scholarly journals Examining the Limits of Predictability of Human Mobility

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 432 ◽  
Author(s):  
Vaibhav Kulkarni ◽  
Abhijit Mahalunkar ◽  
Benoit Garbinato ◽  
John Kelleher
Keyword(s):  
Long Range ◽  
Upper Bound ◽  
Prediction Models ◽  
Statistical Tests ◽  
Human Mobility ◽  
Network Architectures ◽  
Systematic Bias ◽  
Scale Invariant ◽  
Long Distance ◽  
Shed Light

We challenge the upper bound of human-mobility predictability that is widely used to corroborate the accuracy of mobility prediction models. We observe that extensions of recurrent-neural network architectures achieve significantly higher prediction accuracy, surpassing this upper bound. Given this discrepancy, the central objective of our work is to show that the methodology behind the estimation of the predictability upper bound is erroneous and identify the reasons behind this discrepancy. In order to explain this anomaly, we shed light on several underlying assumptions that have contributed to this bias. In particular, we highlight the consequences of the assumed Markovian nature of human-mobility on deriving this upper bound on maximum mobility predictability. By using several statistical tests on three real-world mobility datasets, we show that human mobility exhibits scale-invariant long-distance dependencies, contrasting with the initial Markovian assumption. We show that this assumption of exponential decay of information in mobility trajectories, coupled with the inadequate usage of encoding techniques results in entropy inflation, consequently lowering the upper bound on predictability. We highlight that the current upper bound computation methodology based on Fano’s inequality tends to overlook the presence of long-range structural correlations inherent to mobility behaviors and we demonstrate its significance using an alternate encoding scheme. We further show the manifestation of not accounting for these dependencies by probing the mutual information decay in mobility trajectories. We expose the systematic bias that culminates into an inaccurate upper bound and further explain as to why the recurrent-neural architectures, designed to handle long-range structural correlations, surpass this upper limit on human mobility predictability.

scholarly journals Modelling cholera epidemics: the role of waterways, human mobility and sanitation

2011 ◽  
Vol 9 (67) ◽  
pp. 376-388 ◽  
Author(s):  
L. Mari ◽  
E. Bertuzzo ◽  
L. Righetto ◽  
R. Casagrandi ◽  
M. Gatto ◽  
...  
Keyword(s):  
Long Range ◽  
Large Scale ◽  
Human Mobility ◽  
Human Movement ◽  
Epidemiological Data ◽  
Long Distance ◽  
Regional Patterns ◽  
Spatially Explicit Model ◽  
Kwazulu Natal

We investigate the role of human mobility as a driver for long-range spreading of cholera infections, which primarily propagate through hydrologically controlled ecological corridors. Our aim is to build a spatially explicit model of a disease epidemic, which is relevant to both social and scientific issues. We present a two-layer network model that accounts for the interplay between epidemiological dynamics, hydrological transport and long-distance dissemination of the pathogen Vibrio cholerae owing to host movement, described here by means of a gravity-model approach. We test our model against epidemiological data recorded during the extensive cholera outbreak occurred in the KwaZulu-Natal province of South Africa during 2000–2001. We show that long-range human movement is fundamental in quantifying otherwise unexplained inter-catchment transport of V. cholerae , thus playing a key role in the formation of regional patterns of cholera epidemics. We also show quantitatively how heterogeneously distributed drinking water supplies and sanitation conditions may affect large-scale cholera transmission, and analyse the effects of different sanitation policies.

scholarly journals A Long-Distance Communication Architecture for Medical Devices Based on LoRaWAN Protocol

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 940
Author(s):  
Nicoleta Cristina Gaitan
Keyword(s):  
Energy Consumption ◽  
Long Range ◽  
Medical Devices ◽  
Low Energy ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
Communication Architecture ◽  
Low Energy Consumption ◽  
Distance Communication

Recent market studies show that the market for remote monitoring devices of different medical parameters will grow exponentially. Globally, more than 4 million individuals will be monitored remotely from the perspective of different health parameters by 2023. Of particular importance is the way of remote transmission of the information acquired from the medical sensors. At this time, there are several methods such as Bluetooth, WI-FI, or other wireless communication interfaces. Recently, the communication based on LoRa (Long Range) technology has had an explosive development that allows the transmission of information over long distances with low energy consumption. The implementation of the IoT (Internet of Things) applications using LoRa devices based on open Long Range Wide-Area Network (LoRaWAN) protocol for long distances with low energy consumption can also be used in the medical field. Therefore, in this paper, we proposed and developed a long-distance communication architecture for medical devices based on the LoRaWAN protocol that allows data communications over a distance of more than 10 km.

