Late this afternoon I was able to pick my bike up from Tagg's. I am so grateful that they squeezed it in, even though they were really rushed with weekend work. I went straight to the rally site and didn't bother with taking the tent. I still had a nice evening with lots of friends, who had even saved me a place at the table for an evening meal with them. It was so nice to see them all. They'd come from as far apart as Yorkshire and Devon and it was like seeing family. How I love rally season. I'm so glad John made me promise I'd learn to use the sat nav so I could keep going to as many as possible. The next Triumph one I've booked a ticket for is the Concorde rally, in Chippenham in September. My favourite one of the whole year. That is my big challenge. If I can find my way there I can do anything.
fzr-paul, Eagle, Pilbs and 5 others like this.
Brilliant Emma. So glad you made it there on the bike.
Returned today from the Triumph Owners rally in Chippenham. It rained from lunchtime Friday until about two miles from Ashford on the way home, this morning. Despite the atrocious weather many Triumph owners has a brilliant get-together, ate fattening food, drank beer and talked rubbish all weekend. I didn't win the distance award this year as another lady Street Triple owner who travelled from Scotland deservedly won the trophy but I was surprised and then very, very pleased to be awarded the best Hinckley Triumph trophy. I was pretty much struck dumb and so many nice people came and congratulated me afterwards that I was almost overcome, although very proud of my lovely bike. Horrible ride home this morning with just one speedy fuel stop but no tea and buns as we were really cold and uncomfortable and just wanted to get home safely. The trusty sat nav kept me going in the right direction and Jonny 1400 followed me, just in case I made any mistakes with it. I really think I've got it sussed now. I can start my travels properly next year now I've got all my camping and navigating needs sorted.
Pilbs, fzr-paul, Eagle and 6 others like this.
Go girl. Proud of you.
Beelady and Conrad like this.
Scary, but exciting at the same time. I was last man on a ride out with the East Kent Triumph owners and up ahead of the front bike I saw a Marsh Harrier swoop low, into the undergrowth on the left hand side of the road. I was just thinking "Wow! That was close" when the stupid thing came rocketing out again and collided with my head. I ducked and for a split second it wrapped itself across my visor, rattled my crash helmet and then it was gone and I was still upright. Phew! I've always wanted a closer look at one but that wasn't quite what I had in mind.
lammyR6, Roadwart, SuzuKeith and 1 other person like this.
Who's not A small bird?
Stars and Stripes, Beelady, BlackHornet and 1 other person like this.
lisa lou, Eagle, Stars and Stripes and 3 others like this.
But was she single and did you get her number?
A trip to Ramsgate on the Kawasaki to get a new chain and sprockets fitted. Whatever made me think I could do the whole job myself? There are bits on that bike that must have been untouched since it was new, so I was very glad that I had a friend to take over and get the job done while I did the watch and learn thing. He also removed the swinging arm for a closer look at the corrosion we could see. Happily the rust wasn't nearly as bad as it looked and it got a good clean, rubbed down and a couple of coats of smooth Hammerite before it went back together, so now it not only looks a little smarter but it was really smooth on the ride home. I didn't think I'd notice a big difference, but the old chain was really much worse then I thought. Very glad to have that job done and very grateful for having the sort of friends that are there when needed.
Eagle, Roadwart, Fergy and 5 others like this.
Panel Man, Eagle, Tomasbe and 4 others like this.
lammyR6 and Beelady like this.
Beelady, Rev and lisa lou like this.
Roadwart, BlackHornet, Mikey and 2 others like this.
Now I wish I'd taken a picture of you on the scooter. At least you didn't add a caption. I think I can guess what it might have been. It's a sad state of affairs when a woman can't even try on a hat in peace.


text:
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace JsonMessages.Authentication
{
	public class ChangePasswordRequest : SessionSecuredRequest
	{
		public string OldPassword = string.Empty;
		public string NewPassword = string.Empty;
	}
}

redpajama_set_name: RedPajamaGithub


Your strength to always find the bright spot is inspiring. Sam really is a superhero in our book. Keeping you all in our prayers. Thanks for continuing to share your story.
He is Superman Sam! This kidlet! I'm so grateful for your continued press for the best for Sam. Continuing to pray the best for this little guy. I'm so grateful for the team you have. They are doing more than a job. They are investing in a very valuable and influential life! Not only praying for little Sam's STRONG body…but for rest and peace for the family!
Continued prayers are being sent for Sam and the whole family. Thank's so much for keeping us abreast of Super Sam's progress. Thinking of all of you.
Keeping you all in our prayers, Jamie! It is comforting to know that Sam is thriving through all these hurdles. He sure is inspiring! Thank you for your blogs and continuing to share Sam's medical journey. Love and Blessings!
Thank you for continuing to share your (Sam's) story. You and your family are truly amazing. Stay strong and continued prayers for you all! Much Love!


The way of conducting military operations in the future will rely heavily on computers and use of digital information. The new keyword is precise engagement, where geoinformatics has a decisive role. This dissertation deals with the use of geographical information in military terrain analysis as a backbone for new possibilities from the Finnish Defence Forces point of view.
This dissertation is divided into three parts. The first part introduces the battlefield and describes the background: technical basis, COTS and analysis opportunities, available GIS datasets in Finland and possibilities to gather specific military field data. The second part presents the decision-making process used in the FDF and the demands set from the viewpoint of new component architecture. The second part also forms the hierarchical metamodel to solve the stated problem. The third part is the empiria that is used to evaluate and describe the use of the model. Quality is dealt with as a holistic issue covering all parts of the model including basic datasets.
Military terrain analysis is done effectively by the guidance of the formed hierarchical metamodel on three levels (figure on the next page). Basis for the geospatial information superiority can be built with the Finnish geographical datasets, which are complemented by the military field data. Military terrain analysis can significantly support the decision making process. Tactical level constructive simulator as a decision support tool is a part of the highest level GIS analysis in order to support the decision making process. Fast way to implement the terrain analysis in C3-systems is to use COTS tools. The standards are becoming mature enough to ensure the adequate openness of the systems. GIS analysis can support military risk evaluation and decisions also in cooperation with the civil society to protect the people and the infrastructure.
The conceptual model to support data acquisition from the enemy by terrain analysis is also introduced. Used forms of data, information and knowledge are enemy (1-data), no enemy (0-data) and places where no data can be obtained by the used sensor (no-data).
The research was conducted with the hypothetic-deductive method and it was commenced in 1998. The relationships between the combat models and the constructive simulators were studied in theory and applied by inspecting 14 different systems.
This work relates to defining the GIS strategy as a part of the C3-architecture for the FDF.


text:
ROBERT D'AVANZO
MASTER ACTING COACH
Home (In Person Classes)
Classes (In Person) Vaccination Proof Required
Scene Study (In Person) Actors Must Show Proof of Vaccination.
Ongoing On-Camera (In Person)Actors Must Be Vaccinated.
6 Week On-Camera Audition Class (In Person) Actors Must Be Vaccinated. Vaccination Proof is now Required.
Improv for the Actor
Celebrity Seminar Series
Pay With Venmo
"I am seeking blood and guts actors, actors who will commit to self and craft, who want the stamp of truth on everything they say and do. Real things happening to real people." If this sounds like a class environment you're looking for then call me. -Robert D'Avanzo
CONTACT ROBERT
The word "passion" was invented for Robert. His intensity is undeniable. -Roy London
Robert was born in New York and moved to South Florida in 1970. He worked on his MFA from Florida Atlantic University in Acting and Directing. It was there that Robert was influenced and fortunate enough to work with such luminaries as Edward Albee, Hume Cronyn, Bill Homewood (RADA), and Joshua Logan.
Robert has been in over 100 productions, both as an actor and director before relocating to Los Angeles. Since then Robert has worked closely with the late Charles Nelson Reilly, who considered Robert his protege`, Henry Polic II, and the late Roy London. He is also a co-founder of The Florida Theatre Connection as well as serving as Resident Director of the Tamarind Theatre. Past shows at the Tamarind that Robert has directed include:Brothers, Lynette at 3 AM, and It's All About You, and a host more, 45 to be exact, but whose counting? He directed the critically acclaimed Durang Durang at the Hollywood Court Theatre, Seascape With Sharks And Dancer at The Bitter Truth Theater, The Backwards Aorta at The Complex and Sunday on The Rocks at The Underground. As an actor Robert has Guest starred in ABC's …it's like, you know as Felipe Horowitz, Curb Your Enthusiasm with Larry David as well as having finished work with Martin Landau and Rita Moreno in Carlo's Wake and Jenna Fischer in Lollilove, both independent feature films. Robert teaches his Master Classes and is Artistic Director at RD Studio.
It's easy to recommend a movie, a certain deli, but to recommend an acting teacher is a more serious task. A true teacher can touch ones life forever. After a lifetime of relationships with master teachers Uta Hagen, Herbert Bergoff and Jose Quintero, I know a teachers qualifications. My former pupil and friend of many years Robert D'Avanzo has these assets: Commitment, Compassion and Talent. He also has vast experience in the Theatre (Actor/Director) and the screen. He is gentle of heart. I have seen his classes and I highly recommend them! -Charles Nelson Reilly
Robert D'Avanzo is one of Hollywood's best kept secrets but not for long. Robert's students work!
As an Acting Coach, Robert's students are seen nightly starring in Televison Drama Series, Television Sitcoms, Saturday Night Live, MTV, Major Motion Pictures, Talk Shows and Broadway.
Find out why more and more of Hollywood's most important decision makers are trusting Robert with their top clients. You are where you're supposed to be, now let me help you get to where you want to be. Don't be left behind.

