2,712 research outputs found
sj-docx-1-ahd-10.1177_00914150241235088 - Supplemental material for Intergenerational Caregiving Patterns and Cognitive Health among the Sandwich Generation Within Four-Generation Families
No full textSupplemental material, sj-docx-1-ahd-10.1177_00914150241235088 for Intergenerational Caregiving Patterns and Cognitive Health among the Sandwich Generation Within Four-Generation Families by Jiaming Shi, Denghao Zhang and Xiaoting Liu in The International Journal of Aging and Human Development</p
Illi Racecar: A small-scale platform for autonomous driving
Full text linkThis thesis proposes a safety-critical 1/10 scale autonomous driving platform called Illi Racecar. Sensors, including three cameras, A laser scanner, an inertial measurement unit (IMU), two encoders, and an E-stop button, were installed on the platform for environmental perception. Three levels of computer module were equipped for data processing and control. A servo motor and a DC motor with the Ackermann steering chassis were utilized for motion control. A self-designed PCB board was placed on the vehicle supporting the electronic system. The Illi Racecar was built based on a Real-Time Operating System (RTOS) with a high-low level controller framework. The new generation of Robot Operating System, ROS2, was installed on the main computer station with its real-time features to ensure the platform's reliability. A real-time Drive-by-Wire (DBW) control module with an industry-standard Controller Area Network (CAN) bus was implemented to replace the less reliable ROS serial communication interface. Based on the parameter of the Illi Racecar, two geometric path trackers, namely the Pure pursuit controller and the Stanley controller were simulated using Simulink. After the low-level control programming and sensing system calibration of the platform, real car tests were conducted based on the parameters tuned by the simulation. The program for the real car test was also built in Simulink and generated into C for faster development. After comparing the simulation results and the real car evaluation of different controllers, several factors that influenced the results were determined. The Illi Racecar was the first application of ROS2 on a 1/10 scale Ackermann steering platform and in using Simulink modeling for rapid control system prototyping.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01The student, Jiaming Zhang, accepted the attached license on 2021-07-21 at 14:19.The student, Jiaming Zhang, submitted this Thesis for approval on 2021-07-21 at 14:25.This Thesis was approved for publication on 2021-07-22 at 14:45.DSpace SAF Submission Ingestion Package generated from Vireo submission #17038 on 2022-01-12 at 12:55:33Made available in DSpace on 2022-01-12T22:35:20Z (GMT). No. of bitstreams: 2
ZHANG-THESIS-2021.pdf: 2976070 bytes, checksum: 4d826a4a7bbd0b7e13e934d752032a0d (MD5)
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Previous issue date: 2021-07-22Embargo set by: Seth Robbins for item 121147
Lift date: 2024-01-12T22:35:30Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Offroad autonomous vehicle development and model-based adaptive robust control strategy
No full textAutonomous driving has seen increasing applications in off-road environments, driven by advancements in sensing and control technologies. To operate reliably under severe off-road conditions, a robust and adaptable off-road platform is essential. Off-road environments, in particular, present unique challenges, including low traction, uneven terrain, rapidly changing slopes, and high vibration levels. Model-based controllers have the potential to improve control performance in challenging off-road scenarios significantly.
Preliminary work focused on simulator development and control architecture design for an electric vehicle prototype. Motivated by platform limitations and off-road driving requirements, the research was extended to develop an off-road vehicle platform, the R-Gator. A redesigned modular system architecture was implemented on the R-Gator, accompanied by a high-fidelity simulator that enables flexible and safe testing. Building on this upgraded platform, three key research efforts are presented to address the challenges of environmental disturbances in off-road path-tracking control.
First, vehicle dynamics were identified using Dynamic Mode Decomposition with Control (DMDc) to enable model-based control, with noise reduced by a Savitzky–Golay filter. The identified model was validated against a Least Squares Estimation (LSE) baseline and actual vehicle responses under multi-input conditions. A Linear Quadratic Regulator (LQR) was then designed using the identified model for vehicle control.
Second, to handle slope variations in off-road environments, a real-time system identification method combining Set Membership Estimation (SME) and Least Squares Estimation (LSE) was developed. The updated model was incorporated into a Slope-aware Adaptive Model Predictive Controller (SAMPC) to reduce slope-induced path-tracking disturbances. The framework was validated in simulation and real-world tests, improving performance over a standard MPC.
