An actual task nowadays is to identify remaining defects in software products after their testing. The purpose of this study is to develop an intelligent information technology for identification of remaining defects ...
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The use of features of the internal circuitry of integrated circuits (ICs), when designing pulse shapers based on transistor-transistor logic (TTL) ICs, provides the maximum steepness of the generated pulse edges with...
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This paper presents an approach for developing an interoperable and privacy-respecting smart city data ecosystem. We propose an architecture that enables companies to share data securely and efficiently, while also re...
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This paper presents a wireless sensor network employing heterogeneous mobile robot platforms designed for data-acquisition and research in agriculture, forestry and green spaces in smart cities. Where conventional sen...
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As human-robot interaction (HRI) advances, the nuanced interpretation of implicit commands embedded in human gestures becomes paramount for fostering seamless collaboration. In this context, we present a novel machine...
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ISBN:
(纸本)9798350355376;9798350355369
As human-robot interaction (HRI) advances, the nuanced interpretation of implicit commands embedded in human gestures becomes paramount for fostering seamless collaboration. In this context, we present a novel machine learning algorithm designed to endow robots with the ability to decipher implicit commands from Inertial Measurement Unit (IMU) sensor data worn at specific locations on the human body. Our approach integrates memory and attention mechanisms inspired by ideomotor cues, allowing the robot to comprehend both temporal and spatial relationships within the sensor data. The attention mechanism operates bidirectionally, enhancing the system's awareness of the temporal sequence of human movements and the spatial interdependencies between sensor data across different body locations. This unique spatial attention enables the robot to understand the kinematic chain between joints during human motion, accommodating variations in sensor data arising from factors such as height differences and motion range capacity. Drawing on prior research in attention mechanisms, ideomotor cues, and memory augmentation, our algorithm represents a significant advancement in addressing the challenges of implicit command understanding in HRI. The proposed system's adaptability and nuanced comprehension of human gestures make it well-suited for diverse anatomies and movement patterns. Through comprehensive experiments, we demonstrate the effectiveness of our algorithm, paving the way for more intuitive and adaptable robotic systems in real-world applications.
This paper presents a system for continuous vibration recording using sensors in a smartphone and the MATLAB Mobile application. The study aims to compare two different ways of measurement: using a mobile phone for th...
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The precise description of the photons' scattering in matter is a complex physical, mathematical and computational task. However, just the scattered radiation is the dominant factor of X-ray images formation. So a...
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The article presents an approach to pollution data for EU countries correlated to the Summary Innovation Index (SII). The analysis is based on data from 2015 to 2020. It compares pollution with health problems and dea...
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An intelligent air quality monitoring system, based on the versatile and widely-used Arduino Uno microcontroller, has been designed and developed as the foundational platform. The system was subjected to testing proce...
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Biometric security systems are rapidly developing and becoming widespread. The purpose of the research is to develop a system for recognizing a person's face, since these are contactless identification systems and...
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