text:
@PACKAGE_INIT@

SET(PN EventSystem)

# location of installed headers
SET(${PN}_INCLUDE_DIR "@PACKAGE_CMAKE_INSTALL_INCLUDEDIR@")

SET(${PN}_LIBRARY "")
SET(${PN}_DEFINITIONS USING_${PN})

LIST(APPEND CMAKE_MODULE_PATH "@PACKAGE_VALIDATION_INSTALL_DIR@/cmake")

CHECK_REQUIRED_COMPONENTS(${PN})

repository: HRI-EU/ESLib

repo_name: HRI-EU/ESLib

extension: in


text:
file(REMOVE_RECURSE
  "CMakeFiles/G__EG"
  "G__EG.cxx"
  "../../lib/libEG_rdict.pcm"
  "../../lib/libEG.rootmap"
)

# Per-language clean rules from dependency scanning.
foreach(lang )
  include(CMakeFiles/G__EG.dir/cmake_clean_${lang}.cmake OPTIONAL)
endforeach()

license_type: permissive

branch_name: refs/heads/master

extension: cmake


text:
@book{birge1987standard,
  title={A standard input format for multiperiod stochastic linear programs},
  author={Birge, John R and Dempster, Michael AH and Gassmann, Horand I and Gunn, Eldon A and King, Alan J and Wallace, Stein W},
  year={1987},
  publisher={IIASA Laxenburg Austria}
}

@book{birge2011introduction,
  title={Introduction to stochastic programming},
  author={Birge, John R and Louveaux, Francois},
  year={2011},
  publisher={Springer}
}

@article{bezanson2012julia,
  title={Julia: A fast dynamic language for technical computing},
  author={Bezanson, Jeff and Karpinski, Stefan and Shah, Viral B and Edelman, Alan},
  journal={arXiv preprint arXiv:1209.5145},
  year={2012}
}

@inproceedings{huchette2014parallel,
  title={Parallel algebraic modeling for stochastic optimization},
  author={Huchette, Joey and Lubin, Miles and Petra, Cosmin},
  booktitle={Proceedings of the 1st First Workshop for High Performance Technical Computing in Dynamic Languages},
  pages={29--35},
  year={2014},
  organization={IEEE Press}
}

@article{lubin2013computing,
  title={{Computing in operations research using Julia}},
  author={Lubin, Miles and Dunning, Iain},
  journal={arXiv preprint arXiv:1312.1431},
  year={2013}
}

repository: bcdandurand/DSP

repo_name: bcdandurand/DSP

extension: bib


text:
DESCRIPTION = "Scikits Samplerate"
HOMEPAGE = "http://www.scikits.org"
SECTION = "devel/python"
LICENSE = "GPLv2"
LIC_FILES_CHKSUM = "file://COPYING;md5=94d55d512a9ba36caa9b7df079bae19f"

SRCNAME = "samplerate"
PR = "r0"

# SETUP DEPENDS
DEPENDS += " libsamplerate0 python-dev python-numpy python-pygame"

SRC_URI = "https://github.com/cournape/samplerate/archive/${PV}.tar.gz"

S = "${WORKDIR}/${SRCNAME}-${PV}"

BBCLASSEXTEND = "native"

inherit distutils
export BUILD_SYS
export HOST_SYS
export STAGING_INCDIR
export STAGING_LIBDIR

# This really shouldn't need to be here but the build blows up trying to find numpy.distutils
export PYTHONPATH="${STAGING_LIBDIR}:${STAGING_LIBDIR}/${PYTHON_DIR}/site-packages/:$PYTHONPATH"

do_configure_prepend() {

     touch ${S}/site.cfg
     rm ${S}/site.cfg
     echo "[samplerate]" >> ${S}/site.cfg
     echo "library_dirs = ${STAGING_LIBDIR}" >> ${S}/site.cfg
     echo "include_dirs = ${STAGING_INCDIR}" >> ${S}/site.cfg
}

SRC_URI[md5sum] = "78020e08af5c1fab8dd71b7e846b8fc8"
SRC_URI[sha256sum] = "f97df7ed18380775076d97a1f9ff175854a6c853fde66dc245a674f581791677"

INHIBIT_PACKAGE_DEBUG_SPLIT="1"

license: MIT

repository: yoctopidge/meta-hurdy

repo_name: yoctopidge/meta-hurdy

extension: bb


text:
require recipes-core/images/core-image-minimal.bb

PACKAGE_ARCH = "${MACHINE_ARCH}"

CORE_IMAGE_EXTRA_INSTALL += "udev-extraconf lsb"

IMAGE_FSTYPES = "tar.gz cpio.gz"

SUMMARY = "Image to be used for IFC1410 and IFC1420"
DESCRIPTION = "IFC14XX image"

LICENSE = "MIT"

IMAGE_FEATURES += "package-management"
IMAGE_INSTALL_append = " \
    packagegroup-core-ssh-openssh \
"

IMAGE_LINGUAS = "en-gb en-us"

repository: jeonghanlee/yocto-ess

repo_name: jeonghanlee/yocto-ess

gha_license_id: MIT


text:
DESCRIPTION = "Library for rendering SVG files"
SECTION = "x11/utils"
MAINTAINER = "Phil Blundell <pb@handhelds.org>"
DEPENDS = "gtk+ libcroco libart-lgpl libxml2 popt"
LICENSE = "LGPL"
PR = "r1"

EXTRA_OECONF = "--disable-mozilla-plugin"

inherit autotools pkgconfig gnome

PACKAGES =+ "librsvg-gtk librsvg-gtk-dev rsvg"
FILES_${PN} = "${libdir}/*.so.*"
FILES_rsvg = "${bindir}/rsvg ${bindir}/rsvg-view ${datadir}/pixmaps/svg-viewer.svg"
FILES_librsvg-gtk = "${libdir}/gtk-2.0/*/*/*.so"
FILES_librsvg-gtk-dev = "${libdir}/gtk-2.0"

EXTRA_OECONF = "--disable-mozilla-plugin"

do_stage() {
	autotools_stage_all
}


text:
---
---

@article{bischof2023complexity,
  title={Can Simple Language Affect Voters' Political Knowledge and Their Beliefs About Politicians?},
  author={Daniel Bischof and Roman Senninger},
  journal={revise & resubmit: Journal of Politics},
  volume={},
  number={},
  pages={},
  year={2023},
  publisher={},
  selected={true},
  abbr={OSF},
  HTML={https://osf.io/cgz4k},
  abstract={How do the tone and style of political messages affect citizens? While research has unpacked which politicians demarcate themselves with their tone and style, we know little about how this resonates with citizens. We theorize that linguistic simplicity, as a communication style, should increase citizens' political knowledge and affect their beliefs about politicians. Simple language is used as a heuristic signaling that politicians are among the ``people'' and this might increase politicians' public support. In pre-registered and large-scale survey experiments conducted in Germany, respondents are shown political statements randomly varying in linguistic simplicity, among other factors. Simplicity increases respondents' political knowledge and is used by them as a heuristic to fill informational gaps about politicians' socio-economic backgrounds. In the electoral arena sophistication moderates the effect of politicians' policy positions. Our findings showcase that linguistic styles can be a major tool for contemporary political campaigns.}
}

@article{bischof2023demnorm,
  title={(Mis-)Perceiving Support for Democracy: The Role of Social Norms for Democracies},
  author={Daniel Bischof and Tim Lars Allinger and Morgan Le Corre Juratic and Kristian Vrede Skaaning Frederiksen},
  journal={},
  volume={},
  number={},
  pages={},
  year={2023},
  publisher={},
  selected={false},
  abbr={OSF},
  HTML={https://osf.io/dpq7w},
  abstract={Generations of political scientists seek to understand the relationship between citizens' democratic values and democratic stability. The key premise of this research tradition is that democratic societies live on a ``social consensus'' over a set of democratic values; a democratic norm. Yet, until today scholarship has neither carefully theorized the role of nor measured this social consensus. Building on research in social psychology, we conceptualize democratic norms as social norms: citizens may think that most people in democracies support its institutions (descriptive norm) and also that one ought to do so (injunctive norm). Based on this, we provide a theoretical framework and derive observable implications of which country- and individual-level characteristics structure social democratic norms. Using existing surveys and large-scale original survey experiments, we will then measure these democratic norms in up to 15 democracies. Our research has important implications for research on democracy showcasing the role social norms play to craft democratic support in our societies. }
}

@article{bischof2022bans,
  title={The Consequences of Punishing Political Ideologies in Democracies – Evidence from Employment Bans in Germany},
  author={Daniel Bischof and Vicente Valentim},
  journal={},
  volume={},
  number={},
  pages={},
  year={2022},
  publisher={},
  selected={false},
  abbr={OSF},
  HTML={https://osf.io/usqdb},
  abstract={How can states counter growing political radicalism? We look at the effect of states persecuting ``extreme'' individuals by studying the case of the Anti-Radical Decree in West Germany. Implemented in 1972, this policy allowed individuals with connections to mostly communist groups to be banned from working in the public sector. Drawing upon a newly collected data set of individuals targeted by the bans, we run regression models to estimate the effect of such bans on the political behavior of German citizens measured in surveys and official election results. In particular, we look at the long-term effects of the bans by estimating their effects on establishing the Green party, formed a few years after the policy was first implemented. We find that counties that experienced bans are significantly more likely to take protest against the bans on the streets and subsequently vote for the Green party. Added to that individuals, who voice opposition to the bans in surveys are more likely to support the Greens. The effect is stronger in counties that were more leftist, politicized, and had more public sector workers. Our findings have implications for the sets of policies democracies can use to ensure their institutional survival.}
}

@article{bischof2022experiment,
  title={Using the Party as a Shield? How British MPs Explain Policy Positions to Constituents},
  author={Daniel Bischof and Vanessa Cheng-Matsuno and Gidon Cohen and Sarah Cohen and Florian Foos and Patrick M. Kuhn and Kyriaki Nanou and Neil Visalvanich and Nick Vivyan},
  journal={},
  volume={},
  number={},
  pages={},
  year={2022},
  publisher={},
  selected={false},
  abbr={OSF},
  HTML={https://osf.io/z8ycg},
  abstract={How do legislators respond to constituents' requests? Recent studies showcase that US legislators are particularly responsive to their voters, even tailoring their messages toward them. But little research investigates if these findings hold for parliamentary systems which are characterized by high party discipline forcing legislators to fall in line. We theorize that in such systems legislators use their party as a shield if their opinion contradicts their constituents' positional wishes. We test our argument in an audit study involving both legislators and actual voters during the Brexit negotiations in 2019 in the United Kingdom. Contrary to conventional wisdom about party-dominated systems we find no evidence that MPs are less responsive to correspondence from party-incongruent constituents nor that they use their party as a shield. These null findings have important implications for our understanding of how legislative behavior in parliamentary systems is (not) constrained by party discipline.}
}

