Miracle-dz/UniFAR-FTUs huggingface dataset:
CAP-Net: Correspondence-Aware Point-view Fusion Network for 3D Shape Analysis

Learning 3D representations by fusing point cloud and multi-view data has been proven to be fairly effective. While prior works typically focus on exploiting global features of the two modalities, in this paper we argue that more discriminative features can be derived by modeling “where to fuse”. To investigate this, we propose a novel Correspondence-Aware Point-view Fusion Net (CAP-Net). The core element of CAP-Net is a module named Correspondence-Aware Fusion (CAF) which integrates the local features of the two modalities based on their correspondence scores. We further propose to ﬁlter out correspondence scores with low values to obtain salient local correspondences, which reduces redundancy for the fusion process. In our CAP-Net, we utilize the CAF modules to fuse the multi-scale features of the two modalities both bidi-rectionally and hierarchically in order to obtain more informative features. Comprehensive evaluations on popular 3D shape benchmarks covering 3D object classiﬁcation and retrieval show the superiority of the proposed framework.
Morphology, Sorting and Microclimates of Relict Sorted Polygons, Krkonoše Mountains, Czech Republic

The influence of past microclimates on the morphology and distribution of clasts is considered for relict large‐scale sorted polygons in the Krkonoše Mountains (Czech Republic). Sixty‐two sorted polygons with an average length of 194 cm and an average height of 21.5 cm were measured at four sites on Mt Luční hora, at elevations of 1455 to 1555 m asl. The polygons consist of tabular clasts with a mean length of 11 cm at the borders and 5 cm in the interiors. Smaller polygons are better sorted because of the shorter distances for the clasts to reach their borders. Polygons with greater relative height are better sorted due to more intensive slope processes associated with differential frost heaving. Better sorted and more domed polygons at higher altitudes suggest more severe and longer‐lasting microclimates suitable for the development of sorted polygons. The altitudinal gradient in polygon morphology and sorting suggests the dominant role of microclimate in the periglacial environment of the summit area of the Krkonoše Mountains during the Last Glacial/Holocene period. Polygon development probably involves positive feedback between morphology and frost susceptibility, driven by microclimate. The proposed method for evaluating frost sorting allows for rapid non‐invasive assessment of sorting using modern methods including high‐resolution remote sensing (especially terrestrial photogrammetry). Copyright © 2013 John Wiley & Sons, Ltd.
Multihoming Performance Benefits: An Experimental Evaluation of Practical Enterprise Strategies

Multihoming is increasingly being employed by large enterprises and data centers as a mechanism to extract good performance from their provider connections. Today, multihomed end-networks can employ a variety of commercial route control products to optimize performance over multiple ISP links. However, little is known about the mechanisms employed by such products and their relative trade-offs. In this paper, we propose and evaluate a wide range practical schemes that could go into the design of a route control device and analyze their trade-offs. We implement the proposed schemes on a Linux-based Web proxy and perform a trace-based emulation of their relative performance benefits. We show that both passive and active monitoring based techniques are equally effective and could improve Web performance by about 25% when compared to using a single provider. Another key observation is that the conventional practice of employing historical measurement samples to monitor and predict ISP performance could, in fact, result in sub-optimal performance.
Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data

Accurate crop yield assessments using satellite remote sensing-based methods are of interest for regional monitoring and the design of policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations is generally too coarse to capture cropland heterogeneity. The fusion of data from different sensors can provide enhanced information and overcome many of the limitations of individual sensors. In thitables study, we estimate annual crop yields for seven important crop types across Montana in the continental USA from 2008–2015, including alfalfa, barley, maize, peas, durum wheat, spring wheat and winter wheat. We used a satellite data-driven light use efficiency (LUE) model to estimate gross primary productivity (GPP) over croplands at 30-m spatial resolution and eight-day time steps using a fused NDVI dataset constructed by blending Landsat (5 or 7) and Terra MODIS reflectance data. The fused 30-m NDVI record showed good consistency with the original Landsat and MODIS data, but provides better spatiotemporal delineations of cropland vegetation growth. Crop yields were estimated at 30-m resolution as the product of estimated GPP accumulated over the growing season and a crop-specific harvest index (HIGPP). The resulting GPP estimates capture characteristic cropland productivity patterns and seasonal variations, while the estimated annual crop production results correspond favorably with reported county-level crop production data (r = 0.96, relative RMSE = 37.0%, p < 0.05) from the U.S. Department of Agriculture (USDA). The performance of estimated crop yields at a finer (field) scale was generally lower, but still meaningful (r = 0.42, relative RMSE = 50.8%, p < 0.05). Our methods and results are suitable for operational applications of crop yield monitoring at regional scales, suggesting the potential of using global satellite observations to improve agricultural management, policy decisions and regional/global food security.
Studies on ‘precarious rocks’ in the epicentral area of the AD 1356 Basle earthquake, Switzerland

