Epidemiologists and ecologists often collect data in the field and, on returning to their laboratory, enter their data into a database for further analysis. The recent introduction of mobile phones ...that utilise the open source Android operating system, and which include (among other features) both GPS and Google Maps, provide new opportunities for developing mobile phone applications, which in conjunction with web applications, allow two-way communication between field workers and their project databases.
Here we describe a generic framework, consisting of mobile phone software, EpiCollect, and a web application located within www.spatialepidemiology.net. Data collected by multiple field workers can be submitted by phone, together with GPS data, to a common web database and can be displayed and analysed, along with previously collected data, using Google Maps (or Google Earth). Similarly, data from the web database can be requested and displayed on the mobile phone, again using Google Maps. Data filtering options allow the display of data submitted by the individual field workers or, for example, those data within certain values of a measured variable or a time period.
Data collection frameworks utilising mobile phones with data submission to and from central databases are widely applicable and can give a field worker similar display and analysis tools on their mobile phone that they would have if viewing the data in their laboratory via the web. We demonstrate their utility for epidemiological data collection and display, and briefly discuss their application in ecological and community data collection. Furthermore, such frameworks offer great potential for recruiting 'citizen scientists' to contribute data easily to central databases through their mobile phone.
Fast-paced mobile technology development has permitted augmented reality experiences to be delivered on mobile pedestrian navigation context. The fact that the more prevalent of this technology ...commonly will substituting the digital map visualization to present the geo-location information is still debatable. This paper comprises a report on a field study comparing about user experience when interacting with different modes of mobile electronic assistance in the context of pedestrian navigation interfaces which utilize location-based augmented reality (AR) and two-dimensional digital map to visualize the points of interest (POIs) location in the vicinity of the user. The study was conducted with two subsequent experiments in the Zhongli District, Taoyuan City, Taiwan. The study involved 10 participants aged between 22 and 28 years with different experiences in using smartphones and navigation systems. Navigation performance was measured based on a usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction in real outdoor conditions. The evaluation findings have been cross-checked with the user’s personal comments. We aim at eliciting knowledge about user requirements related to mobile pedestrian interfaces and evaluating user experience from pragmatic and hedonic viewpoints. Results show that in the context of pedestrian navigation, digital map interfaces lead to significantly better navigation performance in pragmatic attributes in comparison to AR interfaces. Nevertheless, the study also reveals that location-based AR is more valued by participants in hedonic qualities and overall performance.
•Three-dimensional digital map is used to characterize the complex pedestrian network in Hong Kong.•Influences of connectivity of pedestrian network and accessibility of grade-separated crossings on ...pedestrian safety are investigated.•Multivariate Poisson lognormal regression approach is applied to account for correlation between counts.•Crosswalks, footbridges, and underpasses can advocate pedestrian safety.•More connected and integrated pedestrian network can worsen pedestrian safety.
Hong Kong is a compact city with high activity and travel intensity. In the past decades, many footbridges and underpasses were installed to reduce the pedestrian-vehicle conflicts on urban roads. However, it is rare that the effects of configuration of pedestrian network on pedestrian crashes are investigated. In Hong Kong, many footbridges and underpasses are connected to major transport hubs and commercial building development and become parts of giant elevated and underground walkway systems. It is challenging to characterize such a complicated pedestrian network. In this study, a three-dimensional digital map is applied to estimate the connectivity and accessibility of pedestrian network, and measure the relationship between pedestrian network characteristics and pedestrian safety at the macroscopic level. Hence, the effects of footbridge and underpass on pedestrian safety are examined. For example, comprehensive built environment, pedestrian network, traffic, and crash data are aggregated to 379 grids (0.5 km × 0.5 km). Then, multivariate Poisson lognormal regression approach is applied to model fatal and severe injury (FSI) and slight injury pedestrian crashes, with which the effects of unobserved heterogeneity, spatial correlation, and correlation between crash counts are accounted. Results indicate that population density, traffic volume, walking trip, footpath density, node density, number of vertices per footpath segment, bus stop, metro exit, residential area, commercial area, and government and utility area are positively associated with pedestrian crashes. In contrast, average gradient, accessibility of footbridge, accessibility of underpass, and number of crossings per road segment are negatively associated with pedestrian crashes. In other word, pedestrian safety would be improved when footbridge and underpass are more accessible. Findings have implications for the design and planning of pedestrian network to promote walkability and improve pedestrian safety.