@article{lang2022,
  title={Place-Based Policies and Inequality Within Regions},
  author={Daniel Bischof and Valentin Lang and Nils Redeker},
  journal={},
  volume={},
  number={},
  pages={},
  year={2022},
  publisher={},
  selected={false},
  abbr={OSF},
  HTML={https://osf.io/2xmzj/},
  abstract={What are the distributional effects of placed-based policies? Drawing on household data from 2.4 million survey respondents in the European Union (EU), we show that income inequality within European regions is substantial, has widened since the 1990s and contributes more to overall inequality than cross-regional inequality. Using regression discontinuity and difference-in-differences designs, we find that the world's largest place-based policy, the EU's Cohesion Policy, increases incomes for affluent households but barely affects low-income households in supported regions. Evidence on mechanisms demonstrates that place-based funds exacerbate intra-regional inequality by primarily boosting labor incomes for the highly skilled.}
}

@article{bischof2020sd,
  title={Lost in Transition – Where Are All the Social Democrats Today?},
  author={Daniel Bischof and Thomas Kurer},
  journal  = {prepared for an edited book by Silja Häusermann and Herbert Kitschelt},
  year={2021},
  selected={false},
  abbr={OSF},
  HTML={https://osf.io/n2hbu/},
  abstract={This chapter follows individual voter flows using panel data for Social Democrats in Germany (1984-2018), the United Kingdom (1991-2018) and Switzerland (1999-2018). To our knowledge this chapter, thus, provides the first long running study of individual voting transitions amongst Social Democratic voters, following their transitions for almost 40 years. The key goal of this chapter is to understand where initial voters of the Social Democrats are today and which individual level characteristics correlate with leaving SDs. We find: 1) Social Democrats manage to keep some of their core 2) but a lot of their core gets de-mobilized or moves on to more progressive options (Greens, LibDem, Green Liberal Party). 3) SDs struggle in all countries to attract new voters, less so in Switzerland which we think is at least partly due to the progressive offer provided by the SP. In contrast, the German SPD loses to everyone and gains almost nothing. We also find evidence that SDs die out: the key factor correlated with `leaving' is the generational cohort Social Democrats belong to. In contrast, often theorized and emphasized factors such as occupation, income or unemployment show much smaller correlations with former Social Democrats' decision to leave the party behind.}
}

@article{bischof2021legacy,
  title={The Political Legacies of Military Service: Evidence From a Natural Experiment},
  journal={available upon request},
  volume={},
  number={},
  pages={},
  year={2021},
  publisher={},
  selected={false},
  abstract={Does military service affect draftees' political attitudes after service? While a rich body of research investigates the effects of combat participation on soldiers' attitudes, we know little about the effects of military service in the absence of combat. However, a widely shared concern is that the military socializes its draftees into authoritarian values running orthogonal to the values of civilians' lives in democracies. I identify the causal effect of compulsory military service on recruits' political attitudes by studying the quasi-random assignment of the re-introduced draft in Germany in 1956 using the German Socio-Economic Panel. I find that draftees are more left-leaning and show higher trust in foreigners even 40 years after their service; but also that in most regards serving has no effects on recruits. To better understand the mechanisms behind these long-term legacy effects I rely on a three-wave panel of draftees conducted by the military in 1966. Panel analyses reveal that recruits' experiences during service do not travel beyond the workplace. Overall, the findings imply that in many ways our experiences at our workplaces might have a much smaller effect on our attitudes and values than previous research suggests.}
}

@article{bischof2021protest,
  title={Does Exposure to Radical Right Rallies Affect Political Behavior and Preferences -- Evidence From the Far Right Pegida Movement in Germany},
  journal={available upon request},
  volume={},
  number={},
  pages={},
  year={2021},
  publisher={},
  selected={false},
  abstract={What are the effects of far right movements on citizens' electoral behavior and preferences? Previous research implies that protests and social movements can sway the public towards their goals. However research that actually studies the effect of local protests on the local community and public is scarce. Collecting the full history of local mobilization by a German anti-migration, radical right movement -- the `Patriotic Europeans Against the Islamicisation of the Occident (PEGIDA)' -- on the street-level I study the effects on the affected communities by using Difference-in-Differences and matching methods. I find that PEGIDA increased voting for radical right parties and made the public support stricter limits on migration. But not all citizens react equally: the effects are driven by mainstream right voters, while the left backlashes. The findings have important implications for the study of public opinion in contemporary societies and political science understanding of protesters' relevance.}
}

@article{cohen2020switching,
  title={How Perception of Support Drives Vote Switching to Challenger Parties},
  author={Daniel Bischof and Denis Cohen},
  journal={available upon request},
  volume={},
  number={},
  pages={},
  year={2020},
  publisher={},
  selected={false}
}

@article{bischof2023m5s,
  title={Can Populist Parties Increase Electoral Turnout? The Case of the M5S Movement in Italy},
  author={Daniel Bischof and Tim Lars Allinger and Thomas Kurer},
  journal={},
  volume={},
  number={},
  pages={},
  year={ongoing},
  publisher={},
  selected={false},
  abbr={},
  abstract={Can populist parties increase electoral turnout? On the one hand, classical scholarship suggests that populist movements mobilize disenfranchised citizens by providing an alternative to established parties -- the ``corrective for democracy'' hypothesis. On the other hand, populist parties might as well decrease voter turnout by inflaming societal divides and excluding minority groups. We turn to the Italian Movimento Cinque Stelle, arguably one of the most relevant populist parties, which followed the unusual practice of coordinating all political activities on a public online platform. We webscraped the entire event history of the Movement's more than 1,000 local branches with over 200,000 geocoded political activities to study how the staggered local emergence of M5S chapters affects electoral turnout. Using staggered difference-in-differences models on election results and surveys spanning thirty years, our preliminary analyses suggest that the rise of M5S decreases turnout. Our findings have important implications for the study of turnout in contemporary democracies and the negative consequences of populism in the electoral arena.  }
}

@article{bischof2023socdes,
  title={Social Desirability Bias as Substance and Not Nuisance},
  author={Daniel Bischof and Tim Lars Allinger and Morgan Le Corre Juratic and Kristian Vrede Skaaning Frederiksen},
  journal={},
  volume={},
  number={},
  pages={},
  year={ongoing},
  publisher={},
  selected={false},
  abbr={},
  abstract={Social scientists have long debated the question of how threatening social desirability biases are for what scientists can learn from survey respondents. Until today such biases are treated as a nuisance at best. In contrast, we argue that social desirability biases are key to understand for social scientists as they are important proxies for social norms and the need for conformity within societies. We compare six different designs to measure social desirability bias in relation to support for democracy in three European countries. Besides a list experiment, we rely on various approaches that trigger respondents' need to provide socially acceptable answers. We show that triggering social desirability is outperforming list experiments and observational measures for various reasons. Most importantly it allows researchers to test whether social desirability is actually manipulated. It also ensures that social desirability is not treated as a nuisance but as a matter of substantive research interest.  }
}

@article{bischof2023localleaders,
  title={Social Norms, Local Opinion Leaders, and Support for Policy Proposals},
  author={Daniel Bischof and Julia Schulte-Cloos and Roman Senninger},
  journal={},
  volume={},
  number={},
  pages={},
  year={ongoing},
  publisher={},
  selected={false},
  abbr={},
  abstract={By involving ordinary citizens in decision-making, citizens' assemblies can help to strengthen legitimacy and trust in democratic institutions. While previous literature has focused primarily on the effects on citizens' trust in democratic decision-making processes, we have little insight into the potential effects they have in influencing public opinion on salient policy issues. As the recommendations or decisions made by the participants can be widely publicized, the positions advanced by ordinary citizens can provide the public with relevant cues on social norms around a given issue. This may have significant implications for voters' opinion formation, particularly if they share a common social identity with the citizen representative. To test this argument, we present a visual conjoint experiment designed to closely mirror the actual online participation forum of the Conference for the Future of Europe, one of the largest citizens’ assemblies ever undertaken. By virtue of the conjoint design, we experimentally manipulate the policy position of the message, the extent to which the sender is conceived as an opinion leader, the polarization associated with the policy position put forward, and the sender's shared local social identity. }
}

@article{bischof2023affect,
  title={The Unexpected Democrats? Democratic Norms Protection in Context of Affective Polarization},
  author={Daniel Bischof and Morgan Le Corre Juratic and Markus Wagner},
  journal={},
  volume={},
  number={},
  pages={},
  year={ongoing},
  publisher={},
  selected={false},
  abbr={}
}

@article{bischof2023weimarriot,
  title={The Effects of Spirals of Electoral Violence on Extremist Voting},
  author={Daniel Bischof and Alexander De Juan and Felix Haass and Henry Thomson},
  journal={},
  volume={},
  number={},
  pages={},
  year={ongoing},
  publisher={},
  selected={false},
  abbr={},
  abstract={How do spirals of electoral violence shape electoral outcomes? A large body of research highlights that electoral violence serves as strategic tool of political elites trying to influence election results. In particular, violence aims at demobilizing opponents’ constituencies. We shift attention to another potential mechanism. In contexts of political polarization, elites can use violence to mobilize their own constituencies: spirals of violence, i.e. repeated attacks and counter-attacks by extremist parties on opposing ends of the political spectrum, allow candidates to portray themselves as resolute guardians against political radicals. Our analyses of the electoral effects of these spirals of violence focus on a most likely context: the final phase of the Weimar Republic before Hitler’s ascension to power. We draw on archival police records on more than 3000 violent clashes in the elections years 1930, 1932 and 1933. We combine this information with county-level election results and historical census data.}
}

gha_language: JavaScript


text:
@inproceedings{singh-etal-2016-mapping,
    title = "Mapping it differently: A solution to the linking challenges",
    author = "Singh, Meghna  and
      Shukla, Rajita  and
      Saraswati, Jaya  and
      Kashyap, Laxmi  and
      Kanojia, Diptesh  and
      Bhattacharyya, Pushpak",
    booktitle = "Proceedings of the 8th Global WordNet Conference (GWC)",
    month = "27--30 " # jan,
    year = "2016",
    address = "Bucharest, Romania",
    publisher = "Global Wordnet Association",
    url = "https://aclanthology.org/2016.gwc-1.57",
    pages = "411--418",
    abstract = "This paper reports the work of creating bilingual mappings in English for certain synsets of Hindi wordnet, the need for doing this, the methods adopted and the tools created for the task. Hindi wordnet, which forms the foundation for other Indian language wordnets, has been linked to the English WordNet. To maximize linkages, an important strategy of using direct and hypernymy linkages has been followed. However, the hypernymy linkages were found to be inadequate in certain cases and posed a challenge due to sense granularity of language. Thus, the idea of creating bilingual mappings was adopted as a solution. A bilingual mapping means a linkage between a concept in two different languages, with the help of translation and/or transliteration. Such mappings retain meaningful representations, while capturing semantic similarity at the same time. This has also proven to be a great enhancement of Hindi wordnet and can be a crucial resource for multilingual applications in natural language processing, including machine translation and cross language information retrieval.",
}

repository: dipteshkanojia/academic-kickstart

repo_name: dipteshkanojia/academic-kickstart


text:
@misc{TODO,
  title = "\todo{Citation to be filled}"
}

@string{ase = "IEEE/ACM International Conference on Automated Software Engineering (ASE)"}

@string{oopsla = "ACM Symposium on Object-Oriented Programming, Systems,
Languages and Applications (OOPSLA)"}

