Ladder: A software to label images, detect objects and deploy models recurrently for object detection

Object Detection (OD) is a computer vision technology that can locate and classify objects in images and videos, which has the potential to significantly improve efficiency in precision agriculture. To simplify OD application process, we developed Ladder - a software that provides users with a friendly graphic user interface (GUI) that allows for efficient labelling of training datasets, training OD models, and deploying the trained model. Ladder was designed with an interactive recurrent framework that leverages predictions from a pre-trained OD model as the initial image labeling. After adding human labels, the newly labeled images can be added into the training data to retrain the OD model. With the same GUI, users can also deploy well-trained OD models by loading the model weight file to detect new images. We used Ladder to develop a deep learning model to access wheat stripe rust in RGB (red, green, blue) images taken by an Unmanned Aerial Vehicle (UAV). Ladder employs OD to directly evaluate different severity levels of wheat stripe rust in field images, eliminating the need for photo stitching process for UAVs-based images. The accuracy for low, medium and high severity scores were 72%, 50% and 80%, respectively. This case demonstrates how Ladder empowers OD in precision agriculture and crop breeding.Comment: 5 pages, 2 figure

Environmental, Economic and Social Impact Assessment: Study of Bridges in China's Five Major Economic Regions

[EN] The construction industry of all countries in the world is facing the issue of sustainable development. How to make effective and accurate decision-making on the three pillars (Environment; Economy; Social influence) is the key factor. This manuscript is based on an accurate evaluation framework and theoretical modelling. Through a comprehensive evaluation of six cable-stayed highway bridges in the entire life cycle of five provinces in China (from cradle to grave), the research shows that life cycle impact assessment (LCIA), life cycle cost assessment (LCCA), and social impact life assessment (SILA) are under the influence of multi-factor change decisions. The manuscript focused on the analysis of the natural environment over 100 years, material replacement, waste recycling, traffic density, casualty costs, community benefits and other key factors. Based on the analysis data, the close connection between high pollution levels and high cost in the maintenance stage was deeply promoted, an innovative comprehensive evaluation discrete mathematical decision-making model was established, and a reasonable interval between gross domestic product (GDP) and sustainable development was determined.This research was funded by the Spanish Ministry of Economy and Competitiveness, along with FEDER (Fondo Europeo de Desarrollo Regional), project grant number: BIA2017-85098-R.Zhou, Z.; Alcalá-González, J.; Yepes, V. (2021). Environmental, Economic and Social Impact Assessment: Study of Bridges in China's Five Major Economic Regions. International Journal of Environmental research and Public Health. 18(1):1-33. https://doi.org/10.3390/ijerph18010122S133181ISO 14044:2006/AMD 1:2017. Environmental Management-Life Cycle Assessment-Requirements and Guidelines. ISOhttps://www.iso.org/standard/72357.htmlWuni, I. Y., Shen, G. Q. P., & Osei-Kyei, R. 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Proposal of Environmental Impact Assessment Method for Concrete in South Korea: An Application in LCA (Life Cycle Assessment). International Journal of Environmental Research and Public Health, 13(11), 1074. doi:10.3390/ijerph13111074OpenLCA 1.10http://www.openlca.org/openlca/ISO,14044:2006/AMD 2:2020, Environmental Management-Life Cycle Assessment-Requirements and Guidelines. ISOhttps://www.iso.org/standard/76122.htmlNavarro, I. J., Yepes, V., Martí, J. V., & González-Vidosa, F. (2018). Life cycle impact assessment of corrosion preventive designs applied to prestressed concrete bridge decks. Journal of Cleaner Production, 196, 698-713. doi:10.1016/j.jclepro.2018.06.110O’Born, R. (2018). Life cycle assessment of large scale timber bridges: A case study from the world’s longest timber bridge design in Norway. Transportation Research Part D: Transport and Environment, 59, 301-312. doi:10.1016/j.trd.2018.01.018Milani, C. J., & Kripka, M. (2019). Evaluation of short span bridge projects with a focus on sustainability. Structure and Infrastructure Engineering, 16(2), 367-380. doi:10.1080/15732479.2019.1662815Trunzo, G., Moretti, L., & D’Andrea, A. (2019). Life Cycle Analysis of Road Construction and Use. Sustainability, 11(2), 377. doi:10.3390/su11020377Li, H., Deng, Q., Zhang, J., Xia, B., & Skitmore, M. (2019). Assessing the life cycle CO2 emissions of reinforced concrete structures: Four cases from China. Journal of Cleaner Production, 210, 1496-1506. doi:10.1016/j.jclepro.2018.11.102Frangopol, D. M., Dong, Y., & Sabatino, S. (2017). Bridge life-cycle performance and cost: analysis, prediction, optimisation and decision-making. Structure and Infrastructure Engineering, 13(10), 1239-1257. doi:10.1080/15732479.2016.1267772Goh, K. C., Goh, H. H., & Chong, H.