Article
Engineering, Multidisciplinary
Behrouz Mataei, Fereidoon Moghadas Nejad, Hamzeh Zakeri
Summary: This paper presents a 3D automatic device based on a cumulative imaging technique for measuring pavement texture. The device generates 3D point cloud models and extracts evaluation indices for assessing pavement texture, including a new method for evaluating texture in rainy conditions. Experimental tests demonstrate a high correlation between the results of this system and traditional sand patch tests.
Article
Engineering, Multidisciplinary
Hongjia Chen, Dejin Zhang, Rong Gui, Fangling Pu, Min Cao, Xin Xu
Summary: Pavement texture evaluation is crucial for enhancing skid resistance and pavement maintenance. Existing methods mainly focus on damaged areas and static measurement environment, resulting in a gap between theory and practice. In this study, an efficient texture decomposition method and the Pavement Transformer were proposed to overcome these limitations and improve the accuracy and stability of texture evaluation.
Article
Chemistry, Analytical
Chu Chu, Ya Wei, Haipeng Wang
Summary: The surface quality of pavement has a significant impact on driving comfort and skid resistance. 3D pavement texture measurement is used to calculate the pavement performance index of different pavements. However, the accuracy of measuring large surface areas, like pavement surfaces, using the interference-fringe-based texture measurement is affected by unequal incident angles. This study aims to improve the accuracy of 3D pavement texture reconstruction by considering the influence of unequal incident angles during postprocessing.
Article
Construction & Building Technology
Yuchen Wang, Bin Yu, Xiaoyu Zhang, Jia Liang
Summary: This paper develops a 3D laser scanning system and corresponding methods for the extraction and evaluation of pavement texture depth. The proposed methods have high accuracy and provide a reference for autonomous detection of pavement performance.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Sheng Wei, Yuhong Wang, Huailei Cheng, Dawei Wang
Summary: The study evaluated the impact of pavement textures on tire-induced stress distribution, revealing that different textures play an important role in surface stress distribution. Compared to flat surfaces, all types of textures cause stress concentrations, with arc-shaped textures experiencing the highest tensile and compressive stresses, while rectangular and rounded trapezoidal textures exhibit similar behavior in stress magnitude and distribution.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Chemistry, Analytical
Guangwei Yang, Kelvin C. P. Wang, Joshua Q. Li, Guolong Wang
Summary: This study explores the feasibility of using a 0.1 mm 3D Safety Sensor for pavement safety evaluation, and the results indicate that the sensor is capable of accurately measuring pavement texture data and friction numbers, and can be used to predict hydroplaning speed.
Article
Construction & Building Technology
Shihai Ding, Kelvin C. P. Wang, Enhui Yang, You Zhan
Summary: This study used 3D laser technology to measure the texture of different types of asphalt pavement surfaces and found a significant positive correlation between pavement anti-skid value and texture surface area within the depth range of 0.5-2 mm, with the lowest determination coefficient of 0.6836. This research confirms that the effective texture depth influencing pavement friction is 2 mm and that texture surface area can be used as an indicator of pavement friction during its service life.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Construction & Building Technology
Shihai Ding, Guangwei Yang, Kelvin C. P. Wang, Enhui Yang, Aonan Zhan
Summary: This study presents an automatic non-contact method using high resolution 3D images for accurate and efficient pavement texture evaluation. The results indicate that it is accurate and efficient to evaluate pavement texture using high resolution 3D images in a non-contact and automatic manner.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Mathematics
Han-Cheng Dan, Yongcheng Long, Hui Yao, Songlin Li, Yanhao Liu, Quanfeng Zhou
Summary: This paper applies multi-visual technology to capture the surface image of asphalt pavement and transform it into a visualized 3D point cloud model. Then, the disordered 3D point cloud is rasterized and projected into a 2D matrix based on the principle of the digital elevation model (DEM). Fractal dimensions are calculated in different dimensions to characterize the pavement roughness.
ELECTRONIC RESEARCH ARCHIVE
(2023)
Article
Engineering, Multidisciplinary
Cunqiang Liu, Juan Li, Jie Gao, Dongdong Yuan, Ziqiang Gao, Zhongjie Chen
Summary: This study proposes a method based on deep learning to measure and reconstruct macro-texture using any number of pavement views, and demonstrates its effectiveness and stability through experiments. The 3D model allows for the assessment of pavement performance, with average errors of 7.62% for mean texture depth and 6.32% for dynamic fraction coefficient.
Article
Chemistry, Physical
Bo Chen, Pengbo Ding, Guojie Wei, Chunlong Xiong, Fangli Wang, Jinfeng Yu, Huayang Yu, Yuxun Zou
Summary: Tire-road characteristics research is crucial for the automotive and transportation industries. It helps optimize tire design and analyze the mechanical response of pavement under vehicle load. The distribution of tire ground stress also directly affects skid resistance and driving safety. However, current testing technologies mainly focus on flat platforms, ignoring the roughness of actual pavement surfaces.
