Miracle-dz/UniFAR-FTUs huggingface dataset:
A high-level approach to confidence estimation in speech recognition

Errors in the output of a speech recogniser can be said to be due to the interaction of inadequate phonetic and language modelling components. We investigate an approach to estimating conﬁdence scores for the words output by a recogniser in which the language modelling and acoustic modelling are decoupled by the use of a phone recogniser working in parallel with the word recogniser. An advantage of such an approach is that it avoids techniques which rely on the use of side-information derived from the decoder: such information may depend heavily on the type and conﬁguration of the decoder used. We have investigated two ways of using the additional information provided by the phone-loop recogniser. One is based on correlating the phone strings from the two recognisers; the other is based on using the phone-loop recogniser output to construct hypotheses for the utterance and correlating these hypotheses with the word recogniser output.
Experimental Investigation of CO2, CO2SWAG and CO2-Foam Injection Scenarios for Enhanced Heavy Oil Recovery

In heavy oil reservoir, CO2 does not develop miscibility but it can substantially reduce the oil viscosity by dissolving in the oil and hence, improve recovery factor. Viscosity reductions of up to two orders of magnitude may be achieved as a result of CO2 dissolution in heavy oil. However, adverse viscosity ratio which results in viscous fingering and early breakthrough of CO2 is a constraint for application of CO2 injection in heavy oil reservoirs. In addition, in the case of thin reservoirs (horizontal displacement) gravity segregation results in gravity override which further reduces the sweep efficiency. As a result, CO2 injection requires be combining with either water flood or injecting in the form of CO2-foam in order to have acceptable sweep efficiency in viscous and heavy oil reservoirs. In our previous papers, the displacement efficiency in waterflood, CO2 and CO2-foam injection in heavy oil systems under gravity stable condition were investigated. This paper presents the results of a series of coreflood experiments performed to evaluate the potential of water, CO2, CO2SWAG and CO2-foam injection in a heavy oil reservoir under condition of gravity segregation. This paper presents the results of a series of coreflood experiments performed in order to evaluate the potential of different water and CO2 injection strategies for improving heavy oil recovery. CO2 injection showed great potentials for increasing oil recovery when it was injected in secondary mode and an ultimate recovery of around 45 %IOIP was achieved. Compared to water flood, secondary CO2 injection recovered much more oil especially after breakthrough. Combining CO2 and water injection by simultaneously injecting CO2 and water (CO2SWAG) increased oil recovery more that only water or only CO2 injection. CO2SWAG reduced the CO2 mobility and increased sweep efficiency and a final recovery of 70 %IOIP accomplished. The addition of an appropriate surfactant to the flood water and its co-injection with CO2 resulted in the in-situ formation of CO2-foam which provided better mobility control and resulted in the highest oil recovery amongst the injection strategies tested. The differential pressure across the core significantly increased during the co-injection of CO2 and the surfactant solution which was a strong indication of in-situ formation of CO2-foam even at high oil saturation of up to 60%.
ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding

We present ThreshNet, a post-processing method to re-ﬁne the output of neural networks designed for binary segmentation tasks. ThreshNet uses the conﬁdence map produced by a base network along with global and lo-cal patch information to signiﬁcantly improve the performance of even state-of-the-art methods. Binary segmentation models typically convert conﬁdence maps into predictions by thresholding the conﬁdence scores at 0.5 (or some other ﬁxed number). However, we observe that the best threshold is image-dependent and often even region-speciﬁc – different parts of the image beneﬁt from using different thresholds. Thus ThreshNet takes a trained segmentation model and learns to correct its predictions by us-ing a memory-efﬁcient post-processing architecture that incorporates region-speciﬁc thresholds as part of the training mechanism. Our experiments show that ThreshNet consistently improves over current the state-of-the-art methods in binary segmentation and saliency detection, typically by 3 to 5% in mIoU and mBA.
I. On the origin and mechanism of production of the prismatic (or columnar) structure of basalt

The author having briefly traced the history of geological opinion on this subject, from before the period at which the controversy at which the igneous or aqueous origin of basalt might be viewed as settled, and having stated the views of some of the more prominent British authors on this subject of recent date, points out that, up to the present, no clear and definite theoretic views have been enunciated to account for prismatic structure in basalt, and that it is impossible to gather, with any distinctness, from systematic writers, whether prismatic structure be due to contraction by cooling alone, or whether the structure is due to preexisting concretionary or crystalline arrangement of the integral particles of the mass, or to this coacting with enormous external pressures, the origin of which is left perfectly vague, or to some play of successive and joint actions of all these various forces. Prof. James Thomson, in a paper read some years ago, and since repeated at the late Belfast Meeting of the British Association, has proposed views, in some respects new, tracing prismatic structure to contraction by cooling only, and has expressed entire doubt as to the part supposed to be played by concretionary spheroids pressed together. Prof. Thomson’s views, however, are still far from complete, and the mode assigned by him to the production of cup-shaped cross joints in the prisms fails to account for the phenomena.
Information Model for IP Flow Information Export (IPFIX)

