Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Environmental Benefits of Conservation Practices: The Conservation Effects Assessment Project (CEAP)-A Model Calibration Approach at the National Level

The purpose of the Conservation Effects Assessment Project (CEAP) is to provide people involved with environmental policy issues an accounting of the environmental benefits obtained from United States Department of Agriculture (USDA) conservation program expenditures. There are two main components in CEAP: (1) The national assessment and (2) watershed assessment. This paper will focus on the calibration aspects of modeling component of the national assessment part of the project. The primary focus of the project is on cropland where most of the conservation practices were implemented. Hence field level modeling for CEAP will be conducted by APEX (Agricultural Policy/Environmental eXtender). Outputs from the APEX model runs will be input to the watershed scale model Soil and Water Assessment Tool (SWAT) in HUMUS (Hydrologic Unit Modeling for the United States) setup to route flow, sediment, and pollutants to the outlet of each watershed in different agricultural regions. Environmental benefits at the national scale will be estimated based on the differences in output between the two scenarios “before conservation practices” and “after conservation practices”. In this modeling approach a calibration is necessary to compensate for the uncertainties in input data. The scale of the study, limits manual calibration. Hence an automated calibration procedure is developed to manage the large-scale calibration efforts. The auto-calibration procedure automatically adjusts the input parameters in HUMUS-SWAT so that the annual average stream flow and sediment yield values from HUMUS-SWAT system match to that of SPARROW (SPAtially Referenced Regression On Watershed attributes) model estimates for each 8-digit watershed.
An Experimental Study of Embodied Interaction and Human Perception of Social Presence for Interactive Robots in Public Settings

The human perception of robots as social depends on many factors, including those that do not necessarily pertain to a robot’s cognitive functioning. Experience design (ED) offers a useful framework for evaluating when participants interact with robots as products or tools and when they regard them as social actors. This paper describes a between-participants experiment conducted at a science museum, where visitors were invited to play a game of noughts and crosses with a Baxter robot. The goal is to foster meaningful interactions that promote engagement between the human and the robot in a museum context. Using an ED framework, we tested the robot in three different conditions to better understand which factors contribute to the perception of robots as social. The experiment also outlines best practices for conducting human–robot interaction research in museum exhibitions. Results from the study indicate that perceived social presence can be evaluated using a combination of human robot interaction and ED methods that measure co-presence and co-experience.
Multi-modal Interaction in Collaborative Virtual Environments: Study and analysis of performance in collaborative work. (Assistance multimodale pour l'interaction 3D collaborative : étude et analyse des performances pour le travail collaboratif)

The recent advancement in the field of high quality computer graphics and the capability of inexpensive computers to render realistic 3D scenes have made it possible to develop virtual environments where two or more users can co-exist and work collaboratively to achieve a common goal. Such environments are called Collaborative Virtual Environments (CVEs). The potential application domains of CVEs are many, such as military, medical, assembling, computer aided designing, teleoperation, education, games and social networks etc. One of the problems related to CVEs is the user's low level of awareness about the status, actions and intentions of his/her collaborator, which not only reduces users' performance but also leads to non satisfactory results. In addition, collaborative tasks without using any proper computer generated assistance are very dicult to perform and are more prone to errors. The basic theme of this thesis is to provide assistance in collaborative 3D interaction in CVEs. In this context, we study and develop the concept of multimodal (audio, visual and haptic) assistance of a user or group of users. Our study focuses on how we can assist users to collaboratively interact with the entities of CVEs. We propose here to study and analyze the contribution of multimodal assistance in collaborative (synchronous and asynchronous) interaction with objects in the virtual environment. Indeed, we propose and implement various multimodal virtual guides. These guides are evaluated through a series of experiments where selection/manipulation task is carried out by users both in synchronous and asynchronous mode. The experiments were carried out in LISA (Laboratoire d'Ingenierie et Systemes Automatises) lab at University of Angers and IBISC (Informatique, Biologie Integrative et Systemes Complexes) lab at University of Evry. In these experiments users were asked to perform a task under various conditions ( with and without guides). Analysis was done on the basis of task completion time, errors and users' learning. For subjective evaluations questionnaires were used. The ndings of this research work can contribute to the development of collaborative systems for teleoperation, assembly tasks, e-learning, rehabilitation, computer aided design and entertainment.
Radiance‐based validation of the V5 MODIS land‐surface temperature product