There is limited evidence on labour exploitation's impact on migrant health. This population is, however, often employed in manual low-skilled jobs known for poor labour conditions and exploitation ...risks. The lack of a common conceptualisation of labour exploitation in health research impedes the development of research measuring its effects on migrant health and, ultimately, our understanding of migrants' health needs. To develop an operational conceptual framework of labour exploitation focusing on migrant workers in manual low-skilled jobs. Non-probabilistic sampling was used to recruit multidisciplinary experts on labour exploitation. An online Group Concept Mapping (GCM) was conducted. Experts: 1) generated statements describing the concept 'labour exploitation' focusing on migrants working in manual low-skilled jobs; 2) sorted generated statements into groups reflecting common themes; and 3) rated them according to their importance in characterising a situation as migrant labour exploitation. Multidimensional Scaling and Cluster Analysis were used to produce an operational framework detailing the concept content (dimensions, statements, and corresponding averaged rating). Thirty-two experts sorted and rated 96 statements according to their relative importance (1 "relatively unimportant" to 5 "extremely important"). The operational framework consists of four key dimensions of migrant labour exploitation, distributed along a continuum of severity revealed by the rating: 'Shelter and personal security' (rating: 4.47); 'Finance and migration' (4.15); 'Health and safety' (3.96); and 'Social and legal protection' (3.71). This study is the first to both generate an empirical operational framework of migrant labour exploitation, and demonstrate the existence of a "continuum from decent work to forced labour". The framework content can be operationalised to measure labour exploitation. It paves the way to better understand how different levels of exploitation affect migrant workers' health for global policymakers, health researchers, and professionals working in the field of migrant exploitation.
We identified 2 genes, histone deacetylase 1 (HDAC1) and HDAC2, contributing to the pathogenesis of proteinuric kidney diseases, the leading cause of end-stage kidney disease. mRNA expression ...profiling from proteinuric mouse glomeruli was linked to Connectivity Map databases, identifying HDAC1 and HDAC2 with the differentially expressed gene set reversible by HDAC inhibitors. In numerous progressive glomerular disease models, treatment with valproic acid (a class I HDAC inhibitor) or SAHA (a pan-HDAC inhibitor) mitigated the degree of proteinuria and glomerulosclerosis, leading to a striking increase in survival. Podocyte HDAC1 and HDAC2 activities were increased in mice podocytopathy models, and podocyte-associated Hdac1 and Hdac2 genetic ablation improved proteinuria and glomerulosclerosis. Podocyte early growth response 1 (EGR1) was increased in proteinuric patients and mice in an HDAC1- and HDAC2-dependent manner. Loss of EGR1 in mice reduced proteinuria and glomerulosclerosis. Longitudinal analysis of the multicenter Veterans Aging Cohort Study demonstrated a 30% reduction in mean annual loss of estimated glomerular filtration rate, and this effect was more pronounced in proteinuric patients receiving valproic acid. These results strongly suggest that inhibition of HDAC1 and HDAC2 activities may suppress the progression of human proteinuric kidney diseases through the regulation of EGR1.
