text:
(function(ava) {
ava.NewCard = {}
ava.NewCard.controller = function(props) {
	if (!ava.isLoggedIn()) {
		return m.route("/login?r=" + encodeURIComponent(window.location.search))
	}
	var ctrl = this
	var saveBtn = function() {
		return document.getElementById("card-save-btn")
	}
	var cancelBtn = function() {
		return document.getElementById("card-cancel-btn")
	}
	var errorHolder = function() {
		return document.getElementById("card-error")
	}
	var cardNumberHolder = function() {
		return document.getElementById("card-number")
	}
	var cardExpiryHolder = function() {
		return document.getElementById("card-expiry")
	}
	var cardCVCHolder = function() {
		return document.getElementById("card-cvc")
	}
	ctrl.saveCard = function(ev) {
		ev.preventDefault()
		if (ctrl.props.saving()) {
			return
		}
		ctrl.save()
		ctrl.props.error(ctrl.vm.validateFields())
		if (!!ctrl.props.error()) {
			ctrl.saveComplete()
			return
		}
		ctrl.props.card().save().then(function(data) {
			m.route("/profile")
			m.redraw()
		}, function(err) {
			ctrl.props.error(err.message)
			ctrl.saveComplete()
		})
	}
	ctrl.saveAgain = function() {
		var deferred = m.deferred()
		ctrl.saveStripe().then(function(resp) {
			_this.brand(resp.card.brand)
			var data = {
				UserID: parseInt(cookie.getItem("id")),
				StripeToken: resp.id,
				CardholderName: resp.card.name,
				ExpMonth: resp.card.exp_month,
				ExpYear: resp.card.exp_year,
				Brand: _this.brand(),
				Last4: resp.card.last4,
				AddressZip: _this.zip5()
			}
			m.request({
				method: "POST",
				url: "/api/cards.json",
				data: data
			}).then(function(data) {
				deferred.resolve(data)
			}, function(err) {
				deferred.reject(new Error(err.Msg))
			})
		}, function(err) {
			deferred.reject(err)
		})
		return deferred.promise
	}
	ctrl.saveStripe = function() {
		var deferred = m.deferred()
		Stripe.card.createToken({
			number: _this.number(),
			cvc: _this.cvc(),
			exp: _this.expiry(),
			name: _this.cardholderName(),
			address_zip: _this.zip5()
		}, function(status, response) {
			if (response.error) {
				return deferred.reject(new Error(response.error.message))
			}
			deferred.resolve(response)
		})
		return deferred.promise
	}
	ctrl.save = function() {
		ctrl.props.saving(true)
		ctrl.props.savingText("Saving...")
		cancelBtn().classList.add("hidden")
		errorHolder().classList.add("hidden")
	}
	ctrl.saveComplete = function() {
		ctrl.props.saving(false)
		cancelBtn().classList.remove("hidden")
		ctrl.props.savingText("Save")
		if (!!ctrl.props.error()) {
			errorHolder().innerText = ctrl.props.error()
			errorHolder().classList.remove("hidden")
		} else {
			errorHolder().classList.add("hidden")
		}
	}
	ctrl.validateFields = function() {
		var card = ctrl.props.card
		if (Stripe.card.validateCardNumber(card.number())) {
			cardNumberHolder().classList.remove("has-error")
		} else {
			cardNumberHolder().classList.add("has-error")
			return "Card number is invalid."
		}
		if (Stripe.card.validateExpiry(card.expiry())) {
			cardExpiryHolder().classList.remove("has-error")
		} else {
			cardExpiryHolder().classList.add("has-error")
			return "Card expiration is invalid."
		}
		if (Stripe.card.validateCVC(card.cvc())) {
			cardCVCHolder().classList.remove("has-error")
		} else {
			cardCVCHolder().classList.add("has-error")
			return "Card CVC is invalid. This is the 3 or 4 digit security code."
		}
		return ""
	}
	props = props || {}
	ctrl.props = {
		error: m.prop(""),
		saving: m.prop(false),
		savingText: m.prop("Save"),
		card: {
			id: m.prop(props.id || 0),
			cardholderName: m.prop(props.cardholderName || ""),
			number: m.prop(props.number || ""),
			expMonth: m.prop(props.expMonth || ""),
			expYear: m.prop(props.expYear || ""),
			expiry: m.prop(props.expiry || ""),
			cvc: m.prop(props.cvc || ""),
			zip5: m.prop(props.zip5 || ""),
			brand: m.prop(""),
			last4: m.prop(props.last4 || "")
		}
	}
	if ((ctrl.props.card.expMonth()+ctrl.props.expYear()).length > 0) {
		if (ctrl.props.card.expiry().length === 0) {
			var x = ctrl.props.card.expMonth() + " / " + ctrl.props.expYear()
			ctrl.props.card.expiry(x)
		}
	}
}
ava.NewCard.view = function(ctrl) {
	return m(".body", [
		m.component(ava.Header),
		ava.NewCard.addView(ctrl),
		m.component(ava.Footer)
	])
}
ava.NewCard.addView = function(ctrl) {
	cformdata = [
		{field:"number", ph: "4444 0000 0000 1234", txt: "Card number"},
		{field:"expiry", ph: "01 / 2017", txt: "Expires"},
		{field:"cvc", ph: "123", txt: "CVC"},
		{field:"cardholderName", ph: "Cardholder name", txt: "Cardholder name"},
		{field:"zip5", ph: "90210", txt: "Billing Zip"},
	]
	var formfields = cformdata.map(function(fd) {
		return m("#card-"+fd.field+".form-group", [
			m("label.col-md-3.control-label", fd.txt),
			m(".col-md-9", [
				m("input", {
					class: "form-control",
					type: "text",
					placeholder: fd.ph,
					onchange: m.withAttr("value", ctrl.props.card[fd.field]),
					value: ctrl.props.card[fd.field]()
				})
			])
		])
	})
	return m("#full.container", [
		m(".row.margin-top-sm", m(".col-md-12", m("h1", "Add Card"))),
		m(".row margin-top-sm", [
			m("form.col-md-7.card", [
				m("div", {
					id: "card-error",
					class: "alert alert-danger hidden"
				}, ctrl.props.error()),
				m(".form-horizontal", formfields),
				m(".text-right", [
					m("a", {
						id: "card-cancel-btn",
						class: "btn btn-sm",
						href: "/profile",
						config: m.route
					}, "Cancel"),
					m("input", {
						id: "card-save-btn",
						type: "submit",
						class: "btn btn-primary btn-sm btn-collection",
						value: ctrl.props.savingText(),
						onclick: ctrl.saveCard,
						onsubmit: ctrl.saveCard
					})
				])
			])
		])
	])
}
})(!window.ava ? window.ava={} : window.ava);


text:
@misc{menichinelli_openp2pdesign/openmetadesign:_2019,
 abstract = {A platform for the collaborative design and discussion of collaborative design processes.},
 author = {Menichinelli, Massimo},
 doi = {10.5281/zenodo.2597616},
 month = {March},
 publisher = {Zenodo},
 shorttitle = {openp2pdesign/OpenMetaDesign},
 title = {openp2pdesign/OpenMetaDesign: v1.0: Version tested with users on 16/10/2018},
 url = {https://zenodo.org/record/2597616#.XJAAFkRKgb0},
 urldate = {2019-03-18},
 year = {2019}
}

license: MIT

license_type: permissive

branch_name: refs/heads/master

gha_license_id: MIT

extension: bib


text:
@misc{Geyer2007,
  author = "Geyer, C. J.",
  title = "Stat 5102 Notes: Fisher Information and Confidence Intervals Using Maximum Likelihood",
  year = "2007",
  month = "March",
  howpublished = "\url{https://www.stat.umn.edu/geyer/s06/5102/notes/fish.pdf}"
}

@book{CasellaBerger2002,
  author = "Casella, G. {\&} Berger, R. L.",
  title = "Statistical Inference",
  year = "2002",
  publisher = "Thomson Learning"
}

license: Unlicense

gha_license_id: Unlicense

gha_language: TeX


text:
var assert = require('assert');
var ezmq = require('../');
var protoEvent = require('./ezmqtestutils.js');

function subCallback(ezmqEvent) {}

function subTopicCallback(topic, ezmqEvent) {}

var ezmqAPI = new ezmq.EZMQAPI();
ezmqAPI.initialize();
var ip = 'localhost';
var port = 5562;
var ezmqSub = new ezmq.EZMQSubscriber(ip, port, subCallback, subTopicCallback);

describe('#start()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.start(), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#subscribe()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.subscribe(), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#subscribeOnTopic()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.subscribe('topic'), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#subscribeOnTopicList()', function() {
    it('should return EZMQ_OK', function() {
        var topicList = ['Topic1', 'Topic2'];
        assert.equal(ezmqSub.subscribe(topicList), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#subscribeSecured()', function() {
    it('should return EZMQ_OK', function() {
        var clientSecretKey = "";
        var clientPublicKey = "";
        var serverPublicKey = "";
        try {
            assert.equal(ezmqSub.setClientKeys(clientSecretKey, clientPublicKey), ezmq.EZMQErrorCode.EZMQ_OK);
            assert.equal(ezmqSub.setServerPublicKey(serverPublicKey), ezmq.EZMQErrorCode.EZMQ_OK);
        } catch (err) {}
        assert.equal(ezmqSub.start(), ezmq.EZMQErrorCode.EZMQ_OK);
        assert.equal(ezmqSub.subscribe(), ezmq.EZMQErrorCode.EZMQ_OK);
        assert.equal(ezmqSub.subscribeWithIPPort(ip, port, "topic"), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#unSubscribe()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.unSubscribe(), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#unSubscribeOnTopic()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.unSubscribe('topic'), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

describe('#unSubscribeOnTopicList()', function() {
    it('should return EZMQ_OK', function() {
        var topicList = ['Topic1', 'Topic2'];
        assert.equal(
            ezmqSub.unSubscribe(topicList),
            ezmq.EZMQErrorCode.EZMQ_OK
        );
    });
});

describe('#getIp()', function() {
    it('should return 5562', function() {
        assert.equal(ezmqSub.getIp(), ip);
    });
});

describe('#getPort()', function() {
    it('should return 5562', function() {
        assert.equal(ezmqSub.getPort(), port);
    });
});

describe('#stop()', function() {
    it('should return EZMQ_OK', function() {
        assert.equal(ezmqSub.stop(), ezmq.EZMQErrorCode.EZMQ_OK);
    });
});

repository: mgjeong/protocol-ezmq-node

repo_name: mgjeong/protocol-ezmq-node

extension: js


text:
%%% -*-BibTeX-*-
@inproceedings{Multiexit2010Wang,
   author    = {Peng Wang and Chunhua Shen and Hong Zheng and Zhang Ren},
   title     = {Training a multi-exit cascade with linear asymmetric classification for efficient object detection},
   booktitle = {IEEE International Conference on Image Processing (ICIP'10)},
   year      = {2010},
   pages     = {61--64},
   volume    = {},
   address   = {Hong Kong},
   month     = {October},
   publisher = {IEEE Press},
   url       = {},
   pdf       = {},
   venue     = {ICIP}
}


text:
# SPDX-License-Identifier: MIT

DESCRIPTION = "Linux ONIE tools"
LICENSE = "MIT"
SECTION = "base"
LIC_FILES_CHKSUM = "file://${COREBASE}/meta/COPYING.MIT;md5=3da9cfbcb788c80a0384361b4de20420"

#FIXME add support for ARM tools
#RDEPENDS_onie-tools = "bash ${@oe.utils.conditional('ARCH', 'u-boot-arch', ' u-boot-fw-utils', '', d)}"

SRC_URI = " \
  file://common-blkdev \
  file://onie-install \
  file://onie-uninstall \
  file://onie-update \
  file://onie-rescue \
"

S = "${WORKDIR}"

do_install () {
  install -m 0755 -d ${D}${libdir}/onie/
  install -m 0755 common-blkdev ${D}${libdir}/onie/
  install -m 0755 -d ${D}${bindir}
  install -m 0755 onie-install ${D}${bindir}
  install -m 0755 onie-uninstall ${D}${bindir}
  install -m 0755 onie-update ${D}${bindir}
  install -m 0755 onie-rescue ${D}${bindir}
}