This paper presents the procedure and results of the radiance‐based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land‐Surface Temperature (LST) product. Surface emissivity spectra were retrieved by a sun‐shadow method from surface‐leaving radiance spectra measured with a thermal infrared (TIR) spectroradiometer in the 3.5–14 µm spectral region under sunshine and sun‐shadow conditions. By using the measured surface emissivity spectrum and atmospheric profiles obtained by radiosonde balloons, and the LST values at validation sites in the V5 MODIS level‐2 LST products, radiative transfer simulations were made with the MODTRAN4 code to calculate the top‐of‐atmosphere (TOA) radiance values in MODIS band 31 (L31). By adjusting the LST input values in the simulations to match the calculated L31 values to the MODIS measured radiance (MOD L31) values, MOD L31 inverted LSTs can be obtained. The MODIS LST product was validated by comparison to the values of the MOD L31 inverted LSTs. This approach compares well with the conventional temperature‐based approach. The results of the radiance‐based validation indicate that the accuracy of the MODIS LST product is better than 1 K in most cases, including lake, vegetation and soil sites in clear‐sky conditions. The errors in the split‐window retrieved LSTs may be larger in bare soil sites and highly heterogeneous sites due to large uncertainties in surface emissivities. The results of the radiance‐based validation also reveal the weakness of the split‐window algorithm used for the generation of the MODIS LST product in two situations: one in cases where LSTs are larger than the air temperature at the surface level (T s‐air) by more than 16 K and the columnar water vapour (cwv) is larger than 1.5 cm, and another in cases under the influence of thin cirrus clouds or heavy aerosol loadings. These two situations were not considered in the development of the current MODIS LST algorithm.
Predicting college students' acceptance of podcasting as a learning tool

Purpose – Podcasting is one of today's most prominent trends in media and computing, but until now, factors predicting its adoption in higher education settings remain largely unexplored. The purpose of this paper is to examine students' perceptions of enhanced podcasting as a review and exam preparatory tool, through the use of the Technology Acceptance Model (TAM). Design/methodology/approach – The responses from a structured, self‐administered questionnaire were used to develop an understanding of the role of perceived ease of use, usefulness and enjoyment on behavioral intention to use enhanced (audiovisual) podcasts.Findings – The statistical analysis indicated that perceived ease of use and perceived enjoyment were positively related to intention to use video podcasts, whereas perceived usefulness was not emerged as a strong prognostic indicator of user acceptance. Results also revealed that perceived ease of use is a strong predictor of perceived usefulness, supporting thus the view that perceived e.
As-Is Approximate Computing

Although approximate computing promises better performance for applications allowing marginal errors, dearth of hardware support and lack of run-time accuracy guarantees makes it difficult to adopt. We present As-Is, an Anytime Speculative Interruptible System that takes an approximate program and executes it with time-proportional approximations. That is, an approximate version of the program output is generated early and is gradually refined over time, thus providing the run-time guarantee of eventually reaching 100% accuracy. The novelty of our As-Is architecture is in its ability to conceptually marry approximate computing and speculative computing. We show how existing innovations in speculative architectures can be repurposed for anytime, best-effort approximation, facilitating the design efforts and overheads needed for approximate hardware support. As-Is provides a platform for real-time constraints and interactive users to interrupt programs early and accept their current approximate results as is. 100% accuracy is always guaranteed if more time can be spared. Our evaluations demonstrate favorable performance-accuracy tradeoffs for a range of approximate applications.
Unusual drawdown curves for a pumping test in an unconfined aquifer at Lachenaie, Quebec: field data and numerical modeling

