Expanding the Uses of Truck GPS Data in Freight Modeling and Planning Activities

2017 ◽  
Vol 2646 (1) ◽  
pp. 68-76 ◽  
Author(s):  
Pedro Camargo ◽  
Shuyao Hong ◽  
Vladimir Livshits
Keyword(s):  
Open Source ◽  
Low Frequency ◽  
The United States ◽  
Time Of Day ◽  
Gps Data ◽  
Data Sets ◽  
Trajectory Data ◽  
Practical Applications ◽  
Time Stamps ◽  
Commercial Sources

Progress in practical applications of large, passively collected data sets is often hindered by the lack of appropriate analytical tools or the proprietary nature of applicable software. One of the most widely used data sources in the United States is truck GPS data that are commercially available from a few sources nationwide. Although many large GPS data sets are used in the development of tour-based truck models, the development of a fairly general approach to data analysis and processing that can be readily applied to various GPS data sets without need of proprietary software is still of interest. First, this paper presents a set of tools and techniques used to transform low-frequency truck GPS data available from commercial sources into complete trajectories on the network, that is, sequences of links constituting continuous paths traversed by each truck, with corresponding time stamps on each of the nodes. For this exercise, only open-source software was used, and the algorithm implementation was released as an open-source tool under a business-friendly license. Second, use of the truck GPS data was expanded beyond the standard extraction of trip matrices and estimation of tour models. Additional applications include select link analysis, time-of-day analysis, and trajectory data visualization.

scholarly journals RippleNet: A Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection

2020 ◽  
Author(s):  
Espen Hagen ◽  
Anna R. Chambers ◽  
Gaute T. Einevoll ◽  
Klas H. Pettersen ◽  
Rune Enger ◽  
...  
Keyword(s):  
Neural Networks ◽  
Open Source ◽  
Short Term Memory ◽  
Field Potential ◽  
Low Frequency ◽  
Data Sets ◽  
Brain Functions ◽  
Sharp Wave ◽  
Ca1 Region ◽  
Multidisciplinary Study

AbstractHippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. SPW-R detection typically relies on hand-crafted feature extraction, and laborious manual curation is often required. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. The output prediction can be interpreted as the time-varying probability of SPW-R events for the duration of the input. A simple thresholding applied to the output probabilities is found to identify times of events with high precision. The reference implementation of the algorithm, named ‘RippleNet’, is open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.

Improved location filtering using a context-aware approach

2021 ◽  
Vol 13 (1) ◽  
pp. 55-72
Author(s):  
Iuon-Chang Lin ◽  
Chen-Yang Cheng ◽  
Yen-Ting Lin
Keyword(s):  
Online Communities ◽  
Gps Data ◽  
Data Sets ◽  
Context Aware ◽  
Time Stamps ◽  
Data Points ◽  
Gps Trajectories ◽  
Gps Traces ◽  
Gps Trajectory ◽  
Almost All

With the pervasiveness of GPS-enabled devices, a considerable number of GPS traces are accumulating continuously and unobtrusively in online communities. However, almost all current applications directly use raw GPS data, such as coordinates and time stamps, without interpreting these data. Thus far, online communities cannot offer much support to users in terms of recommending geospatial locations. Furthermore, because the data sets involved are large, users cannot browse each GPS trajectory individually. Therefore, users’ GPS trajectories must be mined and then classified as positive or negative. When the number of ratings for a place exceeds a certain threshold, the place is considered suitable for the user. By contrast, when the ratings for a place are mostly negative, this place is considered unsuitable for the user. When a user searches for the best place, the recommender system determines the user’s location (latitude, longitude) and then sends the best-rated destinations and the shortest routes between the user’s location and the destination to the user’s mobile device. Experiments were conducted in this study to determine the requisite similarity for GPS data points, the user’s information, and the best route for the user.

Asian Americans and Pacific Islanders: Employment Issues in the United States

2011 ◽  
Vol 9 (1-2) ◽  
pp. 58-69
Author(s):  
Marlene Kim
Keyword(s):  
United States ◽  
Asian Americans ◽  
The United States ◽  
Current Data ◽  
Pacific Islanders ◽  
Native Hawaiians ◽  
Data Sets ◽  
High Poverty ◽  
Unemployment Rates

Asian Americans and Pacific Islanders (AAPIs) in the United States face problems of discrimination, the glass ceiling, and very high long-term unemployment rates. As a diverse population, although some Asian Americans are more successful than average, others, like those from Southeast Asia and Native Hawaiians and Pacific Islanders (NHPIs), work in low-paying jobs and suffer from high poverty rates, high unemployment rates, and low earnings. Collecting more detailed and additional data from employers, oversampling AAPIs in current data sets, making administrative data available to researchers, providing more resources for research on AAPIs, and enforcing nondiscrimination laws and affirmative action mandates would assist this population.