FILES_${PN} = "/"

repository: NetworkGradeLinux/meta-mion

repo_name: NetworkGradeLinux/meta-mion

branch_name: refs/heads/dunfell

gha_language: C

extension: bb


text:
package fake

import (
	"testing"
)

func TestSetLang(t *testing.T) {
	err := SetLang("ru")
	if err != nil {
		t.Error("SetLang should successfully set lang")
	}

	err = SetLang("sd")
	if err == nil {
		t.Error("SetLang with nonexistent lang should return error")
	}
}

func TestFakerRuWithoutCallback(t *testing.T) {
	SetLang("ru")
	EnFallback(false)
	brand := Brand()
	if brand != "" {
		t.Error("Fake call with no samples should return blank string")
	}
}

func TestFakerRuWithCallback(t *testing.T) {
	SetLang("ru")
	EnFallback(true)
	brand := Brand()
	if brand == "" {
		t.Error("Fake call for name with no samples with callback should not return blank string")
	}
}

// TestConcurrentSafety runs fake methods in multiple go routines concurrently.
// This test should be run with the race detector enabled.
func TestConcurrentSafety(t *testing.T) {
	workerCount := 10
	doneChan := make(chan struct{})

	for i := 0; i < workerCount; i++ {
		go func() {
			for j := 0; j < 1000; j++ {
				FirstName()
				LastName()
				Gender()
				FullName()
				Day()
				Country()
				Company()
				Industry()
				Street()
			}
			doneChan <- struct{}{}
		}()
	}

	for i := 0; i < workerCount; i++ {
		<-doneChan
	}
}

repository: icrowley/fake

repo_name: icrowley/fake

gha_language: Go

extension: go


text:
package sched

import (
	"fmt"
	"image"
	"image/color"
	"image/png"
	"io"
	"time"

	"bosun.org/_third_party/github.com/MiniProfiler/go/miniprofiler"
	"bosun.org/_third_party/github.com/ajstarks/svgo"
	"bosun.org/_third_party/github.com/bradfitz/slice"
	"bosun.org/_third_party/github.com/vdobler/chart"
	"bosun.org/_third_party/github.com/vdobler/chart/imgg"
	"bosun.org/_third_party/github.com/vdobler/chart/svgg"
	"bosun.org/cmd/bosun/expr"
)

var chartColors = []color.Color{
	color.NRGBA{0xe4, 0x1a, 0x1c, 0xff},
	color.NRGBA{0x37, 0x7e, 0xb8, 0xff},
	color.NRGBA{0x4d, 0xaf, 0x4a, 0xff},
	color.NRGBA{0x98, 0x4e, 0xa3, 0xff},
	color.NRGBA{0xff, 0x7f, 0x00, 0xff},
	color.NRGBA{0xa6, 0x56, 0x28, 0xff},
	color.NRGBA{0xf7, 0x81, 0xbf, 0xff},
	color.NRGBA{0x99, 0x99, 0x99, 0xff},
}

// Autostyle styles a chart series.
func Autostyle(i int) chart.Style {
	c := chartColors[i%len(chartColors)]
	return chart.Style{
		// 0 uses a default
		SymbolSize: 0.00001,
		LineStyle:  chart.SolidLine,
		LineWidth:  1,
		LineColor:  c,
	}
}

var white = color.RGBA{0xff, 0xff, 0xff, 0xff}

func (s *Schedule) ExprSVG(t miniprofiler.Timer, w io.Writer, width, height int, res []*expr.Result, q string, now time.Time) error {
	ch, err := s.ExprGraph(t, res, q, now)
	if err != nil {
		return err
	}
	g := svg.New(w)
	g.StartviewUnit(100, 100, "%", 0, 0, width, height)
	g.Rect(0, 0, width, height, "fill: #ffffff")
	sgr := svgg.AddTo(g, 0, 0, width, height, "", 12, white)
	ch.Plot(sgr)
	g.End()
	return nil
}

func (s *Schedule) ExprPNG(t miniprofiler.Timer, w io.Writer, width, height int, res []*expr.Result, q string, now time.Time) error {
	ch, err := s.ExprGraph(t, res, q, now)
	if err != nil {
		return err
	}
	g := image.NewRGBA(image.Rectangle{Min: image.ZP, Max: image.Pt(width, height)})
	sgr := imgg.AddTo(g, 0, 0, width, height, white, nil, nil)
	ch.Plot(sgr)
	return png.Encode(w, g)
}

func (s *Schedule) ExprGraph(t miniprofiler.Timer, res []*expr.Result, q string, now time.Time) (chart.Chart, error) {
	c := chart.ScatterChart{
		Title: fmt.Sprintf("%s - %s", q, now.Format(time.RFC1123)),
		Key:   chart.Key{Pos: "itl"},
	}
	c.XRange.Time = true
	for ri, r := range res {
		rv := r.Value.(expr.Series)
		pts := make([]chart.EPoint, len(rv))
		idx := 0
		for k, v := range rv {
			pts[idx].X = float64(k.Unix())
			pts[idx].Y = v
			idx++
		}
		slice.Sort(pts, func(i, j int) bool {
			return pts[i].X < pts[j].X
		})
		c.AddData(r.Group.String(), pts, chart.PlotStyleLinesPoints, Autostyle(ri))
	}
	return &c, nil
}

repository: onetwotrip/bosun

repo_name: onetwotrip/bosun


text:
@InProceedings{linb16,
  title = {Fixed Point Quantization of Deep Convolutional Networks},
  author = {Darryl Lin and Sachin Talathi and Sreekanth Annapureddy},
  pages = {2849-2858},
  abstract = {In recent years increasingly complex architectures for deep convolution networks (DCNs) have been proposed to boost the performance on image recognition tasks. However, the gains in performance have come at a cost of substantial increase in computation and model storage resources. Fixed point implementation of DCNs has the potential to alleviate some of these complexities and facilitate potential deployment on embedded hardware. In this paper, we propose a quantizer design for fixed point implementation of DCNs. We formulate and solve an optimization problem to identify optimal fixed point bit-width allocation across DCN layers. Our experiments show that in comparison to equal bit-width settings, the fixed point DCNs with optimized bit width allocation offer >20\% reduction in the model size without any loss in accuracy on CIFAR-10 benchmark. We also demonstrate that fine-tuning can further enhance the accuracy of fixed point DCNs beyond that of the original floating point model. In doing so, we report a new state-of-the-art fixed point performance of 6.78\% error-rate on CIFAR-10 benchmark.},
}

repository: mreid/papersite

repo_name: mreid/papersite


text:
#
# This recipe installs start script watchdog.sh in /etc/init.d
#

LICENSE = "Proprietary"
LIC_FILES_CHKSUM = "file://${WORKDIR}/watchdog-init.sh;beginline=3;endline=31;md5=3da9d00ad07c09b1c5d373fa9a25b0ed"

SRC_URI = "\
	file://watchdog-init.sh \
	"

FILESEXTRAPATHS_prepend := "${THISDIR}/files:"

COMPATIBLE_MACHINE = "^$"
COMPATIBLE_MACHINE_zynqmp = "zynqmp"

do_install() {
	install -Dm 0755 ${WORKDIR}/watchdog-init.sh ${D}${sysconfdir}/init.d/watchdog-init
}

FILES_${PN} = "$(datadir)/* ${sysconfdir}/*"

repository: narrucmot/meta-petalinux

repo_name: narrucmot/meta-petalinux


text:
package mongodb_test

import (
	"context"
	"fmt"
	"testing"
	"time"

	ad "github.com/hiroaki-yamamoto/reusable-services/adapter"
	"github.com/hiroaki-yamamoto/reusable-services/adapter/db/mongodb"
	. "github.com/onsi/ginkgo"
	. "github.com/onsi/gomega"
	"go.mongodb.org/mongo-driver/bson"
	pr "go.mongodb.org/mongo-driver/bson/primitive"
	"go.mongodb.org/mongo-driver/mongo"
	"go.mongodb.org/mongo-driver/mongo/options"
)

var cli *mongo.Client
var db *mongo.Database
var col *mongo.Collection
var adapter ad.IAdapter
var rootCtx context.Context

type Sample struct {
	ID     pr.ObjectID `bson:"_id"`
	Number int
	Meta   string
}

var samples []*Sample

// TimeoutContext creates a new timeout context with 3 seconds-timeout from
// rootCtx
func TimeoutContext() (ctx context.Context, cancelFunc context.CancelFunc) {
	ctx, cancelFunc = context.WithTimeout(rootCtx, 3*time.Second)
	return
}

func TestMongodb(t *testing.T) {
	RegisterFailHandler(Fail)
	RunSpecs(t, "Mongodb Suite")
}

// ContainObjectID returns true if the specified ObjectID "target" is found
// in a slice of []ObjectID named "arr"
func ContainObjectID(target pr.ObjectID, arr []pr.ObjectID) bool {
	for _, v := range arr {
		if v.Hex() == target.Hex() {
			return true
		}
	}
	return false
}

var _ = BeforeSuite(func() {
	rootCtx = context.Background()
	ctx, cancel := TimeoutContext()
	defer cancel()
	var err error
	cli, err = mongo.Connect(
		ctx, options.Client().ApplyURI("mongodb://adapter:adapter@mongo/"),
	)
	Expect(err).To(Succeed())
	db = cli.Database("adapter-test")
	adapter = mongodb.New(db.Collection("adapters"))
	col = db.Collection("adapters")
})

var _ = BeforeEach(func() {
	samples = make([]*Sample, 20)
	toInsert := make(bson.A, len(samples))
	for i := range samples {
		samples[i] = &Sample{
			ID:     pr.NewObjectID(),
			Number: i,
			Meta:   fmt.Sprintf("Hello %d", i),
		}
		toInsert[i] = samples[i]
	}
	ctx, cancel := TimeoutContext()
	defer cancel()
	col.InsertMany(ctx, toInsert)
})

var _ = AfterEach(func() {
	samples = nil
	ctx, cancel := TimeoutContext()
	defer cancel()
	Expect(col.Drop(ctx)).To(Succeed())
})

var _ = AfterSuite(func() {
	ctx, cancel := TimeoutContext()
	defer cancel()
	Expect(db.Drop(ctx)).To(Succeed())
	Expect(cli.Disconnect(ctx)).To(Succeed())
})

repository: hiroaki-yamamoto/reusable-services

repo_name: hiroaki-yamamoto/reusable-services


text:
include(ExternalData)
set(ExternalData_URL_TEMPLATES
  "ExternalDataCustomScript://RelPathKey/%(algo)/%(hash)"
  )
set(ExternalData_CUSTOM_SCRIPT_RelPathKey "RelPathScript.cmake")
ExternalData_Add_Target(Data)

extension: cmake


text:
---
---

@inproceedings{tulathum2022human,
  bibtex_show={true},
  title={Human-robot interaction system for non-expert users in convenience stores using behavior trees},
  author={Tulathum, Pattaraporn and Usawalertkamol, Bunyapon and Ricardez, Gustavo Alfonso Garcia and Takamatsu, Jun and Ogasawara, Tsukasa and Matsumoto, Kenichi},
  booktitle={2022 IEEE/SICE International Symposium on System Integration (SII)},
  pages={1072--1077},
  year={2022},
  organization={IEEE}
}

@article{garcia2022autonomous,
  bibtex_show={true},
  title={Autonomous service robot for human-aware restock, straightening and disposal tasks in retail automation},
  author={Garcia Ricardez, Gustavo A and Uriguen Eljuri, Pedro M and Kamemura, Yuta and Yokota, Shiori and Kugou, Noriyuki and Asama, Yoshitatsu and Wang, Ziyu and Kumamoto, Hikaru and Yoshimoto, Kotaro and Chan, Wai Y and Nagatani, Tomoki and Tulathum, Pattaraporn and Usawalertkamol, Bunyapon and Hafi, Lotfi El and Ikeuchi, Hiroki and Yamamoto, Masaki and Takamatsu, Jun and Taniguchi, Tadahiro and Ogasawara, Tsukasa},
  journal={Advanced Robotics},
  volume={36},
  number={17-18},
  pages={936--950},
  year={2022},
  publisher={Taylor \& Francis}
}