@string{icse = "International Conference on Software Engineering (ICSE)"}

@string{fse = "ACM SIGSOFT International Symposium on the Foundations of
Software Engineering (FSE)"}

@string{tse = "IEEE Transactions on Software Engineering (TSE)"}

@string{issta = "International Symposium on Software Testing and Analysis (ISSTA)"}

@string{pldi = "ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)"}

@string{acsac = "Annual Computer Security Applications Conference (ACSAC)" }

@string{lastaccessed = {}}

@string{usenixsec = {USENIX Security Symposium}}

@string{sac = {ACM Symposium on Applied Computing (SAC)}}

@string{ndss = "Network and Distributed System Security Symposium (NDSS)"}

@string{esorics = "European Symposium on Research in Computer Security (ESORICS)"}

@string{cacm = "Communications of the ACM (CACM)"}

@string{fc = "International Conference on Financial Cryptography and Data Security (FC)"}

@string{asplos = "International Conference on Architectural Support for Programming Languages
  and Operating Systems (ASPLOS)"}

@string{acmccs = "ACM Conference on Computer and Communications Security (CCS)" }

@string{hotmobile = "HotMobile" }

@string{sosp = "ACM Symposium on Opererating Systems Principles (SOSP)" }

@string{mobisys = "International Conference on Mobile Systems, Applications, and Services (MobiSys)" }

@string{oakland = "IEEE Symposium on Security and Privacy (Oakland)" }

@string{eurosys = "European Conference on Computer Systems (EuroSys)" }

@string{hotos = "USENIX Workshop on Hot Topics in Operating Systems (HotOS)"}

@string{icac = "International Conference on Autonomic Computing (ICAC)"}

@string{most = "IEEE Mobile Security Technologies Workshop (MoST)" }

@string{asiaccs = "ACM Sympsium on Information, Computer and Communications Security (ASIACCS)" }

@string{isc = "International Information Security Conference (ISC)"}

@string{securecomm = "International Conference on Security and Privacy in Communication Networks (SecureComm)"}

@string{osdi = "USENIX Symposium on Operating Systems Design and Implementation
(OSDI)"}

@string{hotsec = "Workshop on Hot Topics in Security (HotSec)" }

@string{ubicomp = "ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)" }

@string{soups = "Symposium on Usable Privacy and Security (SOUPS)"}

@misc{phonegap,
  title = "Adobe {PhoneGap}",
  note = "\url{http://phonegap.com}"
}

@misc{sencha,
  title = "Sencha: {HTML5} App Development",
  note = "\url{http://www.sencha.com}"
}

@misc{worklight,
  title = "{IBM} {MobileFirst} Platform Foundation",
  note = "\url{http://www-03.ibm.com/software/products/en/mobilefirstfoundation}"
}

@misc{xamarin,
  title = "{Xamarin} -- {Mobile App Development and App Creation Software}",
  note = "\url{http://xamarin.com}"
}

@misc{apportable,
  title = "Apportable -- {Objective-C} for {Android}",
  note = "\url{www.apportable.com}"
}

@misc{mono,
  title = "Mono -- {Cross-platform}, open source \btcode{.NET} framework",
  note = "\url{http://www.mono-project.com}"
}

@misc{jsonnet,
  title = "{Json.NET} -- Popular high-performance {JSON} framework for
  \btcode{.NET}",
  note = "\url{http://james.newtonking.com/json}"
}

@inproceedings{mam:icse10,
 author = {Zhong, H. and Thummalapenta, S. and Xie, T. and Zhang, L. and Wang,
 Q.},
 title = {Mining {API} Mapping for Language Migration},
 booktitle = icse,
 year = {2010},
}

@article{robillard:tse,
  author = "M. P. Robillard and E. Bodden and D. Kawrykow and M. Mezini and T.
  Ratchford",
  title = "Automated {API} Property Inference Techniques",
  journal = tse,
  volume = 39,
  number = 5,
  month = May,
  year = 2013
}

@article{mckeeman:difftest:1998,
  author = "W. M. McKeeman",
  title = "Differential testing for software",
  journal = "Digital Technical Journal",
  volume = 10,
  number = 1,
  month = Dec,
  year = 1998
}

@misc{xam:bzil:25895,
  title = "Wrong exception is thrown when calling
  \btcode{System}.\btcode{Globalization}.\btcode{CharUnicodeInfo}.\btcode{GetNumericValue} with invalid index",
  author = "Xamarin Bug~25895",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=25895}"
}

@misc{xam:bzil:27901,
  title = "\btcode{XmlConvert}.\btcode{ToString} returns wrong value",
  author = "Xamarin Bug~27901",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=27901}"
}

@misc{xam:bzil:27910,
  title = "\btcode{XmlParserContext} Constructor not throwing \btcode{XmlException}
  when it should",
  author = "Xamarin Bug~27910",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=27910}"
}

@misc{xam:bzil:27922,
  title = "\btcode{XmlConvert.ToUnit} throwing wrong/inconsistent exception",
  author = "Xamarin Bug~27922",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=27922}"
}

@misc{xam:bzil:27982,
  title = "Inconsistent behavior in \btcode{DynamicAttribute.Equals}",
  author = "Xamarin Bug~27982",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=27982}"
}

@misc{xam:bzil:28017,
  title = "\btcode{NameTable.Add} throwing wrong/inconsistent exception",
  author = "Xamarin Bug~28017",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28017}"
}

@misc{xam:bzil:28123,
  title = "Inconsistent behavior in
	\btcode{System}.\btcode{Xml}.\btcode{XmlReaderSettings}.\btcode{MaxCharactersInDocument}",
  author = "Xamarin Bug~28123",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28123}"
}

@misc{xam:bzil:28134,
  title = "\btcode{System}.\btcode{Text}.\btcode{EncoderFallbackException}
	inconsistent initial state compared to \btcode{.NET}
	(two inconsistencies assigned to this bug identifier)",
  author = "Xamarin Bug~28134",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28134}"
}

@misc{xam:bzil:28562,
  title = "Incorrect \btcode{System}.\btcode{Numerics}.\btcode{Complex}.\btcode{Pow}
	result",
  author = "Xamarin Bug~28562",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28562}"
}

@misc{xam:bzil:28571,
  title = "Incorrect behavior in
	\btcode{System}.\btcode{Numerics}.\btcode{BigInteger}",
  author = "Xamarin Bug~28571",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28571}"
}

@misc{xam:bzil:28572,
  title = "Incorrect/Inconsistent behavior in
	\btcode{System}.\btcode{Numerics}.\btcode{Complex}.\btcode{Divide}",
  author = "Xamarin Bug~28572",
  note = "\url{https://bugzilla.xamarin.com/show_bug.cgi?id=28572}"
}

@misc{nader:connect:1,
  title = "{\btcode{System.Globalization.NumberFormatInfo.CurrentInfo} property
          is not read-only when called from {Windows Phone 8.1}}",
  note = "Microsoft Visual Studio Connect Bug~ID 1082098",
  month = "January",
  year = 2015
}

@article{fuzz:unix,
  author = "B. P. Miller and L. Fredriksen and B. So",
  title = "An Empirical Study of the Reliability of {UNIX} Utilities",
  journal = cacm,
  volume = 33,
  number = 12,
  month = Dec,
  year = 1990
}

@inproceedings{fuzz:nt,
  author = "J. E. Forrester and B. P. Miller",
  title = "An Empirical Study of the Robustness of {Windows} {NT} Applications
  using Random Testing",
  booktitle = "USENIX Windows Systems Symposium",
  year = 2000
}

@article{jcrasher,
  author = "C. Csallner and Y. Smaragdakis",
  title = "{JCrasher}: {An} Automatic Robustness Tester for {Java}",
  journal = "Software--Practice and Experience",
  volume = 34,
  number = 11,
  year = 2004
}

@inproceedings{dsd:issta06,
  author = "C. Csallner and Y. Smaragdakis",
  title = "{DSD-Crasher}: A Hybrid Analysis Tool for Bug~Finding",
  booktitle = issta,
  year = 2006
}

@inproceedings{brumley:sec07,
  title = "Towards Automatic Discovery of Deviations in Binary Implementations
  with Applications to Error Detection and Fingerprint Generation",
  author = "D. Brumley and J. Caballero and Z. Liang and J. Newsome and D.
  Song",
  booktitle = usenixsec,
  year = 2007
}

@inproceedings{xpert:icse13,
  author = "S. Choudhary and M. Prasad and A. Orso",
  title = "{X-PERT}: {Accurate} Identification of Cross-Browser Issues in {Web}
  Applications",
  year = 2013,
  booktitle = icse,
}

@inproceedings{csmith:pldi11,
  author = "X. Yang and Y. Chen and E. Eide and J. Regehr",
  title = "Finding and Understanding Bugs in {C} Compilers",
  booktitle = pldi,
  year = 2011
}

@inproceedings{md2:sac13,
  author = "H. Heikotter and T. Majchrzak and H. Kuchen",
  title = "Cross-Platform Model-Driven Development of Mobile Applications with
  {MD$^2$}",
  booktitle = sac,
  year = 2013
}

@inproceedings{dynodroid:fse13,
  author = "A. Machiry and R. Tahiliani and M. Naik",
  title = "Dynodroid: An Input generation System for {Android} apps",
  booktitle = fse,
  year = 2013
}

@inproceedings{concolicandroid:fse12,
  author = "S. Anand and M. Naik and H. Yang and M. Harrold",
  title = "Automated Concolic Testing of Smartphone Apps",
  booktitle = fse,
  year = 2012
}

@inproceedings{eventbreak:oopsla14,
  author = "M. Pradel and P. Schuh and G. Necula and K. Sen",
  title = "EventBreak: {Analyzing} the Responsiveness of User Interfaces
  through Performance-Guided Test Generation",
  booktitle = oopsla,
  year = 2014
}

@inproceedings{azim:oopsla13,
  author = "T. Azim and I. Neamtiu",
  title = "Targeted and Depth-first Exploration for Systematic Testing of
  {Android} Apps",
  booktitle = oopsla,
  year = 2013
}

@inproceedings{memon:ase07,
  author = "P. Brooks and A. Memon",
  title = "Automated {GUI} testing guided by usage profiles",
  booktitle = ase,
  year = 2007
}

@article{guitar:memon,
  author = "B. Nguyen and B. Robbins and I. Banerjee and A. Memon",
  title = "{GUITAR}: An Innovative Tool for Automated Testing of {GUI}-driven
  Software",
  journal = "Journal of Automated Software Engineering",
  number = "1",
  volume = "21",
  year = 2014
}

@inproceedings{rosetta:icse13,
  author = "A. Gokhale and V. Ganapathy and Y. Padmanaban",
  title = "Inferring Likely Mappings Between {APIs}",
  booktitle = icse,
  year = 2013
}

@misc{myappconverter,
  title = "{MyAppConverter} -- Develop Once, Run Anywhere",
  note = "\url{http://www.myappconverter.com}"
}

@inproceedings{fmap:issta14,
  author = "S. R. Choudhary and M. R. Prasad and A. Orso",
  title = "Cross-Platform Feature Matching for {Web} Applications",
  booktitle = issta,
  year = 2014
}

