Embryonic stem cell microenvironment can promote proliferation of terminal cells and reduce invasiveness of tumor ***,implanting embryonic stem cells directly in vivo can result in tumorigenicity,immune rejection afte...
Embryonic stem cell microenvironment can promote proliferation of terminal cells and reduce invasiveness of tumor ***,implanting embryonic stem cells directly in vivo can result in tumorigenicity,immune rejection after differentiation and graft-versus-host reaction.
Open-world survival games pose significant challenges for AI algorithms due to their multi-tasking, deep exploration, and goal prioritization requirements. Despite reinforcement learning (RL) being popular for solving...
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ISBN:
(纸本)9781713899921
Open-world survival games pose significant challenges for AI algorithms due to their multi-tasking, deep exploration, and goal prioritization requirements. Despite reinforcement learning (RL) being popular for solving games, its high sample complexity limits its effectiveness in complex open-world games like Crafter or Minecraft. We propose a novel approach, SPRING, to read Crafter's original academic paper and use the knowledge learned to reason and play the game through a large language model (LLM). Prompted with the LATEX source as game context and a description of the agent's current observation, our SPRING framework employs a directed acyclic graph (DAG) with game-related questions as nodes and dependencies as edges. We identify the optimal action to take in the environment by traversing the DAG and calculating LLM responses for each node in topological order, with the LLM's answer to final node directly translating to environment actions. In our experiments, we study the quality of in-context "reasoning" induced by different forms of prompts under the setting of the Crafter environment. Our experiments suggest that LLMs, when prompted with consistent chain-of-thought, have great potential in completing sophisticated high-level trajectories. Quantitatively, SPRING with GPT-4 outperforms all state-of-the-art RL baselines, trained for 1M steps, without any training. Finally, we show the potential of Crafter as a test bed for LLMs. Code at ***/holmeswww/SPRING
Texture classification plays an important role in different domains of healthcare, agriculture, and industry. In this contribution, we propose an interpretable and efficient texture classification framework that consi...
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ISBN:
(纸本)9783031442360;9783031442377
Texture classification plays an important role in different domains of healthcare, agriculture, and industry. In this contribution, we propose an interpretable and efficient texture classification framework that considers colour or channel information and does not require much data to produce accurate results. Therefore, such a classifier can be suitable for medical applications and resource-limited hardware. We base our work on a Generalized Matrix Learning Vector Quantization (GMLVQ) and introduce a special matrix format for multi-channel images. We compare the performance of different model designs on two data sets emphasising the role of the dissimilarity measure used. We demonstrate that our extension of parametrized angle dissimilarity measure leads to better model generalization and improved robustness against varying lighting conditions than its Euclidean counterpart.
In this paper we perform an exploratory study on the design of claim fraud detection for a typical property and casualty (P&C) insurance company using cost-sensitive classification. We contrast several cost incorp...
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ISBN:
(纸本)3540240543
In this paper we perform an exploratory study on the design of claim fraud detection for a typical property and casualty (P&C) insurance company using cost-sensitive classification. We contrast several cost incorporation scenarios based on different assumptions concerning the available cost information at claim screening time. Our empirical trials are based on a data set of real-life Spanish closed automobile insurance claims that were previously investigated for suspicion of fraud by domain experts and for which we obtained detailed cost information. The reported results show the added value of cost-sensitive claim fraud screening and provide guidance on how to operationalize this strategy.
The paper describes a video tracking system that tracks and analyzes the behavioral pattern of users in a public space. We have obtained important statistical measurements about users' behavior, which can be used ...
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ISBN:
(纸本)0769522718
The paper describes a video tracking system that tracks and analyzes the behavioral pattern of users in a public space. We have obtained important statistical measurements about users' behavior, which can be used to evaluate architectural design in terms of human spatial behavior and model the behavior of users in public spaces. Previously, such measurements could only be obtained through costly manual processes, e.g. behavioral mapping and time-lapse filming with human examiners. Our system has automated the process of analyzing the behavior of users. The system consists of a head detector for detecting people in each single frame of the video and data association for tracking people through frames. We compared the results obtained using our system with those obtained by manual counting, for a small data set, and found the results to be fairly accurate. We then applied the system to a large-scale data set and obtained substantial statistical measurements of parameters such as the total number of users who entered the space, the total number of users who sat by a fountain, the time that each spent by the fountain, etc. These statistics allow fundamental rethinking of the way people use a public space This research is a novel application of computer vision in evaluating architectural design in terms of human behavior.
Educational big data connects learning science with data science, where various educational problems are formulating into data mining tasks towards new solutions and new discoveries. This paper provides a path of auto...
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ISBN:
(纸本)9781665426251
Educational big data connects learning science with data science, where various educational problems are formulating into data mining tasks towards new solutions and new discoveries. This paper provides a path of automatically grading graduate academic dissertations according to the expert-given comment texts. The proposed method fed comment texts to an attention convolutional neural network consisted of an embedding layer, an attention mechanism layer, a convolutional layer, and a fully connected neural network, where the data imbalance issue was handled by data augmentations. The used comment texts were collected from 943 students spreading at 145 universities in China, where these review comments were yielded by experts to grade the academic dissertations. The results from the proposed method achieve a classification accuracy of 77% that gains 12% and 15% implementations compared to the classical convolutional neural network and the linear support vector machine. However, the result analyses show that there are many conflicts between expert-given comments and their given grades in the collected data. This study provides an automatic tool that could remove these conflicts in the dissertation review, leading to more objective dissertation grades.
A case study is provided describing Lloyd's Register's development of a set of Key Performance Indicators (KPIs) for Process Safety Management (PSM) for an oil and gas client. The development process is descri...
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ISBN:
(纸本)9780852955369
A case study is provided describing Lloyd's Register's development of a set of Key Performance Indicators (KPIs) for Process Safety Management (PSM) for an oil and gas client. The development process is described in this paper along with discussion of how the KPIs were developed and designed to support the client in gaining a clearer picture of their current Process Safety performance and to drive the improvement of that performance. This paper includes discussion of the number of KPIs that are introduced, the sequencing of introduction of KPIs, the associated implementation requirements, the reporting of the metrics to management at all levels in the organisation, and the value provided by both the measurement and reporting of the KPIs.
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