An unconfined aquifer was instrumented with monitoring wells over a surface area of about 100 m × 100 m. The aquifer is a sand deposit overlying a thick nonfissured layer of Champlain Sea clay. The paper presents the results of a pumping test at a constant flow rate. None of the curves of drawdown versus time presented the S shape of current theories; however, all drawdowns indicated that the aquifer was homogeneous. The values for the specific yield were too low and varied with distance and time instead of being constant. The theories for steady and unsteady states provided different values for the saturated hydraulic conductivity. To understand the field behavior that differs from theoretical predictions, the pumping test conditions were modeled numerically using a finite element method. The transmissivity was derived from the Dupuit equation, and different curves for capillary retention and unsaturated permeability were examined. The numerical drawdowns agree with the experimental drawdowns. Several nu.
Clay minerals formed during propylitic alteration of a granite and their influence on primary porosity: A multi-scale approach

The porosity of a propylitized granite from Charroux (France), with no fractures or sealed fractures, increases by more than four times from the unaltered (0.3%) to the altered rock (1.4%). This evolution results from several local porosity modifications which occur at different scales in the rock: (1) at the core scale, from 10−1 to 10−5 m, where rock porosity changes as a function of rock-forming mineralogical composition; (2) at the mineral scale, from 10−3 to 10−7 m, where porosity depends both on the nature of the rock-forming mineral and its clay mineral alteration. Mineralogical and porosity data collected from the granite using a mineralogical map (after chemical staining and scanning electron microscopy images combined with autoradiographs) indicate that (1) the ferromagnesian rock-forming minerals — biotite and magnesiohornblende — act as the main porosity source in the unaltered granite, and (2) the nature of the clay minerals replacing rock-forming minerals in the altered granite appears to control the porosity value through two major alteration processes: chloritization and phengitization which affect the ferromagnesian minerals and produce non-porous chloritic and porous phengitic areas, respectively, at the studied scales. The observation that incipient porosity formation in granites is strongly linked to the pathway of ferromagnesian silicate alteration and subsequent clay mineral formation underlines the need to study parent-rock texture and mineralogy and their effects on subsequent near-surface weathering of granites.
AIRS hyper‐spectral measurements for climate research: Carbon dioxide and nitrous oxide effects

Mid‐tropospheric temperature soundings over tropical oceans by the Atmospheric Infrared Sounder, AIRS, using 4.3 micron CO2 R‐branch and P‐branch channels independently measure about 260 K with one Kelvin semi‐annual variability. The difference between the soundings, which cancels seasonal variability, has increased over the past two years by 47 ± 9 mK/year. This trend is explained by the increase of 2.2 ± 0.4 ppmv/year and 0.6 ± 0.2 ppbv/year in the abundance of CO2 and N2O, respectively, which results in a 35 mK/year trend. The ability to achieve closure at this level with only two years of AIRS data is very encouraging for measurements of other trends of atmospheric temperatures relevant to climate research. AIRS covers the 3.7 to 15.4 micron region with spectral resolution of λ/Δλ = 1200. AIRS was launched into a polar 705 km altitude orbit on the EOS Aqua spacecraft on May 4, 2002, and has an expected on‐orbit lifetime of seven years.
A MPC Walking Framework With External Contact Forces

In this work, we present an extension to a linear Model Predictive Control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. To accomplish this we set up a two step optimization problem. In the first optimization, we compute the Center of Mass (CoM) trajectory, foot step locations, and introduce slack variables to account for violating the imposed constraints on the Center of Pressure (CoP). We then use the slack variables to trigger the second optimization, in which we calculate the optimal external force that compensates for the CoP tracking error. This optimization considers multiple contacts with the environment by formulating the problem as a Mixed Integer Quadratic Program (MIQP) that can be solved at the order of 100 Hz. Once contact is created, the MIQP collapses to a single Quadratic Program (QP) that can be solved in real time $<$ 1kHz. Simulations show that the presented control scheme can withstand disturbances 2-5x larger with the additional force provide by a hand contact when considering delays and 3-6x larger when contact is already made.
Eliminating Mole Size in Melanoma Classification

