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Articles 61 - 90 of 2628
Full-Text Articles in Engineering
Mae Enewsbrief Oct-Dec 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University
Mae Enewsbrief Oct-Dec 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University
Department of Mechanical and Aerospace Engineering eNewsBrief
No abstract provided.
Ainet: Integrating Mamba And Cbam For Enhanced Camouflage Object Detection, Henry O. Velesaca, P. Andrea Mero, Abel A. Reyes-Angulo, Angel D. Sappa
Ainet: Integrating Mamba And Cbam For Enhanced Camouflage Object Detection, Henry O. Velesaca, P. Andrea Mero, Abel A. Reyes-Angulo, Angel D. Sappa
Michigan Tech Publications
This paper introduces AINet, a novel deep learning architecture designed for detecting camouflaged objects in complex and diverse environments. The objective of this work is to design an end-to-end camouflaged object detection architecture that simultaneously captures long-range dependencies and refines subtle camouflage cues, improving segmentation accuracy and boundary delineation across both standard COD benchmarks and real-world agricultural scenarios. AINet leverages the strengths of Mamba, an efficient sequential state model for capturing long-range dependencies, and the Convolutional Block Attention Module (CBAM) for feature refinement through attention mechanisms. Detecting camouflaged objects is a significant challenge across a wide range of real-world applications, …
Volcanic Plume Height During The 2021 Tajogaite Eruption (La Palma) From Two Complementary Monitoring Methods-Implications For Satellite-Based Products, África Barreto, Francisco Quirós, Omaira E. García, Jorge Pereda-De-Pablo, Daniel González-Fernández, Andrés Bedoya-Velásquez, Simon Carn, Et. Al.
Volcanic Plume Height During The 2021 Tajogaite Eruption (La Palma) From Two Complementary Monitoring Methods-Implications For Satellite-Based Products, África Barreto, Francisco Quirós, Omaira E. García, Jorge Pereda-De-Pablo, Daniel González-Fernández, Andrés Bedoya-Velásquez, Simon Carn, Et. Al.
Michigan Tech Publications
Volcanic emissions from the Tajogaite volcano, located on the Cumbre Vieja edifice on the island of La Palma (Canary Islands, Spain), caused significant public health and aviation disruptions throughout the eruption (19 September–13 December 2021, officially declared over on 25 December). Nonetheless, it is considered the most significant volcanic event in Europe over the past 75 years due to the substantial amount of SO2 released into the atmosphere. The Instituto Geográfico Nacional (IGN), the authority responsible for volcano surveillance in Spain, implemented extensive operational monitoring to track volcanic activity and to provide a robust estimation of the volcanic plume height …
Understanding Software Engineering Practices And Tools In Undergraduate Mechanical Engineering Students, Prisha Bhatia, Ramzey Burdette, Titilayo Oshinowo, Michelle Jarvie-Eggart, Stephanos Matsumoto
Understanding Software Engineering Practices And Tools In Undergraduate Mechanical Engineering Students, Prisha Bhatia, Ramzey Burdette, Titilayo Oshinowo, Michelle Jarvie-Eggart, Stephanos Matsumoto
Michigan Tech Publications
Though software development has increasingly become a part of modern engineering practice, even outside of computing, we lack a sufficiently deep understanding of how engineers in many disciplines learn and use software engineering practices and tools (SEPTs). SEPTs include, but extend beyond, programming itself, consisting of practices (e.g., unit testing) and tools (e.g., version control software) that support the design, implementation, or maintenance of software. While many disciplines outside of computing teach programming in their undergraduate curricula, little is known about how these disciplines use, teach, or adopt SEPTs. We thus conducted an exploratory qualitative study on SEPTs among undergraduate …
Leaching Of Manganese Using Bio-Solubilized Iron Reductant To Prevent Manganese Carbonate Formation, Palas Kamlakar Borkar, Neha Sharma, Atharva Rane, Kwabena Boafo, Timothy Eisele
Leaching Of Manganese Using Bio-Solubilized Iron Reductant To Prevent Manganese Carbonate Formation, Palas Kamlakar Borkar, Neha Sharma, Atharva Rane, Kwabena Boafo, Timothy Eisele
Michigan Tech Publications
A mixed culture of metal-reducing microorganisms was used to dissolve iron, which was then utilized as a reductant to extract manganese in a 250 mL two-stage bioleaching system. In this two-stage configuration, CO2 generation associated with microbial metabolism occurs in the iron-reduction stage, while MnO2 reduction is confined to a separate manganese-leaching stage, thereby minimizing manganese carbonate formation. The results demonstrated that the two-stage system effectively maintained Fe2+ availability, enhancing manganese dissolution while mitigating loss of manganese through manganese carbonate (MnCO3) formation. In contrast, a single-stage bioleaching approach, where microorganisms directly reduced manganese oxides, led to significant MnCO3 precipitation, …
Solar Backscatter Ultraviolet (Buv) Retrievals Of Mid-Stratospheric Aerosols From The 2022 Hunga Eruption, Robert J.D. Spurr, Matt Christi, Nickolay A. Krotkov, Won Ei Choi, Simon Carn, Can Li, Et Al.
Solar Backscatter Ultraviolet (Buv) Retrievals Of Mid-Stratospheric Aerosols From The 2022 Hunga Eruption, Robert J.D. Spurr, Matt Christi, Nickolay A. Krotkov, Won Ei Choi, Simon Carn, Can Li, Et Al.
