Search Results (6)

With the increasing availability of remote sensing images, the regularization of jagged building outlines extracted from high-resolution remote sensing images has become a current research hotspot. Based on an existing method proposed earlier by this author for extracting the skeleton lines of buildings through integrating vector and raster data using jagged building skeleton lines as the input data, a new method is proposed here for regularizing building outlines through combining the skeleton lines with the Minkowski addition algorithm. Since the size and orientation of the structuring elements remain constant in the traditional morphological method, they can easily lead to large changes in the area between the regularized results and area of the original building. In this work, structuring elements are constructed with the adaptive adjustment of size and orientation. The proposed method has an outstanding ability to maintain the area of the original building. The orthogonal characteristics of the building can be better preserved via rotating the structuring elements. Finally, the angular bisector method is used to dissipate conflicts among the redundant vertices in the building outlines. In comparison to the simplification method used in QGIS software, the method proposed in this paper could reduce the variation in the area while maintaining the orthogonal characteristics of the building more significantly. Full article

The latent space item response model (LSIRM) is a newly-developed approach to analyzing and visualizing conditional dependencies in item response data, manifested as the interactions between respondents and items, between respondents, and between items. This paper provides a practical guide to the Bayesian estimation of LSIRM using three open-source software options, JAGS, Stan, and NIMBLE in R. By means of an empirical example, we illustrate LSIRM estimation, providing details on the model specification and implementation, convergence diagnostics, model fit evaluations and interaction map visualizations. Full article

Designing a high-strength node is significant for space structures. Topological optimization can optimally allocate the material distribution of components to meet performance requirements. Although the material distribution after topology optimization is optimum, the structure becomes complicated to manufacture. By using additive manufacturing technology, this problem can be well solved. At present, both topology optimization technology and additive manufacturing technology are quite mature, but their application in the design of spatial nodes is very recent and less researched. This paper involves the study and improvement of the node optimization design–manufacturing integrated method. This study used the BESO optimization algorithm as the research algorithm. Through a reasonable improvement of the material interpolation method, the algorithm’s dependence on the experience of selecting the material penalty index P was reduced. On this basis, the secondary development was carried out, and a multisoftware integration was carried out for optimization and manufacturing. The spatial node was taken as the research object, and the calculation results of the commercial finite element software were compared. The comparison showed that the algorithm used in this paper was better. Not only was it not trapped in a local optimum, but the maximum stress was also lower. In addition, this paper proposed a practical finite element geometric model extraction method and smoothing of the optimized nodes, completing the experiment of the additive manufacturing forming of the nodes. It provides ideas for processing jagged edges brought by the BESO algorithm. This paper verified the feasibility of the multisoftware integration method of optimized manufacturing. Full article

Bayesian MCMC is a widely used model estimation technique, and software from the BUGS family, such as JAGS, have been popular for over two decades. Recently, Stan entered the market with promises of higher efficiency fueled by advanced and more sophisticated algorithms. With this study, we want to contribute empirical results to the discussion about the sampling efficiency of JAGS and Stan. We conducted three simulation studies in which we varied the number of warmup iterations, the prior informativeness, and sample sizes and employed the multi-level intercept-only model in the covariance- and mean-based and in the classic parametrization. The target outcome was MCMC efficiency measured as effective sample size per second (ESS/s). Based on our specific (and limited) study setup, we found that (1) MCMC efficiency is much higher for the covariance- and mean-based parametrization than for the classic parametrization, (2) Stan clearly outperforms JAGS when the covariance- and mean-based parametrization is used, and that (3) JAGS clearly outperforms Stan when the classic parametrization is used. Full article

The cliff coastline of the central region of Asturias (N Spain) is severely affected by terrain instabilities, causing considerable damage to properties and infrastructures every year. In this study, we applied the A-DInSAR technique based on Sentinel-1 imagery to map and monitor active slopes in an emblematic rocky area of the Asturian coast: the Peñas Cape. The A-DInSAR dataset analysis has been focused at regional and local scales. For the local scale assessment, six areas were selected based on previous work and the landslide database of the Principality of Asturias region (BAPA-Base de datos de Argayos del Principado de Asturias), created by the University of Oviedo. The processing of the data has been performed using two independent sets of processing tools: the PSIG software tools, a professional tool and, the GEP service, an unsupervised platform. The dataset consisted of 113 SAR IW-SLC images acquired by the Sentinel-1 A/B satellites between January 2018 and February 2020. LOS mean deformation velocity maps (mm year⁻¹) and deformation time series (mm) were obtained by PSIG and GEP software, allowing coastal areas with landslide incidence and other terrain movements to be distinguished. Deformation motion has been estimated from PSIG VLOS rates to be from −17.1 to 37.4 mm year⁻¹ and GEP VLOS rates from −23.0–38.3 mm year⁻¹. According to deformation time series (mm), the minimum and maximum accumulated displacements are −68.5–78.8 and −48.8–77.0 mm by means of PSIG and GEP, respectively. These ground motions could be associated with coastal instabilities related to marine activity and coastal retreat, both at regional and local study scales. The main contributions of this work are: (1) the demonstration of the potential of A-DInSAR techniques to evaluate coastal instabilities in a coastal retreat context and (2) the comparison of the results provided by the two sets of tools, which allowed the ground motion to be assessed by using an unsupervised approach vs. a contrasted one (robust software). This study increases the knowledge about coastal instabilities and other ground movements along the rocky coast and cliffs of Central Asturias. As a conclusion for the future, we believe that this work highlights the evaluated methods as significant tools to support the management of coastal territories with jagged and rocky coastlines. Full article

Diseases of fruit and foliage caused by fungi and oomycetes are generally controlled by the application of fungicides. The use of decision support systems (DSSs) may assist to optimize fungicide programs to enhance application on the basis of risk associated with disease outbreak. Case-by-case evaluations demonstrated the performance of DSSs for disease control, but an overall assessment of the efficacy of DSSs is lacking. A literature review was conducted to synthesize the results of 67 experiments assessing DSSs. Disease incidence data were obtained from published peer-reviewed field trials comparing untreated controls, calendar-based and DSS-based fungicide programs. Two meta-analysis generic models, a “fixed-effects” vs. a “random-effects” model within the framework of generalized linear models were evaluated to assess the efficacy of DSSs in reducing incidence. All models were fit using both frequentist and Bayesian estimation procedures and the results compared. Model including random effects showed better performance in terms of AIC or DIC and goodness of fit. In general, the frequentist and Bayesian approaches produced similar results. Odds ratio and incidence ratio values showed that calendar-based and DSS-based fungicide programs considerably reduced disease incidence compared to the untreated control. Moreover, calendar-based and DSS-based programs provided similar reductions in disease incidence, further supporting the efficacy of DSSs. Full article