SUMMARY For the first time precarious rocks have been analysed in the epicentral area of the AD 1356 Basle earthquake in northern Switzerland. Several cliff sites in flat-lying, thickly bedded Upper Jurassic coral limestones in the Jura Mountains were investigated. Seven blocks are regarded as precarious with respect to earthquake strong ground motions. The age of these precarious rocks could not be determined directly as for instance by radiometric dating methods; however, based on slope degradation processes it can be concluded that the formation of these blocks predates the AD 1356 Basle earthquake. The acceleration required to topple a precarious rock from its pedestal is estimated using geometrical data for individual block sections and earthquake strong-motion records from stations on rock sites in the European Strong-Motion Database as input data for the computer program ROCKING V1.0 from the Seismological Laboratory, University of Nevada, Reno. The calculations indicate that toppling of a precarious rock largely depends on earthquake strength but also on the frequency spectrum of the signal. Although most investigated precarious rocks are surprisingly stable for ground motions similar to those expected to have occurred during the AD 1356 Basle earthquake, at least two blocks are clearly precariously balanced, with peak toppling accelerations lower than 0.3 g. Possible reasons why these blocks did not topple during the AD 1356 Basle earthquake include incomplete separation from their base, sliding of precarious rocks, their size, lower than assumed ground accelerations and/or duration of shaking.
Eurographics Symposium on Geometry Processing (2007) Fast Normal Vector Compression with Bounded Error

We present two methods for lossy compression of normal vectors through quantization using " base " polyhedra. The first revisits subdivision-based quantization. The second uses fixed-precision barycentric coordinates. For both, we provide fast (de)compression algorithms and a rigorous upper bound on compression error. We discuss the effects of base polyhedra on the error bound and suggest polyhedra derived from spherical coverings. Finally, we present compression and decompression results, and we compare our methods to others from the literature.
Disentangling Human Error from Ground Truth in Segmentation of Medical Images

Recent years have seen increasing use of supervised learning methods for segmenta-1 tion tasks. However, the predictive performance of these algorithms depends on the 2 quality of labels. This problem is particularly pertinent in the medical image domain, 3 where both the annotation cost and inter-observer variability are high. In a typical la-4 bel acquisition process, different human experts provide their estimates of the “true” 5 segmentation labels under the inﬂuence of their own biases and competence levels. 6 Treating these noisy labels blindly as the ground truth limits the performance that 7 automatic segmentation algorithms can achieve. In this work, we present a method 8 for jointly learning, from purely noisy observations alone, the reliability of individual 9 annotators and the true segmentation label distributions, using two coupled CNNs. 10 The separation of the two is achieved by encouraging the estimated annotators to 11 be maximally unreliable while achieving high ﬁdelity with the noisy training data. 12 We ﬁrst deﬁne a toy segmentation dataset based on MNIST and study the properties 13 of the proposed algorithm. We then demonstrate the utility of the method on three 14 public medical imaging segmentation datasets with simulated (when necessary) and 15 real diverse annotations: 1) MSLSC (multiple-sclerosis lesions); 2) BraTS (brain 16 tumours); 3) LIDC-IDRI (lung abnormalities). In all cases, our method outperforms 17 competing methods and relevant baselines particularly in cases where the number 18 of annotations is small and the amount of disagreement is large. The experiments 19 also show strong ability to capture the complex spatial characteristics of annotators’ 20 mistakes, which could be potentially utilised for the purpose of education. 21
Development of semi-physically based model to predict erosion rate of kaolinite clay under different moisture content

Understanding the susceptibility of soils to concentrated flow erosion is imperative for predicting sustainability of various engineering structures and assessing environmental integrity. Currently, a widely used model is empirical in nature. In this study, we developed a semi-physically based model that predicts the rate of concentrated flow erosion of kaolinite clay based on tensile and erodibility characteristics. To develop this model, direct tensile tests and jet erosion tests (JETs) were performed on kaolinite clay with different percent moisture contents (MCs). The direct tensile test results showed that the energy required to break interparticle bonds across a fracture plane and tensile strength decreases with an increase in MC, whereas the JET results showed that soil resistance to erosion decreases with an increase in MC. Results also showed that an efficiency index of the JET apparatus, which represents the fraction of jet power used in actual erosion processes, diminishes with a decrease in MC.
A Parametric Analysis of Prompting Procedures to Encourage Electrical Energy Conservation

