| 1. |
- Chen, Y., et al.
(author)
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Theory-guided hard constraint projection (HCP) : A knowledge-based data-driven scientific machine learning method
- 2021
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In: Journal of Computational Physics. - : Academic Press Inc.. - 0021-9991 .- 1090-2716. ; 445
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Journal article (peer-reviewed)abstract
- Machine learning models have been successfully used in many scientific and engineering fields. However, it remains difficult for a model to simultaneously utilize domain knowledge and experimental observation data. The application of knowledge-based symbolic artificial intelligence (AI) represented by expert systems is limited by the expressive ability of the model, and data-driven connectionism AI represented by neural networks is prone to produce predictions that might violate physical principles. In order to fully integrate domain knowledge with observations and make full use of the strong fitting ability of neural networks, this study proposes theory-guided hard constraint projection (HCP). This deep learning model converts physical constraints, such as governing equations, into a form that is easy to handle through discretization, and then implements hard constraint optimization through projection in a patch. Based on rigorous mathematical proofs, theory-guided HCP can ensure that model predictions strictly conform to physical mechanisms in the constraint patch. The training process of theory-guided HCP only needs a small amount of labeled data (sparse observation), and it can supervise the model by combining the coordinates (label-free data) with domain knowledge. The performance of the theory-guided HCP is verified by experiments based on a published heterogeneous subsurface flow problem. The experiments show that theory-guided HCP requires fewer data, and achieves higher prediction accuracy and stronger robustness to noisy observations, than the fully connected neural networks and soft constraint models. Furthermore, due to the application of domain knowledge, theory-guided HCP possesses the ability to extrapolate and can accurately predict points outside of the range of the training dataset.
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| 2. |
- Yan, Jinyue, 1959-, et al.
(author)
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Preface
- 2018
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In: Energy Procedia. - : Elsevier Ltd. - 1876-6102. ; 154, s. 1-2
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Journal article (other academic/artistic)
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| 3. |
- Eriksson, Kimmo, et al.
(author)
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Perceptions of the appropriate response to norm violation in 57 societies
- 2021
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In: Nature Communications. - : Nature Research. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- Norm enforcement may be important for resolving conflicts and promoting cooperation. However, little is known about how preferred responses to norm violations vary across cultures and across domains. In a preregistered study of 57 countries (using convenience samples of 22,863 students and non-students), we measured perceptions of the appropriateness of various responses to a violation of a cooperative norm and to atypical social behaviors. Our findings highlight both cultural universals and cultural variation. We find a universal negative relation between appropriateness ratings of norm violations and appropriateness ratings of responses in the form of confrontation, social ostracism and gossip. Moreover, we find the country variation in the appropriateness of sanctions to be consistent across different norm violations but not across different sanctions. Specifically, in those countries where use of physical confrontation and social ostracism is rated as less appropriate, gossip is rated as more appropriate. Little is known about peoples preferred responses to norm violations across countries. Here, in a study of 57 countries, the authors highlight cultural similarities and differences in peoples perception of the appropriateness of norm violations.
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| 4. |
- Hao, D., et al.
(author)
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Solar energy harvesting technologies for PV self-powered applications : A comprehensive review
- 2022
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In: Renewable energy. - : Elsevier Ltd. - 0960-1481 .- 1879-0682. ; 188, s. 678-697
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Journal article (peer-reviewed)abstract
- Many key aspects of society, such as transport, housing and health care, have been significantly improved by the advent of a range of electricity applications, and the power generation for electricity applications has been a major field of research. Photovoltaic (PV) self-powered technologies are promising technologies for addressing applications' power supply challenges and alleviating conventional electricity load and environmental pollution. This study reviews solar energy harvesting (SEH) technologies for PV self-powered applications. First, the PV power generation and scenarios of PV self-powered applications are analyzed. Second, analysis of system design for PV self-powered applications is presented. Third, key components for PV self-powered applications, including maximum power point tracking (MPPT) techniques and power management (PM) systems are discussed in detail. Furthermore, numerous PV self-powered applications and utilizations of energy harvesting are summarized. Finally, some recommendations are proposed for further research.
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| 5. |
- Zhang, Kai, et al.