This document defines the data types and management policy for the information model for the IP Flow Information Export (IPFIX) protocol. This information model is maintained as the IANA "IPFIX Information Elements" registry, the initial contents of which were defined by RFC 5102. This information model is used by the IPFIX protocol for encoding measured traffic information and information related to the traffic Observation Point, the traffic Metering Process, and the Exporting Process. Although this model was developed for the IPFIX protocol, it is defined in an open way that allows it to be easily used in other protocols, interfaces, and applications. This document obsoletes RFC 5102.
An illumination invariant skin-color model for face detection

Face detection is an important step towards a fully automatic face recognition system. Among existing techniques in the literature, methods based on skin-color information have shown computational effectiveness as well as robustness in terms of rotation, scaling and partial occlusion. However, due to color variations resulted from illumination changes, many color-based techniques have yet to demonstrate a stable state of performance. In this paper, we present an illumination invariant color space model to address the color variation issue. The proposed method is evaluated both in terms of skin-color detection and face detection performances. Our empirical experiments evidenced both effectiveness and usefulness of the proposed method.
Xar

INTRODUCTION The vision of semantic interoperability on a large-scale, such as that envisioned by the concept of the Semantic-Web (Berners-Lee, Hendler & Lassila, 2001), continues to sustain interest and excitement. The availability of automated tools for semantic annotation of data on the open Web is recognized as critical for Semantic-Web enablement. In the process of semantic annotation we annotate significant entities and relationships in documents and pages on the Web, thus making them amenable for machine processing. The time and investment of marking and annotating Web content manually is prohibitive for all but a handful of Web content providers, which leads us to develop automated tools for this task. As an example, consider Web pages of academic researchers with their biographies in free text as shown in Fig 1.
A Domain-Specific Risk-Taking (DOSPERT) Scale for Adult Populations

This paper proposes a revised version of the original Domain-Specific Risk-Taking (DOSPERT) scale developed by Weber, Blais, and Betz (2002) that is shorter and applicable to a {broader range of ages, cultures, and educational levels}. It also provides a French translation of the revised scale. Using multilevel modeling, we investigated the risk-return relationship between apparent risk taking and risk perception in 5 risk domains. The results replicate previously noted differences in reported degree of risk taking and risk perception at the mean level of analysis. The multilevel modeling shows, more interestingly, that within-participants variation in risk taking across the 5 content domains of the scale was about 7 times as large as between-participants variation. We discuss the implications of our findings in terms of the person-situation debate related to risk attitude as a stable trait.
intelligent The Nature , Importance , and Difficulty of Machine Ethics

T he question of whether machine ethics exists or might exist in the future is difficult to answer if we can't agree on what counts as machine ethics. Some might argue that machine ethics obviously exists because humans are machines and humans have ethics. Others could argue that machine ethics obviously doesn't exist because ethics is simply emotional expression and machines can't have emotions. A wide range of positions on machine ethics are possible, and a discussion of the issue could rapidly propel us into deep and unsettled philosophical issues. Perhaps, understandably, few in the scientific arena pursue the issue of machine ethics. You're unlikely to find easily testable hypotheses in the murky waters of philosophy. But we can't—and shouldn't—avoid consideration of machine ethics in today's technological world. As we expand computers'decision-making roles in practical matters, such as computers driving cars, ethical considerations are inevitable. Computer scientists and engineers must examine the possibilities for machine ethics because, knowingly or not, they've already engaged—or will soon engage—in some form of it. Before we can discuss possible implementations of machine ethics, however, we need to be clear about what we're asserting or denying. When people speak of technology and values, they're often thinking of ethical values. But not all values are ethical. For example, practical, economic, and aesthetic values don't necessarily draw on ethical considerations. A product of technology, such as a new sailboat, might be practically durable, economically expensive, and aesthetically pleasing, absent consideration of any ethical values. We routinely evaluate technology from these nonethical nor-mative viewpoints. Tool makers and users regularly evaluate how well tools accomplish the purposes for which they were designed. With technology, all of us—ethicists and engineers included—are involved in evaluation processes requiring the selection and application of standards. In none of our professional activities can we retreat to a world of pure facts, devoid of subjective normative assessment. By its nature, computing technology is normative. We expect programs, when executed, to proceed toward some objective—for example, to correctly compute our income taxes or keep an airplane on course. Their intended purpose serves as a norm for evaluation—that is, we assess how well the computer program calculates the tax or guides the airplane. Viewing computers as technological agents is reasonable because they do jobs on our behalf. They're normative agents in the limited sense that we can assess their performance in terms of how well they do …
Mars aeolian sand: Regional variations among dark-hued crater floor features

