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We use Reinforcement Meta Learning to optimize an adaptive guidance system suitable for the approach phase of a gliding hypersonic vehicle. Adaptability is achieved by optimizing over a range of off-nominal flight conditions including perturbation of aerodynamic coefficient parameters, actuator failure scenarios, and sensor noise. The system maps observations directly to commanded bank angle and angle of attack rates. These observations include a velocity field tracking error formulated using parallel navigation, but adapted to work over long trajectories where the Earth's curvature must be taken into account. Minimizing the tracking error keeps the curved space line of sight to the target location aligned with the vehicle's velocity vector. The optimized guidance system will then induce trajectories that bring the vehicle to the target location with a high degree of accuracy at the designated terminal speed, while satisfying heating rate, load, and dynamic pressure constraints. We demonstrate the adaptability of the guidance system by testing over flight conditions that were not experienced during optimization. The guidance system's performance is then compared to that of a linear quadratic regulator tracking an optimal trajectory., Comment: Under review for 2021 AIAA scitech GN&C conference

Disease transmission is studied through disciplines like epidemiology, applied mathematics, and statistics. Mathematical simulation models for transmission have implications in solving public and personal health challenges. The SIR model uses a compartmental approach including dynamic and nonlinear behavior of transmission through three factors: susceptible, infected, and removed (recovered and deceased) individuals. Using the Lambert W Function, we propose a framework to study solutions of the SIR model. This demonstrates the applications of COVID-19 transmission data to model the spread of a real-world disease. Different models of disease including the SIR, SIRmp and SEIRpqr model are compared with respect to their ability to predict disease spread. Physical distancing impacts and personal protection equipment use are discussed with relevance to the COVID-19 spread., Comment: 12 pages, NN20 Conference proceedings, published version

Currently available temperature measurements or imaging at nano-micro scale are limited to fluorescent molecules and luminescent nanocrystals, whose spectral properties respond to temperature variation. The principle of operation of these conventional temperature probes is typically related to temperature induced multiphonon quenching or temperature dependent energy transfers, therefore, above 12%/K sensitivity and high thermal resolution remain a serious challenge. Here we demonstrate a novel class of highly sensitive thermographic phosphors operating in room temperature range with milikelvin thermal resolution, whose temperature readings are reproducible, luminescence is photostable and brightness is not compromised by thermal quenching. Corroborated with phase transition structural characterization and high spatio-temporal temperature imaging, we demonstrated that optically active europium ions are highly and smoothly susceptible to monoclinic to tetragonal phase transition in LiYO2 host, which is evidenced by changed number and the splitting of Stark components as well as by smooth variation of contribution between magnetic and electric dipole transitions. Further, reducing the size of phosphor from bulk to nanocrystalline matrix, shifted the phase transition temperature from 100oC down to room temperature. These findings provide insights into the mechanism underlaying phase transition based luminescence nanothermometry and motivate future research toward new, highly sensitive, high temporal and spatial resolution nano-thermometers aiming at precise studying heat generation or diffusion in numerous biological and technology applications.

Matrix engines or units, in different forms and affinities, are becoming a reality in modern processors; CPUs and otherwise. The current and dominant algorithmic approach to Deep Learning merits the commercial investments in these units, and deduced from the No.1 benchmark in supercomputing, namely High Performance Linpack, one would expect an awakened enthusiasm by the HPC community, too. Hence, our goal is to identify the practical added benefits for HPC and machine learning applications by having access to matrix engines. For this purpose, we perform an in-depth survey of software stacks, proxy applications and benchmarks, and historical batch job records. We provide a cost-benefit analysis of matrix engines, both asymptotically and in conjunction with state-of-the-art processors. While our empirical data will temper the enthusiasm, we also outline opportunities to misuse these dense matrix-multiplication engines if they come for free., Comment: IEEE International Parallel and Distributed Processing Symposium 2021 (IPDPS'21)

The dedicated memory of hardware accelerators can be insufficient to store all weights and/or intermediate states of large deep learning models. Although model parallelism is a viable approach to reduce the memory pressure issue, significant modification of the source code and considerations for algorithms are required. An alternative solution is to use out-of-core methods instead of, or in addition to, data parallelism. We propose a performance model based on the concurrency analysis of out-of-core training behavior, and derive a strategy that combines layer swapping and redundant recomputing. We achieve an average of 1.52x speedup in six different models over the state-of-the-art out-of-core methods. We also introduce the first method to solve the challenging problem of out-of-core multi-node training by carefully pipelining gradient exchanges and performing the parameter updates on the host. Our data parallel out-of-core solution can outperform complex hybrid model parallelism in training large models, e.g. Megatron-LM and Turning-NLG., Comment: ACM/IEEE Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'20)