(author)
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Power generation assessment of photovoltaic noise barriers across 52 major Chinese cities
- 2024
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In: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 361
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Journal article (peer-reviewed)abstract
- Photovoltaic noise barriers (PVNBs) have the potential to contribute to sustainable urban development by increasing the supply of renewable energy to cities while decreasing traffic noise pollution. However, estimating the power generation of PVNBs at the city or national scale remains a challenge due to the complexities of the urban environment and the difficulties associated with collecting data on road noise barriers (RNBs) and radiation. This study used RNBs, 2.5-dimensional (2.5D) buildings, and hourly time resolution radiation data, to estimate the power generation of PVNBs in 52 of China's major cities. First, hourly building shadows were estimated for each day of the year, covering the period from sunrise to sunset, to identify areas of RNB that are shaded at any given time. Second, hourly clear-sky radiation data were collected and corrected using a radiation correction model to simulate real weather radiation. Finally, utilizing an inclined surface radiation estimation model, the photovoltaic (PV) potential both inside and outside RNBs affected by building shadows was assessed. Subsequently, the power generation of PVNB was estimated based on parameters of mainstream PV systems in the market. The results show that the RNB mileage in 52 selected cities represents 87.7% of China's total RNB mileage. Building shadows often result in a radiation loss of approximately 30% for RNBs reception. The installed capacity and annual power generation of PVNBs in all investigated cities are 2.04 GW and 690.74 GWh, respectively. This study estimates the comprehensive PV potential of potentially exploitable PVNBs in China, offering essential scientific insights to inform and facilitate the strategic development of PVNB projects at both the national and municipal levels.
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| 6. |
- Zhang, Tingshen, et al.
(author)
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Vibration energy harvesting system based on track energy-recycling technology for heavy-duty freight railroads
- 2022
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In: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 323
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Journal article (peer-reviewed)abstract
- To ensure the efficient and safe operation of train transportation systems, the track vibration resulting from train movement can be utilized to power the sensors for intelligent applications. This paper presents a vibration energy harvesting system based on track energy-recycling technology for heavy-duty freight railroads. The energy-recycling system includes a vibration conversion module, a generator module and a power storage module. The irregular vertical vibrations produced by contact between the wheel and railroad are considered. The vibration conversion module converts the reciprocating vertical displacement into a one-way rotation through a scissor linkage and slider mechanism. A three-phase generator is coupled with an energy conversion module shaft and generates a three-phase direct current. Then, after rectification and filtering, the electricity is stored in the supercapacitors. Theoretical analysis, dynamic model analysis and mechanical simulation verify the dynamic response of the system under input excitation. Furthermore, mechanical testing and sensing (MTS) machine tests yield a 73.38% maximum mechanical efficiency with a 7.44 W peak power. Moreover, the charging tests of the proposed system with a supercapacitor indicate that the proposed system is suitable for self-powered sensors in railroads.
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| 7. |
- Andrighetto, Giulia, et al.
(author)
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Changes in social norms during the early stages of the COVID-19 pandemic across 43 countries
- 2024
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In: Nature Communications. - : NATURE PORTFOLIO. - 2041-1723. ; 15:1
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Journal article (peer-reviewed)abstract
- The emergence of COVID-19 dramatically changed social behavior across societies and contexts. Here we study whether social norms also changed. Specifically, we study this question for cultural tightness (the degree to which societies generally have strong norms), specific social norms (e.g. stealing, hand washing), and norms about enforcement, using survey data from 30,431 respondents in 43 countries recorded before and in the early stages following the emergence of COVID-19. Using variation in disease intensity, we shed light on the mechanisms predicting changes in social norm measures. We find evidence that, after the emergence of the COVID-19 pandemic, hand washing norms increased while tightness and punishing frequency slightly decreased but observe no evidence for a robust change in most other norms. Thus, at least in the short term, our findings suggest that cultures are largely stable to pandemic threats except in those norms, hand washing in this case, that are perceived to be directly relevant to dealing with the collective threat. Tightness-looseness theory predicts that social norms strengthen following threat. Here the authors test this and find that, after the emergence of the COVID-19 pandemic, hand washing norms increased, but no evidence was observed for a robust change in most other norms.
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| 8. |
- Arghavani, M., et al.