@article{tulathum2022robot,
  bibtex_show={true},
  title={Robot behavior debugger for non-expert users in convenience stores using behavior trees},
  author={Tulathum, Pattaraporn and Usawalertkamol, Bunyapon and Garcia Ricardez, Gustavo Alfonso and Takamatsu, Jun and Ogasawara, Tsukasa and Matsumoto, Kenichi},
  journal={Advanced Robotics},
  volume={36},
  number={17-18},
  pages={951--966},
  year={2022},
  publisher={Taylor \& Francis}
}

@article{yuguchi2022toward,
  bibtex_show={true},
  title={Toward robot-agnostic home appliance operation: a task execution framework using motion primitives, ontology, and GUI},
  author={Yuguchi, Akishige and Nakamura, Takumi and Toyoda, Mayuki and Yamada, Masayuki and Tulathum, Pattaraporn and Aubert, Ma{\"e}l and Garcia Ricardez, Gustavo Alfonso and Takamatsu, Jun and Ogasawara, Tsukasa},
  journal={Advanced Robotics},
  volume={36},
  number={11},
  pages={548--565},
  year={2022},
  publisher={Taylor \& Francis}
}


text:
@article{Munro2018,
 author = {Munro, Jason M. and Akamatsu, Hirofumi and Padmanabhan, Haricharan and Liu, Vincent S. and Shi, Yin and Chen, Long-Qing and VanLeeuwen, Brian K. and Dabo, Ismaila and Gopalan, Venkatraman},
 doi = {10.1103/PhysRevB.98.085107},
 issn = {2469-9950},
 journal = {Physical Review B},
 month = {aug},
 number = {8},
 pages = {085107},
 title = {Discovering minimum energy pathways via distortion symmetry groups},
 url = {https://link.aps.org/doi/10.1103/PhysRevB.98.085107},
 volume = {98},
 year = {2018}
}

repository: munrojm/academic-kickstart

repo_name: munrojm/academic-kickstart


text:
LICENSE = GPL
DESCRIPTION = "libxine"
SECTION = "libs"
PRIORITY = "optional"
MAINTAINER = "Pawel Osiczko <p.osiczko@tetrapyloctomy.org>"
DEPENDS = "zlib libogg tremor libmad esound-gpe"
PROVIDES = "virtual/libxine"
PR = "r1"

DEFAULT_PREFERENCE = "-1"

inherit autotools pkgconfig gettext

S = "${WORKDIR}/xine-lib-1-rc5"

SRC_URI = "http://heanet.dl.sourceforge.net/sourceforge/xine/xine-lib-1-rc5.tar.gz \
	file://cpu.patch;patch=1 \
	file://configure.patch;patch=1 \
	file://no-caca-no-aalib.patch;patch=1 \
	file://libxine-tremor-autoconf.patch;patch=1 \
	file://libxine-libvorbis.patch;patch=1"

SOV = "1.0.6"

# Omit the annoying xine-config in ${bindir}
FILES_${PN}="${libdir}/*.so*"

# And include it in the dev package
FILES_${PN}-dev += " ${bindir}"

EXTRA_OECONF="-with-zlib-path=${STAGING_DIR}/${HOST_SYS} \
	--with-vorbis-prefix=${STAGING_DIR}/${HOST_SYS} \
	--disable-oggtest \
	--with-ogg-prefix=${STAGING_DIR}/${HOST_SYS} \
	--disable-altivec --disable-vis --disable-mlib \
	--disable-fb --disable-alsa --disable-vcd \
	--disable-asf --disable-faad --disable-iconv \
	--without-v4l --without-arts --without-sdl"

do_compile() {
	oe_runmake LIBTOOL=${S}/${TARGET_SYS}-libtool
}

do_install() {
	oe_runmake DESTDIR=${D} LIBTOOL=${S}/${TARGET_SYS}-libtool install
}

HEADERS="src/xine-engine/xineintl.h src/xine-utils/xineutils.h \
	src/xine-engine/xine_internal.h src/xine-engine/xine_plugin.h \
	src/xine-utils/xine_buffer.h"

do_stage() {
	install -d ${STAGING_INCDIR}/xine

	install -m 0644 ${S}/include/xine.h ${STAGING_INCDIR}

	for file in ${HEADERS}; do
		cp ${S}/$file ${STAGING_INCDIR}/xine/`basename $file`
	done

	install -m 0644 ${S}/m4/xine.m4 ${STAGING_DATADIR}/aclocal/

	oe_libinstall -so -C src/xine-engine libxine ${STAGING_LIBDIR}
}

python populate_packages_prepend () {
	bb.data.setVar('PKG_libxine', 'libxine', d)

	plugindir = bb.data.expand('${libdir}/xine/plugins/1.0.0', d)
	do_split_packages(d, plugindir, '^xineplug_(.*)\.so$', 'libxine-plugin-%s', 'Xine plugin for %s')

	postdir = bb.data.expand('${libdir}/xine/plugins/1.0.0/post', d)
	do_split_packages(d, postdir, '^xineplug_(.*)\.so$', 'libxine-plugin-%s', 'Xine plugin for %s')

	fontdir = bb.data.expand('${datadir}/xine/libxine1/fonts', d)
	do_split_packages(d, fontdir, '^(.*).xinefont.gz$', 'libxine-font-%s', 'Xine font %s')
}

repository: BackupTheBerlios/openslug-svn

repo_name: BackupTheBerlios/openslug-svn


text:
package main

import (
	"fmt"
)

func main() {
	/*
		Channel创建方式：
		var c1 chan [value type]
		c1 = make([channel type] [value type], [capacity])

		[value type] 定义的是 Channel 中所传输数据的类型。
		[channel type] 定义的是 Channel 的类型，其类型有以下三种：
				"chan" 	  可读可写 : chan int 则表示可读写 int 数据的 channel
				"chan<-"  仅可写   : chan<- float64 则表示仅可写64位 float 数据的 channel
				"<-chan"  仅可读   : <-chan int 则表示仅可读 int 数据的 channel
		[capacity] 是一个可选参数，其定义的是 channel 中的缓存区 (buffer)。
					  如果不填则默认该 channel 没有缓冲区 (unbuffered)。
					  对于没有缓冲区的 channel，消息的发送和收取必须能同时完成，否则会造成阻塞并提示死锁错误。
		chan读写使用的符号都是<-
	*/

	var c1 chan int
	c1 = make(chan int, 100)

	// 1.向 Channel1 发送(写入)10
	c1 <- 10

	// 2.从 Channel1 接收(读取)
	i := <-c1

	fmt.Println("Receive from channel 1: ", i)

	// ==================================================================

	/*
		Channel死锁：对 channel 的发送和接收动作永远不会同时发生，从而阻塞造成死锁。
		fatal error: all goroutines are asleep - deadlock!
	*/
	var c2 chan int
	c2 = make(chan int)

	// 没有buffer的channel，先写后读 会出现死锁：
	// func() {
	// 	c2 <- 0
	// }()
	//
	// j := <-c2

	// 避免死锁方式1：使用goroutine并发执行
	// 通过 go 语句定义发送操作的方程在另一个协程并发运行，chan读取没有数据时会阻塞等待，从而能够解决死锁问题。
	go func() {
		c2 <- 2
	}()

	j := <-c2

	fmt.Println("Receive from channel 2: ", j)

	// 避免死锁方式2：使用buffer
	// 为 channel 添加一个缓冲区（buffer），这样只要 buffer 没有用尽，阻塞就不会发生，死锁也不会发生。
	var c3 chan int
	c3 = make(chan int, 1)

	func() {
		c3 <- 3
	}()

	k := <-c3

	fmt.Println("Receive from channel 3: ", k)
}

repository: farwish/go-lab

repo_name: farwish/go-lab


text:
DESCRIPTION="XFCE extensions and framework library with session management support"
DEPENDS = "libxfce4util hal liburi-perl-native python-native cairo"
SECTION = "x11"
PR = "r2"

inherit xfce46 python-dir

XFCE_VERSION = "4.6.1"

SRC_URI += " \
    file://exo-0.3.105-iocharset.patch \
    file://exo-no-tests.patch \
    file://configure.patch \
"

# Note: Python checking is broken
do_configure_prepend() {
	sed -i -e s:'`$PKG_CONFIG --variable=defsdir pygtk-2.0`':\"${STAGING_DATADIR}/pygtk/2.0/defs\":g ${S}/configure.in
}

FILES_${PN} += "${datadir}/xfce4/ \
                ${PYTHON_SITEPACKAGES_DIR}/* \
                ${prefix}/share/pygtk/2.0/defs/exo-0.3/exo.defs \
"

FILES_${PN}-dbg += "${PYTHON_SITEPACKAGES_DIR}/*/.debug/*"

SRC_URI[md5sum] = "ba87f84894498bf23ae39d849c55f98c"
SRC_URI[sha256sum] = "278f702d890c89bd3923ce1bdaf29bd9f2c800c2e4cfd9e902d99663bba337e5"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD


text:
if (Protobuf_PROTOC_EXECUTABLE)
    option (ENABLE_PARQUET "Enable parquet" ${ENABLE_LIBRARIES})
endif()

if (ENABLE_PARQUET)

if (NOT OS_FREEBSD AND NOT OS_DARWIN) # Freebsd: ../contrib/arrow/cpp/src/arrow/util/bit-util.h:27:10: fatal error: endian.h: No such file or directory
    option(USE_INTERNAL_PARQUET_LIBRARY "Set to FALSE to use system parquet library instead of bundled" ${NOT_UNBUNDLED})
endif()

if(NOT EXISTS "${ClickHouse_SOURCE_DIR}/contrib/arrow/cpp/CMakeLists.txt")
    if(USE_INTERNAL_PARQUET_LIBRARY)
        message(WARNING "submodule contrib/arrow (required for Parquet) is missing. to fix try run: \n git submodule update --init --recursive")
    endif()
    set(USE_INTERNAL_PARQUET_LIBRARY 0)
    set(MISSING_INTERNAL_PARQUET_LIBRARY 1)
endif()

if(NOT USE_INTERNAL_PARQUET_LIBRARY)
    find_package(Arrow)
    find_package(Parquet)
endif()

if(ARROW_INCLUDE_DIR AND PARQUET_INCLUDE_DIR)
elseif(NOT MISSING_INTERNAL_PARQUET_LIBRARY AND NOT OS_FREEBSD)
    include(cmake/find/snappy.cmake)
    if(SNAPPY_LIBRARY)
        set(CAN_USE_INTERNAL_PARQUET_LIBRARY 1)
    endif()

    include(CheckCXXSourceCompiles)
    if(NOT USE_INTERNAL_DOUBLE_CONVERSION_LIBRARY)
        set(CMAKE_REQUIRED_LIBRARIES ${DOUBLE_CONVERSION_LIBRARIES})
        set(CMAKE_REQUIRED_INCLUDES ${DOUBLE_CONVERSION_INCLUDE_DIR})
        check_cxx_source_compiles("
            #include <double-conversion/double-conversion.h>
            int main() { static const int flags_ = double_conversion::StringToDoubleConverter::ALLOW_CASE_INSENSIBILITY; return 0;}
        " HAVE_DOUBLE_CONVERSION_ALLOW_CASE_INSENSIBILITY)

        if(NOT HAVE_DOUBLE_CONVERSION_ALLOW_CASE_INSENSIBILITY) # HAVE_STD_RANDOM_SHUFFLE
            message(STATUS "Disabling internal parquet library because arrow is broken (can't use old double_conversion)")
            set(CAN_USE_INTERNAL_PARQUET_LIBRARY 0)
        endif()
    endif()

