text:
#
# base recipe: http://cgit.openembedded.org/cgit.cgi/meta-openembedded/tree/meta-networking/recipes-support/ipvsadm/ipvsadm_1.26.bb?h=master
# base branch: master
#
SUMMARY = "Linux Virtual Server administration Utility"
DESCRIPTION = "Ipvsadm  is  used  to set up, maintain or inspect the virtual server \
table in the Linux kernel. The Linux Virtual  Server  can  be  used  to \
build  scalable  network  services  based  on  a cluster of two or more nodes. \
The active node of the cluster redirects service requests  to  a \
collection  of  server  hosts  that will actually perform the services. \
Supported features include two protocols (TCP and UDP),  three  packet-forwarding \
methods (NAT, tunneling, and direct routing), and eight load balancing algorithms \
(round robin, weighted round robin,  least-connec-tion, weighted least-connection, \
locality-based  least-connection, locality-based least-connection with replication, \
destination-hashing, and source-hashing)."
SECTION = "net"

inherit debian-package
PR = "r0"

LICENSE = "GPL-2.0"
LIC_FILES_CHKSUM = "file://README;beginline=40;endline=56;md5=a54cba37b64924aa5008881607942892"

DEPENDS += "libnl popt"

# 0001-Modify-the-Makefile-for-cross-compile.patch: Modify the Makefile for cross compile
# 0002-Replace-nl_handle-to-nl_sock.patch: The nl_handle was replace with nl_sock in the libnl-3
SRC_URI += " \
	file://0001-Modify-the-Makefile-for-cross-compile.patch \
	file://0002-Replace-nl_handle-to-nl_sock.patch \
    "

do_compile() {
	oe_runmake \
	CC="${CC} -I${STAGING_INCDIR} -I${STAGING_INCDIR}/libnl3 -L${STAGING_LIBDIR}" all
}

do_install() {
	oe_runmake 'BUILD_ROOT=${D}' install

	install -d ${D}${sysconfdir}/default
	install -m 0644 ${S}/debian/ipvsadm.default ${D}${sysconfdir}/default/ipvsadm
}

repository: nghiaht-tsdv/meta-debian

repo_name: nghiaht-tsdv/meta-debian

branch_name: refs/heads/jethro


text:
// Copyright 2018 ETH Zurich
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//   http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package main

func shortcut_peer_to_internal_host() int {
	pkt0 := AllocatePacket()
	pkt0.ParsePacket(`
		Ethernet: SrcMAC=f0:0d:ca:fe:be:ef DstMAC=f0:0d:ca:fe:00:12 EthernetType=IPv4
		IP4: Src=192.168.12.3 Dst=192.168.12.2 NextHdr=UDP Flags=DF
		UDP: Src=40000 Dst=50000
		SCION: NextHdr=UDP CurrInfoF=8 CurrHopF=10 SrcType=IPv4 DstType=IPv4
			ADDR: SrcIA=1-ff00:0:2 Src=172.16.2.1 DstIA=1-ff00:0:1 Dst=192.168.0.51
			IF_1: ISD=1 Hops=3 Flags=Peer
				HF_1: ConsIngress=231 ConsEgress=0   Flags=Xover
				HF_2: ConsIngress=211 ConsEgress=0   Flags=Xover
				HF_3: ConsIngress=0   ConsEgress=321
			IF_2: ISD=1 Hops=3 Flags=ConsDir
				HF_4: ConsIngress=0   ConsEgress=311
				HF_5: ConsIngress=121 ConsEgress=0   Flags=Xover
				HF_6: ConsIngress=131 ConsEgress=0   Flags=Xover
		UDP_1: Src=40111 Dst=40222
	`)
	pkt0.SetDev("veth_121")
	pkt0.SetChecksum("UDP", "IP4")
	pkt0.SetChecksum("UDP_1", "SCION")
	pkt0.GenerateMac("SCION", "IF_2", "HF_5", "HF_4")

	pkt1 := pkt0.CloneAndUpdate(`
		Ethernet: SrcMAC=f0:0d:ca:fe:00:01 DstMAC=f0:0d:ca:fe:be:ef
		IP4: Src=192.168.0.11 Dst=192.168.0.51 Checksum=0
		UDP: Src=30001 Dst=30041
	`)
	pkt1.SetDev("veth_int")
	pkt1.SetChecksum("UDP", "IP4")

	SendPackets(pkt0)

	return ExpectedPackets("shortcut peer to internal/host", defaultTimeout, pkt1)
}

func shortcut_internal_host_to_peer() int {
	// XXX should we check both segments have Peer flag set? currently not required
	pkt0 := AllocatePacket()
	pkt0.ParsePacket(`
		Ethernet: SrcMAC=f0:0d:ca:fe:be:ef DstMAC=f0:0d:ca:fe:00:01 EthernetType=IPv4
		IP4: Src=192.168.0.51 Dst=192.168.0.11 NextHdr=UDP Flags=DF
		UDP: Src=30041 Dst=30001
		SCION: NextHdr=UDP CurrInfoF=4 CurrHopF=6 SrcType=IPv4 DstType=IPv4
			ADDR: SrcIA=1-ff00:0:1 Src=192.168.0.51 DstIA=1-ff00:0:2 Dst=172.16.2.1
			IF_1: ISD=1 Hops=3 Flags=Peer,Shortcut
				HF_1: ConsIngress=131 ConsEgress=0   Flags=Xover
				HF_2: ConsIngress=121 ConsEgress=0   Flags=Xover
				HF_3: ConsIngress=0   ConsEgress=311 Flags=VerifyOnly
			IF_2: ISD=1 Hops=3 Flags=ConsDir
				HF_4: ConsIngress=0   ConsEgress=321 Flags=VerifyOnly
				HF_5: ConsIngress=211 ConsEgress=0   Flags=Xover
				HF_6: ConsIngress=231 ConsEgress=0   Flags=Xover
		UDP_1: Src=40111 Dst=40222
	`)
	pkt0.SetDev("veth_int")
	pkt0.SetChecksum("UDP", "IP4")
	pkt0.SetChecksum("UDP_1", "SCION")
	pkt0.GenerateMac("SCION", "IF_1", "HF_1", "HF_3")
	pkt0.GenerateMac("SCION", "IF_1", "HF_2", "HF_1")

	pkt1 := pkt0.CloneAndUpdate(`
		Ethernet: SrcMAC=f0:0d:ca:fe:00:12 DstMAC=f0:0d:ca:fe:be:ef
		IP4: Src=192.168.12.2 Dst=192.168.12.3 Checksum=0
		UDP: Src=50000 Dst=40000
		SCION: CurrInfoF=8 CurrHopF=10
	`)
	pkt1.SetDev("veth_121")
	pkt1.SetChecksum("UDP", "IP4")

