arXiv subjects

Jiawei Gao

Publications and source records attributed to Jiawei Gao.

25 records · Page 2Linked to original sources

arXiv2024

A microwave photonic prototype for concurrent radar detection and spectrum sensing over an 8 to 40 GHz bandwidth

In this work, a microwave photonic prototype for concurrent radar detection and spectrum sensing is proposed, designed, built, and investigated. A direct digital synthesizer and an analog electronic circuit are integrated to generate an intermediate frequency (IF) linearly frequency-modulated (LFM) signal with a tunable center frequency from 2.5 to 9.5 GHz and an instantaneous bandwidth of 1 GHz. The IF LFM signal is converted to the optical domain via an intensity modulator and then filtered by a fiber Bragg grating (FBG) to generate only two 2nd-order optical LFM sidebands. In radar detection, the two optical LFM sidebands beat with each other to generate a frequency-and-bandwidth-quadrupled LFM signal, which is used for ranging, radial velocity measurement, and imaging. By changing the center frequency of the IF LFM signal, the radar function can be operated within 8 to 40 GHz. In spectrum sensing, one 2nd-order optical LFM sideband is selected by another FBG, which then works in conjunction with the stimulated Brillouin scattering gain spectrum to map the frequency of the signal under test to time with an instantaneous measurement bandwidth of 2 GHz. By using a frequency shift module to adjust the pump frequency, the frequency measurement range can be adjusted from 0 to 40 GHz. The prototype is comprehensively studied and tested, which is capable of achieving a range resolution of 3.75 cm, a range error of less than $\pm$ 2 cm, a radial velocity error within $\pm$ 1 cm/s, delivering clear imaging of multiple small targets, and maintaining a frequency measurement error of less than $\pm$ 7 MHz and a frequency resolution of better than 20 MHz.

physics.optics↗

arXiv2024

Seamless Integration and Implementation of Distributed Contact and Contactless Vital Sign Monitoring

Real-time vital sign monitoring is gaining immense significance not only in the medical field but also in personal health management. Facing the needs of different application scenarios of the smart and healthy city in the future, the low-cost, large-scale, scalable, and distributed vital sign monitoring system is of great significance. In this work, a seamlessly integrated contact and contactless vital sign monitoring system, which can simultaneously implement respiration and heartbeat monitoring, is proposed. In contact vital sign monitoring, the chest wall movement due to respiration and heartbeat is translated into changes in the optical output intensity of a fiber Bragg grating (FBG). The FBG is also an important part of radar signal generation for contactless vital sign monitoring, in which the chest wall movement is translated into phase changes of the radar de-chirped signal. By analyzing the intensity of the FBG output and phase of the radar de-chirped signal, real-time respiration and heartbeat monitoring are realized. In addition, due to the distributed structure of the system and its good integration with the wavelength-division multiplexing optical network, it can be massively scaled by employing more wavelengths. A proof-of-concept experiment is carried out. Contact and contactless respiration and heartbeat monitoring of three people are simultaneously realized. During a monitoring time of 60 s, the maximum absolute measurement errors of respiration and heartbeat rates are 1.6 respirations per minute and 2.3 beats per minute, respectively. The measurement error does not have an obvious change even when the monitoring time is decreased to 5 s.

eess.SY↗

arXiv2024

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response

Robust locomotion control depends on accurate state estimations. However, the sensors of most legged robots can only provide partial and noisy observations, making the estimation particularly challenging, especially for external states like terrain frictions and elevation maps. Inspired by the classical Internal Model Control principle, we consider these external states as disturbances and introduce Hybrid Internal Model (HIM) to estimate them according to the response of the robot. The response, which we refer to as the hybrid internal embedding, contains the robot's explicit velocity and implicit stability representation, corresponding to two primary goals for locomotion tasks: explicitly tracking velocity and implicitly maintaining stability. We use contrastive learning to optimize the embedding to be close to the robot's successor state, in which the response is naturally embedded. HIM has several appealing benefits: It only needs the robot's proprioceptions, i.e., those from joint encoders and IMU as observations. It innovatively maintains consistent observations between simulation reference and reality that avoids information loss in mimicking learning. It exploits batch-level information that is more robust to noises and keeps better sample efficiency. It only requires 1 hour of training on an RTX 4090 to enable a quadruped robot to traverse any terrain under any disturbances. A wealth of real-world experiments demonstrates its agility, even in high-difficulty tasks and cases never occurred during the training process, revealing remarkable open-world generalizability.

