187 research outputs found
Replication Data for: Investigating Locality Effects and Surprisal in Written English Syntactic Choice Phenomena
No full textThis datset can be used to replicate the main findings of our paper:
Rajakrishnan Rajkumar, Marten van Schinjdel, Michael White, and William Schuler. Investigating Locality Effects and Surprisal in Written English Syntactic Choice Phenomena. Cognition, To appea
DandeBot - An Autonomous Weeding Solution for Residential Lawns
No full textDandeBot – An Autonomous Weeding Solution for Residential Lawns
Author: Nishanth Rajkumar
This thesis presents the development and validation of DandeBot, an autonomous robotic system designed for comprehensive residential lawn maintenance. The robot addresses the need for efficient, eco-conscious, and low maintenance lawn care through a fully electric platform powered by an AI-driven software stack. Emphasizing safety, adaptability, and ease of use, the hardware was developed using CAD and Design for Manufacturing (DFM) principles, resulting in a modular and robust design. The integrated software stack combines localization, mapping, and path planning using odometry, visual odometry, and IMU data fusion to navigate dynamic outdoor environments. Task-specific algorithms were developed and validated for autonomous navigation, weed detection, and obstacle avoidance. Key hardware innovations include a modular gripper system for weed removal and adaptable attachments for multiple lawn care tasks. Field trials confirmed the robot’s capability to perform with high precision and reliability in varied lawn conditions, significantly reducing the need for human intervention. This work contributes to the growing field of service robotics by demonstrating how intelligent systems can automate routine household maintenance. The thesis concludes by outlining future research directions, including system scalability, enhanced multi-tasking capabilities, and integration with smart home networks
Exploring Stability and Accuracy Limits of Distributed Real-Time Power System Simulations via System-of-Systems Cosimulation
No full textElectro-Magnetic Transients (EMT) is the most accurate, but computationally expensive method of analyzing power system phenomena. Thereby, interconnecting several real-time simulators can unlock scalability and system coverage, but leads to a number of new challenges, mainly in time synchronization, numerical stability, and accuracy quantification. This study presents such a co-simulation, based on Digital Real-Time Simulator (DRTS), connected via Aurora 8B/10B protocol. Such a setup allows to analyze complex and hybrid System-of-Systems (SoS) whose resulting numerical phenomena and artifacts have been poorly investigated and understood so far. We experimentally investigate the impact of IEEE 1588 Precision Time Protocol (PTP) synchronization assessing both time and frequency domains. The analysis of the experimental results is encouraging and show that numerical stability can be maintained even with complex system setups. Growing shares of inverter-based renewable power generation require larger and interconnected EMT system studies. This work helps to understand the phenomena connected to such DRTS advanced co-simulation setups
Semantic Question Classification Datasets
No full textThis is the datasets used in the following paper:Can Taxonomy Help? Improving Semantic Question Matching using Question TaxonomyPaper: http://aclweb.org/anthology/C18-1042If you use the dataset please cite the following paper:@InProceedings{C18-1042,
author = "Gupta, Deepak
and Pujari, Rajkumar
and Ekbal, Asif
and Bhattacharyya, Pushpak
and Maitra, Anutosh
and Jain, Tom
and Sengupta, Shubhashis",
title = "Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy",
booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
year = "2018",
publisher = "Association for Computational Linguistics",
pages = "499--513",
location = "Santa Fe, New Mexico, USA",
url = "http://aclweb.org/anthology/C18-1042"
}
</div
Stability and Accuracy Analysis of a Real-time Co-simulation Infrastructure
No full textCo-simulation techniques are gaining popularity amongst the power system research community to analyse future scalable Smart Grid solutions. However, complications such as multiple communication protocols, uncertainty in latencies are holding-up the widespread usage of these techniques for power system analysis. These issues are even further exacerbated when applied to Digital Real-Time Simulations (DRTS) with strict real-time constraints for Power Hardware-In-the-Loop (PHIL) tests. In this paper, we thoroughly test and demonstrate an innovative co-simulation infrastructure that allows to interconnect different DRTS through the Aurora 8B/10B protocol to reduce the effects of communication latency and respect real-time constraints. The Ideal Transformer Method Interface Algorithm (ITM IA), commonly used in PHIL applications, is used to interface the DRTS. Finally, we present time-domain and frequency-domain accuracy analyses on the obtained experimental results to demonstrate the potential of the proposed infrastructure.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Electrical Power Grid
Towards Broad Coverage Surface Realization with CCG
No full textThis paper reports on progress towards developing the first broad coverage English surface realizer for Combinatory Categorial Grammar (CCG). The paper provides initial automatic evaluation results which are roughly comparable to those reported with other formalisms when using a (nonblind) grammar derived from the development section of the CCGbank; the results are worse, though still respectable, when using the standard dev/train/test splits, highlighting the need for better lexical smoothing and more focused search. The paper also shows that factored language models that interpolate word-level n-grams with n-grams over POS tags and supertags provide similar absolute performance improvements over word-level n-grams as have been observed with parsing-inspired log-linear models.
Interference Predicts Locality: Evidence from an SOV Language
No full textLocality and Interference are two mechanisms which are attested to drive sentence comprehension. However, the relationship between them remains unclear---are they alternative explanations or do they operate independently? To answer this question, we test the hypothesis that in Hindi, interference effects (measured by semantic similarity and case markers) significantly predict locality effects (modelled using dependency length quantifying distance between syntactic heads and their dependents) within a sentence, while controlling for expectation-based measures and discourse givenness. Using data from the Hindi-Urdu Treebank corpus (HUTB), we validate the stated hypothesis. We demonstrate that sentences with longer dependency length consistently have semantically similar preverbal dependents, more case markers, greater syntactic surprisal, and violate intra-sentential givenness considerations. Overall, our findings point towards the conclusion that locality effects are reducible to broader memory interference effects rather than being distinct manifestations of locality in syntax. Finally, we discuss the implications of our findings for the theories of interference in comprehension
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