	SendPackets(pkt0)

	return ExpectedPackets("shortcut internal/host to peer", defaultTimeout, pkt1)
}

func shortcut_peer_to_internal_child() int {
	pkt0 := AllocatePacket()
	pkt0.ParsePacket(`
		Ethernet: SrcMAC=f0:0d:ca:fe:be:ef DstMAC=f0:0d:ca:fe:00:12 EthernetType=IPv4
		IP4: Src=192.168.12.3 Dst=192.168.12.2 NextHdr=UDP Flags=DF
		UDP: Src=40000 Dst=50000
		SCION: NextHdr=UDP CurrInfoF=8 CurrHopF=10 SrcType=IPv4 DstType=IPv4
			ADDR: SrcIA=1-ff00:0:2 Src=172.16.2.1 DstIA=1-ff00:0:8 Dst=172.16.8.1
			IF_1: ISD=1 Hops=3 Flags=Peer
				HF_1: ConsIngress=231 ConsEgress=0   Flags=Xover
				HF_2: ConsIngress=211 ConsEgress=0   Flags=Xover
				HF_3: ConsIngress=0   ConsEgress=321 Flags=VerifyOnly
			IF_2: ISD=1 Hops=4 Flags=ConsDir,Shortcut,Peer
				HF_4: ConsIngress=0   ConsEgress=311 Flags=VerifyOnly
				HF_5: ConsIngress=121 ConsEgress=181 Flags=Xover
				HF_6: ConsIngress=131 ConsEgress=181 Flags=Xover
				HF_7: ConsIngress=811 ConsEgress=0
		UDP_1: Src=40111 Dst=40222
	`)
	pkt0.SetDev("veth_121")
	pkt0.SetChecksum("UDP", "IP4")
	pkt0.SetChecksum("UDP_1", "SCION")
	pkt0.GenerateMac("SCION", "IF_2", "HF_6", "HF_4")
	pkt0.GenerateMac("SCION", "IF_2", "HF_5", "HF_6")

	pkt1 := pkt0.CloneAndUpdate(`
		Ethernet: SrcMAC=f0:0d:ca:fe:00:01 DstMAC=f0:0d:ca:fe:be:ef
		IP4: Src=192.168.0.11 Dst=192.168.0.13 Checksum=0
		UDP: Src=30001 Dst=30003
		SCION: CurrHopF=11
	`)
	pkt1.SetDev("veth_int")
	pkt1.SetChecksum("UDP", "IP4")

	SendPackets(pkt0)

	return ExpectedPackets("shortcut peer to internal/child", defaultTimeout, pkt1)
}

func shortcut_internal_child_to_peer() int {
	// Xover child/peer
	pkt0 := AllocatePacket()
	pkt0.ParsePacket(`
		Ethernet: SrcMAC=f0:0d:ca:fe:be:ef DstMAC=f0:0d:ca:fe:00:01 EthernetType=IPv4
		IP4: Src=192.168.0.13 Dst=192.168.0.11 NextHdr=UDP Flags=DF
		UDP: Src=30003 Dst=30001
		SCION: NextHdr=UDP CurrInfoF=4 CurrHopF=7 SrcType=IPv4 DstType=IPv4
			ADDR: SrcIA=1-ff00:0:8 Src=172.16.8.1 DstIA=1-ff00:0:2 Dst=172.16.2.1
			IF_1: ISD=1 Hops=4 Flags=Shortcut,Peer
				HF_1: ConsIngress=811 ConsEgress=0
				HF_2: ConsIngress=162 ConsEgress=181 Flags=Xover
				HF_3: ConsIngress=121 ConsEgress=181 Flags=Xover
				HF_4: ConsIngress=0   ConsEgress=612 Flags=VerifyOnly
			IF_2: ISD=1 Hops=3 Flags=ConsDir
				HF_5: ConsIngress=0   ConsEgress=621 Flags=VerifyOnly
				HF_6: ConsIngress=211 ConsEgress=0   Flags=Xover
				HF_7: ConsIngress=261 ConsEgress=0   Flags=Xover
		UDP_1: Src=40111 Dst=40222
	`)
	pkt0.SetDev("veth_int")
	pkt0.SetChecksum("UDP", "IP4")
	pkt0.SetChecksum("UDP_1", "SCION")
	pkt0.GenerateMac("SCION", "IF_1", "HF_2", "HF_4")
	pkt0.GenerateMac("SCION", "IF_1", "HF_3", "HF_2")

	pkt1 := pkt0.CloneAndUpdate(`
		Ethernet: SrcMAC=f0:0d:ca:fe:00:12 DstMAC=f0:0d:ca:fe:be:ef
		IP4: Src=192.168.12.2 Dst=192.168.12.3 Checksum=0
		UDP: Src=50000 Dst=40000
		SCION: CurrInfoF=9 CurrHopF=11
	`)
	pkt1.SetDev("veth_121")
	pkt1.SetChecksum("UDP", "IP4")

	SendPackets(pkt0)

	return ExpectedPackets("shortcut internal/child to peer", defaultTimeout, pkt1)
}

repository: xingyang-liu/scion

license_type: permissive

repo_name: xingyang-liu/scion

branch_name: refs/heads/master

extension: go


text:
DESCRIPTION = "PyRAF is a Python-based interface to IRAF."
HOMEPAGE = "http://www.stsci.edu/resources/software_hardware/pyraf"
AUTHOR = "Space Telescope Science Institute"
SECTION = "devel/python"
LICENSE = "AURA"
PR = "ml1"

SRC_URI = "ftp://ra.stsci.edu/pub/pyraf/release/pyraf-${PV}.tar.gz"
S = "${WORKDIR}/pyraf-${PV}"

inherit distutils

RDEPENDS_${PN} = "python-numarray"

SRC_URI[md5sum] = "9a728aef7bebcd54abc103b00e2e1de6"
SRC_URI[sha256sum] = "dc0f68f2d22cad2166ae3912e20713bb29df1e1450dff18eb426a74ef4087d2a"

license: MIT

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD

extension: bb


text:
require powertop.inc
PR = "${INC_PR}.0"

SRC_URI[md5sum] = "38fd8a6825cd62b6c22df8a44b4e27d0"
SRC_URI[sha256sum] = "7325ea46e5af59c12ea024e69622ac7753010c8de615d668e1f03b0fc05bad3a"


text:
@article{clayton2022bio,
 author = {Clayton, Sophie and Alexander, Harriet and Graff, Jason R and Poulton, Nicole J and Thompson, Luke R and Benway, Heather and Boss, Emmanuel and Martiny, Adam},
 journal = {Frontiers in Marine Science},
 title = {Bio-GO-SHIP: The Time Is Right to Establish Global Repeat Sections of Ocean Biology},
 volume = {8},
 year = {2022}
}

repository: AlexanderLabWHOI/academic-kickstart

repo_name: AlexanderLabWHOI/academic-kickstart

gha_license_id: MIT

gha_language: TeX

extension: bib


text:
#----------------------------------------------------------------
# Generated CMake target import file for configuration "Release".
#----------------------------------------------------------------

# Commands may need to know the format version.
set(CMAKE_IMPORT_FILE_VERSION 1)

# Import target "rmf_door_msgs::rmf_door_msgs__rosidl_generator_c" for configuration "Release"
set_property(TARGET rmf_door_msgs::rmf_door_msgs__rosidl_generator_c APPEND PROPERTY IMPORTED_CONFIGURATIONS RELEASE)
set_target_properties(rmf_door_msgs::rmf_door_msgs__rosidl_generator_c PROPERTIES
  IMPORTED_LOCATION_RELEASE "${_IMPORT_PREFIX}/lib/librmf_door_msgs__rosidl_generator_c.so"
  IMPORTED_SONAME_RELEASE "librmf_door_msgs__rosidl_generator_c.so"
  )

list(APPEND _IMPORT_CHECK_TARGETS rmf_door_msgs::rmf_door_msgs__rosidl_generator_c )
list(APPEND _IMPORT_CHECK_FILES_FOR_rmf_door_msgs::rmf_door_msgs__rosidl_generator_c "${_IMPORT_PREFIX}/lib/librmf_door_msgs__rosidl_generator_c.so" )

