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4 ways to encourage cloud adoption
Government and private sector IT leaders met at FedScoop to discuss how to push the government toward cloud computing.
Federal officials have been hesitant to adopt cloud computing, especially compared to private industry.
Moving to the cloud — an industry buzzword that refers to accessing programs and services over the Internet rather than through traditional hardware and software — holds the potential to save federal agencies money and make them more efficient. Even so, the Government Accountability Office said in a report last year that uptake has been "uneven."
Is the dream of rapid adoption of cloud in government still pie in the sky? Last month, nearly 30 leading government and private sector IT leaders — including chief information, technology and information security officers from a dozen federal agencies, and chief technology officers and executives from a dozen leading IT companies — met at FedScoop's headquarters for a not-for-attribution discussion about how to guide the famously risk-averse government to the cloud.
Here were their top four ideas.
1. Focus on ironing out acquisition issues.
Anxieties about acquisition practices dominated the panel's discussion. As one federal IT leader said, "It always comes back to contracts." A key issue was helping agencies move to a consumption-based model, which can be a challenge for agencies used to buying product services.
Officials also talked about the importance of understanding who owns the information that is stored in a third-party cloud. One official said his agency has been in legal discussions about what happens to stored data if a cloud services provider goes out of business.
2. Concentrate on security, privacy, trust and transparency.
Mitigating risk also remains a major issue for agencies moving to the cloud. Government agency and private industry officials discussed how they could foster trust between the sectors — and how companies could better address agency's worries about security.
One representative from the private sector complained his company spends a large amount of money to adhere to Federal Risk and Authorization Management Program standards. "It's tremendous investment," he said. "But we're not seeing some agencies migrate to FedRAMP."
"Are we transitioning the focus to … feeling sorry for industry right now?" one government official retorted. "The challenges on the government side are extremely demanding too."
Later, a participant noted that before he could acquire cloud services, he was required to conduct a supply-chain risk management assessment. "How do I do due diligence when it's a community-based cloud environment?" he asked. He can't, after all, dictate what pieces of hardware and software these private companies buy, he said.
The supply-chain issues represent a larger dilemma, participants said: making sure agencies have enough information about the clouds' security to satisfy the concerns of their compliance and security officers.
Risk will always be an issue when moving to new technologies, one participant said. But he said risks exist even if the government remains stagnant on IT.
3. Emphasize people, culture and leadership.
It can be a challenge to convince workers that a shiny, new cloud system is better than that server under their desk. It requires a culture change and guidance from senior leadership, panelists said.
One government representative said his agency chief proclaimed the unit would start using email in the cloud — "so we all moved." He added, "If leadership comes, people will follow."
Several panelists agreed. "We don't have a money problem," said one federal official. "I think the leadership … is a much bigger opportunity than the size of the budget."
But one concern was that technologists trained on the legacy systems would be hesitant to embrace something new. And agencies often don't have the resources to train their workers on the latest innovations. IT offices frequently have to rely on half-day conferences or hourlong webinars sponsored by industry to fill that role, said one government official.
At the same time, another IT official said there's room for workers who need to understand various pieces of hybrid systems.
"If you look at an agency that's trying to move to the cloud, it isn't all or nothing," she said.
4. Modernize enterprise architecture.
At the end of the discussion, one private industry representative asked the government officials on the panel whether their enterprise systems were holding them back. Several nodded.
"We have been struggling with enterprise architecture," one govie said. He said senior leadership didn't understand the challenges the enterprise architecture poses as the agency tries to innovate. "Some organizations seem to get it, and some don't. It's a struggle."
One person said agencies need to update their enterprise architecture with modern approaches. "Some of the legacy-based applications will never move to the cloud because they don't belong in the cloud," he said. But he encouraged agencies to "put their toe in the water."
An F22 fighter jet soars above the clouds as the sun begins to set over a beautiful cloudscape. Source: Getty Images
Cloud One: Taking aim at the enemy, one application at a time
From GEARFIT to the Special Warfare Technical Integration Support Center, the Cloud One team shares how its platform is supporting mission-critical applications for the Air Force.
By Cloud One Leadership
(Tajha Chappellet-Lanier / FedScoop)
Interior CIO says outdated policymaking hampering adoption of new tech
Digital accessibility requires a proactive government
Charles Armstrong joins FEMA as chief information officer
GOP House committee leaders probe 'conflicting definitions' in NIST AI framework and AI 'Bill of Rights'
New 'official channels' for sharing data on unexplained phenomena leads to uptick in Pentagon's collection of evidence


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16 of the Best Virginia Woolf Quotes
Virginia Woolf (1882-1941), born Adeline Virginia Stephen, was one of the most important writers of the first half of the twentieth century. A leading modernist novelist and short-story writer whose novels Mrs Dalloway, To the Lighthouse, Orlando, and The Waves are widely regarded as classics, Woolf was also an influential writer of non-fiction.
Many of the quotations gathered below – which represent, for us, the best and most significant quotations found in Woolf's work – come from works of non-fiction Woolf wrote: essays and lectures on the topics of fiction and gender, in particular. They also help to shine a light on Woolf's views and attitudes.
'Life is not a series of gig-lamps symmetrically arranged; life is a luminous halo, a semi-transparent envelope surrounding us from the beginning of consciousness to the end.'
This quotation is from Virginia Woolf's 1919 essay 'Modern Novels', also known by the title 'Modern Fiction'. In the essay, Woolf takes aim at the 'materialist' fiction of writers like H. G. Wells and Arnold Bennett, who are more concerned with the external details of a person's life than the 'inner lives' of their characters.
'In the course of your daily life this past week you have had far stranger and more interesting experiences than the one I have tried to describe.'
After her 1919 essay 'Modern Fiction', Woolf expanded on her ideas concerning fiction in her 1923 essay 'Mr Bennett and Mrs Brown'. She invites her readers to consider how they are being short-changed by the Arnold Bennetts of the world, who fail to capture the multifariousness and complexity of the average reader's everyday thoughts. The quotation continues:
You have overheard scraps of talk that filled you with amazement. You have gone to bed at night bewildered by the complexity of your feelings. In one day thousands of ideas have coursed through your brains; thousands of emotions have met, collided, and disappeared in astonishing disorder. Nevertheless, you allow the writers to palm off upon you a version of all this, an image of Mrs. Brown, which has no likeness to that surprising apparition whatsoever.
'And now I will hazard a second assertion, which is more disputable perhaps, to the effect that on or about December 1910 human character changed.'
Here's another famous quotation from 'Mr Bennett and Mrs Brown'. Critics have puzzled over why Woolf chose December 1910 of all dates, but her broader point is that a shift occurred towards the end of the first decade of the twentieth century, and modern fiction has
failed to reflect that shift. Readers have become 'modern' but most novelists are still relying on old, and now-outdated, approaches to capturing everyday life.
'Mrs. Dalloway said she would buy the flowers herself.'
Woolf's non-fiction is endlessly quotable; her fiction lends itself less to pithy quotation because it is like a Persian carpet whose individual threads are carefully and meticulously intertwined.
However, this opening line from Woolf's 1925 novel Mrs Dalloway, which begins with the titular Clarissa Dalloway preparing to hold a party on the day on which the novel's action takes place, has become famous.
Part of the genius of the line is its subtlety: it appears a perfectly ordinary and even insignificant detail, but it immediately implies that Clarissa Dalloway is a rich woman who has servants, since she is going to buy the flowers herself rather than send a maid for them. It also invites us to wonder what the flowers are for, and thus piques our interest in an adroit way, encouraging us – as good opening lines should – to read on.
'Ah, the mark on the wall! It was a snail.'
Woolf also has a gift for good closing lines, too. This quotation constitutes the last words of her 1917 short story 'The Mark on the Wall'. The story merely uses the mysterious mark as a jumping-off point for the female protagonist's stream of consciousness, but the anti-climax at the end of the story – when the mark is revealed to be nothing more extraordinary than a snail – deliberately reveals material reality to be less important than the chain of thoughts and day-dreams which it sets in motion.
'When I cannot see words curling like rings of smoke round me I am in darkness – I am nothing.'
These words are spoken by Bernard, one of the main characters in Woolf's 1931 novel The Waves. They speak to the power of language and an artist's sensitivity to words.
'I mean, what is a woman? I assure you, I do not know. I do not believe that you know. I do not believe that anybody can know until she has expressed herself in all the arts and professions open to human skill.'
This quotation comes from 'Professions for Women', a 1931 essay, and in some ways it might be regarded as a continuation of the arguments surrounding the idea of the professional woman which Woolf had put forward in A Room of One's Own two years earlier.
'Anything may happen when womanhood has ceased to be a protected occupation.'
The rest of the Virginia Woolf quotations on this list are taken from one work: her 1929 essay A Room of One's Own, which began as a series of lectures at the University of Cambridge. We have analysed the essay in more detail here, but as this quotation makes clear, womanhood is a key theme of Woolf's book.
'I told you in the course of this paper that Shakespeare had a sister; but do not look for her in Sir Sidney Lee's life of the poet.'
One of the most famous sections of A Room of One's Own is Woolf's story about William Shakespeare's fictional sister, whom she calls Judith. What would Judith Shakespeare's life have been like, if she'd had aspirations to become a playwright like her brother?
Woolf concludes that such an ambition would have been a non-starter for Judith, who wouldn't have received the education or the opportunities her brother had.
'All women together ought to let flowers fall upon the tomb of Aphra Behn, for it was she who earned them the right to speak their minds.'
Although 'Judith Shakespeare' was merely a rhetorical construct, several decades after Shakespeare's death, a woman was writing for the English stage: Aphra Behn (1640-89), whom Woolf salutes in A Room of One's Own as the first woman in England to make a living from her pen.
'Literature is strewn with the wreckage of those who have minded beyond reason the opinion of others.'
Another quotation from A Room of One's Own, and one which many writers – especially those seeking to buck the trend and carve out a more original or individualistic path – would do well to bear in mind.
'Fiction is like a spider's web, attached ever so lightly perhaps, but still attached to life at all four corners.'
This quotation is about the delicate complexity of fiction, especially the subtle and layered modernist fiction which Woolf herself wrote. The important thing is that Woolf's fiction deals with the almost transparent and insignificant details of everyday life – but these details are rooted in the realities of our lives.
'I would venture to guess that Anon, who wrote so many poems without signing them, was often a woman.'
This is one of the most famous lines from A Room of One's Own: the words occur when Woolf is tracing the history of women's literature, arguing that although there are few named female writers from the Renaissance (and earlier), women probably had a hand in a lot of anonymous literature that was produced in the past.
'Lock up your libraries if you like; but there is no gate, no lock, no bolt that you can set upon the freedom of my mind.'
Another rousing line from A Room of One's Own. It's hard not to agree!
'One cannot think well, love well, sleep well, if one has not dined well.'
These last two quotations in this list both return our focus to the material realities which surround the writer – here, the importance of having money enough to feed oneself so one can live a good life (and produce good art).
'A woman must have money and a room of her own if she is to write fiction.'
What better place to conclude this pick of the best Virginia Woolf quotations than with the line which provided Woolf with the title for A Room of One's Own?
She goes on to specify that an inheritance of five hundred pounds a year – which would give a woman financial independence – is more important than women getting the vote.
Tags: English Literature, Literature, Quotations, Virginia Woolf

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Hans-Peter Bühler, nascido em 1 de fevereiro de 1942 em Estugarda (Alemanha), é um historiador e negociante de arte e mecenas de vários museus e instituições europeias, que vive em Portugal desde 2006.

