Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Regularized Reconstruction Algorithm Based on Compressed Sensing for the Sparse Underdetermined Problem and Applications of One-Dimensional and Two-Dimensional Signal Recovery

The compressed sensing theory has been widely used in solving undetermined equations in various fields and has made remarkable achievements. The regularized smooth L0 (ReSL0) reconstruction algorithm adds an error regularization term to the smooth L0(SL0) algorithm, achieving the reconstruction of the signal well in the presence of noise. However, the ReSL0 reconstruction algorithm still has some flaws. It still chooses the original optimization method of SL0 and the Gauss approximation function, but this method has the problem of a sawtooth effect in the later optimization stage, and the convergence effect is not ideal. Therefore, we make two adjustments to the basis of the ReSL0 reconstruction algorithm: firstly, we introduce another CIPF function which has a better approximation effect than Gauss function; secondly, we combine the steepest descent method and Newton method in terms of the algorithm optimization. Then, a novel regularized recovery algorithm named combined regularized smooth L0 (CReSL0) is proposed. Under the same experimental conditions, the CReSL0 algorithm is compared with other popular reconstruction algorithms. Overall, the CReSL0 algorithm achieves excellent reconstruction performance in terms of the peak signal-to-noise ratio (PSNR) and run-time for both a one-dimensional Gauss signal and two-dimensional image reconstruction tasks.
Automatic program debugging for intelligent tutoring systems

Program debugging is an important part of the domain expertise required for intelligent tutoring systems that teach programming languages. This article explores the process by which student programs can be automatically debugged in order to increase the instructional capabilities of these systems. The research presented provides a methodology and implementation for the diagnosis and correction of nontrivial recursive programs. In this approach, recursive programs are debugged by repairing induction proofs in the Boyer‐Moore logic. The induction proofs constructed and debugged assert the computational équivalence of student programs to correct exemplar solutions. Exemplar solutions not only specify correct implementations but also provide correct code to replace buggy student code. Bugs in student code are repaired with heuristics that attempt to minimize the scope of repair.
Data driven kernel choice in nonparametric curve estimation

Fur den Fall der eindimensionalen Kern-Dichteschatzung bei unabhangigen, identisch verteilten Beobachtungen wird eine Cross-Validation-Technik fur die Wahl des Kerns aus der Klasse aller $L_2$-integrierbaren Kernfunktionen mit unimodaler Fouriertransformierter vorgeschlagen. Der resultierende Schatzer ist sowohl asymptotisch MISE-effizient als auch asymptotisch minimax-adaptiv auf der gesamten Skala von Sobolev-Klassen mit Glattheitsindex groser als 1/2, einschlieslich $infty$. Die Beweise stutzen sich auf eine additive Zerlegung der betreffenden empirische Prozesse. Die Methode wird anschliesend auf die nichtparametrische Regressionsschatzung ubertragen. Das Minimax-Risiko auf Sobolev-Klassen mit nichtganzzahligen Glattheitsindex wird hergeleitet.
An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

Abstract. Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5∘×0.625∘) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.
A power adjusting anchors with improved localization algorithm for mobile wireless sensor networks

ABSTRACT In Mobile Wireless Sensor Networks (MWSNs), localization is one of the key technologies since it plays a critical role for many location-aware protocols and applications. Existing range-free localization algorithms for MWSNs are usually based on the Sequential Monte Carlo localization algorithm. They suffer from low sampling efficiency, high communication computation cost or require high beacon density to achieve high localization accuracy. In this paper, we propose a novel algorithm called ‘Power Adjusting Anchors’ that outperforms in terms of accuracy. In this algorithm, mobile sensor node localizes its position based on the received power levels transmitted by the neighbouring anchors and by constructing a refined prediction area with the hop-distance estimations between elected anchor nodes. This area will be divided into square grids, and sensor node selects all the grids which owns the highest elections, and then, computes the centroid of such grids. The calculated centroid is considered as the estimated location of the sensor node. In addition, the algorithm addresses the information state provided by the radio communication between sensor nodes and anchor nodes to the success of the localization. Simulation results show that the algorithm is very competitive by achieving high localization accuracy with better localization success.
Standard SAR ATR evaluation experiments using the MSTAR public release data set

