17,997 research outputs found

    Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective

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    This paper introduces a comprehensive, multi-stage machine learning methodology that effectively integrates information systems and artificial intelligence to enhance decision-making processes within the domain of operations research. The proposed framework adeptly addresses common limitations of existing solutions, such as the neglect of data-driven estimation for vital production parameters, exclusive generation of point forecasts without considering model uncertainty, and lacking explanations regarding the sources of such uncertainty. Our approach employs Quantile Regression Forests for generating interval predictions, alongside both local and global variants of SHapley Additive Explanations for the examined predictive process monitoring problem. The practical applicability of the proposed methodology is substantiated through a real-world production planning case study, emphasizing the potential of prescriptive analytics in refining decision-making procedures. This paper accentuates the imperative of addressing these challenges to fully harness the extensive and rich data resources accessible for well-informed decision-making

    The effects of supercritical CO2 on the seepage characteristics and microstructure of water-bearing bituminous coal at in-situ stress conditions

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    CO2 geological storage (CGS) is considered to be an important technology for achieving carbon peak and carbon neutralization goals. Injecting CO2 into deep unminable coal seams can achieve both CGS and enhance coalbed methane (ECBM) production. Therefore, the deep unminable coal seams are considered as promising geological reservoirs. CO2 exists in a supercritical CO2 (ScCO2) when it was injected into deep unminable coal seams. The injection of ScCO2 can induce changes in the seepage characteristics and microstructure of deep water-bearing coal seams. In this study, typical bituminous coal from Shenmu, Shanxi Province was used to investigate the effects of ScCO2 on seepage characteristics, pore characteristics, and mineral composition through experiments such as seepage tests, low-temperature liquid nitrogen adsorption, and X-ray diffraction (XRD). The results indicate that ScCO2 treatment of dry and saturated coal samples caused a significant increase in clay mineral content due to the dissolution of carbonates, leading to the conversion of adsorption pores to seepage pores and an improvement in seepage pore connectivity. Therefore, the Brunauer-Emmett-Teller (BET) specific surface area and pore volume of the two coal samples both decreased after ScCO2 treatment. Moreover, the permeability of dry and saturated coal samples increased by 191.53% and 231.71% at 10 MPa effective stress respectively. In semi-saturated coal samples, a large amount of dolomite dissolved, leading to the precipitation of Ca2+ and CO32- to form calcite. This caused pore throats to clog and macropores to divide. The results show that the pore volume and average pore size of coal samples decrease, while the specific surface area increases after ScCO2 treatment, providing more space for gas adsorption. However, the pore changes also reduced the permeability of the coal samples by 32.21% and 7.72% at effective stresses of 3 MPa and 10 MPa, respectively. The results enhance our understanding of carbon sequestration through ScCO2 injection into water-bearing bituminous coal seams

    Zero-Shot Generalizable End-to-End Task-Oriented Dialog System using Context Summarization and Domain Schema

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    Task-oriented dialog systems empower users to accomplish their goals by facilitating intuitive and expressive natural language interactions. State-of-the-art approaches in task-oriented dialog systems formulate the problem as a conditional sequence generation task and fine-tune pre-trained causal language models in the supervised setting. This requires labeled training data for each new domain or task, and acquiring such data is prohibitively laborious and expensive, thus making it a bottleneck for scaling systems to a wide range of domains. To overcome this challenge, we introduce a novel Zero-Shot generalizable end-to-end Task-oriented Dialog system, ZS-ToD, that leverages domain schemas to allow for robust generalization to unseen domains and exploits effective summarization of the dialog history. We employ GPT-2 as a backbone model and introduce a two-step training process where the goal of the first step is to learn the general structure of the dialog data and the second step optimizes the response generation as well as intermediate outputs, such as dialog state and system actions. As opposed to state-of-the-art systems that are trained to fulfill certain intents in the given domains and memorize task-specific conversational patterns, ZS-ToD learns generic task-completion skills by comprehending domain semantics via domain schemas and generalizing to unseen domains seamlessly. We conduct an extensive experimental evaluation on SGD and SGD-X datasets that span up to 20 unique domains and ZS-ToD outperforms state-of-the-art systems on key metrics, with an improvement of +17% on joint goal accuracy and +5 on inform. Additionally, we present a detailed ablation study to demonstrate the effectiveness of the proposed components and training mechanis

