text:
Journalist Of The Century
Shelton Hull
The recent controversy over creationism in Kansas prompted a trip to the video store, where I rented Inherit The Wind , a 1960s film based on the Scopes Monkey Trial. All the principal figures were fictionalized, I suppose in order to facilitate greater creative license. It stars Spencer Tracy, that lovable lush, as "Henry Drummond," based on famed attorney Clarence Darrow, who represented the teacher who taught his pupils Darwin's theory of evolution. (The teacher is played by Dick York, pre- Bewitched .) On the other side of the aisle sits Fredric Marsh, who plays "Matthew Harrison Bailey," based on William Jennings Bryan, three-time presidential loser and professional polemicist, who sought to argue (with the glittering loquaciousness so sorely lacking in modern discourse) that any curriculum that contradicts the history of man as laid out in the Book of Genesis is an affront to the name of God and a danger to the soul of man. The judge is played by Harry Morgan (later known as Col. Sherman Potter on M*A*S*H ), who always finds his way into good productions, which is why you don't see him on network television anymore. But my favorite character, "E. M. Hornbeck," is played by Gene Kelly — you may have seen his legendary duet with Paula Abdul in a Diet Coke commercial a few years ago. Hornbeck is my favorite character because he is based on the greatest newspaperman of all time, Henry Louis Mencken (1880-1956), whose book Minority Report is the namesake for the online column I write for Ink 19 (www.ink19.com/columns/). September 12 marked the 119th anniversary of his birth, so I thought I'd take a moment to define his place in the history of American journalism.
H. L. Mencken wasn't just good, he was outlandishly good in an era when the general quality of prose emanating from the pages of newspapers and magazines was significantly better than it is now. Our modern eyes sometimes confuse style with substance when it comes to journalism. Television has lowered the bar for content to the point that practically anyone who can conjugate a verb looks like a genius in contrast. Very few of the men and women who draw a salary in the industry today could cut it in Mencken's time, which was the first half of this century, back when the daily paper was the primary source of information for all Americans. The competition was fierce; most major cities had at least two dailies, who fought like bastards to push circulation levels above the other. In the meritocracy that mainstream journalism used to be, the only way to win was to be a better paper, and so there were no arbitrary standards of qualification that ruled out candidates a priori based on superficial criteria.
For example, I think I'm a fairly decent writer, and certainly better than those at my local paper, but I will never be allowed to write for the local paper — or even to interview for the lowliest position on staff — because I don't have a college degree. (I'm not being self-serving; I merely use anecdotal evidence to support my thesis. Plenty of others have similar problems.) As much as this fact sucks for me, it's worse for them, because the daily paper is slowly marching to the graveyard of antiquated ideas. Dailies have been dying off steadily over the past decade, and the most immediate result (which in turn becomes a cause) is that the survivors find themselves without any competition. A media monopoly is great for the bottom line, unless your idea of a bottom line is having a paper you can be proud of.
Mencken was 19 when he first applied for work at the Baltimore Morning Herald ; he was rejected, but later hired after returning to the office every day for a month. You won't find any 19 year-olds on the staff of any "serious" publication today, even if the publication's target audience is 19 year-olds, unless their presence is some sort of gimmick meant to appeal to the demographic that advertisers cherish. ( Ink 19 ran my first concert review when I was 17, bless their forward-thinking little hearts. Who knows where I'd be now without that early bit of validation.) Many of my favorite journalists began their careers as unschooled novices, men like Hunter S. Thompson and Jimmy Breslin. They came up in an era when editors were willing to gamble with a few column inches if it meant nurturing young talent that could make their publication better than the next one. Within five years, Mencken was managing editor of the Morning Herald , which folded (through no fault of his own) in 1906.