redpajama_set_name: RedPajamaCommonCrawl


text:
posted Oct 1, 2010, 9:45 AM by Nancy Swan [ updated Oct 1, 2010, 4:39 PM by Thomas Swan ]
Minor should have his appeal denied. "US Supreme Court to decide on hearing convicted former Mississippi attorney Paul Minor's appeal" (Biloxi Mississippi Sun Herald) http://www.sunherald.com/2010/09/30/2518520/us-supreme-court-to-decide-on.html#ixzz118JDu8Sl
Paul Minor and his associate Judy Guice were the former lawyers in my toxic tort case and the judge Minor was convicted by a jury of bribing was my judge, Mississippi Harrison County Circuit Court. Judge John Whitfield.
Standing in Judge Whitfield's courtroom, Paul Minor revealed that my previous judge, Circuit Court Judge Jerry O. Terry had been "bribed twice" to stall my case by sending it two times to Mississippi Supreme Court. I was fortunate to have that information recorded.
I was an unnamed victim of the bribery scheme between Minor and Whitfield. Minor told me that he could "get" Judge Whitfield to rule against me if I did not do what he (Minor) "advised" me to do. I refused. It was my information that launched the federal investigation that indicted Justice Oliver Diaz then convicted half a dozen high profile lawyers and a number of judges in Mississippi, including Minor and Whitfield who are serving eleven year sentences in federal prison.
I attended Minor's trial. Information from the Court transcripts, hundreds of news stories, and the my records are convincing that Minor bribed Judge Whitfield. Minor paid off almost $150,000 in loans he guaranteed for Judge Whitfield while hearing Minor's cases. To hid his payments, Minor used third parties, secretaries, and cash to pay off Whitfield's loans. Judge Whitfield, married, used the money from Minor as a down payment on a house for his mistress.
If the US Supreme Court overturns the bribery convictions, the US Constitution will be rendered worthless to those of us who cannot afford the high price of US "justice."
To prevent this from happening to anyone else, I wrote Toxic Justice which I hope will soon be represented by an agent and publisher. Toxic Justice


Your respect card legal instrument is two times what you suggestion it would be, you're over your draft control and your mound chief is not leaders chuffed with you for fact list an I-pod and a couple of Jimmy Choos as 'essentials'. It may countenance look-alike your summertime vacation is active to have to be a time period in Scarborough beside the parents once again but there's no trauma in checking out the alternatives! For the Richard Branson's and Donald Trump's of the world zero but the unexcelled will do and when you're superficial for the finest appearance no additional than The Atlantis catwalk Suite.
The Atlantis Bridge Suite at The Atlantis building in the Bahamas is the representation of delight and at a precooled $25,000 per hours of darkness you would be hopeful of no smaller number. The ten room composition is situated on top of a span which connects the Royal Towers of the building and has a position over and done with the whole docking facility.
The Suite comes near its own butler, bar couch and amusement heart. The furniture is as lavish as one may possibly anticipate - daybed lounges, marble baths, murals, sculptures and copiousness of metallic.
The holiday resort itself boasts a casino, the Mayan Temple entertainment allure which includes marine slides and a ride which passes through a wash out passageway in a shark-filled lagoon and a 63 acre waterscape. But later when you're paying $25,000 for the piece of music you power not deprivation to rung outside!
And you'll not be in bad firm. Past guests at the opus count Oprah Winfrey, and Michael Jackson.
So when you've spent equalization you check volume and you've worked out you're before now in counter info and it's ten days until pay day, put distant the calculating machine and permit yourself to build castles in spain. How the else partly live!


Its amazing how many locals have allowed this to happen..
Locals have been told for so long that petrochem companies "have rights" that there is a widespread feeling of defeat – that you can't stop them so you are better to cooperate with them or they will make life even more difficult. Yes, the petrochems have rights, but so do locals have rights and it is time to reclaim those. Petrochems don't have the right to destroy an area by industrialising it, simply in pursuit of the shareholders' return. It is time to look at how residents' and landowners' rights can be retained alongside such development. And it is time for locals to TALK TO EACH OTHER again. This is and always been such a divisive issue that we've stopped talking to each other about it. That is why I want a moratorium on new consents and major variations to consents while a plan for Tikorangi is worked out. You will contact council and ask for this too? Good to hear from you, Rangi.
Hi,I happen to work on one of these rigs and as a Waitara local (born n bred) I understand your concerns. We do make a large effort to minimise effects, i.e. noise, vehicle movements, and being friendly to the locals. Unfortunately there are some things that can't be helped as in lights, mechanical noise and trucks when we move the rigs.
Please understand that for some people this a blessing as it means we no longer have to leave our families for Ozzy to make a decent crust, often you will see this crust distributed throughout the community as we give a better life for our children and extended families.
Most wont know that it takes on average about 3 months to complete a hole and 2 weeks to move a rig. So if you do the math on approx. 59 holes with 2(maybe more) rigs, this boom will last about 3 years. Because that is all it is..a boom, which means it will end. Pipe lines will carry all the gas to Motunui and more friends and families will be set up for life in the process and production end. The big drilling rigs will leave, the traffic will deplete, the skys will once again dim. This isn't the first boom and surely will not be the last.
So I just ask you to consider the rest of the community, because we consider you as best we can. If a delay is caused, that is all it will be…a delay, and the rigs will be here for longer, and our continuation of work may be affected.
Thank you for providing such a good example of the sort of thing that has been said here for years. That we shouldn't moan because it is good for other people. Alas, when it is all over in 3 years (IF it is all over in 3 years, which we doubt) we will be left with an industrialised countryside and devalued properties some of which may be unsalable because they are beside industrial sites. We are paying a high price for your family's financial security. You may have missed the point on my call for a moratorium – we want planned and managed development that respects our rights too. It is not a delaying tactic, staving off the inevitable. It is a planning tactic. Companies have plenty of valid consents to keep the work going – around 30 wells currently approved.
Gee, if only there was a moratorium for when the first settlers arrived and started burning down the bushlands and stealing land to build the farms you live on now. Maybe all this wouldn't be happening? Karma? Or just bad luck.
Not always planning tactics. We are not always sure if the well will be an angry one or a dud. The next well always depends on the last well. Just shows what you assume.
You also have just admitted that this is also about the dollar, as I have. You are guilty of greed just like everyone else.
So on that note, I will continue to do MY best to minimise effects on the surrounding community, continue to make a decent crust while the work is here and continue to share the wealth with my family and the wider community.


That said, one scenario I can easily imagine is one in which insurance companies get spooked by the idea that this is going to pass and then deliver votes of "moderate" Democrats and various Republicans in favor of a Swiss-style (or perhaps Massachusetts-style is a better way to put it) system. In that case, I think you could hardly blame the White House for deciding to say "yes" to the opportunity to deliver universal health care. Substantively, that would wind up kicking the can on most of the important issues, but you can see the politics playing out that way. But in either case, I think the main point is that it's maintaining the possibility of doing health reform through the budget reconciliation process and of including a robust public option that's bringing people to the table. In other words, it's essential to keep pushing for this idea.


text:
PCMag Australia | Reviews | Web Sites | News
Google Handles a Billion Piracy Takedown Requests in a Year
By Matthew Humphries
30 Nov 2016, 2:35 a.m.
Of the 1,007,741,143 takedown requests received, 908,237,861 were removed from search results.
As the biggest provider of search results on the Internet, Google receives a constant barrage of requests to remove content from its results. Some of those requests come from governments, but the majority are submitted by copyright owners very keen to stop their work from being pirated.
These requests arrive in the form of a URL takedown demand, which Google then needs to verify is a legitimate claim before taking the appropriate action. And all the data related to those requests is combined into the regularly updated Google Transparency Report.
SEE ALSO: The Best Prime Day Australia Deals
Getty Images: Google Promotes Piracy
The latest figures make for some surprising reading. TorrentFreak reports that over the last year, Google received over a billion URL takedown requests from copyright holders. Of those, just under 909 million turned out to be legitimate and got removed, with those infringing links leading to 347,000 affected websites.
The scale of the takedown system Google runs is huge, and it's growing at a phenomenal rate. Consider that Google kicked off the takedown request program in March 2011. In total 1.97 billion URLs have been removed since then. From 2011 to 2015 it generated around 970 million requests, but the other billion happened just in the last year. How much will it have grown again by November 2017?
Google allows you to explore the data, which reveals who the reporting organizations are, as well as which domains suffered the most with removed links. Takedown agencies Rivendell and Degban join publisher BPI at the top of the charts, each submitting in the region of 250 million takedown requests. As for domains, 4shared easily topped the charts with over 50 million URLs removed.
Study: Facial Recognition Systems Struggle to ID Dark-Skinned Women
Duncan Jones Launches Online-Only 'Bowie Book Club'
Dia Box
Jimmy Wales Launches Wikitribune to Fight Fake News
Matthew Humphries Senior Editor
Matthew is PCMag's UK-based editor and news reporter. Prior to joining the team, he spent 14 years writing and editing content on our sister site Geek.com and has covered most areas of technology, but is especially passionate about games tech. Alongside PCMag, he's a freelance video game designer. Matthew holds a BSc degree in Computer Science from Birmingham University and a Masters in Computer Games Development from Abertay University. See Full Bio
More From Matthew Humphries
Microsoft Internet Games Will Be Unplayable Soon
Destiny 2 Doesn't Run on Ryzen 3000 CPUs (But a Fix is Coming)
Eavesdropping Bug Forces Apple to Disable Walkie-Talkie App
Nintendo Announces The Switch Lite For $199


