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278 results on '"Mao, Kai"'

1. Automating psychological hypothesis generation with AI: when large language models meet causal graph

Author

Tong, Song, Mao, Kai, Huang, Zhen, Zhao, Yukun, and Peng, Kaiping

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract

Leveraging the synergy between causal knowledge graphs and a large language model (LLM), our study introduces a groundbreaking approach for computational hypothesis generation in psychology. We analyzed 43,312 psychology articles using a LLM to extract causal relation pairs. This analysis produced a specialized causal graph for psychology. Applying link prediction algorithms, we generated 130 potential psychological hypotheses focusing on `well-being', then compared them against research ideas conceived by doctoral scholars and those produced solely by the LLM. Interestingly, our combined approach of a LLM and causal graphs mirrored the expert-level insights in terms of novelty, clearly surpassing the LLM-only hypotheses (t(59) = 3.34, p=0.007 and t(59) = 4.32, p<0.001, respectively). This alignment was further corroborated using deep semantic analysis. Our results show that combining LLM with machine learning techniques such as causal knowledge graphs can revolutionize automated discovery in psychology, extracting novel insights from the extensive literature. This work stands at the crossroads of psychology and artificial intelligence, championing a new enriched paradigm for data-driven hypothesis generation in psychological research.

Published
2024
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3. Core Collapse Supernova Explosions in Active Galactic Nucleus Accretion Disks

Author

Li, Fu-Lin, Liu, Yu, Fan, Xiao, Hu, Mao-Kai, Yang, Xuan, Geng, Jin-Jun, and Wu, Xue-Feng

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

Astrophysical events that occur in active galactic nucleus (AGN) disks are believed to differ significantly from the ordinary in the interstellar medium. We show that stars located in the outer region of the AGN disk would explode near the original migration starting points instead of being accreted by the central supermassive black hole due to the effect of viscosity. AGN disks provide a dense environment for supernova (SN) explosions, which inevitably involve ejecta-disk interactions. In this paper, we investigate the light curves (LCs) of core-collapse SN exploded in AGN disks. In addition to the fundamental energy source of $^{56} \mathrm{Ni}$--$^{56} \mathrm{Co}$--$^{56} \mathrm{Fe}$ decay reaction powering the SN LCs, the forward-reverse shock produced during interactions may contribute significantly to the observed flux. If the stellar winds manage to create a cavity surrounded by a shell near the star before the SN explosion, the ejecta-winds-disk configurations are expected. We present various SN LCs from different types of progenitors and find that the SN LCs are dominated by the radiation of ejecta-disk interaction-induced shocks. The resulting SNe in the AGN disk is a promising transient source for UV and optical band detection by the Neil Gehrels Swift Observatory (Swift), the Ultraviolet Explorer (UVEX) and wide field survey telescopes such as Ultraviolet Transient Astronomy Satellite (ULTRASAT), Wide Field Survey Telescope (WFST) and Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory. These detections could aid in the investigation of AGN discs and the associated high-energy transient occurrences., Comment: 16 pages, 6 figures, 2 tables, matches the published version in ApJ

Published
2023
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4. Enhancing Vital Sign Estimation Performance of FMCW MIMO Radar by Prior Human Shape Recognition

Author

Alidoustaghdam, Hadi, Chen, Min, Willetts, Ben, Mao, Kai, Kokkeler, André, and Miao, Yang

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Radio technology enabled contact-free human posture and vital sign estimation is promising for health monitoring. Radio systems at millimeter-wave (mmWave) frequencies advantageously bring large bandwidth, multi-antenna array and beam steering capability. \textit{However}, the human point cloud obtained by mmWave radar and utilized for posture estimation is likely to be sparse and incomplete. Additionally, human's random body movements deteriorate the estimation of breathing and heart rates, therefore the information of the chest location and a narrow radar beam toward the chest are demanded for more accurate vital sign estimation. In this paper, we propose a pipeline aiming to enhance the vital sign estimation performance of mmWave FMCW MIMO radar. The first step is to recognize human body part and posture, where we exploit a trained Convolutional Neural Networks (CNN) to efficiently process the imperfect human form point cloud. The CNN framework outputs the key point of different body parts, and was trained by using RGB image reference and Augmentative Ellipse Fitting Algorithm (AEFA). The next step is to utilize the chest information of the prior estimated human posture for vital sign estimation. While CNN is initially trained based on the frame-by-frame point clouds of human for posture estimation, the vital signs are extracted through beamforming toward the human chest. The numerical results show that this spatial filtering improves the estimation of the vital signs in regard to lowering the level of side harmonics and detecting the harmonics of vital signs efficiently, i.e., peak-to-average power ratio in the harmonics of vital signal is improved up to 0.02 and 0.07dB for the studied cases., Comment: Accepted for presentation at the IEEE ICC 2023 conference