Biografia
Hans-Peter Bühler estudou história da arte e arqueologia em Munique, Heidelberg e Wurtzburgo. Concluiu o seu Doutoramento em Arqueologia, na Universidade de Wurtzburgo, em 1967, com orientação da Professora Erika Simon, com a tese sobre Vasos antigos de calcedónia (Antike Gefässe aus Chalcedonen), que veio a ser publicada em 1973, sob o título "Antike Gefäße aus Edelsteinen" ("Vasos antigos de pedras preciosas"). Casou-se com Marion Bühler-Brockhaus, descendente direta do fundador da enciclopédia Brockhaus. Hans-Peter Bühler ingressou na casa de arte fundada por seu avô em 1905. Após sete anos de atividade bem-sucedida em Estugarda, ele abriu uma galeria em Munique com foco no pré-impressionismo e impressionismo alemão e francês. Entretanto escreveu alguns livros de arte e trabalhou como especialista de arte. Em 2004, ele doou 41 pinturas, desenhos e esculturas da coleção de Corot a Monet De Barbizon ao Impressionismo ao Museu de Belas Artes de Leipzig.

Radicados em Setúbal, Portugal, Hans-Peter Bühler e sua esposa fundaram em 2008 a Fundação cultural Bühler-Brockhaus, que se destacou pelo amplo com apoio nas áreas de arte e cultura, de que merece referência o mecenato de várias grandes esculturas na cidade de Setúbal.

Como arqueólogo e colecionador, Hans-Peter Bühler e Marion Bühler-Brockhaus, doaram cerca de 300 obras da antiguidade clássica ao Museu Regional de Arqueologia D. Diogo de Sousa, em Braga, incluindo um busto de mármore do Imperador Augusto.

Doações para museus e instituições (seleção)

Na Alemanha
 Coleções de Pintura ao Estado da Baviera.
 Pinturas, desenhos e esculturas ao Museu de Belas Artes de Leipzig em 2004.

Quadros (seleção)

 Eugène Carrière (1849-1906): A Ninfa Echo, 1880. Bayerische Staatsgemäldesammlungen Munique, 1981.
 Rosa Bonheur (1822-1899): Cavaleiros surpreendidos por uma chuva, 1882. Inv. 3134.
 Jean-Baptiste Camille Corot (1796-1875): Lenhadores. Inv. 3136.
 Jean-Baptiste Camille Corot (1796-1875): Memória de Dardagny. Inv. 3137.
 Jean-Baptiste Camille Corot (1796-1875): As vindimas. Inv. 3138.
 Charles-François Daubigny (1817-1878): Balsa em Bonnières. Inv. 3142.
 Charles-François Daubigny (1817-1878): O pomar ao pôr do sol. Inv. 3141.
 Henri Fantin-Latour (1836-1904): Zínias. Inv. 3146.
 Henri Fantin-Latour (1836-1904): Maçãs. Inv. 3148.
 Jean-François Millet (1814-1875): Costa rochosa em Gréville, 1854. Inv. 3152.
 Claude Monet (1840-1926): Barcos na praia de Etretat, 1883. Inv. 3153.
 Theodore Rousseau (1812-1867): O forno da aldeia. Inv. 3153.

Desenhos (seleção)

 Edgar Degas (1834-1917): Mulheres com guarda-sóis. Inv. 2001-121.
 Eugène Delacroix (1798-1863): Leoa sentada, leão em pé. Inv. 2001-122.
 Jean-François Millet (1814-1875): Homem cavando. Inv. 2001-124.

Esculturas (seleção)

 Jean-Baptiste Carpeaux (1827-1875): Porquê nascer escravo ? Inv. P. 853.
 Jean-Baptiste Carpeaux (1827-1875): O chinês. Inv. P. 852.
 Jules Dalou (1838-1902): A leitora. Inv. P. 855.
 Jules Dalou (1838-1902): Estátua do camponês. Inv. P. 857.

Livros

 Biblioteca constituía por 434 publicações de história da arte na pintura francesa do século XIX, 2005.

Outras doações ao Museu de Belas Artes de Leipzig

 Max Liebermann (1845-1935): Passeio no Tiergarten, 2006. Inv.3241.
 Max Liebermann (1845-1935): Rua em Scheveningen, 1891, 2017.

Em França
 Eugène Boudin (1824-1898): Berck, a costa, 1881. Musée du Touquet, Le Touquet, 1998.
 Jules Dalou (1838-1902) A Bolonhesa, (Mulher de Boulogne-sur-Mer), 1876. Bronze. Musée du Touquet, 1998.
 Henri Matisse (1869-1954): Mulher reclinad (Femme accoudée). Desenho. Musée Départemental Matisse, Le Cateau – Cambrésis, 2019.

Na Holanda
 Max Liebermann (1845-1935): Menina andando. Museu Singer Laren.

Em Portugal

Doação para a cidade de Setúbal
A fundação doou à cidade de Setúbal as seguintes obras:
 4 estátuas de barro, em tamanho real (Homem do talho, Descarregador de peixe, Mulher das flores e das frutas, e Mulher dos ovos e galinhas), obras de Augusto Cid expostas no Mercado do Livramento, 2011.
 Grande escultura de mármore (Grupo de golfinhos) em espaço público, de Carlos Andrade, 2017.
 Grande estátua de Luísa Todi, de Sérgio Vicente, em aço inox, frente ao Fórum Luísa Todi, 2012.
 Grande estátua de Zefiro em aço inox de Sérgio Vicente, 2013.
 Grande escultura em mármore "Sardinhas" de Luísa Perienes na rotunda das Fontainhas, 2012.
 Escultura romana: Cautopates (séc. III) e o "Calvário" do século XVII, ao Museu da cidade de Setúbal no Convento de Jesus, 2020.
 Unidade de Internamento de Curta Duração (UICD) do Serviço de Urgência Geral do Centro Hospitalar de Setúbal, E.P.E., que entrou em funcionamento no dia 23 de fevereiro de 2023.

Doação ao Museu de Arqueologia D. Diogo de Sousa em Braga

 200 peças da antiguidade clássica: peças de mármore, esculturas em mármore, bronze e terracota, mosaicos romanos, vasos cerâmicos gregos e etruscos, unguentários romanos em vidro, utensílios, equipamentos e adornos em bronze e metais nobres, incluindo bustos de mármore dos imperadores romanos Augusto e Trajano.
 Em 2021, o mesmo casal fez uma doação de 410 mil euros que foi utilizada em trabalhos de beneficiação e requalificação. A obra inclui a limpeza e pintura do edifício e a melhoria dos seus sistemas de segurança e iluminação.
Coleção Bühler-Brockhaus do Museu D. Diogo de Sousa no Wikimedia Commons

Condecorações

 2010: Ordem do Mérito do Estado da Saxônia, 19 de agosto de 2010.

Publicações
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Além de artigos em revistas de arte, Bühler também é coautor de:

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AKL Allgemeines Künstlerlexikon. Die Bildenden Künstler aller Zeiten und Völker, De Gruyter, DOI.
 .

Ligações externas
 "Uma marca na cidade e um lugar no coração" O Setubalense, 2019.
 Fundação Buehler -Brockhaus: Uma década a apoiar e embelezar Setúbal

Nascidos em 1942
Naturais de Stuttgart
Mecenas
Mecenas de Portugal
Negociantes de arte

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Insgesamt wurden 39 GTO-Fahrzeuge gebaut, davon 3 Exemplare mit einem Vierliter-Motor. Maßstab 1:18.
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CYC general and executive members attended an intensive two day training event, equipping us with some of the essential skills to work as an efficient youth council.
Our Slice of Youth events have become part of what CYC is known for! With the support of EPIC innovation and Inspired by Coffee and Jam, we've run a whole series of these events for young people in Christchurch. Our vision is for Slice of Youth to present an opportunity for rangatahi to listen to inspiring people doing fantastic things in their community, mix and mingle with fascinating people and organisations, and get involved in whatever they're passionate about!
This is our chance to get out into the community and find out what is important to young people, we head to markets, events and other places young people will be to find out how we can best represent them!
CYC has been working with both ECan and the City Council to run events where we can get young peoples opinion on both LTP's. We ran Kai + Consultation with Ecan early March and we are running an event with the CCC on April the 5th. We then take what young people think and write it into a submission.