   if(NOT CAN_USE_INTERNAL_PARQUET_LIBRARY)
        set(USE_INTERNAL_PARQUET_LIBRARY 0)
   else()
    set(USE_INTERNAL_PARQUET_LIBRARY 1)

    if(USE_INTERNAL_PARQUET_LIBRARY_NATIVE_CMAKE)
        set(ARROW_INCLUDE_DIR "${ClickHouse_SOURCE_DIR}/contrib/arrow/cpp/src")
        set(PARQUET_INCLUDE_DIR "${ClickHouse_SOURCE_DIR}/contrib/arrow/cpp/src" ${ClickHouse_BINARY_DIR}/contrib/arrow/cpp/src)
    endif()

    if(${USE_STATIC_LIBRARIES})
        set(FLATBUFFERS_LIBRARY flatbuffers)
        set(ARROW_LIBRARY arrow_static)
        set(PARQUET_LIBRARY parquet_static)
        set(THRIFT_LIBRARY thrift_static)
    else()
        set(FLATBUFFERS_LIBRARY flatbuffers_shared)
        set(ARROW_LIBRARY arrow_shared)
        set(PARQUET_LIBRARY parquet_shared)
        if(USE_INTERNAL_PARQUET_LIBRARY_NATIVE_CMAKE)
            list(APPEND PARQUET_LIBRARY ${Boost_REGEX_LIBRARY})
        endif()
        set(THRIFT_LIBRARY thrift)
    endif()

    set(USE_PARQUET 1)
    set(USE_ORC 1)
   endif()
endif()

endif()

if(USE_PARQUET)
    message(STATUS "Using Parquet: ${ARROW_LIBRARY}:${ARROW_INCLUDE_DIR} ; ${PARQUET_LIBRARY}:${PARQUET_INCLUDE_DIR} ; ${THRIFT_LIBRARY} ; ${FLATBUFFERS_LIBRARY}")
else()
    message(STATUS "Building without Parquet support")
endif()

repository: kssenii/ClickHouse

repo_name: kssenii/ClickHouse


text:
/**
 * Sequelize model for French Departments.
 * @param sequelize The Sequelize instance.
 * @param DataTypes The data types.
 * @returns {Object} The Sequelize model.
 */
module.exports = function (sequelize, DataTypes) {
    var Department = sequelize.define('Department', {
        code: DataTypes.STRING,
        name: DataTypes.STRING,
        region: DataTypes.STRING
    }, {
        tableName: 'departments',
        classMethods: {
            associate: function (models) {
                Department.hasMany(models.Address)
            }
        }
    });
    return Department
};

repository: kidGodzilla/server

repo_name: kidGodzilla/server


text:
include(${CMAKE_TOOLCHAIN_FILE})
include(cpp_unit_test_helpers)
_cpp_setup_test_env("url_parser")

_cpp_add_test(
TITLE "Basic URL"
"include(get_recipe/get_from_url/url_parser)"
"_cpp_url_parser(org repo github.com/organization/repo)"
"_cpp_assert_equal(\${org} organization)"
"_cpp_assert_equal(\${repo} repo)"
)

_cpp_add_test(
TITLE "Works with GitLab too"
"include(get_recipe/get_from_url/url_parser)"
"_cpp_url_parser(org repo gitlab.com/organization/repo)"
"_cpp_assert_equal(\${org} organization)"
"_cpp_assert_equal(\${repo} repo)"
)

_cpp_add_test(
TITLE "Basic URL with https://"
"include(get_recipe/get_from_url/url_parser)"
"_cpp_url_parser(org repo https://github.com/organization/repo)"
"_cpp_assert_equal(\${org} organization)"
"_cpp_assert_equal(\${repo} repo)"
)

_cpp_add_test(
TITLE "Fails if URL does not contain organization/user"
SHOULD_FAIL REASON "github.com//repo does not appear to contain an organization"
"include(get_recipe/get_from_url/url_parser)"
"_cpp_url_parser(org repo github.com//repo)"
)

_cpp_add_test(
TITLE "Fails if URL does not contain repo"
SHOULD_FAIL REASON "github.com/org/ does not appear to contain a repository."
"include(get_recipe/get_from_url/url_parser)"
"_cpp_url_parser(org repo github.com/org/)"
)

repository: keipertk/CMakePackagingProject

repo_name: keipertk/CMakePackagingProject


text:
require kpatch.inc

LIC_FILES_CHKSUM = "file://COPYING;md5=b234ee4d69f5fce4486a80fdaf4a4263"

SRCREV = "0c3c21930895f6582a5c9d9d797f7e11ff41ffb2"

PV = "0.9.1"

S = "${WORKDIR}/git"

BBCLASSEXTEND = "native nativesdk"

repository: openembedded/meta-openembedded

repo_name: openembedded/meta-openembedded

gha_language: BitBake


text:
SUMMARY = "Fetchmail retrieves mail from remote mail servers and forwards it via SMTP"
HOMEPAGE = "http://www.fetchmail.info/"
DESCRIPTION = "Fetchmail is a full-featured, robust, well-documented remote-mail retrieval \
and forwarding utility intended to be used over on-demand TCP/IP links (such as SLIP or PPP \
connections). It supports every remote-mail protocol now in use on the Internet: POP2, POP3, \
RPOP, APOP, KPOP, all flavors of IMAP, ETRN, and ODMR. It can even support IPv6 and IPSEC."
SECTION = "mail"
LICENSE = "GPL-2.0-only & MIT"
LIC_FILES_CHKSUM = "file://COPYING;md5=ee6b9f41d9324434dd11bd8a38f1b044"

DEPENDS = "openssl"

SRC_URI = "${SOURCEFORGE_MIRROR}/${BPN}/${BPN}-${PV}.tar.xz \
           "
SRC_URI[sha256sum] = "4a182e5d893e9abe6ac37ae71e542651fce6d606234fc735c2aaae18657e69ea"

inherit autotools gettext pkgconfig python3-dir python3native

EXTRA_OECONF = "--with-ssl=${STAGING_DIR_HOST}${prefix}"

do_install:append() {
    sed -i 's,${RECIPE_SYSROOT_NATIVE},,g' ${D}${bindir}/fetchmailconf
}

PACKAGES =+ "fetchmail-python"
FILES:fetchmail-python = "${libdir}/${PYTHON_DIR}/*"


text:
@article{2014AJ....148....2L,
 abstract = {We present a template-fitting algorithm for determining photometric
redshifts, z $_phot$, of candidate high-redshift gamma-ray
bursts (GRBs). Using afterglow photometry, obtained by the
Reionization and Transients InfraRed (RATIR) camera, this
algorithm accounts for the intrinsic GRB afterglow spectral
energy distribution, host dust extinction, and the effect of
neutral hydrogen (local and cosmological) along the line of
sight. We present the results obtained by this algorithm and the
RATIR photometry of GRB 130606A, finding a range of best-fit
solutions, 5.6 < z $_phot$ < 6.0, for models of
several host dust extinction laws (none, the Milky Way, Large
Magellanic Clouds, and Small Magellanic Clouds), consistent with
spectroscopic measurements of the redshift of this GRB. Using
simulated RATIR photometry, we find that our algorithm provides
precise measures of z $_phot$ in the ranges of 4 < z
$_phot$ <åisebox-0.5ex~ 8 and 9 < z
$_phot$ < 10 and can robustly determine when z $_phot$
> 4. Further testing highlights the required caution in
cases of highly dust-extincted host galaxies. These tests also
show that our algorithm does not erroneously find z $_phot$
< 4 when z $_sim$ > 4, thereby minimizing false
negatives and allowing us to rapidly identify all potential
high-redshift events.},
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/2014AJ....148....2L},
 archiveprefix = {arXiv},
 author = {Littlejohns, O.~M. and Butler, N.~R. and Cucchiara, A. and
Watson, A.~M. and Kutyrev, A.~S. and Lee, W.~H. and
Richer, M.~G. and Klein, C.~R. and Fox, O.~D. and
Prochaska, J.~X. and Bloom, J.~S. and Troja, E. and
Ramirez-Ruiz, E. and de Diego, J.~A. and Georgiev, L. and
González, J. and Román-Zúñiga, C.~G. and
Gehrels, N. and Moseley, H.},
 doi = {10.1088/0004-6256/148/1/2},
 eid = {2},
 eprint = {1312.3967},
 journal = {\aj},
 keywords = {gamma-ray burst: general, gamma-ray burst: individual: GRB 130606A, techniques: photometric, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics},
 month = {Jul},
 number = {1},
 pages = {2},
 primaryclass = {astro-ph.HE},
 title = {Identifying High-redshift Gamma-Ray Bursts with RATIR},
 volume = {148},
 year = {2014}
}

repository: profjsb/my-content

repo_name: profjsb/my-content


text:
inherit pypi setuptools3

DESCRIPTION = "MarkupSafe Python3"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://LICENSE.rst;md5=ffeffa59c90c9c4a033c7574f8f3fb75"
PYPI_PACKAGE = "MarkupSafe"
SRC_URI[md5sum] = "43fd756864fe42063068e092e220c57b"
SRC_URI[sha256sum] = "29872e92839765e546828bb7754a68c418d927cd064fd4708fab9fe9c8bb116b"
CLEANBROKEN = "1"

BBCLASSEXTEND = "native nativesdk"

repository: plume-design/meta-rdk-opensync

repo_name: plume-design/meta-rdk-opensync


text:
@article{PR2020,
 author = {Rufin, Philippe and Frantz, David and Yan, Lin and Hostert, Patrick},
 geo = {Berlin, Germany (1, 2, 4) and East Lansing, MI, USA (3)},
 doi = {10.1109/LGRS.2020.2982245},
 journal = {IEEE Geoscience and Remote Sensing Letters},
 pages = {712-716},
 title = {Operational Coregistration of the Sentinel-2A/B Image Archive Using Multitemporal Landsat Spectral Averages},
 type = {Journal Article},
 url = {https://ieeexplore.ieee.org/document/9057384},
 volume = {18},
 year = {2021}
}

repository: davidfrantz/academic-kickstart

repo_name: davidfrantz/academic-kickstart


text:
require postfix.inc

SRC_URI[md5sum] = "40d72ea143af7ab0038c2cee1f483707"
SRC_URI[sha256sum] = "3deda4c34631970490b1b5fbb559905f93531bf1c7eb00e38b0d0deb1dba9982"

repository: nedap/meta-openembedded

repo_name: nedap/meta-openembedded


text:
@phdthesis{Grossman:2008:IVD:2520450,
 address = {Toronto, Ont., Canada, Canada},
 author = {Grossman, Tovi},
 isbn = {978-0-494-93110-3},
 note = {AAINR93110},
 publisher = {University of Toronto},
 title = {Interaction with Volumetric Displays},
 year = {2008}
}

repository: jmatejka/group-website

repo_name: jmatejka/group-website


text:
.mat-list >  .mat-list-item:nth-child(2n+1) {
    background-color:#ededed;
}

.mat-list >  .mat-list-item:nth-child(2n) {
    background-color:white;
}

.blocked-card {
    width: 400px;
    margin: 0;
    position: absolute;
    top: 40%;
    left: 50%;
    transform: translate(-50%, -50%);
    text-shadow: none;
}