Published
2023

5. Channel Knowledge Extraction and Completion Methods for 3D CKM Construction

Author

Qiu, Yanheng, Chen, Xiaomin, Mao, Kai, Ye, Xuchao, Zhao, Yi, Ge, Yurao, Zhong, Weizhi, Zhu, Qiuming, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2024
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6. Channel Modeling for UAV-to-Ground Communications with Posture Variation and Fuselage Scattering Effect

Author

Hua, Boyu, Ni, Haoran, Zhu, Qiuming, Wang, Cheng-Xiang, Zhou, Tongtong, Mao, Kai, Bao, Junwei, and Zhang, Xiaofei

Subjects
Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role for reliable communications between UAV and ground terminal. This paper proposes a three-dimensional (3D) non-stationary hybrid model including both large-scale and small-scale fading for U2G multiple-input-multiple-output (MIMO) channels. Distinctive channel characteristics under U2G scenarios, i.e., 3D trajectory and posture of UAV, fuselage scattering effect (FSE), and posture variation fading (PVF), are incorporated into the proposed model. The channel parameters, i.e., path loss (PL), shadow fading (SF), path delay, and path angle, are generated incorporating machine learning (ML) and ray tracing (RT) techniques to capture the structure-related characteristics. In order to guarantee the physical continuity of channel parameters such as Doppler phase and path power, the time evolution methods of inter- and intra- stationary intervals are proposed. Key statistical properties , i.e., temporal autocorrection function (ACF), power delay profile (PDP), level crossing rate (LCR), average fading duration (AFD), and stationary interval (SI) are given, and the impact of the change of fuselage and posture variation is analyzed. It is demonstrated that both posture variation and fuselage scattering have crucial effects on channel characteristics. The validity and practicability of the proposed model are verified by comparing the simulation results with the measured ones.

Published
2022

7. A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture

Author

Hua, Boyu, Zhou, Tongtong, Zhu, Qiuming, Mao, Kai, Bao, Junwei, Zhong, Weizhi, and Ahmed, Naeem

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Considering the unmanned aerial vehicle (UAV) three-dimensional (3D) posture, a novel 3D non-stationary geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) UAV-to-vehicle (U2V) channels. It consists of a line-of-sight (LoS) and non-line-of-sight (NLoS) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e. the temporal autocorrelation function (ACF) and spatial cross correlation function (CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture., Comment: 12 pages, 8 figures, CNCOM

Published
2022

8. Gravitationally Lensed Orphan Afterglows of Gamma-Ray Bursts

Author

Gao, Hao-Xuan, Geng, Jin-Jun, Hu, Lei, Hu, Mao-Kai, Lan, Guang-Xuan, Chang, Chen-Ming, Zhang, Song-Bo, Zhang, Xiao-Li, Huang, Yong-Feng, and Wu, Xue-Feng

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The cosmological nature of gamma-ray bursts (GRBs) implies that a small portion of them could be gravitationally lensed by foreground objects during their propagation. The gravitational lensing effect on the GRB prompt emission and on-axis afterglows has been discussed, and some candidates have been found in the literature. In this work, considering the high detection rate of GRB orphan afterglows in future wide-field survey era, we investigate the gravitationally lensed orphan afterglows in view of three lens models, i.e., the point-mass model, the singular isothermal sphere model, and the Chang-Refsdal model. The structure of the GRB jet itself is also incorporated in calculating the lensed afterglow light curves. It is found that lensed optical/X-ray orphan afterglows in principle could be diagnosed through their temporal characteristics, and the optical band is the best band to observe the galaxy-lensed orphan afterglows. Moreover, the event rate for galaxy-lensed orphan afterglows is estimated to be $\lesssim$ 1.8 $\text{yr}^{-1}$ for the whole sky. If most orphan afterglows could be identified (from other transients in the survey data), the optimistic detection rates of the 2.5m Wide Field Survey Telescope of China and 8.4m Vera Rubin Observatory Legacy Survey of Space and Time for galaxy-lensed orphan afterglows in the optical band are $\lesssim$ 0.01$\sim$0.02 $\text{yr}^{-1}$ and $\lesssim$ 0.04$\sim$0.08 $\text{yr}^{-1}$, respectively., Comment: 13 pages, 10 figures, Accepted for publication in MNRAS

