Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncertainty in Material Characterization Using the Hessian and Filled Waveguide Method

This paper examines an error model that can predict the uncertainty in the electromagnetic material properties $(\epsilon_{r}=\epsilon_{r}^{\prime}-j\epsilon_{r}^{\prime\prime})$ obtained through a curve fitting algorithm. Using a model of the measurement method (filled waveguide, open-ended waveguide, etc.), the algorithm optimizes the material properties to match the scattering parameters obtained through measurements. Utilizing the Jacobian from the optimizer, we can calculate the Hessian matrix of the material properties $(\epsilon_{r})$. This matrix is then used to determine the expected standard deviation in the material properties for the given measurement method. The uncertainty model formulated in this paper is applied to the filled waveguide technique with measurements taken at X-band (8.2-12.4 GHz). Measurements of several materials with known properties are performed to evaluate the uncertainty model by comparing the predicted uncertainty to the error in the calculated materials over the frequency band. In addition, we explore several sources of uncertainty when performing measurements and their impact on the material properties that the algorithm calculates.
Reachable Coverage: Estimating Saturation in Fuzzing

Reachable coverage is the number of code elements in the search space of a fuzzer (i.e., an automatic software testing tool). A fuzzer cannot find bugs in code that is unreachable. Hence, reachable coverage quantifies fuzzer effectiveness. Using static program analysis, we can compute an upper bound on the number of reachable coverage elements, e.g., by extracting the call graph. However, we cannot decide whether a coverage element is reachable in general. If we could precisely determine reachable coverage efficiently, we would have solved the software verification problem. Unfortunately, we cannot approach a given degree of accuracy for the static approximation, either. In this paper, we advocate a statistical perspective on the approximation of the number of elements in the fuzzer's search space, where accuracy does improve as a function of the analysis runtime. In applied statistics, corresponding estimators have been developed and well established for more than a quarter century. These estimators hold an exciting promise to finally tackle the long-standing challenge of counting reachability. In this paper, we explore the utility of these estimators in the context of fuzzing. Estimates of reachable coverage can be used to measure (a) the amount of untested code, (b) the effectiveness of the testing technique, and (c) the completeness of the ongoing fuzzing campaign (w.r.t. the asymptotic max. achievable coverage). We make all data and our analysis publicly available.
A Compact Model Of Off-Grid Micro-Hydro Generation, Low Impact And Accessible In Remote Areas

To reduce energy shortages in remote sectors, it is necessary to increase the availability of energy from renewable sources. This research work develops an off-grid micro-hydro ($\mu HG $) generation model in a proposed study object, sending the power to a three-phase resistive system through a dc link, to evaluate the generation parameters and total harmonic distortion (THD) in the supply. The purpose of the hydraulic model focuses on considering the efficiency factors of the circuit using the Darcy-Weisbach and Hazen-Williams methods to estimate the load losses in each part of the system. The simulation of the hydraulic system is carried out in the “Fluid Flow” program. A PID controller is developed for speed regulation in the coupling shaft and regulation control in the excitation of the synchronous generator by adjusting the power delivery parameters in a stable way. The generated power is converted to dc by means of three-phase uncontrolled rectification and connected to the low voltage direct current (LVDC) link of single-pole-symmetrical topology, sending two lines to the terminals of the sinusoidal pulse width modulation (SPWM) inverter to transfer the ac power to the load. The simulation of the systems is carried out in the “MATLAB-Simulink” program.
Proximal Minimization Algorithm with D-Functions 1'2

The original proximal minimization algorithm employs quadratic additive terms in the objectives of the subproblems. In this paper, we replace these quadratic additive terms by more general D- functions which resemble (but are not strictly) distance functions. We characterize the properties of such D-functions which, when used in the proximal minimization algorithm, preserve its overall convergence. The quadratic case as well as an entropy-oriented proximal minimization algorithm are obtained as special cases.
Study on Voltage Influence on FPGA-Based Time-to-Digital Converters

Field programmable gate arrays (FPGAs) based time-to-digital converters (TDCs) have been broadly investigated and widely used in recent years. However, voltage variations on the power distribution network (PDN) of FPGA are significantly affecting and sometimes devastating to the TDC performance. In this paper, we experimentally measure the performance changes of the tapped delay line (TDL) based TDC under conditions that the PDN has static and transient voltage variations and analyze the voltage influences theoretically. The test results show 0.2%/mV degradation of the TDC resolution with voltage drop and 12%1mV deterioration of the average RMS precision with voltage deviation from typical. Besides, performance degradation due to transient voltage fluctuations caused by switching activities of adjacent digital circuits is also experimentally demonstrated. In particular, the RMS precision exhibits periodic deterioration with the measured time interval, which can be reasonably explained in theory. For the influence coming from static voltage variations, we find the performance change can be greatly suppressed by the dynamic calibration method. However, for the influence coming from voltage transients, the performance degradation is inevitable, which raises a warning for FPGA management, especially for multi-tenant FPGAs where multiple untrusting cloud users simultaneously reside in a single FPGA. The test results and theoretical analysis in this paper can guide system optimization and real-time correction to reduce the impact of voltage transients.
X-IO: A High-performance Unified I/O Interface using Lock-free Shared Memory Processing