# Commands beyond this point should not need to know the version.
set(CMAKE_IMPORT_FILE_VERSION)

branch_name: refs/heads/main

extension: cmake


text:
DESCRIPTION = "Hans 19E"

PN = "enigma2-plugin-settings-hans-19e-23e"

SETTINGS_FILENAME = "hans_19e_23e_e2"

include hans.inc


text:
require navit.inc

SRCREV = "4345"
PV = "0.2.0+svnr${SRCPV}"
PR = "${INC_PR}.12"

S = "${WORKDIR}/navit"
SRC_URI += "svn://anonymous@navit.svn.sourceforge.net/svnroot/navit/trunk;module=navit;proto=https "

repository: buglabs/oe-buglabs

repo_name: buglabs/oe-buglabs


text:
DESCRIPTION = "Lua Lanes is a Lua extension library providing the possibility to run multiple Lua states in parallel."
HOMEPAGE = "https://github.com/LuaLanes/lanes"
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://COPYRIGHT;md5=8cd4045dac80d5036b8a09fed113236e"

DEPENDS += "lua5.1-native"
RDEPENDS_${PN} += "lua5.1"

PR = "r0"
PV = "2.1.0+gitr${SRCREV}"

S = "${WORKDIR}/git/"
SRCREV = "507e02b20f4ce2c57c18992fe68430b0ffb3eee9"

SRC_URI = "git://github.com/LuaLanes/lanes.git;protocol=git \
           file://makefile.patch \
          "

UCLIBC_PATCHES = "file://uclibc.patch"
SRC_URI_append_libc-uclibc = "${UCLIBC_PATCHES}"

LUA_LIB_DIR =  "${libdir}/lua/5.1"
LUA_SHARE_DIR = "${datadir}/lua/5.1"

PACKAGES = "${PN} ${PN}-dbg"
FILES_${PN} = "${LUA_LIB_DIR}/lua51-lanes.so ${LUA_SHARE_DIR}/lanes.lua"
FILES_${PN}-dbg = "${LUA_LIB_DIR}/.debug/lua51-lanes.so"

EXTRA_OEMAKE = "MYFLAGS='${CFLAGS} ${LDFLAGS}'"

do_install() {
	oe_runmake install DESTDIR='${D}/usr'
}

repository: balister/openembedded

repo_name: balister/openembedded


text:
package handlers

var B = `

var Download = http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
	filter := bson.M{"status": TesteeStatus}
	filename := "file.xlsx"
	owner := r.Header.Get("owner")
	if r.Header.Get("status") == AdminStatus {
		owner = r.FormValue("psyUid")
		if owner != "" {
			filter["owner"] = TrimStr(owner, 30)
		}
	}

	grade := TrimStr(r.FormValue("grade"), 30)
	if grade != "" {
		filter["grade"] = NewB64UpString(grade)
	}
	var file *excelize.File
	switch TrimStr(r.FormValue("target"), 20) {
	case "not_yet":
		filter["result"] = -1
		ctx, _ := context.WithTimeout(context.Background(), 5*time.Second)
		cur, err := UsersCol.Find(ctx, filter)
		if err != nil {
			JsonMsg{Kind: FatalKind, Msg: "Не удалось извлечь список испытуемых | " + err.Error()}.Send(w)
			return
		}
		if cur == nil {
			JsonMsg{Kind: FatalKind, Msg: "ТАКОГО НЕ МОЖЕТ СЛУЧИТСЯ, ПОТОМУ ЧТО НЕ МОЖЕТ. КУРСОР, МАТЬ ЕГО, СТАЛ NIL"}.Send(w)
			return
		}
		defer cur.Close(context.TODO())

		file, err = excelize.OpenFile(Config.CurPath + "/not_yet_template.xlsx")
		if err != nil {
			JsonMsg{Kind: FatalKind, Msg: "Не удалось открыть заготовку not_yet_template.xlsx | " + err.Error()}.Send(w)
			return
		}
		row := 2
		ctx, _ = context.WithTimeout(context.Background(), 10*time.Second)
		for cur.Next(ctx) {
			var elem Testee
			err := cur.Decode(&elem)
			if err != nil {
				JsonMsg{Kind: FatalKind, Msg: "В процессе декодирования испытуемых произошла ошибка | " + err.Error()}.Send(w)
				return
			}
			pas, err := Decrypt(elem.Pas)
			login := elem.Login.Decode()
			if err != nil {
				JsonMsg{Kind: FatalKind, Msg: fmt.Sprintf("В процессе дешифрования пароля пользователя %v произошла ошибка | %v", elem.Login.Decode(), err.Error())}.Send(w)
				return
			}
			_ = file.SetCellValue("Логины", "A"+strconv.Itoa(row), login)
			_ = file.SetCellValue("Логины", "B"+strconv.Itoa(row), pas)
			VPrint(elem.Msg)
			if elem.Msg != "" {
				_ = file.SetCellValue("Логины", "D"+strconv.Itoa(row), "Удален")
			}
			row++
		}
		if err := cur.Err(); err != nil {
			JsonMsg{Kind: FatalKind, Msg: "У курсора произошла ошибка | " + err.Error()}.Send(w)
			return
		}
		filename = "Логины.xlsx"

	case "done":
		filter["result"] = bson.D{{"$gt", -1}}
		ctx, _ := context.WithTimeout(context.Background(), 5*time.Second)
		cur, err := UsersCol.Find(ctx, filter)
		if err != nil {
			JsonMsg{Kind: FatalKind, Msg: "Не удалось извлечь список испытуемых | " + err.Error()}.Send(w)
			return
		}
		if cur == nil {
			JsonMsg{Kind: FatalKind, Msg: "ТАКОГО НЕ МОЖЕТ СЛУЧИТСЯ, ПОТОМУ ЧТО НЕ МОЖЕТ. КУРСОР, МАТЬ ЕГО, СТАЛ NIL"}.Send(w)
			return
		}
		defer cur.Close(context.TODO())

		file, err = excelize.OpenFile(Config.CurPath + "/done_template.xlsx")
		if err != nil {
			JsonMsg{Kind: FatalKind, Msg: "Не удалось открыть заготовку done_template.xlsx | " + err.Error()}.Send(w)
			return
		}
		row := 2
		ctx, _ = context.WithTimeout(context.Background(), 10*time.Second)
		for cur.Next(ctx) {
			var elem Testee
			var rowStr = strconv.Itoa(row)
			err := cur.Decode(&elem)
			if err != nil {
				JsonMsg{Kind: FatalKind, Msg: "В процессе декодирования испытуемых произошла ошибка | " + err.Error()}.Send(w)
				return
			}