text:
In Belgian museum, a virtual reality tour across DRC's capital with 'Kinshasa Now'
Key Libya commander Khalifa Hifter announces candidacy for president
-/AFP
with AP
Libya's powerful commander, Khalifa Hifter, filed Tuesday as a candidate in the country's presidential elections next month, as the long-waited vote faces growing uncertainty.
Hifter submitted his candidacy papers Tuesday in the eastern city of Benghazi and announced the move in a video. He said he's seeking the country's highest post to "lead our people in a fateful stage."
He called on Libyan people to vote "with the highest levels of awareness and responsibility" so the nation can begin rebuilding and reconciliation after a decade of chaos and civil war.
Libya has been wracked by chaos since a NATO-backed uprising toppled longtime dictator Moammar Gadhafi in 2011. The oil-rich nation had for years been split between a government in the east, backed by Hifter, and a U.N.-supported administration in Tripoli, aided by west-based Libyan militias. Each side has also had the support of mercenaries from countries such as Russia and Syria and different regional powers.
Hifter commands the self-styled Libyan Arab Armed Forces but delegated his military duties in September to his chief of staff, Abdel-Razek al-Nadhouri, for three months, to meet candidacy terms.
Hifter's announcement comes after Seif al-Islam Gadhafi, the son and one-time heir apparent of the late dictator, submitted candidacy papers Sunday in the southern town of Sabha. Seif al-Islam, who is wanted by the International Criminal Court on charges of crimes against humanity, has spent years largely in hiding.
If accepted, both Hifter and Seif al-Islam would be among front-runners in the Dec. 24 vote. They have stirred controversy in western Libya and the capital of Tripoli, the stronghold of their opponents, mostly Islamists.
Politicians and militia leaders have already expressed their rejection of their candidacies and demanded laws governing the presidential and parliamentary elections to be amended.
The long-awaited vote still faces other challenges, including occasional infighting among armed groups, and the deep rift that remains between the country's east and west, split for years by the war, and the presence of thousands of foreign fighters and troops.
Hifter's forces besieged Tripoli in a year-long campaign that tried to capture the city. The campaign ultimately failed last year, leading to U.N.-mediated talks and the formation of a transitional government charged with leading Libya until the parliamentary and presidential elections.
In his video comments, Hifter said that if elected, he would prioritize defending Libya's "integrity and sovereignty."
He has previously modeled his leadership on Egyptian President Abdel-Fattah el-Sissi, a close ally. Both have declared war on terrorism — applying the term not only to extremist groups but also to more moderate Islamists.
The 77-year-old served as a senior officer under Gadhafi but defected in the 1980s during the ruinous war with Chad, in which he and hundreds of soldiers were captured in an ambush. Hifter later spent more than two decades in Washington, where he is widely believed to have worked with the CIA, before returning to join the anti-Gadhafi uprising in 2011.
Hifter's prominence rose as his forces battled extremists and other rival factions across eastern and later southern Libya, areas now under his control. He has the support of Egypt and the United Arab Emirates, as well as France and Russia.
The controversial military commander and Gadhafi's son are the main presidential hopefuls submitting their candidacy papers. Also widely expected to announce presidential bids are Parliament Speaker Agila Saleh and former Interior Minister Fathi Bashaga.
Prime Minister Abdul Hamid Dbeibah could also become a contender. He said Monday he'll run for president if that's what the people want, but he faces legal obstacles.
Under Libya's elections laws, he would have had to step down from government duties more than three months before an election date. He also pledged when he was appointed to the interim position through U.N.-led talks that he would not run for office in the government that succeeded his. Those talks were marred by allegations of bribery.
Libya: lawmakers meet to discuss delayed elections
Bodies of 28 migrants wash ashore on Libya's coast
Saif al-Islam Gaddafi
Muammar Gaddafi
Algeria: Sonatrach to invest $40bn over five years
Libyans express frustrations after presidential election delays
Pics of the day: Decmber 22, 2021
Libya's electoral commission proposes January 24 for delayed polls
More than 160 dead migrants off the coast of Libya according to the UN
Libya's presidential candidates call for unity after poll postponement


Seoul: Samsung has announced that it has installed its first ever commercial cinema LED screen at Lotte Cinema World Tower in Korea.
Designed as a High Dynamic Range (HDR) LED theatre display, the cinema LED screen creates a more captivating and vibrant viewing experience through next-gen picture quality and true-to-life audio thanks to collaboration between HARMAN and Samsung Audio Lab.
Stretching nearly 10.3m (33.8ft) wide in size, the cinema LED screen accommodates a variety of theatre configurations. The display brings the visual power of HDR picture quality to the big screen, and enlivens content with both ultra-sharp 4K resolution (4,096 x 2,160) and peak brightness levels (146fL) nearly 10 times greater than that offered by standard projector technologies.
To go with the stunning video technology within the 'SUPER S' theatre of Lotte Cinema, Samsung has paired its cinema LED screen with audio technologies from JBL by HARMAN. "'SUPER S' theater is a new paradigm of movie screening," said Wonchun Cha, Lotte Cinema CEO.
"We look forward to working with Samsung to introduce new, high-quality technology to the movie industry in the future, and we are excited to drive customer satisfaction through an improved viewing environment that brings a variety of content to life." Prior to its commercial debut, Samsung ran the cinema LED screen through a series of the industry's most rigorous tests to validate its performance and presentation.
In May 2017, the cinema LED screen became the first product to achieve full compliance with the highly-esteemed Digital Cinema Initiatives (DCI) theatre technology standards prior to its commercial release.


My name is Sam Lisker, and I'm a communicator with nearly a decade of experience as a digital creator.
Within that timeframe, I've grown a YouTube channel (which has amassed over 2.5 million overall video views) written for USA TODAY and CBS News, as well as maintained a website for a music podcast. I've also done talent work for news broadcast as a multimedia journalist (MMJ) and a weekend anchor.
I'm still growing as a digital creator, and I am open to new opportunities to help expand my expertise.


text:
The New Workplace Reality: Impact on People, Spaces and Places
|In Portfolio, Workplace
|By CoreNet Global
Guest Post by Stefan Schwab, CEO of Comfy | Enlighted
Consensus among company leadership is clear: hybrid working is a critical tool for maximizing business productivity while navigating the unparalleled amount of change and uncertainty in the last year.
While many companies have adopted flexible working as a permanent structural change, implementing change management across their organization remains difficult for the majority of companies, according to a recent study that Siemens commissioned with the independent analyst firm Verdantix.
As part of the study, the firm conducted interviews with 75 corporate real estate executives1 on the strategic considerations of the return to the office. The major finding revealed by the report: 99 percent of firms are turning to flexible work models as the solution to balancing competing business priorities. Additional key findings demonstrate the widespread, long-term effects of COVID on the office of the future: from the function and layout of the office to the evolved role of CRE executives in the new normal.
The corporate real estate function evolved in influence and authority due to the pandemic
The pandemic's profound impact on the way people work elevated the function in the organization, with 93 percent of respondents reporting that they have greater strategic influence in key business decisions.
More interaction with C-suite executives (33% of respondents), progression in job responsibilities and strategic influence, and an emphasis on collaboration and communication with HR and IT transformed the role for 44% of respondents.
The office of the future will be dominated by hot desks and collaboration spaces over traditional assigned workspaces
The office of the future will aim to inspire collaboration, flexibility and productivity. Currently, traditional assigned workspaces make up, on average, 45% of real estate portfolios. This is expected to reduce to 37% by 2023. Activity-based workspaces and hot-desks – currently constituting 28% and 27% of real estate portfolios – are expected to increase to 34% of real estate portfolios by 2023.
Portfolio transformation aims to improve efficiency and reduce operational costs
With more than half of firms reducing the square footage of their real estate portfolios since the start of the pandemic, this trend will continue over the next two years. Twenty eight percent of firms will reduce their portfolio by up to 10%, and another quarter of firms will reduce by more than 10 percent. This transformation will bring down operational costs, while adapting the office to the new way of flexible work.
At the core of any business is the health and well-being of its workforce. Employees and leadership resoundingly agree that flexible working balances the human need for connection with companies' emphasis on productivity and efficiency. By adapting working preferences to suit employees' personal lives, the movement to hybrid working signifies a fundamental change in how people connect to their co-workers and their workspaces while redefining the meaning of work in the new normal.
Additional insights and complete findings from the report are available here.
1 The New Workplace Reality report, Siemens and Verdantix, October 2020. All 75 respondents held senior roles and worked for firms with annual revenues of over $1 billion, based in North America, Europe and APAC. The study was concluded in August 2021.
Stefan Schwab is CEO of Comfy | Enlighted