The recent public release of high resolution Synthetic Aperture Radar (SAR) data collected by the DARPA/AFRL Moving and Stationary Target Acquisition and Recognition (MSTAR) program has provided a unique opportunity to promote and assess progress in SAR ATR algorithm development. This paper will suggest general principles to follow and report on a specific ATR performance experiment using these principles and this data. The principles and experiments are motivated by AFRL experience with the evaluation of the MSTAR ATR.
On the extended Stochastic Electrodynamics Interpretation of Quantum Mechanics

An extended version of Stochastic Electrodynamics (SED) which provides an interpretation of Quantum Mechanics free of its preternatural aspects is reviewed briefly. In addition, recent simulations of the hydrogen ground state based on SED which have been inconclusive are criticized for having employed only a restricted understating of the physical consequences of the hypothetical underpinning of SED.
Low profile high gain circular SIW antenna for L and S band applications

In this article, a circular substrate integrated waveguide (CSIW) antenna is proposed. Conventional log‐periodic antenna offers unidirectional and bidirectional radiation patterns that are used in two‐way communications provide moderate gain. The proposed antenna has the advantages of high gain, compact size, low loss, easy to integrate the high frequency components, and it also operates at L band and S band frequencies. To improve the gain and radiation characteristics, circular SIW is introduced and integrated with log‐periodic antenna. The comparison between simulated and measured results shows that the proposed antenna used for wireless communications both in L (1‐2 GHz) and in S (2‐4 GHz) frequency bands. It provides the bandwidth of 9.1%, 10%, 21.6%, and 11.03% and also the realized gain of 6.62 dB, 15.8 dB, 3.9 dB, and 8.3 dB is obtained in 1.2 GHz, 1.6 GHz, 2.4 GHz, and 2.9 GHz, respectively.
6D interaction control with aerial robots: The flying end-effector paradigm

This paper presents a novel paradigm for physical interactive tasks in aerial robotics allowing reliability to be increased and weight and costs to be reduced compared with state-of-the-art approaches. By exploiting its tilted propeller actuation, the robot is able to control the full 6D pose (position and orientation independently) and to exert a full-wrench (force and torque independently) with a rigidly attached end-effector. Interaction is achieved by means of an admittance control scheme in which an outer loop control governs the desired admittance behavior (i.e., interaction compliance/stiffness, damping, and mass) and an inner loop based on inverse dynamics ensures full 6D pose tracking. The interaction forces are estimated by an inertial measurement unit (IMU)-enhanced momentum-based observer. An extensive experimental campaign is performed and four case studies are reported: a hard touch and slide on a wooden surface, called the sliding surface task; a tilted peg-in-hole task, i.e., the insertion of the end-effector in a tilted funnel; an admittance shaping experiment in which it is shown how the stiffness, damping, and apparent mass can be modulated at will; and, finally, the fourth experiment is to show the effectiveness of the approach also in the presence of time-varying interaction forces.
Poling conditions influence on open circuit voltage of PbTiO3/pn-Si structure

Abstract A structure of pn junction with ferroelectric layer (PbTiO3/pn-Si, or PTO/pn cell) was prepared. Instability of open circuit voltage (Voc) was found in this structure. Voc of the cells will decrease rapidly in the first 40 minutes after poled. The pole condition influence of Voc was investigated. Results show that the instability of Voc comes from the polarization and depolarization effect of the PTO layer in the PTO/pn cells. Purely increasing the poling voltage and time cannot improve the stability of the cells significantly. Poling under high temperature (200 °C) is an efficient way to improve the stability of the cells. Finally variation width of Voc is modified from maximum about 80 mV (−16 V poled, 60 minutes) to about 17 mV (±16 V poled, 200 °C).
Fractal Characterization of Earthquake occurrences in Nigeria