Prompting procedures frequently have been used to promote energy conservation. Very little is known about the parametric effects of variables associated with prompts, however, as most research has compared prompt and no-prompt conditions. In this research the parametric effects of frequency of prompts were examined. Five groups of college faculty received 1, 2, 3, 4, and 7 prompts, respectively, to turn off lights after classes. The data show that groups which received two or more prompts were more responsive than the group which received one prompt, but were not different from each other. Relating to other research, these results support the view that timing of prompts is more important than frequency. Needs for future research are outlined. Government, utilities and private interest groups rely heavily on the use of cognitive and affective appeals to encourage energy conservation. Frequently, such appeals involve providing information (e.g., "55 Save Lives") or are directed toward a sense of community spirit (e.g., "Give a Hoot, Don't Pollute"). Given the cost of such campaigns, it is necessary to determine the conditions under which such approaches are likely to be effective. With that information, it should be possible to design an optimal approach to solve a particular problem. Cognitive and affective appeals are prompts. Prompts are antecendent stimuli designed to evoke a response in a situation in which a response otherwise is not likely to occur [1-3]. Examples of prompts include brochures, notices, stickers, flyers, billboards, radio and television "spots" and other reminders of all kinds. Although prompts frequently are used with planned consequences, generally known as incentives, reinforcers or rewards, prompts often are used alone. In the simplest case, citizens are urged to change their lifestyle to save energy. The
Are faults preferential flow paths through semiarid and arid vadose zones?

Numerous faults crosscut the poorly lithified, basin‐fill sands found in New Mexico's Rio Grande rift and in other extensional regimes. The deformational processes that created these faults sharply reduced both fault porosity and fault saturated hydraulic conductivity by altering grains and pores, particularly in structures referred to as deformation bands. The resulting pore distribution changes, which create barriers to saturated flow, should enhance fault unsaturated flow relative to parent sand under the relatively dry conditions of the semiarid southwest. We report the first measurements of unsaturated hydraulic properties for undisturbed fault materials, using samples from a small‐displacement normal fault and parent sands in the Bosque del Apache Wildlife Refuge, central New Mexico. Fault samples were taken from a narrow zone of deformation bands. The unsaturated flow apparatus (UFA) centrifuge system was used to measure both relative permeability and moisture retention curves. We compared these relations and fitted hydraulic conductivity‐matric potential models to test whether the fault has significantly different unsaturated hydraulic properties than its parent sand. Saturated conductivity is 3 orders of magnitude less in the fault than the undeformed sand. As matric potential decreases from 0 to −200 cm, unsaturated conductivity decreases roughly 1 order of magnitude in the fault but 5–6 orders of magnitude in undeformed sands. Fault conductivity is greater by 2–6 orders of magnitude at matric potentials between −200 and −1000 cm, which are typical potentials for semiarid and arid vadose zones. Fault deformation bands have much higher air‐entry matric potential values than parent sands and remain close to saturation well after the parent sands have begun to approach residual moisture content. Under steady state, one‐dimensional, gravity‐driven flow conditions, moisture transport and solute advection is 102–106 times larger in the fault material than parent sands. Faults are sufficiently conductive to hasten the downward movement of water and solutes through vadose‐zone sands under semiarid and arid conditions like those in the Rio Grande rift, thereby potentially enhancing recharge, contaminant migration, and diagenesis.
Enhancing Fairness in AI-based Travel Demand Forecasting Models

Artiﬁcial Intelligence (AI) and machine learning have been increasingly adopted for forecasting real-time travel demand. These AI-based travel demand forecasting models, though generate highly-accurate predictions, may produce prediction biases and thus raise fairness issues. Using such models for decision-making, we may develop transportation policies that could exacerbate social inequalities. However, limited studies have been focused on addressing the fairness issues of AI-based travel demand forecasting models. Therefore, in this study, we propose a novel methodology to develop fairness-aware travel demand forecasting models, which are highly accurate and fair. Speciﬁcally, we add a fairness regularization term, i.e., the correlation between prediction accuracy and the protected attribute such as race or income, into the loss function of the travel demand forecasting model. We include an interactive weight coeﬃcient to both accuracy loss term and fairness loss term. The travel demand forecasting models can thus simultaneously account for prediction accuracy and fairness. An empirical analysis is conducted using real-world ridesourcing-trip data in Chicago. Results show that our proposed methodology eﬀectively addresses the accuracy-fairness trade-oﬀ. It can signiﬁcantly enhance fairness for multiple protected attributes (i.e., race, education, age and income) by only sacriﬁcing a small accuracy drop. This study provides transportation professionals a new type of decision-support tool to achieve fair and accurate travel demand forecasting.
Enhanced Line Search: A Novel Method to Accelerate PARAFAC