.blocked-button {
    width: 50%;
    text-align: center;
}

.button-row {
    display: flex;
    align-items: center;
    justify-content: space-around;
}

repository: chubbers/AddieC

repo_name: chubbers/AddieC

branch_name: refs/heads/develop

gha_language: TypeScript

extension: css


text:
@article{Zhang2015,
abstract = {This paper proposes an effective scale invariant texture representation based on frequency decomposition and gradient orientation. First, the image intensities are decomposed into different orientations by using wedge filters in the frequency domain, and the N-nary coding method is adopted for the vector quantization. Second, the scale invariant gradient orientation is generated by selecting the most stable value of the gradient orientation with different Gaussian scales. Finally, the 2D joint distribution of the two types of local descriptors is used as the representation. The performance was evaluated on texture classification using a nearest neighbor classifier. Simple but not ordinary, our method achieves state of the art classification performance on the KTH-TIPS dataset under the traditional experimental design. Moreover, the main experiments were conducted on the KTH-TIPS and KTH-TIPS2-b datasets with the experimental designs of scale invariance validation. Compared with the methods of basic image features (BIFs) and local energy pattern (LEP), the proposed representation achieves superior performance with much lower dimension of representation.},
author = {Zhang, Jun and Liang, Jimin and Zhang, Chunhui and Zhao, Heng},
doi = {10.1016/j.patrec.2014.08.002},
file = {:E$\backslash$:/Mendeley Papers/2015/Pattern Recognition Letters/2015 - Pattern Recognition Letters - Scale invariant texture representation based on frequency decomposition and gradient orientation ✩.pdf:pdf},
isbn = {0167-8655},
issn = {01678655},
journal = {Pattern Recognition Letters},
keywords = {Frequency decomposition,Gradient orientation,Scale invariance,Texture classification,Wedge filters},
pages = {57--62},
publisher = {Elsevier Ltd.},
title = {{Scale invariant texture representation based on frequency decomposition and gradient orientation}},
url = {http://dx.doi.org/10.1016/j.patrec.2014.08.002},
volume = {51},
year = {2015}
}
@article{Zhang2015a,
abstract = {Object detection methods based on keypoint localization are widely used, and the rotation invariance is one of the fundamental issues to consider. This paper proposes a novel shape prior model with rotation invariance. The proposed shape prior model discards all orientation-involved features and only uses the distance features among keypoints, hence it is competent to detect objects with a rotation of the arbitrary angle when combined with local appearance description with rotation invariance. In the stage of detection, belief propagation algorithm is employed, so that our method no longer needs the initial position of the keypoints. Furthermore, we generalize the classical distance transforms, the generalized distance transforms make the beliefs to be calculated in a nearly linear time. Experiments were carried out on face category and touring-bike category in the Caltech-256 database. The results demonstrated that the proposed method achieved a strong robustness of rotation.},
author = {Zhang, Chunhui and Liang, Jimin and Zhang, Jun and Zhao, Heng},
doi = {10.1016/j.patrec.2014.12.008},
file = {:E$\backslash$:/Mendeley Papers/2015/Pattern Recognition Letters/2015 - Pattern Recognition Letters - A new shape prior model with rotation invariance ✩.pdf:pdf},
issn = {01678655},
journal = {Pattern Recognition Letters},
keywords = {Distance transforms,Rotation invariance,Shape prior model},
pages = {82--88},
publisher = {Elsevier Ltd.},
title = {{A new shape prior model with rotation invariance}},
url = {http://dx.doi.org/10.1016/j.patrec.2014.12.008},
volume = {54},
year = {2015}
}
@article{Chen2015,
abstract = {By recording a time series of tomographic images, dynamic fluorescence molecular tomography (FMT) allows exploring perfusion, biodistribution, and pharmacokinetics of labeled substances in vivo. Usually, dynamic tomographic images are first reconstructed frame by frame, and then unmixing based on principle component analysis (PCA) or independent component analysis (ICA) is performed to detect and visualize functional structures with different kinetic patterns. PCA and ICA assume sources are statistically uncorrelated or independent and donot perform well when correlated sources are present. In this paper, we deduce the relationship between the measured imaging data and the kinetic patterns and present a temporal unmixing approach, which is based on nonnegative blind source separation (BSS) method with a convex analysis framework to separate the measured data. The presented method requires no assumption on source independence or zero correlations. Several numerical simulations and phantom experiments are conducted to investigate the performance of the proposed temporal unmixing method. The results indicate that it is feasible to unmix the measured data before the tomographic reconstruction and the BSS based method provides better unmixing quality compared with PCA and ICA.},
author = {Chen, Duofang and Liang, Jimin and Guo, Kui},
doi = {10.1155/2015/713424},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - Temporal Unmixing of Dynamic Fluorescent Images by Blind Source Separation Method with a Convex Framework.pdf:pdf},
issn = {17486718},
journal = {Computational and Mathematical Methods in Medicine},
pmid = {26089974},
title = {{Temporal Unmixing of Dynamic Fluorescent Images by Blind Source Separation Method with a Convex Framework}},
volume = {2015},
year = {2015}
}
@article{Yang2015,
abstract = {The third-order simplified harmonic spherical approximation (SP3) and diffusion approximation (DA) equations have been widely used in the three-dimensional (3D) whole-body optical imaging of small animals. With different types of tissues, which were classified by the ratio of , the two equations have their own application scopes. However, the classification criterion was blurring and unreasonable, and the scope has not been systematically investigated until now. In this study, a new criterion for classifying tissues was established based on the absolute value of absorption and reduced scattering coefficients. Using the newly defined classification criterion, the performance and applicability of the SP3 and DA equations were evaluated with a series of investigation experiments. Extensive investigation results showed that the SP3 equation exhibited a better performance and wider applicability than the DA one in most of the observed cases, especially in tissues of low-scattering-low-absorption and low-scattering-high-absorption range. For the case of tissues with the high-scattering-low-absorption properties, a similar performance was observed for both the SP3 and the DA equations, in which case the DA was the preferred option for 3D whole-body optical imaging. Results of this study would provide significant reference for the study of hybrid light transport models.},
author = {Yang, Defu and Chen, Xueli and Cao, Xu and Wang, Jing and Liang, Jimin and Tian, Jie},
doi = {10.1007/s11517-015-1293-8},
file = {:E$\backslash$:/Mendeley Papers/2015/Medical {\&} Biological Engineering {\&} Computing/2015 - Medical {\&} Biological Engineering {\&} Computing - Performance investigation of SP 3 and diffusion approximation for three ‑ dimensio.pdf:pdf},
isbn = {01400118},
issn = {0140-0118},
journal = {Medical {\&} Biological Engineering {\&} Computing},
keywords = {Diffusion approximation,Performance investigation,Third-order simplified harmonic spherical approximation,Three-dimensional optical imaging,Tissue classification criterion,approximation,diffusion approximation,investigation,performance,third-order simplified harmonic spherical,three-dimensional optical imaging,tissue classification criterion},
number = {9},
pages = {805--814},
pmid = {109466529},
publisher = {Springer Berlin Heidelberg},
title = {{Performance investigation of SP3 and diffusion approximation for three-dimensional whole-body optical imaging of small animals}},
url = {http://link.springer.com/10.1007/s11517-015-1293-8},
volume = {53},
year = {2015}
}
@article{Cao2015,
abstract = {Weak intensity and poor penetration depth are two big obstacles toward clinical use of Cerenkov luminescence imaging (CLI). In this proof-of-concept study, we overcame these limitations by using lanthanides-based radioluminescent microparticles (RLMPs), called terbium doped Gd2O2S. The characterization experiment showed that the emission excited by Cerenkov luminescence can be neglected whereas the spectrum experiment demonstrated that the RLMPs can actually be excited by gamma-rays. A series of in vitro experiments demonstrated that RLMPs significantly improve the intensity and the penetration capacity of CLI, which has been extended to as deep as 15 mm. In vivo pseudotumor study further prove the huge potential of this enhancement strategy for Cerenkov luminescence imaging in living animal studies.},
author = {Cao, Xin and Chen, Xueli and Kang, Fei and Zhan, Yonghua and Cao, Xu and Wang, Jing and Liang, Jimin and Tian, Jie},
doi = {10.1021/acsami.5b00432},
file = {:E$\backslash$:/Mendeley Papers/2015/ACS Applied Materials and Interfaces/2015 - ACS Applied Materials and Interfaces - Intensity Enhanced Cerenkov Luminescence Imaging Using Terbium-Doped Gd2O2S Microparticles.pdf:pdf},
issn = {19448252},
journal = {ACS Applied Materials and Interfaces},
keywords = {Cerenkov luminescence,biomaterials,biophotonics,imaging,radioluminescence},
number = {22},
pages = {11775--11782},
title = {{Intensity Enhanced Cerenkov Luminescence Imaging Using Terbium-Doped Gd2O2S Microparticles}},
volume = {7},
year = {2015}
}
@article{Cao2015a,
abstract = {Our previous study showed a great attenuation for the Cerenkov luminescence endoscope (CLE), resulting in relatively low detection sensitivity of radiotracers. Here, a kind of radioluminescence nanoparticles (RLNPs), terbium doped Gd2O2S was mixed with the radionuclide68Ga to enhance the intensity of emitted luminescence, which finally improved the detection sensitivity of the CLE by using the radioluminescence imaging technique. With the in vitro and in vivo pseudotumor experiments, we showed that the use of RLNPs mixed with the radionuclide 68Ga enabled superior sensitivity compared with the radionuclide68Ga only, with 50-fold improvement on detection sensitivity, which guaranteed meeting the demands of the clinical diagnosis of gastrointestinal tract tumors.},
author = {Cao, Xin and Chen, Xueli and Kang, Fei and Cao, Xu and Zhan, Yonghua and Wang, Jing and Wu, Kaichun and Liang, Jimin},
doi = {10.1063/1.4921858},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - Sensitivity improvement of Cerenkov luminescence endoscope with terbium doped Gd2O2S nanoparticles Sensitivity improvem.pdf:pdf},
issn = {00036951},
journal = {Applied Physics Letters},
number = {21},
title = {{Sensitivity improvement of Cerenkov luminescence endoscope with terbium doped Gd2O2S nanoparticles}},
volume = {106},
year = {2015}
}
@article{Zhao2015,
author = {Zhao, Fengjun and Liang, Jimin and Chen, Dongmei and Wang, Chuan and Yang, Xiang and Chen, Xueli and Cao, Feng},
doi = {10.1118/1.4922200},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - Automatic segmentation method for bone and blood vessel in murine hindlimb Automatic segmentation method for bone and b.pdf:pdf},
issn = {00942405},
journal = {Medical Physics},
keywords = {blood vessel,bone,centerline,segmentation,split Bregman},
number = {7},
pages = {4043--4054},
title = {{Automatic segmentation method for bone and blood vessel in murine hindlimb}},
volume = {42},
year = {2015}
}
@article{Chen2015a,
abstract = {Aiming at the limitations of the simplified spherical harmonics approximation (SPN) and diffusion equation (DE) in describing the light propagation in tissues, a hybrid simplified spherical harmonics with diffusion equation (HSDE) based diffuse light transport model is proposed. In the HSDE model, the living body is first segmented into several major organs, and then the organs are divided into high scattering tissues and other tissues. DE and SPN are employed to describe the light propagation in these two kinds of tissues respectively, which are finally coupled using the established boundary coupling condition. The HSDE model makes full use of the advantages of SPN and DE, and abandons their disadvantages, so that it can provide a perfect balance between accuracy and computation time. Using the finite element method, the HSDE is solved for light flux density map on body surface. The accuracy and efficiency of the HSDE are validated with both regular geometries and digital mouse model based simulations. Corresponding results reveal that a comparable accuracy and much less computation time are achieved compared with the SPN model as well as a much better accuracy compared with the DE one.},
author = {Chen, Xueli and Sun, Fangfang and Yang, Defu and Ren, Shenghan and Zhang, Qian and Liang, Jimin},
doi = {10.1088/0031-9155/60/16/6305},
file = {:E$\backslash$:/Mendeley Papers/2015/Physics in Medicine {\&} Biology/2015 - Physics in Medicine {\&} Biology - Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues.pdf:pdf},
issn = {13616560},
journal = {Physics in Medicine and Biology},
keywords = {DE,HSDE,SP{\textless}inf{\textgreater}N{\textless}/inf{\textgreater},fluorescence/bioluminescence tomography,hybrid light transport model},
number = {16},
pages = {6305--6322},
pmid = {26237074},
publisher = {IOP Publishing},
title = {{Hybrid simplified spherical harmonics with diffusion equation for light propagation in tissues}},
url = {http://dx.doi.org/10.1088/0031-9155/60/16/6305},
volume = {60},
year = {2015}
}
@article{Zhang2015b,
author = {Zhang, Chunhui and Chen, Xueli and Zhu, Shouping and Wan, Lu and Xie, Qingguo and Liang, Jimin},
doi = {10.1088/0031-9155/60/15/5873},
file = {:E$\backslash$:/Mendeley Papers/2015/Physics in Medicine {\&} Biology/2015 - Physics in Medicine {\&} Biology - Performance evaluation of a 90 ° -rotating dual-head small animal PET system.pdf:pdf},
issn = {13616560},
journal = {Physics in Medicine and Biology},
keywords = {Monte-Carlo simulation,dual-head PET,rotation,symmetry properties},
number = {15},
pages = {5873--5890},
publisher = {IOP Publishing},
title = {{Performance evaluation of a 90°-rotating dual-head small animal PET system}},
url = {http://dx.doi.org/10.1088/0031-9155/60/15/5873},
volume = {60},
year = {2015}
}
@article{Chen2015b,
abstract = {X-ray luminescence computed tomography (XLCT) has become a promising imaging technology for biological application based on phosphor nanoparticles. There are mainly three kinds of XLCT imaging systems: pencil beam XLCT, narrow beam XLCT and cone beam XLCT. Narrow beam XLCT can be regarded as a balance between the pencil beam mode and the cone-beam mode in terms of imaging efficiency and image quality. The collimated X-ray beams are assumed to be parallel ones in the traditional narrow beam XLCT. However, we observe that the cone beam X-rays are collimated into X-ray beams with fan-shaped broadening instead of parallel ones in our prototype narrow beam XLCT. Hence we incorporate the distribution of the X-ray beams in the physical model and collected the optical data from only two perpendicular directions to further speed up the scanning time. Meanwhile we propose a depth related adaptive regularized split Bregman (DARSB) method in reconstruction. The simulation experiments show that the proposed physical model and method can achieve better results in the location error, dice coefficient, mean square error and the intensity error than the traditional split Bregman method and validate the feasibility of method. The phantom experiment can obtain the location error less than 1.1 mm and validate that the incorporation of fan-shaped X-ray beams in our model can achieve better results than the parallel X-rays.},
author = {Chen, Dongmei and Zhu, Shouping and Cao, Xu and Zhao, Fengjun and Liang, Jimin},
doi = {10.1364/BOE.6.002649},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - X-ray luminescence computed tomography imaging based on X-ray distribution model and adaptively split Bregman method.pdf:pdf},
issn = {2156-7085 (Electronic)},
journal = {Biomedical optics express},
number = {7},
pages = {2649--2663},
pmid = {26203388},
title = {{X-ray luminescence computed tomography imaging based on X-ray distribution model  and adaptively split Bregman method.}},
volume = {6},
year = {2015}
}
@article{Qu2015,
abstract = {Fluorescent gold nanoclusters (AuNCs) have been extensively studied due to their unique construction and distinctive properties, which place them between single metal atoms and larger nanoparticles. The dimension of AuNCs is comparable to the Fermi wavelength of ...},
archivePrefix = {arXiv},
arxivId = {784097},
author = {Qu, Xiaochao and Li, Yichen and Li, Lei and Wang, Yanran and Liang, Jingning and Liang, Jimin},
doi = {10.1155/2015/784097},
eprint = {784097},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - Fluorescent Gold Nanoclusters Synthesis and Recent Biological Application.pdf:pdf},
isbn = {1687-4110$\backslash$r1687-4129},
issn = {16874129},
journal = {Journal of Nanomaterials},
title = {{Fluorescent gold nanoclusters: Synthesis and recent biological application}},
volume = {2015},
year = {2015}
}
@article{Chen2015c,
abstract = {For fluorescence tomographic imaging of small animals, the liver is usually regarded as a low-scattering tissue and is surrounded by adipose, kidneys, and heart, all of which have a high scattering property. This leads to a breakdown of the diffusion equation (DE)–based reconstruction method as well as a heavy computational burden for the simplified spherical harmonics equation (SP N  ). Coupling the SP N   and DE provides a perfect balance between the imaging accuracy and computational burden. The coupled third-order SP N   and DE (CSDE)-based reconstruction method is developed for fluorescence tomographic imaging. This is achieved by doubly using the CSDE for the excitation and emission processes of the fluorescence propagation. At the same time, the finite-element method and hybrid multilevel regularization strategy are incorporated in inverse reconstruction. The CSDE-based reconstruction method is first demonstrated with a digital mouse-based liver cancer simulation, which reveals superior performance compared with the SP N   and DE-based methods. It is more accurate than the DE-based method and has lesser computational burden than the SP N  -based method. The feasibility of the proposed approach in applications of in vivo studies is also illustrated with a liver cancer mouse-based in situ experiment, revealing its potential application in whole-body imaging of small animals.},
author = {Chen, Xueli and Sun, Fangfang and Yang, Defu and Liang, Jimin},
doi = {10.1117/1.JBO.20.9.090502},
file = {:E$\backslash$:/Mendeley Papers/2015/Journal of Biomedical Optics/2015 - Journal of Biomedical Optics - Coupled third-order simplified spherical harmonics and diffusion equation–based fluorescence tomo.pdf:pdf},
isbn = {1083-3668},
issn = {1083-3668},
journal = {Journal of Biomedical Optics},
number = {9},
pages = {090502},
title = {{Coupled third-order simplified spherical harmonics and diffusion equation–based fluorescence tomographic imaging of liver cancer}},
url = {http://biomedicaloptics.spiedigitallibrary.org/article.aspx?doi=10.1117/1.JBO.20.9.090502},
volume = {20},
year = {2015}
}
@article{Hu2015,
abstract = {Cerenkov luminescence imaging (CLI) provides potential to use clinical radiotracers for optical imaging. The goal of this study was to present a newly developed endoscopic CLI (ECLI) system and illustrate its feasibility and potential in distinguishing and quantifying cancerous lesions of the GI tract. The ECLI system was established by integrating an electron-multiplying charge-coupled device camera with a flexible fibre endoscope. Phantom experiments and animal studies were conducted to test and illustrate the system in detecting and quantifying the presence of radionuclide in vitro and in vivo. A pilot clinical study was performed to evaluate our system in clinical settings. Phantom and mice experiments demonstrated its ability to acquire both the luminescent and photographic images with high accuracy. Linear quantitative relationships were also obtained when comparing the ECLI radiance with the radiotracer activity (r (2) = 0.9779) and traditional CLI values (r (2) = 0.9025). Imaging of patients revealed the potential of ECLI in the identification and quantification of cancerous tissue from normal, which showed good consistence with the clinical PET examination. The new ECLI system shows good consistence with the clinical PET examination and has great potential for clinical translation and in aiding detection of the GI tract disease.},
author = {Hu, Hao and Cao, Xin and Kang, Fei and Wang, Min and Lin, Yenan and Liu, Muhan and Li, Shujun and Yao, Liping and Liang, Jie and Liang, Jimin and Nie, Yongzhan and Chen, Xueli and Wang, Jing and Wu, Kaichun},
doi = {10.1007/s00330-014-3574-2},
file = {:E$\backslash$:/Mendeley Papers/2015/Unknown/2015 - Unknown - Feasibility study of novel endoscopic Cerenkov luminescence imaging system in detecting and quantifying gastrointestina.pdf:pdf},
isbn = {0938-7994},
issn = {14321084},
journal = {European Radiology},
keywords = {Endoscopy,Gastrointestinal disease,Molecular imaging,Optical imaging,Radionuclide imaging},
number = {6},
pages = {1814--1822},
pmid = {25577521},
title = {{Feasibility study of novel endoscopic Cerenkov luminescence imaging system in detecting and quantifying gastrointestinal disease: first human results}},
volume = {25},
year = {2015}
}