Fractal characterization of Earthquake occurrences in Nigeria was carried out in order to know the b-value of tremor occurrences in the country. This will help in hazard analysis and research in the geological and geophysical structures of Nigeria. The method used in determining the b-value is the box counting method, but for simplicity, we used circle. The areas that are tremor prone were posted on a digitized Nigeria map using Google earth and Surfer 7.0 software. The computation with the box counting method was performed with picked radius of the circle from 50km - 350km and the average number of points that falls within each circle were recorded. The graph of log r (the logarithms of radius of circle or scale) against log (logarithms of average number of points) was plotted using grapher and excels Microsoft word and the slope of the graph was determined. The determined slope gave the fractal dimension and the b-value was thus calculated. In this work, a b-value of 0.6 was obtained indicating that Nigeria falls within seismically less active zone.
(Almost) matrix‐free solver for piecewise linear functions in abs‐normal form

The abs‐normal form (ANF) is a compact algebraic representation for piecewise linear functions. These functions can be used to approximate piecewise smooth functions and contain valuable information about the nonsmoothness of the investigated function. The information helps to define step directions within general Newton methods that obey the structure of the original function and typically yield better convergence. However, the computation of the generalized Newton directions requires the solution of a piecewise linear equation in ANF. It was observed that the ANF can become very large, even for simple functions. Hence, if a solver is based on the ANF and uses the (Schur‐complement) matrices of the explicit ANF representation, it has to be considered computationally expensive. In this paper, we will address this question and present the first (almost) matrix‐free versions of some solver for ANFs. The theoretical discussion is supported by some numerical run‐time experiments.
An FPGA-Based Fast Linear Discharge Readout Scheme Enabling Simultaneous Time and Energy Measurements for TOF-PET Detectors

The readout electronics in time-of-flight positron emission tomography (TOF-PET) detector modules conventionally contain a separate timing circuit and a separate energy measurement circuit. For channel-by-channel readouts, the front-end electronics will be unacceptably large and must rely on application specific integrated circuit (ASIC) chips. In this paper, we present a novel field programmable gate array (FPGA)-based readout scheme that unifies the time and energy measurements with only one analog amplifier per channel in addition to the FPGA. By constructing a simple and effective fast linear discharge circuit, one time-to-digital converter (TDC) per channel can implement time and energy readouts simultaneously with a short measurement dead time. To evaluate the performance of the new approach, a 16-channel PET detector module consisting of LYSO crystals coupled with a silicon photomultiplier (SiPM) array was constructed connecting to the readout electronics. Using a reference detector with a 164.7-ps time resolution to perform 22Na coincidence measurements, the average energy, and time resolution among 16 channels were measured as 12.44% and 372.6 ps, respectively. The typical measurement dead time is approximately 300 ns. The test results show the simplicity and feasibility of the proposed readout scheme, which is particularly useful for laboratory instrumentation.
Integrated track splitting-component merging history for efficient target tracking

The Integrated Track Splitting (ITS) filter is a method for automatic target tracking in clutter. The ITS filter models each track as a set of components, where each component is defined with a unique measurement history which consists of zero or one measurement received each scan. Regarding to clutter density and tracking parameters, a component merging is used for the reason of computational complexity reducing. For each component the state estimate and the a-posteriori probability of component existence are computed recursively. The probability of the new component existence is the probability that the parent component exists and that the measurement used to create the new component is the target measurement. The probability of target existence, mean and covariance of the state estimate for the track are then calculated and used for track maintenance and track output. Using an extensive Monte Carlo simulation, the various parameters (probability of track elimination and confirmation, probability of detection) are changed to obtain the optimal depth of component merging history (CMH), numbers of confirmed false track or lost tracks that each produces. The article is having a practical contribution while approve which depth of CMH is needed for the specific tracking situation.
Using Betteraccent Tutor and Praat for Learning English Intonation

