arXiv subjects

Hang Yuan

Publications and source records attributed to Hang Yuan.

51 records · Page 3Linked to original sources

arXiv2024

Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data

Advances in deep learning for human activity recognition have been relatively limited due to the lack of large labelled datasets. In this study, we leverage self-supervised learning techniques on the UK-Biobank activity tracker dataset--the largest of its kind to date--containing more than 700,000 person-days of unlabelled wearable sensor data. Our resulting activity recognition model consistently outperformed strong baselines across seven benchmark datasets, with an F1 relative improvement of 2.5%-100% (median 18.4%), the largest improvements occurring in the smaller datasets. In contrast to previous studies, our results generalise across external datasets, devices, and environments. Our open-source model will help researchers and developers to build customisable and generalisable activity classifiers with high performance.

eess.SP↗

arXiv2024

The high dimensional psychological profile and cultural bias of ChatGPT

Given the rapid advancement of large-scale language models, artificial intelligence (AI) models, like ChatGPT, are playing an increasingly prominent role in human society. However, to ensure that artificial intelligence models benefit human society, we must first fully understand the similarities and differences between the human-like characteristics exhibited by artificial intelligence models and real humans, as well as the cultural stereotypes and biases that artificial intelligence models may exhibit in the process of interacting with humans. This study first measured ChatGPT in 84 dimensions of psychological characteristics, revealing differences between ChatGPT and human norms in most dimensions as well as in high-dimensional psychological representations. Additionally, through the measurement of ChatGPT in 13 dimensions of cultural values, it was revealed that ChatGPT's cultural value patterns are dissimilar to those of various countries/regions worldwide. Finally, an analysis of ChatGPT's performance in eight decision-making tasks involving interactions with humans from different countries/regions revealed that ChatGPT exhibits clear cultural stereotypes in most decision-making tasks and shows significant cultural bias in third-party punishment and ultimatum games. The findings indicate that, compared to humans, ChatGPT exhibits a distinct psychological profile and cultural value orientation, and it also shows cultural biases and stereotypes in interpersonal decision-making. Future research endeavors should emphasize enhanced technical oversight and augmented transparency in the database and algorithmic training procedures to foster more efficient cross-cultural communication and mitigate social disparities.

cs.CL↗

arXiv2024

CAPTURE-24: A large dataset of wrist-worn activity tracker data collected in the wild for human activity recognition

Existing activity tracker datasets for human activity recognition are typically obtained by having participants perform predefined activities in an enclosed environment under supervision. This results in small datasets with a limited number of activities and heterogeneity, lacking the mixed and nuanced movements normally found in free-living scenarios. As such, models trained on laboratory-style datasets may not generalise out of sample. To address this problem, we introduce a new dataset involving wrist-worn accelerometers, wearable cameras, and sleep diaries, enabling data collection for over 24 hours in a free-living setting. The result is CAPTURE-24, a large activity tracker dataset collected in the wild from 151 participants, amounting to 3883 hours of accelerometer data, of which 2562 hours are annotated. CAPTURE-24 is two to three orders of magnitude larger than existing publicly available datasets, which is critical to developing accurate human activity recognition models.

cs.HC↗

arXiv2024

Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment

Recently, we introduced a new paradigm for alpha mining in the realm of quantitative investment, developing a new interactive alpha mining system framework, Alpha-GPT. This system is centered on iterative Human-AI interaction based on large language models, introducing a Human-in-the-Loop approach to alpha discovery. In this paper, we present the next-generation Alpha-GPT 2.0 \footnote{Draft. Work in progress}, a quantitative investment framework that further encompasses crucial modeling and analysis phases in quantitative investment. This framework emphasizes the iterative, interactive research between humans and AI, embodying a Human-in-the-Loop strategy throughout the entire quantitative investment pipeline. By assimilating the insights of human researchers into the systematic alpha research process, we effectively leverage the Human-in-the-Loop approach, enhancing the efficiency and precision of quantitative investment research.

