Near-field scanning study for radio frequency interference estimation

This dissertation discusses the novel techniques using near-fields scanning to do radio frequency interference (RFI) estimation. As the electronic products are becoming more and more complicated, the radio frequency (RF) receiver in the system is very likely interfered by multiple noise sources simultaneously. A method is proposed to identify the interference from different noise sources separately, even when they are radiating at the same time. This method is very helpful for engineers to identify the contribution of the coupling from different sources and further solve the electromagnetic interference issues efficiently. On the other hand, the equivalent dipole-moment models and a decomposition method based on reciprocity theory can also be used together to estimate the coupling from the noise source to the victim antennas. This proposed method provides convenience to estimate RFI issues in the early design stage and saves the time of RFI simulation and measurements. The finite element method and image theory can also predict the far fields of the radiation source, locating above a ground plane. This method applies the finite element method (FEM) to get the equivalent current sources from the tangential magnetic near fields. With the equivalent current sources, the far-field radiation can be calculated based on Huygens\u27s Principle and image theory. By using only the magnetic near fields on the simplified Huygens\u27s surface, the proposed method significantly saves measurement time and cost while also retaining good far-field prediction --Abstract, page iv

EvaSurf: Efficient View-Aware Implicit Textured Surface Reconstruction on Mobile Devices

Reconstructing real-world 3D objects has numerous applications in computer vision, such as virtual reality, video games, and animations. Ideally, 3D reconstruction methods should generate high-fidelity results with 3D consistency in real-time. Traditional methods match pixels between images using photo-consistency constraints or learned features, while differentiable rendering methods like Neural Radiance Fields (NeRF) use differentiable volume rendering or surface-based representation to generate high-fidelity scenes. However, these methods require excessive runtime for rendering, making them impractical for daily applications. To address these challenges, we present $\textbf{EvaSurf}$, an $\textbf{E}$fficient $\textbf{V}$iew-$\textbf{A}$ware implicit textured $\textbf{Surf}$ace reconstruction method on mobile devices. In our method, we first employ an efficient surface-based model with a multi-view supervision module to ensure accurate mesh reconstruction. To enable high-fidelity rendering, we learn an implicit texture embedded with a set of Gaussian lobes to capture view-dependent information. Furthermore, with the explicit geometry and the implicit texture, we can employ a lightweight neural shader to reduce the expense of computation and further support real-time rendering on common mobile devices. Extensive experiments demonstrate that our method can reconstruct high-quality appearance and accurate mesh on both synthetic and real-world datasets. Moreover, our method can be trained in just 1-2 hours using a single GPU and run on mobile devices at over 40 FPS (Frames Per Second), with a final package required for rendering taking up only 40-50 MB.Comment: Project Page: http://g-1nonly.github.io/EvaSurf-Website

Augmented Genetic Algorithm V2 with Reinforcement Learning for PDN Decap Optimization

Genetic Algorithms (GAs) Use Many Hyperparameters, and Tuning These Parameters Can Determine the Optimization Performance. a GA with an Augmented Initial Population Was Proposed for Decap Optimization but It Had Convergence Issues by Getting Stuck in the Local Minimum. This Work Uses a Reinforcement Learning (RL) Approach to Adaptively Tune the Hyperparameters of GA during its Operation. with This Approach, the Agent Tries to Change the Parameters So that the GA Does Not Get Stuck in the Local Minimum. the Proposed Method Combining the RL Agent and Augmented GA Showed Better Performance in Terms of Solution Quality and Time Cost. overall, in All the Cases Tested, the Proposed Method Showed Better Performance Than the Augmented GA Without RL

Rapid assessment of early biophysical changes in K562 cells during apoptosis determined using dielectrophoresis

Apoptosis, or programmed cell death, is a vital cellular process responsible for causing cells to self-terminate at the end of their useful life. Abrogation of this process is commonly linked to cancer, and rapid detection of apoptosis in vitro is vital to the discovery of new anti-cancer drugs. In this paper, we describe the application of the electrical phenomenon dielectrophoresis for detecting apoptosis at very early stages after drug induction, on the basis of changes in electrophysiological properties. Our studies have revealed that K562 (human myelogenous leukemia) cells show a persistent elevation in the cytoplasmic conductivity occurring as early as 30 minutes following exposure to staurosporine. This method therefore allows a far more rapid detection method than existing biochemical marker methods

The dynamic evolution of multipoint interplanetary coronal mass ejections observed with BepiColombo, Tianwen-1, and MAVEN