We calculate the Grothendieck group $K_0(\cal A)$, where $\cal A$ is an additive category, locally finite over a Dedekind ring and satisfying some additional conditions. The main examples are categories of modules over finite algebras and the stable homotopy category $\mathsf{SW}$ of finite CW-complexes. We show that this group is a direct sum of a free group arising from localizations of the category $\cal A$ and a group analogous to the groups of ideal classes of maximal orders. As a corollary, we obtain a new simple proof of the Freyd's theorem describing the group $K_0(\mathsf{SW})$., Comment: 21 pages

Space Time Block Codes (STBCs) from orthogonal designs have attracted significant interest in recent years. However, with the growing demand for higher capacity schemes, the multiantenna transmission techniques must support and achieve higher symbol transmission rates. In this article, we focus on three and four transmit antenna schemes. For over two decades, STBC schemes for three and four transmit antennas that achieve a very high symbol transmission rate while being orthogonal, fully diverse, delay-efficient, and with very low decoding complexity have not been achieved. The schemes proposed so far trades off orthogonality, delay, diversity, or decoding complexity while achieving rate or vice-versa. This work is first of its kind to solve this problem while fulfilling all the desired properties. In this work, we carefully study the various aspects that must be considered in designing higher symbol transmission rate STBCs. The proposed designs, hereby referred to as, Jagannath schemes - for 4 x 3 and 4 x 4 configurations are orthogonal, achieve full diversity, and support a symbol transmission rate of 2 symbols/s/Hz. The design methodology follows a coding gain maximization approach. The low decoding complexity procedure to decode the proposed transmission schemes are proposed as well as extensively evaluated in simulations under diverse settings. The performance of proposed schemes are empirically compared to two state-of-the-art schemes; ACIOD and Jafarkhani. Jagannath 4 x 3 was shown to outperform ACIOD by ~12 dB while Jagannath 4 x 4 exhibited a ~7 dB superior performance in contrast to Jafarkhani at 4 bpcu. This motivates the adoption of Jagannath schemes in tactical and commercial communication systems to effectively double the throughput or to extend the, Comment: Revising for re-submission. Some Flaws detected based on review

Multiple-input multiple-output (MIMO) systems find immense potential and applicability in the long term evolution (LTE), 5G, Internet of Things (IoT), vehicular ad hoc networks (VANETs), and tactical communication systems. Jamming poses significant communication hindrance as well as security risks to the wireless communication systems. The achievable rate and reliability are the two most compromised aspects of a wireless link under such severe jamming. Owing to the high capacity and reliability of MIMO systems, they are increasingly used in tactical and critical applications. Therefore, it becomes essential to assess and enhance their sustenance under hostile jamming scenarios. To this end, we address the rate and reliability requirements of a MIMO OFDM system and propose a novel rate-reliability beamformer transceiver design for highly reliable and spectrally efficient operation under the most detrimental jamming attacks. We consider the disguised all band and multiband jamming where the jammer continuously attempts to mimic the legit transmissions. Additionally, we evaluate the rate and reliability performance under barrage jamming. The significant contributions of the proposed rate-reliability beamformer scheme are: (i) achieves a minimum of 2 orders of magnitude better reliability in contrast to the state-of-the-art, (ii) outperforms the state-of-the-art scheme by 1.4x with regards to achievable spectral efficiency, (iii) a very low complexity (O(|Q|)) decoder is presented, and (iv) first work to evaluate the performance of state-of-the-art transmit diversity scheme under hostile jamming attacks., Comment: Accepted to 29th International Conference on Computer, Communication and Networks (ICCCN)

We study the behaviour of almost split sequences and \art quivers of an order under rejection of bijective modules. In particular, we establish relations of stable categories and almost split sequences for an order $A$ and the order $A'$ obtained from $A$ by such rejection. These results are specified for Gorenstein and Frobenius cases., Comment: 23 pages

We report on strong pretransitional effects across the isotropic liquid-plastic crystal melting temperature in linear and nonlinear dielectric response. Studies were carried out for cyclooctanol (C8H16O) in the unprecedented range of temperatures 120 K < T < 345 K. Such pretransitional effects have not yet been reported in any plastic crystals. Results include the discovery of the experimental manifestation of the Mossotti Catastrophe behavior, so far considered only as a hypothetical paradox. The model interpretations of experimental findings are proposed. We parallel the observed pretransitional behavior with the one observed in octyloxycyanobiphenyl (8OCB), typical liquid crystal (LC), displaying a reversed sequence of phase transitions in orientational and translational degrees of order on varying temperature. Furthermore, in its nematic phase, we demonstrate first-ever observed temperature-driven crossover between regions dominated by isotropic liquid and smectic A pretransitional fluctuations. We propose a pioneering minimal model describing plastic crystal phase behavior where we mimic derivation of classical Landau-de Gennes-Ginzburg modelling of Isotropic - Nematic - Smectic A LC phase behavior.