Different regions on Mars appear to have low-albedo intracrater deposits that have distinct regional thermophysical and/or aeolian dune characteristics. Thermal inertia derived from a carefully selected set of Viking infrared thermal mapper observations of the dark features obtained in 1977–1978 supports this conclusion. The observed similarities and differences among dark intracrater features on Mars is probably a function of the combined influences of sand availability and regional wind conditions.
FORTAP: Using Formulae for Numerical-Reasoning-Aware Table Pretraining

Tables store rich numerical data, but numerical reasoning over tables is still a challenge. In this paper, we ﬁnd that the spreadsheet formula, which performs calculations on numerical values in tables, is naturally a strong supervision of numerical reasoning. More importantly, large amounts of spreadsheets with expert-made formulae are available on the web and can be obtained easily. FORTAP is the ﬁrst method for numerical-reasoning-aware table pretraining by leveraging large corpus of spreadsheet formulae. We design two formula pretraining tasks to explicitly guide FORTAP to learn numerical reference and calculation in semi-structured tables. FORTAP achieves state-of-the-art results on two representative downstream tasks, cell type classiﬁcation and formula prediction, showing great potential of numerical-reasoning-aware pretraining.
El Plan Piloto de Cali 1950

This article is an approach to one of the projects of modern urbanism considered in Colombia in the middle of the 20th century, the Pilot Plan for Cali, designed by Town Planning Associates. Thanks to the recovery of the Plan original material, the author does a brief resume of the special circumstances that surrounded its elaboration and the main proposals of the project.
Texture Generation Using Graph Generative Adversarial Network And Differentiable Rendering

Novel texture synthesis for existing 3D mesh models is an important step towards photo-realistic asset generation for existing simulators. But existing methods in-herently work in the 2D image space which is the projection of the 3D space from a given camera perspective. These methods take camera angle, 3D model information, lighting information and generate photorealistic 2D image. To generate a photorealistic image from another perspective or lighting, we need to make a computationally expensive forward pass each time we change the parameters. Also, it’s hard to generate such images for a simulator that can satisfy the temporal constraints: the sequences of images should be similar but only need to change the viewpoint of lighting as desired. The solution can’t be directly integrated with existing tools like Blender and Unreal Engine. Manual solution is expensive and time consuming. We thus present a new system called a graph generative adversarial network (GGAN) that can generate textures which can be directly integrated into a given 3D mesh models with tools like Blender and Unreal Engine and can be simulated from any perspective and lighting condition easily.
Distributed Energy Resources Integration Challenges in Low-Voltage Networks: Voltage Control Limitations and Risk of Cascading

The integration of distributed energy resources (DER) in low-voltage networks is expected to increase significantly in the next few years. It is known that the large-scale integration of DER in conventional low-voltage (LV) networks poses many challenges such as voltage rise. To mitigate voltage rise caused by DER, utilities are defining simple voltage regulation strategies such as disconnecting DER when phase voltages rise above a defined threshold. In this paper, we model LV networks as three-phase unbalanced circuits and illustrate that such local regulation strategies may cause the cascading of the DER in a feeder. We then propose an optimal control approach to avoid cascading and optimize DER availability. Local control approaches are discussed in the context of global DER availability and their limitations are illustrated.
Steps Toward Automatic Understanding of the Function of Affective Language in Support Groups

Understanding expression of emotions in support forums has great value and NLP methods are key to automating this. Many approaches use subjective categories which are more fine-grained than a straightforward polarity-based spectrum. However, the definition of such categories is non-trivial, and we argue for a need to incorporate communicative elements even beyond subjectivity. To support our position, we report experiments on a sentiment-labelled corpus of posts from a medical support forum. We argue that a more fine-grained approach to text analysis important, and also simultaneously recognising the social function behind affective expressions enables a more accurate and valuable level of understanding.
MSQNet: Actor-agnostic Action Recognition with Multi-modal Query

Existing action recognition methods are typically actor-specific due to the intrinsic topological and apparent differences among the actors. This requires actor-specific pose estimation ( e.g ., humans vs. animals), leading to cum-bersome model design complexity and high maintenance costs. Moreover, they often focus on learning the visual modality alone and single-label classification whilst neglecting other available information sources ( e.g ., class name text) and the concurrent occurrence of multiple actions. To overcome these limitations, we propose a new approach called ’actor-agnostic multi-modal multi-label action recognition,’ which offers a unified solution for various types of actors, including humans and animals. We further formulate a novel Multi-modal Semantic Query Network (MSQNet) model in a transformer-based object detection framework ( e.g ., DETR), characterized by leveraging visual and textual modalities to represent the action classes better. The elimination of actor-specific model designs is a key advantage, as it removes the need for actor pose estimation altogether. Extensive experiments on five publicly available benchmarks show that our MSQNet consistently outperforms the prior arts of actor-specific alternatives on human and animal single-and multi-label action recognition tasks by up to 50%. Code will be released at https://github.com/mondalanindya/MSQNet.
Wind Stress and Heat Flux over the Ocean in Gale Force Winds

