Understanding neuronal structure and function is essential to studying the human brain. The goal of this project was to create a model of human brain neurons that accurately reflects neuronal function, energy consumpt...
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Sequence modeling faces challenges in capturing long-range dependencies across diverse tasks. Recent linear and transformer-based forecasters have shown superior performance in time series forecasting. However, they a...
Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosi...
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Object segmentation is one of the main activities for the robot to create a sense of its environment. This task is a precursor to other activities, such as autonomous navigation in a given environment. Through sensors...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
Object segmentation is one of the main activities for the robot to create a sense of its environment. This task is a precursor to other activities, such as autonomous navigation in a given environment. Through sensors such as LiDAR, it's possible to generate high-resolution three-dimensional maps of the environment in which the robot is located, thus enabling their interpretation so that tasks such as object segmentation can be performed. In this article, the DBSCAN and HDBSCAN unsupervised clustering methods are explored. Results in a simulated environment in Gazebo together with Robot Operating System ROS framework for capturing sensory data from LiDAR Livox Mid-70 coupled to a mobile robot show the performance of such techniques through comparisons.
Since 2019, the world has suffered from the outbreak of the "Coronavirus Disease (COVID)-19 pandemic. This study used the principle of Ultraviolet (UV)-C disinfection to produce a mobile high-power UV-C sterilize...
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This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization ac...
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The emergence of OpenAI's ChatGPT is paying a lot of attention to Generative AI and its impact on Academic integrity. Generative AI is a system designed to generate content or output such as text, image, audio, si...
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We present Text2PointCloud, a method to process sparse, noisy point cloud input and generate high-quality stylized output. Given point cloud data, our iterative pipeline stylizes and deforms points guided by a text de...
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The electrically evoked compound action potential (ECAP) has been used in various clinical studies and has become a key physiological signal for cochlear implants (CI). This study used four sensing electrodes to recor...
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ISBN:
(数字)9798350348958
ISBN:
(纸本)9798350348965
The electrically evoked compound action potential (ECAP) has been used in various clinical studies and has become a key physiological signal for cochlear implants (CI). This study used four sensing electrodes to record ECAP signals based on the alternating polarity approach. An electrical field imaging (EFI) result based on the finite element method was used to obtain the interface impedance, then ECAP simulation results were computed and compared with a patient's clinical ECAP measurements. Preliminary modeling results show that the interface impedance obtained by this EFI-based technique can improve the simulation accuracy of the ECAP model. The ECAP modeling result will be compared with clinical ECAP measurements to validate the model in the full paper.
In this study, a robust Linear Quadratic Regulator (LQR) controller was developed and evaluated for the Bebop 2 quadrotor drone. Polytopic uncertainties in the dynamic model were taken into account in the control desi...
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ISBN:
(数字)9798331538606
ISBN:
(纸本)9798331538613
In this study, a robust Linear Quadratic Regulator (LQR) controller was developed and evaluated for the Bebop 2 quadrotor drone. Polytopic uncertainties in the dynamic model were taken into account in the control design, ensuring robustness. The drone's localization was achieved using fiducial markers and a Kalman Filter for state estimation, integrating visual and positional data. The controller design utilized Linear Matrix Inequalities (LMIs) to optimize performance while accounting for system constraints. A circular trajectory in three-dimensional space was employed to assess the controller's effectiveness in simulation. Results demonstrated precise trajectory tracking, stability, and robust performance despite parameter uncertainties. These findings highlight the applicability of the proposed framework for real-world scenarios involving underactuated UAVs.
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