@inproceedings{oracle:pldi11,
  author = "V. Srivastava and M. D. Bond and K. S. McKinley and V. Shmatikov",
  title = "A Security Policy Oracle: {Detecting} Security Holes using Multiple
  {API} Implementation",
  booktitle = pldi,
  year = 2011
}

@inproceedings{franken:oak14,
  author = "C. Brubaker and S. Jana and B. Ray and S. Khurshid and V.
  Shmatikov",
  title = "Using {Frankencerts} for Automated Adversarial Testing of
  Certificate Validation in {SSL/TLS} Implementations",
  booktitle = oakland,
  year = 2014
}

@inproceedings{randoop:icse07,
  author = "C. Pacheco and S. K. Lahiri and M. Ernst and T. Ball",
  title = "Feedback-directed Random Test Generation",
  booktitle = icse,
  year = 2007
}

@misc{win10,
  title = "Microsoft invites {Android} and {iOS} apps to join {Windows} 10",
  author = "C. Velazco",
  note = "\url{http://www.engadget.com/2015/04/29/android-ios-apps-on-windows-10}",
  month = "April",
  year = 2015
}

@misc{build15,
	author = "S. Guthrie and T. Myerson and S. Nadella",
	title = "Day One Keynote Presentation, {Microsoft} {Build} Developer
	Conference",
	month = "April",
	year = 2015,
	note = "\url{http://channel9.msdn.com/Events/Build/2015/KEY01}"
}

repository: iisccssl/published-papers

repo_name: iisccssl/published-papers


text:
require poppler.inc

PR = "r0"

EXTRA_OECONF_append = " --disable-abiword-output "

SRC_URI[md5sum] = "29d341f295d01bff64c63a29a6abb274"
SRC_URI[sha256sum] = "45bd5740b07e6c15db9859a5ee82e2acc9eeec62be537735ae5872fc3648257a"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
DESCRIPTION = "Linux kernel for the RZ/G based board"

require recipes-kernel/linux/linux-yocto.inc
include linux.inc

FILESEXTRAPATHS_prepend := "${THISDIR}/${PN}/:"
COMPATIBLE_MACHINE = "iwg20m|iwg21m|iwg22m|iwg23s|aprzg0a"

DEPENDS_append = " util-linux-native openssl-native"

RENESAS_URL="git://github.com/renesas-rz/renesas-cip.git"
SRCREV = "314face074138ffb645e71b87e9d72aab2311233"
SRC_URI = " \
	${RENESAS_URL};protocol=git;branch=v4.4.138-cip25 \
	file://0001-v4l2-core-remove-unhelpful-kernel-warning.patch \
	file://0001-include-uapi-linux-if_pppox.h-include-linux-in.h-and.patch \
"

LINUX_VERSION ?= "4.4.138-cip25"
PV = "${LINUX_VERSION}+git${SRCPV}"
PR = "r1"

S = "${WORKDIR}/git"

SRC_URI_append = " \
    file://defconfig \
    file://common.cfg \
"

SRC_URI_append_iwg20m = " \
    file://iwg20m.cfg \
"

SRC_URI_append_iwg21m = " \
    file://iwg21m.cfg \
"

SRC_URI_append_iwg22m = " \
    file://iwg22m.cfg \
"

SRC_URI_append_iwg23s = " \
    file://iwg23s.cfg \
"

SRC_URI_append_aprzg0a = " \
    file://aprzg0a.cfg \
    file://0010-aprzg0a_linux-v2.00.patch \
    file://0011-aprzg0a_linux-v2.01.patch \
    file://0012-aprzg0a_linux-v2.02.patch \
"

do_configure_append() {
	# If kernel_configure_variable or similar functions is used, add here.
	# Note that the settings here has higher priority than cfg files above.

}


text:
require cuda-shared-binaries-${PV}.inc

SRC_URI[main.sha256sum] = "319771f42db1d9a4a273bc5ff753148247ece9cf7544d2008d57d9061e6964f9"
SRC_URI[dev.sha256sum] = "3bd27507b8eef4ae9d5faf8671e8843ef7bd4cede82dc76a8e6519390e22a5dc"

FILES_${PN}-dev += "${prefix}/local/cuda-${CUDA_VERSION}/extras/CUPTI/Readme.txt \
                    ${prefix}/local/cuda-${CUDA_VERSION}/extras/CUPTI/include ${prefix}/local/cuda-${CUDA_VERSION}/extras/CUPTI/sample"

BBCLASSEXTEND = "native nativesdk"

repository: b-man/meta-tegra

repo_name: b-man/meta-tegra


text:
require nodejs_6.inc
require nodejs_lts.inc

INC_PR = "r1"

LIC_FILES_CHKSUM = "file://LICENSE;md5=19eb7a3bddc44523bf96176c3da4b422"

SRC_URI[src.md5sum] = "b9e6bd6eddb78f34becfa891d60071d8"
SRC_URI[src.sha256sum] = "997121460f3b4757907c2d7ff68ebdbf87af92b85bf2d07db5a7cb7aa5dae7d9"

repository: dzudek/meta-nodejs

repo_name: dzudek/meta-nodejs

gha_language: PHP


text:
# Start with the minimal bundle as a base
require minimal-nilrt-bundle.bb

BUNDLE_IMAGE = "lvcomms-nilrt-bundle-image"

repository: NIwkoe/meta-nilrt

repo_name: NIwkoe/meta-nilrt

branch_name: refs/heads/nilrt/master/sumo


text:
% Encoding: UTF-8

@Article{domingos2012,
  author =     {Domingos, Pedro},
  title =      {A Few Useful Things to Know About Machine Learning},
  journal =    {Commun. ACM},
  year =       {2012},
  volume =     {55},
  number =     {10},
  pages =      {78--87},
  month =      oct,
  acmid =      {2347755},
  address =    {New York, NY, USA},
  doi =        {10.1145/2347736.2347755},
  issn =       {0001-0782},
  issue_date = {October 2012},
  numpages =   {10},
  publisher =  {ACM},
  url =        {http://doi.acm.org/10.1145/2347736.2347755}
}

@Misc{karpathy1,
  author =       {Andrej Karpathy},
  title =        {Neural Networks Part 1: Setting up the Architecture},
  howpublished = {CS231n: Convolutional Neural Networks for Visual Recognition},
  year =         {2016 (accessed July 9, 2016)},
  note =         {http://cs231n.github.io/neural-networks-1/}
}

@Misc{lstm,
  author = {Andrej Karpathy},
  title =  {The Unreasonable Effectiveness of Recurrent Neural Networks},
  month =  {May 21},
  year =   {2015 (accessed Jul 10, 2016)},
  note =   {http://karpathy.github.io/2015/05/21/rnn-effectiveness/}
}

@Book{mitchell1997,
  title =     {Machine Learning},
  publisher = {McGraw-Hill, Inc.},
  year =      {1997},
  author =    {Mitchell, Thomas M.},
  address =   {New York, NY, USA},
  edition =   {1},
  isbn =      {0070428077, 9780070428072}
}

@Misc{nyt,
  title = {NEW NAVY DEVICE LEARNS BY DOING},
  month = {July 08},
  year =  {1958 (accessed Jul 9, 2016)},
  note =  {http://query.nytimes.com/gst/abstract.html?res=9D01E4D8173DE53BBC4053DFB1668383649EDE\&legacy=true}
}


text:
@misc{lyra2-spec,
  author    = {Marcos A. Simpl{\'{\i}}cio and
               Leonardo C. Almeida and
               Ewerton R. Andrade and
               Paulo C. F. dos Santos and
               Paulo S. L. M. Barreto},
  title     = {Lyra2: Password Hashing Scheme with improved security against time-memory
               trade-offs},
  journal   = {{IACR} Cryptology ePrint Archive},
  volume    = {2015},
  pages     = {136},
  year      = {2015},
  howpublished = {\url{http://www.lyra-kdf.net}}
}

@Misc{avx2,
  Title                    = {{Intel Architecture Instruction Set Extensions Programming Reference}},

  Author                   = {Intel},
  HowPublished             = {Technical Report},
  Note                     = {\url{https://software.intel.com/en-us/isa-extensions/}},
  year = {2014}
}

@misc{sponge,
  author = {Guido Bertoni and Joan Daemen and Micha\"el Peeters and Gilles Assche},
  title = {Cryptographic sponge functions},
  howpublished = {\url{http://sponge.noekeon.org/}},
  year = {2011},
}

@inproceedings{blake2b,
  author    = {Jean{-}Philippe Aumasson and
               Samuel Neves and
               Zooko Wilcox{-}O'Hearn and
               Christian Winnerlein},
  editor    = {Michael J. Jacobson Jr. and
               Michael E. Locasto and
               Payman Mohassel and
               Reihaneh Safavi{-}Naini},
  title     = {{BLAKE2:} Simpler, Smaller, Fast as {MD5}},
  booktitle = {Proceedings of the 11th International Conference on Applied Cryptography and Network Security (ACNS)},
  series    = {Lecture Notes in Computer Science},
  volume    = {7954},
  pages     = {119--135},
  publisher = {Springer},
  year      = {2013},
  url       = {http://dx.doi.org/10.1007/978-3-642-38980-1_8},
  doi       = {10.1007/978-3-642-38980-1_8},
  timestamp = {Tue, 25 Jun 2013 10:57:42 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/acns/AumassonNWW13},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

@article{chang2015performance,
  title={Performance Analysis of Some Password Hashing Schemes},
  author={Chang, Donghoon and Jati, Arpan and Mishra, Sweta and Sanadhya, Somitra Kumar},
  year={2015}
}

@misc{cryptoeprint:2015:678,
    author = {Thomas Pornin},
    title = {{Optimizing MAKWA on GPU and CPU}},
    howpublished = {Cryptology ePrint Archive, Report 2015/678},
    year = {2015},
    note = {\url{http://eprint.iacr.org/}},
}


text:
vcpkg_fail_port_install(ON_ARCH "arm" ON_TARGET "uwp")

vcpkg_check_linkage(ONLY_STATIC_LIBRARY)

vcpkg_from_github(
    OUT_SOURCE_PATH SOURCE_PATH
    REPO kibaamor/knet
    REF v1.0.2
    SHA512 fb101d10d3bb08e565618923a10bc39586a934ae562ba7241c079f781baaafbc511e0bd2de13db6263246dede5e602d578e1fbdf45c84a6fecc4d3ddad4735e9
    HEAD_REF master
)

vcpkg_configure_cmake(
    SOURCE_PATH ${SOURCE_PATH}
    PREFER_NINJA
    DISABLE_PARALLEL_CONFIGURE
    OPTIONS
        -DKNET_BUILD_EXAMPLE:BOOL=OFF
        -DKNET_BUILD_TEST:BOOL=OFF
)

vcpkg_install_cmake()
vcpkg_fixup_cmake_targets(CONFIG_PATH lib/cmake/knet TARGET_PATH share/knet)

vcpkg_copy_pdbs()

file(REMOVE_RECURSE "${CURRENT_PACKAGES_DIR}/debug/include")

file(INSTALL ${SOURCE_PATH}/LICENSE DESTINATION ${CURRENT_PACKAGES_DIR}/share/${PORT} RENAME copyright)

file(COPY ${CMAKE_CURRENT_LIST_DIR}/usage DESTINATION ${CURRENT_PACKAGES_DIR}/share/${PORT})

gha_license_id: NOASSERTION


text:
@ARTICLE{Johnson2014-st,
  title    = "Extension of Nakagawa \& Schielzeth's {R2GLMM} to random slopes
              models",
  author   = "Johnson, Paul Cd",
  abstract = "Nakagawa \& Schielzeth extended the widely used goodness-of-fit
              statistic R2 to apply to generalized linear mixed models (GLMMs).
              However, their R2GLMM method is restricted to models with the
              simplest random effects structure, known as random intercepts
              models. It is not applicable to another common random effects
              structure, random slopes models.I show that R2GLMM can be
              extended to random slopes models using a simple formula that is
              straightforward to implement in statistical software. This
              extension substantially widens the potential application of
              R2GLMM.",
  journal  = "Methods in ecology and evolution / British Ecological Society",
  volume   =  5,
  number   =  9,
  pages    = "944-946",
  month    =  sep,
  year     =  2014,
  url      = "http://dx.doi.org/10.1111/2041-210X.12225",
  keywords = "coefficient of determination; generalized linear mixed model;
              random regression; random slopes model",
  language = "en"
}