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Fighting the Sexualization of Children
This week on Family Policy Matters, NC Family President John L. Rustin talks with Cathy Ruse from the Family Research Council about her recent report, Sex Education in Public Schools: Sexualization of Children and LGBT Indoctrination. Ruse's report details how graphic and extensive sex education classes have become in public schools, as activists push material that sexualizes and indoctrinates children. Ruse also gives advice for parents to help them protect their children from this type of material.
fightingthesexualizationofchildren Sex education Education Gay–straight alliance Family Research Council Human activities Human gender and sexuality Gender Abuse Parenting Human sexuality
Family policy matters and engaging and informative weekly radio show and podcast produced by the North Carolina family policy Council hi this is John Ralston, presidency, family, and were grateful to have you with us for this week's program is our prayer that you will be informed, encouraged and inspired by what you hear on family policy matters and that you will fold better equipped to be a voice of persuasion for family values in your community, state and nation. Thanks for joining us this week for family policy matters. Many of us may recall, though slightly uncomfortable days in middle or high school when we received instruction about human growth and development, anatomy, and yes, human sexuality. Today, students are by and large, being exposed to something entirely different in this instruction is causing great concern for parents and students across our nation. Of course this is not a new battle, but we are seeing growing efforts to push the envelope further and further when it comes to what our students are children are being taught about human sexuality and this is prompted a national profamily organization to raise the alarm again about radical changes taking place in America's public schools. Kathy Roos is a highly accomplished attorney and policy expert, and serves as the family research Council, Senior fellow and Dir. of human dignity. Kathy recently authored a report entitled sex education in public schools sexualization of children and LGBT indoctrination and she joins us today on family policy matters to discuss these alarming discoveries. Kathy welcome to family policy matters. It's great to have you with us on the show, Mike.
I'm glad to be here.
Well Kathy as parents. I think most of us hope that schools are communicating truthfully and transparently about the material that is being covered in their sex education classes. After all, these are very sensitive and important topics that your research indicates these programs often go far beyond just the basic facts of life correct, correct, and from parent reaching out to family research Council from my own research on just what is been recorded and then also my local activation in Fairfax County, Virginia, where I then on the Greyhound with families and parents fighting the school board town we decided we needed to report on on what we were learning because we knew that many, many parents didn't know for instance that schools are starting to introduce transgender ideology into effect that the message that children can be born in the wrong body which is a horrifying message for kids the idea that children have sexual rights part of the new sex ed and that's a new trend in teaching so that you get consent for sex act and that the highest moral imperative discounting altogether that even if some sort of consent engaging in sexual activity on the part of children. So it really been a paradigm shift from what sex ed used to be. I'm not saying it was never perfect but radically changed. Today about that now. There seem to be a number of buzzwords that are used to drive the agenda in many of the sex education programs tell us about some of those buzzwords and while parents should be on guard. When they hear these terms and phrases well right great time that parents might not be familiar with this opportunity. Many of these new tech that programs Delphi backwards to not saying students that they are going all the way to promoting sexual agency on the part of a child on year positivity.
Certainly, gender fluidity and gender identification. This may be determined that is not familiar parents.
Anything you seeing words like power and rights when it comes in the context of sex ed bad news is that direction sex ed is going today and it's extremely dangerous. I do cover North Carolina with some of the schools they are doing.
We have stories from Indiana Tennessee and Alex. It really is coming to a school near you and all parents need to wake up and learn about what the new sex ed movement is all about tests. So Kathy you most shocked to discover it is fairly commonplace. What has become run-of-the-mill, so to speak. In today's public school sex education curriculum. Well, wake up call. Really why the transgender ideology really what got my attention when I heard on the radio that my local school board had just voted to let boys into the girls bathrooms and showers. My attention at the boat with 1101 there only one sane person on the school board until I started attending. I wanted to meet her and thank her and that's when I just saw people in positions of power on the school board playing politics with other people's children, pushing policies that would affirm children who are confused about their sex mandating speech forcing people to use false pronouns, which is a serious violation of our religious beliefs are right Christian Tina. We believe that God designed male and female with a purposeful design and if we are forced to use false pronouns or two to even announce our own pronouns. That's really asking us to God and to swear allegiance to a false God tremendously serious things are happening what I'm talking about now is not necessarily an sex ed lessons.
Although all the language is being brought into sex ed but these are also sexuality related policy issues that are being imposed on cantons goes beyond sex ed becoming part of the environment of the whole school.
In many cases and there are good psychological organizations out there that call this child abuse and I agree with them. Teaching kids that they could be born in the wrong body. It psychological child abuse. I will say that I'm to get for saying that happening in public schools, and that's what I think is the most radical change, school, and I think it's important what you said even in some states, parents may have the ability to their children out of these programs or classes, but even in those cases, their children may still be exposed to some of these counseling dangerous materials and agendas because even if it doesn't happen within the context of a sex education class that this is a philosophy and an agenda that is permeating a lot of activities and arenas in our public schools. One of the what you discovered has led you to conclude that many of these programs are actually sexualizing children talk about the difficult to talk about the things on the radio course at Princeton tumbler page that there's nothing bad or unhealthy about having a big number of sexual partners in California, students are given tips about loading foreplay. This preteen children are encouraged to consider the three different types of intercourse in Indiana 19% shopping for conduct and coming back with a worksheet filled out about the price is and whether they're comfortable and what the different brands are like in a course.
It's difficult for me to describe on the radio. One of the worst examples was from West Albemarle County in Virginia where ninth-grade girls were shown a video on basically how to pleasure their partners and joys of sex toys and supportive horrible.
It's outrageous and it's still happening that particular video is called, but part of the new sex ed that the chief architect for this new sex ed is switch is the sexuality information education center in the US and they change their brands to sex ed for social change. That was not about information anymore.
It's not about education. It's about activism and social change for reproductive just social change for gender fluidity. It's all about creating sexual rights ideologues will go out then and change the culture. It's really insidious and in fact in the sex identity policies are really ground zero for manipulating children to be cultural warriors and parents are none the wiser.
Well, I know that you have spoken about the international influences that you have found that are associated involved in driving this agenda help us understand well. It mentioned one goodbye ready what you seek. And then of course Planned Parenthood is International Planned Parenthood founder foundation of America. They have an outsize role.
They claim to be the largest provider of sex ed in the country and in my research and when I'm hearing from parents. It pops up all the time that their schools have adopted part or all of Planned Parenthood sex ed program.
There are others that are big players. Southern poverty Law Center, when we heard about the discredited anti-Christian heat profiteer may have created something called teaching tolerance and they've mailed their best practices guide to every school principal and nation, telling them how to have it clear school culture and how to make sure that your prom is LGBT inclusive and so on and so forth. So they got a lot of money and they are using it to make social change through sex ed so most of the nations influencers at the education level seem to have bought into this program and it does sexualize kids, it does confuse kids. It's very manipulative. I call it political, politicizing all of this, and parents are left in the dark.
More than that parents are seen as the enemy. These programs want to get direct access to kids. They want parents out of the way and it often difficult to protect your kids from the material cut that you mention it's coming at them from all different directions so Kathy, what can and should parents do to help ensure the sex education program in the public schools are appropriate and in line with their values trying to be proactive. We have to be proactive me. One of the things parents can do is promote good sex ed programs. There are good sex ed alternatives and great resource for parents is a group called sand and their website as we ascend W EAS EMD.org champion sex ed alternatives that are known as sexual risk avoidance.
Basically, the term that is replaced abstinence because she can send the rest of them have made the word abstinence. A dirty word. So parents can have a door slammed in your face if you say I want more athletes but you can say sexual risk avoidance is what I want to see in our school and visit group has listed many programs that are in using Ensco today and also the research on how those programs are effective, so taking that last taking it to your school board taking to your County Counsel linear state rep and saying any of these programs being used and why not. If not everything I want to make sure to get in here is that parents can be proactive by filing a universal opt out letter with the school. Every year we provide that family research Council. It is a letter that said, I don't consent to my child being exposed to art to participating in any of the sexuality related issues or assemblies or lessons and not really put schools on notice that you're watching and you're prepared to act if your wishes aren't followed. It's your right you have a right to see the materials in advance and this is goes beyond the sex ed you need to be the squeaky wheel and going*okay, it's a new month. I want to see everything that my child to be learning this month like you really argue that you've got to be the squeaky wheel join with other parents and set out to review every single word every video every slide in your sex ed program but that's hard to tackle alone. So get a group of friends and review it and then Spread the word and then try to help your child start a club at the school that would be a healthy positive club. What were seeing is schools are being taken over by gay straight alliance clubs that are becoming the dominant cultural force in a school. The NEA promotes the TSA club the NEA even offers financial rewards for school to set up GSA clubs. It's all very connected but that is a recruitment center for kids, especially with gender fluidity and transgender is and so we got we got a credit provide alternatives for children in public schools. Those are great recommendations and great information throughout our conversation Kathy and I am so grateful for your work at FRC in the partnership that the family policy Council has with the family research Council in Washington DC. Kathy would just about out of time. But before we go want to give you an opportunity to let our listeners know where they can get a copy of this report.
Sex education in public schools sexualization of children and LGBT indoctrination. Her parents not only policymakers but this is her parents, Debbie WW.FRC.org/education one word and in that you will see, you will find a universal opt out letter. That's very important grade again with Pete that website. It's WWW.FRC.org as an family research Council/sex education and without Kathy Russo, thank you so much for being with us on family policy matters and for sharing your important and insightful findings on this crucial topic. Thank you so much you can listing the family policy matters. We hope you enjoyed the program and play the tune in again next week to listen to the show online insulin more about NC families work to inform, encourage and inspire families across a lot of our website@ncfamily.org that's NC family.org.
Thanks again for listening and may God bless you and your family


text:
\section{Introduction}

Semantic segmentation is a foundation in the computer vision field, which aims to predict the pixel-wise classification of the images and it enjoys a wide range of applications, such as medical image analysis, geological inspection, and auto vehicle. Recently, benefiting from the deep neural networks,  modern semantic segmentation models~\cite{chen2017deeplab,chen2018encoder,lin2016efficient,long2015fully} have achieved remarkable progress with massive human-annotated labeled data.
However, collecting pixel-level labels is very time-consuming and labor-intensive, which shifts much research attention to weakly supervised semantic segmentation (WSSS).

\begin{figure}[]
	\begin{center}
		\centering
		\includegraphics[width=3.3in]{img/CDA1.png}
	\end{center}
	\caption{Illustration of the difference between conventional augmentation approaches and our method. Classical data augmentation consists of generating images obtained by basic geometrical transformations (rotation) and color changes of original training images. Context Decoupling Augmentation (CDA) aims to randomly paste the given object instances into the scenes, so as to decouple the inherent context position of the original objects in the image.}
	\label{fig1}
\end{figure}

There exist various types of weak supervision for semantic segmentation like using bounding boxes~\cite{dai2015boxsup,khoreva2017simple}, scribbles~\cite{lin2016scribblesup,vernaza2017learning}, points~\cite{bearman2016s}, and image-level labels~\cite{hong2017weakly,ahn2018learning,ahn2019weakly,wang2020self,zhang2020splitting}. Among them, image-level class labels have been widely used since they demand the least annotation efforts and are already provided in existing large-scale image datasets.
To tackle the task in WSSS, the mainstream pipelines are based on visualization network CAM~\cite{zhou2016learning}, which first train a classifier network with image-level labels and discover discriminative regions that are activated for classification. Second, by expanding the seed areas using different techniques~\cite{kolesnikov2016seed,ahn2018learning,ahn2019weakly}, we can obtain the pseudo-masks as the ground-truth for training a standard supervised semantic segmentation model.