"Precocious" soon gives way to "prodigious" when assessing HLM's work, which continued unabated until a cerebral thrombosis in 1948 left him virtually paralyzed for the last eight years of his life. (I'm not sure whether the stroke was brought on by Truman's reelection, but it's possible.) Following the demise of the Morning Herald , Mencken moved to the Evening Sun, where in 1911 he began a column called the Free Lance that lasted through '15. He also posted weekly editorials from 1919-41. In 1908 he became a literary critic for Robert Jean Nathan's The Smart Set , often reading as many as 30 books per month before becoming co-editor in 1914. He founded his own magazine, American Mercury , in 1924, which lasted until 1933. In his editorial capacity Mencken helped to establish and legitimize numerous writers, including Theodore Dreiser, F. Scott Fitzgerald, John Fante and Ernest Hemingway. And he contributed reviews, articles, etc. to over 20 other publications than those listed above. He was a man who lived to work and worked to live, who wrote in 1942 that "I edited both newspapers and magazines, some of them successes and some of them not, and got a close, confidential view of the manner in which opinion is formulated and merchanted on this earth." Unlike most of those who call the shots in today's journalism industry, who seem to exist in fat, contented, blissful ignorance of duty and obeisance to advertisers, Mencken understood and relished in his responsibility to the American people.
All you writers out there, especially journalists, consider this: you are going to die, hopefully no time soon, but eventually. And at that moment you shall cease to be Modern. The appeal of modernity is the implication of a future; the modern writer will be modern tomorrow, and will thus be able to maintain or increase his or her position in the industry through words yet to be written. But when you die, you immediately become part of history, one more name in a long list of dead writers. Your legacy will depend on the choices of people who haven't been born yet, whose parents haven't even been born yet. You see, there are only two reasons to read journalism, the writer and the subject. One may be a fan of a writer and seek out his work, or one may be interested in a particular subject and seek out articles relevant to the topic. In the latter case, say you're looking for information on, I don't know, the Scopes Monkey Trial? That was big news at the time, with far-reaching implications for the future, and a lot of different writers were either on hand to cover it or at home writing op-ed pieces. We may safely assume that at least 100 different writers wrote something about the trial, but how many can we name other than H. L. Mencken? How many others' commentaries are even in print anymore? Now, we alt. journalists are lucky in that we gravitate toward stories that have been ignored or de-emphasized by the mainstream press, but still you can be certain that you are not alone in covering anything that is truly important. And that's good. Most of your peers will be forgotten within a generation of their death, because history filters out mediocrity in quite systematic fashion.
Mencken and his contemporaries understood this, so each worked hard to forge his own unique style, and the stories that passed through their typewriters bore an unmistakable imprimatur. To read any of Mencken's 30 books is to step through a portal into the past, a past recorded with vivid language and impeccable logic and precision. Events that have long since ceased to have any real importance to modern life become, by virtue of HLM's interest, essential documents. Just yesterday I was reading "The Land of the Free," a piece about the collusion between the police and post office to censor a newspaper critical of the Fascist government in Italy. (You canread it yourself) Seems the Italian Ambassador to the US pulled some strings and, lo and behold, the paper's publisher gets a year in prison for running an ad for a book on birth control. This story would have never passed my eyes if not for my Mencken fetish, but it is now the oldest case of state-sponsored press suppression that I know of. "What becomes of the old notion that the United States is a free country, that it is the refuge for the oppressed of other lands, that here they may voice their grievances and call for help?" asks Mencken, and the question is just as important today as it was when he wrote it, in 1925. In the hands of a master, the past is history, history is historical.
On its face, writing is a very simple act. 26 letters and some punctuation marks, arranged in a specific order intended to transfer a thought from writer to reader. But because the act is simple doesn't mean one must strive for simplification. The print media has sought to simplify its prose in an effort to reach a larger portion of an audience that has been splintered by the more immediate medium of television, which presents a direct visual image to the viewer, freeing him of the burden of creative visualization that is necessary in reading. This "low-brow" approach is anything but altruistic, for the result is watered-down content and a narrower range of debate. Certain concepts that Americans need to consider in order to fully access the world around them are not presented to them because the nut of interpretation cannot fit within the format of choice. For example, the "unrest" in East Timor is just another case of foreigners going crazy, in the minds of mainstream media victims. Any cursory glance at Z (www.zmag.org) or other alternative media reveals enough information to really understand what is going on. The entire situation can be explained to anyone in under five minutes, providing that one can dig phrases like "client state," "unworthy victims," and "plausible deniability." If one cannot, the five minutes bloats to twenty or more. It seems to me that the media would prefer to keep the collective intellect below what is needed to generate true mass lucidity, and this allows them to slack, to devote a whole day or week of coverage to other stories that are of negligible importance.
