| 1. |
- Fenstermacher, M.E., et al.
(författare)
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DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy
- 2022
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Ingår i: Nuclear Fusion. - : IOP Publishing. - 0029-5515 .- 1741-4326. ; 62:4
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Tidskriftsartikel (refereegranskat)abstract
- DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L-H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ∼8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.
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| 2. |
- You, Xiaohu, et al.
(författare)
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Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts
- 2021
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Ingår i: Science China Information Sciences. - : Science Press. - 1674-733X .- 1869-1919. ; 64:1
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Forskningsöversikt (refereegranskat)abstract
- The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.
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| 3. |
- Lu, R.S., et al.
(författare)
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A ring-like accretion structure in M87 connecting its black hole and jet
- 2023
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Ingår i: Nature. - 0028-0836 .- 1476-4687. ; 616:7958, s. 686-690
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Tidskriftsartikel (refereegranskat)abstract
- The nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation1,2. Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole3. Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of [Formula: see text] Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects, in addition to the gravitationally lensed ring-like emission. The images show that the edge-brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black-hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow.
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| 4. |
- Zhang, Man, et al.
(författare)
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Terahertz Reading of Ferroelectric Domain Wall Dielectric Switching
- 2021
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Ingår i: ACS Applied Materials and Interfaces. - : American Chemical Society (ACS). - 1944-8244 .- 1944-8252. ; 13:10, s. 12622-12628
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Tidskriftsartikel (refereegranskat)abstract
- Ferroelectric domain walls (DWs) are important nanoscale interfaces between two domains. It is widely accepted that ferroelectric domain walls work idly at terahertz (THz) frequencies, consequently discouraging efforts to engineer the domain walls to create new applications that utilize THz radiation. However, the present work clearly demonstrates the activity of domain walls at THz frequencies in a lead-free Aurivillius phase ferroelectric ceramic, Ca0.99Rb0.005Ce0.005Bi2Nb2O9, examined using THz-time-domain spectroscopy (THz-TDS). The dynamics of domain walls are different at kHz and THz frequencies. At low frequencies, domain walls work as a group to increase dielectric permittivity. At THz frequencies, the defective nature of domain walls serves to lower the overall dielectric permittivity. This is evidenced by higher dielectric permittivity in the THz band after poling, reflecting decreased domain wall density. An elastic vibrational model has also been used to verify that a single frustrated dipole in a domain wall represents a weaker contribution to the permittivity than its counterpart within a domain. The work represents a fundamental breakthrough in understanding the dielectric contributions of domain walls at THz frequencies. It also demonstrates that THz probing can be used to read domain wall dielectric switching.
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| 5. |
- Chen, Zhelun, et al.
(författare)
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A review of data-driven fault detection and diagnostics for building HVAC systems
- 2023
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Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 339
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Forskningsöversikt (refereegranskat)abstract
- With the wide adoption of building automation system, and the advancement of data, sensing, and machine learning techniques, data-driven fault detection and diagnostics (FDD) for building heating, ventilation, and air conditioning systems has gained increasing attention. In this paper, data-driven FDD is defined as those that are built or trained from data via machine learning or multivariate statistical analysis methods. Following this definition, this paper reviews and summarizes the literature on data-driven FDD from three aspects: process, systems studied (including the systems being investigated, the faults being identified, and the associated data sources), and evaluation metrics. A data-driven FDD process is further divided into the following steps: data collection, data cleansing, data preprocessing, baseline establishment, fault detection, fault diagnostics, and potential fault prognostics. Literature reported data-driven methods used in each step of an FDD process are firstly discussed. Applications of data-driven FDD in various HVAC systems/components and commonly used data source for FDD development are reviewed secondly, followed by a summary of typical metrics for evaluating FDD methods. Finally, this literature review concludes that despite the promising performance reported in the literature, data-driven FDD methods still face many challenges, such as real-building deployment, performance evaluation and benchmarking, scalability and transferability, interpretability, cyber security and data privacy, user experience, etc. Addressing these challenges is critical for a broad real-building adoption of data-driven FDD.
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| 6. |
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| 7. |
- Ahmed, Shafique, et al.
(författare)
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Terahertz probing of low-temperature degradation in zirconia bioceramics
- 2022
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Ingår i: Journal of The American Ceramic Society. - : Wiley. - 0002-7820 .- 1551-2916. ; 105:2, s. 1106-1115
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Tidskriftsartikel (refereegranskat)abstract
- ZrO2-based ceramics are widely used in biomedical applications due to its color, biocompatibility, and excellent mechanical properties. However, low-temperature degradation (LTD) introduces a potential risk for long-term reliability of these materials. The development of innovative nondestructive techniques, which can explore LTD in zirconia-derived compounds, is strongly required. Yttria stabilized zirconia, 3Y-TZP, is one of the well-developed ZrO2-based ceramics with improved resistance to LTD for dental crown and implant applications. Here, 3Y-TZP ceramic powders were pressed and sintered to study the LTD phenomenon by phase transition behavior. The LTD-driven tetragonal-to-monoclinic phase transition was confirmed by XRD. XPS analysis demonstrated that induced LTD reduced the oxygen vacancies which supports these findings. It is proved that after the degradation, the 3Y-TZP ceramics show the decreased dielectric permittivity at terahertz frequencies due to the crystallographic phase transformation. Terahertz nondestructive probe is a promising method to investigate LTD in zirconia ceramics.
