| 1. |
- Zhang, S. N., et al.
(author)
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The high energy cosmic-radiation detection (HERD) facility onboard China's Space Station
- 2014
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In: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819496126
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Conference paper (peer-reviewed)abstract
- The High Energy cosmic-Radiation Detection (HERD) facility is one of several space astronomy payloads of the cosmic lighthouse program onboard China's Space Station, which is planned for operation starting around 2020 for about 10 years. The main scientific objectives of HERD are indirect dark matter search, precise cosmic ray spectrum and composition measurements up to the knee energy, and high energy gamma-ray monitoring and survey. HERD is composed of a 3-D cubic calorimeter (CALO) surrounded by microstrip silicon trackers (STKs) from five sides except the bottom. CALO is made of about 104 cubes of LYSO crystals, corresponding to about 55 radiation lengths and 3 nuclear interaction lengths, respectively. The top STK microstrips of seven X-Y layers are sandwiched with tungsten converters to make precise directional measurements of incoming electrons and gamma-rays. In the baseline design, each of the four side SKTs is made of only three layers microstrips. All STKs will also be used for measuring the charge and incoming directions of cosmic rays, as well as identifying back scattered tracks. With this design, HERD can achieve the following performance: energy resolution of 1% for electrons and gamma-rays beyond 100 GeV, 20% for protons from 100 GeV to 1 PeV; electron/proton separation power better than 10-5; effective geometrical factors of >3 m2sr for electron and diffuse gamma-rays, >2 m2sr for cosmic ray nuclei. R and D is under way for reading out the LYSO signals with optical fiber coupled to image intensified CCD and the prototype of one layer of CALO.
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| 2. |
- Zhang, S. -N, et al.
(author)
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Introduction to the high energy cosmic-radiation detection (HERD) facility onboard China's future space station
- 2017
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In: Proceedings of Science. - : Sissa Medialab Srl.
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Conference paper (peer-reviewed)abstract
- The High Energy cosmic-Radiation Detection (HERD) facility is one of several space astronomy payloads onboard China's Space Station, which is planned for operation starting around 2025 for about 10 years. The main scientific objectives of HERD are searching for signals of dark matter annihilation products, precise cosmic electron (plus positron) spectrum and anisotropy measurements up to 10 TeV, precise cosmic ray spectrum and composition measurements up to the knee energy, and high energy gamma-ray monitoring and survey. HERD is composed of a 3-D cubic calorimeter (CALO) surrounded by microstrip silicon trackers (STKs) from five sides except the bottom. CALO is made of about 7,500 cubes of LYSO crystals, corresponding to about 55 radiation lengths and 3 nuclear interaction lengths, respectively. The top STK microstrips of six X-Y layers are sandwiched with tungsten converters to make precise directional measurements of incoming electrons and gamma-rays. In the baseline design, each of the four side STKs is made of only three layers microstrips. All STKs will also be used for measuring the charge and incoming directions of cosmic rays, as well as identifying back scattered tracks. With this design, HERD can achieve the following performance: energy resolution of 1% for electrons and gamma-rays beyond 100 GeV and 20% for protons from 100 GeV to 1 PeV; electron/proton separation power better than 10-5; effective geometrical factors of >3 m2sr for electron and diffuse gamma-rays, >2 m2sr for cosmic ray nuclei. R&D is under way for reading out the LYSO signals with optical fiber coupled to image intensified IsCMOS and CALO prototype of 250 LYSO crystals.
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| 3. |
- Tommasini, R., et al.
(author)
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Accepted Tutorials at The Web Conference 2022
- 2022
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In: WWW 2022 - Companion Proceedings of the Web Conference 2022. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 391-399
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Conference paper (peer-reviewed)abstract
- This paper summarizes the content of the 20 tutorials that have been given at The Web Conference 2022: 85% of these tutorials are lecture style, and 15% of these are hands on.
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| 4. |
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| 5. |
- Gu, Feng, et al.
(author)
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Advance reservation for virtual overlay network services
- 2011
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In: 13th International Conference on Transparent Optical Networks (ICTON), 2011. - : IEEE conference proceedings. ; , s. 1-4
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Conference paper (peer-reviewed)abstract
- Network advance reservation is an area of growing interest and focus today. However most proposed solutions in this field have only focused on the scheduling of point-to-point client connections. Now as applications and user communities continue to expand, there is a growing need to extend advance reservation support for multipoint services. To address this concern, a heuristic solution is presented for virtual overlay network scheduling. The scheme uses graph-theoretic schemes and is analyzed in detail using network simulation.
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| 6. |
- Hu, N., et al.
(author)
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Polarimetric Imaging Using One Fractal SNSPD
- 2022
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In: 2022 Conference on Lasers and Electro-Optics, CLEO 2022. - : Institute of Electrical and Electronics Engineers Inc..
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Conference paper (peer-reviewed)abstract
- We demonstrate a polarimetric imaging system with one fractal superconducting nanowire single-photon detector and time-multiplexed photon-counting scheme, which allows us to obtain images with multiple types of contrast.
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| 7. |
- Kristan, M., et al.
(author)
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The Eighth Visual Object Tracking VOT2020 Challenge Results
- 2020
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In: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
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Conference paper (peer-reviewed)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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