On Spotify, record labels and media companies have made more than 70 million songs available, even those with digital copyright limitations. In machine learning terminology, attributes or features refer to the qualiti...
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This paper introduces an interactive visualization interface prototype tailored for electrical power grid system planners and analysts to facilitate the exploration of historical outage data and gain actionable insigh...
This paper introduces an interactive visualization interface prototype tailored for electrical power grid system planners and analysts to facilitate the exploration of historical outage data and gain actionable insights. With the advent of smart sensors, data generation has exponentially increased. As the amount of data has significantly grown, so has the need to effectively monitor it. Our prototype addresses this challenge by seamlessly integrating heterogeneous datasets such as GIS, AMI, and OMS. Our interface is designed to empower system planners and analysts in assessing the performance of distribution systems, focusing on circuit efficiency and outage events. This paper describes the functionalities of the visualization interface and presents its example usage scenarios.
COVID-19 is a global pandemic that has threatened the survival of humans and other living beings. COVID-19 causes illnesses varying from the very mild cold to serious health complications resulting in death. Most Info...
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Time-anchored on-screen comments, as known as bullet comments, are a popular feature for online video streaming. Bullet comments reflect audiences' feelings and opinions at specific video timings, which have been ...
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ISBN:
(纸本)9781665496179
Time-anchored on-screen comments, as known as bullet comments, are a popular feature for online video streaming. Bullet comments reflect audiences' feelings and opinions at specific video timings, which have been shown to be beneficial to video content understanding and social connection level. In this paper, we for the first time investigate the problem of bullet comment display and insertion for 360 degrees video via head-mounted display and controller. We design four bullet comment display methods and evaluate their effects on 360 degrees video experiences. We further propose two controller-based methods for bullet comment insertion. Combining the display and insertion methods, the user can experience 360 degrees videos with bullet comments, and interactively post new ones by selecting among existing comments. User study results revealed how the factors of display and insertion methods affect 360 degrees video experience. With the experiment findings, we also discuss useful design insights for 360 degrees video bullet comments.
Breast cancer is one of the leading causes of death in women, hence accurately locating and removing the tumor is crucial. Current wire and non-wire tumor localization methods are invasive and cause patient discomfort...
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ISBN:
(数字)9798350315790
ISBN:
(纸本)9798350315806
Breast cancer is one of the leading causes of death in women, hence accurately locating and removing the tumor is crucial. Current wire and non-wire tumor localization methods are invasive and cause patient discomfort. While Robot-assisted surgery (RAS) has shown potential in enhancing accuracy, dexterity, and surgeon autonomy, the absence of 3D visualization of the tumor and the deformable nature of the breast have made it challenging for it to be used in breast surgeries extensively. In this paper, we propose a non-invasive augmented reality-based tumor localization and visualization system for robot-assisted breast surgeries. The system can superimpose an augmented tumor on the physical breast and estimate its position in response to various deformations in real-time intraoperatively while being displayed on the da Vinci Research Kit (dVRK) surgical console. The performance of the system is analyzed through experiments in two stages and results show sub-centimeter accuracy in tumor overlay and movement.
This article examines the parameters of speech recognition in audio recordings containing a variety of phrases uttered by different people with different accents and intonations. The aim of the study is to evaluate th...
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ISBN:
(数字)9798350374865
ISBN:
(纸本)9798350374872
This article examines the parameters of speech recognition in audio recordings containing a variety of phrases uttered by different people with different accents and intonations. The aim of the study is to evaluate the recognition speed, the accuracy of audio-to-text conversion and resource consumption when using SpeechRecognition and Levenshtein libraries. During the analysis, the above libraries were used to record and recognize audio files, as well as to calculate the distance between two lines and determine the recognition accuracy. The findings of this study can be useful for improving speech recognition systems and creating more adaptive and efficient solutions for audio data processing. The results of comparing the accuracy of speech recognition models are recorded in JSON format, after which, using the matplotlib library, they are visualized as graphs, comparing the speed and accuracy of recognition. visualization of data in this way contributes to their improvement and more effective integration into educational systems. In conclusion, the authors emphasize the prospects for further development of speech recognition technologies in different fields.
With the continuous progress of meteorological data observation technology, meteorological data showed explosive growth, which brought new opportunities and challenges to the development of meteorological forecasting ...
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In this paper, a cloud platform for remote data interaction and visualization in lower limb exoskeleton robot is developed, which is used for rehabilitation training, remote interaction and visualization of patient tr...
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Spotify is a leading music streaming application, with over 180 million users. Its algorithm is designed in a manner that users never run out of relevant songs. Authors in this research work aim to extract, analyze, a...
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Identifying individual dark web services can be challenging, but several methods exist to overcome this challenge. Automated dark web services labeling can be performed using NLP, sentiment analysis, computer vision, ...
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