cs.RO↗

arXiv2023

Detection of magnetospheric ion drift patterns at Mars

Mars lacks a global magnetic field, and instead possesses small-scale crustal magnetic fields, making its magnetic environment fundamentally different from intrinsic magnetospheres like those of Earth or Saturn. Here we report the discovery of magnetospheric ion drift patterns, typical of intrinsic magnetospheres, at Mars usingmeasurements fromMarsAtmosphere and Volatile EvolutioNmission. Specifically, we observewedge-like dispersion structures of hydrogen ions exhibiting butterfly-shaped distributions within the Martian crustal fields, a feature previously observed only in planetary-scale intrinsic magnetospheres. These dispersed structures are the results of driftmotions that fundamentally resemble those observed in intrinsic magnetospheres. Our findings indicate that the Martian magnetosphere embodies an intermediate case where both the unmagnetized and magnetized ion behaviors could be observed because of the wide range of strengths and spatial scales of the crustal magnetic fields around Mars.

astro-ph.EP↗

arXiv2023

Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning

Offline-to-online reinforcement learning (RL) is a training paradigm that combines pre-training on a pre-collected dataset with fine-tuning in an online environment. However, the incorporation of online fine-tuning can intensify the well-known distributional shift problem. Existing solutions tackle this problem by imposing a policy constraint on the policy improvement objective in both offline and online learning. They typically advocate a single balance between policy improvement and constraints across diverse data collections. This one-size-fits-all manner may not optimally leverage each collected sample due to the significant variation in data quality across different states. To this end, we introduce Family Offline-to-Online RL (FamO2O), a simple yet effective framework that empowers existing algorithms to determine state-adaptive improvement-constraint balances. FamO2O utilizes a universal model to train a family of policies with different improvement/constraint intensities, and a balance model to select a suitable policy for each state. Theoretically, we prove that state-adaptive balances are necessary for achieving a higher policy performance upper bound. Empirically, extensive experiments show that FamO2O offers a statistically significant improvement over various existing methods, achieving state-of-the-art performance on the D4RL benchmark. Codes are available at https://github.com/LeapLabTHU/FamO2O.

cs.LG↗

arXiv2021

A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data

DNA methylation is a well-studied genetic modification that regulates gene transcription of Eukaryotes. Its alternations have been recognized as a significant component of cancer development. In this study, we use the DNA methylation 450k data from The Cancer Genome Atlas to evaluate the efficacy of DNA methylation data on cancer classification for 30 cancer types. We propose a new method for gene selection in high dimensional data(over 450 thousand). Variance filtering is first introduced for dimension reduction and Recursive feature elimination (RFE) is then used for feature selection. We address the problem of selecting a small subsets of genes from large number of methylated sites, and our parsimonious model is demonstrated to be efficient, achieving an accuracy over 91%, outperforming other studies which use DNA micro-arrays and RNA-seq Data . The performance of 20 models, which are based on 4 estimators (Random Forest, Decision Tree, Extra Tree and Support Vector Machine) and 5 classifiers (k-Nearest Neighbours, Support Vector Machine, XGboost, Light GBM and Multi-Layer Perceptron), is compared and robustness of the RFE algorithm is examined. Results suggest that the combined model of extra tree plus catboost classifier offers the best performance in cancer identification, with an overall validation accuracy of 91% , 92.3%, 93.3% and 93.5% for 20, 30, 40 and 50 features respectively. The biological functions in cancer development of 50 selected genes is also explored through enrichment analysis and the results show that 12 out of 16 of our top features have already been identified to be specific with cancer and we also propose some more genes to be tested for future studies. Therefore, our method may be utilzed as an auxiliary diagnostic method to determine the actual clinicopathological status of a specific cancer.

q-bio.TO↗

arXiv2019

The Computational Complexity of Fire Emblem Series and similar Tactical Role-Playing Games

Fire Emblem (FE) is a popular turn-based tactical role-playing game (TRPG) series on the Nintendo gaming consoles. This paper studies the computational complexity of a simplified version of FE (only floor tiles and wall tiles, the HP and other attributes of characters are constants at most 8, the movement distance per character each turn is fixed to 6 tiles), and proves that: 1. Simplified FE is PSPACE-complete (Thus actual FE is at least as hard). 2. Poly-round FE is NP-complete, even when the map is cycle-free, without healing units, and the weapon durability is a small constant. Poly-round FE is to decide whether the player can win the game in a certain number of rounds that is polynomial to the map size. A map is called cycle-free if its corresponding planar graph is cycle-free. These hardness results also hold for other similar TRPG series, such as Final Fantasy Tactics, Tactics Ogre and Disgaea.

cs.CC↗