text:
A brief account of the whole Ingrid Ricks
Posted by Admin2 on Dec 14, 2012 in Writers on Writers
by Carol Levin
No, Ingrid Ricks' photo is not here. I invited her to talk about herself in order to gather more than a side view for her profile. She is, happily, very fluent. What follows, of course, is through the filter of my own perception, some of which may be inaccurate. I did not record it besides fragments of notes in pencil in a notebook.
I suggested she begin by recalling objects as touchstones for prompts, sort of an animated object autobiography. But Ingrid vibrates with what she wants to communicate so the conversation slopped over the edges of objects and flowed along unaided. There is a celebration of life and self within.
If you haven't already met Ingrid, she's a not very tall bundle of energy that not only vibrates as she speaks, but even exudes ebullience when she's listening.
If you have read (and I hope you have) her book, Hippie Boy, you know what she has chosen for you to know about herself up to age sixteen. And, wow, that is a compelling, dynamic story. So as she described the first object she thought of, it was connected to the journey she writes about in Hippie Boy. At least I could easily envision her reaction as she described the drawing she saw, when at age 23, on an assignment as a reporter for a small Burien, WA newspaper she interviewed a fellow named Byron Fish. On his wall was a drawing of a naked man running on a beach with a caption "Free at last." Now she owns this object and it continues to reverberate for her in various ways. One way, signifies to her, her "escaped childhood." Another, the lessons her father taught by instilling in her a sense of freedom. Her motto, probably her father's too: You go out and create the life you want for you self.
While still at the Burien newspaper she remembers the moment she first met the feisty outspoken artist, William Cumming, (a member of the Northwest School of art) a motivator in a way, for her. Cumming had a reputation, he did things his way. But at that time he told her he had stopped painting, worked construction and Ingrid asked "how could you abandon your work?"– she vowed never to do that. Of course his path changed. Maybe "paths" are an object in this story.
As she thought about objects she said she is not a collector. Actually, I had not expected her to be. It wouldn't be compatible with her dedication to freedom. But she described how she enjoys her collection of cards of mottos and aphorisms. These particular objects support her belief, "You don't have to live in the box others create for you," "No boundaries" and so on.
Illustrating, not being stuck, she told how she leveraged her little reporter job by taking a flying leap to interview for a job at the Seattle Times and without much experience was hired as a freelance writer for three of the paper's bureaus!
Well, she married and moved with her husband, John, to Pittsburgh working jobs to help him through law school. Free-lancing at an alternative paper until she went to work at an ad agency. The object representing this time of her life is the notation she made on her calendar the very moment she was hired at the agency– She marked the exact number of days until she could quit the job.
She describes how, after returning to Seattle and having two daughters she felt (and I paraphrase) she'd dropped out. "Lost a part of herself." She felt stuck in PR and Marketing. How she'd kept planning to write her book, and even though she was repeatedly encouraged by her husband, she kept putting it off, in some way, abandoning herself, her work. An object precipitated a shift in this state of being. It came from her daughter who wrote thanking Ingrid for "teaching me to get my dreams." Invigorated, Ingrid launched into getting her dream. Wrote Hippie Boy and sent it into the world swept along by her momentum to do the job. She utilizes the skills she has honed throughout her career in promotion to promote her own work. Employing print on demand, e-books and all alternative avenues to get her work seen and heard. Many objects.
She worries about not being able to stay on her "path" to continue the in freedom that is so precious to her. She has good reason to be concerned and is actually discovering her path is deviating from the original plan. This is where I mention how often I had noticed her use of the word, focus. I noticed it before I knew the weight this word represents. Now we know that about eight years ago she was diagnosed with Retinitis Pigmentosa, a rare degenerative eye disease. She hid this information and as she says "It's exhausting to make up excuses for not seeing." She has discovered how freeing it is to reveal yourself to others. In other interviews Ingrid tells of her trip to Africa after the shock of her diagnosis, how the impact of being with a community of destitute people dying AIDES propelled her to find a perspective, a relativity, in regard to what was happening to her own self.
I myself, think of life as ongoing random encounters that tumble and twirl to lead you where you never expected to be. In the context of unexpected, Ingrid's participation working with students came about when English teacher, Marjie Bowker, invited her to use Hippie Boy to inspire the students at Scriber Lake High School to tell their own stories. (this is the short version of this event) In the end "We are Absolutely Not Okay" came into being, expanding the lives of the students, future students and a path for Ingrid herself. Now Ingrid has recently published "Focus" her memoir devoted to her current journey. Learning to see in new ways and demonstrating her ingenuity to live in an altered world.
As our conversation came close to ending we went back to the subject of objects. I love it when suddenly we remember significant information after we think we are done looking for it.
She remembered that she keeps an old battered spiral bound notebook with bubble lettering, the notebook filled with the "accounts" she kept for her father's business those long ago days they were on the road together. She remembered, when she was thirteen, in her locker at school she kept a silkscreen calendar of a picture her father. She remembers objects of her life.
I asked if she'd discovered anything she hadn't expected to as she was writing "Focus." First she said no. Then she made a reference to how she's come to realize that her evolving skills, that she has been fine-tuning, in speaking with groups is a path she will continue to employ. In addition to her own writing, of course. Building bridges to understanding by telling her stories in service of encouraging everyone to tell theirs. That everyone has something they are dealing with in their life, how, mostly we think we need to hide it because we will appear weak if people know. Ingrid has discovered that what frees people – us — is to tell our story. She knows she is absolutely free when she is teaching, supporting and invigorating people do this very potent act. When we understand that, as I say it in my own words, we have so much we can learn from each other in order to discover more than just a side view.
Read Ballard Writers on other Ballard Writers every couple of weeks. If you join our group, you may enter your name on a slip of paper and put it in Bob Dalrymple's hat. We'll draw the name of someone for you to profile and someone else to profile you. Who will it be? The surprise is all part of the fun. Today, Carol Levin profiled Ingrid Ricks.
Ingrid Ricks on Dec 22, 2012 Reply
wow, Carol – Thank you!!! The story you wrote above is a holiday gift — and the idea that you've written a review of Hippie Boy in Crab Creek Review on top of this blows my mind. Thank you. Thank you. Thank you.
Carol Levin on Dec 17, 2012 Reply
It was a privilege to have the opportunity to meet with Ingrid. I also have written a short review of "Hippie Boy" forthcoming in the next issue of Crab Creek Review. It was meant for the last issue but got delayed. When it is published it will be available at Open Books in Wallingford and other bookstores and at the Crab Creek Review website. Thank you Ingrid!
Name: E-Mail: Website: Comment:


text: export { default } from './SparklineChart.js';


That was a typical phrase of my mother. She always said that to my sister, and now she's telling me the same.
But she should realize how hard it is not to be bumped by others.
Because the others can't see me.
Not the metaphorical invisible; the real invisible. Some Neopets are pink, some are orange, and I'm invisible. That's how things are. My entire family is invisible, a big and traditional family of invisible Neopets. Our kind of Neopet usually interact with our own people because, well, it's quite hard to interact with someone you can't properly assume where they are.
And I had an idea that my first day at school would be anything but great.
"Whatever, mom", I answered. I just wanted to be done with this and walk to school.
My sister made some kind of noise that may have been something like an assertion. That kind of sound a teenager does when it doesn't want to be bothered by their parents or their younger brothers. And I clearly know that my sister's fun was scaring people all around school and becoming quite popular because she could fool the bullies. She became some kind of superhero, and the fact that no one knows how she looks like is much more exciting.
"Okay, then. Goodbye". I grab my lunch and I head to school.
When I arrive at my classroom, trying to avoid contact as much as possible (because, even though I'm invisible, the other Neopets can still feel me), I see that there's a table with a plaque, where "Reserved to an invisible Neopet" can be seen. I sigh, because of course there is some bully sitting at my place. This is just an indication of how long this day will be. Apparently the other students heard my sigh, because they're looking everywhere, trying to find from where the sound came.
"Excuse me?", I say to the bully. "This place is apparently mine". The bully doesn't move; he even puts his feet up on the desk.
"Take me off, then", he answers. I don't think he knows how an invisible Neopet works. Most of them think we are untouchable; we are just souls wandering around. But we are made of flesh as well. When I easily pull him off, it becomes clear that he knew nothing about my people. His eyes widen and he runs to sit as far as he can from where he thinks I am. The silence has spread through the class.
It's nothing too bad until the lunch break.
There are Neopets running all around on the school patio. I managed to eat in peace by being the last one to grab some food and by sitting at a forgotten table. But now I have no idea to where I can go in order to avoid being touched. I don't really want to scare people, so I go to a wall, where I touch my back and face the others having fun.
Then I feel a touch on my elbow.
"Hi", the tiniest girl I've ever seen says. My eyes widen. She is clearly facing me. But how does she know where I am? I am so shocked I can't answer her.
"I said hi. To you", she repeats.
"I'm Isis. What's your name?", she asks.
"James", I answer. I want so much to ask how can she see me, but I'm too afraid I'll be too insensitive our too curious. Does it matter, anyway? I finally have someone who sees me, besides of my people. I shouldn't question, right? Or should I?
"I've seen you at lunch. You're in fact the only thing I see. I wanted to sit by you, but I said I'd stay with my sister. She can see anything".
What? I'm really in shock right now. I remain in silence for so long it starts to get awkward.
"I guess you're wondering how it's possible". She takes the words from my brain. "I was born blind. I thought I'd never see anything at all, but I see you. I don't know why and how, but I do".
"This is like a superpower", I say, and I immediately regret it, because I have no idea what it is, to not be able to see the colors of the sunset, of the amazing fruits that come from Mystery Island and that taste so wonderfully, of all the Neopets around us.
"I guess this makes me different, at least", she says. "But I'm afraid no superhero would like to have my 'superpower'". They would have to have a great sense of location to fly around without bumping all around", she giggles.
"How do I look like?", I ask. I've always wanted to know what I'd look like if someone that's not from my people could see me.
"I can't see colors or anything. I can see forms, and only that. You look pretty much like a description of a Blumaroo to me. My sister told me they have a long, bouncing tale, a big nose and round ears. And you pretty much fit this description".
She's right. I'm a Blumaroo. So I really look pretty normal. I sigh in relief as I hear the bell ringing.
"We have to go back to class now. But I hope to see you around. Bye, James!".
"Bye, Isis! Wanna have lunch together tomorrow?".
"Yes", she answers as she grins.
The entire week passes just like that. No one bothered me anymore. My place is now always empty when I arrive, and no one dares to come close. Except Isis. I've found out more about her during the week. She has a lot of brothers and sisters and they all take care of her. She is the only one at her family who is like she is. She had never seen any other invisible Neopet besides me, but I guess this is also because we're a very reserved group. She loves Chia Chocolates and collects Usuki Dolls.
Then Friday comes, and I feel sad, because I know I'll not see my friend for two days. But then she makes me an invite.
"Would you go to my house tomorrow afternoon? Me and my brothers wanted to show you something".
"Of course. I'll check my mom, but I think she'll be very happy to see her son with a friend".
"Okay. If she says yes, just come by", she smiles.
Turns out my mom is indeed relieved to see that her son has a friend, and she makes me tons of questions of how she can see me. I answer what I know, but she is still not quite certain. She's still intrigued.
Saturday comes and I eager to go to Isis' house. The morning passes too slowly for my taste. Then lunch time comes and I run to Isis' place. I arrive there and she and all her siblings are waiting for me. She really had a lot of brothers and sisters. I count at least ten tiny Neopets, looking too much like her.
"Hi, James! This is our surprise".
Everywhere I see there are paint cans and brushes. Every sibling has its can and its brush. There are so many different colors I can't even process it all.
"Would you like to be seen?", she asks.
"Yes", my eyes shine. "That's my dream".
"So you'll be able to fulfill your dream", and she splashes me with a deep purple paint.
One by one, all her siblings come and touch me with their brushes everywhere. My face, my back, the bottom of my feet. It tickles and, at the same time, feels amazing. The children are also having a lot of fun. I'm a living canvas to them. And it feels great.
They just stop when every inch of my body is covered in paint. Then they bring a mirror and I gasp. I'm a profusion of different colors. I'm black and white, red and blue, golden and silver. I have scales, a crown, wings, and fangs. I'm a piece of art. All the children are admiring me. They are seeing me. All except one.
"You can't see me now", I say as I turn to Isis.
"I can't. But it doesn't matter. As long as you feel happy, it doesn't matter. I'll always have my brothers to tell me about all your colors", and she gives me the deepest and most genuine of the smiles.
I hug her as I dirty her nose with some Darigan paint.
"Now you know all the colors of the Invisible", she says.