Article
Chemistry, Physical
Yiwen Zou, Guangwei Yang, Wanqing Huang, Yang Lu, Yanjun Qiu, Kelvin C. P. Wang
Summary: The study conducted field evaluation of pavement micro- and macro-texture using a portable high-resolution 3D laser scanner. The 3D areal parameters were calculated to characterize pavement texture, providing an alternative to comprehensively describe the evolution of pavement texture under traffic polish.
Article
Optics
Jaehoon Lee, Myungjin Cho, Min-chul Lee
Summary: In this paper, a three-dimensional (3D) photon counting integral imaging method is proposed using multi-level decomposition, such as discrete wavelet transform, to improve the visual quality and measurement accuracy under photon-starved conditions. The method effectively emphasizes object photons and enhances the visual quality and accuracy of 3D images.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
(2022)
Article
Construction & Building Technology
Zhihao Pan, Jinchao Guan, Xu Yang, Kang Fan, Ningqun Guo, Xin Wang
Summary: A one-stage pavement crack detection and quantification method is proposed to directly extract crack geometry from 3D pavement profile, improving the robustness and efficiency of crack inspection tasks. A low-cost stereo imaging system is used for high-resolution 3D reconstruction, and an algorithm integrating crack detection and quantification is developed based on the generated 3D profile to obtain crack map, length, width, and depth simultaneously. The proposed method shows robustness to surrounding noises and does not require prior data, outperforming existing methods in terms of crack detection accuracy and measurement.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Engineering, Mechanical
Shenqing Xiao, Mingliang Li, Bo Chen, Xingye Zhou, Chenchen Xi, Yiqiu Tan
Summary: To understand the evolution of pavement texture, the self-affine characteristics and spatiotemporal variation of pavement texture were analyzed using long-term field observation data. The texture roughness of the same pavement shows similarity at a small scale but variability at a large scale. This variability is also reflected in the spatial variation of on-site texture depth. Additionally, the pavement texture depth increases over time, especially with traffic polishing, which leads to enlarged particle gaps and smoother particle surfaces.
TRIBOLOGY INTERNATIONAL
(2023)
Article
Multidisciplinary Sciences
Bruno Oliveira, Helena R. Torres, Pedro Morais, Fernando Veloso, Antonio L. Baptista, Jaime C. Fonseca, Joao L. Vilaca
Summary: Chronic Venous Disorders (CVD) of the lower limbs are a common medical condition that affects a significant proportion of adults in Europe and North America. The increase in the aging population and the worsening of CVD with age means that the healthcare costs and resources required for its treatment are expected to rise. This paper proposes a novel automatic strategy, using a multi-task deep learning network, for the joint segmentation and classification of CVDs, improving the efficiency and performance of both tasks.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu, Armine Vardazaryan, Fangfang Xia, Zixuan Zhao, Tong Xia, Fucang Jia, Yuxuan Yang, Hao Wang, Derong Yu, Guoyan Zheng, Xiaotian Duan, Neil Getty, Ricardo Sanchez-Matilla, Maria Robu, Li Zhang, Huabin Chen, Jiacheng Wang, Liansheng Wang, Bokai Zhang, Beerend Gerats, Sista Raviteja, Rachana Sathish, Rong Tao, Satoshi Kondo, Winnie Pang, Hongliang Ren, Julian Ronald Abbing, Mohammad Hasan Sarhan, Sebastian Bodenstedt, Nithya Bhasker, Bruno Oliveira, Helena R. Torres, Li Ling, Finn Gaida, Tobias Czempiel, Joao L. Vilaca, Pedro Morais, Jaime Fonseca, Ruby Mae Egging, Inge Nicole Wijma, Chen Qian, Guibin Bian, Zhen Li, Velmurugan Balasubramanian, Debdoot Sheet, Imanol Luengo, Yuanbo Zhu, Shuai Ding, Jakob-Anton Aschenbrenner, Nicolas Elini van der Kar, Mengya Xu, Mobarakol Islam, Lalithkumar Seenivasan, Alexander Jenke, Danail Stoyanov, Didier Mutter, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Nicolas Padoy
Summary: Context-aware decision support in the operating room can enhance surgical safety and efficiency by utilizing real-time feedback from surgical workflow analysis. However, most existing works only recognize surgical activities at a coarse-grained level, lacking fine-grained interaction details that are crucial for more effective AI assistance in the operating room.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Chemistry, Analytical
Ali Abbasi, Sandro Queiros, Nuno M. C. da Costa, Jaime C. Fonseca, Joao Borges
Summary: This study explores the advantages of a low-level sensor fusion approach that combines grayscale and neuromorphic vision sensor (NVS) data for multi-human detection and tracking in indoor surveillance. By generating a custom dataset using an NVS camera in an indoor environment, we conducted a comprehensive study by experimenting with different image features and deep learning networks, followed by a multi-input fusion strategy to optimize our experiments. Our results demonstrate the potential of sensor fusion and deep learning techniques for multi-human tracking in indoor surveillance, although further studies are needed to confirm our findings.