Cloud-native microservice applications use different communication paradigms to network microservices, including both synchronous and asynchronous I/O for exchanging data. Existing solutions depend on kernel-based networking, incurring significant overheads. The interdependence between microservices for these applications involves considerable communication, including contention between multiple concurrent flows or user sessions. In this paper, we design X-IO, a high-performance unified I/O interface that is built on top of shared memory processing with lock-free producer/consumer rings, eliminating kernel networking overheads and contention. X-IO offers a feature-rich interface. X-IO’s zero-copy interface supports building provides truly zero-copy data transfers between microservices, achieving high performance. X-IO also provides a POSIX-like socket interface using HTTP/REST API to achieve seamless porting of microservices to X-IO, without any change to the application code. X-IO supports concurrent connections for microservices that require distinct user sessions operating in parallel. Our preliminary experimental results show that X-IO’s zero-copy interfaces achieve 2.8x-4.1x performance improvement compared to kernel-based interfaces. Its socket interfaces outperform kernel TCP sockets and achieve performance close to UNIX-domain sockets. The HTTP/REST APIs in X-IO perform 1.4 x-2.3 x better than kernel-based alternatives with concurrent connections.
On Some Properties of the Max Algebra System Over Tensors

Recently we generalized the max algebra system to the class of nonnegative tensors. In this paper we give some basic properties for the left (right) inverse, under the new system. The existence of order 2 left (right) inverse of tensors is characterized. Also we generalize the direct product of matrices to the direct product of tensors (of the same order, but may be different dimensions) and investigate its properties relevant to the spectral theory.
The Nature of Compact Sources Selected by LOFAR

Radio-loud active galactic nuclei (RLAGN) produce jets on large scales heating their local environments and preventing the hot phase of baryonic matter from cooling hence slowing or halting galaxy formation and evolution; a model popularly known as AGN feedback. To understand this model, new views of low-luminosity compact RLAGN inhabiting massive galaxies have been obtained using the new LOw Frequency ARray (LOFAR) northern-sky radio survey LoTSS (LOFAR Two Metre Sky Survey) to study RLAGN in the local Universe at low frequencies (150 MHz). In this thesis, I investigate lowluminosity compact RLAGN selected from LoTSS first Data Release (DR1) in an attempt to reveal their radio morphologies and the physical scales at which they affect the inter-galactic medium (IGM) of the host galaxy on sub-kpc scales. We have conservatively selected 55 low-luminosity compact RLAGN based on LoTSS DR1 within redshift range 0.03 < z < 0.1. I show using high-frequency Jansky Very Large Array (VLA) observations that only 9 out of 55 objects show extended radio emission (1−3 kpc), 43 are compact at the limiting angular resolution of 0.35 arcsec (corresponding to projected maximum physical sizes of < 1 kpc), while 3 are undetected. The extended objects display a wide range of radio morphologies on smaller angular scales: doubles (3), two-sided jets (3), one-sided jets (2), and complex (1). I discuss their radio spectra which range from steep to flat and/or inverted radio spectra (−1.31 < α < 0.36) and span the range seen in various compact RLAGN such as compact symmetric objects (CSOs), compact steep spectrum (CSS) sources, and gigahertz peaked-spectrum (GPS) sources. Assuming synchrotron self-absorption (SSA) models for flat and/or inverted radio spectrum sources, I predict the physical sizes of 35 RLAGN to be between 2−53 pc. On their position on the power-linear size (P −D) diagram, we see that these objects populate the bottom left lower-end of the diagram; this position corresponds to the low-radio power CSOs. Finally, I compare their radio properties with those of the Fanaroff-Riley class 0 (‘FR0’) sources. Interestingly, some of the compact RLAGN presented in this thesis show extended radio emission in the second Data Release (DR2) images; these appear to be in fact the radio cores of low-luminosity yet extended Fanaroff-Riley (FRI/FRII) sources that could populate the right-lower end of the P −D diagram, limited by LOFAR’s surface brightness. Could we be underestimating the sizes of some of these compact objects? Continued VLBI observations of LOFAR sources could help us answer this question, which in turn will help us further understand AGN feedback.
FusedF0: Improving DNN-based F0 Estimation by Fusion of Summary-Correlograms and Raw Waveform Representations of Speech Signals