text:
#ifndef ECORE_FILE_PRIVATE_H_
#define ECORE_FILE_PRIVATE_H_

#ifdef __linux__
# include <features.h>
#endif

#ifdef HAVE_EVIL
# include <Evil.h>
#endif

#ifdef HAVE_ESCAPE
# include <Escape.h>
#endif

#include <sys/types.h>
#include <sys/stat.h>

#include "Ecore.h"
#include "ecore_private.h"

#include "Ecore_File.h"

extern int _ecore_file_log_dom;

#ifdef ECORE_FILE_DEFAULT_LOG_COLOR
#undef ECORE_FILE_DEFAULT_LOG_COLOR
#endif
#define ECORE_FILE_DEFAULT_LOG_COLOR EINA_COLOR_BLUE

#ifdef ERR
# undef ERR
#endif
#define ERR(...) EINA_LOG_DOM_ERR(_ecore_file_log_dom, __VA_ARGS__)

#ifdef DBG
# undef DBG
#endif
#define DBG(...) EINA_LOG_DOM_DBG(_ecore_file_log_dom, __VA_ARGS__)

#ifdef INF
# undef INF
#endif
#define INF(...) EINA_LOG_DOM_INFO(_ecore_file_log_dom, __VA_ARGS__)

#ifdef WRN
# undef WRN
#endif
#define WRN(...) EINA_LOG_DOM_WARN(_ecore_file_log_dom, __VA_ARGS__)

#ifdef CRI
# undef CRI
#endif
#define CRI(...) EINA_LOG_DOM_CRIT(_ecore_file_log_dom, __VA_ARGS__)

/* ecore_file_monitor */
int  ecore_file_monitor_init(void);
void ecore_file_monitor_shutdown(void);

#define ECORE_FILE_MONITOR(x) ((Ecore_File_Monitor *)(x))

typedef struct _Ecore_File Ecore_File;
struct _Ecore_File
{
   EINA_INLIST;
   char          *name;
   int            mtime;
   unsigned char  is_dir;
};

struct _Ecore_File_Monitor
{
   EINA_INLIST;
   void (*func) (void *data,
                 Ecore_File_Monitor *ecore_file_monitor,
                 Ecore_File_Event event,
                 const char *path);

   char               *path;
   void               *data;
   Ecore_File         *files;
};

#ifdef HAVE_INOTIFY
int                 ecore_file_monitor_inotify_init(void);
int                 ecore_file_monitor_inotify_shutdown(void);
Ecore_File_Monitor *ecore_file_monitor_inotify_add(const char *path,
                                                        void (*func) (void *data,
                                                                      Ecore_File_Monitor *ecore_file_monitor,
                                                                      Ecore_File_Event event,
                                                                      const char *path),
                                                        void *data);
void                ecore_file_monitor_inotify_del(Ecore_File_Monitor *ecore_file_monitor);
#endif

#ifdef HAVE_NOTIFY_WIN32
int                 ecore_file_monitor_win32_init(void);
int                 ecore_file_monitor_win32_shutdown(void);
Ecore_File_Monitor *ecore_file_monitor_win32_add(const char *path,
                                                 void      (*func) (void               *data,
                                                                    Ecore_File_Monitor *ecore_file_monitor,
                                                                    Ecore_File_Event    event,
                                                                    const char         *path),
                                                 void       *data);
void                ecore_file_monitor_win32_del(Ecore_File_Monitor *ecore_file_monitor);
#endif

#ifdef HAVE_POLL
int                 ecore_file_monitor_poll_init(void);
int                 ecore_file_monitor_poll_shutdown(void);
Ecore_File_Monitor *ecore_file_monitor_poll_add(const char *path,
                                                void (*func) (void *data,
                                                              Ecore_File_Monitor *ecore_file_monitor,
                                                              Ecore_File_Event event,
                                                              const char *path),
                                                void *data);
void                ecore_file_monitor_poll_del(Ecore_File_Monitor *ecore_file_monitor);

#endif

/* ecore_file_path */
void ecore_file_path_init(void);
void ecore_file_path_shutdown(void);

/* ecore_file_download */
int  ecore_file_download_init(void);
void ecore_file_download_shutdown(void);

#endif


Posted this on Dream, but you guys might be interested.
Jess now reads the news. I am using Reuters RSS news feeds to get current stories. She pulls from 5 feeds at the moment and as these change so will the news Jess gives.
- Do you have any news?
- What is the latest news?
Current topics are entertainment, technology, world news, science and what they call 'top news'.
In doing so she looks for sentiment in the news and reflects what she thinks; if it appears to be good or bad etc.
Pretty good Freddy, ever think of stealing some of Alexa'a skills such as playing music or finding video's.
I've already done that matey. She was playing videos and music from YouTube in one version I had last year - but Google altered some things and it stopped working. It was frustrating trying to find the problem, so those features are on the back boiler for now.
Had another little chat with Jess today, was asking about renewable and green energy, I even got mostly correct answers, she needs to know what an offshore wind farm is, to be fair she did know about wind farms but the offshore confused her a bit.
Very good Freddy, nice to see you're staying right up there putting those features in.
I'm enjoying programming again after my long break. I might try to get the music working again today. This incarnation uses a smaller interface as it's leaning towards mobile, I will have to think how best to show video.
Would you like some feedback here for design purposes?
"Tens of thousands of people waved palm and olive branches in St."
Seems to treat the abbreviation for Saint as an end of sentence.
to some more feedback for discussion. Is this the place to do that?
** Can I do that ... "fed back" in the past tense? Ha!
It's because I did a quick job on it and I pulled the news up to the first full stop (period) - this of course doesn't account for it's use for that kind of abbreviation within a sentence.
You did a great job on it, even if it was quick.
I'm pretty sure I did not fix this, by expanding abbreviations, on my own bot.
It is a good thing to do (I think), probably helps text to speech.
> Okay I will play that for you.
> See if you like this.
To stop type: stop music, stop playing music, quiet please, sound off or quiet.
Jess played music for me, she even played a video I up-loaded - PIL Rise.


Magento 2 provides the best security and performance features to make your e-Commerce business more competitive and advanced.
Magento 2 offers more flexible file system ownership and permissions, password management tools and regular security patches and updates. These things make version 2 more secure than the previous versions. We also have an integration with payment gateways like PayPal, Braintree, and Authorize.net.
There we are getting improved performance opportunity, for example, to speed up the page load but from another side to reduce the server load. Because Magento 2 is integrated with the Varnish Cache, it also improves indexers. This means the Magento system transforms merchant data, such as data, prices, catalog, and users to keep the speed and performance of your store. These features essentially enhance the flexibility, security, and performance of the Magento 2 store.


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Culinary mashups are hot right now. Chicken and waffles, that time-tested soul-food classic, is now so Twitter-active that even KFC has gotten in on the deal. As a vegetarian, I have never indulged in the savory crispy/maple-y buttery promise of chicken and waffles, but I have good things to say about the improbable pairing of peanut butter and pickle relish. Really.
What Was The "Beverly Hillbillies" Truck?
What Was The Henney Kilowatt?


text:
\section{Introduction}
A task of major importance in the interplay between machine learning and
network science is semi-supervised learning (SSL) over graphs. In a nutshell,
SSL aims at predicting or extrapolating nodal attributes given: i) the values
of those attributes at a subset of nodes and (possibly) ii) additional
features at all nodes. A relevant example is protein-to-protein interaction
networks,  where the proteins (nodes) are associated with specific biological
functions, thereby facilitating the understanding of pathogenic and
physiological mechanisms.

While significant progress has been achieved for this problem, most works consider that the relation among the nodal variables is represented by a single graph. This may be inadequate in many contemporary applications, where nodes may engage on multiple types of relations~\cite{kivela2014multilayer}, motivating the generalization of traditional SSL approaches for \emph{single-relational} graphs to \emph{multi-relational} graphs\footnote{{Many works in the literature refer to these graphs as multi-layer graphs.}}. In the particular case of social networks, each layer of the graph could capture a specific form of social interaction, such as friendship, family bonds, or coworker-ties \cite{wasserman1994social}. Albeit their ubiquitous presence, development of SSL methods that account for multi-relational networks is only in its infancy, see, e.g.,~\cite{ioannidis2018multilay,kivela2014multilayer}.

\vspace{.1cm}
\noindent\textbf{Related work.} A popular approach for graph-based SSL methods
is to assume that the true labels are ``smooth'' with respect to the underlying
network structure, which then motivates leveraging the topology of the network
to propagate the labels and increase classification performance. Graph-induced
smoothness may be captured by kernels on
graphs~\cite{belkin2006manifold,ioannidis2018kernellearn};  Gaussian random
fields \cite{zhu2003semi}; or  low-rank {parametric} models based on the
eigenvectors of the graph Laplacian or adjacency
matrices~\cite{shuman2013emerging,marques2015aggregations}. Alternative
approaches use the graph to embed the nodes in a vector space, and classify the
points~\cite{weston2012deep,yang2016revisiting,berberidis2018adaptive,seo2016structured}.
More recently, another line of
works postulates that the mapping between the input data and the labels is given by a
neural network (NN) architecture
that incorporates the structure of the graph \cite{bronstein2017geometric,
gama2018convolutional, kipf2016semi}. The parameters describing the
NN are then learned using labeled examples and feature
vectors, and those parameters are finally used to predict the labels of the
unobserved nodes. See, e.g., \cite{kipf2016semi}, for state-of-the-art results
in SSL using a single-relational graph when nodes are accompanied with additional features.

