feat: Added publications

Gemfile

@@ -16,6 +16,7 @@ group :jekyll_plugins do
   gem "jekyll-feed", "~> 0.12"
   gem "jekyll-seo-tag", "~> 2.6"
   gem 'jekyll-redirect-from'
+  gem 'jekyll-scholar'
 end
 
 # Windows and JRuby does not include zoneinfo files, so bundle the tzinfo-data gem

Gemfile.lock

@@ -3,8 +3,21 @@ GEM
   specs:
     addressable (2.8.6)
       public_suffix (>= 2.0.2, < 6.0)
+    bibtex-ruby (6.1.0)
+      latex-decode (~> 0.0)
+      racc (~> 1.7)
+    citeproc (1.0.10)
+      namae (~> 1.0)
+    citeproc-ruby (1.1.14)
+      citeproc (~> 1.0, >= 1.0.9)
+      csl (~> 1.6)
     colorator (1.1.0)
     concurrent-ruby (1.2.3)
+    csl (1.6.0)
+      namae (~> 1.0)
+      rexml
+    csl-styles (1.0.1.11)
+      csl (~> 1.0)
     em-websocket (0.5.3)
       eventmachine (>= 0.12.9)
       http_parser.rb (~> 0)
@@ -41,6 +54,11 @@ GEM
       jekyll (>= 3.3, < 5.0)
     jekyll-sass-converter (3.0.0)
       sass-embedded (~> 1.54)
+    jekyll-scholar (7.1.3)
+      bibtex-ruby (~> 6.0)
+      citeproc-ruby (~> 1.0)
+      csl-styles (~> 1.0)
+      jekyll (~> 4.0)
     jekyll-seo-tag (2.8.0)
       jekyll (>= 3.8, < 5.0)
     jekyll-watch (2.2.1)
@@ -49,14 +67,18 @@ GEM
       rexml
     kramdown-parser-gfm (1.1.0)
       kramdown (~> 2.0)
+    latex-decode (0.4.0)
     liquid (4.0.4)
     listen (3.8.0)
       rb-fsevent (~> 0.10, >= 0.10.3)
       rb-inotify (~> 0.9, >= 0.9.10)
     mercenary (0.4.0)
+    namae (1.2.0)
+      racc (~> 1.7)
     pathutil (0.16.2)
       forwardable-extended (~> 2.6)
     public_suffix (5.0.4)
+    racc (1.7.3)
     rb-fsevent (0.11.2)
     rb-inotify (0.10.1)
       ffi (~> 1.0)
@@ -94,6 +116,7 @@ DEPENDENCIES
   jekyll (~> 4.3.3)
   jekyll-feed (~> 0.12)
   jekyll-redirect-from
+  jekyll-scholar
   jekyll-seo-tag (~> 2.6)
   tzinfo (>= 1, < 3)
   tzinfo-data

publications.bib → _bibliography/publications.bib

@@ -7,7 +7,7 @@ @Article{bresnehan_cyronak_brewin_etal_csr_2022
   pages    = {104748},
   volume   = {242},
   abstract = {Coastal populations and hazards are escalating simultaneously, leading to an increased importance of coastal ocean observations. Many well-established observational techniques are expensive, require complex technical training, and offer little to no public engagement. Smartfin, an oceanographic sensor–equipped surfboard fin and citizen science program, was designed to alleviate these issues. Smartfins are typically used by surfers and paddlers in surf zone and nearshore regions where they can help fill gaps between other observational assets. Smartfin user groups can provide data-rich time-series in confined regions. Smartfin comprises temperature, motion, and wet/dry sensing, GPS location, and cellular data transmission capabilities for the near-real-time monitoring of coastal physics and environmental parameters. Smartfin's temperature sensor has an accuracy of 0.05 °C relative to a calibrated Sea-Bird temperature sensor. Data products for quantifying ocean physics from the motion sensor and additional sensors for water quality monitoring are in development. Over 300 Smartfins have been distributed around the world and have been in use for up to five years. The technology has been proven to be a useful scientific research tool in the coastal ocean—especially for observing spatiotemporal variability, validating remotely sensed data, and characterizing surface water depth profiles when combined with other tools—and the project has yielded promising results in terms of formal and informal education and community engagement in coastal health issues with broad international reach. In this article, we describe the technology, the citizen science project design, and the results in terms of natural and social science analyses. We also discuss progress toward our outreach, education, and scientific goals.},
-  doi      = {https://doi.org/10.1016/j.csr.2022.104748},
+  doi      = {10.1016/j.csr.2022.104748},
   keywords = {Coastal oceanography, Citizen science, Surfing, Sea surface temperature, Outreach},
   url      = {https://www.sciencedirect.com/science/article/pii/S0278434322001029},
 }
@@ -49,7 +49,6 @@ @inproceedings{ayers_perry_tiwari_et_al_neurips_2021
   year={2021}
 }
 