Abstract An offshore stable platform has been instrumented with wind turbulence, temperature and wave height sensors. Data from this platform have been analyzed by the eddy correlation method to obtain wind stress and heat flux at wind speeds from 6 to 22 m s−1 in a deep-water wave regime, significantly extending the range of available measurements. The sea surface drag coefficient increases gradually with increasing wind speed. Sensible heat fluxes have been observed over a much wider range than previously available. Heat flux coefficients are higher in unstable than stable conditions, but are not seen to increase with increasing wind speed.
PASS2: a semi-automated database of Protein Alignments Organised as Structural Superfamilies

PASS2 is a nearly automated version of CAMPASS and contains sequence alignments of proteins grouped at the level of superfamilies. This database has been created to fall in correspondence with SCOP database (1.53 release) and currently consists of 110 multi-member superfamilies and 613 superfamilies corresponding to single members. In multi-member superfamilies, protein chains with no more than 25% sequence identity have been considered for the alignment and hence the database aims to address sequence alignments which represent 26 219 protein domains under the SCOP 1.53 release. Structure-based sequence alignments have been obtained by COMPARER and the initial equivalences are provided automatically from a MALIGN alignment and subsequently augmented using STAMP4.0. The final sequence alignments have been annotated for the structural features using JOY4.0. Several interesting links are provided to other related databases and genome sequence relatives. Availability of reliable sequence alignments of distantly related proteins, despite poor sequence identity and single-member superfamilies, permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. The database can be queried by keywords and also by sequence search, interfaced by PSI-BLAST methods. Structure-annotated sequence alignments and several structural accessory files can be retrieved for all the superfamilies including the user-input sequence. The database can be accessed from http://www.ncbs. res.in/%7Efaculty/mini/campass/pass.html.
The Multiple-partners Assignment Game with Heterogeneous Sells and Multi-unit Demands: Competitive Equilibria

A multiple-partners assignment game with heterogeneous sells and multi-unit demands consists of a set of sellers that own a given number of indivisible units of (potentially many di¤erent) goods and a set of buyers who value those units and want to buy at most an exogenously …xed number of units. We de…ne a competitive equilibrium for this generalized assignment game and prove its existence using linear programming. We show that the set of competitive equilibria (pairs of price vectors and assignments) has a Cartesian product structure: each equilibrium price vector is part of a competitive equilibrium with all equilibrium assignments, and vice versa. We also show that the set of equilibrium price vectors has a natural lattice structure and we study how this structure is translated into the set of agents'utilities that are attainable at equilibrium.
A transdisciplinary collaborative journey leading to sensorial clothing

ABSTRACT Recent science funding initiatives have enabled participants from a diverse array of disciplines to engage in common spaces for developing solutions for new wearables. These initiatives include collaborations between the arts and sciences, fields which have traditionally contributed very different forms of knowledge, methodology, and results. However, many such collaborations often turn out as science communication and dissemination activities that make no concrete contribution to technological innovation. Magic Lining, a transdisciplinary collaborative project involving artistic and scientific partners working in the fields of e-textile design, cognitive neuroscience and human-computer interaction, creates a shared experiential knowledge space. This article focuses on the research question of how a transdisciplinary collaborative design processinvolving material explorations, prototyping, first-person-perspective and user studies, can lead to the creation of a garment that invites various perceptual and emotional responses in its wearer. The article reflects on the design journey, highlighting the transdisciplinary team’s research through design experience and shared language for knowledge exchange. This process has revealed new research paths for an emerging field of ‘sensorial clothing’, combining the various team members’ fields of expertise and resulting in a wearable prototype.
Single fiber EMG reference values: A collaborative effort

Single fiber electromyography (SFEMG) measurements of fiber density and jitter are used in the diagnosis of a variety of peripheral nervous system disorders. However, the normal values of these measurements for most muscles and age groups are not well documented in the literature. We present a retrospective and prospective multicenter collection of SFEMG jitter and fiber density data from control subjects obtained for the purpose of defining reference values for many muscles and different ages. The data and calculated upper limits for fiber density, individual pair jitter, and mean jitter are presented for each muscle in tabular and graphical format, for different age groups.