Michigan Tech Publications
On 15 January 2022, a highly explosive eruption of the submarine Hunga volcano (Kingdom of Tonga) generated the largest stratospheric hydration event ever observed and the largest aerosol perturbation since the 1991 Pinatubo eruption. Here, we develop a novel method for satellite retrieval of stratospheric aerosol optical depth (AOD) and layer peak height (zp) using solar backscattered ultraviolet (BUV) radiation; this is made possible by the exceptional mid-stratospheric altitude of the Hunga aerosols. We analyze BUV observations of the Hunga stratospheric aerosol cloud on 17 January 2022 (47 h after the eruption), using BUV band 1 measurements from the TROPOspheric …
An Autonomous Robotic System For Object Retrieval And Delivery: Enhancing Independence For Users Living With Disability And Older Adults, Jincheng Li, Chenghao Lin, Amna Mazen, Youssef A. Bazzi
An Autonomous Robotic System For Object Retrieval And Delivery: Enhancing Independence For Users Living With Disability And Older Adults, Jincheng Li, Chenghao Lin, Amna Mazen, Youssef A. Bazzi
Michigan Tech Publications
As the global population ages, there is a growing need for assistive technologies to help older adults maintain their independence. This work presents a cost-effective autonomous socially assistive robot designed for object retrieval and delivery, enhancing accessibility in home environments. The system is built on the Robot Operating System (ROS) framework and integrates three key components: the Pioneer P3-DX mobile robot for autonomous navigation, the ReactorX-200 robotic arm for pick-and-place operations, and the Kinect v2 RGB-D camera for object detection and localization. Users interact with the robot through natural language processing by issuing voice commands to retrieve various objects. Microsoft …
Mechanism And Performance Characterization Of Dry-Process Asphalt Mixtures Modified With Ldpe/Eva/Sbs Composite Particles, Zhengwei Yi, Junhong Jiang, Xiaoxuan Du, Xiangyang Ren, Dongzhao Jin, Tai Sheng, Xiaoxue Li, Hongfu Liu
Mechanism And Performance Characterization Of Dry-Process Asphalt Mixtures Modified With Ldpe/Eva/Sbs Composite Particles, Zhengwei Yi, Junhong Jiang, Xiaoxuan Du, Xiangyang Ren, Dongzhao Jin, Tai Sheng, Xiaoxue Li, Hongfu Liu
Michigan Tech Publications
This study employed a dry-process method to prepare SBS/recycled LDPE/EVA composite-modified particles (CMP) for asphalt mixture modification. Conventional performance tests, including penetration tests, determined the optimal CMP dosage to be 8% by mass of asphalt. The rheological properties and microstructure of base asphalt, SBS-modified asphalt, and composite-modified asphalt were systematically compared, and the road performance of the corresponding mixtures was evaluated. The results demonstrated that the composite modifier forms a uniform elastic network within the asphalt, significantly enhancing both high- and low-temperature performance and fatigue life while also improving thermal stability and deformation resistance. The modification mechanism is predominantly based …
Diverse Enteric Bacterial, Viral, And Parasitic Pathogen Genes Are Shed In Animal Feces In Indiana, Anna A. Heintzman, Ishi Keenum, Drew Capone
Diverse Enteric Bacterial, Viral, And Parasitic Pathogen Genes Are Shed In Animal Feces In Indiana, Anna A. Heintzman, Ishi Keenum, Drew Capone
Michigan Tech Publications
Southern Indiana has intensive livestock production, yet species-resolved fecal pathogen and pathogen associated gene profiles are limited. At 10 sites in southern Indiana (April-June 2024), we collected 128 fecal specimens from 10 hosts: pigs (n=12), horses (12), cats (12), chickens (12), dogs (22), white-tailed deer (12), sheep (12), goats (12), cows (12), and humans (10). We extracted and assayed total nucleic acids using a custom 43-target TaqMan Array Card (RT-qPCR). Flotation microscopy was performed on pig and dog stools for helminth ova. In-silico specificity checks were conducted for selected targets due to potential for cross reactivity between pathogen species. Most …
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 12, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 12, 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 16, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 16, 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 20, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 20, 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 34, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 34, 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 76, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 76, 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.
Bulk Absorber Acoustic Characterization Via The Two-Cavity Impedance Tube Methoda), Anthony Ciletti, Janith Godakawela, Martha Brown, Bhisham Sharma
Bulk Absorber Acoustic Characterization Via The Two-Cavity Impedance Tube Methoda), Anthony Ciletti, Janith Godakawela, Martha Brown, Bhisham Sharma
Michigan Tech Publications
The primary goal of this study is to investigate and refine the two-cavity impedance tube method for acoustic characterization of bulk porous materials, specifically addressing previously unexplained inaccuracies in the prediction of surface impedance and absorption coefficients. Unlike the conventional two-thickness approach, the two-cavity method requires only one sample thickness and involves conducting measurements at various air cavity depths behind the sample. The initial analyses revealed previously unidentified numerical instabilities, resulting in anomalous predictions of sound absorption at specific frequencies. Through systematic investigation and use of calculated data, the numerical origins of these anomalies are uncovered and a practical solution, …
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 11, Yiming Yang, Jeremy P. Bos
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 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 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 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 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 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 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 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 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 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 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 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 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 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 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.