-% Optional fields: editor, volume/number, series, pages, address, month, organization, publisher, note
 @InProceedings{crutchfield_sutton_ngo_mb12_2021,
   author    = {Christopher L. Crutchfield and Jake Sutton and Anh Ngo and Emmanuel Zadorian and Gabrielle Hourany and Dylan Nelson and Alvin Wang and Fiona McHenry-Crutchfield and Deborah Forster and Shirley C. Strum and Ryan Kastner and Curt Schurgers},
   booktitle = {12th International Conference on Methods and Techniques in Behavioral Research and 6th Seminar on Behavioral Methods},
@@ -63,7 +62,6 @@ @InProceedings{crutchfield_sutton_ngo_mb12_2021
   url       = {https://www.researchgate.net/profile/Andrew-Spink/publication/344557101_Volume_1_of_the_Proceedings_of_the_joint_meeting_of_the_12th_International_Conference_on_Measuring_Behavior_and_the_6th_Seminar_on_Behavioral_Methods_to_be_held_in_Krakow_Poland_October_15-18_2021/links/5f802f22458515b7cf71fa14/Volume-1-of-the-Proceedings-of-the-joint-meeting-of-the-12th-International-Conference-on-Measuring-Behavior-and-the-6th-Seminar-on-Behavioral-Methods-to-be-held-in-Krakow-Poland-October-15-18-2021.pdf#page=38},
 }
 
-% Optional fields: editor, volume/number, series, type, chapter, pages, address, edition, month, note
 @INCOLLECTION{hsu_dorian_qi_ucsd_2021,
 	author = {Astrid J. Hsu and John Dorian and Katherine Qi and Eric Lo and Benigno Guerror Martinez},
 	title = {Drone Imagery Processing Procedure},
@@ -81,10 +79,8 @@ @article{hui_lo_moss_et_al_jfr_2021
 	keywords = {aerial robotics, environmental monitoring, exploration, rotorcraft},
 	doi = {https://doi.org/10.1002/rob.22017},
 	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.22017},
-	eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/rob.22017},
 	abstract = {Abstract Radio telemetry is a commonly used technique in conservation biology and ecology, particularly for studying the movement and range of individuals and populations. Traditionally, most radio telemetry work is done using handheld directional antennae and either direction-finding and homing techniques or radio-triangulation techniques. Over the past couple of decades, efforts have been made to utilize unmanned aerial vehicles to make radio-telemetry tracking more efficient, or cover more area. However, many of these approaches are complex and have not been rigorously field-tested. To provide scientists with reliable quality tracking data, tracking systems need to be rigorously tested and characterized. In this paper, we present a novel, drone-based, radio-telemetry tracking method for tracking the broad-scale movement paths of animals over multiple days and its implementation and deployment under field conditions. During a 2-week field period in the Cayman Islands, we demonstrated this system's ability to localize multiple targets simultaneously, in daily 10 min tracking sessions over a period of 2 weeks, generating more precise estimates than comparable efforts using manual triangulation techniques.}}
 
-% Optional fields: editor, volume/number, series, pages, address, month, organization, publisher, note
 @InProceedings{perry_tiwari_balaji_reuns_2021,
   author    = {Perry, Sean and Tiwari, Vaibhav and Balaji, Nishant and Joun, Erika and Ayers, Jacob and Tobler, Mathias and Ingram, Ian and Kastner, Ryan and Schurgers, Curt},
   booktitle = {2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)},
@@ -97,7 +93,6 @@ @InProceedings{perry_tiwari_balaji_reuns_2021
   issn      = {2155-6814},
 }
 