path: /publications/2015 - 副本.bib


text:
@String{aaai="Association for the Advancement of Artificial Intelligence"}
@String{aaim="International Conference on Algorithmic Aspects in Information and Management"}
@String{acl="Proceedings of the Association for Computational Linguistics"}
@String{aistats="Proceedings of Artificial Intelligence and Statistics"}
@String{cl="Computational Linguistics"}
@String{chi="International Conference on Human Factors in Computing Systems"}
@String{cvpr="Computer Vision and Pattern Recognition"}
@String{coling="Proceedings of International Conference on Computational Linguistics"}
@String{colt="Proceedings of Conference on Learning Theory"}
@String{conll="Conference on Computational Natural Language Learning"}
@String{eacl="Proceedings of the European Chapter of the Association for Computational Linguistics"}
@String{ecml="Proceedings of European Conference of Machine Learning"}
@String{emnlp="Proceedings of Empirical Methods in Natural Language Processing"}
@String{hlt="Proceedings of the Human Language Technology Conference"}
@String{ica="International Conference on Independent Component Analysis and Signal Separation"}
@String{icdm="International Conference on Data Mining"}
@String{iccv="International Conference on Computer Vision"}
@String{icwsm="International Conference on Weblogs and Social Media"}
@String{ai="Artificial Intelligence"}
@String{ijcai="International Joint Conference on Artificial Intelligence"}
@String{ijcv="International Journal of Computer Vision"}
@String{icml="Proceedings of the International Conference of Machine Learning"}
@String{ismir="International Society for Music Information Retrieval Conference"}
@String{jacm="Journal of the Association for Computing Machinery"}
@String{jasa="Journal of the American Statistical Association"}
@String{lrec="International Language Resources and Evaluation"}
@String{kdd="Knowledge Discovery and Data Mining"}
@String{jmlr="Journal of Machine Learning Research"}
@String{cikm="Proceedings of the ACM International Conference on Information and Knowledge Management"}
@String{naacl="Conference of the North American Chapter of the Association for Computational Linguistics"}
@String{nips="Proceedings of Advances in Neural Information Processing Systems"}
@String{osdi="Symposium on Operating System Design and Implementation"}
@String{pami="IEEE Transactions on Pattern Analysis and Machine Intelligence"}
@String{pnas="Proceedings of the National Academy of Sciences"}
@String{sdm="SIAM on Data Mining"}
@String{semeval="Proceedings of the Workshop on Semantic Evaluation"}
@String{sigir="Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval"}
@String{ecir="Proceedings of the European Conference on Information Retrieval"}
@String{uai="Proceedings of Uncertainty in Artificial Intelligence"}
@String{vldb="International Conference on Very Large Databases"}
@String{www="Proceedings of the ACM Conference on World Wide Web"}
@String{icassp="IEEE International Conference on Acoustics, Speech, and Signal Processing"}
@String{ica="International Conference on Independent Component Analysis and Signal Separation"}
@String{sdm="Proceedings of SIAM International Conference on Data Mining"}
@String{tacl="Transactions of the Association for Computational Linguistics"}
@String{taslp="Transactions on Audio, Speech, and Language Processing"}
@String{wsdm="Proceedings of ACM International Conference on Web Search and Data Mining"}
@String{jrssb="Journal of the Royal Statistical Society: Series B"}
% These are hardly ever used
@String{nodalida="Proceedings of the Nordic Conference on Computational Linguistics"}
@String{adcs="Proceedings of the Aurstralasian Document Computing Symposium"}

@article{miller-90,
    Abstract = {Definitions of common nouns typically give a superordinate term plus distinguishing features; that information provides the basis for organizing noun files in WordNet. The superordinate relation (hyponymy) generates a hierarchical semantic organization that is duplicated in the noun files by the use of labeled pointers between sets of synonyms (synsets). The hierarchy is limited in depth, seldom exceeding more than a dozen levels. Distinguishing features are entered in such a way as to create a lexical inheritance system, a system in which each word inherits the distinguishing features of all its superordinates. Three types of distinguishing features are discussed: attributes (modification), parts (meronymy) and functions (predication), but only meronymy is presently implemented in the noun files. Antonymy is also found between nouns, but it is not a fundamental organizing principle for nouns.  Coverage is partitioned into twenty-five topical files, each of which deals with a different primitive semantic component. Characteristics of each topic are discussed.
},
    Author = {Miller, George A.},
    Date-Added = {2006-05-01 12:28:48 -0400},
    Date-Modified = {2006-05-01 12:29:01 -0400},
    Journal = {International Journal of Lexicography},
    Number = {4},
    Pages = {245-264},
    Title = {Nouns in {WordNet}: A Lexical Inheritance System},
    Volume = {3},
    Year = {1990},
    Bdsk-Url-1 = {http://dx.doi.org/10.1093/ijl/3.4.245}
}

