Robots are increasingly being deployed in densely populated environments, such as homes, hotels, and office buildings, where they rely on explicit instructions from humans to perform tasks. However, complex tasks ofte...
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Robots are increasingly being deployed in densely populated environments, such as homes, hotels, and office buildings, where they rely on explicit instructions from humans to perform tasks. However, complex tasks often require multiple instructions and prolonged monitoring, which can be time-consuming and demanding for users. Despite this, there is limited research on enabling robots to autonomously generate tasks based on real-life scenarios. Advanced intelligence necessitates robots to autonomously observe and analyze their environment and then generate tasks autonomously to fulfill human requirements without explicit commands. To address this gap, we propose the autonomous generation of navigation tasks using natural language dialogues. Specifically, a robot autonomously generates tasks by analyzing dialogues involving multiple persons in a real office environment to facilitate the completion of item transportation between various *** propose the leveraging of a large language model(LLM) through chain-of-thought prompting to generate a navigation sequence for a robot from dialogues. We also construct a benchmark dataset consisting of 625 multiperson dialogues using the generation capability of LLMs. Evaluation results and real-world experiments in an office building demonstrate the effectiveness of the proposed method.
Distinguishing between quality and substandard tablets is vital for public health, patient safety, and regulatory adherence. Stringent healthcare and pharmaceutical regulations underscore the importance of medication ...
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Person re-identification (ReID) aims to identify pedestrian images with the same identity across non-overlapping camera views. Intra-camera supervised person re-identification (ICS-ReID) is a new paradigm that trains ...
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We propose a protocol in quantum illumination (QI) leveraging entanglement in discrete-variable states. Our investigation shows that, as M→∞, the M-mode Bell state matches the 6 dB advantage of the two-mode squeezed...
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We propose a protocol in quantum illumination (QI) leveraging entanglement in discrete-variable states. Our investigation shows that, as M→∞, the M-mode Bell state matches the 6 dB advantage of the two-mode squeezed vacuum in high noise. It also excels in low- and mid-noise conditions, demonstrating that QI's benefits are not restricted to high background noise. Moreover, the protocol benefits from a sequential decision rule, increasing the advantage beyond 6 dB. These findings present an intriguing alternative to continuous-variable states and open different applications for QI using discrete-variable states.
This paper proposes a fair allocation approach for dynamic operating envelope-integrated local energy trading with the intention of offering financial benefits to electricity customers unbiasedly while ensuring distri...
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The growing demand for online programming education underscores the necessity for engaging and efficient learning tools. While interactive exercises enhance student engagement and outcomes, creating them presents chal...
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Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity,pseudo-defect interference,and random elastic *** study evaluates the approach for detect...
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Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity,pseudo-defect interference,and random elastic *** study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection *** paper proposes an improved Gauss-Laplace(LoG)operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection *** the process of scratch identification,it is challenging to differentiate between the scratch edge and the interference ***,local texture screening is utilized by deep learning techniques that evaluate and identify scratch edges and interference edges based on the local texture characteristics of *** have proven that by combining the improved LoG operator with a deep learning strategy,it is able to effectively detect image edges,distinguish between scratch edges and interference edges,and identify clear scratch *** based on the six categories of meta scratches indicate that the proposedmethod has achieved rolled-in crazing(100%),inclusion(94.4%),patches(100%),pitted(100%),rolled(100%),and scratches(100%),respectively.
This paper reports on a single-fed compact slotted implantable patch antenna for biomedical applications. The proposed antenna operates at 915 MHz in the industrial, scientific, and medical (ISM) band. The antenna des...
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This paper proposes a non-isolated high-gain DC-DC converter capable of delivering a lOx voltage gain with a 50 percent duty cycle. The topology represents an enhanced version of the Zeta converter and aims to address...
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Fast fluctuations in wind farm power produce voltage flicker in the *** way to mitigate the flicker is to place a static VAr compensator(SVC).Due to the operating delay of SVCs,it is essential to predict the wind farm...
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Fast fluctuations in wind farm power produce voltage flicker in the *** way to mitigate the flicker is to place a static VAr compensator(SVC).Due to the operating delay of SVCs,it is essential to predict the wind farm reactive ***,a novel fuzzy nonlinear modeling approach is suggested and used in the one-step-ahead prediction of the power *** base of the developed fuzzy modeling is the Takagi-Sugeno fuzzy representation and a dual-unscented Kalman filter(D-UKF).In other words,a nonlinear TS fuzzy system is trained online via the *** forecasted value is used as the SVC’s reference signal.A large amount of actual data gathered from a wind farm is used for the performance *** data is collected in winter and summer for different climate *** the actual data,a current source with changing amplitude and phase which is updated every half-cycle,is used to model the wind *** results,including the flicker indices,confirm the improvement in the SVC’s performance.
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