scholarly journals On Time Scales of Intrinsic Oscillations in the Climate System

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 459
Author(s):  
Anastasios A. Tsonis ◽  
Geli Wang ◽  
Wenxu Lu ◽  
Sergey Kravtsov ◽  
Christopher Essex ◽  
...  
Keyword(s):  
Low Frequency ◽  
Milankovitch Cycles ◽  
Data Sets ◽  
External Forcing ◽  
Natural Oscillations ◽  
Climatic Oscillations ◽  
Slow Feature Analysis ◽  
Limited Length ◽  
Past Data ◽  
Cumulative Evidence

Proxy temperature data records featuring local time series, regional averages from areas all around the globe, as well as global averages, are analyzed using the Slow Feature Analysis (SFA) method. As explained in the paper, SFA is much more effective than the traditional Fourier analysis in identifying slow-varying (low-frequency) signals in data sets of a limited length. We find the existence of a striking gap from ~1000 to about ~20,000 years, which separates intrinsic climatic oscillations with periods ranging from ~ 60 years to ~1000 years, from the longer time-scale periodicities (20,000 yr +) involving external forcing associated with Milankovitch cycles. The absence of natural oscillations with periods within the gap is consistent with cumulative evidence based on past data analyses, as well as with earlier theoretical and modeling studies.

Detection by real-time quaking-induced conversion (RT-QuIC), ELISA, and IHC of chronic wasting disease prion in lymph nodes from Pennsylvania white-tailed deer with specific PRNP genotypes

2021 ◽  
pp. 104063872110214
Author(s):  
Deepanker Tewari ◽  
David Steward ◽  
Melinda Fasnacht ◽  
Julia Livengood
Keyword(s):  
Real Time ◽  
Disease Susceptibility ◽  
Chronic Wasting Disease ◽  
Low Frequency ◽  
The United States ◽  
Detection Methods ◽  
Spongiform Encephalopathy ◽  
Wasting Disease ◽  
Diagnostic Laboratory ◽  
Highly Sensitive

Chronic wasting disease (CWD) is a prion-mediated, transmissible disease of cervids, including deer ( Odocoileus spp.), which is characterized by spongiform encephalopathy and death of the prion-infected animals. Official surveillance in the United States using immunohistochemistry (IHC) and ELISA entails the laborious collection of lymphoid and/or brainstem tissue after death. New, highly sensitive prion detection methods, such as real-time quaking-induced conversion (RT-QuIC), have shown promise in detecting abnormal prions from both antemortem and postmortem specimens. We compared RT-QuIC with ELISA and IHC for CWD detection utilizing deer retropharyngeal lymph node (RLN) tissues in a diagnostic laboratory setting. The RLNs were collected postmortem from hunter-harvested animals. RT-QuIC showed 100% sensitivity and specificity for 50 deer RLN (35 positive by both IHC and ELISA, 15 negative) included in our study. All deer were also genotyped for PRNP polymorphism. Most deer were homozygous at codons 95, 96, 116, and 226 (QQ/GG/AA/QQ genotype, with frequency 0.86), which are the codons implicated in disease susceptibility. Heterozygosity was noticed in Pennsylvania deer, albeit at a very low frequency, for codons 95GS (0.06) and 96QH (0.08), but deer with these genotypes were still found to be CWD prion-infected.

Effect of Changing a Traffic Control Device Color on Driver Behavior and Perception across Different Age Groups

2021 ◽  
pp. 036119812110111
Author(s):  
Hatem Abou-Senna ◽  
Mohamed El-Agroudy ◽  
Mustapha Mouloua ◽  
Essam Radwan
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Driving Simulator ◽  
Age Groups ◽  
The United States ◽  
Time Of Day ◽  
General Purpose ◽  
Traffic Density ◽  
Driving Conditions ◽  
And Performance

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.

scholarly journals The Sampling Distribution of Disease-Associated Alleles

Genetics ◽  
1997 ◽  
Vol 147 (4) ◽  
pp. 1855-1861 ◽  
Author(s):  
Montgomery Slatkin ◽  
Bruce Rannala
Keyword(s):  
Low Frequency ◽  
Null Model ◽  
Sampling Distribution ◽  
Death Process ◽  
Published Data ◽  
Data Sets ◽  
Likelihood Functions ◽  
Alternative Hypotheses ◽  
Size Standard ◽  
Birth Death