@inbook{Boyd-Graber:Mimno:Newman-2014,
    Publisher = {CRC Press},
    Address = {Boca Raton, Florida},
    Author = {Jordan Boyd-Graber and David Mimno and David Newman},
    Series = {CRC Handbooks of Modern Statistical Methods},
    Booktitle = {Handbook of Mixed Membership Models and Their Applications},
    Title = {Care and Feeding of Topic Models: Problems, Diagnostics, and Improvements},
    Year = {2014},
    Editor = {Edoardo M. Airoldi and David Blei and Elena A. Erosheva and Stephen E. Fienberg},
}

@misc{sandhaus-08,
    Author = {Evan Sandhaus},
    Location = {Philadelphia},
    Note = {http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp? catalogId=LDC2008T19},
    Publisher = {Linguistic Data Consortium},
    Title = {The {New York Times} Annotated Corpus},
    Year = {2008}
}

@inproceedings{Nguyen:Hu:Boyd-Graber:Resnik-2013,
    Title = {Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations},
    Booktitle = naacl,
    Author = {Viet-An Nguyen and Yuening Hu and Jordan Boyd-Graber and Philip Resnik},
    Year = {2013},
    pages = {36--39},
}

@Article{Cleveland1985,
  author =     "William S. Cleveland and Robert McGill",
  title =     "Graphical Perception and Graphical Methods for
                  Analyzing Statistical Data",
  journal =     "Science",
  volume =     "229",
  month =     "30~" # aug,
  year =      "1985",
  pages =     "828--833",
}

@incollection{kleinberg-03,
title = {An Impossibility Theorem for Clustering},
author = {Jon M. Kleinberg},
booktitle = nips,
editor = {S. Becker and S. Thrun and K. Obermayer},
year = {2003},
url = {http://papers.nips.cc/paper/2340-an-impossibility-theorem-for-clustering.pdf}
}

@Article{Viegas2009,
  title =     "Participatory Visualization with {Wordle}",
  author =     "Fernanda B. Vi{\'e}gas and Martin Wattenberg and
                  Jonathan Feinberg",
  journal =     "IEEE Transactions on Visualization and Computer
                  Graphics",
  year =      "2009",
  number =     "6",
  volume =     "15",
  pages =     "1137--1144",
}

@InProceedings{Don2007,
  title =     "Discovering interesting usage patterns in text
                  collections: integrating text mining with
                  visualization",
  author =     "Anthony Don and Elena Zheleva and Machon Gregory and
                  Sureyya Tarkan and Loretta Auvil and Tanya Clement
                  and Ben Shneiderman and Catherine Plaisant",
  booktitle =     cikm,
  year =      "2007"
}

@article{Gad2015,
  title =   "{ThemeDelta}: Dynamic Segmentations over Temporal Topic Models",
  author =  {Samah Gad and Waqas Javed and Sohaib Ghani and Niklas Elmqvist and Tom Ewing and Keith N. Hampton and Naren Ramakrishnan},
  year = {2015},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = "21",
}

@Article{Collins2009b,
  title =     "{DocuBurst}: Visualizing Document Content using
                  Language Structure",
  author =     "Christopher Collins and M. Sheelagh T. Carpendale and
                  Gerald Penn",
  journal =     "Computer Graphics Forum",
  year =      "2009",
  number =     "3",
  volume =     "28",
  pages =     "1039--1046",
}

@InProceedings{Viegas2006,
  author =     "Fernanda B. Vi{\'e}gas and Scott Golder and Judith
                  Donath",
  title =     "Visualizing email content: portraying relationships
                  from conversational histories",
  booktitle =     chi,
  year =      "2006",
}

@InProceedings{Wattenberg2002,
  title =     "Arc Diagrams: Visualizing Structure in Strings",
  author =     "Martin Wattenberg",
  year =      "2002",
  booktitle =     "Proceedings of the IEEE Symposium on Information
                  Visualization",
  pages =     "110--116",
}

@InProceedings{Rivadeneira2007,
  title =     "Getting our head in the clouds: toward evaluation
                  studies of tagclouds",
  author =     "A. W. Rivadeneira and Daniel M. Gruen and Michael J.
                  Muller and David R. Millen",
  booktitle =     chi,
  year =      "2007"
}

@InProceedings{Kim2011,
  title =      "{WordBridge:} Using Composite Tag Clouds in
                  Node-Link Diagrams for Visualizing Content and
                  Relations in Text Corpora",
  author =      "Kyung Tae Kim and Sungahn Ko and Niklas Elmqvist and
                  David S. Ebert",
  booktitle =     "Proceedings of the Hawaiian International Conference
                  on System Sciences",
  year =      "2011",
}

@Article{Koh2010,
  title =     "{ManiWordle}: Providing Flexible Control over
                  {Wordle}",
  author =     "Kyle Koh and Bongshin Lee and Bo Hyoung Kim and
                  Jinwook Seo",
  journal =     "IEEE Transactions on Visualization and Computer
                  Graphics",
  year =      "2010",
  number =     "6",
  volume =     "16",
  pages =     "1190--1197",
}

@InProceedings{Halvey2007,
  author =      "Martin Halvey and Mark T. Kean",
  title =      "An Assessment of Tag Presentation Techniques",
  booktitle =      www,
  year =      "2007",
}

@InProceedings{Kuo2007,
  title =     "Tag clouds for summarizing web search results",
  author =     "Byron Yu-Lin Kuo and Thomas Hentrich and Benjamin M.
                  Good and Mark D. Wilkinson",
  booktitle =     www,
  year =      "2007"
}

@Article{Sinclair2008,
  title =     "The folksonomy tag cloud: when is it useful?",
  author =     "James Sinclair and Michael Cardew-Hall",
  journal =     "Journal of Information Science",
  year =      "2008",
  number =     "1",
  volume =     "34",
  pages =     "15--29",
}

@InProceedings{Lohmann2009,
  title =     "Comparison of Tag Cloud Layouts: Task-Related
                  Performance and Visual Exploration",
  author =     "Steffen Lohmann and J{\"u}rgen Ziegler and Lena
                  Tetzlaff",
  booktitle =     "Proceedings of INTERACT",
  publisher =     "Springer",
  year =      "2009",
  volume =     "5726",
  pages =     "392--404",
  series =     "Lecture Notes in Computer Science",
}

@InProceedings{Wei2010,
  title =     "{TIARA}: a visual exploratory text analytic system",
  author =     "Furu Wei and Shixia Liu and Yangqiu Song and Shimei
                  Pan and Michelle X. Zhou and Weihong Qian and Lei
                  Shi and Li Tan and Qiang Zhang",
  booktitle =     cikm,
  year =      "2010",
  pages =     "153--162",
}

@InProceedings{Shi2010,
  author =      "Lei Shi and Furu Wei and Shixia Liu and Li Tan and
                  Xiaoxiao Lian and Michelle Zhou",
  title =      "Understanding Text Corpora with Multiple Facets",
  booktitle =      "Proceedings of the IEEE Conference on Visual
                  Analytics Science and Technology",
  pages =      "99-106",
  year =      "2010",
}

@InProceedings{Hassan-Montero2006,
  title =     "Improving Tag-Clouds as Visual Information Retrieval
                  Interfaces",
  author =     "Yusef Hassan-Montero and V{\'i}ctor Herrero-Solana",
  year =      "2006",
  booktitle =     "Proceedings of the International Conference on
                  Multidisciplinary Information Sciences and
                  Technologies",
}

@InProceedings{Don2007,
  title =     "Discovering interesting usage patterns in text
                  collections: integrating text mining with
                  visualization",
  author =     "Anthony Don and Elena Zheleva and Machon Gregory and
                  Sureyya Tarkan and Loretta Auvil and Tanya Clement
                  and Ben Shneiderman and Catherine Plaisant",
  booktitle =     cikm,
  year =      "2007"
}

@InProceedings{Ghoniem2007,
  author =     "Mohammad Ghoniem and Dongning Luo and Jing Yang and
                  William Ribarsky",
  booktitle =      "Proceedings of the IEEE Symposium on Visual
                  Analytics Science \& Technology",
  title =      "{NewsLab}: Exploratory Broadcast News Video
                  Analysis",
  year =      "2007",
}

@Article{Havre2002,
  author =     "Susan Havre and Elizabeth Hetzler and Paul Whitney
                  and Lucy Nowell",
  title =     "{ThemeRiver}: Visualizing Thematic Changes in Large
                  Document Collections",
  journal =     "IEEE Transactions on Visualization and Computer
                  Graphics",
  volume =     "8",
  number =     "1",
  pages =     "9--20",
  month =     jan,
  year =      "2002",
}

@InProceedings{Bateman2008,
  title =     "Seeing things in the clouds: the effect of visual
                  features on tag cloud selections",
  author =     "Scott Bateman and Carl Gutwin and Miguel A. Nacenta",
  booktitle =     "Proceedings of the ACM Conference on Hypertext and
                  Hypermedia",
  year =      "2008"
}

@Article{vanHam2009,
  title =     "Mapping Text with Phrase Nets",
  author =     "Frank van Ham and Martin Wattenberg and Fernanda B.
                  Vi{\'e}gas",
  journal =     "IEEE Transactions on Visualization and Computer
                  Graphics",
  year =      "2009",
  number =     "6",
  volume =     "15",
  pages =     "1169--1176",
}

@Article{Wattenberg2008,
  author =     "Martin Wattenberg and Fernanda B. Vi{\'e}gas",
  title =     "The Word Tree, an Interactive Visual Concordance",
  journal =     "IEEE Transactions on Visualization and Computer
                  Graphics",
  volume =     "14",
  number =     "6",
  pages =     "1221--1228",
  month =     nov # "\slash " # dec,
  year =      "2008",
}

@Article{Viegas2008,
  author =     "Fernanda B. Vi{\'e}gas and Martin Wattenberg",
  title =     "Tag Clouds and the Case for Vernacular
                  Visualization",
  journal =     "Interactions",
  year =      "2008",
  volume =     "15",
  number =     "4",
  pages =     "49--52",
}

@inproceedings{newman2010evaluating,
  title={Evaluating topic models for digital libraries},
  author={Newman, David and Noh, Youn and Talley, Edmund and Karimi, Sarvnaz and Baldwin, Timothy},
  booktitle={Proceedings of the IEEE/ACM Joint Conference on Digital Libraries},
  year={2010},
}

@article{lau2014machine,
  title={Machine reading tea leaves: Automatically evaluating topic coherence and topic model quality},
  author={Lau, Jey Han and Newman, David and Baldwin, Timothy},
  journal=eacl,
  year={2014}
}

@InProceedings{Wise1995,
  author =    "James A. Wise and James J. Thomas and Kelly Pennock
             and David Lantrip and Marc Pottier and Anne Schur and
             Vern Crow",
  title =        "Visualizing the non-visual: spatial analysis and
                 interaction with information from text documents",
  booktitle =    "Proceedings of the IEEE Symposium on Information Visualization",
  year =         "1995"
}

@InProceedings{Shneiderman1996,
  author =    "Ben Shneiderman",
  title =    "The Eyes Have It: {A} Task by Data Type Taxonomy for Information Visualizations",
  booktitle =    "Proceedings of the IEEE Symposium on Visual Languages",
  year =     "1996",
}

@inproceedings{wallach2009evaluation,
  title={Evaluation methods for topic models},
  author={Wallach, Hanna M and Murray, Iain and Salakhutdinov, Ruslan and Mimno, David},
  booktitle=icml,
  year={2009},
}

@book{playfair1786,
  title={The commercial and political atlas: Representing, by means of stained copper-plate charts, the progress of the commerce, revenues, expenditure and debts of England during the whole of the Eighteenth Century},
  author={Playfair, William},
  year={1786},
}

