Minimizing Age of Information for Mobile Edge Computing Systems: A Nested Index Approach

Exploiting the computational heterogeneity of mobile devices and edge nodes, mobile edge computation (MEC) provides an efficient approach to achieving real-time applications that are sensitive to information freshness, by offloading tasks from mobile devices to edge nodes. We use the metric Age-of-Information (AoI) to evaluate information freshness. An efficient solution to minimize the AoI for the MEC system with multiple users is non-trivial to obtain due to the random computing time. In this paper, we consider multiple users offloading tasks to heterogeneous edge servers in a MEC system. We first reformulate the problem as a Restless Multi-Arm-Bandit (RMAB) problem and establish a hierarchical Markov Decision Process (MDP) to characterize the updating of AoI for the MEC system. Based on the hierarchical MDP, we propose a nested index framework and design a nested index policy with provably asymptotic optimality. Finally, the closed form of the nested index is obtained, which enables the performance tradeoffs between computation complexity and accuracy. Our algorithm leads to an optimality gap reduction of up to 40%, compared to benchmarks. Our algorithm asymptotically approximates the lower bound as the system scalar gets large enough

PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting

When predicting PM2.5 concentrations, it is necessary to consider complex information sources since the concentrations are influenced by various factors within a long period. In this paper, we identify a set of critical domain knowledge for PM2.5 forecasting and develop a novel graph based model, PM2.5-GNN, being capable of capturing long-term dependencies. On a real-world dataset, we validate the effectiveness of the proposed model and examine its abilities of capturing both fine-grained and long-term influences in PM2.5 process. The proposed PM2.5-GNN has also been deployed online to provide free forecasting service.Comment: Pre-print version of a ACM SIGSPATIAL 2020 poster [paper](https://dl.acm.org/doi/10.1145/3397536.3422208). The code is available at [Github](https://github.com/shawnwang-tech/PM2.5-GNN), and the talk is available at [YouTube](https://www.youtube.com/watch?v=VX93vMthkGM

Novel Wideband Metallic Patch Antennas with Low Profile

Two planar metallic patch (MP) antennas with low profiles are investigated and compared in this paper. The MP of each antenna consists of metallic patch cells and it is centrally fed by a rectangular slot. Two modes with close resonance frequencies are excited, providing a quite wide bandwidth. The antenna principle is explained clearly through a parametric study. Simulated and measured results show that the MP antennas with profile of 0.06λ0 can obtain a 10 dB impedance bandwidth of ~32% and an average gain of ~10 dBi

Text Injection for Capitalization and Turn-Taking Prediction in Speech Models

Text injection for automatic speech recognition (ASR), wherein unpaired text-only data is used to supplement paired audio-text data, has shown promising improvements for word error rate. This study examines the use of text injection for auxiliary tasks, which are the non-ASR tasks often performed by an E2E model. In this work, we use joint end-to-end and internal language model training (JEIT) as our text injection algorithm to train an ASR model which performs two auxiliary tasks. The first is capitalization, which is a de-normalization task. The second is turn-taking prediction, which attempts to identify whether a user has completed their conversation turn in a digital assistant interaction. We show results demonstrating that our text injection method boosts capitalization performance for long-tail data, and improves turn-taking detection recall

Low-degree melt metasomatic origin of heavy Fe isotope enrichment in the MORB mantle

Studies of mid-ocean ridge basalts (MORB) show a variable Fe isotope composition of the oceanic upper mantle. To test a recent hypothesis that heavy Fe isotope enrichment in the MORB mantle results from the same process of incompatible element enrichment, we conduct an Fe isotope study of well-characterized MORB samples from a magmatically robust segment (OH-1) of the Mid-Atlantic Ridge (MAR) at ∼ 35°N. The data show large Fe isotope variation (Fe = +0.03 to +0.18‰) that correlates well with the abundances and ratios of more-to-less incompatible elements and with Sr-Nd-Hf isotopes. Our findings in support of the hypothesis can be detailed as follows: (1) the oceanic upper mantle has a heterogeneous Fe isotope composition on varying small spatial scales with isotopically heavy Fe (high-Fe) preferentially associated with pyroxenite lithologies; (2) such lithologies, which are also enriched in the progressively more incompatible elements, are of low-degree (low-F) melt metasomatic origin; (3) with all the conceivable processes considered, the low-F melt metasomatism takes place at the lithosphere-asthenosphere boundary (LAB) beneath ocean basins through crystallization of incipient (Low-F) melt in the seismic low velocity zone (LVZ) at the base of the growing oceanic lithosphere (i.e., LAB) over the Earth's history since the onset of plate tectonics, forming composite lithologies with geochemically enriched pyroxenite veins dispersed in the depleted peridotite matrix; (4) such mantle of composite lithology when transported to beneath the present-day ocean ridges will undergo decompression melting and produce MORB melts with geochemical trends of “melting-induced mixing” as observed at the MAR and global MORB; (5) we predict all this to be a globally common process and widespread

Leakage Characteristic of Helical Groove Seal Designed in Reactor Coolant Pump

Helical groove seal is designed in reactor coolant pump to control the leakage along the front surface of the impeller face due to its higher resistance than the circumferentially grooved seal. The flow and the friction factors in helical groove seals are predicted by employing a commercial CFD code, FLUENT. The friction factors of the helical groove seals with helix angles varying from 20 deg to 50 deg, at a range of rotational speed and axial Reynolds number, were, respectively, calculated. For the helically grooved stator with the helix angle greater than 20 deg, the leakage shows an upward trend with the helix angle. The circumferentially grooved stator has a lower resistance to leakage than the 20 deg and 30 deg stators. It can be predicated that, for a bigger helix angle, the friction factor increases slightly with an increase in high axial Reynolds number, which arises from the high-pressure operation condition, and the friction factor is generally sensitive to changes in the helix angle in this operation condition. The study lays the theoretical foundation for liquid seal design of reactor coolant pump and future experimental study to account for the high-pressure condition affecting the leakage characteristic