In this paper, we aim at focusing the research on augmentation for WSSS,  which is crucial for deep learning networks. As shown in Figure~\ref{fig1} upper part, given a training image, traditional data augmentation methods utilize some geometrical transformations, such as rotation, scaling, flipping, and even some color conversions to increase the diversity of images to avoid overfitting. However, for weakly supervised semantic segmentation, adjusting the image as a whole and maintain the same contextual semantic relation will not significantly help the networks to mine the object areas.
For example, "sofa"  always appears in the room in the datasets, therefore, the trained network may not only recognize the objects depending on the instance features but also their co-occurrence context information~\cite{li2018tell}. 	Specifically, when object instances often appear at the same time with some accompanying backgrounds, it will cause the networks to yield confounding bias. Namely, the networks can perform classification task well is not due to successfully distinguishing the characteristics of objects, but to being aware of the appearance of certain contextual semantic information, which is harmful to mine the object regions.

Based on this observation, we propose a Context Decoupling Augmentation (CDA) method, designing for disassembling the inherent contextual information of the original image. As shown in Figure~\ref{fig1} bottom half, the "cat" shows in the "sky", and the "sofa" falls on the "road". Although some of these scene collocations rarely appear in life, the models can pay more attention to the objects corresponding to the classification labels.
Unlike the fully-supervised data augmentation approaches~\cite{dvornik2018modeling}, we cannot access the object instance labels to extract the objects under the weakly supervised setting.
Therefore, we first adopt off-the-shelf WSSS approaches to obtain the object instances that have been well-segmented. Secondly, we randomly paste the selected foreground instances into the input images to get the new enhanced images and put them into the model for training together with  the original ones without augmentation.
In this way, we can break the dependency between objects and contextual background, and the models will focus on the internal information of the foreground instances rather than the context information to predict the categories they belong to. Besides, we use an online training technique to conduct data augmentation, which means that the combination of the raw input images and the object instances to be pasted are different each time.
This greatly increases the diversity of combinations of various scenes and object instances, and thus enhance the decoupling capability of the networks.

In the proposed context decoupling augmentation framework, we utilize different WSSS networks as our baselines. Specifically,  we investigate several architectures, including AffinityNet~\cite{ahn2018learning}, IRNet~\cite{ahn2019weakly}, SEAM~\cite{wang2020self}. To verify the effectiveness of our proposed method, extensive experiments show that CDA can improve pseudo-masks more than 2.8\% mIoU on average. We achieve new state-of-the-art performance by 66.1\% mIoU on the $\mathit{val}$ set and 66.8\% mIoU on the $\mathit{test}$ set of PASCAL VOC 2012~\cite{everingham2015pascal}.

The main contributions of our paper can be summarized as follows:
\begin{itemize}
	\item
	We present a generally applicable data augmentation approach for weakly supervised semantic segmentation, which, to the best of our knowledge, has not been well explored.
	\item
	The proposed context decoupling augmentation (CDA) method does not require additional data and it can remove the correlation between foreground object instances and background context information, which can drive the network focus on object regions rather than the background.
	\item
	Experimental evaluations on PASCAL VOC 2012 show the effectiveness of our proposed method and CDA can boost the performance of  different WSSS methods to the new state-of-the-art by a large margin.
\end{itemize}

\begin{figure*}
	\begin{center}
		\centering
		\includegraphics[width=6.8in]{img/001.png}
	\end{center}
	\caption{Overview of the proposed augmentation scheme. Stage-I: use the off-the-shelf weakly supervised semantic segmentation methods to obtain some simple object instances with good segmentation. Stage-II: paste the object instances randomly into the raw images to form the new input images, and perform online data augmentation training in a pairwise way with the original input images.}
	\label{fig2}
\end{figure*}

\section{Related Work}

In this section, we first give a brief review on weakly supervised semantic segmentation, and then we introduce related work on data augmentation.

\subsection{WSSS}

Image labels as the weak supervision for segmentation have been widely studied in the past few years. Many approaches~\cite{wei2017object,ahn2018learning,ahn2019weakly} use CAM~\cite{zhou2016learning} to mine the object seed regions by predicting image labels. To solve the problem that only the discriminative regions can be highlighted, researchers designed to expand the object seed regions in various ways. For example, in~\cite{yu2015multi}, the target regions are expanded by fusing different discriminative regions generated by convolutional layers with different expansion rates. ~\cite{wei2017object} drives the network to learn the rest parts of the objects by iteratively erasing the target areas. In addition, some previous works~\cite{hong2017weakly,hou2018self} use additional data, such as videos and saliency maps, to explore the objects areas.

Although object expansion technologies emerge endlessly, they all use CAM~\cite{zhou2016learning} as the cornerstone. The effect of subsequent diffusion depends on the first step of the CAM learning features.
As only image-level labels are provided, when objects are closely coupled with contextual backgrounds, such as "boat" and "water", "aeroplane" and "sky", "train" and "track", CAM will mistakenly recognize the background together with foreground objects. As mentioned in~\cite{li2018tell}, the training networks have no incentive to focus attention only on the foreground class as there may be bias towards other contextual factors as a distractor with high correlation. Thus, this is an issue that's worth thinking about and that needs to be solved.

\subsection{Data Augmentation}

Data augmentation is a major trick to train deep neural networks, which aims to increase the diversity of the data by increasing the training samples and avoid overfitting to a certain extent.
Conventional data augmentation approaches perform a series of operations on the basic data, such as rotation, flipping, adding Gaussian noise, etc.
Some works have explored synthesizing training data~\cite{frid2018synthetic,peng2015learning} for further generalizability. Generating new training samples by Stylizing ImageNet~\cite{geirhos2018imagenet} can lead to better classification performances. Recently, GAN~\cite{zhu2017unpaired} has been employed to transfer the style of the images and to make the content of the images from one domain to another, which can enrich the semantic information of the images to train the deep neural networks.
Furthermore, ~\cite{mixup} introduced a method to mix two random samples and divide the classification results proportionally to enhance images.~\cite{cutout} conducted augmentation by randomly cutting out some areas in the sample and filled it with 0 pixel value, and keep the result of classification unchanged.

For object detection and segmentation, a popular data augmentation way is "copy-and-paste"~\cite{dvornik2018modeling,dwibedi2017cut}. These works pasted real segmented objects into natural images, which is beneficial to increase the object complexity of the internal images and can help to solve the problem of small target detection. However, obtaining these segmented objects requires pixel-wise instance labels.~\cite{remez2018learning} used box-supervision and the off-the-shelf faster-RCNN~\cite{ren2015faster} method to segment and generate masks via cut-and-paste.~\cite{arandjelovic2019object} adopted the unsupervised cut-and-paste learning method to generate new combined images, but this kind of method is only applicable to the image of single object.
It is the first time that we employ copy-and-paste in the WSSS field and it does not require the help of pixel-wise labels and other auxiliary approaches. Thus, for WSSS, such a data augmentation scheme is significant and has not been well explored.

\section{Framework}

Our approach mainly consists of two stages : (1) we first collect the easy examples of well-segmented objects by using off-the-shelf \ WSSS methods; (2) then we train the network in a pairwise manner with online augmentation. In this section, we describe these two stages in details.

\subsection{Object Instances Collecting}

We aim to apply data augmentation on one of the WSSS models ($\mathit{e.g.,}$ IRNet~\cite{ahn2019weakly}). To some extent, the WSSS method can successfully predict good masks for some easy objects with class labels. Therefore, as shown in Figure~\ref{fig2}, in the first stage, we train the original network and we are able to select qualified object instances through the scene complexity of the image, the scope of the object and the semantic relevance by setting some criteria.

Specifically, for the inferring phase after training the network, we follow two main criteria for collecting object instances: (i) the current image should only have a single class. The intuition behind this is that in the case of only a single class, the image information should be simple and without a complex semantic environment, the segmentation results of the model should be more accurate; (ii) the segmentation result of the current image should meet the condition, $\epsilon_1 < \frac{m}{n} < \epsilon_2$, where $\epsilon_1$ and $\epsilon_2$ are two threshold factors, respectively. $m$ is the number of pixels belonging to the foreground object, $n$ is the number of pixels of the entire image. The reason lies that if the scale value of $\frac{m}{n}$ is too large, it should be that the background is incorrectly identified as the foreground. In contrast, if the scale value is too small, it should be that the model has not been able to recognize enough foreground object pixel information.
Different from existing synthesis approaches~\cite{dvornik2018modeling,dwibedi2017cut} , our method is based on self-provided masks to obtain qualified object instances images.

\begin{figure}[]
	\begin{center}
		\centering
		\includegraphics[width=3.3in]{img/blend.png}
	\end{center}
	\caption{Different kinds of pasting methods used in experiments. (a) Raw input, (b) Random rescale pasting, (c) Random rescale + rotation pasting, (d) Random rescale + rotation +  Gaussian smoothing pasting. }
	\label{fig3}
\end{figure}

\subsection{Online Augmentation Training}

\textbf{Blending.}
Before we take a step to train the network in the second stage, we first introduce how to blend the object instances into the natural images.
As shown in Figure~\ref{fig3}, we show different types of pasting skills in our experiments. It's worth mentioning that we only paste objects that have not appeared in the original images. The significance of this is that we can increase the diversity of objects of the images, while also reducing the dependence of the same objects in the inherent scene.
By randomly rescaling the objects, we can paste them into the images appropriately to prevent them from being too large or too small. The addition of random rotation can change the inherent orientation properties of the objects. Adding Gaussian smoothing can help the added objects boundary blend more naturally.

\begin{figure}[]
	\begin{center}
		\centering
		\includegraphics[width=3.3in]{img/good2.png}
	\end{center}
	\caption{Examples of the input augmented images with varying degrees of occlusion.}
	\label{fig4}
\end{figure}

In some cases, the blending may not be ideal, we elaborate on several possibilities for random pasting. As shown in Figure~\ref{fig4}, we have listed several augmented images of random pasting and we call them "perfect", "good" and "noise" examples.
As for the "good" example, the new object "bird"  covers part of the "dog" in the original image, however, we argue that this could help to erase the discriminative regions and force the network to discover more object regions like the function in ~\cite{wei2017object}. The noise example shows that the "sofa" completely covers the "aeroplane" in the original image, which will cause confusion to network classification.
However, we consider that such hard examples do not account for the majority. Most objects occupy in the middle or prominent location of the natural images. The random blending method we employ tends to paste the new objects into the off-center position of the images. Thus, this case does not affect learning. Hence, our framework is robust to the quality of augmentation. According to our experiments, this simple random blending method performs well in boosting the performance.