@article{fruchterman1991graph,
  title={Graph drawing by force-directed placement},
  author={Fruchterman, Thomas MJ and Reingold, Edward M},
  journal={Software: Practice and experience},
  volume={21},
  number={11},
  pages={1129--1164},
  year={1991},
  publisher={Wiley Online Library}
}

@Article{Blei2012,
  title =    "Probabilistic topic models",
  author =    "David M. Blei",
  journal =    "Communications of the ACM",
  year =     "2012",
  number =    "4",
  volume =    "55",
  pages =    "77--84",
}

@inproceedings{malik2013topicflow,
  title={{TopicFlow}: visualizing topic alignment of twitter data over time},
  author={Malik, Sana and Smith, Alison and Hawes, Timothy and Papadatos, Panagis and Li, Jianyu and Dunne, Cody and Shneiderman, Ben},
  booktitle={Proceedings of the IEEE/ACM Conference on Advances in Social Networks Analysis and Mining},
  pages={720--726},
  year={2013},
}
n},
  volume = {19},
  number = {3},
  pages = {19},
  year = {2012},
}

% not sure about the formatting of this one
@online{steinbock11,
@author={Steinbock, Daniel},
title={{TagCrowd} visualization: State of the Union},
year={2011},
howpublished = "\url{http://www.tagcrowd.com/blog/2011/03/05/state-of-the-union-2002-vs-2011/}"
}

@inproceedings{halvey2007assessment,
  title={An assessment of tag presentation techniques},
  author={Halvey, Martin J and Keane, Mark T},
  booktitle=www,
  year={2007},
}

@inproceedings{collins2009parallel,
  title={Parallel tag clouds to explore and analyze faceted text corpora},
  author={CollVisualization and Computer Graphics},
  volume = "16",
  number = "6",
  pages={1182--1189},
  year={2010},
}

@Article{Shneiderman1992,
  author =    "Ben Shneiderman",
  title =    "Tree visualization with treemaps: a {2-D} space-filling
         approach",
  journal =    "ACM Transactions on Graphics",
  year =     "1992",
  volume =    "11",
  number =    "1",
  month =    jan,
  pages =    "92--99",
}

@inproceedings{rodrigues2011group,
  title={Group-in-a-Box layout for multi-faceted analysis of communities},
  author={Rodrigues, Eduarda Mendes and Milic-Frayling, Natasa and Smith, Marc and Shneiderman, Ben and Hansen, Derek},
  booktitle={Proceedings of the IEEE Conference on Social Computing},
  pages={354--361},
  year={2011},
}

@inproceedings{aleteras-14,
  title={Representing topics labels for exploring digital libraries},
  author={Aletras, Nikolaos and Baldwin, Timothy and Lau, Jey Han and Stevenson, Mark},
  booktitle={Proceedings of the IEEE/ACM Joint Conference on Digital Libraries},
  pages={239--248},
  year={2014},
}

@misc{harris11,
author={Harris, Jacob},
title={Word clouds considered harmful},
year={2011},
howpublished = "\url{http://www.niemanlab.org/2011/10/word-clouds-considered-harmful/}"
}

% Word cloud python implementation that we used
@misc{amueller2012,
  author = {Mueller, Andrew},
  title = {Word Cloud},
  year = {2012},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/amueller/word_cloud}},
  commit = {e9015fd537}
}


text:
@inbook{,
  abstract = {Abstract textwith linebreak},
  author = {Name},
  booktitle = {Test Title},
  pages = {10},
  year = {2000}
}

repository: JabRef/jabref

repo_name: JabRef/jabref

branch_name: refs/heads/main

gha_language: Java


text:
DESCRIPTION = "GPE contacts manager"
LICENSE = "GPL"
SECTION = "gpe"

DEPENDS = "libcontactsdb libgpewidget libgpepimc libdisplaymigration libgpevtype dbus-glib"
RDEPENDS_${PN} = "gpe-icons"
PR = "r1"

GPE_TARBALL_SUFFIX = "bz2"

inherit gpe autotools

FILES_${PN} += " ${datadir}/gpe ${datadir}/gpe-contacts"

SRC_URI[md5sum] = "5fcffd454e9c8f0b14804283c32da0ee"
SRC_URI[sha256sum] = "5ceab2c275036da754ae7b7cbe162f9f2a5936334050beb34838d4f82e89843c"


text:
import { connect } from 'react-redux'
import { getReviewDetail, getReviewList, storeReviewId, followArchive } from '../../store/ArchivePage/actions'
import ArchiveReviewList from '../../components/pages/ArchivePage/molecules/ArchiveReviewList'

const mapStateToProps = (state) => {
  return {
    statefunction: state,
  }
}

const mapDispatchToProps = (dispatch) => {
  return {
    onReviewClick: (reviewId, archiveOwnerNickname) => {
      dispatch(getReviewDetail(reviewId, archiveOwnerNickname))
    },
    requestReviews: (sortOption, archiveOwnerNickname) => {
      dispatch(getReviewList(sortOption, archiveOwnerNickname))
    },
    sendReviewId: (id) => {
      dispatch(storeReviewId(id))
    },
    doFollow: (archiveOwner) => {
      dispatch(followArchive(archiveOwner))
    }
  }
}

export default connect(mapStateToProps, mapDispatchToProps)(ArchiveReviewList)

gha_language: JavaScript


text:
%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/
%% Created for  at 2010-09-29 17:00:14 -0500
%% Saved with string encoding Unicode (UTF-8)

@techreport{AMD1995,
	Author = {AMD},
	Date-Added = {2008-07-09 13:16:06 -0500},
	Date-Modified = {2008-07-09 13:17:46 -0500},
	Institution = {AMD},
	Number = {18448D},
	Title = {{CPU Thermal Management}},
	Type = {Application Note},
	Year = {1995}}


text:
package main

import (
	"encoding/json"
	"fmt"
	"os"

	"github.com/atulanand206/go-kafka"
	"github.com/atulanand206/go-mongo"
	"github.com/atulanand206/ms-db-publisher/objects"
	"github.com/atulanand206/ms-db-publisher/routes"
	"github.com/joho/godotenv"
)

func main() {
	godotenv.Load()

	// Register the MongoDB cloud atlas database.
	mongoClientId := os.Getenv("MONGO_CLIENT_ID")
	database := os.Getenv("DATABASE")
	collection := os.Getenv("MONGO_COLLECTION")

	mongo.ConfigureMongoClient(mongoClientId)

	// Register the Kafka cluster subscriber.
	kafkaTopic := os.Getenv("KAFKA_TOPIC")
	kafkaBrokerId := os.Getenv("KAFKA_BROKER_ID")

	kafka.LoadConsumer(kafkaBrokerId, kafkaTopic)
	kafka.Read(func(val string) {
		// Decode the kafka response from message.
		r := &objects.Response{}
		json.Unmarshal([]byte(val), &r)
		var game = r.Match
		document, _ := mongo.Document(&game)
		// Create a game in the database.
		mongo.Write(database, collection, *document)
		// Get the user from the users service.
		user, err := routes.GetUser(game.Player.Username, r.Token)
		if err != nil {
			return
		}
		// Create the  user request
		var userRequest objects.UserRequest
		userRequest.Username = user.Username
		userRequest.Name = user.Name
		userRequest.Rating = user.Rating + game.Score
		// Update the user in the database.
		_, err = routes.UpdateUser(user.Id, userRequest, r.Token)
		if err != nil {
			fmt.Println(err)
			return
		}
	})
}


text:
@incollection{Treichler:2017,
  booktitle={Exascale Scientific Applications: Scalability and Performance Portability},
  editor={Straatsma, T.P. and Antypas, K.B. and Williams, T.J.},
  title = "{S3D-Legion: An Exascale Software for Direct Numerical Simulation of Turbulent Combustion with Complex Multicomponent Chemistry}",
  author={Treichler, Sean and Bauer, Michael A. and Bhagatwala, Ankit V. and Borghesi, Giulio and Sankaran, Ramanan and Kolla, Hemanth and Larkin, Jeffrey M. and Slaughter, Elliott and Lee, Wonchan and Aiken, Alex and Chen, Jacqueline H. and McCormick, Patrick S.},
  isbn={9781351999236},
  series={Chapman \& Hall/CRC Computational Science},
  url={https://books.google.com/books?id=rGQ-DwAAQBAJ},
  month={11},
  year={2017},
  publisher={CRC Press}
}

repository: ndebard/ECP-ST-CAR-PUBLIC

repo_name: ndebard/ECP-ST-CAR-PUBLIC


text:
@inproceedings{card.2018,
  author = {Dallas Card and Chenhao Tan and Noah A. Smith},
  title = {Neural Models for Documents with Metadata},
  booktitle = {Proceedings of ACL},
  year = {2018},
}

repository: rococode/scholar

repo_name: rococode/scholar

gha_language: Python


text:
@article{POLLAK2023120176,
title = {Quantifying MR head motion in the Rhineland Study – A robust method for population cohorts},
journal = {NeuroImage},
volume = {275},
pages = {120176},
year = {2023},
issn = {1053-8119},
doi = {https://doi.org/10.1016/j.neuroimage.2023.120176},
url = {https://www.sciencedirect.com/science/article/pii/S1053811923003270},
author = {Clemens Pollak and David Kügler and Monique M.B. Breteler and Martin Reuter},
abstract = {Head motion during MR acquisition reduces image quality and has been shown to bias neuromorphometric analysis. The quantification of head motion, therefore, has both neuroscientific as well as clinical applications, for example, to control for motion in statistical analyses of brain morphology, or as a variable of interest in neurological studies. The accuracy of markerless optical head tracking, however, is largely unexplored. Furthermore, no quantitative analysis of head motion in a general, mostly healthy population cohort exists thus far. In this work, we present a robust registration method for the alignment of depth camera data that sensitively estimates even small head movements of compliant participants. Our method outperforms the vendor-supplied method in three validation experiments: 1. similarity to fMRI motion traces as a low-frequency reference, 2. recovery of the independently acquired breathing signal as a high-frequency reference, and 3. correlation with image-based quality metrics in structural T1-weighted MRI. In addition to the core algorithm, we establish an analysis pipeline that computes average motion scores per time interval or per sequence for inclusion in downstream analyses. We apply the pipeline in the Rhineland Study, a large population cohort study, where we replicate age and body mass index (BMI) as motion correlates and show that head motion significantly increases over the duration of the scan session. We observe weak, yet significant interactions between this within-session increase and age, BMI, and sex. High correlations between fMRI and camera-based motion scores of proceeding sequences further suggest that fMRI motion estimates can be used as a surrogate score in the absence of better measures to control for motion in statistical analyses.}
}


text:
DESCRIPTION = "A frontend for the nmap port scanner, Qt/Embedded Palmtop Environment"
SECTION = "opie/applications"
PRIORITY = "optional"
LICENSE = "GPL"
RDEPENDS_${PN} = "nmap"
PR = "r1"

SRC_URI = "http://www.bluelightning.org/qpe-nmap/files/qpe-nmap-${PV}.tar.bz2"

APPNAME = "qpe-nmap"
APPTYPE = "binary"
APPDESKTOP = "${WORKDIR}"

S = "${WORKDIR}/qpe-nmap"

inherit opie

do_install () {
    install -d ${D}${palmtopdir}/pics/${APPNAME}/
    install -m 0644 ${WORKDIR}/qpe-nmap/ipk/opt/QtPalmtop/pics/qpe-nmap.png ${D}${palmtopdir}/pics/
    install -d ${D}${palmtopdir}/apps/Applications/
    install -m 0644 ${WORKDIR}/qpe-nmap/ipk/opt/QtPalmtop/apps/Applications/qpe-nmap.desktop ${D}${palmtopdir}/apps/Applications/
}

SRC_URI[md5sum] = "82d20f06942324af7fc4ce302efb1028"
SRC_URI[sha256sum] = "5ea7f9188aa221f004db1688713f35199adf3075d0b54f2bffa2461e9f11ee05"