Published
2022
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10. Research on Dynamic Emulation of Non-Stationary Channel of Unmanned Aerial Vehicles Based on FPGA

Author

Fang Sheng, Mao Kai, Wang Manxi, Hua Boyu, Song Maozhong, Zhu Qiuming

Subjects
uavs, non-stationary channel, channel emulation, field-programmable gate array, path loss, dynamic scene, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Abstract

Considering the rapid time-varying channel conditions and large Doppler frequency fluctuations caused by high-speed movement of unmanned aerial vehicles, this paper proposes a non-stationary channel emulation scheme for Unmanned Aerial Vehicles(UAVs) using a field-programmable gate array platform. The proposed scheme adopts the sum of frequency modulation method to generate non-stationary channel fading and proposes a real-time algorithm for generating channel parameters to improve the real-time performance of channel emulation and ensure the real-time updating of channel status. In addition, to address the issue of power random fluctuation caused by large Doppler frequency fluctuations, this paper designs an adaptive power equalization module that ensures the stability of fading power by limiting the maximum fluctuation to only 1.13%. Finally, the results of hardware resource consumption analysis demonstrate that the proposed approach in this study significantly reduces the utilization of storage resources compared to replay-based and pre-stored solutions, with reductions of 52.44% and 9.31%, respectively. This makes the proposed approach well-suited for simulating long-duration non-stationary channel fading in UAV scenarios. Additionally, the measured analysis results demon-strate that the channel characteristics output by the proposed hardware emulation scheme, such as path loss and Doppler power spectrum density,closely align with theoretical results when compared to the emulation scheme without the equalizer. This research can be applied to the design and optimization of UAVs communication systems.

Published
2024
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13. Measurements and Analysis for the Second-Order Statistical Properties of Time-Variant A2G Channels

Author

Mao, Kai, Lei, Taiya, Qiu, Yanheng, Zhu, Qiuming, Song, Maozhong, Miao, Yang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2023
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14. Design and Optimization of Sounding Sequence for Multi-antenna Air-to-ground Channel Measurements

Author

Duan, Fuqiao, Mao, Kai, Zhu, Qiuming, Qiu, Yanheng, Chen, Xiaomin, Lin, Zhipeng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2023
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15. Fast Multi-target Sensing and Tracking for Directional Array-Deployed UAV Systems

Author

Lin, Zhipeng, Zhu, Qiuming, Lv, Tiejun, Zhong, Weizhi, Wang, Jie, Mao, Kai, Liu, Kun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2023
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24. List of contributors

Author

Chen, Jinyu, primary, Guo, Zhiling, additional, Huang, Dou, additional, Jiang, Renhe, additional, Jiang, Wenxiao, additional, Kobayashi, Hill Hiroki, additional, Li, Peiran, additional, Li, Wenjing, additional, Lin, Lifeng, additional, Mao, Kai, additional, Shao, Xiaowei, additional, Shi, Xiaodan, additional, Shibasaki, Ryosuke, additional, Song, Xuan, additional, Wu, Guangming, additional, Zhang, Haoran, additional, and Zhang, Junxiang, additional

Published
2023
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25. Infrared and Near-Infrared Image Generation via Content Consistency and Style Adversarial Learning

Author

Mao, Kai, Yang, Meng, Wang, Haijian, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yu, Shiqi, editor, Zhang, Zhaoxiang, editor, Yuen, Pong C., editor, Han, Junwei, editor, Tan, Tieniu, editor, Guo, Yike, editor, Lai, Jianhuang, editor, and Zhang, Jianguo, editor

Published
2022
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26. Effects of Fuselage Scattering and Posture on UAV Channel

Author

Hua, Boyu, Zhu, Qiuming, Wang, Cheng-Xiang, Ni, Haoran, Mao, Kai, Zhou, Tongtong, Zhong, Weizhi, Chang, Hengtai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2022
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27. Height-Dependent LoS Probability Model for A2G MmWave Communications Under Built-Up Scenarios