@ARTICLE{Kennedy1981-xu,
  title     = "Estimation with Correctly Interpreted Dummy Variables in
               Semilogarithmic Equations",
  author    = "Kennedy, Peter",
  journal   = "The American economic review",
  publisher = "American Economic Association",
  volume    =  71,
  number    =  4,
  year      =  1981,
  url       = "https://EconPapers.repec.org/RePEc:aea:aecrev:v:71:y:1981:i:4:p:801"
}

@ARTICLE{Giles2011-cv,
  title   = "Interpreting dummy variables in semi-logarithmic regression
             models: exact distributional results",
  author  = "Giles, David E",
  journal = "University of Victoria Department of Economics Econometrics
             Working Paper",
  number  =  1101,
  year    =  2011,
  url     = "http://web.uvic.ca/~dgiles/downloads/working_papers/ewp1101.pdf"
}

@ARTICLE{Christiansen2015-nb,
  title    = "Electricity consumption of medical plug loads in hospital
              laboratories: Identification, evaluation, prediction and
              verification",
  author   = "Christiansen, Nils and Kaltschmitt, Martin and Dzukowski, Frank
              and Isensee, Friedrich",
  abstract = "Evaluating the energy demand of heating, ventilation and air
              conditioning (HVAC) as well as lighting equipment through
              standardized calculation methods has become a self-evident
              measure for planning and optimizing non-residential buildings in
              recent years. For the case of hospitals however, information
              about the magnitude of electricity consumption caused by the vast
              amounts of medical equipment is still lacking. Not least due to
              the strongly growing use of such electrically operated devices in
              an increasingly complex environment, electricity has become the
              major energy cost driver in modern hospitals. Against this
              background this paper presents a model approach based on over
              33,500h of measurements within a modern University Medical Center
              of Hamburg/Germany to assess the time-dependent course as well as
              the weekly sum of the demand for electrical energy due to medical
              laboratory plug loads. This assessment method allows for
              approximating the electricity demand of the installed equipment
              as a supplement to the established prediction methods for the
              electricity demand of HVAC, lighting, etc. It was found that only
              a few plug load groups contribute the greater part of the total
              electrical energy demand. Cumulative load predictions for a full
              building were possible with an error of less than 6\%.",
  journal  = "Energy and Buildings",
  volume   =  107,
  pages    = "392-406",
  month    =  nov,
  year     =  2015,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778815302073",
  keywords = "Hospital energy consumption; Internal loads; Laboratory
              equipment; Medical equipment; Plug loads"
}

@ARTICLE{Gunay2016-ul,
  title    = "Modeling plug-in equipment load patterns in private office spaces",
  author   = "Gunay, H Burak and O'Brien, William and Beausoleil-Morrison, Ian
              and Gilani, Sara",
  abstract = "The uncertainty of plug-in office equipment choices and usage
              patterns is a major challenge in making proper design and control
              decisions by using building energy models. In this paper, the
              factors contributing to the plug-in equipment load patterns were
              investigated through an office equipment survey conducted with
              203 participants, and the concurrent motion sensor and plug load
              data gathered in ten private office spaces. Results indicate that
              over 75\% of the plug-in equipment electricity use in private
              offices takes place during unoccupied periods; and the plug load
              during the unoccupied periods exhibits a relationship with the
              duration of absence following departures. Drawing on these
              findings, this paper puts forward a data-driven model form to
              predict plug-in equipment load patterns in office spaces. The
              model is built on the plug-in equipment load patterns during five
              different time periods: (a) occupancy, (b) intermediate breaks,
              (c) weekday evenings, (d) weekends, and (e) vacations. The model
              inputs the predictions of an occupancy model and employs random
              sampling over the learned plug load patterns to generate plug
              load forecasts. The data gathered from the ten private offices
              were used to assess the accuracy and appropriateness of the model
              form. It was found that the models can accurately generate
              plug-in equipment load forecasts.",
  journal  = "Energy and Buildings",
  volume   =  121,
  pages    = "234-249",
  month    =  jun,
  year     =  2016,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778816301268",
  keywords = "Plug-in equipment loads; Office spaces; Occupant behavior;
              Building energy model; Office equipment"
}

@ARTICLE{Mahdavi2016-hm,
  title    = "Prediction of plug loads in office buildings: Simplified and
              probabilistic methods",
  author   = "Mahdavi, Ardeshir and Tahmasebi, Farhang and Kayalar, Mine",
  abstract = "To predict buildings' energy use, multiple systems and processes
              must be considered. Next to factors such as building fabric and
              construction, indoor environmental control systems, and weather
              conditions, the energy demand attributable to buildings' internal
              heat gains resulting from inhabitants, lighting, and equipment
              usage also needs to be addressed. Given this background, the
              present contribution focuses on plug loads in office buildings
              associated mainly with computers and peripherals. Using long-term
              observational data obtained from a continuously monitored office
              building in Vienna, we specifically explore the relationship
              between inhabitants' presence, installed power for equipment, and
              the resulting electrical energy use. The findings facilitate the
              formulation of both simplified and probabilistic office plug
              loads predictions methods. Thereby, the model evaluation results
              suggest that the non-stochastic model provides fairly reasonable
              predictions of annual energy use associated with plug loads.
              However, the stochastic plug load model -- together with a
              stochastic occupancy model -- outperforms the simplified model in
              predicting the plug loads peak and distribution.",
  journal  = "Energy and Buildings",
  volume   =  129,
  pages    = "322-329",
  month    =  oct,
  year     =  2016,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778816307071",
  keywords = "Occupancy; Plug loads; Equipment; Electrical energy use;
              Stochastic model; Non-stochastic method"
}

@ARTICLE{Menezes2014-ng,
  title    = "Estimating the energy consumption and power demand of small power
              equipment in office buildings",
  author   = "Menezes, A C and Cripps, A and Buswell, R A and Wright, J and
              Bouchlaghem, D",
  abstract = "Small power is a substantial energy end-use in office buildings
              in its own right, but also significantly contributes to internal
              heat gains. Technological advancements have allowed for higher
              efficiency computers, yet current working practices are demanding
              more out of digital equipment. Designers often rely on benchmarks
              to inform predictions of small power consumption, power demand
              and internal gains. These are often out of date and fail to
              account for the variability in equipment speciation and usage
              patterns in different offices. This paper details two models for
              estimating small power consumption in office buildings, alongside
              typical power demand profiles. The first model relies solely on
              the random sampling of monitored data, and the second relies on a
              `bottom-up' approach to establish likely power demand and
              operational energy use. Both models were tested through a blind
              validation demonstrating a good correlation between metered data
              and monthly predictions of energy consumption. Prediction ranges
              for power demand profiles were also observed to be representative
              of metered data with minor exceptions. When compared to current
              practices, which often rely solely on the use of benchmarks, both
              proposed methods provide an improved approach to predicting the
              operational performance of small power equipment in offices.",
  journal  = "Energy and Buildings",
  volume   =  75,
  pages    = "199-209",
  month    =  jun,
  year     =  2014,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778814001224",
  keywords = "Small power; Plug loads; Offices; Predictions; Estimates;
              Computers; Energy consumption; Power demand; Operational
              performance"
}

@ARTICLE{Guo2015-yo,
  title     = "Home Appliance Load Modeling From Aggregated Smart Meter Data",
  author    = "Guo, Z and Wang, Z J and Kashani, A",
  abstract  = "With recent developments in the infrastructure of smart meters
               and smart grid, more electric power data is available and allows
               real-time easy data access. Modeling individual home appliance
               loads is important for tasks such as non-intrusive load
               disaggregation, load forecasting, and demand response support.
               Previous methods usually require sub-metering individual
               appliances in a home separately to determine the appliance
               models, which may not be practical, since we may only be able to
               observe aggregated real power signals for the entire-home
               through smart meters deployed in the field. In this paper, we
               propose a model, named Explicit-Duration Hidden Markov Model
               with differential observations (EDHMM-diff), for detecting and
               estimating individual home appliance loads from aggregated power
               signals collected by ordinary smart meters. Experiments on
               synthetic data and real data demonstrate that the EDHMM-diff
               model and the specialized forward-backward algorithm can
               effectively model major home appliance loads.",
  journal   = "IEEE Transactions on Power Systems",
  publisher = "ieeexplore.ieee.org",
  volume    =  30,
  number    =  1,
  pages     = "254-262",
  month     =  jan,
  year      =  2015,
  url       = "http://dx.doi.org/10.1109/TPWRS.2014.2327041",
  keywords  = "domestic appliances;hidden Markov models;load forecasting;smart
               meters;smart power grids;aggregated smart meter data;demand
               response support;differential observations;electric power
               data;explicit-duration hidden Markov model;forward-backward
               algorithm;home appliance load modeling;home appliance loads;load
               forecasting;nonintrusive load disaggregation;smart
               grid;Computational modeling;Data models;Estimation;Hidden Markov
               models;Home appliances;Load modeling;Disaggregation;explicit
               duration hidden Markov model (HMM);forward-backward;load
               modeling"
}

@INPROCEEDINGS{Weiss2012-bs,
  title     = "Leveraging smart meter data to recognize home appliances",
  booktitle = "2012 {IEEE} International Conference on Pervasive Computing and
               Communications",
  author    = "Weiss, M and Helfenstein, A and Mattern, F and Staake, T",
  abstract  = "The worldwide adoption of smart meters that measure and
               communicate residential electricity consumption gives rise to
               the development of new energy efficiency services. Several
               particularly promising applications involve the disaggregation
               of individual appliances within a particular household in terms
               of their energy demand. In this paper we present an
               infrastructure and a set of algorithms that make use of smart
               meters together with smartphones to realize new energy
               efficiency services (such as itemized electricity bills or
               targeted energy saving advice). The smartphones, together with a
               novel filtering approach, much simplify the training process for
               appliances signature recognition. We also report on the
               performance of our system that was tested with 8 simultaneous
               devices, achieving recognition rates of 87\%.",
  publisher = "ieeexplore.ieee.org",
  pages     = "190-197",
  month     =  mar,
  year      =  2012,
  url       = "http://dx.doi.org/10.1109/PerCom.2012.6199866",
  keywords  = "domestic appliances;energy conservation;power engineering
               computing;smart phones;appliances signature recognition;energy
               demand;energy efficiency services;energy saving advice;filtering
               approach;home appliances recognition;itemized electricity
               bills;residential electricity consumption;smart meter data
               leveraging;smart phones;Databases;Electricity;Home
               appliances;Kernel;Power measurement;Sensors;Switches;electricity
               consumption;energy break down;energy monitoring;non-intrusive
               load monitoring;smart metering"
}