Comparison between photoplethysmographic heart rate monitor from Polar Vantage M and Polar V800 with H10 chest strap while running on a treadmill: Validation of the Polar Precision PrimeTM photoplestimographic system

2020 ◽  
pp. 175433712097665
Author(s):  
Emilio J Ruiz-Malagón ◽  
Santiago A Ruiz-Alias ◽  
Felipe García-Pinillos ◽  
Gabriel Delgado-García ◽  
Victor M Soto-Hermoso
Keyword(s):  
Heart Rate ◽  
Random Error ◽  
Maximum Speed ◽  
Systematic Bias ◽  
Long Distance ◽  
Time Intervals ◽  
Heart Rate Monitor ◽  
Calibration Time

Chest bands have been the most used device to monitor heart rate during running. However, some runners feel uncomfortable with the use of bands due to the friction and pressure exerted on the chest. Thus, the aim of this study was to determine if the photoplethysmography (PPG) system Polar Precision Prime used in the Polar Vantage M watch could replace chest bands (Polar V800-H10) to monitor heart rate with the same precision. A group of 37 people, middle-distance and long-distance professional runners, participated in this study. The submaximal speed was determined using 50% of the participants’ maximum speed in the height of their season. The Polar Vantage M reported high correlation ( r > 0.84) and high ICC (ICC > 0.86) when comparing its heart rate monitor with the Polar V800 synchronised with H10 chest strap during recording intervals of more than 2 min. The systematic bias and random error were very small (<1 bpm), especially for the 600 s recording interval (0.26 ± 5.10 bpm). Nevertheless, the error increased for 10 s (−5.13 ± 9.20 bpm), 20 s (−8.65 ± 12.60 bpm) and 30 s (−10.71 ± 14.99 bpm) time intervals. In conclusion, the PPG Polar Precision Prime included in the Polar Vantage M demonstrates that it could be a valid alternative to chest bands for monitoring heart rate while running, taking into account some usage considerations, good strap adjustment and an initial calibration time during the first 2–3 min.

scholarly journals Establishing the Middle Sea: The Late Bronze Age of Mediterranean Europe (1700–900 BC)

2021 ◽  
Author(s):  
Francesco Iacono ◽  
Elisabetta Borgna ◽  
Maurizio Cattani ◽  
Claudio Cavazzuti ◽  
Helen Dawson ◽  
...  
Keyword(s):  
Social Organization ◽  
Bronze Age ◽  
Long Range ◽  
Human Mobility ◽  
Late Bronze Age ◽  
Archaeological Record ◽  
Mediterranean Europe ◽  
Northern Shore ◽  
Comparative Survey ◽  
The Bronze Age

AbstractThe Late Bronze Age (1700–900 BC) represents an extremely dynamic period for Mediterranean Europe. Here, we provide a comparative survey of the archaeological record of over half a millennium within the entire northern littoral of the Mediterranean, from Greece to Iberia, incorporating archaeological, archaeometric, and bioarchaeological evidence. The picture that emerges, while certainly fragmented and not displaying a unique trajectory, reveals a number of broad trends in aspects as different as social organization, trade, transcultural phenomena, and human mobility. The contribution of such trends to the processes that caused the end of the Bronze Age is also examined. Taken together, they illustrate how networks of interaction, ranging from the short to the long range, became a defining aspect of the “Middle Sea” during this time, influencing the lives of the communities that inhabited its northern shore. They also highlight the importance of research that crosses modern boundaries for gaining a better understanding of broad comparable dynamics.