-Y. (2019). Integration Model of Fuzzy AHP and Life-Cycle Cost Analysis for Evaluating Highway Infrastructure Investments. Journal of Infrastructure Systems, 25(1), 04018045. doi:10.1061/(asce)is.1943-555x.0000473Heidari, M. R., Heravi, G., & Esmaeeli, A. N. (2020). Integrating life-cycle assessment and life-cycle cost analysis to select sustainable pavement: A probabilistic model using managerial flexibilities. Journal of Cleaner Production, 254, 120046. doi:10.1016/j.jclepro.2020.120046Wang, Z., Yang, D. Y., Frangopol, D. M., & Jin, W. (2019). Inclusion of environmental impacts in life-cycle cost analysis of bridge structures. Sustainable and Resilient Infrastructure, 5(4), 252-267. doi:10.1080/23789689.2018.1542212Cadenazzi, T., Dotelli, G., Rossini, M., Nolan, S., & Nanni, A. (2019). Life-Cycle Cost and Life-Cycle Assessment Analysis at the Design Stage of a Fiber-Reinforced Polymer-Reinforced Concrete Bridge in Florida. Advances in Civil Engineering Materials, 8(2), 20180113. doi:10.1520/acem20180113Social Impact Assessment (SIA)https://www.iucn.org/sites/dev/files/iucn_esms_sia_guidance_note.pdfZhang, A., Zhong, R. Y., Farooque, M., Kang, K., & Venkatesh, V. G. (2020). Blockchain-based life cycle assessment: An implementation framework and system architecture. Resources, Conservation and Recycling, 152, 104512. doi:10.1016/j.resconrec.2019.104512Parent, J., Cucuzzella, C., & Revéret, J.-P. (2010). Impact assessment in SLCA: sorting the sLCIA methods according to their outcomes. The International Journal of Life Cycle Assessment, 15(2), 164-171. doi:10.1007/s11367-009-0146-9Vanclay, F. (2019). Reflections on Social Impact Assessment in the 21st century. Impact Assessment and Project Appraisal, 38(2), 126-131. doi:10.1080/14615517.2019.1685807Zamarrón-Mieza, I., Yepes, V., & Moreno-Jiménez, J. M. (2017). A systematic review of application of multi-criteria decision analysis for aging-dam management. Journal of Cleaner Production, 147, 217-230. doi:10.1016/j.jclepro.2017.01.092Parsons, R. (2019). Forces for change in social impact assessment. Impact Assessment and Project Appraisal, 38(4), 278-286. doi:10.1080/14615517.2019.1692585Vanclay, F. (2003). International Principles for Social Impact Assessment: their evolution. Impact Assessment and Project Appraisal, 21(1), 3-4. doi:10.3152/147154603781766464Domínguez-Gómez, J. A. (2016). Four conceptual issues to consider in integrating social and environmental factors in risk and impact assessments. Environmental Impact Assessment Review, 56, 113-119. doi:10.1016/j.eiar.2015.09.009Fischer, T. B., Jha-Thakur, U., Fawcett, P., Clement, S., Hayes, S., & Nowacki, J. (2017). Consideration of urban green space in impact assessments for health. Impact Assessment and Project Appraisal, 36(1), 32-44. doi:10.1080/14615517.2017.1364021Balasbaneh, A. T., & Marsono, A. K. B. (2020). Applying multi-criteria decision-making on alternatives for earth-retaining walls: LCA, LCC, and S-LCA. The International Journal of Life Cycle Assessment, 25(11), 2140-2153. doi:10.1007/s11367-020-01825-6Balasbaneh, A. T., Marsono, A. K. B., & Khaleghi, S. J. (2018). Sustainability choice of different hybrid timber structure for low medium cost single-story residential building: Environmental, economic and social assessment. Journal of Building Engineering, 20, 235-247. doi:10.1016/j.jobe.2018.07.006Penadés-Plà, V., Martínez-Muñoz, D., García-Segura, T., Navarro, I. J., & Yepes, V. (2020). Environmental and Social Impact Assessment of Optimized Post-Tensioned Concrete Road Bridges. Sustainability, 12(10), 4265. doi:10.3390/su12104265Ali, M. S., Aslam, M. S., & Mirza, M. S. (2015). A sustainability assessment framework for bridges – a case study: Victoria and Champlain Bridges, Montreal. Structure and Infrastructure Engineering, 1-14. doi:10.1080/15732479.2015.1120754Kloepffer, W. (2008). Life cycle sustainability assessment of products. The International Journal of Life Cycle Assessment, 13(2), 89-95. doi:10.1065/lca2008.02.376Hu, M. (2019). Building