			_ = file.SetCellValue("Результаты", "A"+rowStr, elem.Login.Decode())
			_ = file.SetCellValue("Результаты", "B"+rowStr, elem.Grade.Decode())
			_ = file.SetCellValue("Результаты", "C"+rowStr, strings.Join(elem.Tests, ", "))
			_ = file.SetCellValue("Результаты", "D"+rowStr, time.Unix(int64(elem.CreatedDate), 0).UTC().Add(MskOffset*time.Second).Format("2006-01-02 15:04:05")+" МСК")
			_ = file.SetCellValue("Результаты", "E"+rowStr, elem.Result)
			_ = file.SetCellValue("Результаты", "F"+rowStr, ResultDecode[elem.Result][1])
			row++
		}
		if err := cur.Err(); err != nil {
			JsonMsg{Kind: FatalKind, Msg: "У курсора произошла ошибка | " + err.Error()}.Send(w)
			return
		}
		for row := 2; row < 9; row++ {
			strRow := strconv.Itoa(row)
			formula, _ := file.GetCellFormula("Результаты", "J"+strRow)
			_ = file.SetCellFormula("Результаты", "I"+strRow, formula)
			_ = file.SetCellFormula("Результаты", "J"+strRow, "")
			_ = file.SetCellStr("Результаты", "J"+strRow, "")
		}
		filename = "Результаты.xlsx"
	}

	w.Header().Set("Content-Type", "application/octet-stream")
	w.Header().Set("Content-Disposition", fmt.Sprintf(attachment; filename="%v", filename))
	w.Header().Set("File-Name", filename)
	w.Header().Set("Content-Transfer-Encoding", "binary")
	w.Header().Set("Expires", "0")
	err := file.Write(w)
	if err != nil {
		JsonMsg{Kind: FatalKind, Msg: "В процессе конвертации в json возникла ошибка | " + err.Error()}.Send(w)
		return
	}
})
`

repository: Sergisa/go-soam

repo_name: Sergisa/go-soam


text:
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// 	protoc-gen-go v1.30.0
// 	protoc        v3.21.6
// source: mcube/pb/resource/meta.proto

package resource

import (
	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
	reflect "reflect"
	sync "sync"
)

const (
	// Verify that this generated code is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
	// Verify that runtime/protoimpl is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)

type Meta struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// 对象Id
	// @gotags: bson:"_id" json:"id"
	Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id" bson:"_id"`
	// 创建时间
	// @gotags: bson:"create_at" json:"create_at"
	CreateAt int64 `protobuf:"varint,2,opt,name=create_at,json=createAt,proto3" json:"create_at" bson:"create_at"`
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	// @gotags: bson:"update_at" json:"update_at"
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	// 更新人
	// @gotags: bson:"update_by" json:"update_by"
	UpdateBy string `protobuf:"bytes,4,opt,name=update_by,json=updateBy,proto3" json:"update_by" bson:"update_by"`
}

func (x *Meta) Reset() {
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		mi := &file_mcube_pb_resource_meta_proto_msgTypes[0]
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func (x *Meta) String() string {
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		if ms.LoadMessageInfo() == nil {
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func (x *Scope) String() string {
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func (*Scope) ProtoMessage() {}

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func (*Scope) Descriptor() ([]byte, []int) {
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func file_mcube_pb_resource_meta_proto_rawDescGZIP() []byte {
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	})
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}

var file_mcube_pb_resource_meta_proto_msgTypes = make([]protoimpl.MessageInfo, 2)
var file_mcube_pb_resource_meta_proto_goTypes = []interface{}{
	(*Meta)(nil),  // 0: infraboard.mcube.resource.Meta
	(*Scope)(nil), // 1: infraboard.mcube.resource.Scope
}
var file_mcube_pb_resource_meta_proto_depIdxs = []int32{
	0, // [0:0] is the sub-list for method output_type
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func file_mcube_pb_resource_meta_proto_init() {
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			case 1:
				return &v.sizeCache
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				return &v.unknownFields
			default:
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			}
		}
	}
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: file_mcube_pb_resource_meta_proto_rawDesc,
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	file_mcube_pb_resource_meta_proto_rawDesc = nil
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}

repository: infraboard/mcube

repo_name: infraboard/mcube

gha_language: Go


text:
SUMMARY = "library for handling OpenGL function pointer management"

LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://COPYING;md5=58ef4c80d401e07bd9ee8b6b58cf464b"

SRC_URI = "https://github.com/anholt/libepoxy/releases/download/v${PV}/${BP}.tar.bz2"
SRC_URI[md5sum] = "96f6620a9b005a503e7b44b0b528287d"
SRC_URI[sha256sum] = "1d8668b0a259c709899e1c4bab62d756d9002d546ce4f59c9665e2fc5f001a64"

inherit autotools pkgconfig

DEPENDS = "util-macros"


text:
function(add_airframe pack_airframe_path)

    # Airframe file paths
    if($ENV{ROS_HOME})
    set(local_airframe_path "$ENV{ROS_HOME}/etc")
    else()
    set(local_airframe_path "$ENV{HOME}/.ros/etc")
    endif()

    # aborts if directory where airframe config is put does not exist
    if(NOT EXISTS ${local_airframe_path})
        file(MAKE_DIRECTORY ${local_airframe_path}/init.d-posix)
    endif()

    # get filename
    get_filename_component(file_name ${pack_airframe_path} NAME)
    # replace airframe number by "airframe_" to obtain target name
    string(REGEX REPLACE ^[0-9]+_ "airframe_" target_name ${file_name})

    # add target that makes symbolic link
    add_custom_target(${target_name} ALL
                      ln -s -b ${pack_airframe_path} ${local_airframe_path}/init.d-posix/${file_name})

endfunction()


text:
@InProceedings{habeck12,
  title = {Evaluation of marginal likelihoods via the density of states},
  author = {Michael Habeck},
  pages = {486--494},
  abstract = {Bayesian model comparison involves the evaluation of the marginal likelihood, the expectation of the likelihood under the prior distribution. Typically, this high-dimensional integral over all model parameters is approximated using Markov chain Monte Carlo methods. Thermodynamic integration is a popular method to estimate the marginal likelihood by using samples from annealed posteriors. Here we show that there exists a robust and flexible alternative. The new method estimates the density of states, which counts the number of states associated with a particular value of the likelihood. If the density of states is known, computation of the marginal likelihood reduces to a one- dimensional integral. We outline a maximum likelihood procedure to estimate the density of states from annealed posterior samples. We apply our method to various likelihoods and show that it is superior to thermodynamic integration in that it is more flexible with regard to the annealing schedule and the family of bridging distributions. Finally, we discuss the relation of our method with Skilling's nested sampling.},
  pdf = {http://jmlr.org/proceedings/papers/v22/habeck12/habeck12.pdf},
}

repository: mreid/papersite

repo_name: mreid/papersite


text:
@book{bishop2006pattern,
    title={Pattern Recognition and Machine Learning},
    author={Christopher Bishop},
    year={2006},
    publisher={Springer}
}

@book{Goodfellow2016deep,
    title={Deep Learning},
    author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
    publisher={MIT Press},
    note={\url{http://www.deeplearningbook.org}},
    year={2016}
}

@book{gonzalezDIP2006,
    author = {Gonzalez, Rafael C. and Woods, Richard E.},
    title = {Digital Image Processing (3rd Edition)},
    year = {2006},
    isbn = {013168728X},
    publisher = {Prentice-Hall, Inc.},
    address = {Upper Saddle River, NJ, USA},
}

@book{murphy2012machine,
    title={Machine learning: a probabilistic perspective},
    author={Murphy, Kevin P},
    year={2012},
    publisher={MIT press}
}

@book{sammut2011encyclopedia,
  title={Encyclopedia of machine learning},
  author={Sammut, Claude and Webb, Geoffrey I},
  year={2011},
  publisher={Springer Science \& Business Media}
}