Learning English pronunciation necessitates a deep understanding of the prosodic features such as intonation. The present study reports the effective use of BetterAccent Tutor and Praat programs for the learning of English intonation with an experimental and a control group that involves nine students during a third semester phonetics course, at the Department of English, University of Guelma, Algeria. The research aims at investigating the usability of audio-visual feedback paradigm to learn prosody by Algerian students in order to enhance their English intonation renditions. The experimental method enabled generating, measuring and analyzing intonation contours, pitch and intensity of English wh-questions and tag-questions. The results revealed that the audio-visualization technology support helped the students to identify the errors and to understand the functionality of acoustic features they produce regarding intonation patterns.
Effects of Wood Species and Log Diameter on Veneer Recovery

The total plywood production depends on veneer production due to log consumption. The ratio of veneer volume to log volume was stated as veneer recovery. The veneer recovery was affected by wood species and log diameter. Three wood species of Shorea selanica, Terminalia catapa and Duabanga moluccana were used in this experiment with four levels of log diameters. This experiment used the split block design and orthogonal polynomial analyses for equal space. The statistical analysis shows that wood species, log diameter and their interaction gave significance to highly significant effects on veneer recovery. The regression model for effect of log diameter (X) on veneer recovery (Y) by orthogonal polynomial analysis was Y = 34.373+ 0.429 X, with R 2 = 0.7366
Unsupervised Network Anomaly Detection

In this paper we present a completely unsupervised approach to detect attacks, without relying on signatures, labeled traffic, or training. The unsupervised detection of network attacks represents an extremely challenging goal. The structure of the anomaly identified by the clustering algorithms is used to automatically construct specific filtering rules that characterize its nature, providing easy-to-interpret information to the network operator. In addition, these rules are combined to create an anomaly signature, which can be directly exported towards standard security devices like IDSs, IPSs, and/or Firewalls.
Imaging Simulator and Geometric Image Stitching for a Low Earth Orbit Satellite with High Spin Rates

ESTCube-2 on maalahedase orbiidiga satelliit mille pohieesmargiks on elektrilise paikesepurje tehnoloogia traadi valja kerimine ja katsetamine. Korvaline missioon on pinnase taimestiku pildistamine. Traadi valja kerimine ja alal hoidmine vajab aarmiselt suurt poordesagedust, mis esitab mitmeid valjakutseid olemasolevale pildistamise alamsusteemile. Selle probleemi lahendamiseks on valja toodud uus pildimoondus ja -omblus algoritm, mis kasutab geomeetriat piltide kaardistamiseks. Estitatud meetodit katsetati spetsiaalselt loodud simulatsioonikeskonnas, mis jaljendab kaamera parameetreid. Soltumata suurest poordesagedusest tingitud moonutustustest, tootas pilditootlus algoritm soovitud vahemikus.
Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system

Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.
Flexible, Free Software for Multilevel Multiple Imputation: A Review of Blimp and jomo

Multiple imputation is a popular method for addressing data that are presumed to be missing at random. To obtain accurate results, one’s imputation model must be congenial to (appropriate for) one’s intended analysis model. This article reviews and demonstrates two recent software packages, Blimp and jomo, to multiply impute data in a manner congenial with three prototypical multilevel modeling analyses: (1) a random intercept model, (2) a random slope model, and (3) a cross-level interaction model. Following these analysis examples, I review and discuss both software packages.
FPGA implementation of a LSTM Neural Network

Este trabalho pretende fazer uma implementacao customizada, em Hardware, duma Rede Neuronal Long Short-Term Memory. O modelo python, assim como a descricao Verilog, e sintese RTL, encontram-se terminadas. Falta apenas fazer o benchmarking e a integracao de um sistema de aprendizagem.