impact assessment—A combined life cycle assessment and multi-criteria decision analysis framework. Resources, Conservation and Recycling, 150, 104410. doi:10.1016/j.resconrec.2019.104410Ecoinventhttps://www.ecoinvent.org/database/database.htmlThe Regional Catalan Governmenthttps://en.itec.cat/database/Psilca Greendatebasehttps://psilca.net/Ortiz, O., Castells, F., & Sonnemann, G. (2009). Sustainability in the construction industry: A review of recent developments based on LCA. Construction and Building Materials, 23(1), 28-39. doi:10.1016/j.conbuildmat.2007.11.012Asdrubali, F., Baldassarri, C., & Fthenakis, V. (2013). Life cycle analysis in the construction sector: Guiding the optimization of conventional Italian buildings. Energy and Buildings, 64, 73-89. doi:10.1016/j.enbuild.2013.04.018Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: An overview. Energy and Buildings, 42(10), 1592-1600. doi:10.1016/j.enbuild.2010.05.007Cabeza, L. F., Rincón, L., Vilariño, V., Pérez, G., & Castell, A. (2014). Life cycle assessment (LCA) and life cycle energy analysis (LCEA) of buildings and the building sector: A review. Renewable and Sustainable Energy Reviews, 29, 394-416. doi:10.1016/j.rser.2013.08.037Chau, C. K., Leung, T. M., & Ng, W. Y. (2015). A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings. Applied Energy, 143, 395-413. doi:10.1016/j.apenergy.2015.01.023Baker, L. (2018). Of embodied emissions and inequality: Rethinking energy consumption. Energy Research & Social Science, 36, 52-60. doi:10.1016/j.erss.2017.09.027Chen, L., Pelton, R. E. O., & Smith, T. M. (2016). Comparative life cycle assessment of fossil and bio-based polyethylene terephthalate (PET) bottles. Journal of Cleaner Production, 137, 667-676. doi:10.1016/j.jclepro.2016.07.094Walker, S., & Rothman, R. (2020). Life cycle assessment of bio-based and fossil-based plastic: A review. Journal of Cleaner Production, 261, 121158. doi:10.1016/j.jclepro.2020.121158Recipehttps://www.researchgate.net/publication/230770853_Recipe_2008New Version ReCiPe 2016 to Determine Environmental Impact|RIVMhttps://www.rivm.nl/en/news/new-version-recipe-2016-to-determine-environmental-impactPenadés-Plà, V., Martí, J. V., García-Segura, T., & Yepes, V. (2017). Life-Cycle Assessment: A Comparison between Two Optimal Post-Tensioned Concrete Box-Girder Road Bridges. Sustainability, 9(10), 1864. doi:10.3390/su9101864Zhou, Z., Alcalá, J., & Yepes, V. (2020). Bridge Carbon Emissions and Driving Factors Based on a Life-Cycle Assessment Case Study: Cable-Stayed Bridge over Hun He River in Liaoning, China. 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Bridge Structures, 15(4), 181-186. doi:10.3233/brs-190153Matos, J., Solgaard, A., Santos, C., Silva, M. S., Linneberg, P., Strauss, A., … Akiyama, M. (2017). Life Cycle Cost, As a Tool for Decision Making on Concrete Infrastructures. High Tech Concrete: Where Technology and Engineering Meet, 1832-1839. doi:10.1007/978-3-319-59471-2_210Edited by the Ministry of Construction, National Development and Reform Commission, 2002. Engineering Survey and Design Charging Standardshttps://wenku.baidu.com/view/3fa74a62effdc8d376eeaeaad1f34693daef1088.htmlRossi, B., Marquart, S., & Rossi, G. (2017). Comparative life cycle cost assessment of painted and hot-dip galvanized bridges. Journal of Environmental Management, 197, 41-49. doi:10.1016/j.jenvman.2017.03.022Wang, H., Schandl, H., Wang, X., Ma, F., Yue, Q., Wang, G., … Zheng, R. (2020). Measuring progress of China’s circular economy. Resources, Conservation and Recycling, 163, 105070. doi:10.1016/j.resconrec.2020.105070Wang, D., Liu, Q., Ma, L., Zhang, Y., & Cong, H. (2019). Road traffic accident severity analysis: A census-based study in China. Journal of Safety Research, 70, 135-147. doi:10.1016/j.jsr.2019.06.002Van der Vlegel, M., Haagsma, J. A., de Munter, L., de Jongh, M. A. C., & Polinder, S. (2020). Health Care and Productivity Costs of Non-Fatal Traffic Injuries: A Comparison of Road User Types. International Journal of Environmental Research and Public Health, 17(7), 2217. doi:10.3390/ijerph17072217Al-Rukaibi, F., AlKheder, S., AlOtaibi, N., & Almutairi, M. (2019). Traffic crashes cost estimation in Kuwait. International Journal of Crashworthiness, 25(2), 203-212. doi:10.1080/13588265.2019.1567966Jiménez, J. R., Ayuso, J., Agrela, F., López, M., & Galvín, A. P. (2012). Utilisation of unbound recycled aggregates from selected CDW in unpaved rural roads. 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Optimized Application of Sustainable Development Strategy in International Engineering Project Management