Author

Pang, Minghui, Zhu, Qiuming, Bai, Fei, Li, Zhuo, Li, Hanpeng, Mao, Kai, Tian, Yue, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Wang, Wei, editor, Liu, Xin, editor, Na, Zhenyu, editor, and Zhang, Baoju, editor

Published
2022
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30. Numerical Simulation of Hypersonic Aerodynamic Heat Based on High Resolution Scheme

Author

Sun Zhensheng, Wang Jiangbin, Hu Yu, Mao Kai

Subjects
hypersonic, aerodynamic heat, grid scale, scheme accuracy, scheme dissipation, vehicle, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Abstract

Hypersonic aerodynamic heat has always been the key in the design of hypersonic vehicles, and it is also an important basis for aerodynamic layout design, structural design and material selection for thermal protection. However, the numerical simulation of aerodynamic heating is influenced by many factors, such as grid scale and numerical scheme, which is one of the difficulties in computational fluid dynamics. In this paper, a typical three-dimensional blunt cone model is selected, and the related research on hypersonic aerothermal problems is mainly focused on the grid scale, numerical scheme accuracy and dissipation. The results show that with the increasing of grid Reynolds number, the calculated value of heat flux shows a decreasing trend, and the calculated value of heat flux is more sensitive to the grid scale in the parts where aerodynamic heating is severe. When the grid scale is small, the higher the accuracy, the more accurate the heat flow calculation is. When the grid scale is large, the MDADF-HY scheme with high resolution is more dominant. At the same time, proper dissipation is also the premise that the numerical scheme can accurately calculate the heat flux.

Published
2022
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34. Height‐dependent LoS probability model for A2G channels incorporating airframe shadowing under built‐up scenario.

Author

Ali, Farman, Pan, Yinglan, Zhu, Qiuming, Ahmad, Naeem, Mao, Kai, and Ullah, Habib

Subjects
GRAPH neural networks, ADAPTIVE signal processing, DRONE aircraft, RAY tracing, MACHINE learning
Abstract

The line of sight (LoS) probability is a key factor for the channel modeling of air‐to‐ground (A2G) communication. However, the existing LoS probability models do not account for the effects of airframe shadowing (AS) and building density, which can cause serious link obstruction and performance loss due to the six‐dimensional (6D) mobility and self‐body of unmanned aerial vehicle (UAV). In this article, a new LoS probability model is proposed that considers the AS and building density for different UAV heights. Adding to this, the AS is derived in terms of UAV framework and 6D mobility. Next, the machine learning (ML) based graph neural network (GNN) method is developed to learn the features and structure of the urban environment and predict the LoS probability. Then, the GNN model is trained and evaluated based on the ray tracing (RT) data to establish the relationship between model parameters and UAV heights under the building density and AS factors. The interpretation and explanation of the proposed GNN model and prediction are also discussed in this article. It is shown from the simulation analysis that the GNN model accurately captures the effects of AS, building height distributions, and UAV heights, with high accuracy compared to the baseline 3GPP, GCM and NYU models. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Path Loss and Shadowing for UAV-to-Ground UWB Channels Incorporating the Effects of Built-Up Areas and Airframe

Author

Ni, Haoran, Zhu, Qiuming, Hua, Boyu, Mao, Kai, Pan, Yinglan, Ali, Farman, Zhong, Weizhi, and Chen, Xiaomin

Abstract

A realistic channel model is vital for designing, optimizing, and evaluating unmanned aerial vehicle (UAV)-to-ground (U2G) communication systems. This paper presents a comprehensive U2G ultra-wideband (UWB) channel model by considering the large-scale fading (LSF), including path loss (PL), shadow fading (SF), and airframe shadowing (AS). The effects of carrier frequency, bandwidth, building distribution, and UAV airframe structure on the LSF are fully studied. Different from the traditional bandwidth-independent PL calculation method, an extended closed-form expression for calculating PL is proposed to capture the new characteristics of ultra-wide bandwidth. The SF part is statistically described by a parametric lognormal model, and the built-up scenario-dependent parameters are predicted by a hybrid method with the ray-tracing and virtual scenario technologies. In addition, the AS part with respect to the airframe structure and posture variation is derived. It consists of the direct and reflected path components which are obtained by the deterministic and statistical approaches, respectively. The numerical simulations show that bandwidth, building distribution, and airframe structure have great influence on the LSF characteristics. For example, the fluctuation of received power can reach 30 dB due to the AS. The proposed model also shows its effectiveness and reliability by comparing with the RT and measured data, as well as the good compatibility with standardized models for some typical scenarios.