DSP-based F0 estimation algorithms, such as multi-band summary-correlogram (MBSC), are robust to noisy speech. Recent studies show that mapping from raw waveform segments into F0 estimates by DNNs can outperform DSP-based methods in F0 estimation. However, generalization and noise robustness of DNNs have not been fully addressed previously. We propose a hybrid DSP and DNN based approach to F0 estimation. Key contributions include: (a) a modified version of MBSC that is substantially faster than the original algorithm while maintaining the accuracy of F0 estimates; (b) a method for fusing DSP features with raw waveform representations using a DNN architecture to obtain noise-robust F0 estimation; (c) demonstrating that auxiliary DSP features improve generalization with a relatively small number of DNN parameters. On the PTDB-TUG database, the proposed algorithm outperforms the MBSC and CREPE DNN baselines (including optimized versions) for clean and noisy speech at 20, 10, and 0 dB SNR.
LogicDP: Creating Labels for Graph Data via Inductive Logic Programming

Graph data, such as scene graphs and knowledge graphs, see wide use in AI systems. In real-world and large applications graph data are usually incomplete, motivating graph reasoning models for missing-fact or missing-relationship inference. While these models can achieve state-of-the-art performance, they require a large amount of training data. Recent years have witnessed the rising interest in label creation with data programming (DP) methods, which aim to generate training labels from heuristic labeling functions. However, existing methods typically focus on unstructured data and are not optimized for graphs. In this work, we propose LOGICDP, a data programming framework for graph data. Unlike existing DP methods, (1) LOGICDP utilizes the inductive logic programming (ILP) technique and automatically discovers the labeling functions from the graph data; (2) LOGICDP employs a budget-aware framework to iteratively refine the functions by querying an oracle, which significantly reduces the human efforts in function creations. Experiments show that LOGICDP achieves better data efficiency in both scene graph and knowledge graph reasoning tasks.
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates

Abstract. The cosmogenic radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Combining 7Be and 10Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the influence of radionuclide production uncertainties on simulations. Here we use the GEOS-Chem chemical transport model driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis to simulate 7Be and 10Be with the state-of-the-art production rate from the CRAC:Be (Cosmic Ray Atmospheric Cascade: Beryllium) model considering realistic spatial geomagnetic cutoff rigidities (denoted as P16spa). We also perform two sensitivity simulations: one with the default production rate in GEOS-Chem based on an empirical approach (denoted as LP67) and the other with the production rate from the CRAC:Be but considering only geomagnetic cutoff rigidities for a geocentric axial dipole (denoted as P16). The model results are comprehensively evaluated with a large number of measurements including surface air concentrations and deposition fluxes. The simulation with the P16spa production can reproduce the absolute values and temporal variability of 7Be and 10Be surface concentrations and deposition fluxes on annual and sub-annual scales, as well as the vertical profiles of air concentrations. The simulation with the LP67 production tends to overestimate the absolute values of 7Be and 10Be concentrations. The P16 simulation suggests less than 10 % differences compared to P16spa but a significant positive bias (∼18 %) in the 7Be deposition fluxes over East Asia. We find that the deposition fluxes are more sensitive to the production in the troposphere and downward transport from the stratosphere. Independent of the production models, surface air concentrations and deposition fluxes from all simulations show similar seasonal variations, suggesting a dominant meteorological influence. The model can also reasonably simulate the stratosphere–troposphere exchange process of 7Be and 10Be by producing stratospheric contribution and 10Be/7Be ratio values that agree with measurements. Finally, we illustrate the importance of including the time-varying solar modulations in the production calculation, which significantly improve the agreement between model results and measurements, especially at mid-latitudes and high latitudes. Reduced uncertainties in the production rates, as demonstrated in this study, improve the utility of 7Be and 10Be as aerosol tracers for evaluating and testing transport and scavenging processes in global models. For future GEOS-Chem simulations of 7Be and 10Be, we recommend using the P16spa (versus default LP67) production rate.
The Subjunctive Mood In Kikisi, Kindendeule and Chingoni1