Abstract A theory is developed that provides the sampling distribution of low frequency alleles at a single locus under the assumption that each allele is the result of a unique mutation. The numbers of copies of each allele is assumed to follow a linear birth-death process with sampling. If the population is of constant size, standard results from theory of birth-death processes show that the distribution of numbers of copies of each allele is logarithmic and that the joint distribution of numbers of copies of k alleles found in a sample of size n follows the Ewens sampling distribution. If the population from which the sample was obtained was increasing in size, if there are different selective classes of alleles, or if there are differences in penetrance among alleles, the Ewens distribution no longer applies. Likelihood functions for a given set of observations are obtained under different alternative hypotheses. These results are applied to published data from the BRCA1 locus (associated with early onset breast cancer) and the factor VIII locus (associated with hemophilia A) in humans. In both cases, the sampling distribution of alleles allows rejection of the null hypothesis, but relatively small deviations from the null model can account for the data. In particular, roughly the same population growth rate appears consistent with both data sets.

Animal Pain Scales in Public Policy

1990 ◽  
Vol 18 (1_part_1) ◽  
pp. 41-50
Author(s):  
F. Barbara Orlans
Keyword(s):  
Public Policy ◽  
Animal Welfare ◽  
The United States ◽  
Pain Scale ◽  
Laboratory Animals ◽  
Practical Applications ◽  
Animal Pain ◽  
Pain Scales ◽  
History Of ◽  
And Control

Pain scales classify the severity of pain inflicted on laboratory animals from little or none up to severe. A pain scale as part of public policy serves beneficial purposes that promote animal welfare. It can be used to educate people about the two alternatives of refinement and replacement, and the need to reduce animal pain. Furthermore, a pain scale has practical applications: 1) in review procedures for animal welfare concerns; 2) in developing policies on the use of animals in education; and 3) as a basis for collecting national data on animal experimentation, so that meaningful data can be collected on trends in reduction and control in animal pain. So far, only a few countries (including Sweden, the Netherlands, Canada and New Zealand) have adopted pain scales as part of their public policy. Most countries, including the United States, have not yet done so. The history of the development and adoption of pain scales by various countries is described and the case is presented for wider adoption of a pain scale in countries not currently using one.

Origins and Destinations – Social Security Claimant Dynamics

1998 ◽  
Vol 27 (3) ◽  
pp. 351-369 ◽  
Author(s):  
MICHAEL NOBLE ◽  
SIN YI CHEUNG ◽  
GEORGE SMITH
Keyword(s):  
The United States ◽  
Data Sets ◽  
Income Support ◽  
Data Set ◽  
Family Structures ◽  
Highly Educated ◽  
Lone Parents ◽  
Lone Mothers ◽  
Time Period ◽  
Short Time

This article briefly reviews American and British literature on welfare dynamics and examines the concepts of welfare dependency and ‘dependency culture’ with particular reference to lone parents. Using UK benefit data sets, the welfare dynamics of lone mothers are examined to explore the extent to which they inform the debates. Evidence from Housing Benefits data show that even over a relatively short time period, there is significant turnover in the benefits-dependent lone parent population with movement in and out of income support as well as movement into other family structures. Younger lone parents and owner-occupiers tend to leave the data set while older lone parents and council tenants are most likely to stay. Some owner-occupier lone parents may be relatively well off and on income support for a relatively short time between separation and a financial settlement being reached. They may also represent a more highly educated and highly skilled group with easier access to the labour market than renters. Any policy moves paralleling those in the United States to time limit benefit will disproportionately affect older lone parents.

Local seismic attributes

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. A29-A33 ◽  
Author(s):  
Sergey Fomel
Keyword(s):  
Image Registration ◽  
Seismic Signal ◽  
Seismic Attributes ◽  
Data Sets ◽  
Local Similarity ◽  
Seismic Signals ◽  
Practical Applications ◽  
Regularized Inversion ◽  
Signal Characteristics ◽  
Land Survey

Local seismic attributes measure seismic signal characteristics not instantaneously, at each signal point, and not globally, across a data window, but locally in the neighborhood of each point. I define local attributes with the help of regularized inversion and demonstrate their usefulness for measuring local frequencies of seismic signals and local similarity between different data sets. I use shaping regularization for controlling the locality and smoothness of local attributes. A multicomponent-image-registration example from a nine-component land survey illustrates practical applications of local attributes for measuring differences between registered images.

Sign in / Sign up

Export Citation Format

Share Document