@book{mackay2003information,
  title={Information theory, inference and learning algorithms},
  author={MacKay, David JC},
  year={2003},
  publisher={Cambridge university press}
}

@article{ren2015object,
    title={Object detection networks on convolutional feature maps},
    author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Zhang, Xiangyu
and Sun, Jian},
    journal={arXiv preprint arXiv:1504.06066},
    year={2015}
}

@article{yilmaz2006object,
  title={Object tracking: A survey},
  author={Yilmaz, Alper and Javed, Omar and Shah, Mubarak},
  journal={Acm computing surveys (CSUR)},
  volume={38},
  number={4},
  pages={13},
  year={2006},
  publisher={Acm}
}

@inproceedings{viola2001rapid,
  title={Rapid object detection using a boosted cascade of simple features},
  author={Viola, Paul and Jones, Michael},
  booktitle={Computer Vision and Pattern Recognition, 2001. CVPR 2001.
Proceedings of the 2001 IEEE Computer Society Conference on},
  volume={1},
  pages={I--I},
  year={2001},
  organization={IEEE}
}

@article{russakovsky2015imagenet,
  title={Imagenet large scale visual recognition challenge},
  author={Russakovsky, Olga and Deng, Jia and Su, Hao and Krause, Jonathan and
Satheesh, Sanjeev and Ma, Sean and Huang, Zhiheng and Karpathy, Andrej and
Khosla, Aditya and Bernstein, Michael and others},
  journal={International Journal of Computer Vision},
  volume={115},
  number={3},
  pages={211--252},
  year={2015},
  publisher={Springer}
}

@article{aanaes2012interesting,
  title={Interesting interest points},
  author={Aan{\ae}s, Henrik and Dahl, Anders Lindbjerg and Pedersen, Kim
Steenstrup},
  journal={International Journal of Computer Vision},
  volume={97},
  number={1},
  pages={18--35},
  year={2012},
  publisher={Springer}
}

@inproceedings{zagoruyko2015learning,
  title={Learning to compare image patches via convolutional neural networks},
  author={Zagoruyko, Sergey and Komodakis, Nikos},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition},
  pages={4353--4361},
  year={2015}
}

@article{alcantarilla2011fast,
  title={Fast explicit diffusion for accelerated features in nonlinear scale
spaces},
  author={Alcantarilla, Pablo F and Solutions, T},
  journal={IEEE Trans. Patt. Anal. Mach. Intell},
  volume={34},
  number={7},
  pages={1281--1298},
  year={2011}
}

@inproceedings{rublee2011orb,
  title={ORB: An efficient alternative to SIFT or SURF},
  author={Rublee, Ethan and Rabaud, Vincent and Konolige, Kurt and Bradski,
Gary},
  booktitle={2011 International conference on computer vision},
  pages={2564--2571},
  year={2011},
  organization={IEEE}
}

@inproceedings{bay2006surf,
  title={Surf: Speeded up robust features},
  author={Bay, Herbert and Tuytelaars, Tinne and Van Gool, Luc},
  booktitle={European conference on computer vision},
  pages={404--417},
  year={2006},
  organization={Springer}
}

@article{lowe2004distinctive,
  title={Distinctive image features from scale-invariant keypoints},
  author={Lowe, David G},
  journal={International journal of computer vision},
  volume={60},
  number={2},
  pages={91--110},
  year={2004},
  publisher={Springer}
}

@book{szeliski2010computer,
  title={Computer vision: algorithms and applications},
  author={Szeliski, Richard},
  year={2010},
  publisher={Springer Science \& Business Media}
}

@article{zbontar2016stereo,
  title={Stereo matching by training a convolutional neural network to compare
image patches},
  author={Zbontar, Jure and LeCun, Yann},
  journal={Journal of Machine Learning Research},
  volume={17},
  pages={1--32},
  year={2016}
}

@article{zhang1995robust,
  title={A robust technique for matching two uncalibrated images through the
recovery of the unknown epipolar geometry},
  author={Zhang, Zhengyou and Deriche, Rachid and Faugeras, Olivier and Luong,
Quang-Tuan},
  journal={Artificial intelligence},
  volume={78},
  number={1-2},
  pages={87--119},
  year={1995},
  publisher={Elsevier}
}

@article{brown2011discriminative,
  title={Discriminative learning of local image descriptors},
  author={Brown, Matthew and Hua, Gang and Winder, Simon},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={33},
  number={1},
  pages={43--57},
  year={2011},
  publisher={IEEE}
}

@inproceedings{tola2008fast,
  title={A fast local descriptor for dense matching},
  author={Tola, Engin and Lepetit, Vincent and Fua, Pascal},
  booktitle={Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE
Conference on},
  pages={1--8},
  year={2008},
  organization={IEEE}
}

@article{alexe2012measuring,
    title={Measuring the objectness of image windows},
    author={Alexe, Bogdan and Deselaers, Thomas and Ferrari, Vittorio},
    journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
    volume={34},
    number={11},
    pages={2189--2202},
    year={2012},
    publisher={IEEE}
}

@incollection{endres2010category,
    title={Category independent object proposals},
    author={Endres, Ian and Hoiem, Derek},
    booktitle={Computer Vision--ECCV 2010},
    pages={575--588},
    year={2010},
    publisher={Springer}
}

@inproceedings{rahtu2011learning,
    title={Learning a category independent object detection cascade},
    author={Rahtu, Esa and Kannala, Juho and Blaschko, Matthew},
    booktitle={Computer Vision (ICCV), 2011 IEEE International Conference on},
    pages={1052--1059},
    year={2011},
    organization={IEEE}
}

@article{uijlings2013selective,
    title={Selective search for object recognition},
    author={Uijlings, Jasper RR and van de Sande, Koen EA and Gevers, Theo
    and Smeulders, Arnold WM},
    journal={International journal of computer vision},
    volume={104},
    number={2},
    pages={154--171},
    year={2013},
    publisher={Springer}
}

@incollection{zitnick2014edge,
    title={Edge boxes: Locating object proposals from edges},
    author={Zitnick, C Lawrence and Doll{\'a}r, Piotr},
    booktitle={Computer Vision--ECCV 2014},
    pages={391--405},
    year={2014},
    publisher={Springer}
}

@article{kang2015data,
    title={Data-driven objectness},
    author={Kang, Hongwen and Hebert, Martial and Efros, Alexei A and
    Kanade, Takeo},
    journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
    volume={37},
    number={1},
    pages={189--195},
    year={2015},
    publisher={IEEE}
}

@inproceedings{kuo2015deepbox,
    title={Deepbox: Learning objectness with convolutional networks},
    author={Kuo, Weicheng and Hariharan, Bharath and Malik, Jitendra},
    booktitle={Proceedings of the IEEE International Conference on Computer
    Vision},
    pages={2479--2487},
    year={2015}
}

@article{hosang2016makes,
  title={What makes for effective detection proposals?},
  author={Hosang, Jan and Benenson, Rodrigo and Doll{\'a}r, Piotr and Schiele,
Bernt},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={38},
  number={4},
  pages={814--830},
  year={2016},
  publisher={IEEE}
}

@inproceedings{ren2015faster,
    title={Faster R-CNN: Towards real-time object detection with region
    proposal networks},
    author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
    booktitle={Advances in Neural Information Processing Systems},
    pages={91--99},
    year={2015}
}

