power level used by that sensor. An important issue in sensor networks is the power effi- ciency, thus we consider the optimization of a family of cost functions that include both the accuracy of a measurement and the power used to do that measurement. We define our problem as a control policy optimization for a partially observed Markov chain. For such scenarios, we derive optimal power control policies based only on partial observations of the target location, and propose hand-off techniques based on this policies

Partially trombosed glomus type spinal arteriovenous malformation: Case presentation

Spinal AVM are very rare vascular lesions and most o the studies give reports on only a few cases. Given their localization between the spinal tracts and the gray matter core of the medulla and their multiple feeders from posterior and anterior spinal arteries they are amongst the most difficult surgical pathology in the nervous sistem. We present the case of a 60 years old male with a glomus type T10-L2 spinal AVM that presented with motor deficit in the lower limbs and urinary incontinence. The partially thrombosed lesion was completely resected without previous embolisation, and the patient was walking with assistance at discharge. This is a rare case that presented with progressive neurological deterioration consistent with an ischemic rather than a hemorrhagic event. Microsurgery is a better option than conservative treatment in these rare cases of spontaneous occlusion of intramedullary arteriovenous malformations

Taxonomic classification of asteroids based on MOVIS near-infrared colors

We aim to provide a taxonomic classification for asteroids observed by VISTA-VHS survey. We derive a method for assigning a compositional type to an object based on its (Y-J), (J-Ks), and (H-Ks) colors. We present a taxonomic classification for 18\,265 asteroids from the MOVIS catalog, using a probabilistic method and the k-nearest neighbors algorithm. Because our taxonomy is based only on NIR colors, several classes from Bus-DeMeo were clustered into groups and a slightly different notation was used (i.e. the superscript indicates that the classification was obtained based on the NIR colors and the subscript indicates possible miss-identifications with other types). Our results are compared with the information provided by the Sloan Digital Sky Survey (SDSS) and Wide-field Infrared Survey Explorer (WISE). The two algorithms used in this study give a taxonomic type for all objects having at least (Y-J) and (J-Ks) observed colors. A final classification is reported for a set of 6\,496 asteroids based on the criteria that KNN and probabilistic algorithms gave the same result, (Y-J)$_{err}\leq$ 0.118 and (J-Ks)$_{err}\leq$0.136. This set includes 144 bodies classified as $B_k^{ni}$, 613 as $C^{ni}$, 197 as $C_{gx}^{ni}$, 91 as $X_t^{ni}$, 440 as $D_s^{ni}$, 665 as $K_l^{ni}$, 233 as $A_d^{ni}$, 3\,315 as $S^{ni}$, and 798 as $V^{ni}$. We report the albedo distribution for each taxonomic group and we compute new median values for the main types. We found that V-type and A-type candidates have identical size frequency distributions, but the V-types are five times more common than the A-types. Several particular cases, such as the A-type asteroid (11616) 1996 BQ2 and the S-type (3675) Kematsch, both in the Cybele population, are discussed. Files and codes available at: https://github.com/marcelpopescu/MOVIS-TaxonomyComment: 18 pages, 10 figures, accepted for publication in Astronomy & Astrophysics (A&A

Cross-continental emergence of Nannizziopsis barbatae disease may threaten wild Australian lizards

Members of the genus Nannizziopsis are emerging fungal pathogens of reptiles that have been documented as the cause of fatal mycoses in a wide range of reptiles in captivity. Cases of severe, proliferative dermatitis, debility and death have been detected in multiple free-living lizard species from locations across Australia, including a substantial outbreak among Eastern water dragons (Intellagama lesueurii) in Brisbane, Queensland. We investigated this disease in a subset of severely affected lizards and identified a clinically consistent syndrome characterized by hyperkeratosis, epidermal hyperplasia, dermal inflammation, necrosis, ulceration, and emaciation. Using a novel fungal isolation method, histopathology, and molecular techniques, we identified the etiologic agent as Nannizziopsis barbatae, a species reported only once previously from captive lizards in Australia. Here we report severe dermatomycosis caused by N. barbatae in five species of Australian lizard, representing the first cases of Nannizziopsis infection among free-living reptiles, globally. Further, we evaluate key pathogen and host characteristics that indicate N. barbatae-associated dermatomycosis may pose a concerning threat to Australian lizards

On the interaction of data representation and routing in sensor networks

We consider data gathering by a network with a sink node and a tree communication structure, where the goal is to minimize the total transmission cost of transporting the information, collected by the nodes, to the sink node. This problem requires a joint optimization of the data representation at the nodes and of the transmission structure. First, we study the case when the measured data are correlated random variables, both in the lossless scenario with Slepian-Wolf coding, and in the high-resolution lossy scenario with optimal rate-distortion allocation. We show that the optimal transmission structure is the shortest path tree, and we find, in closed-form, the rate and distortion allocation. Second, we study the case when the measured data are deterministic piecewise constant signals, and data is described with adaptive level wavelet-based multiresolution representation. We show experimentally that, when computation is decentralized, there is an optimal network division into node groups of adaptive size. Finally, we also analyze the node positioning problem where, given a correlation structure and an available number of sensors, the goal is to place the nodes optimally in terms of minimizing the transmission cost; our results show that important gains can be obtained compared to a uniformly distributed sensor positionin