Published
2024
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47. Image-Based Beam Tracking With Deep Learning for mmWave V2I Communication Systems

Author

Zhong, Weizhi, Zhang, Lulu, Jin, Haowen, Liu, Xin, Zhu, Qiuming, He, Yi, Ali, Farman, Lin, Zhipeng, Mao, Kai, and Durrani, Tariq S.

Abstract

Effective beam alignment is essential for vehicle-to-infrastructure (V2I) millimeter wave (mmWave) communication systems, particularly in high-mobility vehicle scenarios. This paper explores a three-dimensional (3D) vehicle environment and introduces a novel deep learning (DL)-based beam search method that incorporates an image-based coding (IBC) technique. The mmWave beam search is approached as an image processing problem based on situational awareness. We propose IBC to leverage the locations, sizes, and information of vehicles, and utilize convolutional neural network (CNN) to train the image dataset. Consequently, the optimal beam pair index(BPI)can be determined. Simulation results demonstrate that the proposed beam search method achieves satisfactory performance in terms of accuracy and robustness compared to conventional methods.

Published
2024
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48. Automating Psychological Hypothesis Generation with AI: Large Language Models Meet Causal Graph

Author

Tong, Song, Mao, Kai, Huang, Zhen, Zhao, Yukun, Peng, Kaiping, Tong, Song, Mao, Kai, Huang, Zhen, Zhao, Yukun, and Peng, Kaiping

Abstract

Leveraging the synergy between causal knowledge graphs and a large language model (LLM), our study introduces a groundbreaking approach for computational hypothesis generation in psychology. We analyzed 43,312 psychology articles using a LLM to extract causal relation pairs. This analysis produced a specialized causal graph for psychology. Applying link prediction algorithms, we generated 130 potential psychological hypotheses focusing on `well-being', then compared them against research ideas conceived by doctoral scholars and those produced solely by the LLM. Interestingly, our combined approach of a LLM and causal graphs mirrored the expert-level insights in terms of novelty, clearly surpassing the LLM-only hypotheses (t(59) = 3.34, p=0.007 and t(59) = 4.32, p<0.001, respectively). This alignment was further corroborated using deep semantic analysis. Our results show that combining LLM with machine learning techniques such as causal knowledge graphs can revolutionize automated discovery in psychology, extracting novel insights from the extensive literature. This work stands at the crossroads of psychology and artificial intelligence, championing a new enriched paradigm for data-driven hypothesis generation in psychological research.

Published
2024
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49. Fermentation Parameters, Amino Acids Profile, Biogenic Amines Formation, and Bacterial Community of Ensiled Stylo Treated with Formic Acid or Sugar.

Author

Mao, Kai, Franco, Marcia, Xu, Yi, Chai, Huan, Wang, Jian, Huang, Shuai, Wang, Zhiyong, Xun, Wenjuan, Liang, Zuoxiang, Yu, Zhu, and Wang, Musen

Subjects
*SILAGE fermentation, *FORMIC acid, *BIOGENIC amines, *BUTYRIC acid, *BACTERIAL population, *TYRAMINE
Abstract

