| 1. |
- Ghorbani, Mohammad, et al.
(författare)
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Testing the first-order separability hypothesis for spatio-temporal point patterns
- 2021
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Ingår i: Computational Statistics & Data Analysis. - : Elsevier. - 0167-9473 .- 1872-7352. ; 161
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Tidskriftsartikel (refereegranskat)abstract
- First-order separability of a spatio-temporal point process plays a fundamental role in theanalysis of spatio-temporal point pattern data. While it is often a convenient assumptionthat simplifies the analysis greatly, existing non-separable structures should be accountedfor in the model construction. Three different tests are proposed to investigate thishypothesis as a step of preliminary data analysis. The first two tests are exact orasymptotically exact for Poisson processes. The first test based on permutations and globalenvelopes allows one to detect at which spatial and temporal locations or lags the datadeviate from the null hypothesis. The second test is a simple and computationally cheapχ2-test. The third test is based on stochastic reconstruction method and can be generallyapplied for non-Poisson processes. The performance of the first two tests is studied in asimulation study for Poisson and non-Poisson models. The third test is applied to the realdata of the UK 2001 epidemic foot and mouth disease.
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| 2. |
- Gorjian, Shiva, et al.
(författare)
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Technological advancements and research prospects of innovative concentrating agrivoltaics
- 2023
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Ingår i: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 337
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Tidskriftsartikel (refereegranskat)abstract
- Agrivoltaic is a strategic and innovative approach that combines photovoltaic (PV) energy conversion with agricultural production, enabling synergies in the production of food, energy, and water, as well as the preservation of the ecological landscape. Shading management, intensity adjustment, and spectral distribution allow innovative PV systems to generate significant amounts of electricity without affecting agricultural production. Demonstration projects have already been developed around the world and there is a wealth of experience with various design solutions for commercial use. One of these new technologies is concentrator photovoltaics (CPV). The CPV has excellent spectral processing capabilities and highly concentrated power generation efficiency, which makes it a perfect solution for integrating with photosynthesis. This study aims to present the working principle of CPV modules considering agricultural applications and discuss the recent advancements in concentrating agrivoltaics. In this method, the problem of shading is mitigated by two main strategies: (i) parabolic glasses covered with a multilayer dichroic polymer film that reflects near-infrared (NIR) radiation onto the solar cells installed at the focal area and transmits photons in the range of photosynthetically active radiation (PAR), and (ii) highly transparent sun-tracking louvers or Fresnel lenses that concentrate direct sunlight onto the solar cells to generate electricity. In the latter solution, the remaining diffuse sunlight is directed to the ground for use by growing plants. Although the CPV development trend has been slow due to the lower cost of crystalline silicon, the development of CPV for agriculture with accurate spectral separation could revitalize this industry. In this regard, more research and development are needed to evaluate the suitability of materials that split solar radiation and their impacts on the electrical performance of CPV modules, taking into account the physiology of plants.
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| 3. |
- Vafaei, Nafiseh, et al.
(författare)
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Spatio-temporal determinantal point processes
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Determinantal point processes are models for regular spatial point patterns, with appealingprobabilistic properties. We present their spatio-temporal counterparts and give examples ofthese models, based on spatio-temporal covariance functions which are separable and non-separablein space and time.
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| 4. |
- Vafaei, Nafiseh, et al.
(författare)
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Spatio-temporal determinantal point processes and a kernel-based test for first-order separability
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Determinant point processes (DPPs) are models for regular spatial point patterns. They have densities in a closed form, moment expressions can be easily evaluated for them and realizations from these models can be quickly simulated. In this study, we propose spatio-temporal counterparts of the spatial dpps. We present spatio-temporal DPPs and their statistical properties and give examples of these models considering spatio-temporal covariance functions which are separable and non-separable in space and time. We then propose a novel statistical test for the first-order separability of the spatio-temporal DPPs using a machine learning technique called Hilbert-Schmidt independent criterion, which uses the kernel trick for feasibility. Based on our simulation study, the empirical level of the test is close to the nominal level or a bit conservative,
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