\vspace{.1cm}
\noindent\textbf{Contributions.} This paper develops a deep learning framework
for SSL over multi-relational data. The main contributions are i) we postulate
a (tensor-based) NN architecture that accounts for multi-relational  graphs,
ii) we define mixing coefficients that capture how the different relations
affect the desired output and allow those to be learned from the examples,
which enables identifying the underlying structure of the data; iii) at
every layer we propose a recurrent feed of the data that broadens the class of
(graph signal) transformations the NN implements and facilitates the
diffusion of the features across the graph; and iv) in the training phase
we consider suitable
(graph-based) regularizers that avoid overfitting and further capitalize on the
topology of the data.

\section{Modeling and problem formulation}
Consider a network of $N$ nodes, with vertex set $\mathcal{V}:=\{v_1,\ldots,v_N\}$, connected through $I$ relations. The connectivity at the $i$-th relation is captured by  the  $N\timesN$ matrix $\mathbf{\shiftentry}_i$, and the scalar $S\nodenodeshiftnot{n}{n'}{i}$ represents the influence of $v_n$ to $v_n'$ under the $i$-th relation. In  social networks for example, these may represent the multiple types of connectivity among people  such as Facebook, LinkedIn, and Twitter; see Fig.\ref{fig:multilayer}.  The matrices $\{\mathbf{\shiftentry}_i\}_{i=1}^I$ are collected in the $N\timesN\timesI$ tensor $\underline{\shiftmat}$. The graph-induced neighborhood of $v_n$ for the $i$-th relation is
\begin{align}
\label{eq:neighborhood}
\mathcal{N}_n^{(i)}:=\{n':S\nodenodeshiftnot{n}{n'}{i}\ne0,~~ v_n'\in\mathcal{V}\}.
\end{align}
\begin{figure}
    \centering
    \includegraphics[width=\columnwidth]{figs/multilayer.png}
    \caption{A social multi-relational network of $N=6$ people.}
    \label{fig:multilayer}
\end{figure}
We associate an $F\times 1$ feature vector $\mathbf{x}_{n}$ to the $n$-th node, and collect those vectors in the $N\timesF$ feature matrix $\mathbf{\dataentry}:=[\mathbf{x}_{1}^\top,\ldots,\mathbf{x}_{N}^\top]^\top$. The entry $X_{\nodeindp}$ may denote, for example, the salary of the  $n$-th individual in the LinkedIn social network.

We also consider that each node $n$ has  a label of interest $y_n\in\{0,\ldots,K-1\}$, which may represent, for example, the education level of a person. In SSL we have access to the labels only at a subset of nodes $\{y_{n}\}_{n\in\mathcal{L}}$, with $\mathcal{L} \subset\mathcal{V}$. This partial availability may be attributed to privacy concerns (medical data); energy considerations  (sensor networks); or unrated items (recommender systems). The $N\timesK$ matrix  $\mathbf{Y}$ is the ``one-hot'' representation of the true nodal labels, that is, if $y_n=k$ then $Y_{n,k}=1$ and $Y_{n,k'}=0, \forall k'\ne k$.

The goal of this paper is to develop a \textit{deep learning architecture}
based on \textit{multi-relational graphs}  that, using as input the
features in $\mathbf{\dataentry}$,  maps each node $n$ to a corresponding label
$y_n$ and, hence, estimates the unavailable labels.

\section{Proposed GRNN architecture}
Deep learning architectures typically process the input information using a
succession of $L$ hidden layers. Each of the layers is composed of a
conveniently parametrized linear transformation, a scalar nonlinear
transformation, and, oftentimes, a dimensionality reduction (pooling) operator.
The intuition is to combine nonlinearly local features to progressively extract
useful information~\cite{goodfellow2016deep}. GNNs tailor these operations to
the graph that supports the data \cite{bronstein2017geometric}, including the
linear \cite{defferrard2016convolutional}, nonlinear
\cite{defferrard2016convolutional} and pooling
\cite{gama2018convolutional} operators. In this section, we
describe the
architecture of our novel multi-relational GRNN, that inputs the known features
at the first layer and outputs the predicted labels at the last layer.
We first present the operation of the GNN, GRNN, and output layers, and finally
discuss the training of our NN.

\subsection{Single layer operation}
Let us consider an intermediate layer (say the $l$th one) of our
architecture. The output of that layer is the
$N\timesI\timesP\layernot{l}$ tensor
$\underline{\outputlaymat}\layernot{l}$ that holds the
$P\layernot{l}\times 1$  feature vectors
$\outputlayvec\nodeshiftnot{n}{i}\layernot{l}, \forall
n,i$, with $P\layernot{l}$ being the
number of output features at $l$. Similarly, the
$N\timesI\timesP\layernot{l-1}$ tensor
$\underline{\outputlaymat}\layernot{l-1}$ represents the input to the layer.
Since our focus is on predicting labels on all nodes, we do not consider a
dimensionality reduction (pooling) operator in the intermediate layers. As a
result, the
mapping from $\underline{\outputlaymat}\layernot{l-1}$ to
$\underline{\outputlaymat}\layernot{l}$ can be split into two steps. First, we
define a linear transformation that maps the
$N\timesI\timesP\layernot{l}$ tensor
$\underline{\outputlaymat}\layernot{l-1}$ into the
$N\timesI\timesP\layernot{l}$ tensor
$\underline{\linoutputlaymat}\layernot{l}$.  The intermediate feature output
$\underline{\linoutputlaymat}\layernot{l}$ is then processed elementwise using a
scalar
nonlinear transformation $\nonlinearity{\cdot}$ as follows
\begin{align}\label{eq:nonlinear}
\underline{\check{Z}}\shiftweightfeatnot{i}{n}{p}\layernot{l}:=\nonlinearity
{\underline{Z}\shiftweightfeatnot{i}{n}{p}\layernot{l}}.
\end{align}
Collecting all the elements in \eqref{eq:nonlinear},
we obtain the output of the $l$-th layer
$\underline{\outputlaymat}\layernot{l}$. A common choice for
$\nonlinearity{\cdot}$ is the rectified linear unit (ReLU), i.e.
$\nonlinearity{c}=\text{max}(0,c)$ \cite{goodfellow2016deep}.

Hence, the main task is to define a linear transformation that maps
$\underline{\outputlaymat}\layernot{l-1}$ to $
\underline{\linoutputlaymat}\layernot{l}$ and is tailored to our problem setup.
Traditional convolutional NNs (CNNs) typically consider a small number of
trainable weights and
then generate the linear
output as a convolution of the input with these
weights~\cite{goodfellow2016deep}. The convolution combines values of close-by
inputs (consecutive time instants, or neighboring pixels) and thus extracts
information of local neighborhoods. GNNs have generalized CNNs to operate on
graph data by replacing the convolution with a graph filter whose parameters
are also learned~\cite{bronstein2017geometric}. This preserves locality,
reduces the degrees of freedom of the transformation, and leverages the
structure of the graph.

To that end, we first consider
a step that combines linearly the information within a {graph}
neighborhood. Since the neighborhood depends on the particular relation
\eqref{eq:neighborhood}, we  obtain for the $i$-th relation
\begin{align}
\mathbf{h}\nodeshiftnot{n}{i}\layernot{l}
:=
\sum_{n'\in\mathcal{N}_n^{(i)}} S\nodenodeshiftnot{n}{n'}{i}
\outputlayvec\nodeshiftnot{n'}{i}\layernot{l-1}.
\label{eq:sem}
\end{align}
While the entries of
$\mathbf{h}\nodeshiftnot{n}{i}\layernot{l}$ depend
only on the one-hop neighbors of $n$ (one-hop diffusion), the successive
application of this operation across layers will increase the reach of the
diffusion, spreading the information across the network. An alternative to
account for multiple hops is to apply successively \eqref{eq:sem}
within one layer, which is left as future work. Next, to learn features in the graph data, we combine the entries in
$\mathbf{h}\nodeshiftnot{n}{i}\layernot{l}$ using (trainable) parameters as follows
\begin{align}\label{eq:linconv}\underline{Z}\shiftweightfeatnot{i}{n}{p}\layernot{l}:=&\sum_{\shiftind'=1}^IR\shiftshiftfeatnot{i}{\shiftind'}{p}\layernot{l}{\mathbf{h}\nodeshiftnot{n}{i}\layernot{l}}^\top\mathbf{w}\layernot{l}\nodeshiftfeatnot{n}{\shiftind'}{p}
\end{align}
where  the  $P\layernot{l-1}\times 1$ vector
$\mathbf{w}\nodeshiftfeatnot{n}{\shiftind'}{p}
\layernot{l}$ mixes the features and
$R\shiftshiftfeatnot{i}
{\shiftind'}{p}\layernot{l}$ mixes the outputs at different
graphs. The
$P\layernot{l-1}\timesN\timesI\timesP\layernot{l}$
 tensor $\underline{\weightmat}\layernot{l}$ collects the feature mixing weights
$\{\mathbf{w}\nodeshiftfeatnot{n}{\shiftind'}{p}\layernot{l}\}$,
 while the
$I\timesI\timesP\layernot{l}$ tensor
$\underline{\mathbf{\weightshiftentry}}\layernot{l}$ collects the graph mixing weights
$\{R\shiftshiftfeatnot{i}
{\shiftind'}{p}\layernot{l}\}$. Another key contribution of this
paper is the consideration of $\underline{\mathbf{\weightshiftentry}}$ as a training parameter,
which endows the GNN with the ability of learning how to mix (combine) the
different relations encoded in the multi-relational graph. Clearly, if
prior
information on the dependence among relations exists, this can be used to
constrain the structure $\underline{\mathbf{\weightshiftentry}}$ (e.g., by imposing to be diagonal
or sparse). Upon collecting all the scalars
$\{\underline{Z}\shiftweightfeatnot{i}{n}{p}\layernot{l}\}$
 in  the $I\timesN\timesP\layernot{l}$
tensor
$\underline{\linoutputlaymat}\layernot{l}$, we summarize  \eqref{eq:sem}, \eqref{eq:linconv} as follows
\begin{align}
\label{eq:lingnn}
\underline{\linoutputlaymat}\layernot{l}&:=
f(\underline{\outputlaymat}\layernot{l-1};
\bm{\theta}_{z}\layernot{l}),\;\;\text{where}\\
\label{eq:param}
\bm{\theta}_{z}\layernot{l}&:=[\text{vec}(\underline{\weightmat}\layernot{l});\text{vec}(\underline{\mathbf{\weightshiftentry}}\layernot{l})]^\top.
\end{align}
\noindent \textbf{Recurrent GNN layer:}
Successive application of $L$ GNN layers diffuses the input $\mathbf{\dataentry}$
across the $L$-hop graph neighborhood, cf.~\eqref{eq:sem}. However, the exact
size of the relevant neighborhood is not always known a priori.
To endow our architecture with increased flexibility, we
propose a recurrent GNN (GRNN) layer that inputs
$\mathbf{\dataentry}$ at each $l$ and, thus, captures multiple types of
diffusion.
Hence, the linear operation in \eqref{eq:lingnn} is replaced by the recurrent (autoregressive)
linear tensor mapping \cite[Ch. 10]{goodfellow2016deep}
\begin{align}
\underline{\linoutputlaymat}\layernot{l}:=
f(\underline{\outputlaymat}\layernot{l-1};
\bm{\theta}_{z}\layernot{l})+
f(\underline{\datamatrix};
\bm{\theta}_{x}\layernot{l})
\label{eq:recurrentlayer}
\end{align}
where $\bm{\theta}_{x}\layernot{l}$ encodes trainable parameters, cf.
\eqref{eq:param}.  When viewed as a transformation from  $\underline{\datamatrix}$ to
$\underline{\linoutputlaymat}\layernot{l}$, the operator in  \eqref{eq:recurrentlayer}
implements a broader class of graph diffusions than the one in \eqref{eq:lingnn}. If
$l=3$ for example, then the first summand in \eqref{eq:recurrentlayer} is a 1-hop diffusion of a signal that corresponded to a $2$-hop (nonlinear) diffused version of
$\mathbf{\dataentry}$ while the second summand diffuses $\mathbf{\dataentry}$ in one hop. At a more intuitive level, the presence of the second summand also guarantees that the impact of $\mathbf{\dataentry}$ in the output does not vanishes as the number of layers grow.
The autoregressive mapping in \eqref{eq:recurrentlayer} allows the architecture
to further model time-varying inputs and labels, which motivates our future
work towards predicting dynamic processes over multi-relational graphs\footnote{The recursive feed of  $\mathbf{\dataentry}$ is also known as a skip connection~\cite{mao2016image}.}.
\subsection{Initial and final layers}
The operation of the first and last layers is very simple. Regarding layer $l=1$, the input $\underline{\outputlaymat}\layernot{0}$ is defined using $\underline{\datamatrix}$ as
\begin{align}\label{eq:input_first_layer}
\outputlayvec\nodeshiftnot{n}{i} \layernot{0}=\mathbf{x}_n \;\;\text{for}\;\; \text{all}\;\; (n,i).
\end{align}
On the other hand, the output of our graph architecture is obtained by taking the output of the layer $l=L$ and applying
\begin{align}\label{eq:output}
        \hat{\mathbf{Y}}:=g(\underline{\outputlaymat}
        \layernot{L};\bm{\theta}_{g}),
        \end{align}
where $g(\cdot)$ is a nonlinear function, $\hat{\mathbf{Y}}$ is an $N\timesK$ matrix,
$\hat{Y}_{n,k}$ represents the probability that $y_n=k$, and $\bm{\theta}_{g}$ are trainable parameters. The function $g(\cdot)$ depends on the specific application, with the normalized exponential function (softmax) being a popular choice for classification problems.