q-fin.CP↗

arXiv2024

QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model

Autonomous agents based on Large Language Models (LLMs) that devise plans and tackle real-world challenges have gained prominence.However, tailoring these agents for specialized domains like quantitative investment remains a formidable task. The core challenge involves efficiently building and integrating a domain-specific knowledge base for the agent's learning process. This paper introduces a principled framework to address this challenge, comprising a two-layer loop.In the inner loop, the agent refines its responses by drawing from its knowledge base, while in the outer loop, these responses are tested in real-world scenarios to automatically enhance the knowledge base with new insights.We demonstrate that our approach enables the agent to progressively approximate optimal behavior with provable efficiency.Furthermore, we instantiate this framework through an autonomous agent for mining trading signals named QuantAgent. Empirical results showcase QuantAgent's capability in uncovering viable financial signals and enhancing the accuracy of financial forecasts.

cs.AI↗

arXiv2024

eSIM Technology in IoT Architecture

eSIM(embedded SIM) is an advanced alternative to traditional physical SIM cards initially developed by the GSM Association(GSMA) in 2013 [1][2]. The eSIM technology has been deployed in many commercial products such as mobile devices. However, the application of the eSIM technology in IoT devices has yet to start being primarily deployed. Understanding the eSIM architecture and the basic ideas of the eSIM provisioning and operations is very important for engineers to promote eSIM technology deployment in more areas, both academics and industries. The report focuses on the eSIM technology in the IoT architecture and two major operations of Remote SIM Provisioning(RSP) procedure: the Common Mutual Authentication procedure, a process used to authenticate eSIM trusted communication parties over the public internet, and the Profile Downloading procedure, the way to download the Profile from the operator SM-DP+ server and eventually remotely provision the end-user devices.

cs.NI↗

arXiv2023

Queer In AI: A Case Study in Community-Led Participatory AI

We present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community's programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization's impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI's work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods.

cs.CY↗

arXiv2023

The Meta Distribution of SINR in UAV-Assisted Cellular Networks

Mounting compact and lightweight base stations on unmanned aerial vehicles (UAVs) is a cost-effective and flexible solution to provide seamless coverage on the existing terrestrial networks. While the coverage probability in UAV-assisted cellular networks has been widely investigated, it provides only the first-order statistic of signal-to-interference-plus-noise ratio (SINR). In this paper, to analyze high-order statistics of SINR and characterize the disparity among individual links, we provide a meta distribution (MD)-based analytical framework for UAV-assisted cellular networks, in which the probabilistic line-of-sight channel and realistic antenna pattern are taken into account for air-to-ground transmissions. To accurately characterize the interference from UAVs, we relax the widely applied uniform off-boresight angle (OBA) assumption and derive the exact distribution of OBA. Using stochastic geometry, for both steerable and vertical antenna scenarios, we obtain mathematical expressions for the moments of condition success probability, the SINR MD, and the mean local delay. Moreover, we study the asymptotic behavior of the moments as network density approaches infinity. Numerical results validate the tightness of the theoretical results and show that the uniform OBA assumption underestimates the network performance, especially in the regime of moderate altitude of UAV. We also show that when UAVs are equipped with steerable antennas, the network coverage and user fairness can be optimized simultaneously by carefully adjusting the UAV parameters.

cs.IT↗

arXiv2022

Stokesian Dynamics with odd viscosity

Stokesian Dynamics is a well-established computational method for simulating dynamics of many particles suspended in a conventional passive fluid medium. Active fluids composed of self-propelling particles with broken time reversal symmetry permit the emergence of a so-called odd viscosity. In this work, we extended the conventional Stokesian Dynamics formalism to incorporate the additional hydrodynamic effects due to odd viscosity, which enables simulating collective behaviors of many particles suspended in an active fluid medium with both even viscosity and odd viscosity.

physics.flu-dyn↗

arXiv2022

Disk counting and wall-crossing phenomenon via family Floer theory

We use the wall-crossing formula in the non-archimedean SYZ mirror construction (arXiv: 2003.06106) to compute the Landau-Ginzburg superpotential and the one-pointed open Gromov-Witten invariants for a Chekanov-type Lagrangian torus in any smooth toric Fano compactification of C^n. It agrees with the works of Auroux, Chekanov-Schlenk, and Pascaleff-Tonkonog.