-% Optional fields: editor, volume/number, series, pages, address, month, organization, publisher, note
 @InProceedings{tueller_maddukuri_paxson_et_al_oceans_2021,
   author    = {Peter Tueller and Raghav Maddukuri and Patrick Paxson and Vivaswat Suresh and Arjun Ashok and Madison Bland and Ronan Wallace and Julia Guerrero and Brice Semmens and Ryan Kastner},
   booktitle = {OCEANS 2021 MTS/IEEE SAN DIEGO},
@@ -109,7 +104,6 @@ @InProceedings{tueller_maddukuri_paxson_et_al_oceans_2021
   url       = {https://agu.confex.com/agu/OVS21/meetingapp.cgi/Paper/787405},
 }
 
-% Optional fields: volume, number, pages, month, note
 @Article{gautier_garrison_rushton_jchmsd_2020,
   author   = {Gautier, Quentin Kevin and Garrison, Thomas G and Rushton, Ferril and Bouck, Nicholas and Lo, Eric and Tueller, Peter and Schurgers, Curt and Kastner, Ryan},
   journal  = {Journal of Cultural Heritage Management and Sustainable Development},
@@ -211,7 +205,6 @@ @Article{tolkova_bauer_wilby_et_al_jasa_2017
   volume   = {141},
   abstract = {Acoustic methods are an established technique to monitor marine mammal populations and behavior, but developments in computer science can expand the current capabilities. A central aim of these methods is the automated detection and classification of marine mammal vocalizations. While many studies have applied bioacoustic methods to cetacean calls, there has been limited success with humpback whale (Megaptera novaeangliae) social call classification, which has largely remained a manual task in the bioacoustics community. In this project, we automated this process by analyzing spectrograms of calls using PCA-based and connected-component-based methods, and derived features from relative power in the frequency bins of these spectrograms. These features were used to train and test a supervised Hidden Markov Model (HMM) algorithm to investigate classification feasibility. We varied the number of features used in this analysis by varying the sizes of frequency bins. Generally, we saw an increase in precision, recall, and accuracy for all three classified groups, across the individual data sets, as the number of features decreased. We will present the classification rates of our algorithm across multiple model parameters. Since this method is not specific to humpback whale vocalizations, we hope it will prove useful in other acoustic applications.},
   doi      = {10.1121/1.4987715},
-  eprint   = {https://doi.org/10.1121/1.4987715},
   url      = {https://doi.org/10.1121/1.4987715},
 }
 

_config.yml

@@ -52,7 +52,6 @@ whitelist:
 #
 exclude:
   - README.md
-  - publications.bib
 #   - .sass-cache/
 #   - .jekyll-cache/
 #   - gemfiles/
@@ -64,4 +63,13 @@ exclude:
 #   - vendor/gems/
 #   - vendor/ruby/
 
-is_dev: false
+is_dev: false
+
+scholar:
+  style: ieee
+  bibliography: publications.bib
+  bibtex_filters:
+    - latex
+    - smallcaps
+    - superscript
+  bibliography_template: bib

_layouts/bib.html

@@ -0,0 +1,27 @@
+---
+---
+<style>ol.bibliography li { list-style: none }</style>
+{{ reference }}
+
+{% assign urls = "" %}
+{% capture doi_url %}<a href="https://doi.org/{{ entry.doi| remove_first: "https://doi.org/"}}">DOI</a>|{% endcapture %}
+{%if entry.doi%}{% capture urls %}{{urls | append: doi_url }}{% endcapture %}{% endif %}
+
+{% capture arxiv_url %}<a href="https://arxiv.org/abs/{{ entry.eprint }}">arXiv</a>|{% endcapture %}
+{% if entry.eprint %}{% capture urls %}{{urls | append: arxiv_url }}{% endcapture %} {% endif %}
+
+{% capture http_url %}<a href="{{ entry.url }}">http</a>|{% endcapture %}
+{% if entry.url %}{% capture urls %}{{urls | append: http_url }}{% endcapture %} {% endif %}
+
+
+
+<p>[{{urls | split: "|" | join: " | "}}]</p>
+
+{% if entry.abstract %}
+<p></p>
+<blockquote><p>{{ entry.abstract }}</p></blockquote>
+{% endif %}
+
+{% if entry.keywords %}
+<blockquote><p>Keywords: {{ entry.keywords }}</p></blockquote>
+{% endif %}

publications.md

@@ -0,0 +1,5 @@
+---
+title: Publications
+layout: page
+---
+{% bibliography %}