\renewcommand{\algorithmicrequire}{ \textbf{Input:}}
\renewcommand{\algorithmicensure}{ \textbf{Output:}}

\begin{algorithm}[htb]
	\caption{Stage-II: Online Augmentation.}
	\label{alg:Framwork}
	\begin{algorithmic}[1]
		\REQUIRE ~~\\
		The training dataset images $\mathcal{I}$ and the corresponding label $\mathcal{L}$;\\
		The object instances $\mathcal{O}$ and the corresponding label $\mathcal{T}$.

		\label{ code:fram:extract
		\WHILE{not done}
		\STATE ($\mathcal{I}_i$, $\mathcal{L}_i$) $\gets$ Draw one sample from training dataset;\
		\STATE ($\mathcal{O}_j$, $\mathcal{T}_j$) $\gets$ Draw one sample from object instances subset;\
		\WHILE{$\mathcal{T}_j$ in $\mathcal{L}_i$}
		\STATE ($\mathcal{O}_j$, $\mathcal{T}_j$) $\gets$ Resample;\
		\ENDWHILE
		\STATE $\mathcal{I}^{'}_i$ $\gets$ Blend $\mathcal{O}_j$ into $\mathcal{I}_i$;\
		\STATE $\mathcal{L}^{'}_i$ $\gets$ Append $\mathcal{T}_j$ in $\mathcal{L}_i$;\
		\STATE Train CAM $\gets$ Loss($\mathbb{C}$($\mathcal{I}_i$), $\mathcal{L}_i$) + Loss($\mathbb{C}$($\mathcal{I}^{'}_i$), $\mathcal{L}^{'}_i$);\
		\ENDWHILE
		\label{code:fram:trainbase}
		\STATE Expansion.
	\end{algorithmic}
\end{algorithm}

\textbf{Online Training.}
The augmentation scheme is conducted online to enhance the network trained in stage-I to improve the ability to distinguish object features.
Formally, in each batch, we sample $N$ images from the training dataset and the same number object instances images  from the subset which is provided from stage-I. Then we randomly paste the segmented objects into the input images, which creates a $N$ batch new images. Thus, a batch of size $2N$ is generated online for each  augmentation iteration.
The construction process of the online augmentation learning is summarized in Algorithm~\ref{alg:Framwork}.

Note that we train the online augmentation method in a pairwise manner as shown in Figure~\ref{fig2} stage-II left. We consider this can further help the networks to recognize the objects for the reason that some images have new blended objects, while some do not, which can help the classifier find more discriminative features.
The motivation behind this is similar to "finding the differences" with the human visual system. When the two images have a different object but with a duplicated background, which can often leave a deep impression. For the same reason, this can make the network classifier learn better features of this kind of object.

\subsection{Discussion}

The proposed CDA framework contributes a new data augmentation learning strategy. Unlike the previous "copy-and-paste" works, we do not use additional pixel-wise labels.
Specifically, by using the self-provided initial segmentation masks of the models, we can obtain the object instances for the next phase augmentation training. Furthermore, since our goal is to decouple the high correlation between objects and their contextual background, we don't need to consider much about visual context~\cite{dvornik2018modeling,chu2018deep}, which can greatly improve the efficiency of pasting objects into the images.
Besides, we adopt online augmentation training skills. Compared with static offline data augmentation, which merely enlarges the scale of the training dataset in linear-level. Namely, once a new dataset is formed, the number of images will remain unchanged. However, our method is able to obtain exponential-level augmentation, because the combination of object instances and natural images can be ever-changing in each round of training.

\section{Experiments}

To demonstrate the contributions of the proposed method, we conduct several ablation studies to show the effectiveness of CDA and compare different baselines models to the state-of-the-arts. We will give the details of the datasets, evaluation metric, and baseline models in the following.

\subsection{Dataset}

All the networks in our framework are trained and evaluated on the PASCAL VOC 2012~\cite{everingham2015pascal} segmentation benchmark for a fair comparison to previous approaches.
The official dataset separation has 1464 images for training, 1449 for validation and 1456 for testing.
Following the common practice, we take additional annotations to build an augmented training set with 10582 images presented in~\cite{hariharan2011semantic}.
We use the standard mean Intersection-over-Union (\textbf{mIoU}) as the evaluation metric for all experiments.

\subsection{Implementation Details}

To validate the applicability of CDA, we deploy it on three popular WSSS models including IRNet~\cite{ahn2019weakly}, AffinityNet~\cite{ahn2018learning} and SEAM~\cite{wang2020self}.
The general training architecture components include a multi-label image classification step, a
pseudo-mask generation step, and the final segmentation model (DeepLab-v2~\cite{chen2017deeplab}). We strictly follow the same settings as reported in the official codes. Specially, for SEAM~\cite{wang2020self} and AffinityNet~\cite{ahn2018learning} baselines, ResNet38~\cite{he2016deep} that pre-trained on ImageNet~\cite{deng2009imagenet} is adopted as backbone with batch size as 8 and 16, respectively. When training the networks,  multi-scale and data augmentation techniques like horizontal flip, random cropping, and color jittering are deployed in both architectures. Following the poly policy $lr_{init}$ = $lr_{init}(1-itr/max\_itr)^\rho$ with $\rho$ = 0.9 for decay, the models are trained with a fix input size as 448 $\times$ 448 using Adam optimizer~\cite{kingma2014adam}. Besides, online hard example mining~\cite{shrivastava2016training} is employed on the training loss in SEAM.
As for IRNet~\cite{ahn2019weakly}, ResNet50~\cite{he2016deep} is used as the backbone network (pretrained on ImageNet). The batch size is set to 16 for the image classification model and 32 for the inter-pixel relation model. The input image is cropped into a fix size of 512 $\times$ 512 using zero padding if needed. The model is trained with the same polynomial decay strategy as in AffinityNet~\cite{ahn2018learning} using stochastic gradient descent (SGD) for optimization with 8, 000 iterations.
The fully-connected CRF~\cite{krahenbuhl2011efficient} is used in three baselines to refine CAM, pseudo-mask, and segmentation mask with the default parameters in the public code.
We set the threshold $\epsilon_1$ = 0.1 and $\epsilon_2$ = 0.7 by experience.

\subsection{Ablation Studies}

To verify the effectiveness of our CDA, we evaluate CAM seed regions, pseudo-masks, and segmentation masks. In our experiments, the standard mean Intersection over Union (mIoU) is used on the training set for evaluating CAM seed area masks and pseudo-masks, and on the $\mathit{val}$ and $\mathit{test}$ sets for evaluating segmentation masks. For the sake of simplicity, since the three WSSS models are all based on CAM~\cite{zhou2016learning}, we use one of the representative models (IRNet~\cite{ahn2019weakly}) as a baseline to conduct several ablation studies on CAM in mIoU to illustrate the role of each component of our approach.

\begin{table}[]
	\begin{center}
		\scalebox{0.9}{
			\begin{tabular}{c|c|c}
				\toprule
				\toprule
				Method  \ & \ operation \ & \ mIoU (\%)\\
				\midrule
				\multirow{2}*{Conventional Augmentation }& Rotation & 48.5  \\
				& Translation & 48.4 \\
				\midrule
				\multirow{3}*{Mixup~\cite{mixup}}& $\alpha$ = 0.3& 48.7  \\
				& $\alpha$ = 0.5 & 48.5 \\
				& $\alpha$ = 0.8 & 49.0 \\
				\midrule
				CutOut~\cite{cutout} & Random& 48.9 \\
				\midrule
				CutMix~\cite{cutmix} &  Random& 49.2 \\
				\midrule
				Random pasting (ours) & Rescale & \textbf{49.8} \\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{Experiments of different augmentation methods. Here $\alpha$ is the intensity of the interpolation between the eigenvector and the target vector.}\label{table1}
\end{table}

\begin{table}[]
	\begin{center}
		\scalebox{0.9}{
			\begin{tabular}{ccccc}
				\toprule
				\toprule
				Baseline  & Rescale &Rotation& Gaussian & mIoU (\%)\\
				\midrule
				$\checkmark$&  & & & 48.3 \\
				$\checkmark$&  $\checkmark$& & & 49.8 \\
				$\checkmark$&  $\checkmark$&$\checkmark$ & & \textbf{50.8} \\
				$\checkmark$&  $\checkmark$& & $\checkmark$& 49.6 \\
				$\checkmark$&  $\checkmark$&$\checkmark$ & $\checkmark$& 50.4 \\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{The ablation study of the effect on different pasting methods. Baseline indicates the original CAM method without pasting new objects for augmentation.}\label{table2}
\end{table}

\begin{table}[]
	\begin{center}
		\scalebox{0.9}{
			\begin{tabular}{c|c}
				\toprule
				\toprule
				Training manner  \ & \ \ mIoU (\%) \\
				\midrule
				Pairwise& \textbf{50.8} \\
				None-pairwise & 50.1 \\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{Experiments of augmentation training manner.}\label{table3}
\end{table}