Experimental study on the factors affecting squeak noise occurrence in automotive suspension bushings

2021 ◽  
pp. 095440702110241
Author(s):  
Byunghyun Kang ◽  
Cheol Choi ◽  
Daeun Sung ◽  
Seongho Yoon ◽  
Byoung-Ho Choi
Keyword(s):  
Neural Network ◽  
Logistic Regression ◽  
Influencing Factors ◽  
Frictional Force ◽  
Prediction Models ◽  
Statistical Tests ◽  
Network Models ◽  
Multiple Logistic Regression ◽  
Neural Network Models ◽  
Automotive Suspension

In this study, friction tests are performed, via a custom-built friction tester, on specimens of natural rubber used in automotive suspension bushings. By analyzing the problematic suspension bushings, the eleven candidate factors that influence squeak noise are selected: surface lubrication, hardness, vulcanization condition, surface texture, additive content, sample thickness, thermal aging, temperature, surface moisture, friction speed, and normal force. Through friction tests, the changes are investigated in frictional force and squeak noise occurrence according to various levels of the influencing factors. The degree of correlation between frictional force and squeak noise occurrence with the factors is determined through statistical tests, and the relationship between frictional force and squeak noise occurrence based on the test results is discussed. Squeak noise prediction models are constructed by considering the interactions among the influencing factors through both multiple logistic regression and neural network analysis. The accuracies of the two prediction models are evaluated by comparing predicted and measured results. The accuracies of the multiple logistic regression and neural network models in predicting the occurrence of squeak noise are 88.2% and 87.2%, respectively.

scholarly journals Power-law bounds for critical long-range percolation below the upper-critical dimension

2021 ◽  
Author(s):  
Tom Hutchcroft
Keyword(s):  
Long Range ◽  
Power Law ◽  
Upper Bound ◽  
Mean Field ◽  
Maximum Size ◽  
Finite Graph ◽  
Critical Dimension ◽  
Point Function ◽  
Upper Critical Dimension ◽  
Infinite Cluster

AbstractWe study long-range Bernoulli percolation on $${\mathbb {Z}}^d$$ Z d in which each two vertices x and y are connected by an edge with probability $$1-\exp (-\beta \Vert x-y\Vert ^{-d-\alpha })$$ 1 - exp ( - β ‖ x - y ‖ - d - α ) . It is a theorem of Noam Berger (Commun. Math. Phys., 2002) that if $$0<\alpha <d$$ 0 < α < d then there is no infinite cluster at the critical parameter $$\beta _c$$ β c . We give a new, quantitative proof of this theorem establishing the power-law upper bound $$\begin{aligned} {\mathbf {P}}_{\beta _c}\bigl (|K|\ge n\bigr ) \le C n^{-(d-\alpha )/(2d+\alpha )} \end{aligned}$$ P β c ( | K | ≥ n ) ≤ C n - ( d - α ) / ( 2 d + α ) for every $$n\ge 1$$ n ≥ 1 , where K is the cluster of the origin. We believe that this is the first rigorous power-law upper bound for a Bernoulli percolation model that is neither planar nor expected to exhibit mean-field critical behaviour. As part of the proof, we establish a universal inequality implying that the maximum size of a cluster in percolation on any finite graph is of the same order as its mean with high probability. We apply this inequality to derive a new rigorous hyperscaling inequality $$(2-\eta )(\delta +1)\le d(\delta -1)$$ ( 2 - η ) ( δ + 1 ) ≤ d ( δ - 1 ) relating the cluster-volume exponent $$\delta $$ δ and two-point function exponent $$\eta $$ η .

scholarly journals Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Prediction Models ◽  
Long Distance ◽  
Chromatin Looping ◽  
Gene Regulatory ◽  
The Impact

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.