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| 8. |
- Du, Rong, et al.
(författare)
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Effective Urban Traffic Monitoring by Vehicular Sensor Networks
- 2015
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Ingår i: IEEE Transactions on Vehicular Technology. - : IEEE Press. - 0018-9545 .- 1939-9359. ; 64:1, s. 273-286
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Tidskriftsartikel (refereegranskat)abstract
- Traffic monitoring in urban transportation systems can be carried out based on vehicular sensor networks. Probe vehicles (PVs), such as taxis and buses, and floating cars (FCs), such as patrol cars for surveillance, can act as mobile sensors for sensing the urban traffic and send the reports to a traffic-monitoring center (TMC) for traffic estimation. In the TMC, sensing reports are aggregated to form a traffic matrix, which is used to extract traffic information. Since the sensing vehicles cannot cover all the roads all the time, the TMC needs to estimate the unsampled data in the traffic matrix. As this matrix can be approximated to be of low rank, matrix completion (MC) is an effective method to estimate the unsampled data. However, our previous analysis on the real traces of taxis in Shanghai reveals that MC methods do not work well due to the uneven samples of PVs, which is common in urban traffic. To exploit the intrinsic relationship between the unevenness of samples and traffic estimation error, we study the temporal and spatial entropies of samples and successfully define the important criterion, i.e., average entropy of the sampling process. A new sampling rule based on this relationship is proposed to improve the performance of estimation and monitoring.With the sampling rule, two new patrol algorithms are introduced to plan the paths of controllable FCs to proactively participate in trafficmonitoring. By utilizing the patrol algorithms for real-data-set analysis, the estimation error reduces from 35% to about 10%, compared with the random patrol or interpolation method in traffic estimation. Both the validity of the exploited relationship and the effectiveness of the proposed patrol control algorithms are demonstrated.
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| 9. |
- Qin, Zidi, et al.
(författare)
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Accelerating Deep Neural Networks by Combining Block-Circulant Matrices and Low-Precision Weights
- 2019
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Ingår i: Electronics. - : MDPI. - 2079-9292. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- As a key ingredient of deep neural networks (DNNs), fully-connected (FC) layers are widely used in various artificial intelligence applications. However, there are many parameters in FC layers, so the efficient process of FC layers is restricted by memory bandwidth. In this paper, we propose a compression approach combining block-circulant matrix-based weight representation and power-of-two quantization. Applying block-circulant matrices in FC layers can reduce the storage complexity from O(k2) to O(k). By quantizing the weights into integer powers of two, the multiplications in the reference can be replaced by shift and add operations. The memory usages of models for MNIST, CIFAR-10 and ImageNet can be compressed by 171x, 2731x and 128x with minimal accuracy loss, respectively. A configurable parallel hardware architecture is then proposed for processing the compressed FC layers efficiently. Without multipliers, a block matrix-vector multiplication module (B-MV) is used as the computing kernel. The architecture is flexible to support FC layers of various compression ratios with small footprint. Simultaneously, the memory access can be significantly reduced by using the configurable architecture. Measurement results show that the accelerator has a processing power of 409.6 GOPS, and achieves 5.3 TOPS/W energy efficiency at 800 MHz.
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| 10. |
- Yang, Chen, et al.
(författare)
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Towards IoT-enabled dynamic service optimal selection in multiple manufacturing clouds
- 2020
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 56, s. 213-226
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Tidskriftsartikel (refereegranskat)abstract
- With the Internet of Things, it is now possible to sense the real-time status of manufacturing objects and processes. For complex Service Selection (SS) in Cloud Manufacturing, real-time information can be utilized to deal with uncertainties emerging during task execution. Moreover, in the face of diversified demands, multiple manufacturing clouds (MCs) can provide a much wider range of choices of services with their real-time status. However, most researchers have neglected the superiority of multiple MCs and failed to make a study of how to utilize the abundant and diverse resources of multiple MCs, let alone the multi-MCs service mode under dynamic environment. Therefore, we first propose a new dynamic SS paradigm that can leverage the abundant services from multiple MCs, real-time sensing ability of the Internet of Things (IoT) and big data analytics technology for knowledge and insights. In this way, providing optimal manufacturing services (with high QoS) for customers can be guaranteed under dynamic environments. In addition, considering that a relatively long time might be spent to complete a complex manufacturing task after SS, a quantified approach, based on the Analytic Hierarchy Process and big data, is proposed to evaluate whether the intended cloud manufacturing services should be reserved to make sure that eligible services are ready to use without compromising cost or time. In this paper, the problem of IoT-enabled dynamic SS across multiple MCs is formulated in detail to enable an event-driven adaptive scheduling when the model is faced with three kinds of uncertainties (of the service market, service execution and the user side respectively). Experiments with different settings are also performed, which show the advantages of our proposed paradigm and optimization model.
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