Several modifications have been proposed to speed up the alternating least squares (ALS) method of fitting the PARAFAC model. The most widely used is line search, which extrapolates from linear trends in the parameter changes over prior iterations to estimate the parameter values that would be obtained after many additional ALS iterations. We propose some extensions of this approach that incorporate a more sophisticated extrapolation, using information on nonlinear trends in the parameters and changing all the parameter sets simultaneously. The new method, called “enhanced line search (ELS),” can be implemented at different levels of complexity, depending on how many different extrapolation parameters (for different modes) are jointly optimized during each iteration. We report some tests of the simplest parameter version, using simulated data. The performance of this lowest-level of ELS depends on the nature of the convergence difficulty. It significantly outperforms standard LS when there is a “convergence bottleneck,” a situation where some modes have almost collinear factors but others do not, but is somewhat less effective in classic “swamp” situations where factors are highly collinear in all modes. This is illustrated by examples. To demonstrate how ELS can be adapted to different N-way decompositions, we also apply it to a four-way array to perform a blind identification of an under-determined mixture (UDM). Since analysis of this dataset happens to involve a serious convergence “bottleneck” (collinear factors in two of the four modes), it provides another example of a situation in which ELS dramatically outperforms standard line search.
Vowel Space as a Tool to Evaluate Articulation Problems

Treatment for oral tumors can lead to long term changes in the anatomy and physiology of the vocal tract and result in problems with articulation. There are currently no readily available automatic methods to evaluate changes in articulation. We developed a Praat script which plots and measures vowel space coverage. The script reproduces speaker specific vowel space use and speaking-style dependent vowel reduction in normal speech from a Dutch corpus. Speaker identity and speaking style explain more than 60% of the variance in the measured area of the vowel triangle. In recordings of patients treated for oral tumors, vowel space use before and after treatment is still significantly correlated. Articulation before and after treatment is evaluated in a listening experiment and from a maximal articulation speed task. Linear models can explain 50-75% of variance in perceptual ratings and relative articulation rate from values at previous recordings and vowel space measures.
Task-oriented Communication System Design in Cyber-Physical Systems: A Survey on Theory and Applications

Communication system design has been traditionally guided by task-agnostic principles, which aim at efﬁciently transmitting as many correct bits as possible through a given channel. However, in the era of cyber-physical systems, the effectiveness of communications is not dictated simply by the bitrate, but most importantly by the efﬁcient completion of the task in hand, e.g., controlling remotely a robot, automating a production line or collaboratively sensing through a drone swarm. In parallel, it is projected that by 2023 half of the worldwide network connections will be among machines rather than humans. In this context, it is crucial to establish a new paradigm for designing communications strategies for multi-agent cyber-physical systems. This is a daunting task, since it requires a combination of principles from information, communication, control theories and computer science theory in order to formalize a general framework for task-oriented communication design. In this direction, this paper reviews and structures the relevant theoretical work across a wide range of scientiﬁc communities. Subsequently, it proposes a general conceptual framework for task-oriented communication design, along with its specializations according to the targeted use case. Furthermore , it provides a survey of relevant contributions in dominant applications, such as of Industrial Internet of Things, multi-UAV systems, Tactile Internet and Federated Learning. Finally, it highlights the most important open research topics from both framework and application points of view.
DALE: A Word Sense Disambiguation System for Biomedical Documents Trained using Automatically Labeled Examples

Automatic interpretation of documents is hampered by the fact that language contains terms which have multiple meanings. These ambiguities can still be found when language is restricted to a particular domain, such as biomedicine. Word Sense Disambiguation (WSD) systems attempt to resolve these ambiguities but are often only able to identify the meanings for a small set of ambiguous terms. DALE (Disambiguation using Automatically Labeled Examples) is a supervised WSD system that can disambiguate a wide range of ambiguities found in biomedical documents. DALE uses the UMLS Metathesaurus as both a sense inventory and as a source of information for automatically generating labeled training examples. DALE is able to disambiguate biomedical documents with the coverage of unsupervised approaches and accuracy of supervised methods.