@inproceedings{girshick2015fast,
  title={Fast R-CNN},
  author={Girshick, Ross},
  booktitle={Proceedings of the IEEE international conference on computer
vision},
  pages={1440--1448},
  year={2015}
}

@inproceedings{cheng2014bing,
  title={BING: Binarized normed gradients for objectness estimation at 300fps},
  author={Cheng, Ming-Ming and Zhang, Ziming and Lin, Wen-Yan and Torr, Philip},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern
recognition},
  pages={3286--3293},
  year={2014}
}

@article{hosang2014good,
  title={How good are detection proposals, really?},
  author={Hosang, Jan and Benenson, Rodrigo and Schiele, Bernt},
  journal={arXiv preprint arXiv:1406.6962},
  year={2014}
}

@inproceedings{chavali2016object,
  title={Object-proposal evaluation protocol is' gameable'},
  author={Chavali, Neelima and Agrawal, Harsh and Mahendru, Aroma and Batra,
Dhruv},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition},
  pages={835--844},
  year={2016}
}

@article{everingham2010pascal,
  title={The pascal visual object classes (voc) challenge},
  author={Everingham, Mark and Van Gool, Luc and Williams, Christopher KI and
Winn, John and Zisserman, Andrew},
  journal={International journal of computer vision},
  volume={88},
  number={2},
  pages={303--338},
  year={2010},
  publisher={Springer}
}

@inproceedings{erhan2014scalable,
  title={Scalable object detection using deep neural networks},
  author={Erhan, Dumitru and Szegedy, Christian and Toshev, Alexander and
Anguelov, Dragomir},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition},
  pages={2147--2154},
  year={2014}
}

@article{vcehovin2016visual,
  title={Visual object tracking performance measures revisited},
  author={{\v{C}}ehovin, Luka and Leonardis, Ale{\v{s}} and Kristan, Matej},
  journal={IEEE Transactions on Image Processing},
  volume={25},
  number={3},
  pages={1261--1274},
  year={2016},
  publisher={IEEE}
}

@inproceedings{held2016learning,
  title={Learning to track at 100 fps with deep regression networks},
  author={Held, David and Thrun, Sebastian and Savarese, Silvio},
  booktitle={European Conference on Computer Vision},
  pages={749--765},
  year={2016},
  organization={Springer}
}

@inproceedings{redmon2016you,
  title={You only look once: Unified, real-time object detection},
  author={Redmon, Joseph and Divvala, Santosh and Girshick, Ross and Farhadi,
Ali},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition},
  pages={779--788},
  year={2016}
}

@article{qi2017pointnet,
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}

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Christopher KI and Winn, John and Zisserman, Andrew},
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}

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    year={2014}
}

@article{iandola2016squeezenet,
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    Ashraf, Khalid and Dally, William J and Keutzer, Kurt},
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    year={2016}
}

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}

@article{zhang2016understanding,
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}

@article{sermanet2013overfeat,
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convolutional networks},
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Micha{\"e}l and Fergus, Rob and LeCun, Yann},
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}

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}

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}

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  year={2015}
}

@InProceedings{Schroff_2015_CVPR,
author = {Schroff, Florian and Kalenichenko, Dmitry and Philbin, James},
title = {FaceNet: A Unified Embedding for Face Recognition and Clustering},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition
(CVPR)},
month = {June},
year = {2015}
}

@inproceedings{sun2017revisiting,
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Abhinav},
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Recognition},
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  year={2017}
}

@article{ruder2017overview,
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  year={2017}
}

@article{kendall2017multi,
  title={Multi-Task Learning Using Uncertainty to Weigh Losses for Scene
Geometry and Semantics},
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  year={2017}
}

@inproceedings{glorot2010understanding,
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networks},
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  year={2010}
}

@article{saxe2013exact,
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neural networks},
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  journal={arXiv preprint arXiv:1312.6120},
  year={2013}
}

@article{wu2018group,
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  year={2018}
}

@article{ba2016layer,
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  author={Ba, Jimmy Lei and Kiros, Jamie Ryan and Hinton, Geoffrey E},
  journal={arXiv preprint arXiv:1607.06450},
  year={2016}
}

@article{bergstra2012random,
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  year={2012}
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@article{ruder2016overview,
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  author={Ruder, Sebastian},
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  year={2016}
}

@inproceedings{reddi2018convergence,
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  year={2018}
}

@article{tieleman2012lecture,
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recent magnitude},
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  journal={COURSERA: Neural networks for machine learning},
  volume={4},
  number={2},
  pages={26--31},
  year={2012}
}

@article{duchi2011adaptive,
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optimization},
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  year={2011}
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@inproceedings{zeiler2014visualizing,
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  author={Zeiler, Matthew D and Fergus, Rob},
  booktitle={European conference on computer vision},
  pages={818--833},
  year={2014},
  organization={Springer}
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@phdthesis{gal2016uncertainty,
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  school={University of Cambridge},
  year={2016}
}

@article{simonyan2014very,
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  journal={arXiv preprint arXiv:1409.1556},
  year={2014}
}

@inproceedings{szegedy2015going,
  title={Going deeper with convolutions},
  author={Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre
and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent
and Rabinovich, Andrew},
  booktitle={Proceedings of IEEE CVPR},
  pages={1--9},
  year={2015}
}

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
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  year={2016}
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@article{baydin2017automatic,
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@article{de2011multidimensional,
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  year={2011}
}

@phdthesis{caruana1997multitask,
  title={Multitask Learning},
  author={Caruana, Rich},
  year={1997},
  school={Carnegie Mellon University Pittsburgh, PA}
}

@Article{caruana1997multitaskJournalML,
author="Caruana, Rich",
title="Multitask Learning",
journal="Machine Learning",
year="1997",
month="Jul",
day="01",
volume="28",
number="1",
pages="41--75",
abstract="Multitask Learning is an approach to inductive transfer that improves
generalization by using the domain information contained in the training signals
of related tasks as an inductive bias. It does this by learning tasks in
parallel while using a shared representation; what is learned for each task can
help other tasks be learned better. This paper reviews prior work on MTL,
presents new evidence that MTL in backprop nets discovers task relatedness
without the need of supervisory signals, and presents new results for MTL with
k-nearest neighbor and kernel regression. In this paper we demonstrate multitask
learning in three domains. We explain how multitask learning works, and show
that there are many opportunities for multitask learning in real domains. We
present an algorithm and results for multitask learning with case-based methods
like k-nearest neighbor and kernel regression, and sketch an algorithm for
multitask learning in decision trees. Because multitask learning works, can be
applied to many different kinds of domains, and can be used with different
learning algorithms, we conjecture there will be many opportunities for its use
on real-world problems.",
issn="1573-0565",
doi="10.1023/A:1007379606734",
url="https://doi.org/10.1023/A:1007379606734"
}

@article{stanley2002evolving,
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  author={Stanley, Kenneth O and Miikkulainen, Risto},
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  volume={10},
  number={2},
  pages={99--127},
  year={2002},
  publisher={MIT Press}
}

@inproceedings{zoph2018learning,
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  author={Zoph, Barret and Vasudevan, Vijay and Shlens, Jonathon and Le, Quoc
V},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern
recognition},
  pages={8697--8710},
  year={2018}
}

@article{liu2018darts,
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  journal={arXiv preprint arXiv:1806.09055},
  year={2018}
}