math.SG↗

arXiv2021

Polar state memory in active fluids

Spontaneous emergence of correlated states such as flocks and vortices are prime examples of remarkable collective dynamics and self-organization observed in active matter. The formation of globally correlated polar states in geometrically confined systems proceeds through the emergence of a macroscopic steadily rotating vortex that spontaneously selects a clockwise or counterclockwise global chiral state. Here, we reveal that a global vortex formed by colloidal rollers exhibits state memory. The information remains stored even when the energy injection is ceased and the activity is terminated. We show that a subsequent formation of the collective states upon re-energizing the system is not random. We combine experiments and simulations to elucidate how a combination of hydrodynamic and electrostatic interactions leads to hidden asymmetries in the local particle positional order encoding the chiral state of the system. The stored information can be accessed and exploited to systematically command subsequent polar states of active liquid through temporal control of the activity. With the chirality of the emergent collective states controlled on-demand, active liquids offer new possibilities for flow manipulation, transport, and mixing at the microscale.

cond-mat.soft↗

arXiv2021

Quincke oscillations of colloids at planar electrodes

Dielectric particles in weakly conducting fluids rotate spontaneously when subject to strong electric fields. Such Quincke rotation near a plane electrode leads to particle translation that enables physical models of active matter. Here, we show that Quincke rollers can also exhibit oscillatory dynamics, whereby particles move back and forth about a fixed location. We explain how oscillations arise for micron-scale particles commensurate with the thickness of a field-induced boundary layer in the nonpolar electrolyte. This work enables the design of colloidal oscillators.

cond-mat.soft↗

arXiv2020

Training Ethically Responsible AI Researchers: a Case Study

Ethical oversight of AI research is beset by a number of problems. There are numerous ways to tackle these problems, however, they leave full responsibility for ethical reflection in the hands of review boards and committees. In this paper, we propose an alternative solution: the training of ethically responsible AI researchers. We showcase this solution through a case study of a centre for doctoral training and outline how ethics training is structured in the program. We go on to present two second-year students' reflections on their training which demonstrates some of their newly found capabilities as ethically responsible researchers.

cs.CY↗

arXiv2020

Hybrid Beamforming for Terahertz Multi-Carrier Systems over Frequency Selective Fading

We propose novel hybrid beamforming schemes for the terahertz (THz) wireless system where a multi-antenna base station (BS) communicates with a multi-antenna user over frequency selective fading. Here, we assume that the BS employs sub-connected hybrid beamforming and multi-carrier modulation to deliver ultra high data rate. We consider a three-dimensional wideband THz channel by incorporating the joint effect of molecular absorption, high sparsity, and multi-path fading, and consider the carrier frequency offset in multi-carrier systems. With this model, we first propose a two-stage wideband hybrid beamforming scheme which includes a beamsteering codebook searching algorithm for analog beamforming and a regularized channel inversion method for digital beamforming. We then propose a novel wideband hybrid beamforming scheme with two digital beamformers. In this scheme, an additional digital beamformer is developed to compensate for the performance loss caused by the constant-amplitude hardware constraints and the difference of channel matrices among subcarriers. Furthermore, we consider imperfect channel state information (CSI) and propose a probabilistic robust hybrid beamforming scheme to combat channel estimation errors. Numerical results demonstrate the benefits of our proposed schemes for the sake of practical implementation, especially considering its high spectral efficiency, low complexity, and robustness against imperfect CSI.

eess.SP↗

arXiv2019

Crystalline membrane morphology beyond polyhedra

Elastic crystalline membranes exhibit a buckling transition from sphere to polyhedron. However, their morphologies are restricted to convex polyhedra and are difficult to externally control. Here, we study morphological changes of closed crystalline membrane of super-paramagnetic particles. The competition of magnetic dipole-dipole interactions with the elasticity of this magnetoelastic membrane leads to concave morphologies. Interestingly, as the magnetic field strength increases, the symmetry of the buckled membrane decreases from 5-fold to 3-fold, to 2-fold and, finally, to 1-fold rotational symmetry. This gives the ability to switch the membrane morphology between convex and concave shapes with specific symmetry and provides promising applications for membrane shape control in the design of actuatable micro-containers for targeted delivery systems.

cond-mat.soft↗