Third, an Adaptive Tube Model Predictive Controller (ATMPC) was developed for complex off-road environments with unmodeled disturbances. Terrain classification enabled online model selection, while slope, slip ratio, and vibration indices were incorporated for adaptive dynamics and stability constraints. The controller was tested in both simulated multi-terrain settings and real-world experiments, showing improved tracking and stability over a standard MPC.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-12-01The student, Jiaming Zhang, accepted the attached license on 2025-12-02 at 20:07.The student, Jiaming Zhang, submitted this Dissertation for approval on 2025-12-02 at 20:08.This Dissertation was approved for publication on 2025-12-03 at 11:37.DSpace SAF Submission Ingestion Package generated from Vireo submission #23000 on 2026-02-19 at 18:46:1
On Factors Affecting Industrial Development Growth RatesâA Discussion with Comrade Zhu Jiaming
No full textIn the past few months, the unabating high rate of industrial development has, in an acute fashion, presented to theoretical circles the question of how to view the current high growth rate. In his article published in the second issue of the >i>Forum of Young Economists>/i>, Comrade Zhu Jiaming declares that China "already has the preliminary material preconditions for high-speed growth," and that "since 1978, some indexes of economic growth have shown that the period of high-speed growth has already come." This author, however, holds that the problem cannot be explained by looking only at indexes of a few years, and that in order to determine whether or not China has entered a period of high-speed growth, it is necessary to analyze the factors that affect the rate of industrial development and the trend of their changes. The present article is written to invite comments and corrections by Comrade Zhu Jiaming and others.
sj-docx-3-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-3-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
sj-docx-2-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-2-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
sj-docx-1-tag-10.1177_17562848221101722 – Supplemental material for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study
No full textSupplemental material, sj-docx-1-tag-10.1177_17562848221101722 for SARS-CoV-2-inactivated vaccine hesitancy and the safety in inflammatory bowel disease patients: a single-center study by Yubin Cao, Jiaming Feng, Shihao Duan, Yi Yang and Yan Zhang in Therapeutic Advances in Gastroenterology</p
Multilayered microstructures achieved by a concentration gradient initial condition via spinodal decomposition evidenced in the Ti-Nb multifunctional alloy
No full textMetals with multilayered structures have attracted much attention due to their excellent mechanical and physical properties. While it remains a challenge to achieve nanolayered structures in bulk materials. Spinodal decomposition is an effective and cost-efficient method for producing nano/micro-scale patterns in bulk materials. However, conventional spinodal decomposition usually forms droplet or interpenetrated microstructures, rather than layered structures. From mechanics' point of view, microstructures of materials can be tailored by controlling initial or boundary conditions of equations governing the evolution of microstructures. In this work, by employing computer simulations, we show that nano/micro-layered structures can be achieved in bulk materials by setting a special concentration gradient initial condition upon spinodal decomposition. The mechanism is found to be the "inductive effect" of the multilayered boundary condition induced by the concentration gradient initial condition. The findings of this study provide valuable insights and guidance for developing multilayered materials with desired properties
A LightGBM-Based EEG Analysis Method for Driver Mental States Classification
Full text linkFatigue driving can easily lead to road traffic accidents and bring great harm to individuals and families. Recently, electroencephalography-
(EEG-) based physiological and brain activities for fatigue detection have been increasingly investigated.
However, how to find an effective method or model to timely and efficiently detect the mental states of drivers still remains a
challenge. In this paper, we combine common spatial pattern (CSP) and propose a light-weighted classifier, LightFD, which is
based on gradient boosting framework for EEG mental states identification. ,e comparable results with traditional classifiers,
such as support vector machine (SVM), convolutional neural network (CNN), gated recurrent unit (GRU), and large margin
nearest neighbor (LMNN), show that the proposed model could achieve better classification performance, as well as the decision
efficiency. Furthermore, we also test and validate that LightFD has better transfer learning performance in EEG classification of
driver mental states. In summary, our proposed LightFD classifier has better performance in real-time EEG mental state
prediction, and it is expected to have broad application prospects in practical brain-computer interaction (BCI)
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