[EN] The aim of this paper is to establish an international framework for sustainable project management in engineering, to make up the lack of research in this field, and to propose a scientific theoretical basis for the establishment of a new project management system. The article adopts literature review, mathematical programming algorithm and case study as the research method. The literature review applied the visual clustering research method and analyzed the results of 21-year research in this field. As a result, the project management system was found to have defects and deficiencies. A mathematical model was established to analyze the composition and elements of the optimized international project management system. The case study research selected large bridges for analysis and verified the superiority and practicability of the theoretical system. Thus, the goal of sustainable development of bridges was achieved. The value of this re-search lies in establishing a comprehensive international project management system model; truly integrating sustainable development with project management; providing new research frames and management models to promote the sustainable development of the construction industry.This research was funded by the Spanish Ministry of Science and Innovation, along with FEDER (Fondo Europeo de Desarrollo Regional), project grant number: PID2020-117056RB-I00.Zhou, Z.; Alcalá-González, J.; Yepes, V. (2021). Optimized Application of Sustainable Development Strategy in International Engineering Project Management. Mathematics. 9(14):1-30. https://doi.org/10.3390/math9141633S13091

Research on Sustainable Development of the Regional Construction Industry Based on Entropy Theory

[EN] Human beings are now facing the increasingly urgent problem of global ecological environment pollution. To verify the scientific nature of environmental governance by governments of various countries, researchers need to provide a scientific basis and practical support for governments to adjust and formulate new policies and regulatory measures at any time through data analysis. This paper applies visual literature, aggregate analysis, engineering data programming, advanced mathematical science algorithms, and innovation entropy theory, and through this study obtains sustainable impact data from eight Chinese provinces in the 21st century, including environmental, economic, and social impacts. The results show that China¿s sustainable data should grow from 2021 to about 2044. After 2045, it will be stable, and there will be negative growth in a short period. The overall life cycle assessment (LCA) and social impact assessment (SIA) continue to remain in the positive range. There will be no negative growth in aggregate data and zero or negative emissions before 2108. The final research data are accurately presented in the form of annual emissions, which provide a scientific and theoretical basis for the government to formulate medium- and long-term ecological regulations and plans.This research was funded by the financial support of the Spanish Ministry of Science and Innovation (project: PID2020-117056RB-100), along with FEDER fundingZhou, Z.; Alcalá-González, J.; Yepes, V. (2022). Research on Sustainable Development of the Regional Construction Industry Based on Entropy Theory. Sustainability. 14(24):1-23. https://doi.org/10.3390/su142416645123142

Bridge Carbon Emissions and Driving Factors Based on a Life-Cycle Assessment Case Study: Cable-Stayed Bridge over Hun He River in Liaoning, China

