Results from a study on Perceived Sociability of a robot dependent on different gaze behaviors of human observers are presented. A 2x2 between-subjects design is used with independent variables’gaze-behavior’ (stati...
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Understanding documents with rich layouts is an essential step towards information extraction. Business intelligence processes often require the extraction of useful semantic content from documents at a large scale fo...
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Image-to-image translation has become an important technique in computervision and focuses on preserving the effective content of images while enabling them to be translated from one domain to another. Among differen...
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In the following, we analyze and discuss the implementation of a novel approach for distributed flocking behavior applied to a group of Uncrewed Aerial Vehicle (UAV)s, also referred to as drones. Inspired by natural f...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
In the following, we analyze and discuss the implementation of a novel approach for distributed flocking behavior applied to a group of Uncrewed Aerial Vehicle (UAV)s, also referred to as drones. Inspired by natural flocking phenomena observed in birds, which demonstrate coordinated movement in response to internal and external stimuli, we tackle the problem of robust and dynamic aerial motion for robots and design a control law based on a novel physical model. In contrast to previous works that rely on velocity or position-based references, this approach leverages an acceleration-based law to describe the collective dynamics of many interacting particles. As observed in the following, a third-order control possesses several advantages compared to first or second-order control, such as smoother transitions, better force balancing, and more responsive and dynamic behaviors. These advantages are thoroughly analyzed in the following, thanks to physics-based realistic simulations and field experiments with medium-sized UAVs in an unstructured outdoor environment.
High accuracy, low latency and high energy efficiency represent a set of conflicting goals when searching for system solutions for image classification and detection. While high-quality images naturally result in more...
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Person search, which aims to find the target person in the whole scene images, has become a crucial application in security surveillance with various types of noise. Existing methods solve this problem by addressing t...
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The gender gap in STEM is an issue that affects regions and countries worldwide. Furthermore, the percentage of women in these areas depends on a range of different factors. In particular, the gender gap is critical i...
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An SIEM system enabled by Artificial Intelligence (AI) was proposed to solve the major challenges of current security monitoring practices. The proposed architecture incorporates the use of artificial intelligence at ...
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ISBN:
(数字)9798331597092
ISBN:
(纸本)9798331597108
An SIEM system enabled by Artificial Intelligence (AI) was proposed to solve the major challenges of current security monitoring practices. The proposed architecture incorporates the use of artificial intelligence at all levels of the security operation center to transform traditional security operations from passive detection to active protection. The system design incorporates the application of machine learning for pattern recognition, contextual analysis, and alert prioritization to overcome the major challenges of traditional SIEM solutions that are based on rules and produce numerous alerts. The detection efficiencies for complicated attack patterns, including APT and zero-day attacks, were found to be significantly higher than those of the conventional systems in the experimental analysis. Integration with high-performance computing provides real-time security data analysis without compromising the performance, whereas the mean time to detection and response is significantly reduced. The effectiveness of the system in detecting threats early, classifying them correctly, and recommending response actions in multiple case studies involving various attacks was demonstrated. The architecture is a major improvement over current security monitoring technologies, and it provides more effective protection against ever-increasing threats with less analyst workload through contextualized and automated alerts.
Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly...
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Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly restricted to self-sustained steady state,controllable manipulation and dynamic switching between period doubling and other intriguing dynamical states are still largely ***,we propose to expand the vision of dissipative soliton periodic doubling,which we illustrate experimentally by reporting original spontaneous,collisional,and controllable spectral period doubling in a polarization-maintaining ultrafast fiber ***,the spontaneous period doubling can be observed in both single-and *** mechanism of the switchable state and periodic doubling was revealed by numerical ***,state transformation of individual solitons can be resolved during the collision of triple solitons involving stationary,oscillating,and period ***,controllable deterministic switching between period doubling and other dynamical states,as well as exemplifying the application of period-doubling-based digital encoding,is achieved under programmable pump *** results open a new window for unveiling complex Hopf bifurcation in dissipative systems and bring useful insights into nonlinear science and applications.
Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road *** a result,reckle...
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Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road *** a result,reckless driving behaviour can cause congestion and *** vision and multimodal sensors have been used to study driving behaviour categorization to lessen this *** research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s *** the other hand,driving a car is a complicated action that requires a wide range of body *** this work,we proposed a ResNet-SE model,an efficient deep learning classifier for driving activity clas-sification based on signal data obtained in real-world traffic conditions using smart ***-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning *** data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this *** performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LSTMs)to demonstrate its *** to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.
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