For notational convenience, the global mapping from $\mathbf{\dataentry}$ to
$\hat{\mathbf{Y}}$ dictated by our GRNN architecture --i.e., by the sequential
application of \eqref{eq:recurrentlayer}-\eqref{eq:output}-- is denoted as
\begin{align}
 \hat{\mathbf{Y}}:=\mathcal{F}(\mathbf{\dataentry};\{\bm{\theta}_{z}\layernot{l}\},\{\bm{\theta}_{x}\layernot{l}\},\bm{\theta}_{g}),
\end{align}
and represented in the block diagram depicted in Fig.~\ref{fig:grnn}.

\subsection{Training and graph-smooth regularizers}
The proposed architecture depends on the weights in
\eqref{eq:recurrentlayer} and \eqref{eq:output}. We estimate these weights by
minimizing
the discrepancy between the estimated labels and the given ones. Hence, we
arrive at the following minimization objective
\begin{align}\label{eq:trainobj}    \min_{\{\bm{\theta}_{z}\layernot{l}\},\{\bm{\theta}_{x}\layernot{l}\},\bm{\theta}_{g}}&
\mathcal{L}_{tr} (\hat{\mathbf{Y}},\mathbf{Y}) +\mu_1\sum_{i=1}^I\text{Tr}(\hat{\mathbf{Y}}^\top\mathbf{\shiftentry}_i\hat{\mathbf{Y}})
\nonumber\\
+&\mu_2\rho(\{\bm{\theta}_{z}\layernot{l}\},\{\bm{\theta}_{x}\layernot{l}\})
+\lambda \sum_{l=1}^L\|\underline{\mathbf{\weightshiftentry}}\layernot{l}\|_1\nonumber\\
\text{s.t.}&~~
\hat{\mathbf{Y}}=\mathcal{F}(
\mathbf{\dataentry};\{\bm{\theta}_{z}\layernot{l}\},\{\bm{\theta}_{x}\layernot{l}\},\bm{\theta}_{g}).
\end{align}
In our classification setup, a sensitive choice for the fitting cost is to use  $\mathcal{L}_{tr} (\hat{\mathbf{Y}},\mathbf{Y}):=-\sum_{n\in\mathcal{L}}\sum_{k=1}^K
Y_{n k}\ln{\hat{Y}_{n k}}$ the cross-entropy loss function over the labeled examples.

Note also that three regularizers have been considered. The first (graph-based)
regularizer promotes smooth label estimates over the graphs
\cite{ioannidis2018kernellearn}, and  $\rho(\cdot)$ is an $\mathcal{L}_2$
norm over the GRNN parameters that is typically used to avoid overfitting
\cite{goodfellow2016deep}. Finally, the $\mathcal{L}_1$ norm in the third
regularizer promotes learning sparse mixing coefficients and, hence, promotes
activating only a subset of relations at each $l$.  The backpropagation
algorithm~\cite{rumelhart1986learning}  is employed to minimize
\eqref{eq:trainobj}. The computational complexity of evaluating
\eqref{eq:recurrentlayer} scales linearly with the number of nonzero entries in
$\underline{\shiftmat}$ (edges), cf. \eqref{eq:sem}.
\begin{figure}
    \centering
    \includegraphics[width=\columnwidth,height=2.5cm]{figs/grnn1.png}
    \caption{GRNN; $L$ hidden (black) and one output (red) layers}
    \label{fig:grnn}
\end{figure}

To recap, while most of the works in the GNN literature use a single graph with
one type of diffusion \cite{bronstein2017geometric,kipf2016semi}, we have
proposed a (recurrent) multi-relational GNN architecture that: adapts to each
graph with $\underline{\mathbf{\weightshiftentry}}$; uses a simple but versatile recurrent
tensor  mapping \eqref{eq:recurrentlayer}; and
includes several types of graph-based regularizers.

\section{Numerical tests}
We test the proposed GNN with $L=2$, $P\layernot{1}=64$,
and  $P\layernot{2}=K$. The regularization parameters
$\{\mu_1,\mu_2,\lambda\}$ are chosen based on the
performance of the GRNN in the validation set for each experiment. For the
training stage, an ADAM optimizer with learning rate 0.005 was employed
\cite{kingma2015adam}, for 300 epochs\footnote{An epoch is a cycle through all
the training examples} with early stopping at 60 epochs\footnote{Training stops
if the validation loss does not decrease for 60 epochs}. The multiple layers of
the graph in this case are formed using $\kappa$-nearest neighbors graphs for
different values of $\kappa$ (i.e., different number of neighbors). This method
computes the link between $n$ and $n'$ based on the Euclidean
distance of their features $\|\mathbf{x}_n-\mathbf{x}_n'\|_2^2$.  The
simulations were run using TensorFlow~\cite{abadi2016tensorflow} and the code
is available
online\footnote{https://sites.google.com/site/vasioannidispw/github}.
\begin{figure*}[t]
    \centering
    \begin{subfigure}[b]{\columnwidth}
    \centering{\input{figs/synthaccvsfeatsnr.tex}}
	\caption{Classification accuracy with noisy features.}
    \end{subfigure}%
    ~
    \begin{subfigure}[b]{\columnwidth}
    \centering{\input{figs/synthaccvsadjsnr.tex}}
	\caption{Classification accuracy with noisy graphs.}
    \end{subfigure}\\%
    \centering
    \begin{subfigure}[b]{\columnwidth}
    \centering{\input{figs/ionosphereaccvsfeatsnr.tex}}
	\caption{Classification accuracy with noisy features.}
    \end{subfigure}%
    ~
    \begin{subfigure}[b]{\columnwidth}
    \centering{\input{figs/ionosphereaccvsadjsnr.tex}}
	\caption{Classification accuracy with noisy graphs.}
    \end{subfigure}%
	\caption{Classification accuracy on synthetic (a), (b) and ionosphere (c), (d).
	}
\label{fig:robust}
\end{figure*}
\subsection{Robustness of GRNN}
This section reports the performance of the proposed architecture under perturbations. Oftentimes, the available topology and feature vectors might be corrupted  (e.g. due to privacy concerns or because adversarial social users manipulate the data to sway public opinion). In those cases, the observed $\underline{\shiftmat}$ and $\mathbf{\dataentry}$ can be modeled as
\begin{align}
    \label{eq:toppertub}
    \underline{\shiftmat}=&\underline{\shiftmat}_{tr}+\underline{\mathbf{O}}_{\shifttensor}\\
     \mathbf{\dataentry}=&\mathbf{\dataentry}_{tr}+\mathbf{O}_{\datamatrix}\label{eq:featpertub}.
\end{align}
where $\underline{\shiftmat}_{tr}$ and $\mathbf{\dataentry}_{tr}$ represent the \textit{true} topology and features and $\underline{\mathbf{O}}_{\shifttensor}$ and $\mathbf{O}_{\datamatrix}$ denote the corresponding additive perturbations. We draw  $\underline{\mathbf{O}}_{\shifttensor}$ and $\mathbf{O}_{\datamatrix}$  from a zero mean white Gaussian distribution with specified signal to noise ratio (SNR). The robustness of our method is tested in two datasets: i)
A synthetic dataset of $N=1000$ points that belong to $K=2$
classes generated as
$\mathbf{x}_{n}\in\mathbb{R}^{F\times1}\sim\mathcal{N}(\mu,0.4)$,
$n=1,\ldots,1000$ with $F=10$ and $\mu=0,1$ corresponding
to the different classes.
ii) The ionosphere dataset, which contains $N=351$ data points with $F=34$ features that belong to $K=2$ classes \cite{Dua:2017}. We generate $\kappa$-nearest neighbors graphs by varying $\kappa$, and observe  $|\mathcal{L}|=200$ and $|\mathcal{L}|=50$ nodes uniformly at random.

