| 1. |
- Kristan, M., et al.
(författare)
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The Eighth Visual Object Tracking VOT2020 Challenge Results
- 2020
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Ingår i: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ).
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| 2. |
- Chen, Pohua, et al.
(författare)
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Stabilization of Extra-Large-Pore Zeolite by Boron Substitution for the Production of Commercially Applicable Catalysts
- 2022
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Ingår i: Chemistry - A European Journal. - : Wiley. - 0947-6539 .- 1521-3765. ; 28:63
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Tidskriftsartikel (refereegranskat)abstract
- Stable extra-large-pore zeolites are desirable for industrial purposes due to their ability to accommodate bulky reactants and diffusion through channels. Although there are several extra-large pore zeolites reported, stable ones are rare. Thus, their stabilization is a feasible strategy for industrial applications. Here, an extra-large-pore zeolite EWT with boron substitution is presented, and the resulting zeolite B-RZM-3 increased the thermal stability from 600 °C in its silica form to 850 °C. The crystal structure, determined by combining continuous rotation electron diffraction (cRED) and powder X-ray diffraction (PXRD), shows that B atoms preferentially substitute the interrupted (HO)T(OT)3 (Q3) sites and are partially converted into 3-coordination to relax framework deformation upon heating. After Al-reinsertion post-treatment, Al-B-RZM-3 shows higher ethylbenzene selectivity and ethylene conversion rate per mol acid site than commercial ZSM-5 and Beta zeolite in benzene alkylation reaction. Synthesizing extra-large-pore zeolite in borosilicate form is a potential approach to stabilize interrupted zeolites for commercial applications.
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| 3. |
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| 4. |
- Fang, Shan, et al.
(författare)
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A Dynamic Transformation Car-Following Model for the Prediction of the Traffic Flow Oscillation
- 2024
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Ingår i: IEEE Intelligent Transportation Systems Magazine. - 1939-1390 .- 1941-1197. ; 16:1, s. 174-198
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Tidskriftsartikel (refereegranskat)abstract
- Car-following (CF) behavior is a fundamental of traffic flow modeling; it can be used for the virtual testing of connected and automated vehicles and the simulation of various types of traffic flow, such as free flow and traffic oscillation. Although existing CF models can replicate the free flow well, they are incapable of simulating complicated traffic oscillation, and it is difficult to strike a balance between accuracy and efficiency. This article investigates the error variation when the traffic oscillation is simulated by the intelligent driver model (IDM). Then, it divides the traffic oscillation into four phases (coasting, deceleration, acceleration, and stationary) by using the space headway of multiple steps. To simulate traffic oscillation between multiple human-driven vehicles, a dynamic transformation CF model is proposed, which includes the long-time prediction submodel [modified sequence-to-sequence (Seq2seq)] model, short-time prediction submodel (Transformer), and their dynamic transformation strategy]. The first submodel is utilized to simulate the coasting and stationary phases, while the second submodel is utilized to simulate the acceleration and deceleration phases. The results of experiments indicated that compared to K-nearest neighbors, IDM, and Seq2seq CF models, the dynamic transformation CF model reduces the trajectory error by 60.79–66.69% in microscopic traffic flow simulations, 7.71–29.91% in mesoscopic traffic flow simulations, and 1.59–18.26% in macroscopic traffic flow simulations. Moreover, the runtime of the dynamic transformation CF model (Inference) decreased by 14.43–66.17% when simulating the large-scale traffic flow.
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| 5. |
- Feng, Kailun, 1991-, et al.
(författare)
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Embedding Ensemble Learning into Construction Optimisation : A Computational Reduction Approach
- 2020
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Tidskriftsartikel (refereegranskat)abstract
- Simulation-based optimisation (SO), which combines simulation and optimisation technologies, is a popular approach for construction planning optimisation. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computing loads to levels that are unrealistic to support the real-time construction decision. This study proposes ensemble learning embedded simulation optimisation (ESO) as an alternative approach for construction optimisation. The ensemble learning (EL) algorithm modifies the SO framework through establishing a connection between the simulation and optimisation technologies. This approach reduces the computing loads associated with the conventional SO framework by accurately learning from simulations and providing efficient fitness evaluations for optimisation. A large-scale project application shows that the proposed approach was able to reduce the computing loads of SO by approximately 90% yet still provide comparable optimisation quality. The proposed method is an alternative approach to SO that can be run on standard computing platforms and supports nearly real-time optimisation decisions.
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| 6. |
- Feng, Kailun, 1991-, et al.
(författare)
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Embedding ensemble learning into simulation-based optimisation : a learning-based optimisation approach for construction planning
- 2023
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Ingår i: Engineering Construction and Architectural Management. - : Emerald Group Publishing Limited. - 0969-9988 .- 1365-232X. ; 30:1, s. 259-295
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Tidskriftsartikel (refereegranskat)abstract
- Purpose - Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.Design/methodology/approach - This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.Findings - A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.Originality/value - The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.
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| 7. |
- Murari, A., et al.
(författare)
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A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors
- 2024
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Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.
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| 10. |
- Wang, Shunfeng, 1991, et al.
(författare)
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Co-utilization of quarry tailings and fly ash for non-sintered ultra-lightweight aggregates (ULWAs) by autoclave technology
- 2022
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Ingår i: Construction and Building Materials. - : Elsevier BV. - 0950-0618. ; 346
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Tidskriftsartikel (refereegranskat)abstract
- Quarry tailings as solid waste with large output bring a heavy environmental and economic burden. The main objective of this study is to investigate the feasibility of co-utilizing quarry tailings and fly ash (FA) as the main sources in preparing the lightweight aggregates (LWAs). The expand perlite powder (characterized with low density and high surface area) and two chemical foaming agents (ammonium carbonate and Al powder) was added to reduce the density of LWAs furtherly and fabricate a type of ultra-lightweight aggregates (ULWAs) through autoclave curing. In spite of the basic properties (compressive strength, 1 h of water absorption, loose bulk density and apparent particle density), the evolution of pore structures in relation to the type of foaming agents were also determined by combining scanning electron microscope (SEM), mercury intrusion porosimetry (MIP) and Nuclear Magnetic Resonance (NMR). The results show that increasing the expand perlite content could increases the compressive strength and water absorption, decreases the loose bulk density, apparent density and the total porosity. The pores wall gradually reduces with the increase of chemical foaming agents. Isolated pores will transform into connected pores, which also increase the most probable pore diameter and total porosity. The loose bulk density of specimens with 3 wt% (NH4)2CO3 and Al powder are 873 kg/m3 and 798 kg/m3 compared to blank (1132 kg/m3). This work lays a solid foundation for the design and preparation of ULWAs from solid wastes.
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