| 1. |
- Gao, Hongyuan, et al.
(författare)
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Monostatic MIMO radar direction finding in impulse noise
- 2021
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Ingår i: Digital Signal Processing: A Review Journal. - : Elsevier BV. - 1051-2004. ; 117
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Tidskriftsartikel (refereegranskat)abstract
- This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be robust to the presence of impulsive noise, offering preferable performance as compared to recent related approaches, even in cases when the number of available snapshots is small.
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| 2. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. 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(1).
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| 3. |
- Zhang, Min, et al.
(författare)
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Multidimensional factors affecting care needs in daily living among community-dwelling older adults : A structural equation modelling approach
- 2021
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Ingår i: Journal of Nursing Management. - : John Wiley & Sons. - 0966-0429 .- 1365-2834. ; 29:5, s. 1207-1219
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Tidskriftsartikel (refereegranskat)abstract
- Aims: To develop a model illustrating the factors that can influence care needs in daily living (CNDL) of older adults and the pathways between these. Background: The care needs in community-dwelling older adults have increased sharply. A better understanding of the elderly's CNDL would thus help policymakers define which types of support and services should be given. Methods: A multicentre study with structural equation modelling was conducted in this study. We recruited 3,448 community-dwelling older adults in China by using a stratified random cluster sampling technique. Results: Physical and mental health was the strongest predictor of CNDL. Both age and living situation had positive effects on CNDL, while economic factors, social support and family support were the major risk factors for CNDL. Conclusion: The presented model provides a better understanding of how to address CNDL in the targeted population. The older adults who are the oldest, low-income, non-empty nesters, and with poor self-rated health or the signs of loneliness should be firstly targeted for daily assistance. Implications for Nursing Management: Using this model could provide health authorities and managers with the information of distinguishing between the priority group and the strategies for easing the caregiving burden in older adults care, and thus improving resource utilization.
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