Digital Commons Network^™

Comparative Study On Visual Recognition Distances Of Chinese And British Symbolic Traffic Signs And Guide Signs For Chinese Drivers, Wang Heng, Yuan Wanfu, Ren Jiaming, Pei Weihao, Li Weidong, Yang Zhen

Journal of China & Foreign Highway

To reveal the differences in drivers' visual recognition of traffic signs in a transnational context and provide a methodological reference for research on visual recognition distance differences, this study, based on the SILAB driving simulation platform, used triangular slippery road signs, circular end-of-speed-limit signs, and guide signs as examples to compare and analyze the differences in the relationship between sign size and visual recognition distance for Chinese drivers regarding Chinese and British traffic signs. In the experiment, the information content and location of the same types of Chinese and British traffic signs were kept consistent, and the sign sizes were …

Technical Framework Design For Unmanned Roller Cluster Operations, Jin Yongquan, Wu Difei, Fu Yingli, Liang Wenyao

Journal of China & Foreign Highway

To improve the efficiency and safety of road construction and address problems such as harsh environments, unstable construction quality, and high labor costs in traditional road construction, a technical framework for unmanned roller cluster operations was proposed. The framework consists of three modules:underlying hardware control, trajectory planning calculation, and cooperative operation scheduling, realizing unmanned compaction operations for the roller cluster. Specifically, the underlying hardware control module achieves unmanned control, positioning, and communication by retrofitting active rollers; the trajectory planning calculation module is used to plan the operation trajectories of unmanned rollers; the cooperative operation scheduling module coordinates the operation process …

Multi-Objective Maintenance Strategy Optimization Of Deteriorated Bridges Considering Carbon Emissions, Wei Yonghua, Tian Zhongchu

Journal of China & Foreign Highway

In order to realize the new situation of safe, economic, and low-carbon bridge maintenance and ensure the efficient operation of the bridge during the maintenance period, the reliability evaluation model of the deteriorated bridge was obtained based on the reliability theory. According to the carbon emission factor method, the carbon emission calculation model of the bridge maintenance stage was established. An objective function considering bridge reliability, maintenance cost, and carbon emission was constructed. Based on the objective function and bridge reliability constraints, a multi-objective optimization model of bridge maintenance strategy considering carbon emission was formed. By taking a bridge as …

Research On Carbon Emission Accounting For Road Engineering Foundation Reinforcement, Yang Penghui, Liu Rui, Wan Ch Uanfeng, Zhang Haixiao, Zhou Yefei, Lu Chunying

Journal of China & Foreign Highway

To cope with the increasingly serious global warming and implement China's carbon peak and carbon neutrality goals, the promotion of energy conservation and emission reduction in the construction industry should be accelerated. Starting with the foundation treatment project in road engineering, this study used the carbon emission factor method. According to the budget consumption quota of the project, the carbon emissions of each sub-project in the project were calculated. Then, the cost of each sub-project was calculated based on the engineering cost standard. From the perspectives of carbon emissions and engineering costs, data analysis was conducted to explore the project's …

Environmental And Economic Benefits Of Brick Aggregate For Road Applications In Bangladesh, Liu Zhifang, Liu Gang, Xu Jinlong, Zhang Jingbo

Journal of China & Foreign Highway

In response to the shortage of stone materials in Bangladesh, which leads to higher costs for road construction due to reliance on imports, this study investigated the significant potential of utilizing brick slag aggregate and recycled aggregate as substitutes for graded gravel. This approach was particularly relevant given the country’s large production of clay-fired bricks and substantial construction waste. Using a life cycle analysis (LCA) method, the study established environmental impact inventories for graded gravel, brick slag aggregate, and recycled aggregate. The BEPAS model was employed to quantitatively analyze the environmental impacts of the two alternative solutions, providing a comprehensive …

Translating Social Accountability Values Into Practice: Doctors’ Experiences From Problem- Based Learning Medical Curriculum In The United Arab Emirates, Nihar Ranjan Dash, Ahmed Alrazzak Hasswan, Mayar Abbas Ahmed Essam Samaha, Kamel A. Samara, Mohamed Hassan Taha

Abington Jefferson Health Papers

Purpose: Medical schools play a crucial role in preparing future doctors to address the health needs of patients and their communities. Graduates are expected to provide socially accountable care by upholding values such as relevance, equity, quality, and cost- effectiveness. This study explores how these values are understood and applied by medical graduates trained in problem-based learning (PBL) curricula. Methods: A cross-sectional online survey was conducted among University of Sharjah medical graduates to assess their exposure to and practice of social accountability values. Results: Of the 689 graduates invited, 503 (73%) responded, including 329 (65%) women. Most respondents, 375 (75%), …

Spartan Daily, February 5, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 7

Spectator 2026-02-05, Editors Of The Spectator

The Spectator

No abstract provided.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 11, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 13, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 14, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 15, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 17, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 18, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 23, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 26, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 28, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 30, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 35, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 36, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 37, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77 Lidar, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

The Cowl - V. 89 N. 13 - February 5, 2026

The Cowl

The Cowl - student newspaper of Providence College. Vol. 89 No. 13 - February 5, 2026. 20 pages.

Curriculum Subcommittee Minutes February 5, 2026, Utah State University

Educational Policies Committee

• Approval of Minutes - January 8, 2026
• Program Proposals
• Semester Course Approval Reviews
• Other Business
• Adjourn: 3:00 pm

General Education Subcommittee Agenda February 5, 2026, Utah State University

Educational Policies Committee

• Call to Order
• Approval of Minutes - January 8, 2026
• Course Approvals/Removals/Syllabi Approvals
• New Business
• Additional Items
• Adjourn: 9:30 am

General Education Subcommittee Minutes February 5, 2026, Utah State University

Educational Policies Committee

• Call to Order
• Approval of Minutes - January 8, 2025
• Course Approvals/Removals/Syllabi Approvals
• New Business
• Catalog Language Changes
• Utah's Public Lands
• Adjourn: 9:30 am

Educational Policies Committee Minutes February 5, 2026, Utah State University

Educational Policies Committee

• Approval of Minutes - January 8, 2026
• Subcommittee Reports
• Curriculum Subcommittee
• Program Proposals
• Academic Standards Subcommittee
• General Education Subcommittee
• Center for Civic Excellence
• Other Business
• Adjourn: 3:47 pm

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 22, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.

Wads 3d Object Detection Dataset (Wads-3d) - Sequence 24, Yiming Yang, Jeremy P. Bos

WADS-3D

WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.