\textbf{Random pasting vs. Other sophisticated augmentation methods:} As for the traditional augmentation methods, we adopt the random rotation and translation to expand the dataset to three times the original size, however, they can not bring significant boost for the performance. We also compare Mixup~\cite{mixup}, CutOut~\cite{cutout} and CutMix~\cite{cutmix} methods to generate new augmented images.
As shown in Table~\ref{table1}, random rescale pasting outperforms the other three methods achieving \textbf{49.8}\% mIoU.
These results demonstrate that random pasting is suitable for our CDA framework. We consider that proper occlusion helps the network to better mine the features of other areas of the objects, and the situation of complete occlusion is relatively rare which will not affect our learning process.

\begin{figure}[]
	\begin{center}
		\centering
		\includegraphics[width=3.3in]{img/cam.png}
	\end{center}
	\caption{Qualitative visualization of CAMs. Our CDA framework not only suppresses over-activation ($1^{st}, 2^{nd}, 3^{rd}$ row) of the high correlation contextual backgrounds of the objects and expands CAMs to cover the whole object regions ($4^{th}$ row).}
	\label{fig5}
\end{figure}

\textbf{Comparison with baseline:} We further explore the impact of different pasting methods on data augmentation. Table~\ref{table2} shows that using random rescale pasting has a 1.5\% improvement compared to baseline. After combining rescale and rotation, we can get the best performance to \textbf{50.8}\% mIoU on PASCAL VOC training set. The results show that applying Gaussian smoothing can not help to improve the performance. Therefore, in subsequent experiments, unless otherwise specified, we will use the random rescale combining with the rotation method.

\begin{table*}[]
	\begin{center}
		\scalebox{0.9}{
			\begin{tabular}{c|c|c|c|c|c}
				\toprule
				\toprule
				Network  & \  \ Backbone \ & \ \ \ \ CAM \ \ \ \ & \ Pseudo-Masks \ & \ Seg. Masks (val-set)  & \ Seg. Masks (test-set)\\
				\midrule
				AffinityNet~\cite{ahn2018learning} &  ResNet-38 & 48.0 & 59.7  & 61.7 & 63.7\\
				+ CDA &  ResNet-38 & $48.9_{\color{red}+0.9}$ & $63.3_{\color{red}+3.6}$  & $64.2_{\color{red}+2.5}$  & $65.8_{\color{red}+2.1}$\\
				\midrule
				IRNet$^{*}$~\cite{ahn2019weakly} &  ResNet-50 & 48.3 & 65.9  & 63.5 & 64.8\\
				+ CDA &  ResNet-50 & $50.8_{\color{red}+2.5}$ & $67.7_{\color{red}+1.8}$  & $65.8_{\color{red}+2.3}$  & $66.4_{\color{red}+1.6}$\\
				\midrule
				SEAM~\cite{wang2020self} &  ResNet-38 & 55.4 & 63.4  & 64.5 & 65.7\\
				+ CDA &  ResNet-38 & $58.4_{\color{red}+3.0}$ & $66.4_{\color{red}+3.0}$  & $66.1_{\color{red}+1.6}$  & $66.8_{\color{red}+1.1}$\\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{Different baselines with our CDA framework performance in mIoU on PASCAL VOC. $^{*}$denotes our reimplemented results since the original code does not provided pre-trained weights.}\label{table5}
\end{table*}

Figure~\ref{fig5} shows the qualitative comparison between our CAM+Aug by CDA method and the original CAM.
As shown in the first and second rows in the figure and the labels of objects are "table". The original CAM will activate background semantic information that is strongly related to the "table", such as "chair". However, by employing  the decoupling augmentation training strategy, our method can focus on the target areas. For the image with the label of "train", CAM even pays attention not to the object itself, but the "track", which will be detrimental to the subsequent segmentation task. Moreover, CDA can also help the network expand and discover more comprehensive object features but not only the most discriminative regions like the "cat" shown in the last row.

\textbf{The effect on pairwise training:} Compared to merely using the augmented images to train the networks, we use the none-augmented images with the augmented images as pair images to jointly train the models as shown in Figure~\ref{fig2} stage-II.
The results shown in Table~\ref{table3} show that applying pairwise training strategy outperforms the one in single augmented images, which illustrates that this helps the network classifier to learn more discriminative features.

\begin{table}[]
	\begin{center}
		\scalebox{0.85}{
			\begin{tabular}{c|c|c}
				\toprule
				\toprule
				Number of pasted objects  &  Same category objects  & mIoU (\%)\\
				\midrule
				1 & $\times$ & \textbf{50.8}\\
				2 & $\times$ & 48.9\\
				3 & $\times$ & 47.8\\
				\bottomrule
				1 & \checkmark & 50.2\\
				2 & \checkmark & 48.6\\
				3 & \checkmark & 47.4\\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{Experiments of different number of pasted objects for augmentation.}\label{table4}
\end{table}

\textbf{The effect on objects numbers:} Under the default settings of our experiment, we only paste one new instance that does not exist in the original images. We further explore the effect of pasting multiple objects into the images to conduct augmentation. As shown in Table~\ref{table4} above the solid line, when the number of object to be pasted increases from one to two, the mIoU performance will decrease. As the number of pasted objects changes to three, it will even worse than the baseline. The results show that over-pasted objects may cover the objects in the original image, making the noise sample dominant. This will confuse the classifier, which will bring negative effects.
In addition, as depicted below the solid line in Table~\ref{table4}, when we allow the pasted object to be consistent with the object category in the original image, their general performance is worse than the former.
This shows that forcing objects of different categories to be pasted into images can decouple the strong contextual dependence of objects in the original semantic environment.

\begin{figure}[]
	\begin{center}
		\centering
		\includegraphics[width=3.3in]{img/pse.png}
	\end{center}
	\caption{Visualization of pseudo-masks (baseline: IRNet~\cite{ahn2019weakly}). (a) Input images. (b) Ground-Truth labels. (c) Our CAM+Aug. (d) Original CAM.}
	\label{fig6}
\end{figure}

\begin{figure*}
	\begin{center}
		\centering
		\includegraphics[width=6.6in]{img/deeplab.png}
	\end{center}
	\caption{Qualitative results on the PASCAL VOC 2012 val set. (a) Input images. (b) Ground-truth labels. (c) Results obtained by IRNet~\cite{ahn2019weakly} baseline. (d) Results of our IRNet + CDA. More results can be found in the supplementary material.}
	\label{fig7}
\end{figure*}

\begin{table}[]
	\begin{center}
		\scalebox{0.88}{
			\begin{tabular}{ccc|cc}
				\toprule
				\toprule
				Methods & Backbone &  Saliency & $\mathit{val}$ & $\mathit{test}$\\
				\midrule
				CCNN~\cite{pathak2015constrained}$_{\text{ICCV'15}}$ & VGG16 & -& 35.3 & 35.6\\
				SEC~\cite{kolesnikov2016seed}$_{\text{ECCV'16}}$ & VGG16 & -&50.7& 51.1\\
				STC~\cite{wei2016stc}$_{\text{TPAMI'17}}$ & VGG16 & \checkmark&49.8 & 51.2\\
				AdvEra~\cite{wei2017object}$_{\text{CVPR'17}}$& VGG16 & \checkmark & 55.0 & 55.7\\
				DCSP~\cite{chaudhry2017discovering}$_{\text{BMVC'17}}$& ResNet101 & \checkmark & 60.8 & 61.9\\
				MDC~\cite{wei2018revisiting}$_{\text{CVPR'18}}$& VGG16 & \checkmark & 60.4 & 60.8\\
				MCOF~\cite{wang2018weakly}$_{\text{CVPR'18}}$& ResNet101 & \checkmark & 60.3 & 61.2\\
				DSRG~\cite{huang2018weakly}$_{\text{CVPR'18}}$& ResNet101 & \checkmark & 61.4 & 63.2\\
				AffinityNet~\cite{ahn2018learning}$_{\text{CVPR'18}}$& ResNet-38 & - & 61.7 & 63.7\\
				IRNet~\cite{ahn2019weakly}$_{\text{CVPR'19}}$& ResNet50 & - & 63.5 & 64.8\\
				FickleNet~\cite{lee2019ficklenet}$_{\text{CVPR'19}}$& ResNet101 & \checkmark & 64.9 & 65.3\\
				SEAM~\cite{wang2020self}$_{\text{CVPR'20}}$& ResNet38 & - & 64.5 & 65.7\\
				ICD~\cite{IDC}$_{\text{CVPR'20}}$ & ResNet101 & - & 64.1 & 64.3 \\
				\midrule
				IRNet + CDA (ours)& ResNet50 & - & {\color{blue} 65.8} & {\color{blue} 66.4} \\
				SEAM + CDA (ours)& ResNet38 & - & {\color{red} 66.1} & {\color{red} 66.8} \\
				\bottomrule
		\end{tabular}}
	\end{center}\caption{Performance comparisons with other state-of-the-art WSSS methods on PASCAL VOC 2012 dataset. The {\color{red} best} and {\color{blue} second best} performance under each set are marked with corresponding formats.}\label{table6}
\end{table}

\textbf{Analysis of pseudo labels and Segmentation masks:} The overall results are shown in Table~\ref{table5}. We can observe that deploying CDA on different weakly supervised semantic segmentation models can improve all their performances. Specifically, SEAM~\cite{wang2020self}  can achieve the best performance in Segmentation Masks on both validation set and testing set.
Figure~\ref{fig6} shows that we can obtain more accurate and complete masks covering the object areas.

\subsection{Comparison with State-of-the-arts}

Finally, we compare our framework with state-of-the-art methods on the PASCAL VOC 2012 dataset including both the validation set and the testing set. For a fair comparison, we adopt the same DeepLab~\cite{chen2014semantic,chen2017deeplab} architectures as reported in the original papers.
Table~\ref{table6} shows experiment results of previous approaches.
Although different baselines already boosts performance compared to previous methods, when CDA is deployed in the models, SEAM~\cite{wang2020self} can achieve the best performance and outperform other state-of-the-arts by a large margin. IRNet~\cite{ahn2019weakly} yield the second best performance and can beat its later published works.
Figure~\ref{fig7} presents qualitative results of our CDA approach applying on IRNet baseline and compares them to those of IRNet itself.
We can observe that CDA can make more accurate predictions on objects, which shows better demarcations in some coherent areas. Meanwhile, CDA can help to expand and discover more comprehensive object regions.

