Towards Healthy Aging: Influence of the Built Environment on Elderly Pedestrian Safety at the Micro-Level

As vulnerable road users, elderly pedestrians are more likely to be injured in road crashes due to declining physical and perceptual capabilities. Most previous studies on the influence of the built environment on elderly pedestrian safety focused on intersections or areal units. Using a district of Shanghai as the study area, this research investigated the effects of the built environment at the road segment level with elderly pedestrian collision, taxi tracking point, point of interest, street view image, open street map, land use, housing price, and elderly population datasets. In particular, this research employed both Poisson and geographically weighted Poisson regression (GWPR) models to account for spatial nonstationarity. The Poisson model indicates that green space, sidewalks, and junctions on the roads significantly affected elderly pedestrian safety, and roads around nursing homes, schools, bus stops, metro stations, traditional markets, and supermarkets were hazardous for elderly pedestrians. The results of the GWPR model suggest that the influence of factors varied across the study area. Green space could decrease the risk of elderly pedestrian collisions only in areas without congested environments. Separations need to be installed between roadways and sidewalks to improve elderly road safety.

Soft computing and IoT based solar tracker

<p>The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.</p>

Experiment-Based Synthetic Structural Analysis Combining Digital Image Processing and a Strong Form Meshfree Method

This paper presents an experiment-based synthetic structural analysis method that combines digital image processing (DIP) and the particle difference method (PDM), which is a strong form-based meshfree method. The proposed method uses images to determine the displacement of deformed specimens, interpolates the displacement onto nodes of the PDM model without meshes or grids, and calculates the kinematic variables. Furthermore, the pixel extraction method for the target area and the method of setting the region of interest for expediting DIP were used during the synthetic structural analysis. A method for effectively expanding the number of tracking points and an improved method for labeling tracking points are also presented. To verify the performance of the analysis, the experimental and numerical analysis results of a three-point bending test on a rubber beam were compared in terms of various mechanical variables as well as with the PDM results of a simulated bending test. It was found that tracking point expansion and adjusting the radius of the domain of influence are advantageous for performing an accurate calculation without losing computational efficiency. It was demonstrated that the synthetic structural analysis effectively overcomes the shortcomings of the conventional experiments and the limitations of pure simulations.

Wave Climate Patterns from Spatial Tracking of Global Long-Term Ocean Wave Spectra

Long-term wave spectral statistics can provide a better description of wave climate than integrated wave parameters because several wave climate systems (WCSs) generated by different wind climate systems can coexist at the same location. In this study, global wave climate patterns are presented by spatially tracking point-wise long-term wave spectra (probability density distributions of wave spectral partitions) from a WAVEWATCH III hindcast, providing new insights into global wave climate. Tens of well-defined WCSs, which are generated in different source regions by different wind systems, including prevailing westerlies, polar easterlies, trade winds, and monsoons, were identified. These WCSs are independent of each other because wave systems from different origins travel independently. The spatial distributions of these WCSs can illustrate the entire life cycle of ocean waves, from being generated as dominant wind-seas to becoming less dominant swells in far fields, from a climatic point of view. The mean wave directions in WCS patterns, especially those in westerlies-generated WCSs, are generally in agreement with the great circles on Earth’s surface, which display the propagation routes of ocean swells.

Revisiting Cyclone Detection and Tracking Methods using ECMWF ERA5 dataset for climatological purposes in the Mediterranean Region

&lt;p&gt;The main target of this study is to evaluate the Cyclone Detection and Tracking Methods (CDTM) using the ECMWF ERA5 dataset, state-of-the-art in reanalysis models, to identify the main cyclogenesis zones and cyclone tracks inside the Mediterranean region during a climatological period. Several studies based on ECMWF analysis and reanalysis (ERA40 and ERA Interim) datasets indicate a large divergence related to the average number of cyclones passing through the Mediterranean region by year. However, the majority agrees on the most important cyclogenesis areas, seasonality variation of the number of cyclones, and trends of cyclone track. In general, the differences between those methodologies concerns to the meteorological variable used to detect cyclones and the metric used to define its intensity. Nevertheless, spatial and temporal resolutions were fundamental to achieve the results, since the most advanced dataset used in the literature presented relatively low values &amp;#8203;&amp;#8203;such as 1.125&amp;#176;x1.125&amp;#176; and 6h, respectively. Past studies reported that these values &amp;#8203;&amp;#8203;were already high enough to produce numerical noises. Here, the geopotential height at 1000 hPa (Z1000) was used, with horizontal spatial resolution of 0.25&amp;#176;x0.25&amp;#176; and time resolution of 1h, to identify the local minima for each time step (hereafter, candidates), and filtering those with negative gradients of Z1000 within a radius of 1000 km to exclude candidates associated with thermal lows or geopotential troughs.&lt;br&gt;Following the literature, the domain for Mediterranean region was defined by the area within 9&amp;#176;W to 42&amp;#176;E, and 27&amp;#176;N to 48&amp;#176;N, where were considered only cyclones with at least one tracking point inside the domain. Also, the results were produced for the period 1979-2008 using two types of input data: (Model I) ERA5 data with resolutions reduced to 1.5&amp;#176;x1.5&amp;#176; and 6h, as well as the main previous studies; and (Model II) full-resolution ERA5 data. As expected, Model I results were very similar to those found in the literature in all aspects (number of cyclones, seasonal distribution, areas of cyclogenesis and tracks). On the other hand, since the use of higher resolution data provides greater spatiotemporal detailing of the climatological period, the results of Model II presented a total number of cyclones substantially higher than that of Model I (~25%), but still within the range described in the literature. The models indicated more frequent cyclones during the spring months with maximums in April (Model I) and May (Model II). An interesting point highlighted in other studies but not observed in their results, is an increase in cyclone frequency between August and October, captured in both Models I and II and more evident in Model II. An explanation is found in the greater number of short-life cyclones, which act in relatively narrow areas intangible to datasets with limited resolution.&lt;/p&gt;

On-Line Visual Tracking with Occlusion Handling

One of the core challenges in visual multi-target tracking is occlusion. This is especially important in applications such as video surveillance and sports analytics. While offline batch processing algorithms can utilise future measurements to handle occlusion effectively, online algorithms have to rely on current and past measurements only. As such, it is markedly more challenging to handle occlusion in online applications. To address this problem, we propagate information over time in a way that it generates a sense of déjà vu when similar visual and motion features are observed. To achieve this, we extend the Generalized Labeled Multi-Bernoulli (GLMB) filter, originally designed for tracking point-sized targets, to be used in visual multi-target tracking. The proposed algorithm includes a novel false alarm detection/removal and label recovery methods capable of reliably recovering tracks that are even lost for a substantial period of time. We compare the performance of the proposed method with the state-of-the-art methods in challenging datasets using standard visual tracking metrics. Our comparisons show that the proposed method performs favourably compared to the state-of-the-art methods, particularly in terms of ID switches and fragmentation metrics which signifies occlusion.