- While skin cancer classification has been a popular and valuable deep learning application for years, there has been little consideration of the context in which testing images are taken. Traditional melanoma classifiers rely on the assumption that their testing environments are analogous to the structured images on which they are trained. This paper combats this notion, arguing that mole size, a vital attribute in professional dermatology, is a red herring in automated melanoma detection. Although malignant melanomas are consistently larger than benign melanomas, this distinction proves unreliable and harmful when images cannot be contextually scaled. This implementation builds a custom model that eliminates size as a training feature to prevent overfitting to incorrect parameters. Additionally, random rotation and contrast augmentations are performed to simulate the real-world use of melanoma detection applications. Several custom models with varying forms of data augmentation are implemented to demonstrate the most significant features of the generalization abilities of mole classifiers. These implementations show that user unpredictability is crucial when utilizing such applications. The caution required when manually modifying data is acknowledged, as data loss and biased conclusions are necessary considerations in this process. Additionally, mole size inconsistency and its significance are discussed in both the dermatology and deep learning communities.
On-Device Evaluation Toolkit for Machine Learning on Heterogeneous Low-Power System-on-Chip

—Network delays, throughput bottlenecks and privacy issues push Artiﬁcial Intelligence of Things (AIoT) designers towards evaluating the feasibility of moving model training and execution (inference) as near as possible to the terminals. Mean-while, Results from the TinyML community demonstrate that, in some cases, it is possible to execute model inference directly on the terminals themselves, even if these are small microcontroller-based devices. However, to date, researchers and practitioners in the domain lack convenient all-in-one toolkits to help them evaluate the feasibility of moving execution of arbitrary models to arbitrary low-power IoT hardware. To this effect, we present in this paper U-TOE, a universal toolkit we designed to facilitate the task of AIoT designers and researchers, by combining functionalities from a low-power embedded OS, a generic model transpiler and compiler, an integrated performance measurement module, and an open-access remote IoT testbed. We provide an open source implementation of U-TOE and we demonstrate its use to experimentally evaluate the performance of a wide variety of models, on a wide variety of low-power boards, based on popular microcontroller architectures (ARM Cortex-M and RISC-V). U-TOE thus allows easily reproducible and customisable comparative evaluation experiments in this domain, on a wide variety of IoT hardware all-at-once. The availability of a toolkit such as U-TOE is desirable to accelerate the ﬁeld of AIoT, towards fully exploiting the potential of edge computing.
Experimental investigation of etch pit formation on quartz sand grains

Summary An experimental investigation into the formation of crystallographically orientated etch pits on quartz sand grains was undertaken. The methods and materials used in the experiments differ considerably from those of other workers in this field. Using natural as opposed to artificial solutions, V-shaped or triangular etch pits as well as rectangular pits have been produced on the quartz grains after time periods of 4 hours and 20 hours. Features of intense surface disintegration have also been recorded. The etch pits are compared to those of natural occurrence on grains from the Millstone Grit (Namurian) sediments and the differences discussed.
Reusing Certain Database Design Principles, Methods and Techniques for Ontology Theory, Construction and Methodology