Simple Summary: Stylo silage is widely used as a protein source for ruminants in tropical and subtropical regions. High levels of biogenic amines in stylo silage are harmful to the health of ruminant animals. The purpose of this work was to evaluate the effect of formic acid and sugar on biogenic amines and amino acids concentrations and bacterial composition and fermentation profile of stylo silage. The results showed that putrescine, cadaverine, and tyramine became predominant in the control silage, and applying formic acid and sugar significantly decreased putrescine, cadaverine, tyramine, and total biogenic amine concentrations. Clostridium pabulibutyricum, Weissella cibaria and W. paramesenteroides were the predominant bacteria in the control silage, and the application of both additives remarkably lowered their relative abundance. Correlation analysis showed that C. pabulibutyricum, W. cibaria and W. paramesenteroides were positively related to putrescine, cadaverine, and tyramine formation. The application of formic acid or sugar significantly reduced the undesirable bacterial population and improved the fermentation and hygienic quality of the stylo silage. Substantial proteolysis occurs and free amino acids can be degraded to biogenic amines by decarboxylation during stylo (Stylosanthes guianensis) ensiling. High biogenic amine concentrations in silage are harmful to the health of ruminant animals. The purposes of this work were to (1) analyze the biogenic amines and amino acids concentrations, bacterial composition, and fermentation profile of spontaneously fermented stylo silage, (2) explore the effect of formic acid or sugar additive on these silage parameters, and (3) further reveal the correlations between silage amines and fermentation parameters, amino acids, and bacteria. Freshly chopped stylo was treated with distilled water (control), formic acid (4 mL/kg), and sugar (20 g/kg) and fermented for 28 days. The results indicated that putrescine (321 mg/kg dry matter), cadaverine (384 mg/kg dry matter), and tyramine (127 mg/kg dry matter) rapidly increased in concentration and become predominant in the control silage after 28 days of fermentation. Applying formic acid and sugar at ensiling, especially the acidifier, significantly decreased putrescine, cadaverine, tyramine, and total biogenic amine concentrations compared with the control treatment (p < 0.0001). Clostridium pabulibutyricum, Weissella cibaria and W. paramesenteroides were the predominant bacteria in the control silage, and the application of both additives remarkably lowered their relative abundance in comparison with the control treatment (p < 0.001). Correlation analysis showed that putrescine, cadaverine, and tyramine were positively related to pH, butyric acid, non-protein nitrogen, and ammonia nitrogen (p < 0.01). These amines also had significant correlations with C. pabulibutyricum, W. cibaria and W. paramesenteroides (p < 0.001). Putrescine, cadaverine, and tyramine were the main biogenic amines and C. pabulibutyricum was the predominant undesirable bacterium in naturally fermented stylo silage. C. pabulibutyricum, W. cibaria and W. paramesenteroides were positively related to putrescine, cadaverine, and tyramine formation. The application of formic acid or sugar significantly reduced the undesirable bacterial population and improved the fermentation and hygienic quality of the stylo silage. These findings lay the foundation for further elucidating the microbial mechanism underlying the main biogenic amine formation during fermentation of stylo silage. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Structural selective regulation of Fe3O4@C composite as adsorbent for removing different organic pollutants.

Author

Chen, Luyao, Ren, Sen, Mao, Kai, Yu, Changyuan, and Liu, Yunfang

Subjects
WASTEWATER treatment, ADSORPTION kinetics, WASTE recycling, ADSORPTION capacity, SURFACE properties
Abstract

Many wastewater treatment methods have been developed because large amounts of organic pollutants (OPs) entered into the water bodies and adsorption is one of the classic and important technologies. Recently, magnetic adsorbents have garnered extensive attention due to the high efficiency and distinctive recyclability. The control of their structures and surface properties is crucial. Here, the magnetite@carbon (Fe3O4@C) composite was prepared by coupling microreactor and pyrolysis reactor. The structures and surface properties of the Fe3O4@C were effectively adjusted by changing the pyrolysis temperature and Na2CO3 concentration. The Fe3O4@C composite prepared at 800°C of pyrolysis temperature with 1 mol·L−1 of Na2CO3 concentration has lipophilicity and the highest adsorption capacity of 92# gasoline among those adsorbents, which is as high as 7.6 g·g−1. The Fe3O4@C synthesized at 500°C with 1 mol·L−1 of Na2CO3 concentration has hydrophilicity and the highest adsorption capacity of Rhodamine B and Methyl Blue. The saturated adsorption capacities are about 166 and 301 mg·g−1, respectively. Fe3O4@C can be easily separated from wastewater and simply regenerated with less capacity loss after five cycles. The results show that the Fe3O4@C prepared by this method could be suitable for the removal of different OPs by adjusting the preparation conditions. Magnetic adsorbents Fe3O4@C were prepared by coupling microreactor and pyrolysis reactor. Structure and property of Fe3O4@C were effectively controlled by adjusting reaction parameters. Fe3O4@C composite exhibits outstanding adsorption performances for different organic pollutants. Fe3O4@C composite shows excellent recyclability and reusability. The adsorption kinetics fitted the pseudo-second-order model. [ABSTRACT FROM AUTHOR]

Published
2024
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