We present two multipoint interplanetary coronal mass ejections (ICMEs) detected by the Tianwen-1 and Mars Atmosphere and Volatile Evolution spacecraft at Mars and the BepiColombo (0.56 au ∼0.67 au) upstream of Mars from 2021 December 5 to 31. This is the first time that BepiColombo is used as an upstream solar wind monitor ahead of Mars and that Tianwen-1 is used to investigate the magnetic field characteristics of ICMEs at Mars. The Heliospheric Upwind Extrapolation time model was used to connect the multiple in situ observations and the coronagraph observations from STEREO/SECCHI and SOHO/LASCO. The first fast coronal mass ejection event (∼761.2 km s−1), which erupted on December 4, impacted Mars centrally and grazed BepiColombo by its western flank. The ambient slow solar wind decelerated the west flank of the ICME, implying that the ICME event was significantly distorted by the solar wind structure. The second slow ICME event (∼390.7 km s−1) underwent an acceleration from its eruption to a distance within 0.69 au and then traveled with the constant velocity of the ambient solar wind. These findings highlight the importance of background solar wind in determining the interplanetary evolution and global morphology of ICMEs up to Mars distance. Observations from multiple locations are invaluable for space weather studies at Mars and merit more exploration in the future

Far-Field Prediction by only Magnetic Near Fields on a Simplified Huygens\u27s Surface

For radiation source locating above a ground plane, its far field can be predicted by only the magnetic near field through the method proposed in this paper. This method applies the finite element method to get the equivalent current sources from the tangential magnetic near fields. With the equivalent current sources, the far-field radiation can be calculated based on Huygens\u27s principle and image theory. The magnetic near field is scanned on a Huygens\u27s surface that encloses the source with its ground. In this paper, this Huygens\u27s surface was first proposed as a five-surface cube on the ground. Then, the Huygens\u27s surface was further simplified by using four lines instead of four side walls to make the proposed method easier in regards to practical near-field scanning. Several numerical examples were tested to validate the proposed method. In addition, the proposed method was validated experimentally by using a patch antenna. The performance of using only the top plane near fields was also investigated and discussed. By using only the magnetic near fields on the simplified Huygens\u27s surface, the proposed method significantly saves measurement time and cost while also retaining good far-field prediction

Identifying Interference from Multiple Noise Sources by Magnetic Near Fields Only

As electronic products become more and more complicated, multiple noise sources very likely interfere with the radio frequency receiver simultaneously. This paper proposes a method to identify the interference from different noise sources separately, even when they are radiating at the same time. This method converts magnetic fields to electric fields by the finite-element method (FEM) and employs the decomposition method based on reciprocity theory. In the proposed method, Huygens\u27s surface will be set up for each source. The tangential magnetic near fields on each Huygens\u27s surface are used to solve tangential electric fields correspondingly by the FEM. Then, the sources are removed but their Huygens\u27s surfaces are kept. The victim structure is excited in this case to get the tangential magnetic fields on Huygens\u27s surfaces. A creative FEM processing procedure is applied to obtain tangential electric fields in this situation. Finally, with these two groups of fields, the interference from each noise source can be estimated separately based on reciprocity theory. This method is validated by a numerical example. It is very helpful for engineers to be able to identify the contribution of the coupling from different sources and further solve the electromagnetic interference issues efficiently

Real-Time HD Map Change Detection for Crowdsourcing Update Based on Mid-to-High-End Sensors

Continuous maintenance and real-time update of high-definition (HD) maps is a big challenge. With the development of autonomous driving, more and more vehicles are equipped with a variety of advanced sensors and a powerful computing platform. Based on mid-to-high-end sensors including an industry camera, a high-end Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU), and an onboard computing platform, a real-time HD map change detection method for crowdsourcing update is proposed in this paper. First, a mature commercial integrated navigation product is directly used to achieve a self-positioning accuracy of 20 cm on average. Second, an improved network based on BiSeNet is utilized for real-time semantic segmentation. It achieves the result of 83.9% IOU (Intersection over Union) on Nvidia Pegasus at 31 FPS. Third, a visual Simultaneous Localization and Mapping (SLAM) associated with pixel type information is performed to obtain the semantic point cloud data of features such as lane dividers, road markings, and other static objects. Finally, the semantic point cloud data is vectorized after denoising and clustering, and the results are matched with a pre-constructed HD map to confirm map elements that have not changed and generate new elements when appearing. The experiment conducted in Beijing shows that the method proposed is effective for crowdsourcing update of HD maps