(author)
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SUSS : Improving TCP Performance by Speeding Up Slow-Start
- 2024
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In: ACM SIGCOMM 2024 - Proceedings of the 2024 ACM SIGCOMM 2024 Conference. - : Association for Computing Machinery, Inc. - 9798400706141 ; , s. 151-165
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Conference paper (peer-reviewed)abstract
- The traditional slow-start mechanism in TCP can result in slow ramping-up of the data delivery rate, inefficient bandwidth utilization, and prolonged completion time for small-size flows, especially in networks with a large bandwidth-delay product (BDP). Existing solutions either only work in specific situations, or require network assistance, making them challenging (if even possible) to deploy. This paper presents SUSS (Speeding Up Slow Start): a lightweight, sender-side add-on to the traditional slow-start mechanism, that aims to safely expedite the growth of the congestion window when a flow is significantly below its optimal fair share of the available bandwidth. SUSS achieves this by accelerating the growth in cwnd when exponential growth is predicted to continue in the next round. SUSS employs a novel combination of ACK clocking and packet pacing to effectively mitigate traffic burstiness caused by accelerated increases in cwnd. We have implemented SUSS in the Linux kernel, integrated into the CUBIC congestion control algorithm. Our real-world experiments span many device types and Internet locations, demonstrating that SUSS consistently outperforms traditional slow-start with no measured negative impacts. SUSS achieves over 20% improvement in flow completion time in all experiments with flow sizes less than 5MB and RTT larger than 50 ms.
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| 9. |
- Li, Hailong, 1976-, et al.
(author)
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A self-powered smart wave energy converter for sustainable sea
- 2024
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In: Mechanical systems and signal processing. - : Academic Press. - 0888-3270 .- 1096-1216. ; 220
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Journal article (peer-reviewed)abstract
- Self-powered smart buoys are widely used in sustainable sea, such as marine environmental monitoring. The article designs a self-powered and self-sensing point-absorber wave energy converter based on the two-arm mechanism. The system consists of the wave energy capture module, the power take-off module, the generator module and the energy storage module. As the core component of the wave energy converter, the power take-off module is mainly composed of a two-arm mechanism, which can convert the oscillation heave motion into unidirectional rotary motion. To evaluate the power generation performance of the system, the kinematic and dynamic models of the wave energy converter with the flywheel are established, and the disengagement and engagement phenomena of the flywheel are analyzed. The effectiveness of the prototype in capturing wave energy is verified through dry experiments in lab and field tests. The dry experiment reveals that the maximum output power of the system is 5.67 W, and the maximum and average mechanical efficiency are 66.63 % and 48.35 %, respectively. Additionally, the field test demonstrates that the peak output power can reach 92 W. Meanwhile, the generated electrical signals can be processed by deep learning algorithms to accurately identify different wave states. This high performance confirms that the proposed wave energy converter can meet its own energy needs by capturing wave energy in the marine environment, while also achieving self-sensing for wave condition monitoring. The system has great potential for promoting the development of intelligent sustainable sea in the future.
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| 10. |
- Li, Y., et al.
(author)
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CO2 emissions reduction by switching conference online : Uncertainty analysis of global air travel
- 2020
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In: Energy Proceedings. - : Scanditale AB.
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Conference paper (peer-reviewed)abstract
- Ideally, primary data collection is recommended for every life cycle assessment (LCA) study. However, due to limited availability or accessibility to first-hand data, related sources of secondary data can be a good alternative in practice. In this work, the uncertainty of using secondary data from the Ecoinvent Life Cycle Inventory (LCI) database is illustrated with an LCA case study on global air travel. Inside the database, both parameters’ basic uncertainty from measurements and additional uncertainty from data quality criteria are considered with the pedigree approach. The effect of updated pedigree matrix coefficients is also evaluated. Furthermore, the sensitivity with respect to the choice of system boundary is studied with a hotspot analysis for air travel. Outside the database, the uncertainty associated with mapping real world processes to those available in the database is analyzed. In particular, the influence of flight specific parameters, e.g. plane type and occupancy level, is assessed by comparing the International Civil Aviation Organizations (ICAO) carbon emissions calculator with database calculations. The results show that emissions calculated by ICAO generally lie on the lower end of confidence intervals provided by uncertainty analysis of the database, especially for very long-haul flights. Finally, for the LCA case study on air travel, a two-step method combining the advantages of both the ICAO calculator and the Ecoinvent database is proposed.
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