In the Bantu languages of Kikisi, Kindendeule and Chingoni, the subjunctive is a grammatical category that stands in contrast with the indicative mood. Morphologically, the subjunctive is characterized by the verbal suffix -e (or some other variants), absence of tense marking and the obligatory presence of the subject and/or object marker. Two types of subjunctive are illustrated (Quer, 2005; Stowell, 1993): (i) Intentional subjunctives that are triggered by matrix predicates and (ii) polarity subjunctives that are licensed by some operator. The subjunctive is associated with irrealis-inducing environments such as irrealis-inducing adverbs and complements of manipulative verbs (Givon, 1994). This paper argues that the subjunctive ambiguously exhibits Inflection or Tense features as well as COMP features. With respect to Inflection features, the subjunctive is in complementary distribution with tense marking. However, it displays COMP features in its selectional relations with the superordinate volitional and directive predicates. This ambiguity is accounted for if we adopt Rizzi’s (1997) proposal of an articulated CP. The Inflection features are FinP features and the COMP features ForceP features, which are all on the left periphery.
Intrafraction Motion Management in Cyberknife SRS with 6D-Skull Tracking

Datasets of five patients with intracranial targets treated with CyberKnife VSI using customized, non-invasive frameless thermoplastic cast based immobilization were analyzed. Standard CyberKnife couch for correcting positional offsets and 6D-skull tracking for detecting and correcting intrafraction shifts was used. For each sequential pair of images, the correction to the target position (position “offset”) was determined in six-degrees of motion (3 translations and 3 rotations). In all, 175 intrafraction positional offsets were analyzed to calculate the intrafraction shifts. Mean shifts, standard deviations, and range of shifts were estimated.
Optimal control for networked control systems with disturbances: a delta operator approach

This study deals with the optimal control problem for a class of delta-domain networked control systems (NCSs) subjected to both matched and unmatched disturbances. In the presence of the disturbances, the so-called ϵ -optimum is proposed to quantify the control performance. The purpose of the addressed problem is to design the optimal control strategy such that the cost function is minimised over the finite-/infinite-horizon under the network-induced constraints. In virtue of the dynamic programming method, sufficient conditions are established to guarantee the existence of the desired control strategies, and the controller parameters are designed. For the obtained optimal control strategy, an upper bound for the ϵ -optimum is provided explicitly, and convex optimisation algorithms are given to compute such upper bound. Both simulation and experimental results are provided to illustrate the usefulness and applicability of the proposed methods.
Interferometry in diffusive systems: Theory, limitation to its practical application and its use in Bayesian estimation of material properties

Interferometry in geosciences uses mathematical tec hniques to image subsurface properties. This method turns a receiver in to a vi rtual source through utilizing either random noises or engineered sources. The method in seismol ogy has been discussed extensively. Electromagnetic interferometry at high frequencies with coupled electromagnetic fields was developed in the past. However, the problem was not addressed for diffusive electromagnetic fields where the quasi-static limit holds. One of t he objectives of this dissertation was to theoretically derive the impulse response of the Ea rth for low-frequency electromagnetic fields. Applying the theory of interferometry in the regio ns where the wavefields are diffusive requires volumetrically distributed sources in an i nfinite domain. That precondition imposed by the theory is not practical in experiments. Hence, th aim of this study was to quantify the important areas and distribution of sources that ma kes it possible to apply the theory in practice through conducting numerical experiments. Results o f the numerical analysis in double halfspace models revealed that for surface-based explor ation scenarios sources are required to reside in a region with higher diffusivity. In contrast, w hen the receivers straddle an interface, as in borehole experiments, there is no universal rule fo r which region is more important; it depends on the frequency, receiver separation and also diff usivity contrast between the layers and varies
: Persisting volcanic ash

We would like to start by thanking both referees for their thoughtful reviews and constructive comments which have greatly helped to improve the manuscript. Before responding to the referee’s comments, we would first like to acknowledge that we received feedback from discussions outside of the official peer review and these have led to some additional improvements. Also, our work on other projects identified some improvements to our IASI post-processing which we then applied to our results here. We will discuss these changes first and then go on to address the reviewers' comments. We hope that the referees agree that these help to improve the manuscript.
Hierarchical Reinforcement Learning with Attention Reward

Hierarchical Reinforcement Learning (HRL) is a promising approach for complex tasks with greater sample efficiency because it can break a task into sets of short subtasks and provide a denser subgoal-related intrinsic reward, making credit assignments less challenging. However, none of the conventional subgoal-related intrinsic rewards utilize task-specified knowledge, which limits the sample efficiency of these HRL methods. We propose Hierarchical Reinforcement Learning with Attention Reward (HiAR) that motivates agents to focus on the part of the environment controlled by their actions. We introduce a measure of the control over each dimension in the state space and discuss how we integrated it into the HRL method to improve the sample efficiency