[EN] Due to the rapid growth of the construction industry¿s global environmental impact, especially the environmental impact contribution of bridge structures, it is necessary to study the detailed environmental impact of bridges at each stage of the full life cycle, which can provide optimal data support for sustainable development analysis. In this work, the environmental impact case of a three-tower cable-stayed bridge was analyzed through openLCA software, and more than 23,680 groups of data were analyzed using Markov chain and other research methods. It was concluded that the cable-stayed bridge contributed the most to the global warming potential value, which was mainly concentrated in the operation and maintenance phases. The conclusion shows that controlling the exhaust pollution of passing vehicles and improving the durability of building materials were the key to reducing carbon contribution and are also important directions for future research.This research was funded by the Spanish Ministry of Economy and Competitiveness, along with FEDER (Fondo Europeo de Desarrollo Regional), project grant number: BIA2017-85098-R.Zhou, Z.; Alcalá-González, J.; Yepes, V. (2020). Bridge Carbon Emissions and Driving Factors Based on a Life-Cycle Assessment Case Study: Cable-Stayed Bridge over Hun He River in Liaoning, China. International Journal of Environmental research and Public Health. 17(16):1-22. https://doi.org/10.3390/ijerph17165953S1221716The Intergovernmental Panel on Climate Change https://www.ipcc.ch/2018/10/08/summary-for-policymakers-of-ipcc-special-report-on-global-warming-of-1-5c-approved-by-governments/Sánchez-Garrido, A. J., & Yepes, V. (2020). 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Residual-Sparse Fuzzy CC-Means Clustering Incorporating Morphological Reconstruction and Wavelet frames

Instead of directly utilizing an observed image including some outliers, noise or intensity inhomogeneity, the use of its ideal value (e.g. noise-free image) has a favorable impact on clustering. Hence, the accurate estimation of the residual (e.g. unknown noise) between the observed image and its ideal value is an important task. To do so, we propose an $\ell_0$ regularization-based Fuzzy $C$-Means (FCM) algorithm incorporating a morphological reconstruction operation and a tight wavelet frame transform. To achieve a sound trade-off between detail preservation and noise suppression, morphological reconstruction is used to filter an observed image. By combining the observed and filtered images, a weighted sum image is generated. Since a tight wavelet frame system has sparse representations of an image, it is employed to decompose the weighted sum image, thus forming its corresponding feature set. Taking it as data for clustering, we present an improved FCM algorithm by imposing an $\ell_0$ regularization term on the residual between the feature set and its ideal value, which implies that the favorable estimation of the residual is obtained and the ideal value participates in clustering. Spatial information is also introduced into clustering since it is naturally encountered in image segmentation. Furthermore, it makes the estimation of the residual more reliable. To further enhance the segmentation effects of the improved FCM algorithm, we also employ the morphological reconstruction to smoothen the labels generated by clustering. Finally, based on the prototypes and smoothed labels, the segmented image is reconstructed by using a tight wavelet frame reconstruction operation. Experimental results reported for synthetic, medical, and color images show that the proposed algorithm is effective and efficient, and outperforms other algorithms.Comment: 12 pages, 11 figur

Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow

A major challenge for video semantic segmentation is the lack of labeled data. In most benchmark datasets, only one frame of a video clip is annotated, which makes most supervised methods fail to utilize information from the rest of the frames. To exploit the spatio-temporal information in videos, many previous works use pre-computed optical flows, which encode the temporal consistency to improve the video segmentation. However, the video segmentation and optical flow estimation are still considered as two separate tasks. In this paper, we propose a novel framework for joint video semantic segmentation and optical flow estimation. Semantic segmentation brings semantic information to handle occlusion for more robust optical flow estimation, while the non-occluded optical flow provides accurate pixel-level temporal correspondences to guarantee the temporal consistency of the segmentation. Moreover, our framework is able to utilize both labeled and unlabeled frames in the video through joint training, while no additional calculation is required in inference. Extensive experiments show that the proposed model makes the video semantic segmentation and optical flow estimation benefit from each other and outperforms existing methods under the same settings in both tasks.Comment: Published in AAAI 202

Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications

This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are further used to adjust the similarity matrix for constrained spectral clustering. Other than the traditional constraint propagation on single-source data, our approach is also extended to more challenging constraint propagation on multi-source data where each pairwise constraint is defined over a pair of data points from different sources. This multi-source constraint propagation has an important application to cross-modal multimedia retrieval. Extensive results have shown the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201