811 research outputs found

    Implementation of an efficient Fuzzy Logic based Information Retrieval System

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    This paper exemplifies the implementation of an efficient Information Retrieval (IR) System to compute the similarity between a dataset and a query using Fuzzy Logic. TREC dataset has been used for the same purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query. Each query is assigned a score value based on its fuzzy similarity with the index keywords. The relevant documents are retrieved based on the score value. The performance and accuracy of the proposed fuzzy similarity model is compared with Cosine similarity model using Precision-Recall curves. The results prove the dominance of Fuzzy Similarity based IR system.Comment: arXiv admin note: substantial text overlap with http://ntz-develop.blogspot.in/ , http://www.micsymposium.org/mics2012/submissions/mics2012_submission_8.pdf , http://www.slideshare.net/JeffreyStricklandPhD/predictive-modeling-and-analytics-selectchapters-41304405 by other author

    A Knowledge-Grounded Multimodal Search-Based Conversational Agent

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    Multimodal search-based dialogue is a challenging new task: It extends visually grounded question answering systems into multi-turn conversations with access to an external database. We address this new challenge by learning a neural response generation system from the recently released Multimodal Dialogue (MMD) dataset (Saha et al., 2017). We introduce a knowledge-grounded multimodal conversational model where an encoded knowledge base (KB) representation is appended to the decoder input. Our model substantially outperforms strong baselines in terms of text-based similarity measures (over 9 BLEU points, 3 of which are solely due to the use of additional information from the KB

    Improving Context Modelling in Multimodal Dialogue Generation

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    In this work, we investigate the task of textual response generation in a multimodal task-oriented dialogue system. Our work is based on the recently released Multimodal Dialogue (MMD) dataset (Saha et al., 2017) in the fashion domain. We introduce a multimodal extension to the Hierarchical Recurrent Encoder-Decoder (HRED) model and show that this extension outperforms strong baselines in terms of text-based similarity metrics. We also showcase the shortcomings of current vision and language models by performing an error analysis on our system's output

    Helping or Hindering? How Browser Extensions Undermine Security

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    Browser extensions enhance the functionality of native Web applications on the client side. They provide a rich end-user experience by utilizing feature-rich JavaScript APIs, otherwise inaccessible for native applications. However, prior studies suggest that extensions may degrade the client-side security to execute their operations, such as by altering the DOM, executing untrusted scripts in the applications' context, and performing other security-critical operations for the user. In this study, we instead focus on extensions that tamper with the security headers between the client-server exchange, thereby undermining the security guarantees that these headers provide to the application. To this end, we present our automated analysis framework to detect such extensions by leveraging static and dynamic analysis techniques. We statically identify extensions with the permission to modify headers and then instrument the dangerous APIs to investigate their runtime behavior with respect to modifying headers in-flight. We then use our framework to analyze the three snapshots of the Chrome extension store from Jun 2020, Feb 2021, and Jan 2022. In doing so, we detect 1,129 distinct extensions that interfere with security-related request/response headers and discuss the associated security implications. The impact of our findings is aggravated by the extensions, with millions of installations dropping critical security headers like Content-Security-Policy or X-Frame-Options

    Assessment of foot trajectories and ground reaction force in a trans-femoral amputee with Jaipur Knee and 3R20 knee joints

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    In developing countries like India, unilateral transfemoral amputees encounter with the challenge to select and evaluate the knee joint performance. This study aims to evaluate the response of knee joint on vertical ground reaction forces (vGRFs), walking speed, range of motion (ROM) of joints like hip, knee and ankle joints in first two weeks and enhanced response. Movements of different joints were recorded through VICON motion analysis system. Vertical ground reaction forces were captured through AMTI strain gauzed force plate. It has been observed that in two weeks normalized speed increases 0.41 to 0.49 with 3R20. Range of motion of joints was observed with interesting fact that in general with 3R20, joints angle their respective ROM were more than Jaipur Knee but in same cases in second half of gait cycle Jaipur Knee responded better than 3R20 knee joint
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