What Mencken brought to the table was a mastery of the technical and stylistic aspects of writing that I have not seen before or since in the journalism business. It's been noted that Mencken never cut corners when it came to the work. He saw America as being a permanent battleground between Aristocrats and the Booboisie. His Aristocrat was an enlightened man, and the Booboisie were not. Many have taken his vernacular as proof that HLM was some kind of snob who thought himself better than others, and that's untrue; he merely realized that he was luckier than most because his job put him in a position where he had to look at things from multiple angles. What separated the Aristocrat and Booboisie was access to information and their willingness to embrace it. His early work predates women's suffrage (which was granted in 1920), and he died just as Martin Luther King was beginning the civil rights campaign, but I think he would have approved of and endorsed this stuff, for the central thesis of his work was that man should push ever harder to take control of his life by making informed decisions. His writing was ammo for Aristocrats.
"Booboisie" is my favorite example of HLM's invented vernacular. I find it interesting that a man as well-read as he (who wrote a book on Nietzsche in 1905, only five years after he died) needed to make up a word in order to express himself with optimum clarity. For his purpose was not to glorify his own intelligence; that would be a gratuitous waste of space. What he meant, I believe, was that these people were neglecting their potential. A lot of people like to have the truth handed to them, which works well for politicians and unsavory media types who happily exploit their trust for personal gain. To rest on the truth as imparted by some politician was to rest on a bed of broken glass: laying down is much easier than trying to get back up. "A creative artist always comes to ruin when he begins to defend the reigning demagogues," he said, thus implicating many of his colleagues, who were (and still are) only too eager to attach themselves to the reigning ideology of the time. So the Booboisie were those who would not or could not think beyond the pre-set boundaries of two-dimensional debate. Among them, those restricted by lack of education or other mitigating circumstances were deemed merely unfortunate; his most seething contempt was saved for the well-educated, well-fed, upper-class dogmatists who chose self-perpetuation over raising the consciousness of those they'd rather bleed for money and votes.
H. L. Mencken is often cited as an original Libertarian thinker, and that makes sense to me. But Libertarianism has been so misrepresented by the two-party mentality that we might want to revisit the idea. We commonly think of Libertarians as the "legalize everything" party. By that standard, it's no wonder that nobody votes for them. Libertarian theory assumes that all citizens are capable of making informed decisions about their bodies and bankroll. But we have bred a culture where this is not the case; if told one day "Everything's legal! Do what the hell you want!" lots of people would be hopelessly confused. We're lucky. If we want to know something, we look for the answers, and eventually find them. Others don't know where to look. The Internet, as important as it has been in balancing the news, is not the waterfall of opportunity it is alleged to be, because most of those who most need information have neither access nor the inclination. Of course, the best thing is the library, but who goes to the library? I am constantly amazed when I see people who don't read. I always wish I had some Mencken in my bag to give them. He had ample reserves of both style and substance, neither of which pops up often today.
Six Finger Satellite
Review by Charles D.J. Deppner
Rick Bain and the Genius Position
Crooked Autumn Sun (Official). Review by Daniel Gill.
Extra Virgin (RCA). Review by Phil Bailey
Julian Schnabel directs this true story of a successful French magazine editor, Jean-Dominque Bauby, who was struck with a paralyzing condition that leaves the afflicted with all his mental faculties, but unable to talk or move. Through the use of one good eye, a brilliant therapist, and patient transcriptionist, Bauby was able to create the book upon which the film is based. S D Green is suitably awed.
Malediction (Checkered Past). Review by Matthew Moyer
UK Subs / National Razor F.D.I.C.
Gruesome Twosome Vol. 1 (VMS). Review by Brian Kruger.
943 Recluse (Recordhead / Mr. Whiggs). Review by Stein Haukland.
Light In Motion (self-released). Review by Andrew Ellis.