@INPROCEEDINGS{Liao2014-ux,
  title     = "Non-intrusive appliance load monitoring using low-resolution
               smart meter data",
  booktitle = "2014 {IEEE} International Conference on Smart Grid
               Communications ({SmartGridComm})",
  author    = "Liao, J and Elafoudi, G and Stankovic, L and Stankovic, V",
  abstract  = "We propose two algorithms for power load disaggregation at
               low-sampling rates (greater than 1sec): a low-complexity,
               supervised approach based on Decision Trees and an unsupervised
               method based on Dynamic Time Warping. Both proposed algorithms
               share common pre-classification steps. We provide reproducible
               algorithmic description and benchmark the proposed methods with
               a state-of-the-art Hidden Markov Model (HMM)-based approach.
               Experimental results using three US and three UK households,
               show that both proposed methods outperform the HMM-based
               approach and are capable of disaggregating a range of domestic
               loads even when the training period is very short.",
  pages     = "535-540",
  month     =  nov,
  year      =  2014,
  url       = "http://dx.doi.org/10.1109/SmartGridComm.2014.7007702",
  keywords  = "decision trees;domestic appliances;hidden Markov models;load
               management;smart meters;HMM-based approach;decision
               tree;domestic load;dynamic time warping;hidden Markov
               model;low-resolution smart meter data;low-sampling
               rate;nonintrusive appliance load monitoring;power load
               disaggregation;preclassification step;reproducible algorithmic
               description;unsupervised method;Accuracy;Feature
               extraction;Hidden Markov models;Home appliances;Image edge
               detection;Libraries;Training"
}

@ARTICLE{Chahine2011-kq,
  title    = "Electric Load Disaggregation in Smart Metering Using a Novel
              Feature Extraction Method and Supervised Classification",
  author   = "Chahine, Khaled and Drissi, Khalil El Khamlichi and Pasquier,
              Christophe and Kerroum, Kamal and Faure, Claire and Jouannet,
              Thierry and Michou, Michel",
  abstract = "Improving energy efficiency by monitoring household electrical
              consumption is of significant importance with the present-day
              climate change concerns. A solution for the electrical
              consumption management problem is the use of a nonintrusive
              appliance load monitoring system. This system captures the
              signals from the aggregate consumption, extracts the features
              from these signals and classifies the extracted features in order
              to identify the switched on appliances. This paper complements a
              novel feature extraction scheme presented in a previous work for
              load disaggregation with a comparative study of supervised
              classification methods. The objective of the current work is
              hence to make use of the feature extraction scheme to construct a
              database of signatures and then to compare different supervised
              learning methods for load classification. Preliminary results
              indicate high classification accuracy of all tested methods.",
  journal  = "Energy Procedia",
  volume   =  6,
  pages    = "627-632",
  month    =  jan,
  year     =  2011,
  url      = "http://www.sciencedirect.com/science/article/pii/S1876610211014834",
  keywords = "Matrix Pencil Method; Nonintrusive Appliance Load Monitoring;
              Supervised Learning; Power Saving; Smart Meters"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Perez2014-qt,
  title    = "Nonintrusive disaggregation of residential air-conditioning loads
              from sub-hourly smart meter data",
  author   = "Perez, Krystian X and Cole, Wesley J and Rhodes, Joshua D and
              Ondeck, Abigail and Webber, Michael and Baldea, Michael and
              Edgar, Thomas F",
  abstract = "The installation of smart meters has provided an opportunity to
              better analyze residential energy consumption and energy-related
              behaviors. Air-conditioning (A/C) use can be determined through
              non-intrusive load monitoring, which separates A/C cooling energy
              consumption from whole-house energy data. In this paper, a
              disaggregation technique is described and executed on 1-min smart
              meter data from 88 houses in Austin, TX, USA, from July 2012
              through June 2013. Nineteen houses were sub-metered to validate
              the accuracy of the disaggregation technique. The R2 value
              between the predicted and actual A/C energy use for the 19 houses
              was 0.90. The algorithm was then applied to all houses. On
              average, daily energy use from A/C increased by 25$\pm$11kWh
              between a mild temperature day of 15.5°C (60°F) and a hotter day
              of 31.5°C (89°F), with an 11kWh increase just during peak hours
              (14:00--20:00). Average time operated, number of cycles, and A/C
              fraction of energy were found to increase linearly with outdoor
              temperature up to 25°C (77°F); a plateau was detected at higher
              temperatures. The accuracy of A/C disaggregation on 5-min data
              was found to be comparable to 1-min data. However, 15-min data
              did not yield accurate results due to insufficient granularity.",
  journal  = "Energy and Buildings",
  volume   =  81,
  pages    = "316-325",
  month    =  oct,
  year     =  2014,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778814005131",
  keywords = "Nonintrusive load monitoring; Disaggregation; Residential energy;
              Air conditioning; Smart meter"
}

@ARTICLE{So2016-of,
  title     = "A high level method to disaggregate electricity for
               cluster-metered buildings",
  author    = "So, Nicholas and Richman, Russell",
  abstract  = "Many large institutions do not have a means to gauge electricity
               consumption for their campus building portfolios. The
               installation of utility meters is typically outside of the
               institution's budget. A multiple linear regression approach to
               estimating consumption for academic buildings is an ideal tool
               that balances performance and utility. Using 80 buildings from
               Ryerson University (Toronto) and the University of Toronto,
               significant building characteristics were identified that showed
               a strong linear relationship with electricity consumption. Four
               equations were created to represent the diversity in size of
               academic buildings on both campuses. Tested using
               cross-validation, the coefficient of variation of the RMSE for
               all models was 33\%, with a range of error between 20\% and
               43\%. The models were highly successful at predicting high-level
               electricity consumption at Ryerson University with an average
               error of 14.8\% for five building clusters. Using metered data
               from each cluster, raw estimates for individual buildings were
               adjusted to improve accuracy.",
  journal   = "Energy and Buildings",
  publisher = "Elsevier",
  volume    =  111,
  pages     = "351-368",
  month     =  jan,
  year      =  2016,
  url       = "http://www.sciencedirect.com/science/article/pii/S0378778815303844",
  keywords  = "Disaggregating electricity; Cluster-metered buildings; Multiple
               linear regression; Academic buildings; Electricity prediction"
}

@ARTICLE{Kalluri2016-ri,
  title    = "Applicability of using time series subsequences to study office
              plug load appliances",
  author   = "Kalluri, Balaji and Kamilaris, Andreas and Kondepudi, Sekhar and
              Kua, Harn Wei and Tham, Kwok Wai",
  abstract = "Energy management in offices requires efficient methods (e.g.
              non-intrusive load monitoring techniques, NILM) to monitor the
              large number of workstations and office appliances. The key
              purpose of this study is to ascertain the applicability of using
              time series subsequence data mining to study and classify the
              transient operations of typical appliances in an office. The
              approach involves discovering hidden subsequences (i.e. feature
              extraction) that are characteristic of individual appliance
              transient states, using an extension of Symbolic Aggregate
              approXimation (SAX). Such characteristic features are used to
              create a repository of rules to help supervised classification of
              aggregate time series measurements. It is one of the first
              studies to demonstrate the potential of classifying subsequence
              features into individual appliances and their states within large
              aggregate time series data using a ``Bag of Rules'' approach. The
              results indicate that distinct, characteristic patterns represent
              office appliances and their states, in the form of SAX grammar
              rules. These patterns can then be used for NILM with promising
              results. This ongoing study demonstrates SAX based time series
              subsequence mining as a proof-of-concept; not only to discover
              similarities presented by appliance events but also to
              demonstrate their applicability to disambiguate aggregate
              signatures in the context of office NILM.",
  journal  = "Energy and Buildings",
  volume   =  127,
  pages    = "399-410",
  month    =  sep,
  year     =  2016,
  url      = "http://www.sciencedirect.com/science/article/pii/S0378778816304546",
  keywords = "Office appliances; Office plug load dataset; Subsequence mining;
              Grammar induction; SAX; Motif discovery; Feature extraction;
              Characterization; Bag of Rules; Classification"
}

@ARTICLE{Norford1996-qk,
  title   = "Non-intrusive electrical load monitoring in commercial buildings
             based on steady-state and transient load-detection algorithms",
  author  = "Norford, Leslie K and Leeb, Steven B",
  journal = "Energy and Buildings",
  volume  =  24,
  pages   = "5l-64",
  year    =  1996,
  url     = "https://pdfs.semanticscholar.org/d6b1/43ad1c53a9c5263b62e5534ef899425a23bd.pdf"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Dinesh2016-cf,
  title    = "Residential Appliance Identification Based on Spectral
              Information of Low Frequency Smart Meter Measurements",
  author   = "Dinesh, C and Nettasinghe, B W and Godaliyadda, R I and
              Ekanayake, M P B and Ekanayake, J and Wijayakulasooriya, J V",
  abstract = "A nonintrusive load monitoring (NILM) method for residential
              appliances based on uncorrelated spectral components of an active
              power consumption signal is presented. This method utilizes the
              Karhunen Loéve expansion to breakdown the active power signal
              into subspace components (SCs) so as to construct a unique
              information rich appliance signature. Unlike existing NILM
              techniques that rely on multiple measurements at high sampling
              rates, this method works effectively with a single active power
              measurement taken at a low sampling rate. After constructing the
              signature data base, SC level power conditions were introduced to
              reduce the number of possible appliance combinations prior to
              applying the maximum a posteriori estimation. Then, an appliances
              matching algorithm was presented to identify the turned-on
              appliance combination in a given time window. After identifying
              the turned-on appliance combination, an energy estimation
              algorithm was introduced to disaggregate the energy contribution
              of each individual appliance in that combination. The proposed
              NILM method was validated by using two public databases: 1)
              tracebase; and 2) reference energy disaggregation data set. The
              presented results demonstrate the ability of the proposed method
              to accurately identify and disaggregate individual energy
              contributions of turned-on appliance combinations in real
              households.",
  journal  = "IEEE transactions on smart grid",
  volume   =  7,
  number   =  6,
  pages    = "2781-2792",
  month    =  nov,
  year     =  2016,
  url      = "http://dx.doi.org/10.1109/TSG.2015.2484258",
  keywords = "Karhunen-Loeve transforms;domestic appliances;maximum likelihood
              estimation;smart meters;Karhunen Loéve expansion;NILM method;SC
              level power conditions;active power consumption signal;active
              power measurement;energy contribution;energy estimation
              algorithm;low frequency smart meter measurements;maximum a
              posteriori estimation;nonintrusive load monitoring
              method;reference energy disaggregation data set;residential
              appliances;signature data base;subspace
              components;tracebase;turned-on appliance combination;uncorrelated
              spectral components;Databases;Frequency measurement;Home
              appliances;Monitoring;Power demand;Power measurement;Time-domain
              analysis;Appliances identification;energy
              disaggregate;nonintrusive load monitoring (NILM);smart grid;smart
              meter;uncorrelated spectral information"
}

