A Decision-theoretic Approach to Detection-based Target Search with a UAV

Search and rescue missions and surveillance require finding targets in a large area. These tasks often use unmanned aerial vehicles (UAVs) with cameras to detect and move towards a target. However, common UAV approaches make two simplifying assumptions. First, they assume that observations made from different heights are deterministically correct. In practice, observations are noisy, with the noise increasing as the height used for observations increases. Second, they assume that a motion command executes correctly, which may not happen due to wind and other environmental factors. To address these, we propose a sequential algorithm that determines actions in real time based on observations, using partially observable Markov decision processes (POMDPs). Our formulation handles both observations and motion uncertainty and errors. We run offline simulations and learn a policy. This policy is run on a UAV to find the target efficiently. We employ a novel compact formulation to represent the coordinates of the drone relative to the target coordinates. Our POMDP policy finds the target up to 3.4 times faster when compared to a heuristic policy.Comment: Published in IEEE IROS 2017. 6 page

Maximizing Success Rate of Payment Routing using Non-stationary Bandits

This paper discusses the system architecture design and deployment of non-stationary multi-armed bandit approaches to determine a near-optimal payment routing policy based on the recent history of transactions. We propose a Routing Service architecture using a novel Ray-based implementation for optimally scaling bandit-based payment routing to over 10000 transactions per second, adhering to the system design requirements and ecosystem constraints with Payment Card Industry Data Security Standard (PCI DSS). We first evaluate the effectiveness of multiple bandit-based payment routing algorithms on a custom simulator to benchmark multiple non-stationary bandit approaches and identify the best hyperparameters. We then conducted live experiments on the payment transaction system on a fantasy sports platform Dream11. In the live experiments, we demonstrated that our non-stationary bandit-based algorithm consistently improves the success rate of transactions by 0.92\% compared to the traditional rule-based methods over one month.Comment: 7 Pages, 6 Figure

PLUME: An ECDSA Nullifier Scheme for Unique Pseudonymity within Zero Knowledge Proofs

ZK-SNARKs (Zero Knowledge Succinct Noninteractive ARguments of Knowledge) are one of the most promising new applied cryptography tools: proofs allow anyone to prove a property about some data, without revealing that data. Largely spurred by the adoption of cryptographic primitives in blockchain systems, ZK-SNARKs are rapidly becoming computationally practical in real-world settings, shown by i.e. tornado.cash and rollups. These have enabled ideation for new identity applications based on anonymous proof-of-ownership. One of the primary technologies that would enable the jump from existing apps to such systems is the development of deterministic nullifiers. Nullifiers are used as a public commitment to a specific anonymous account, to forbid actions like double spending, or allow a consistent identity between anonymous actions. We identify a new deterministic signature algorithm that both uniquely identifies the keypair, and keeps the account identity secret. In this work, we will define the full DDH-VRF construction, and prove uniqueness, secrecy, and existential unforgeability. We will also demonstrate a proof of concept of our Pseudonymously Linked Unique Message Entity (PLUME) scheme

Wake Up and Join Me! An Energy-Efficient Algorithm for Maximal Matching in Radio Networks

We consider networks of small, autonomous devices that communicate with each other wirelessly. Minimizing energy usage is an important consideration in designing algorithms for such networks, as battery life is a crucial and limited resource. Working in a model where both sending and listening for messages deplete energy, we consider the problem of finding a maximal matching of the nodes in a radio network of arbitrary and unknown topology. We present a distributed randomized algorithm that produces, with high probability, a maximal matching. The maximum energy cost per node is $O(\log^2 n)$, where $n$ is the size of the network. The total latency of our algorithm is $O(n \log n)$ time steps. We observe that there exist families of network topologies for which both of these bounds are simultaneously optimal up to polylog factors, so any significant improvement will require additional assumptions about the network topology. We also consider the related problem of assigning, for each node in the network, a neighbor to back up its data in case of node failure. Here, a key goal is to minimize the maximum load, defined as the number of nodes assigned to a single node. We present a decentralized low-energy algorithm that finds a neighbor assignment whose maximum load is at most a polylog($n$) factor bigger that the optimum.Comment: 14 pages, 2 figures, 3 algorithm

Effect of passive smoking as a risk factor for chronic obstructive pulmonary disease in normal healthy women

Background: Environmental tobacco smoke (ETS) is a risk factor for cardiovascular disease, asthma in children and lung cancer. There is a biological plausibility of ETS as a causal factor for COPD. Objectives of the study were to examine the effect of passive smoking on lung function in non-smoking healthy women and to co-relate the effects of passive smoke as a risk factor for COPD.Methods: 50 women between 20-40 years of age exposed to passive smoke at home and workplace were assessed by questionnaire. The pulmonary function tests were performed and the values of FEV1 and FVC were obtained by a spirometer.Results: Out of 50 women, 34 % at workplace, 54% at home and 12% at home and workplace were exposed. Mean age was 30.3 years. Mean±SD of FEV1 was 1.94±0.9, FVC was 2.54±1.06, FEV1/FVC was 73.5±10.06 predicted FEV1 % was 63.2±23.2. FEV1/FVC of women exposed at home and workplace was 70.84 indicating that they have higher chances of developing COPD later in life.Conclusions: Passive smoking represents a serious health hazard that can be prevented by health education campaigns

Pathological alpha-synuclein impairs adult-born granule cell development and functional integration in the olfactory bulb

Although the role of noxious alpha-synuclein (alpha-SYN) in the degeneration of midbrain dopaminergic neurons and associated motor deficits of Parkinson's disease is recognized, its impact on non-motor brain circuits and related symptoms remains elusive. Through combining in vivo two-photon imaging with time-coded labelling of neurons in the olfactory bulb of A30P alpha-SYN transgenic mice, we show impaired growth and branching of dendrites of adult-born granule cells (GCs),with reduced gain and plasticity of dendritic spines. The spine impairments are especially pronounced during the critical phase of integration of new neurons into existing circuits. Functionally, retarded dendritic expansion translates into reduced electrical capacitance with enhanced intrinsic excitability and responsiveness of GCs to depolarizing inputs, while the spine loss correlates with decreased frequency of AMPA-mediated miniature EPSCs. Changes described here are expected to interfere with the functional integration and survival of new GCs into bulbar networks, contributing towards olfactory deficits and related behavioural impairments