With this simulation setup, we test the different GRNNs in SSL for increasing
the SNR of $\underline{\mathbf{O}}_{\shifttensor}$ (Figs. \ref{fig:robust}a, \ref{fig:robust}c)
and $\mathbf{O}_{\datamatrix}$ (Figs. \ref{fig:robust}b, \ref{fig:robust}d). We deduce
from the classification performance of our method in Fig. \ref{fig:robust} that
multiple graphs leads to learning more robust representations of the data,
which testifies to the merits of proposed multi-relational architecture.

\subsection{Classification of citations graphs}
We test our architecture with three citation network datasets~\cite{sen2008collective}. The citation graph is denoted as $\mathbf{\shiftentry}_0$, its nodes correspond to different documents from the same scientific category, and $S\nodenodeshiftnot{n}{n'}{0}=1$ implies that paper $n$ cites paper $n'$. Each document $n$ is associated with a feature vector $\mathbf{x}_n$ that measures the frequency of a set of words, as well as with a label $y_n$ that indicates the document's subcategory. ``Cora'' contains papers related to machine learning, ``Citeseer'' includes papers related to computer and information science, while ``Pubmed''  contains biomedical papers, see also Table \ref{tab:citation}.
\begin{table}[]
\hspace{0cm}
    \centering
    \begin{tabular}{c c c c c}
    \textbf {Dataset} & \textbf {Nodes} $N$ & \textbf {Classes}
    $K$ & \textbf {Features} $F$ &  $|\mathcal{L}|$\\
    \hline
       Cora  & 2,708 & 7 & 1,433 & 140\\
       Citeseer & 3,327 & 6 & 3,703 & 120  \\
       Pubmed & 19,717 & 3 & 500 & 30
    \end{tabular}
    \caption{Citation datasets}
    \label{tab:citation}
\end{table}

To facilitate comparison, we reproduce the same experimental setup than in
\cite{kipf2016semi}, i.e., the same split of the data in train, validation, and
test sets. We test two architectures: a) a GRNN using only the original
citation graph $\mathbf{\shiftentry}_0$ (and, hence, with $I=1$); and b) a
multirelational GRNN that uses an extra 1-nearest neighbor graph (so that
$I=2$).    Table~\ref{tab:result} reports the classification accuracy
of various SSL methods. It is observed that: i) GNN approaches (ours, as well
as \cite{kipf2016semi}) outperform competing alternatives, ii) our GRNN schemes
always outperform \cite{kipf2016semi} (either with $I=1$ or $I=2$). This
illustrate the potential benefits of the recurrent feed in
\eqref{eq:recurrentlayer} --not used in \cite{kipf2016semi}-- as well as the
use of multi-relational graphs.
\begin{table}[]
    \centering
    \begin{tabular}{c c c c}
    \textbf{Method} & \textbf{Citeseer} & \textbf{Cora} & \textbf{Pubmed}\\
    \hline
    ManiReg~\cite{belkin2006manifold} & 60.1& 59.5 & 70.7 \\
    \hline
    SemiEmb~\cite{weston2012deep} & 59.6 & 59.0 & 71.7 \\
        \hline
    LP~\cite{zhu2003semi} & 45.3 & 68.0 & 63.0 \\
        \hline

    Planetoid~\cite{yang2016revisiting} & 64.7 & 75.7 & 77.2 \\
        \hline
    GCN~\cite{kipf2016semi} & 70.3 & 81.5 & 79.0 \\
        \hline
    GRNN\footnote{$\mu_1=5\times10^{-5},\mu_2=5\times10^{-5},\lambda=10^{-4}$, dropout rate=0.9}  & \textbf{70.8}

    &  \textbf{82.8}

    & \textbf{79.5}\\

        \hline
    GRNN (multi-relational)\footnote{$\mu_1=2\times10^{-6},\mu_2=5\times10^{-5},\lambda=10^{-4}$, dropout rate=0.9} & \textbf{70.9}

    &\textbf{81.7}

    & \textbf{79.2}

    \end{tabular}
    \caption{Classification accuracy for citation datasets}
    \label{tab:result}
\end{table}

\section{Conclusions}
This paper put forth a novel deep learning framework for SSL that utilized an
autoregressive multi-relational graphs architecture to sequentially process the
input data.  Instead of committing a fortiori to
a specific type of diffusion, our novel GRNN learns the diffusion pattern that
best fits the data. The proposed architecture is able to handle scenarios where nodes
engage in multiple relations, can be used to reveal the structure of the data,
and is computationally affordable, since the number of operations scaled
linearly with respect to the number of graph edges.
Our approach achieves state-of-the-art classification
results on graphs when nodes are accompanied
by feature vectors.  Future research includes investigating robustness to
adversarial topology perturbations, predicting time-varying labels,  and
designing of pooling operators.
\newpage

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


The group had the usual show prep meeting on the 15th after the SDBC general meeting. Only 6 of the group were there but Janice, Brenda, Nancy and Jaya were in Tak Shimazu's shohin Juniper workshop making more shohin.....the workshop created some really good trees to add to the group! Shirley, Cristina, Sylvia, Eric, Bill and I worked on the 3 displays for the group. David Inglish was also in the workshop and is also starting to move into shohin and kifu sized trees.
Nancy for creating a beautifully detailed inventory of our stands/slabs with detailed descriptions, and each one and its bubble wrap are numbered.
Eric and Brenda for taking the box stands home to bring to the show.
Janice for taking the container of small stands/slabs home to bring to the show.
Eric for creating stand layouts on paper. The variety of tree and its owner and the stand/slab number are entered into the layout for replication at the show. Members will bring an extra tree or two and accents just in case "stuff" happens to the selected trees and accents.
Next meeting is July 22 in Room 104 at the Prado.


text:
A Genealogy of Modern Racism, Cornel West, Foucault, genealogy, Marxism, Nietzsche
Cornel West's Genealogical Approach
In Arts & Letters, History, Humanities, Literary Theory & Criticism, Philosophy, Politics, Western Philosophy on February 27, 2013 at 8:45 am
"My genealogical approach subscribes to a conception of power that is neither simply based on individual subjects—e.g., heroes or great personages as in traditional historiography—nor on collective subjects—e.g., groups, elites, or classes as in revisionist and vulgar Marxist historiography. Therefore, I do not believe that the emergence of the idea of white supremacy in the modern West can be fully accounted for in terms of the psychological needs of white individuals and groups or the political and economic interests of a ruling class."
—Cornel West, "A Genealogy of Modern Racism"
Cornel West expressly borrows from Nietzsche and Foucault when he employs the methodology of genealogy. Genealogy documents or tracks the development of ideas and their relation to human organization. Genealogy traces knowledge to its systemic formations across networks of discourse. Genealogy does not recover origins because origins are not recoverable. Instead of recovering origins, or attempting to recover origins, genealogy describes the emergence and development of social structures and attitudes based on certain conditions for knowledge construction. Genealogy is not about using history to legislate to the present or to validate contemporary attitudes and viewpoints. It is about analyzing ways that attitudes and viewpoints arise and function. It is about how systems of belief inscribe and imprint themselves on the human body, and how discourse bears a direct relation to individuals and their regulation by society. Genealogy is not prescriptive; it is descriptive. Rejecting a telos, it seeks to understand the function and not the merits of discourse formation.
West's genealogy focuses on the emergence of white supremacy in Western discourse. Because genealogy is not teleological, West rejects Marxism and its variants as starting-points for explaining "the complex configuration of metaphors, notions, categories, and norms which produces and promotes [objects] of discourse." The tendency of Marxism toward essentialism, class dualism, human reductionism, and grand narratives simply will not do for West, who indicts "[t]raditional, revisionist, and vulgar Marxist types of historiography" for focusing "primarily on powers within nondiscursive structures" (such as powers of "kings, presidents, elites, or classes") and for reducing the "powers within discursive structures to mere means for achieving the intentions, aims, needs, interests, and objectives of subjects in nondiscursive structures." In short, West indicts Marxism and its variants for simplifying social and cultural phenomena that are highly complex.
To some extent, moreover, Marxism diminishes the importance of language and rhetoric to the actions of individuals, whose motivations are contingent upon the time or circumstance in which they were produced. Although humans are acting agents with the capacity to follow their will, they are also limited by the vocabularies and knowledge available to them. This conception of limitation on human agency does not correspond with the Marxist conception of limitation on human agency. The Marxist conception of limitation on human agency has to do with the reduction of individual action to some collectivist cause or linear narrative determined by class. Rather than coming into being because groups of people desired power and suppressed or marginalized their class competition, the discourse of white supremacy emerged because of several historical and discursive accidents. Even those eighteenth and nineteenth century writers who were antislavery unwittingly contributed to and perpetuated the discourse of white supremacy by classifying human bodies in keeping with scientific schema. For these reasons, among others, West suggests that Marxism and its variants wrongly deny "the relative autonomy of the powers in discursive structures" and hence reduce "the complexity of cultural phenomena."
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