    Procedure-Aware Pretraining for Instructional Video Understanding

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    Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a key challenge in procedure understanding is to be able to extract from unlabeled videos the procedural knowledge such as the identity of the task (e.g., 'make latte'), its steps (e.g., 'pour milk'), or the potential next steps given partial progress in its execution. Our main insight is that instructional videos depict sequences of steps that repeat between instances of the same or different tasks, and that this structure can be well represented by a Procedural Knowledge Graph (PKG), where nodes are discrete steps and edges connect steps that occur sequentially in the instructional activities. This graph can then be used to generate pseudo labels to train a video representation that encodes the procedural knowledge in a more accessible form to generalize to multiple procedure understanding tasks. We build a PKG by combining information from a text-based procedural knowledge database and an unlabeled instructional video corpus and then use it to generate training pseudo labels with four novel pre-training objectives. We call this PKG-based pre-training procedure and the resulting model Paprika, Procedure-Aware PRe-training for Instructional Knowledge Acquisition. We evaluate Paprika on COIN and CrossTask for procedure understanding tasks such as task recognition, step recognition, and step forecasting. Paprika yields a video representation that improves over the state of the art: up to 11.23% gains in accuracy in 12 evaluation settings. Implementation is available at https://github.com/salesforce/paprika.Comment: CVPR 202

    Saliency-aware Stereoscopic Video Retargeting

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    Stereo video retargeting aims to resize an image to a desired aspect ratio. The quality of retargeted videos can be significantly impacted by the stereo videos spatial, temporal, and disparity coherence, all of which can be impacted by the retargeting process. Due to the lack of a publicly accessible annotated dataset, there is little research on deep learning-based methods for stereo video retargeting. This paper proposes an unsupervised deep learning-based stereo video retargeting network. Our model first detects the salient objects and shifts and warps all objects such that it minimizes the distortion of the salient parts of the stereo frames. We use 1D convolution for shifting the salient objects and design a stereo video Transformer to assist the retargeting process. To train the network, we use the parallax attention mechanism to fuse the left and right views and feed the retargeted frames to a reconstruction module that reverses the retargeted frames to the input frames. Therefore, the network is trained in an unsupervised manner. Extensive qualitative and quantitative experiments and ablation studies on KITTI stereo 2012 and 2015 datasets demonstrate the efficiency of the proposed method over the existing state-of-the-art methods. The code is available at https://github.com/z65451/SVR/.Comment: 8 pages excluding references. CVPRW conferenc

    The development of the Kent coalfield 1896-1946

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    One of the unique features of the Kent Coalfield is that it is entirely concealed by newer rocks. The existence of a coalfield under southern England, being a direct link between those of South Wales, Somerset and Bristol in the west and the Ruhr, Belgium. and northern France in the east, was predicted by the geologist R. A. C. Godwin-Austen as early as 1856. It was, however, only the rapid increase in demand for Britain's coal in the last quarter of the nineteenth century that made it worth considering testing this hypothesis. The first boring was made in the years 1886-90, and although it discovered coal, this did not in itself prove the existence of a viable coalfield. This could be done only by incurring the heavy cost of boring systematically over a wide area. As the financial returns from such an undertaking were uncertain, it was not surprising that in the early years, around the turn of the century, a dominant role was played by speculators, who were able to induce numerous small investors to risk some of their savings in the expectation of high profits. As minerals in Britain were privately owned, the early pioneer companies not only had to meet the cost of the exploratory borines, but also, if they were not to see the benefit of their work accrue to others, lease beforehand the right to mine coal from local landowners in as much of the surrounding area as possible. This policy was pursued most vigorously by Arthur Burr, a Surrey land specula tor, who raised capital by creating the Kent Coal Conoessions Ltd. and then floating a series of companies allied to it. Burr's enterprise would probably have been. successful had it not been for the water problems encountered at depth in -v- the coalfield. As a result, the Concessions group found itself in control of most of the coalfield, but without the necessary capital to sink and adequately equip its 01ffi collieries. By 1910, however, the discovery of iron ore deposits in east Kent, coupled with the fact that Kent coal was excellent for coking purposes, began to attract the large steel firms of Bolckow, Vaughan Ltd. and Dorman, Long & Co. Ltd. in to the area. The First World War intervened, however, to delay their plans, and to provide an extended lease of life to the Concessions group, which, by the summer of 1914, was facing financial collapse. By the time Dorman, Lone & Co, in alliance with Weetman Pearson (Lord Cowdray), had acquired control over the greater part of the coalfield from the Concessions group, not only was the country's coal industry declining, but so was its steel industry, which suffered an even more severe rate of contraction during the inter-war years. As a result, Pearson and Dorman Long Ltd. was forced to concentrate just on coal production, and this in turn was hampered not only by the water problems, but also by labour shortages and the schemes introduced by the government in 1930 to restrict the country's coal output, in an attempt to maintain prices and revenue in the industry. Nevertheless, production did show a substantial increase between 1927 and 1935, after which it declined as miners left the coalfield to return to their former districts, where employment opportunities were improving in the late thirties. Supporting roles were played in the inter-war years by Richard Tilden Smith, a share underwriter turned industrialist with long standing interests in the coalfield, who acquired one of the Concessions group's two collieries, and by the Powell Duffryn Steam Coal Co. Ltd., which through subsidiary companies, took over the only colliery to be developed by a pioneer company outside the Concessions group. The impossibility of Kent coal, because of its nature, ever gaining more than token access to the more lucrative household market, and then the failure of the local steel industry to materialise meant that the -vi- companies had to develop alternative outlets for their growing outputs. Although nearness to industrial markets in the south-east of England did confer certain advantages were poor consolation for the hoped for developments of either the early pioneers or the later industrialists. Instead of the expected profits, the companies mostly incurred losses, and only the company acquired by Powell Duffryn ever paid a dividend to its shareholders in the years before nationalisation. From the point of view of the Kent miners, the shortage of labour in the coalfield, particularly in the years 1914-20 and 1927-35, was to an important extent responsible for their being amongst the highest paid in the industry. At the same time the more favourable employment opportunities prevailing in Kent compared with other mining districts enabled the Kent Nine Workers Association to develop into a well organised union, which on the whole was able to look after the interests of its members fairly successfully. Throughout the period 1896 to 1946 the Kent Coalfield existed very much at the margin of the British coal industry. Its failure to develop substantially along the lines envisaged by either the early pioneers or by the later industrialists meant that its importance in national terms always remained small

