In Active Learning (AL) applications, it is crucial to develop a model that efficiently represents data using a limited number of labeled samples. In this context, an oracle is often employed to label samples that are...
详细信息
India’s reliance on fossil fuels to meet its energy generation demands has a negative impact on both the environment and public health. In the present energy transition, photovoltaic (PV) technologies have become mor...
详细信息
The bandwidth and latency requirements of modern datacenter applications have led researchers to propose various topology designs using static, dynamic demand-oblivious (rotor), and/or dynamic demand-aware switches. H...
详细信息
This paper investigates bidirectional DC-DC converters in distributed electric propulsion systems, focusing on the dual active bridge (DAB) converter. To minimize voltage fluctuations in aircraft operating under compl...
详细信息
We study randomized algorithms for the online non-crossing matching problem. Given an online sequence of n online points in general position, the goal is to create a matching of maximum size so that the line segments ...
Abnormal growth of cells in the brain and its surrounding tissues is known as a brain tumor. There are two types, one is benign (non-cancerous) and another is malignant (cancerous) which may cause death. The radiologi...
详细信息
The Named Data Networking (NDN) paradigm has been used as a promising vehicle communication model, namely the Vehicular Named Data Networking (V-NDN) model. In NDN, delivery of interest in the NDN network is done by s...
详细信息
This work introduces a refined image-processing method explicitly designed to amalgamate raster-scanned images obtained with a compact planar microwave resonator. The resonator tuned for use on the skin provides a dee...
详细信息
ISBN:
(数字)9798331510473
ISBN:
(纸本)9798331510480
This work introduces a refined image-processing method explicitly designed to amalgamate raster-scanned images obtained with a compact planar microwave resonator. The resonator tuned for use on the skin provides a deeper field penetration into the dermis layer, compared to the skin impedance measurements. The resonance of the sensor is sensitive to the dielectric properties of the tissues underneath the skin. Healthy and abnormal tissues exhibit different dielectric characteristics. Pixelated images can leverage resonant frequencies and reflection coefficients to enhance contrasts and boundaries to identify the abnormal tissues. We proposed using analytical tools like the structural similarity index to correlate frequency shifts with reflection coefficient magnitudes precisely. Preliminary results suggested the adeptness of the technique at classifying whether the tissue depth surpasses 15 mm and detecting tumor locations with a high accuracy when the image depth does not exceed 15 mm. A compact neural network model was implemented for processing the microwave images when the tumor depth exceeded 15 mm and achieved a high Dice coefficient. The work incorporated simulations to substantiate the novel concept and demonstrated its potential for noninvasive, efficient, and cost-effective subcutaneous imaging in medical applications.
Visual imagery is a critical perceptual source in human-robot interaction (HRI), extensively applied in various domains such as robotic navigation, target detection, and task planning. Aerial robots, also known as UAV...
详细信息
ISBN:
(纸本)9789819789627
Visual imagery is a critical perceptual source in human-robot interaction (HRI), extensively applied in various domains such as robotic navigation, target detection, and task planning. Aerial robots, also known as UAVs, are the typical representatives of teleoperation robots. The substantial distance between humans and remotely operated robots, coupled with the dynamic and open environments these robots navigate, exposes image-based HRI to significant security risks from both known and unknown threats. The trustworthiness of data sources is a fundamental prerequisite for ensuring the security of HRI systems. However, the multidimensionality of trust factors and the uncertainty of trust evidence have constrained its practical application. To advance this field, we have innovatively proposed a trust evaluation scheme based on multidimensional evidence fusion within the Belief Functions (BFs) framework. This scheme constructs an adaptive trust evaluation model capable of addressing both known and unknown threats. For known threats, we developed coarse-grained multidimensional trust elements and employed multiple lightweight SVM submodels to construct Basic Belief Assignments (BBAs), thereby achieving direct trust modeling and enabling rapid trust evaluation of images. Conversely, for unknown threats, we utilized pretrained models to establish fine-grained multidimensional trust elements, implementing indirect trust modeling through trust recommendation, thus facilitating indirect trust evaluation of images. We further combined direct and indirect trust to derive a overall trust assessment of the images, achieving adaptive dynamic trust evaluation in image-based HRI. Additionally, to more accurately represent image trustworthiness, we introduced a BBAs weighted fusion method, which aids in more rational trust aggregation. To validate the efficacy of our proposed method, we conducted experiments on a real aerial image dataset. The results demonstrate that our approach ef
Cyber-physical systems, such as unmanned aerial vehicles and connected and autonomous vehicles, are vulnerable to cyber attacks, which can cause significant damage to society. This paper examines the attack issue in c...
详细信息
Cyber-physical systems, such as unmanned aerial vehicles and connected and autonomous vehicles, are vulnerable to cyber attacks, which can cause significant damage to society. This paper examines the attack issue in cyber-physical systems within the framework of discrete event systems. Specifically, we consider a scenario where a malicious intruder injects a jamming signal into an actuator channel. It disrupts the transmission of control commands and prevents an actuator from receiving them. This is termed an actuator jamming attack. In the paper, we first analyze the closed-loop system behavior under such an attack. An attack structure is constructed to illustrate how an intruder exploits a jamming attack to drive a system into unsafe states. Then, we study the supervisory control problem for a system exposed to such an attack. The problem is reduced to a basic supervisory control one in discrete event systems by introducing the concept of dynamically controllable language. A solution to this problem is explored, where we establish an existence condition for a supremal and robust supervisor that is capable of defending against actuator jamming attacks, and design an algorithm to derive it. Finally, the effectiveness of our method is illustrated by an intelligent automated guided vehicle system. IEEE
暂无评论