@article{quanming2018taking,
  title={Taking human out of learning applications: A survey on automated
machine learning},
  author={Quanming, Yao and Mengshuo, Wang and Hugo, Jair Escalante and
Isabelle, Guyon and Yi-Qi, Hu and Yu-Feng, Li and Wei-Wei, Tu and Qiang, Yang
and Yang, Yu},
  journal={arXiv preprint arXiv:1810.13306},
  year={2018}
}

@article{santurkar2018does,
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Internal Covariate Shift)},
  author={Santurkar, Shibani and Tsipras, Dimitris and Ilyas, Andrew and Madry,
Aleksander},
  journal={arXiv preprint arXiv:1805.11604},
  year={2018}
}

@article{luo2018understanding,
  title={Understanding Regularization in Batch Normalization},
  author={Luo, Ping and Wang, Xinjiang and Shao, Wenqi and Peng, Zhanglin},
  journal={arXiv preprint arXiv:1809.00846},
  year={2018}
}

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  pages={23--27},
  year={2012},
  publisher={Elsevier}
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@article{veenstra2012airborne,
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  pages={63--68},
  year={2012},
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@article{laist1987overview,
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  pages={842--852},
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@article{watters2010assessing,
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Schroeder, Donna M},
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  volume={60},
  number={1},
  pages={131--138},
  year={2010},
  publisher={Elsevier}
}

@article{schlining2013debris,
  title={Debris in the deep: Using a 22-year video annotation database to survey
marine litter in Monterey Canyon, central California, USA},
  author={Schlining, Kyra and Von Thun, Susan and Kuhnz, Linda and Schlining,
Brian and Lundsten, Lonny and Stout, Nancy Jacobsen and Chaney, Lori and Connor,
Judith},
  journal={Deep Sea Research Part I: Oceanographic Research Papers},
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  year={2013},
  publisher={Elsevier}
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@techreport{beduhn1966removal,
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  year={1966},
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@article{kader2015design,
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WNW},
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  pages={1--13},
  year={2015}
}

@article{oigman2007quantification,
  title={Quantification and classification of marine litter on beaches along
Arma{\c{c}}{\~a}o dos B{\'u}zios, Rio de Janeiro, Brazil},
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  year={2007}
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@article{tyrrell2013associations,
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concentrations in adults in the USA: NHANES 2001--2010},
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Tamara S and Osborne, Nicholas J},
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  pages={328--335},
  year={2013},
  publisher={Elsevier}
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@article{katsanevakis2008marine,
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and impacts},
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  pages={53--100},
  year={2008}
}

@article{canyon1978international,
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Ships (MARPOL 73/78)},
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  year={1978}
}

@article{dayton1995environmental,
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Robert J},
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}

@article{mori2011survey,
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Yanagisawa, Hideaki},
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@article{willis2017differentiating,
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of marine debris in coastal and estuarine environments},
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Wilcox, Chris},
  journal={Scientific Reports},
  volume={7},
  pages={44479},
  year={2017},
  publisher={Nature Publishing Group}
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@article{li2016plastic,
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occurrence and effects},
  author={Li, WC and Tse, HF and Fok, L},
  journal={Science of the Total Environment},
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  pages={333--349},
  year={2016},
  publisher={Elsevier}
}

@book{weis2015marine,
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  author={Weis, Judith S},
  year={2015},
  publisher={Oxford University Press}
}

@article{ryan2014litter,
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  author={Ryan, Peter G},
  journal={Marine Pollution Bulletin},
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  number={1-2},
  pages={220--224},
  year={2014},
  publisher={Elsevier}
}

@article{stefatos1999marine,
  title={Marine debris on the seafloor of the Mediterranean Sea: examples from
two enclosed gulfs in Western Greece},
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G},
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  year={1999},
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@article{jambeck2015plastic,
  title={Plastic waste inputs from land into the ocean},
  author={Jambeck, Jenna R and Geyer, Roland and Wilcox, Chris and Siegler,
Theodore R and Perryman, Miriam and Andrady, Anthony and Narayan, Ramani and
Law, Kara Lavender},
  journal={Science},
  volume={347},
  number={6223},
  pages={768--771},
  year={2015},
  publisher={American Association for the Advancement of Science}
}

@article{eriksen2014plastic,
  title={Plastic pollution in the world's oceans: more than 5 trillion plastic
pieces weighing over 250,000 tons afloat at sea},
  author={Eriksen, Marcus and Lebreton, Laurent CM and Carson, Henry S and
Thiel, Martin and Moore, Charles J and Borerro, Jose C and Galgani, Francois and
Ryan, Peter G and Reisser, Julia},
  journal={PloS one},
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  pages={e111913},
  year={2014},
  publisher={Public Library of Science}
}

@article{chiba2018human,
  title={Human footprint in the abyss: 30 year records of deep-sea plastic
debris},
  author={Chiba, Sanae and Saito, Hideaki and Fletcher, Ruth and Yogi, Takayuki
and Kayo, Makino and Miyagi, Shin and Ogido, Moritaka and Fujikura, Katsunori},
  journal={Marine Policy},
  year={2018},
  publisher={Elsevier}
}

@incollection{laist1997impacts,
  title={Impacts of marine debris: entanglement of marine life in marine debris
including a comprehensive list of species with entanglement and ingestion
records},
  author={Laist, David W},
  booktitle={Marine Debris},
  pages={99--139},
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  publisher={Springer}
}

@article{gall2015impact,
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  number={1-2},
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  year={2015},
  publisher={Elsevier}
}

@article{wilcox2015threat,
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increasing},
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  journal={Proceedings of the National Academy of Sciences},
  volume={112},
  number={38},
  pages={11899--11904},
  year={2015},
  publisher={National Acad Sciences}
}

@article{paleczny2015population,
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  author={Paleczny, Michelle and Hammill, Edd and Karpouzi, Vasiliki and Pauly,
Daniel},
  journal={PLoS One},
  volume={10},
  number={6},
  pages={e0129342},
  year={2015},
  publisher={Public Library of Science}
}

@article{engler2012complex,
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the ocean},
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  pages={12302--12315},
  year={2012},
  publisher={ACS Publications}
}

@article{smith1997marine,
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@article{rochman2016strategies,
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guided by science},
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@article{nelms2017marine,
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@inproceedings{valdenegro2016objectness,
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@inproceedings{valdenegro2016end,
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@inproceedings{valdenegro2016submerged,
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{U}nderwater {V}ehicles},
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@inproceedings{valdenegro2017rtcnns,
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@inproceedings{valdenegro2016object,
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@inproceedings{valdenegro2017limits,
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@inproceedings{valdenegro2017improving,
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@inproceedings{dmitrieva2017object,
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@misc{tritechStarfish,
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@misc{krakenAquapix,
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@inproceedings{williams2018underwater,
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repository: mvaldenegro/phd-thesis

repo_name: mvaldenegro/phd-thesis


text:
@InProceedings{KSR:PAAR-2016,
    author =     {Kaliszyk, Cezary and Sutcliffe, Geoff and Rabe, Florian},
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    title =      {{TH1: The TPTP Typed Higher-Order Form with Rank-1
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    editor =     {Fontaine, P. and Schulz, S. and Urban, J.},
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                  Aspects of Automated Reasoning}},
    place =      {Coimbra, Portugal},
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@InProceedings{BP:CADE-2013,
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@Article{Sut17,
    Author       = "Sutcliffe, G.",
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                    From CNF to TH0, TPTP v6.4.0}",
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@InCollection{SZS04,
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@InProceedings{KSR16,
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    Title        = "{TH1: The TPTP Typed Higher-Order Form with Rank-1
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	author={Python Software Foundation},
	title={The Python Standard Library: Built-in Types},
	url = {https://docs.python.org/3/library/stdtypes.html#str},
	urldate = {2020-05-10}
}