Field Study of Low-Energy Long-Distance Wireless Communication for IoT Application in Remote Areas

Mekatronika ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 52-62
Author(s):  
Kwai Yang Sak ◽  
Ahmad Najmuddin Ibrahim
Keyword(s):  
Radio Frequency ◽  
Long Range ◽  
Essential Element ◽  
Low Energy ◽  
Line Of Sight ◽  
Area Network ◽  
Structural Elements ◽  
Wide Area Network ◽  
Residential Areas ◽  
Long Distance

Long Range (LoRa) is a wireless radio frequency technology under the Low Power Wide Area Network (LPWAN). LoRa is able to communicate long range and low energy consumption. The communication range has become an essential element in the wireless radio frequency technology in the Internet of Things (IoT). The presence of LoRa is able IoT application performs in long communication distances with high noise sensitivity ability. People can operate, monitor, and do a variety of tasks from a remote distance. Therefore, this research aims to evaluate the performance of the LoRa connection between radio transceivers in remote locations. The different environment and structural elements affect the LoRa performance. This thesis will be supported by the experiment that LoRa communication in different environments and tests. This experiment tests in line of sight (LOS) and non-line of sight (NLOS). Two sets of LoRa parameters, including Spreading Factor (SF), Bandwidth, and coding rate, are tested in different environments. The experiment tests the LoRa performance in various aspects: received signal strength indicator (RSSI) and packet received ratio (PPR) at different coverage ranges. In addition, the LoRa performance is evaluated in university, residential areas and vegetation areas under similar temperature, weather, and time. The LoRa coverage distance in the vegetation area and university area is reached 900 meters in the LOS test. Still, the vegetation area's signal is more stable and able to receive weaker RSSI signals. The LoRa coverage distance in the NLOS test is shorter compared to the LOS test. NLOS test has only one-third of the LOS LoRa communication distance. It is due to the signal penetration on structural elements such as buildings and woods cause the signal power loss and only transmitting a shorter distance. The LoRa parameter with SF9, 31.25kHz bandwidth and 4/8 coding rate has a better coverage range and stable connection.

scholarly journals Interval Training with Active Recovery and the Physical Capacity of Recreational Male Runners

2018 ◽  
Vol 25 (4) ◽  
pp. 15-20 ◽  
Author(s):  
Kamil Michalik ◽  
Szymon Glinka ◽  
Natalia Danek ◽  
Marek Zatoń
Keyword(s):  
Aerobic Power ◽  
Statistical Tests ◽  
Training Session ◽  
Interval Training ◽  
Physical Capacity ◽  
Control Group ◽  
Active Recovery ◽  
Distance Runners ◽  
Continuous Training ◽  
Long Distance

Abstract Introduction. So far there have been few studies on the effect of interval training with active recovery aimed at increasing aerobic power on the physical capacity of long-distance runners. Unlike standard interval training, this particular type of interval training does not include passive rest periods but combines high-intensity training with low-intensity recovery periods. The aims of the study were to determine the effect of aerobic power training implemented in the form of interval training with active recovery on the physical capacity of amateur long-distance runners as well as to compare their results against those of a group of runners who trained in a traditional manner and only performed continuous training. Material and methods. The study involved 12 recreational male long-distance runners, who were randomly divided into two groups, consisting of 6 persons each. Control group C performed continuous training 3 times a week (for 90 minutes, with approximately 65-85% VO2max). Experimental group E participated in one training session similar to the one implemented in group C and additionally performed interval training with active recovery twice a week. The interval training included a 20-minute warm-up and repeated running sprints of maximum intensity lasting 3 minutes (800-1,000 m). Between sprints, there was a 12-minute bout of running with an intensity of approximately 60-70% VO2max. The time of each repetition was measured, and the first one was treated as a benchmark in a given training unit. If the duration of a subsequent repetition was 5% shorter than that of the initial repetition, the subjects underwent a 15-minute cool-down period. A progressive treadmill test was carried out before and after the 7-week training period. The results were analysed using non-parametric statistical tests. Results. VO2max increased significantly both in group E (p < 0.05; d = 0.86) and C (p < 0.05; d = 0.71), and there was an improvement in effort economy at submaximal intensity. Although the differences were not significant, a much greater change in the post-exercise concentrations of lactate and H+ ions was found in group E. Conclusions. The study showed that interval training with active recovery increased VO2max in amateur runners with higher initial physical capacity and stimulated adaptation to metabolic acidosis more than continuous training.

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