A digital interface for wireless networks

This dissertation addresses the problem of determining the capacity of wireless networks and how to operate them. Within this context we present results on Gaussian relay, interference, and multicast networks. Two new models for wireless networks are introduced here: the discrete network and the superposition network. As with a Gaussian network, one can construct either a discrete network or a superposition network. The discrete network is obtained by simply quantizing the received signals in the Gaussian model and by restricting the transmit signals to a finite alphabet. The superposition network, inspired by the Gaussian model, is a noiseless deterministic network, the inputs and outputs of the channels are discrete, and channel gains are signed integers. The capacity of a class of Gaussian relay networks and its corresponding discrete or superposition network is always within a bounded gap, where the gap is independent of channel gains or signal-to-noise ratio (SNR), and depends only on the number $M$ of nodes in the network. More importantly, a near-optimal coding strategy for either the discrete or the superposition network can be converted into a near-optimal coding strategy for the original Gaussian network. Hence, both these networks serve as near-optimal digital interfaces for operating the Gaussian network. The discrete network is obtained from a Gaussian network by simply quantizing the received signals and restricting transmitted signals to a certain finite precision. Since its signals are obtained from those of a Gaussian network and its transmissions are transmittable as-is on a Gaussian network, the discrete network provides a particularly simple quantization-based digital interface for operating layered Gaussian relay networks. These are relay networks in which the nodes are grouped into layers, and only nodes of one layer can transmit to the nodes of the next layer. The cut-set upper bounds on the capacities of the Gaussian and the discrete network are within an SNR-independent bounded gap of $O(M \log M)$ bits. Moreover, a simple linear network code is a near-optimal coding strategy for the discrete relay network, achieving all rates within $O(M^2)$ bits of its cut-set bound, where the bound is independent of channel gains or SNR. The linear code can be used as-is on the Gaussian network after quantizing its received signals. It achieves all rates within $O(M^2)$ bits of the capacity for Gaussian relay networks. The linear network code improves on existing approximately-optimal coding schemes for the relay network by virtue of its simplicity and robustness, and it explicitly connects wireline network coding with codes for Gaussian networks. The approximation of Gaussian networks by other previously proposed deterministic networks is also studied in this dissertation, and two main results are presented, one positive and the other negative. The gap between the capacity of a Gaussian relay network and a corresponding linear deterministic network can be unbounded. The key reasons are that the linear deterministic model fails to capture the phase of received signals, and there is a loss in signal strength in the reduction to a linear deterministic network. On the positive side, Gaussian relay networks with a single source-destination pair are indeed well approximated by the superposition network. The difference between the capacity of a Gaussian relay network and the corresponding superposition network is bounded by $O(M \log M)$ bits, where the gap is again independent of channel gains or SNR. As a corollary, multiple-input multiple-output (MIMO) channels cannot be approximated by the linear deterministic model but can be by the superposition model. A code for a Gaussian relay network can be designed from {\em any} code for the corresponding superposition network simply by pruning it, suffering no more than a rate loss of $O(M \log M)$ bits that is independent of SNR. Similar results hold for the $K \times K$ Gaussian interference network, MIMO Gaussian interference networks, MIMO Gaussian relay networks, and multicast networks, with the constant gap depending additionally on the number of antennas in case of MIMO networks

Real-Time Detection of Robotic Traffic in Online Advertising

Detecting robotic traffic at scale on online ads needs an approach that is scalable, comprehensive, precise, and can rapidly respond to changing traffic patterns. In this paper we describe SLIDR or SLIce-Level Detection of Robots, a real-time deep neural network model trained with weak supervision to identify invalid clicks on online ads. We ensure fairness across different traffic slices by formulating a convex optimization problem that allows SLIDR to achieve optimal performance on individual traffic slices with a budget on overall false positives. SLIDR has been deployed since 2021 and safeguards advertiser campaigns on Amazon against robots clicking on ads on the e-commerce site. We describe some of the important lessons learned by deploying SLIDR that include guardrails that prevent updates of anomalous models and disaster recovery mechanisms to mitigate or correct decisions made by a faulty model