Article
Chemistry, Analytical
Antonio Real, Pedro Morais, Bruno Oliveira, Helena R. R. Torres, Joao L. Vilaca
Summary: This study aims to design a force measuring system that can be embedded into an existing PC orthosis to monitor the applied pressure accurately. Three concepts of silicone-based sensors were proposed and tested, with one capacitive sensor showing identical response to a solid silicone pad. This system demonstrated its potential for clinical practice.
Article
Chemistry, Analytical
Nuno Costa, Luis Ferreira, Augusto R. V. F. de Araujo, Bruno Oliveira, Helena R. R. Torres, Pedro Morais, Victor Alves, Joao L. Vilaca
Summary: Breast cancer is a common and deadly disease, and early screening and treatment are crucial. This study proposes a visualization system for breast biopsy using AR glasses and computer applications, which greatly improves lesion visualization and needle alignment. The system was evaluated and showed promising results, with precise needle alignment and accurate lesion targeting.
Article
Chemistry, Analytical
Nelson R. P. Rodrigues, Nuno M. C. da Costa, Cesar Melo, Ali Abbasi, Jaime C. Fonseca, Paulo Cardoso, Joao Borges
Summary: This article proposes a fusion monitoring solution using deep learning algorithms, including violent action detection, violent object detection, and lost items detection. State-of-the-art algorithms like YOLOv5, I3D, R(2+1)D, SlowFast, TSN, and TSM were trained on public datasets to achieve real-time operation with an embedded automotive solution.
Article
Acoustics
Ablenya Barros, Michiel Geluykens, Frederico Pereira, Elisabete Freitas, Susana Faria, Luc Goubert, Cedric Vuye
Summary: This study explores the role of psychoacoustic indicators in pass-by vehicle noise, including different vehicle categories, driving speeds, and temperatures. These indicators are used as features to train a classification algorithm and predict vehicle category. The results show that a predictive model using ISO 11819-1 defined vehicle categories achieves an accuracy of 84%. Including an additional vehicle category decreases accuracy to 72%, but combining the two categories increases overall accuracy to 86%. These findings are important for achieving consistent vehicle classification in terms of noise worldwide and developing vehicle classification systems that resemble the human auditory experience.
Article
Materials Science, Composites
E. Pimentela, P. Costa, C. R. Tubio, J. L. Vilaca, C. M. Costa, S. Lanceros-Mendez, D. Miranda
Summary: Flexible sensor devices are in high demand for new and improved health treatments, particularly for neurogenic bladder dysfunction. Polymer composites based on different matrices (CMC, SEBS, and PVA) and varying concentrations of multiwalled carbon nanotubes (CNT) have been developed for catheter medical device application. These composites demonstrate excellent electrical and mechanical properties, with high conductivity and piezoresistive response.
COMPOSITES SCIENCE AND TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Kelly Payette, Hongwei Bran Li, Priscille de Dumast, Roxane Licandro, Hui Ji, Md Mahfuzur Rahman Siddiquee, Daguang Xu, Andriy Myronenko, Hao Liu, Yuchen Pei, Lisheng Wang, Ying Peng, Juanying Xie, Huiquan Zhang, Guiming Dong, Hao Fu, Guotai Wang, ZunHyan Rieu, Donghyeon Kim, Hyun Gi Kim, Davood Karimi, Ali Gholipour, Helena R. Torres, Bruno Oliveira, Joao L. Vilaca, Yang Lin, Netanell Avisdris, wOri Ben-Zvi, Dafna Ben Bashat, Lucas Fidon, Michael Aertsen, Tom Vercauteren, Daniel Sobotka, Georg Langs, Mireia Alenya, Maria Inmaculada Villanueva, Oscar Camara, Bella Specktor Fadida, Leo Joskowicz, Liao Weibin, Lv Yi, Li Xuesong, Moona Mazher, Abdul Qayyum, Domenec Puig, Hamza Kebiri, Zelin Zhang, Xinyi Xu, Dan Wu, Kuanlun Liao, Yixuan Wu, Jintai Chen, Yunzhi Xu, Li Zhao, Lana Vasung, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
Summary: In-utero fetal MRI is an important tool for diagnosing and analyzing the developing human brain. Manual segmentation of cerebral structures is time-consuming and prone to errors, so the Fetal Tissue Annotation (FeTA) Challenge was organized to encourage the development of automatic segmentation algorithms. The challenge utilized the FeTA Dataset, and 20 international teams participated, submitting a total of 21 algorithms. This paper provides a detailed analysis of the results and serves as a benchmark for future algorithms in this field.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Computer Science, Artificial Intelligence
Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma, Aditya Murali, Deepak Alapatt, Armine Vardazaryanau, Kun Yuan, Jonas Hajek, Wolfgang Reiter, Amine Yamlahi, Finn-Henri Smidt, Xiaoyang Zou, Guoyan Zheng, Bruno Oliveira, Helena R. Torres, Satoshi Kondo, Satoshi Kasai, Felix Holm, Ege Oezsoy, Shuangchun Gui, Han Li, Sista Raviteja, Rachana Sathish, Pranav Poudel, Binod Bhattarai, Ziheng Wang, Guo Rui, Melanie Schellenberg, Joao L. Vilaca, Tobias Czempiel, Zhenkun Wang, Debdoot Sheet, Shrawan Kumar Thapa, Max Berniker, Patrick Godau, Pedro Morais, Sudarshan Regmi, Thuy Nuong Tran, Jaime Fonseca, Jan-Hinrich Noelke, Estevao Lima, Eduard Vazquez, Lena Maier-Hein, Nassir Navab, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Didier Mutter, Nicolas Padoy
Summary: Formalizing surgical activities as triplets of instruments, actions, and anatomies is a standard approach for surgical activity modeling. This helps in understanding tool-tissue interaction and developing better AI assistance for image-guided surgery. This paper presents the CholecTriplet2022 challenge, which extends surgical action modeling to detection and provides baseline methods and deep learning algorithms to solve the task.
MEDICAL IMAGE ANALYSIS
(2023)
Review
Chemistry, Analytical
Claver Pinheiro, Salmon Landi Jr, Orlando Lima Jr, Larissa Ribas, Nathalia Hammes, Iran Rocha Segundo, Natalia Candido Homem, Veronica Castelo Branco, Elisabete Freitas, Manuel Filipe Costa, Joaquim Carneiro
Summary: This research provides a dual-pronged bibliometric and systematic review of the integration of phase change materials (PCM) in asphalt pavements to counteract the urban heat island (UHI) effect. The findings identify polyethylene glycols (PEGs) as the prevailing PCM for UHI mitigation, and highlight the need for further research to achieve optimal thermal and mechanical balance in asphalt pavements.
Review
Materials Science, Multidisciplinary
Iran Gomes da Rocha Segundo, Elida Melo Margalho, Orlando de Sousa Lima, Claver Giovanni da Silveira Pinheiro, Elisabete Fraga de Freitas, Joaquim Alexandre S. A. Oliveira Carneiro
Summary: This research provides a bibliometric review of smart asphalt mixtures, showing that China is the most productive country and that self-healing is the most important capability. The research articles were mainly published in the journal Construction and Building Materials.
Article
Construction & Building Technology
Behzad Zahabizadeh, Iran Rocha Segundo, Jose Pereira, Elisabete Freitas, Aires Camoes, Vasco Teixeira, Manuel F. M. Costa, Vitor M. C. F. Cunha, Joaquim O. Carneiro
Summary: The objective of this study was to evaluate the photocatalytic behavior of 3D printed cementitious mortars functionalized with TiO2 nanoparticles. The results indicated successful activation of catalyst particles under illumination, where higher light power intensity increased the degradation efficiency. Furthermore, dye degradation efficiency increased with increasing coating rates of nano-TiO2 particles on the surface of the specimens.
JOURNAL OF BUILDING ENGINEERING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Sergio G. Pereira, Fernando Veloso, Tiago H. Barros, Pedro Lobo, Pedro Morais, Joao L. Vilaca
Summary: Deformational Plagiocephaly (DP) is a common medical condition in children that can be corrected using physical therapy and cranial orthoses. This study proposes a new method to quantify pressure in a TPU structure and demonstrates that the applied force varies proportionally with the internal thickness of the material.
2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Andreia Caldas, Simao Valente, Nuno S. Rodrigues, Augusto R. V. F. de Araujo, Rolands Storzs, Antonio Real, Raul R. Ribeiro, Margarida R. Ferreira, Pedro Morais, Demetrio Matos, Joao L. Vilaca
Summary: Ultrasound (US) phantoms are models used to simulate human tissues for various purposes. This study focuses on constructing a breast phantom compatible with US for breast biopsy training. A synthetic breast model was created in SolidWorks and used as a reference for molds creation and 3D printing. The proposed methodology proved to be accurate, efficient, and cost-effective for breast biopsy training.
2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS
(2023)
