This study proposes a low-cost microwave sensor for the monitoring of water quality contamination in irrigation systems. The sensor was employed for monitoring the concentration of specific compounds in mixtures of gl...
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Camouflaged object detection(COD)refers to the task of identifying and segmenting objects that blend seamlessly into their surroundings,posing a significant challenge for computer vision *** recent years,COD has garne...
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Camouflaged object detection(COD)refers to the task of identifying and segmenting objects that blend seamlessly into their surroundings,posing a significant challenge for computer vision *** recent years,COD has garnered widespread attention due to its potential applications in surveillance,wildlife conservation,autonomous systems,and *** several surveys on COD exist,they often have limitations in terms of the number and scope of papers covered,particularly regarding the rapid advancements made in the field since *** address this void,we present the most comprehensive review of COD to date,encompassing both theoretical frameworks and practical contributions to the *** paper explores various COD methods across four domains,including both image-level and video-level solutions,from the perspectives of traditional and deep learning *** thoroughly investigate the correlations between COD and other camouflaged scenario methods,thereby laying the theoretical foundation for subsequent ***,we delve into novel tasks such as referring-based COD and collaborative COD,which have not been fully addressed in previous *** object-level detection,we also summarize extended methods for instance-level tasks,including camouflaged instance segmentation,counting,and ***,we provide an overview of commonly used benchmarks and evaluation metrics in COD tasks,conducting a comprehensive evaluation of deep learning-based techniques in both image and video domains,considering both qualitative and quantitative ***,we discuss the limitations of current COD models and propose 9 promising directions for future research,focusing on addressing inherent challenges and exploring novel,meaningful *** comprehensive examination aims to deepen the understanding of COD models and related methods in camouflaged *** those interested,a curated list of CODrelated techniques,datasets,and addit
Transcranial temporal interference stimulation (tTIS) is a promising brain stimulation method that can target deep brain regions by delivering an interfering current from surface electrodes. Most instances of tTIS sti...
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Transcranial temporal interference stimulation (tTIS) is a promising brain stimulation method that can target deep brain regions by delivering an interfering current from surface electrodes. Most instances of tTIS stimulate the brain with a single-frequency sinusoidal waveform generated by wave interference. Theta burst stimulation is an effective stimulation scheme that can modulate neuroplasticity by generating long-term potentiation- or depression-like effects. To broaden tTIS application, we developed a theta burst protocol using tTIS technique to modulate neuroplasticity in rats. Two cannula electrodes were unilaterally implanted into the intact skull over the primary motor cortex. electrical field of temporal interference envelopes generated by tTIS through cannula electrodes were recorded from primary motor cortex. Theta burst schemes were characterized, and motor activation induced by the stimulation was also evaluated simultaneously by observing electromyographic signals from the corresponding brachioradialis muscle. After validating the stimulation scheme, we further tested the modulatory effects of theta burst stimulation delivered by tTIS and by conventional transcranial electrical stimulation on primary motor cortex excitability. Changes in the amplitude of motor evoked potentials, elicited when the primary motor cortex was activated by electrical pulses, were measured before and after theta burst stimulation by both techniques. Significant potentiation and suppression were found at 15 to 30 min after the intermittent and continuous theta burst stimulation delivered using tTIS, respectively. However, comparing to theta burst stimulations delivered using conventional form of transcranial electrical stimulation, using tTIS expressed no significant difference in modulating motor evoked potential amplitudes. Sham treatment from both methods had no effect on changing the motor evoked potential amplitude. The present study demonstrated the feasibility of usin
We have successfully demonstrated, for the first time, an innovative back-end-of-line (BEOL) compatible electro-optic modulator and memory (EOMM) based on Lithium Niobate on Insulator (LNOI) micro-ring resonator (MRR)...
Fabric cooling channels for twisted coiled actuators (TCAs) were recently proposed to achieve the required response times for motion assistance in a manner suitable for soft wearable robotic devices. While previous wo...
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ISBN:
(数字)9798350386523
ISBN:
(纸本)9798350386530
Fabric cooling channels for twisted coiled actuators (TCAs) were recently proposed to achieve the required response times for motion assistance in a manner suitable for soft wearable robotic devices. While previous work demonstrated that the fabric channel reduced the cooling time by 42% in comparison to the same TCA without the cooling channel, the TCAs were still not cooled quickly enough to support human motion. Therefore, in this paper, two variations to the channel are proposed to further reduce the cooling time of the TCAs. The variations include unsealing the inlet and adding vents along the length of the channel to take advantage of air entrainment and natural convection. While both variations reduced the cooling time on their own, when they were employed together there was a 34% reduction in cooling time compared to the original channel design (
$19.1 \pm 2.4\ \mathrm{s}$
vs.
$13.5 \pm 0.9\ \mathrm{s}, \mathrm{p} < 0.001$
). This decrease occurred without any significant differences in the stroke or heating time of the TCA. The modified channel was then compared to the TCA without the cooling apparatus and the cooling time was reduced by 57% (
$25.1 \pm 1.7\ \mathrm{s}$
vs.
$14.0 \pm 1.2\ \mathrm{s}, \mathrm{p} < 0.001)$
. This work advances the development of a cooling system for TCAs, making it suitable for soft wearable robotic devices by improving portability, and thereby enabling their use in wearable devices for rehabilitation applications.
We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a large language model (LLM). Our maximum likelihood model leverages expert-writ...
We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a large language model (LLM). Our maximum likelihood model leverages expert-written and AI-generated reference texts to accurately and efficiently examine real-world LLM-use at the corpus level. We apply this approach to a case study of scientific peer review in AI conferences that took place after the release of ChatGPT: ICLR 2024, NeurIPS 2023, CoRL 2023 and EMNLP 2023. Our results suggest that between 6.5% and 16.9% of text submitted as peer reviews to these conferences could have been substantially modified by LLMs, i.e. beyond spell-checking or minor writing updates. The circumstances in which generated text occurs offer insight into user behavior: the estimated fraction of LLM-generated text is higher in reviews which report lower confidence, were submitted close to the deadline, and from reviewers who are less likely to respond to author rebuttals. We also observe corpus-level trends in generated text which may be too subtle to detect at the individual level, and discuss the implications of such trends on peer review. We call for future interdisciplinary work to examine how LLM use is changing our information and knowledge practices.
This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between...
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ISBN:
(数字)9798350386844
ISBN:
(纸本)9798350386851
This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between efficiency and detail, it cuts triangle count from over 160,000 to below 4,000, maintaining high DPI. The approach automates optimization, promising scalability and efficiency in VR fashion, setting a foundation for future 3D content development, enhancing virtual garment realism and interactivity.
We demonstrate Purcell enhancement of a single T center integrated in a silicon photonic crystal cavity, increasing the fluorescence decay rate by a factor of 6.89 and achieving a photon outcoupling rate of 73.3 kHz. ...
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