A low-cost collaborative location scheme with GNSS and RFID for the Internet of Things

The emergence and development of the Internet of Things (IoT) has attracted growing attention to low-cost location systems when facing the dramatically increased number of public infrastructure assets in smart cities. Various radio frequency identification (RFID)-based locating systems have been developed. However, most of them are impractical for infrastructure asset inspection and management on a large scale due to their high cost, inefficient deployment, and complex environments such as emergencies or high-rise buildings. In this paper, we proposed a novel locating system by combing the Global Navigation Satellite System (GNSS) with RFID, in which a target tag was located with one RFID reader and one GNSS receiver with sufficient accuracy for infrastructure asset management. To overcome the cost challenge, one mobile RFID reader-mounted GNSS receiver is used to simulate multiple location known reference tags. A vast number of reference tags are necessary for current RFID-based locating systems, which means higher cost. To achieve fine-grained location accuracy, we utilize a distance-based power law weight algorithm to estimate the exact coordinates. Our experiment demonstrates the effectiveness and advantages of the proposed scheme with sufficient accuracy, low cost and easy deployment on a large scale. The proposed scheme has potential applications for location-based services in smart cities

Molecular Composition of Oxygenated Organic Molecules and Their Contributions to Organic Aerosol in Beijing

The understanding at a molecular level of ambient secondary organic aerosol (SOA) formation is hampered by poorly constrained formation mechanisms and insufficient analytical methods. Especially in developing countries, SOA related haze is a great concern due to its significant effects on climate and human health. We present simultaneous measurements of gas-phase volatile organic compounds (VOCs), oxygenated organic molecules (OOMs), and particle-phase SOA in Beijing. We show that condensation of the measured OOMs explains 26-39% of the organic aerosol mass growth, with the contribution of OOMs to SOA enhanced during severe haze episodes. Our novel results provide a quantitative molecular connection from anthropogenic emissions to condensable organic oxidation product vapors, their concentration in particle-phase SOA, and ultimately to haze formation.Peer reviewe

Climate change : strategies for mitigation and adaptation

The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change

Association between actual weight status, perceived weight and depressive, anxious symptoms in Chinese adolescents: a cross-sectional study

<p>Abstract</p> <p>Backgroud</p> <p>The purpose of this study was to describe actual measured weight and perceived weight and to explore associations with depressive, anxiety symptoms in school adolescents in China.</p> <p>Methods</p> <p>A sample of 1144 Chinese adolescents was randomly selected from four schools in Wuhan, China, including 665 boys and 479 girls with ages ranging between 10 and 17 years. Actual measured weight and height and perceived weight status were compared to anxiety and depressive symptoms measured using the revised Self-Rating Anxiety Scale and Children's Depression Inventory. A general linear model was used to compare differences in psychological symptoms among the teenagers with different measured and perceived weights.</p> <p>Results</p> <p>When compared with standardized weight tables (WHO age- and gender-specific body mass index (BMI) cutoffs (2007 reference)), girls were more likely to misperceive themselves as overweight, whereas more boys misclassified their weight status as underweight. The adolescents who perceived themselves as overweight were more likely to experience depressive and anxiety symptoms (except girls) than those who perceived themselves as normal and/or underweight. However, no significant association was found between depressive and anxiety symptoms actual measured weight status.</p> <p>Conclusions</p> <p>Perceived weight status, but not the actual weight status, was associated with psychological symptoms.</p

Brazilian cave heritage under siege

info:eu-repo/semantics/publishe

A Low-cost RFID/GPS Location Sensing Algorithm for Urban Infrastructure

Low-cost Radio Frequency Identification (RFID) location sensing algorithm is practical and crucial for urban infrastructure location. Current RFID location algorithms are based on fixed multiple RFID reader or reference points (reader or tag) with known position, which is cost and difficult to deployment in urban environment. The objective of this study is to develop a low-cost location sensing algorithm using RFID technique to locate urban infrastructure. This paper presents an algorithm based on multilateration with the integration of mobile RFID and Global Position System (GPS). The mobility of RFID reader can measure many distances between different RFID reader positions and target tag which represent multilateration. The GPS provides coordination of RFID reader. The location of tag is calculated based on triangle geometric property. The redundant observation is adopted to get the optimum location. In practice, the only one RFID reader is necessary, thus the cost is reduced hardly. The performance and accuracy assessment are conducted in field experiment. The experiment proves that the proposed low-cost location sensing algorithm is able to location the urban infrastructure with smaller position error. The lower cost makes it even more economically feasible than other algorithm

Surface Heterogeneity-Involved Estimation of Sample Size for Accuracy Assessment of Land Cover Product from Satellite Imagery

Sample size estimation is a key issue for validating land cover products derived from satellite images. Based on the fact that present sample size estimation methods account for the characteristics of the Earth&rsquo;s subsurface, this study developed a model for estimating sample size by considering the scale effect and surface heterogeneity. First, we introduced a watershed with different areas to indicate the scale effect on the sample size. Then, by employing an all-subsets regression feature selection method, three landscape indicators describing the aggregation and diversity of the land cover patches were selected (from 14 indicators) as the main factors for indicating the surface heterogeneity. Finally, we developed a multi-level linear model for sample size estimation using explanatory variables, including the estimated sample size (n) calculated from the traditional statistical model, size of the test region, and three landscape indicators. As reference data for developing this model, we employed a case study in the Jiangxi Province using a 30 m spatial resolution global land cover product (Globeland30) from 2010 as a classified map, and national 30 m land use/cover change (LUCC) data from 2010 in China. The results showed that the adjusted square coefficient of R2 is 0.79, indicating that the joint explanatory ability of all predictive variables in the model to the sample size is 79%. This means that the predictability of this model is at a good level. By comparing the sample size NS obtained by the developed multi-level linear model and n as calculated from the statistics model, we find that NS is much smaller than n, which mainly contributes to the concerns regarding surface heterogeneity in this study. The validity of the established model is tested and is proven as effective in the Anhui Province. This indicates that the estimated sample size from considering the scale effect and spatial heterogeneity in this study achieved the same accuracy as that calculated from a probability statistical model, while simultaneously saving more time, labour, and money in the accuracy assessment of a land cover dataset