    The place where curses are manufactured : four poets of the Vietnam War

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    The Vietnam War was unique among American wars. To pinpoint its uniqueness, it was necessary to look for a non-American voice that would enable me to articulate its distinctiveness and explore the American character as observed by an Asian. Takeshi Kaiko proved to be most helpful. From his novel, Into a Black Sun, I was able to establish a working pair of 'bookends' from which to approach the poetry of Walter McDonald, Bruce Weigl, Basil T. Paquet and Steve Mason. Chapter One is devoted to those seemingly mismatched 'bookends,' Walt Whitman and General William C. Westmoreland, and their respective anthropocentric and technocentric visions of progress and the peculiarly American concept of the "open road" as they manifest themselves in Vietnam. In Chapter, Two, I analyze the war poems of Walter McDonald. As a pilot, writing primarily about flying, his poetry manifests General Westmoreland's technocentric vision of the 'road' as determined by and manifest through technology. Chapter Three focuses on the poems of Bruce Weigl. The poems analyzed portray the literal and metaphorical descent from the technocentric, 'numbed' distance of aerial warfare to the world of ground warfare, and the initiation of a 'fucking new guy,' who discovers the contours of the self's interior through a set of experiences that lead from from aerial insertion into the jungle to the degradation of burning human feces. Chapter Four, devoted to the thirteen poems of Basil T. Paquet, focuses on the continuation of the descent begun in Chapter Two. In his capacity as a medic, Paquet's entire body of poems details his quotidian tasks which entail tending the maimed, the mortally wounded and the dead. The final chapter deals with Steve Mason's JohnnY's Song, and his depiction of the plight of Vietnam veterans back in "The World" who are still trapped inside the interior landscape of their individual "ghettoes" of the soul created by their war-time experiences

    Augmented classification for electrical coil winding defects

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    A green revolution has accelerated over the recent decades with a look to replace existing transportation power solutions through the adoption of greener electrical alternatives. In parallel the digitisation of manufacturing has enabled progress in the tracking and traceability of processes and improvements in fault detection and classification. This paper explores electrical machine manufacture and the challenges faced in identifying failures modes during this life cycle through the demonstration of state-of-the-art machine vision methods for the classification of electrical coil winding defects. We demonstrate how recent generative adversarial networks can be used to augment training of these models to further improve their accuracy for this challenging task. Our approach utilises pre-processing and dimensionality reduction to boost performance of the model from a standard convolutional neural network (CNN) leading to a significant increase in accuracy

    Drilling into mines for heat: geological synthesis of the UK Geoenergy Observatory in Glasgow and implications for mine water heat resources

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    Thermal energy from groundwater in abandoned, flooded, coal mines has the potential to make a significant contribution to decarbonisation of heat and Net-Zero carbon emissions. In Glasgow, UK, a subsurface observatory has been constructed for mine water heat and heat storage research. We synthesise geological and mine water resource findings from a four-year period of borehole planning, drilling, logging and testing. The heterogenous bedrock is typical of the Scottish Coal Measures Group, whereas superficial deposits are more sand- and gravel-dominated than prognosed. Mine water boreholes encountered workings in the Glasgow Upper, Glasgow Ell and Glasgow Main coal seams, proving water-filled voids, mine waste, fractured rock mass and intact coal pillars with high yields on initial hydrogeological testing. Whilst the depth and extent of mine workings delineated on mine abandonment plans proved accurate, metre-scale variability was expected and proved in the boreholes. A mine water reservoir classification established from the observatory boreholes highlights the resource potential in areas of total extraction, stowage, and stoop and room workings. Since their spatial extent is more extensive across the UK than shafts or roadways, increasing the mine water energy evidence base and reducing exploration risk in these types of legacy workings is important
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