Formal ontologies can be seen as mathematical objects that form the range of a classical "Tarskian" semantics interpretation mapping of first-order language constructs that could represent situations, functions or procedures related to a given domain. In this paper we try to identify some of the theoretical and practical issues that result from this view, in particular concerning the problems of definition, representation, organization of ontologies, and methodologies for their construction and maintenance. We identify and discuss a number of the critical success factors for the “ontologization” of IT, namely large standardized ontological resources (ontobases), the so-called Semantic Web, and methodological, teachable approaches. Some design methods and techniques such as view integration that were originally developed for large databases, where the "data models" and their semantics typically are limited to a particular application, could be relevant for this purpose, and we analyze parallelisms and fundamental differences between databases and ontologies. In particular the ORM (Object-Role Modeling) method, or rather its precursor NIAM, with its rigorous distinction and handling of so-called lexical and non-lexical knowledge proved to be an interesting candidate to help identify and clarify a number of these issues, and a number of examples are given. In this paper we report on research within STARLab’s DOGMA Project that indicates how such methods may or must be adapted to be usable in the context of ontologies, and how they may then help to define ontology updates, the role of domain constraints, and future tools that assist in e.g. the alignment of ontologies.
Granitoids of the Dry Valleys area, southern Victoria Land: geochemistry and evolution along the early Paleozoic antarctic craton margin

Abstract Field relationships and geochemistry indicate granitoid plutons of the Dry Valleys area comprise at least three petrogenetically distinct suites. The older Dry Valleys 1a (DV1a) suite, comprising the Bonney, Catspaw, Denton, Cavendish, and Wheeler Plutons and hornblende‐biotite orthogneisses, and Dry Valleys 1b (DV1b) suite, comprising the Hedley, Valhalla, St Johns, Dun, Calkin, and Suess Plutons, biotite granitoid dikes and biotite orthogneisses, were emplaced before prominent swarms of Vanda mafic and felsic dikes. Both the DV1a and DV1b suites are time transgressive, with older intrusions in each suite being emplaced during the later stages of deformation of the Koettlitz Group. Younger granitoids that postdate the majority of the Vanda dikes include: the Dry Valleys 2 (DV2) suite, comprising the Pearse and Nibelungen Plutons plus several smaller, unnamed plugs; and the Harker, Swinford, Orestes, and Brownworth Plutons with identical field relationships and enclaves but distinct chemistries.
History Matching: Towards Geologically Reasonable Models

This work focuses on the development of a new method for history matching problem that through a deterministic search finds a geologically feasible solution. Complex geology is taken into account evaluating multiple point statistics from earth model prototypes - training images. Further a function that measures similarity between statistics of a training image and statistics of any smooth model is introduced and its analytical gradient is computed. This allows us to apply any gradient-based method to history matching problem and guide a solution until it satisfies both production data and complexity of a prior model with desired accuracy. As a consequence of the approach, we sufficiently decrease the amount of forward simulations needed to resolve historical data and prior information.
Approximating p-Mean Curve of Large Data-Sets

Given $p$, $k$ and a set of polygonal curves $P_1,\ldots,P_L$, the $p$-mean curve $M$ of $P_1,\ldots,P_L$ is the curve with at most $k$ vertices that minimizes the $L_p$ norm of the vector of Frechet distances between each $P_i$ and $M$. Also, the $p$-mean curve is the cluster representative (center) of $L_p$-based clusterings such as $k$-center, $k$-medians, and $k$-means. For $p\rightarrow \infty$, this problem is known to be NP-hard, with lower bound $2.25-\epsilon$ on its approximation factor for any $\epsilon>0$. By relaxing the number of vertices to $O(k)$, we were able to get constant factor approximation algorithms for $p$-mean curve with $p=O(1)$ and $p\rightarrow\infty$, for curves with few changes in their directions.
The Infinite Hidden Markov Model

We show that it is possible to extend hidden Markov models to have a countably infinite number of hidden states. By using the theory of Dirichlet processes we can implicitly integrate out the infinitely many transition parameters, leaving only three hyperparameters which can be learned from data. These three hyperparameters define a hierarchical Dirichlet process capable of capturing a rich set of transition dynamics. The three hyperparameters control the time scale of the dynamics, the sparsity of the underlying state-transition matrix, and the expected number of distinct hidden states in a finite sequence. In this framework it is also natural to allow the alphabet of emitted symbols to be infinite— consider, for example, symbols being possible words appearing in En-glish text.