\section{Conclusion}

In this paper, we discuss and investigate the confounding bias by the network classifier in object recognition when there are only class-labels. To this end, we propose a Context Decoupling Augmentation (CDA) method for weakly supervised semantic segmentation and to narrow the gap with fully supervision.
Specifically, through two-stage training, the object instances provided by the network itself are pasted into the input natural images to conduct augmentation. To further improve the ability of network for learning object features, we adopt pairwise training manner to help the classifier to distinguish more discriminative features.
Experimental results show that CDA can help boost various WSSS methods to the new state-of-the-arts without using extra data and labels.

\vspace{1ex}

\noindent \textbf{Acknowledgment.} \ This work was supported by NSFC 61876208, Key-Area Research and Development Program of Guangdong 2018B010108002, National Research Foundation Singapore under its AI Singapore Programme (AISG-RP-2018-003) and the MOE Tier-1 research grants: RG28/18 (S) and RG22/19 (S).

{\small
\bibliographystyle{ieee}

redpajama_set_name: RedPajamaArXiv


Hi all! My name is Regan and I am a first-year from Elon University. I am currently planning on majoring in marketing with a digital marketing track, and want to pair it with a communications minor. At Elon, I am a member of the Business Fellowship Program, which gives me the opportunity to take special classes, work closely with a cohort of 30, and prepare for a future career in business. I have grown up in a family of business owners, so I have always known a business track would be right for me. I have chose marketing because I enjoy the statistical analysis of data, but also the creative design aspects used in marketing in order to design campaigns, products, and advertisements. I have helped my dads company, the Merjant Group, with CIS Reports and presentations as a graphic design consultant, and love the challenge of design consistency and matching color schemes and fonts. I applied to the University Innovations Fellows program for the opportunity to create change on my campus– and hopefully on a broader spectrum, too– through innovation, entrepreneurship, and design.
This page was last modified on 25 February 2018, at 22:25.


text:
#pragma once

#include <functional>
#include <atomic>
#include <memory>
#include <chrono>

#include "../input.h"

namespace Vingine {

	/*
		The BaseCallback is what's visible to the InputManager alonside the final implementation of a callback
	*/
	class BaseCallback {
	public:

		/*
			Get a clock-type that is suitable for us
		*/
		typedef std::conditional<std::chrono::high_resolution_clock::is_steady,
			std::chrono::high_resolution_clock,
			std::chrono::steady_clock>::type ClockType;
		typedef ClockType::time_point TimePoint;
		typedef std::optional<TimePoint> TimePointOptional;

		/*
			Executing will call the user callback and reset the time
			We will keep this for us, a user may override a later function in the inhertiance chain
		*/
		virtual void Execute(const TimePointOptional & now) = 0;

	protected:
		/*
			Memory-orders used for store and load operations on atomic variables inside the callbacks
		*/
		static constexpr std::memory_order m_StoreOrder = std::memory_order_release;
		static constexpr std::memory_order m_LoadOrder = std::memory_order_acquire;
	};

	/*
		One can register a callback for whatever this is defined for, e.g. keyboard or mouse
		Executing the callback will have to be done on the users terms
		The window thread will only update the callbacks data to ensure thread-safety
		I.e. the window-thread accesses only data it knows everything about
	*/
	template<class CallbackTy, typename CallbackEnum>
	class Callback : public BaseCallback {
		/*
			Note that Callbacks have to be friended to the InputManager
			Without the InputManager a Callback can do nothing
		*/
		friend class InputManager;

	public:
		/// TODO: Profiled and saw that using std::function will have significantly
		/// worse performance as opposed to a lambda or virtual function... What to do!?
		/// Hypothetically the callback is not run more than once a frame, so it shouldn't be a big problem
		/// It will probably still be faster using virtual function calls, however that's extremely inconvenient for a user
		// Definitions for a user-provided callback
		enum class CallbackUsage {
			Consumed,
			Ignored
		};
		typedef std::function<CallbackUsage(const CallbackTy & callback)> CallbackFun;

		/*
			A callback must be specified on construction
			If no callback is provided then this must be a concious decision
		*/
		Callback() = delete;
		Callback(CallbackFun callback);
		Callback(CallbackFun callback, double deltaTime);
		virtual ~Callback();

		/*
			Find out if a callback was provided on construction
		*/
		bool HasCallback() const;

		/*
			Where the magic happens, the actual execution of the callback
		*/
		virtual void Execute(const TimePointOptional &  now) final override;

		/*
			Functions to let the user get information about this callback
		*/
		double GetMillisecondsSinceLastExecution() const;
		double GetSecondsSinceLastExecution() const;

		/*
			Abstraction to get a callbackCode, e.g. keyCode
		*/
		virtual CallbackEnum GetCallbackCode() const;

	protected:

		/*
			A post execute function has to be provided for each implementation
		*/
		virtual void PostExecute(const CallbackUsage &callbackUsage) = 0;

		/*
			Abstraction to set a callbackCode, e.g. keyCode
		*/
		virtual void SetCallbackCode(CallbackEnum callbackCode);

		/*
			Convenience for implementing new callback types
		*/
		double GetMillisecondsSinceLastTimePoint(TimePoint timePoint) const;

		/*
			This is the user-provided callback
		*/
		const CallbackFun mCallback;

		/*
			TimePoint of the current execution
		*/
		TimePoint mNow;

		/*
			TimePoint of the last successful execution
		*/
		TimePoint mTimeExecuted;

		/*
			The minimum time to do an update after in milliseconds
		*/
		double mMinDeltaTime;

	};
}

#include "callback.inl"

redpajama_set_name: RedPajamaGithub


This program creates a Java application that contains a Processing sketch and a Swing GUI. The Swing GUI contains a button that shows a color picker, and that color is sent to the Processing sketch to be displayed.
This class contains variables that keep track of a color, a draw() function that displays that color, and a setColor() function that sets those variables. It also contains a run() function that calls the PApplet.runSketch() function to run this as a sketch. Notice that it uses the this keyword to pass itself in as a parameter.
This class creates a Swing GUI that contains a button. When that button is pressed, the JColorChooser.showDialog() function is called, which allows the user to pick a color. That color is sent to the ProcessingSketch instance, which is passed in as a parameter.
This is just a basic example, but it shows the general setup of creating a Swing GUI and a Processing sketch and communicating data between them.
Make it so only one window is shown at a time. First show the Swing GUI and allow a user to pick a color, and then show the Processing sketch after the settings were chosen. Bonus: add a button to the Processing sketch that goes back to the Swing control window.
Create a Swing GUI that allows a user to specify input to a procedural generator, which is drawn in Processing.


text:
Westpac Global Currency Card
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text:
The man in the No. 24 car talks Tiger
So maybe Jeff Gordon can explain the FedEx Cup points system to us, since the FedEx Cup was patterned in a way after the NASCAR Chase.
At any rate, Gordon, in a news conference at Kansas Speedway over the weekend, was asked about Tiger Woods after Forbes magazine reported that he is the first from sports to exceed $1 billion in earnings. Gordon's reply, in part:
"There are certain people who come along in the world who change the way you look at that industry. I don't like to watch golf if Tiger's not playing. That is why he has been able to do what he's done. He makes far more money in endorsements than he does actually playing golf...Michael Jordan was the same way. There are certain individuals who change how you perceive the sport, how you follow it, and they have a following beyond just that game of golf...I really think he's done an excellent job in how he's handled himself, the things that he's associated himself with, and it's still unfathomable that he has made the impact that he's made from a financial standpoint. But obviously it works.
"Another thing that is so huge about Tiger and golf is its world wide. They might play golf somewhere on another planet. If they did, they'd want to play with Tiger. He's just that one rare guy that's come along and has lived up to the expectations or exceeded them. He's very marketable and has obviously surrounded himself with some very smart people to help him make good decisions."


text:
TrendMD recommendations help readers discover more journal articles directly related to their interests.
The first figures released since Ingenta Connect and TrendMD announced their partnership in May 2016 show the immediate success that the TrendMD recommendation widget has had on driving additional traffic to Ingenta publishers' content. TrendMD continues to demonstrate it consistently delivers online readership and visibility for scholarly publishers. Participating publishers...
Ingenta acquires advertising software company 5 fifteen Ltd
Ingenta has acquired 5 fifteen Ltd, software supplier to the magazine and newspaper industry. This purchase will allow us to strengthen our product portfolio and strategically build on our existing plans to diversify our client base, extending our offering into the media industry, in addition to trade and academic publishing markets. Established in the UK in...
Institutional library budgets set to increase, global study concludes
Institutional library budgets across the globe will increase by 1.4 per cent overall this year, reports the Annual Library Budget Survey, carried out by the Publishers Communication Group (PCG), Ingenta's publishing consultancy arm. The worldwide study, which interviewed senior librarians in 686 institutional libraries across the globe about their budget...
TrendMD and ReadCube integration across Ingenta Connect enhances scholarly article discovery
Ingenta has partnered with the scholarly discovery services TrendMD and ReadCube to boost discoverability of articles hosted on its aggregated content portal Ingenta Connect. The platform integration with TrendMD enables Ingenta Connect publishers to drive traffic to their content online and grow their readership. TrendMD generates personalised on-site content recommendations, based...
Ingenta Connect and Kudos collaborate to increase discoverability of academic content
Ingenta and Kudos have announced a new partnership to make the Kudos service available to publishers hosted on the Ingenta Connect platform. Kudos works with academic publishers to help scholarly authors to maximise the visibility and impact of their published articles. The service provides an easy-to-use platform for creating information...
Publishing Technology becomes Ingenta
Publishing Technology has announced that it will change its name to Ingenta, with immediate effect, as part of a comprehensive rebrand and unification of its business. Already a well-established and trusted brand within the scholarly publishing arena, the Ingenta name will bring together the company's products and services under one...
Henry Stewart Publications signs international journal representation deal with PCG
Leading vocational journal publisher, Henry Stewart Publications, has signed a multi-year, global sales representation contract with Publishers Communication Group (PCG), an Ingenta company. The agreement will see PCG represent the publisher's 16 journals, primarily at an institutional level, across major international markets including North America, Latin America, China, India, UK...
Ingenta joins the Annotating All Knowledge coalition
Ingenta is proud to be working with Annotating All Knowledge, a coalition formed to improve the quality of information available online. Bringing together some of the world's key scholarly publishers, academic institutions, researchers and individuals alongside technology developers and platform providers, Annotating All Knowledge was formed to foster greater collaboration...
Sabinet signs up to Ingenta's CMS GO! platform solution
South African electronic publication aggregator, Sabinet, has signed an agreement with Ingenta to launch an online platform on its packaged web solution, CMS GO!. The partnership means that Sabinet will now host its major journal service, the Sabinet African ePublications (SA ePublications), on ingentaDrive, an out-of-the-box product launched by Ingenta...
Ingenta renews hosting collaboration with ASM
The American Society for Microbiology (ASM) has signed an extension to its online hosting contract with Ingenta, which will see the organization solidify its long term commitment to its digital platform ASMscience and continue its development plan for the future. The custom built website, which houses a vast and varying...