This paper focuses on the pedestrian navigation in highly urbanized area, where a current smartphone and a commercial global navigation satellite system (GNSS) receiver perform poorly because of the ...reflection and blockage of GNSS signal by buildings and foliage. A 3-D map-aided pedestrian positioning method is previously developed to mitigate and correct the multipath GNSS signal. However, it still suffers from the low availability due to the insufficient number of satellites. We develop a smartphone-based pedestrian dead reckoning (PDR) algorithm, which is carried in the pedestrian's trousers. This PDR is capable of not only providing continues solutions but also indicating the pedestrian motions. A closedloop Kalman filter with adaptive tuning is proposed to integrate the 3-D map-aided GNSS method with the smartphone-based PDR system. According to the experiment results, the proposed integration system can achieve ~1.5and 5.5-m of positioning errors in a middle-class and deep urban canyon, respectively.
Network function virtualization (NFV) technology deploys network functions as software functions on a generalised hardware platform and provides customised network services in the form of service ...function chain (SFC), which improves the flexibility and scalability of network services and reduces network service costs. However, irrational resource allocation during service function chain mapping will cause problems such as low resource utilisation, long service request processing time and low mapping rate. To address the unreasonable problem of service mapping resource allocation, an improved service function chain mapping resource allocation method (SA3C) based on the Asynchronous advantageous action evaluation algorithm (A3C) is proposed. This study proposes an SFC mapping model and a mathematical model for joint allocation, which modeled the minimization of processing time as a Markov process. The main network was trained and multiple sub‐networks were generated in parallel using the ternary and deep reinforcement learning algorithm A3C, with the goal of identifying the optimal resource allocation strategy. The experimental simulation results show that compared with the Actor‐Critic (AC) and Policy Gradient (PG) methods, SA3C algorithm can improve the resource utilisation by 9.85%, reduce the total processing time by 10.72%, and improve the mapping rate by 6.72%, by reasonably allocating node computational resources and link bandwidth communication resources.
To address the unreasonable problem of service mapping resource allocation, this paper proposes an improved service function chain mapping resource allocation method (SA3C) based on the asynchronous advantageous action evaluation algorithm (A3C) for finding the optimal resource allocation strategy. The experimental simulation results show that the proposed method can effectively improve resource utilisation and mapping rate.
The 3D city model is one of the crucial topics that are still under analysis by many engineers and programmers because of the great advancements in data acquisition technologies and 3D computer ...graphics programming. It is one of the best visualization methods for representing reality. This paper presents different techniques for the creation and spatial analysis of 3D city modeling based on Geographical Information System (GIS) technology using free data sources. To achieve that goal, the Mansoura University campus, located in Mansoura city, Egypt, was chosen as a case study. The minimum data requirements to generate a 3D city model are the terrain, 2D spatial features such as buildings, landscape area and street networks. Moreover, building height is an important attribute in the 3D extrusion process. The main challenge during the creation process is the dearth of accurate free datasets, and the time-consuming editing. Therefore, different data sources are used in this study to evaluate their accuracy and find suitable applications which can use the generated 3D model. Meanwhile, an accurate data source obtained using the traditional survey methods is used for the validation purpose. First, the terrain was obtained from a digital elevation model (DEM) and compared with grid leveling measurements. Second, 2D data were obtained from: the manual digitization from (30 cm) high-resolution imagery, and deep learning structure algorithms to detect the 2D features automatically using an object instance segmentation model and compared the results with the total station survey observations. Different techniques are used to investigate and evaluate the accuracy of these data sources. The procedural modeling technique is applied to generate the 3D city model. TensorFlow & Keras frameworks (Python APIs) were used in this paper; moreover, global mapper, ArcGIS Pro, QGIS and CityEngine software were used. The precision metrics from the trained deep learning model were 0.78 for buildings, 0.62 for streets and 0.89 for landscape areas. Despite, the manual digitizing results are better than the results from deep learning, but the extracted features accuracy is accepted and can be used in the creation process in the cases not require a highly accurate 3D model. The flood impact scenario is simulated as an application of spatial analysis on the generated 3D city model. Doi: 10.28991/CEJ-2022-08-01-08 Full Text: PDF
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