@online{BeautifulSoup,
	author={Leonard Richardson},
	title={beautifulsoup4 4.9.0},
	url = {https://pypi.org/project/beautifulsoup4/},
	urldate = {2020-04-08}
}

@online{BeautifulSoupDoku,
	author={Leonard Richardson},
	title={Beautiful Soup Documentation},
	url = {https://www.crummy.com/software/BeautifulSoup/bs4/doc/},
	urldate = {2020-05-10}
}

@online{argparse,
	author={Python Software Foundation},
	title={argparse - Parser for command-line options, arguments and sub-commands - Python 3.8.2 documentation},
	url = {https://docs.python.org/3/library/argparse.html},
	urldate = {2020-03-09}
}

@online{urllib,
	author={Michael Foord},
	title={HOWTO Fetch Internet Resources Using The urllib Package},
	url = {https://docs.python.org/3/howto/urllib2.html},
	urldate = {2020-04-18}
}

@online{TPTP,
	author={Geoff Sutcliffe and Christian Suttner},
	title={TPTP},
	url = {http://www.tptp.org},
	urldate = {2020-03-21}
}

@online{Yacc,
	author={Johnson, Stephen C.},
	title={Yacc: Yet Another Compiler-Compiler},
	url = {http://dinosaur.compilertools.net/yacc/index.html},
	urldate = {2020-05-16}
}

@online{Lex,
	author={Lesk, M. E. and Schmidt, E.},
	title={Lex - A Lexical Analyzer Generator},
	url = {http://dinosaur.compilertools.net/lex/index.html},
	urldate = {2020-05-16}
}

@online{Flex,
	author={Paxson, Vern},
	title={Flex - a scanner generator - Description},
	url = {http://dinosaur.compilertools.net/flex/flex_4.html#SEC4},
	urldate = {2020-05-16}
}

@online{Bison,
	author={Donnelly, Charles and Stallman, Richard},
	title={Bison 1.25 - Introduction},
	url = {http://dinosaur.compilertools.net/bison/bison_1.html#SEC1},
	urldate = {2020-06-03}
}

@book{Mogensen.2017,
Title = "Introduction to Compiler Design",
Author = "Mogensen, Torben Aegidius",
Publisher = "Springer",
Year = "2017",
ISBN = "9783319669656"
}

@book{AutomataTheory.2007,

Title = "Introduction to Automata Theory, Languages, and Computation 3rd Edition",
Author = "Hopcroft, John E. and Motwani, Rajeev and Ullman, Jeffrey D.",
Publisher = "Pearson Education, Inc.",
Year = "2007",
ISBN = "0321455363"
}

@article{EBNF.1977, author = {Wirth, Niklaus}, title = {What Can We Do about the Unnecessary Diversity of Notation for Syntactic Definitions?}, year = {1977}, issue_date = {November 1977}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {20}, number = {11}, issn = {0001-0782}, url = {https://doi.org/10.1145/359863.359883}, doi = {10.1145/359863.359883}, journal = {Commun. ACM}, month = nov, pages = {822–823}, numpages = {2}, keywords = {syntactic description language, extended BNF} }

@Article{Cremers75,
	Author = "Cremers, Armin and Ginsburg, Seymour",
	Year = "1975",
	Title = "Context-free grammar forms",
	Journal = "Journal of Computer and System Sciences",
	Volume = "11",
	Pages = "86-117"
}

@article{BNF.1964, author = {Knuth, Donald E.}, title = {Backus Normal Form vs. Backus Naur Form}, year = {1964}, issue_date = {December 1964}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {7}, number = {12}, issn = {0001-0782}, url = {https://doi.org/10.1145/355588.365140}, doi = {10.1145/355588.365140}, journal = {Commun. ACM}, month = dec, pages = {735–736}, numpages = {2} }

@book{Aho.2007,
  author = {Aho, Alfred V. and Lam, Monica S. and Sethi, Ravi and Ullman, Jeffrey D.},
  edition = {Second},
  editor = {Hirsch, Michal and Goldstein, Matt and Harutunian, Katherine and Holocumb, Jefferey},
  publisher = {Addison-Wesley},
  title = {Compilers : Principles, Techniques, \& Tools, Second Edition},
  year = 2007
}

repository: nahku/CLDTSDocumentation

repo_name: nahku/CLDTSDocumentation


text:
DESCRIPTION = "A demo phone application based on FSO 2.0"
AUTHOR = "Michael 'Mickey' Lauer <mlauer@vanille-media.de>"
HOMEPAGE = "http://www.freesmartphone.org"
SECTION = "x11"
LICENSE = "GPLv2"
DEPENDS = "edje-native evas ecore edje libeflvala libfsobasics libfsoframework libfso-glib"
SRCREV = "1e3dca8a407f4e69636c47d9f22b31f8ae718d5a"
PV = "2.0.0+gitr${SRCPV}"
PR = "r2"
PE = "1"

SRC_URI = "\
  ${FREESMARTPHONE_GIT}/aurora.git;protocol=git;branch=master \
  http://www.linuxtogo.org/~mickeyl/misc/splash;name=splash \
  file://zhone2 \
"
SRC_URI[splash.md5sum] = "e198d5c83cc47a216562e435df0e03c3"
SRC_URI[splash.sha256sum] = "3e41bcf4ea50ab7406d3833e412a78ddb9afaab4b0a8cca1bf93755d1ce9a215"
S = "${WORKDIR}/git/zhone2"

inherit autotools update-rc.d vala

INITSCRIPT_NAME = "zhone2"
INITSCRIPT_PARAMS = "defaults 40"

do_install_append() {
	install -d ${D}${datadir}/zhone2/
	install -d ${D}${sysconfdir}/init.d/
	install -m 0644 ${WORKDIR}/splash ${D}${datadir}/zhone2/
	install -m 0755 ${WORKDIR}/${INITSCRIPT_NAME} ${D}${sysconfdir}/init.d/
}


text:
@article{1997Natur.387Q.859B,
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/1997Natur.387Q.859B},
 author = {Bloom, Joshua S. and Ruderman, Malvin},
 doi = {10.1038/43082},
 journal = {\nat},
 month = {Jun},
 number = {6636},
 pages = {859},
 title = {Gamma-ray astronomy: Bursting out all over},
 volume = {387},
 year = {1997}
}

repository: profjsb/my-content

repo_name: profjsb/my-content


text:
package tests

import (
	"github.com/Rirush/forlabs"
	"testing"
	"time"
)

func TestAuthentication(t *testing.T) {
	_, err := forlabs.Authenticate(ValidUsername, ValidPassword)
	if err != nil {
		t.Errorf("Successful login failed, %s", err)
	}
	time.Sleep(time.Second)
	_, err = forlabs.Authenticate("a", "b")
	if err == nil {
		t.Errorf("Invalid login failed")
		return
	}
	if err.Error() != "invalid password" {
		t.Errorf("Invalid login failed, %s", err)
	}
}

repository: Rirush/forlabs

repo_name: Rirush/forlabs