@INPROCEEDINGS{Reinhardt2012-aq,
  title     = "On the accuracy of appliance identification based on distributed
               load metering data",
  booktitle = "2012 Sustainable Internet and {ICT} for Sustainability
               ({SustainIT})",
  author    = "Reinhardt, A and Baumann, P and Burgstahler, D and Hollick, M
               and Chonov, H and Werner, M and Steinmetz, R",
  abstract  = "Dynamic load management, i.e., allowing electricity utilities to
               remotely turn electric appliances in households on or off,
               represents a key element of the smart grid. Appliances should
               however only be disconnected from mains when no negative side
               effects, e.g., loss of data or thawing food, are incurred
               thereby. This motivates the use of appliance identification
               techniques, which determine the type of an attached appliance
               based on the continuous sampling of its power consumption. While
               various implementations based on different sampling resolutions
               have been presented in existing literature, the achievable
               classification accuracies have rarely been analyzed. We address
               this shortcoming and evaluate the accuracy of appliance
               identification based on the characteristic features of traces
               collected during the 24 hours of a day. We evaluate our
               algorithm using more than 1,000 traces of different electrical
               appliances' power consumptions. The results show that our
               approach can identify most of the appliances at high accuracy.",
  pages     = "1-9",
  month     =  oct,
  year      =  2012,
  url       = "https://ieeexplore.ieee.org/abstract/document/6388037/",
  keywords  = "domestic appliances;smart power grids;appliance
               identification;distributed load metering data;dynamic load
               management;electrical appliance power consumptions;electricity
               utilities;smart grid;thawing food;time 24
               hour;Accuracy;Computers;Feature extraction;Home appliances;Power
               demand;Program processors;Shape"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Lukacs2010-xz,
  title     = "Model selection bias and Freedman's paradox",
  author    = "Lukacs, Paul M and Burnham, Kenneth P and Anderson, David R",
  abstract  = "In situations where limited knowledge of a system exists and the
               ratio of data points to variables is small, variable selection
               methods can often be misleading. Freedman (Am Stat 37: 152--155,
               1983) demonstrated how common it is to select completely
               unrelated variables as highly ``significant'' when the number of
               data points is similar in magnitude to the number of variables.
               A new type of model averaging estimator based on model selection
               with Akaike's AIC is used with linear regression to investigate
               the problems of likely inclusion of …",
  journal   = "Annals of the Institute of Statistical Mathematics",
  publisher = "Springer",
  volume    =  62,
  number    =  1,
  pages     = "117",
  year      =  2010,
  url       = "https://link.springer.com/article/10.1007/s10463-009-0234-4"
}

@ARTICLE{Greven2010-sv,
  title     = "On the behaviour of marginal and conditional {AIC} in linear
               mixed models",
  author    = "Greven, Sonja and Kneib, Thomas",
  abstract  = "In linear mixed models, model selection frequently includes the
               selection of random effects. Two versions of the Akaike
               information criterion, aic, have been used, based either on the
               marginal or on the conditional distribution. We show that the
               marginal aic is not an asymptotically unbiased estimator of the
               Akaike information, and favours smaller models without random
               effects. For the conditional aic, we show that ignoring
               estimation uncertainty in the random effects covariance matrix,
               as is common practice, induces a bias that can lead to the
               selection of any random effect not predicted to be exactly zero.
               We derive an analytic representation of a corrected version of
               the conditional aic, which avoids the high computational cost
               and imprecision of available numerical approximations. An
               implementation in an R package (R Development Core Team, 2010)
               is provided. All theoretical results are illustrated in
               simulation studies, and their impact in practice is investigated
               in an analysis of childhood malnutrition in Zambia.",
  journal   = "Biometrika",
  publisher = "Oxford University Press",
  volume    =  97,
  number    =  4,
  pages     = "773-789",
  month     =  dec,
  year      =  2010,
  url       = "https://academic.oup.com/biomet/article-abstract/97/4/773/241321"
}

@ARTICLE{Vaida2005-mt,
  title     = "Conditional Akaike information for mixed-effects models",
  author    = "Vaida, Florin and Blanchard, Suzette",
  abstract  = "This paper focuses on the Akaike information criterion, AIC, for
               linear mixed-effects models in the analysis of clustered data.
               We make the distinction between questions regarding the
               population and questions regarding the particular clusters in
               the data. We show that the AIC in current use is not appropriate
               for the focus on clusters, and we propose instead the
               conditional Akaike information and its corresponding criterion,
               the conditional AIC, cAIC. The penalty term in cAIC is related
               to the effective degrees of freedom $\rho$ for a linear mixed
               model proposed by Hodges \& Sargent (2001); $\rho$ reflects an
               intermediate level of complexity between a fixed-effects model
               with no cluster effect and a corresponding model with fixed
               cluster effects. The cAIC is defined for both maximum likelihood
               and residual maximum likelihood estimation. A pharmacokinetics
               data application is used to illuminate the distinction between
               the two inference settings, and to illustrate the use of the
               conditional AIC in model selection.",
  journal   = "Biometrika",
  publisher = "Oxford University Press",
  volume    =  92,
  number    =  2,
  pages     = "351-370",
  month     =  jun,
  year      =  2005,
  url       = "https://academic.oup.com/biomet/article-abstract/92/2/351/233128"
}

@ARTICLE{Schwarz1978-hj,
  title     = "Estimating the Dimension of a Model",
  author    = "Schwarz, Gideon",
  abstract  = "Project Euclid - mathematics and statistics online",
  journal   = "Annals of statistics",
  publisher = "Institute of Mathematical Statistics",
  volume    =  6,
  number    =  2,
  pages     = "461-464",
  month     =  mar,
  year      =  1978,
  url       = "https://projecteuclid.org/euclid.aos/1176344136",
  keywords  = "Dimension; Akaike information criterion; asymptotics",
  language  = "en"
}

@ARTICLE{Bates2015-zw,
  title    = "Fitting Linear {Mixed-Effects} Models Using lme4",
  author   = "Bates, Douglas and M{\"a}chler, Martin and Bolker, Ben and
              Walker, Steve",
  abstract = "Maximum likelihood or restricted maximum likelihood (REML)
              estimates of the parameters in linear mixed-effects models can be
              determined using the lmer function in the lme4 package for R. As
              for most model-fitting functions in R, the model is described in
              an lmer call by a formula, in this case including both fixed- and
              random-effects terms. The formula and data together determine a
              numerical representation of the model from which the profiled
              deviance or the profiled REML criterion can be evaluated as a
              function of some of the model parameters. The appropriate
              criterion is optimized, using one of the constrained optimization
              functions in R, to provide the parameter estimates. We describe
              the structure of the model, the steps in evaluating the profiled
              deviance or REML criterion, and the structure of classes or types
              that represents such a model. Sufficient detail is included to
              allow specialization of these structures by users who wish to
              write functions to fit specialized linear mixed models, such as
              models incorporating pedigrees or smoothing splines, that are not
              easily expressible in the formula language used by lmer.",
  journal  = "Journal of Statistical Software, Articles",
  volume   =  67,
  number   =  1,
  pages    = "1-48",
  year     =  2015,
  url      = "https://www.jstatsoft.org/v067/i01",
  keywords = "sparse matrix methods; linear mixed models; penalized least
              squares; Cholesky decomposition"
}

@ARTICLE{Nakagawa2013-zc,
  title     = "A general and simple method for obtaining {R2} from generalized
               linear mixed-effects models",
  author    = "Nakagawa, S and Schielzeth, H",
  abstract  = "The use of both linear and generalized linear mixed-effects
               models (LMMs and GLMMs) has become popular not only in social
               and medical sciences, but also in biological sciences,
               especially in the field of ecology and evolution. Information
               criteria, such as Akaike Information Criterion (AIC), are
               usually presented as model comparison tools for mixed- effects
               models.",
  journal   = "Methods in ecology and evolution / British Ecological Society",
  publisher = "Wiley Online Library",
  year      =  2013,
  url       = "http://onlinelibrary.wiley.com/doi/10.1111/j.2041-210x.2012.00261.x/full"
}

@ARTICLE{Burnham2004-cr,
  title     = "Multimodel Inference: Understanding {AIC} and {BIC} in Model
               Selection",
  author    = "Burnham, Kenneth P and Anderson, David R",
  abstract  = "The model selection literature has been generally poor at
               reflecting the deep foundations of the Akaike information
               criterion (AIC) and at making appropriate comparisons to the
               Bayesian information criterion (BIC). There is a clear
               philosophy, a sound criterion based in information theory, and a
               rigorous statistical foundation for AIC. AIC can be justified as
               Bayesian using a ?savvy? prior on models that is a function of
               sample size and the number of model parameters. Furthermore, BIC
               can be derived as a non-Bayesian result. Therefore, arguments
               about using AIC versus BIC for model selection cannot be from a
               Bayes versus frequentist perspective. The philosophical context
               of what is assumed about reality, approximating models, and the
               intent of model-based inference should determine whether AIC or
               BIC is used. Various facets of such multimodel inference are
               presented here, particularly methods of model averaging.",
  journal   = "Sociological methods \& research",
  publisher = "SAGE Publications Inc",
  volume    =  33,
  number    =  2,
  pages     = "261-304",
  month     =  nov,
  year      =  2004,
  url       = "https://doi.org/10.1177/0049124104268644"
}

@ARTICLE{Burnham2002-vs,
  title     = "Evaluation of some random effects methodology applicable to bird
               ringing data",
  author    = "Burnham, Kenneth P and White, Gary C",
  abstract  = "Existing models for ring recovery and recapture data analysis
               treat temporal variations in annual survival probability (S) as
               fixed effects. Often there is no explainable structure to the
               temporal variation in S 1 , ? , S k ; random effects can then be
               a useful model: Si = E(S) + k i . Here, the temporal variation
               in survival probability is treated as random with average value
               E( k 2 ) = $\sigma$ 2 . This random effects model can now be fit
               in program MARK. Resultant inferences include point and interval
               estimation for process variation, $\sigma$ 2 , estimation of
               E(S) and var(?(S)) where the latter includes a component for
               $\sigma$ 2 as well as the traditional component for v ar(S|S).
               Furthermore, the random effects model leads to shrinkage
               estimates, S i , as improved (in mean square error) estimators
               of Si compared to the MLE, S i , from the unrestricted
               time-effects model. Appropriate confidence intervals based on
               the S i are also provided. In addition, AIC has been generalized
               to random effects models. This paper presents results of a Monte
               Carlo evaluation of inference performance under the simple
               random effects model. Examined by simulation, under the simple
               one group Cormack-Jolly-Seber (CJS) model, are issues such as
               bias of $\sigma$ 2 , confidence interval coverage on $\sigma$ 2
               , coverage and mean square error comparisons for inference about
               Si based on shrinkage versus maximum likelihood estimators, and
               performance of AIC model selection over three models: S i = S
               (no effects), Si = E(S) + k i (random effects), and S 1 , ? , S
               k (fixed effects). For the cases simulated, the random effects
               methods performed well and were uniformly better than fixed
               effects MLE for the S i .",
  journal   = "Journal of applied statistics",
  publisher = "Taylor \& Francis",
  volume    =  29,
  number    = "1-4",
  pages     = "245-264",
  month     =  jan,
  year      =  2002,
  url       = "https://doi.org/10.1080/02664760120108755"
}