text:
Recent news from the various sectors of the recycling industry
RPlanet Earth opens plastics recovery, recycling plant
RPlanet Earth, previously headquartered in El Segundo, California, has opened its 302,000-square-foot plastics recovery and production facility in Vernon, California, which also now serves as its headquarters. The plant is designed to produce 80 million pounds of food and drink packaging annually using a bottle-grade flake production system supplied by Germany-based Krones that includes a front-end bottle sorting system supplied by Bulk Handling Systems (BHS), Eugene, Oregon.
RPlanet Earth does not sell recycled flake or pellets but processes PET bales and converts them in-house into bottle preforms, extruded sheet and thermoform packaging.
"We really are a technology company," says rPlanet Earth co-CEO Bob Daviduk. "We're going to bring technology to bear to improve the way that postconsumer PET is recycled. We'll have the lowest carbon footprint of any packaging in the marketplace because of the way we've put the plant together."
Earlier this year, the California Department of Resources Recycling and Recovery (CalRecycle) approved a $2 million California Climate Investment loan to rPlanet Los Angeles LLC to help pay for the PET recycling infrastructure at its new facility in Vernon.
Financing from CalRecycle's Greenhouse Gas Reduction Loan Program will allow rPlanet to transform 1,000 tons of plastic scrap into packaging each year, create 52 new jobs and reduce the equivalent of 1,500 metric tons worth of CO2 greenhouse gas emissions annually.
The automated BHS system processes more than 6 tons per hour (tph) of baled postconsumer polyethylene terephthalate (PET) and runs nearly 24 hours a day, according to a news release issued by BHS.
BHS says the system employs BHS screens, Nihot air, NRT optical and Max-AI robotic sorting technologies to produce a clear PET product for further processing. Five NRT optical sorters with In-Flight Sorting technology remove metals, mixed plastics and colored PET and positively sort clear PET. The Max-AI AQC-2, an artificial intelligence-directed robotic sorter, uses a camera, neural networks and two robots to autonomously perform the final quality control (QC) process.
BHS also supplied the plant with its recently launched Total Intelligence Platform, which automatically processes information from the system's controls system and motors, optical and Max-AI equipment, scales, baler and other sensors to provide an information and analytics platform.
The plant recovers aluminum and other metals and mixed plastics for further processing by other companies.
© hroephoto / stock.adobe.com
Agilyx, AmSty plan joint venture
Agilyx, an environmental technology and development company in Tigard, Oregon, has signed a letter of intent with AmSty, a The Woodlands, Texas-based integrated producer of polystyrene and styrene monomer. According to an Agilyx news release, the companies plan to form a joint venture that will assume operations of Agilyx's polystyrene (PS) recycling facility in Tigard and pursue the development of a 50-ton-per-day PS recycling facility at a location to be determined.
The Agilyx process converts used PS products back into their original liquid styrene monomer form. Agilyx reports that new PS products can be made from this recycled styrene monomer without degradation of quality or value.
In August 2017, AmSty and Agilyx announced an agreement to process recycled styrene monomer from Agilyx's Tigard facility and AmSty's styrene monomer plant in St. James, Louisiana.
"Agilyx is very excited to expand our relationship with AmSty," says Joe Vaillancourt, CEO of Agilyx. "This joint venture will greatly advance the circular economy for postconsumer polystyrene waste and reflects the confidence and support by industry for our technology platform."
"We are excited to work with Agilyx as we continue to improve our PolyUsable process, assuring polystyrene remains a viable and growing component of the circular economy," says Brad Crocker, president and CEO of AmSty.
Schupan invests $10.1 million in expansion
Kalamazoo, Michigan-based Schupan & Sons Inc. is expanding at two locations in that city, investing an expected $10.1 million.
The project will increase manufacturing capacities and add office space to Schupan Aluminum & Plastic Sales' current location.
Kendra Townsend, Schupan's marketing and communications manager, says the sales division expects to add more than 40,000 square feet and an additional 50 employees over the next three years.
The aluminum and plastic service center specializes in a full line of new aluminum and plastic mill products. The manufacturing department "utilizes state-of-the-art technology, producing complex components for the medical device, aerospace and office furniture industries," according to the company.
Schupan Electronics Recycling also will be expanding its Kalamazoo footprint, adding 80,000 square feet of processing space and an additional 30 employees over the next three years.
The electronics recycler is nearly tripling its current size, with room to add more processing equipment as it expands services to its growing customer base.
Stress test for the ferrous market


text:
Digital Marketing Latest Trends 2021>
[Funding alert] Northern Arc raises $10M in ECB financing from Calvert Impact Capital
Post category:Digital Marketing Latest Trends 2021
Chennai-based digital debt platform Northern Arc Capital has raised $10 million in debt from US-based Calvert Impact Capital via External Commercial Borrowing (ECB).
According to the company, this is Calvert Impact Capital's largest debt investment in India so far. Northern Arc will deploy the funds towards on-lending to financial institutions as well as lending directly to retail customers and to mid-market corporates.
Bama Balakrishnan, Chief Operating Officer of Northern Arc, said,
"The partnership with Calvert Impact Capital is long-term and multi-dimensional, helping both organisations achieve common goals across impact and growth. These include aiding small businesses and promoting gender equity, a cause that is strongly endorsed by both organisations. The facility's longer duration will expand Northern Arc's ability to fund MSMEs and households."
Kshama Fernandes, MD & CEO, Northern Arc Capital
Underbanked customers, including low-income households and small businesses to whom credit has dried up over the last few months due to the pandemic, will be a key beneficiary of the proceeds, the firm said. These borrowers will be served both directly by Northern Arc as well as through on-lending to partner institutions.
Similarly, high-quality Non-Bank Financial Corporations (NBFCs), early-stage businesses, and small and medium enterprises (SMEs) that have strong business models but are facing liquidity crunch will also benefit from this financing.
"Northern Arc has been instrumental in strengthening Indian debt capital markets to the benefit of organisations serving underbanked populations. Today, more than ever, these companies and their clients benefit from access to a diversity of funding sources and the relationship-based approach of the Northern Arc model. As an investor, we benefit from leveraging the market and credit expertise of the Northern Arc team as we put capital to work for impact in India," added Daniel Ford, Investment Officer, Calvert Impact Capital.
Northern Arc Capital Limited (formerly known as IFMR Capital Finance Limited) is a non-banking finance company that provides access to debt for under-banked individuals and businesses in India. Through a combination of capital, products, and partnerships, Northern Arc and its subsidiaries have created a platform that connects millions of borrowers to mainstream debt investors.
Since its inception, it has enabled over $12 billion of financing to over 200 partner organisations through 140 reputed domestic and global investors.
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text:
From the River (In)to the Sea
Elisheva Goldberg
Updated Jul. 13, 2017 7:39PM ET / Published Jun. 18, 2012 3:15PM ET
Karim Sahib / AFP / GettyImages
Open Zion tends to make a lot of jokes about Greater Israel. But this is really something—Israel is settling the Mediterranean.
Yesterday Israel's cabinet approved exploration for a lavish artificial island to "solve Israel's shortage of space for large industrial facilities"—4.5 kilometers off the coast of Gaza. Yep, Gaza, the fifth-most densely populated place on Earth, will be practically across the street from a $1.5 billion industrial Disneyland.
The island will feature a desalination plant, presumably for Israeli consumers. But according to the ICRC in 2011, "every day hundreds of gallons of waste water are dumped into local waterways that trickle through urban areas in Gaza." The Island will have an airport (Gaza's Yassir Arafat International launched a grand total of zero flights in the last dozen years) and a seaport (Gaza's was destroyed in the 2nd Intifada and never rebuilt), resort hotels, tourist areas, and a marina. Not unambitious for a country deeper in debt than the United States. PA officials called the project "pure fantasy," and in a way, it almost seems like Israel's building itself a private "Never Never Land"—a place where it can esape the problems of the mainland in general and Gaza in particular.


KPMG's Cash to Accrual and IPSAS services look to provide member firms' clients with a broad range of methodologies.
KPMG's services look to provide member firms' clients with a broad range of methodologies.
Accrual accounting improves the quality of general purpose reporting by public sector entities, and can lead to better informed assessments of the resource allocation decisions made by governments, thereby helping in the increase of transparency and accountability. The International Public Sector Accounting Standards Board (IPSASB) has highlighted that the financial and sovereign debt crises have brought to light, as never before, the need for better financial reporting by governments worldwide, and the need for improvements in the management of public sector resources. Strong and transparent financial reporting has the potential to improve public sector decision making and to make governments more accountable to their constituents.
Governments that report on a cash basis do not account for significant liabilities, such as pensions and infrastructure development. As a result, the IPSASB encourages public sector entities to adopt the accrual basis of accounting, which will likely improve financial management and increase transparency resulting in a more complete and accurate view of a government's financial position. Many governments, jurisdictions, and international institutions have already adopted IPSAS, and many more are on the road to implementing the standards.
KPMG's Cash to Accrual and IPSAS services look to provide member firms' clients with broad range of methodologies, including preparing and presenting an impact analysis for the implementation of IPSAS and translating the accounting impacts into tangible actions to help deliver their required changes in the organization's systems, processes, people, and also to the wider business.
Our team works to deliver meaningful results through a deep understanding of the issues and an intimate appreciation of how the public sector works.