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Not AvailablePacific White Shrimp (Penaeus vannamei) farming is an important commercial aquaculture production system contributing substantially to the economic and societal development in India. Though technically efficient, shrimp farming is potentially susceptible to production risks. A risk assessment study was undertaken to ascertain the potential risks in P. vannamei shrimp farming by developing a framework consisting of risk perception and assessment, communication of risk management practices, and evaluation of their efficiency in tackling the risks. The primary data collected from a proportionate randomly chosen 604 shrimp farmers across the coastal states revealed that P. vannamei shrimp farming was prone to twenty seven risks having very low to very high probability of occurrence with marginally negative to a catastrophic impact on the production and income. Appropriate risk preventive and management measures were proposed and suitably communicated to the shrimp farmers through training workshops, farmer handbooks in vernacular languages, and launching a mobile app module on on-farm risk assessment. A follow up study conducted among a random subset of the original sample indicated that 76% of the farmers adopted the proposed risk management practices and experienced that the practices were highly efficient (up to 80%) in tackling the risks associated with shrimp farming. Further, it was observed that adoption of risk management practices is essential to have a successful shrimp production of marketable size and an additional expenditure for adoption of these practices was estimated to be 0.5 USD per kg of shrimp produced. Shrimp farming is a delicate and dynamic production system and it is unrealistic to avoid the emergence of hazards in the production cycle. Therefore, it is imperative to train the farmers on Better Management Practices (BMP) and develop a certification plan to accredit the farms for the adoption of BMPs that would ensure an economically viable shrimp production in India.Not Availabl

A case control study to assess effectiveness of measles containing vaccines in preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children

Currently, most licensed vaccines against SARS-CoV-2 infection are approved for adults and not for children. We conducted a test negative case-control study to assess the effectiveness of Measles Containing Vaccines (MCVs) against SARS-CoV-2 infection in Pune, India, in children who were ≥1 year and <18 years of age and were tested for SARS-CoV-2 infection by Reverse transcription polymerase chain reaction (RT-PCR). The enrolled participants included 274 SARS-CoV-2 positive cases (216 vaccinated and 58 unvaccinated) along with 274 SARS-CoV-2 negative controls (265 vaccinated and 9 unvaccinated). Of the 274 cases, 180 (65.7%) were asymptomatic while 94 (34.3%) were symptomatic, all with mild severity. The number of participants with symptomatic SARS-CoV-2 infection was significantly lower in the vaccinated group compared to the unvaccinated group (p < .0001). The unadjusted overall Vaccine Effectiveness (VE) in the vaccinated group compared to unvaccinated group was 87.4% (OR = 0.126, 95% CI of VE: 73.9–93.9) while the adjusted overall VE after adjusting for age and sex was 87.5% (OR = 0.125, 95% CI of VE: 74.2–94.0). MCVs reduced incidence of laboratory confirmed SARS-CoV-2 infection in children. Number of symptomatic cases were also lower in the vaccinated group compared to the unvaccinated group. Results of our study have provided strong preliminary evidence that MCVs have a good effectiveness against SARS-CoV-2 infection in the pediatric population, which needs to be confirmed further through prospective randomized clinical trials

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Not AvailableThe lockdown on account of the Coronavirus disease 2019 (COVID-19) adversely impacted the food production sector including aquaculture, globally. Unfortunately, it coincided with the major shrimp farming season in India which contributes 60% of the national annual shrimp production hence the impact was substantial. An on-line survey was carried out among the stakeholders of the shrimp farming sector to evaluate the prospective impact of COVID-19 related lockdown across the shrimp supply chain. The study estimated an economic loss of 1.50 billion USD to the shrimp aquaculture sector during the current year. It is expected that shrimp production and its export performance may be declining by 40% in the current season. The Garret ranking and Rank Based Quotient analyses projected severe constraints in shrimp seed production and supply, disruptions in the supply chain, logistics, farming, processing, marketing and loss of employment and income for the workers due to the pandemic. To mitigate the impact, the Government of India declared fisheries and aquaculture as an essential activity, facilitated the movement of inputs and services. Further, a major Fisheries Development Scheme(PMMSY) with a financial outlay of 267 million USD has been announced to usher in a blue revolution by strengthening the value chain, doubling the fisher/farmer income, employment generation, economic and social security for fishers/fish farmers adhering to the sustainability principles. Short and medium-term technical and policy measures are suggested to tide over the impact of COVID-19 related lockdown and related restrictions.Not Availabl