@BOOK{Burnham2003-hn,
  title     = "Model Selection and Multimodel Inference: A Practical
               {Information-Theoretic} Approach",
  author    = "Burnham, Kenneth P and Anderson, David R",
  abstract  = "We wrote this book to introduce graduate students and research
               workers in various scienti?c disciplines to the use of
               information-theoretic approaches in the analysis of empirical
               data. These methods allow the data-based selection of a ``best''
               model and a ranking and weighting of the remaining models in a
               pre-de?ned set. Traditional statistical inference can then be
               based on this selected best model. However, we now emphasize
               that information-theoretic approaches allow formal inference to
               be based on more than one model (m- timodel inference). Such
               procedures lead to more robust inferences in many cases, and we
               advocate these approaches throughout the book. The second
               edition was prepared with three goals in mind. First, we have
               tried to improve the presentation of the material. Boxes now
               highlight ess- tial expressions and points. Some reorganization
               has been done to improve the ?ow of concepts, and a new chapter
               has been added. Chapters 2 and 4 have been streamlined in view
               of the detailed theory provided in Chapter 7. S- ond, concepts
               related to making formal inferences from more than one model
               (multimodel inference) have been emphasized throughout the book,
               but p- ticularly in Chapters 4, 5, and 6. Third, new technical
               material has been added to Chapters 5 and 6. Well over 100 new
               references to the technical literature are given. These changes
               result primarily from our experiences while giving several
               seminars, workshops, and graduate courses on material in the
               ?rst e- tion.",
  publisher = "Springer Science \& Business Media",
  month     =  dec,
  year      =  2003,
  url       = "https://market.android.com/details?id=book-fT1Iu-h6E-oC",
  language  = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Symonds2011-fi,
  title     = "A brief guide to model selection, multimodel inference and model
               averaging in behavioural ecology using Akaike's information
               criterion",
  author    = "Symonds, Matthew R E and Moussalli, Adnan",
  abstract  = "Akaike's information criterion (AIC) is increasingly being used
               in analyses in the field of ecology. This measure allows one to
               compare and rank multiple competing models and to estimate which
               of them best approximates the ``true'' process underlying the
               biological …",
  journal   = "Behavioral ecology and sociobiology",
  publisher = "Springer",
  volume    =  65,
  number    =  1,
  pages     = "13-21",
  year      =  2011,
  url       = "https://link.springer.com/article/10.1007/s00265-010-1037-6"
}

@ARTICLE{Muller2013-pc,
  title         = "Model Selection in Linear Mixed Models",
  author        = "M{\"u}ller, Samuel and Scealy, J L and Welsh, A H",
  abstract      = "Linear mixed effects models are highly flexible in handling
                   a broad range of data types and are therefore widely used in
                   applications. A key part in the analysis of data is model
                   selection, which often aims to choose a parsimonious model
                   with other desirable properties from a possibly very large
                   set of candidate statistical models. Over the last 5-10
                   years the literature on model selection in linear mixed
                   models has grown extremely rapidly. The problem is much more
                   complicated than in linear regression because selection on
                   the covariance structure is not straightforward due to
                   computational issues and boundary problems arising from
                   positive semidefinite constraints on covariance matrices. To
                   obtain a better understanding of the available methods,
                   their properties and the relationships between them, we
                   review a large body of literature on linear mixed model
                   selection. We arrange, implement, discuss and compare model
                   selection methods based on four major approaches:
                   information criteria such as AIC or BIC, shrinkage methods
                   based on penalized loss functions such as LASSO, the Fence
                   procedure and Bayesian techniques.",
  month         =  jun,
  year          =  2013,
  url           = "http://arxiv.org/abs/1306.2427",
  archivePrefix = "arXiv",
  primaryClass  = "stat.ME",
  eprint        = "1306.2427"
}

@INCOLLECTION{Akaike1998-hd,
  title     = "Information Theory and an Extension of the Maximum Likelihood
               Principle",
  booktitle = "Selected Papers of Hirotugu Akaike",
  author    = "Akaike, Hirotogu",
  abstract  = "In this paper it is shown that the classical maximum likelihood
               principle can be considered to be a method of asymptotic
               realization of an optimum estimate with respect to a very
               general information theoretic criterion. This observation shows
               an extension of the principle to provide answers to many
               practical problems of statistical model fitting.",
  publisher = "Springer, New York, NY",
  pages     = "199-213",
  series    = "Springer Series in Statistics",
  year      =  1998,
  url       = "https://link.springer.com/chapter/10.1007/978-1-4612-1694-0_15",
  language  = "en"
}


text:
SUMMARY = "Check for host in reset to disable the NCSI iface"
DESCRIPTION = "If the host is in reset, the NCSI NIC will not be \
               available, so this will manually disable the NIC"

FILESEXTRAPATHS:prepend := "${THISDIR}/${BPN}:"

PV = "1.0"

LICENSE = "Apache-2.0"
LIC_FILES_CHKSUM = "file://${INTELBASE}/COPYING.apache-2.0;md5=34400b68072d710fecd0a2940a0d1658"

SRC_URI = "\
    file://check-for-host-in-reset \
    file://${BPN}.service \
    "

RDEPENDS:${PN} += "bash"

inherit obmc-phosphor-systemd

SYSTEMD_SERVICE:${PN} += "${BPN}.service"

do_install() {
    install -d ${D}${bindir}
    install -m 0755 ${WORKDIR}/check-for-host-in-reset ${D}/${bindir}/check-for-host-in-reset

}

repository: Intel-BMC/openbmc

repo_name: Intel-BMC/openbmc

gha_language: Python


text:
require ${PN}.inc

LICENSE = "LGPLv2"
LIC_FILES_CHKSUM = "file://license.txt;md5=6db3822fc7512e83087ba798da013692"

SRC_URI = "http://ftp.postgresql.org/pub/odbc/versions/src/${BPN}-${PV}.tar.gz \
    file://psqlodbc-remove-some-checks-for-cross-compiling.patch \
    file://psqlodbc-donot-use-the-hardcode-libdir.patch \
    file://psqlodbc-fix-for-ptest-support.patch \
    file://run-ptest \
"

SRC_URI[md5sum] = "4c6e0b22187d7bb1c998ffac89e50f6b"
SRC_URI[sha256sum] = "9521f328bf28aaaf5c8488dc89792b614f9d6271742c0baf9bb41c97537764a8"

repository: ni/meta-openembedded

repo_name: ni/meta-openembedded

branch_name: refs/heads/nilrt/master/hardknott

gha_language: BitBake


text:
@article{hwang_association_2020,
	title = {Association between {FDA} and {EMA} expedited approval programs and therapeutic value of new medicines: retrospective cohort study},
	volume = {371},
	copyright = {© Author(s) (or their employer(s)) 2019. Re-use permitted under CC                 BY-NC. No commercial re-use. See rights and permissions. Published by                 BMJ.. http://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.},
	issn = {1756-1833},
	shorttitle = {Association between {FDA} and {EMA} expedited approval programs and therapeutic value of new medicines},
	url = {https://www.bmj.com/content/371/bmj.m3434},
	doi = {10.1136/bmj.m3434},
	abstract = {Objective To characterize the therapeutic value of new drugs approved by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) and the association between these ratings and regulatory approval through expedited programs.
Design Retrospective cohort study.
Setting New drugs approved by the FDA and EMA between 2007 and 2017, with follow-up through 1 April 2020.
Data sources Therapeutic value was measured using ratings of new drugs by five independent organizations (Prescrire and health authorities of Canada, France, Germany, and Italy).
Main outcome measures Proportion of new drugs rated as having high therapeutic value; association between high therapeutic value rating and expedited status.
Results From 2007 through 2017, the FDA and EMA approved 320 and 268 new drugs, respectively, of which 181 (57\%) and 39 (15\%) qualified for least one expedited program. Among 267 new drugs with a therapeutic value rating, 84 (31\%) were rated as having high therapeutic value by at least one organization. Compared with non-expedited drugs, a greater proportion of expedited drugs were rated as having high therapeutic value among both FDA approvals (45\% (69/153) v 13\% (15/114); P{\textless}0.001) and EMA approvals (67\% (18/27) v 27\% (65/240); P{\textless}0.001). The sensitivity and specificity of expedited program for a drug being independently rated as having high therapeutic value were 82\% (95\% confidence interval 72\% to 90\%) and 54\% (47\% to 62\%), respectively, for the FDA, compared with 25.3\% (16.4\% to 36.0\%) and 90.2\% (85.0\% to 94.1\%) for the EMA.
Conclusions Less than a third of new drugs approved by the FDA and EMA over the past decade were rated as having high therapeutic value by at least one of five independent organizations. Although expedited drugs were more likely than non-expedited drugs to be highly rated, most expedited drugs approved by the FDA but not the EMA were rated as having low therapeutic value.},
	language = {en},
	urldate = {2020-11-27},
	journal = {BMJ},
	author = {Hwang, Thomas J. and Ross, Joseph S. and Vokinger, Kerstin N. and Kesselheim, Aaron S.},
	month = oct,
	year = {2020},
	pmid = {33028575},
	file = {Full Text PDF:C\:\\Users\\pdanio\\Zotero\\storage\\2WLM8HCV\\Hwang et al. - 2020 - Association between FDA and EMA expedited approval.pdf:application/pdf;Snapshot:C\:\\Users\\pdanio\\Zotero\\storage\\WA6L3HVC\\bmj.html:text/html}
}

repository: pdanio/academic-kickstart

repo_name: pdanio/academic-kickstart


text:
@misc{driscollCrashCourseMatlab2003,
 author = {Driscoll, Tobin A},
 publisher = {Department of Mathematical Sciences, University of Delaware, Newark łdots},
 title = {A Crash Course in Matlab},
 year = {2003}
}

repository: tobydriscoll/academic-kickstart

repo_name: tobydriscoll/academic-kickstart


text:
SECTION = "devel/chicken"
DESCRIPTION = "Library for writing text-based user interfaces"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://termbox.meta;md5=d8861d899f3893089503c52cc5c8d816"

SRC_URI = "http://code.call-cc.org/egg-tarballs/4/termbox/termbox-${PV}.tar.gz"

SRC_URI[md5sum] = "85b3d8c4d6facbe034d95f2560a48f51"
SRC_URI[sha256sum] = "9b7f8829eb309f3669db06c85ce7c5e4cec02fac40040cdea4ff48fb597a96a4"

S = "${WORKDIR}/termbox-${PV}"

inherit chicken_install

BBCLASSEXTEND = "cross crosssdk nativesdk"

repository: OSSystems/meta-chicken

repo_name: OSSystems/meta-chicken