Beach House lull a sold-out Chicago crowd into a pleasurable trance before sending them home to conjugate their shared ecstasy.
Gainesville Summer Music Showcase
The Gainesville Summer Music Showcase, featuring Doug Jordan, Red Lester, Future Legend, Ithaca, Argentina, Pop Canon, the Mercury Program, Squeaky, Szechwan Pork, the Bill Perry Orchestra, Flight 121, Spike the Cat, Shermy D, Slow Motion Milkshake, Loyal Frisby, Slack Season, Noah's Red Tattoo, As Friends Rust, and Grain, at various venues throughout Gainesville FL, July 28-29, 2000. Event review by Brian Kruger.
Papa M
Event Review by J. Tritten
Take Off Your Pants and Jacket (MCA). Review by Julio Diaz.


My friend Trish just posted this link on my wall for fun!
Ever get stuck with what to do with that gorgeous scarf you bought on sale? Or that one you got for Christmas from a friend..? Going to a party and you know that friend will be there…and you're thinking you should probably be wearing 'that' scarf…but you have no idea what to do or how to tie it?
This is so what I need to watch right now! I have a scarf on and have no idea what to do with it!
Great! Pick a knot! ANNNYYY knot! You are so set now!
I've always thought I was a "scarf" person, but can never figure out how to wear them. So, THANK YOU!
P.S. I've missed out bantering since I fell in a rabbit hole. I'm back, though!
Hi Kiah! I totally feel the same way..I love scarves..but only ever have one way to tie them!
and um. P.S to YOU….YOU FELL IN A RABBIT HOLE??! Geeeezpers I'm SO glad you are ok!!! 😉 Glad you're back!
i love scarves!! this video is so fun!
It IS fun!! and the best part..we are getting into scarf weather!


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text:
Gallowsnovel 《Release that Witch》 – Chapter 1287 Uneasiness beef undress read-p1
Fantasticnovel Release that Witch novel – Chapter 1287 Uneasiness name vigorous recommend-p1
don't be so proud of this technological terror
Chapter 1287 Uneasiness roomy tender
Boys' Book of Model Boats
Chapter 1246: The s.h.i.+p south
No sooner had he finished than Mick Kinley threw himself toward him.
Having said that, there were clearly over one thousand folks for the port.
If the was what actually transpired within the Sedimentation Bay every day, they then would want a substantial number of metal dishes! It was subsequently unimaginable how many resources and the length of time they would have to spread an iron dish similar to this to each individual refugee. It will probably still not sufficient whether or not they summoned all the blacksmith inside the Empire of Wolfheart.
A Graycastle soldier acquired Manfeld. Most of the clerks were definitely sporting the exact same uniform, thus it was straightforward to differentiate them.
"Properly… that's it?"
Manfeld soon uncovered the sign up desk based on the information available from the coachman. In reality, a banner ad was put up over that area, which captivated lots of pa.s.sers-by.
"Manfeld Castein," Manfeld p.r.o.nounced his reputation for the next time. He pointed out that the moment he announced his identify, anticipation in the ladies' view faded out, and they also quit having difficulties.
"Ident.i.ty? Any illegal documents? What's your competence?"
Nevertheless, he failed to feel totally frustrated about the absence of admiration while he have that simply because that he believed this was the right move to make.
If the was what happened within the Sedimentation Bay every single day, they then would want hundreds of thousands of metal dishes! It was actually unimaginable what number of sources and the length of time they will have to disperse an steel plate similar to this to every one refugee. It would probably still inadequate regardless of whether they summoned all the blacksmith in the Kingdom of Wolfheart.
Having said that, he did not feel very discouraged about the possible lack of admiration because he managed that simply because that they believed it was the proper course of action.
Mick Kinley's servants got apparently also acquired proper coaching. Manfeld was soon impaled during the compact, small safe-keeping space. Mick Kinley kicked his bruised encounter.
Mick Kinley slammed the entrance behind him, as well as after that minute, the 3 impaled had been remaining alone during the stuffy storage room.
"Free up them," Manfeld mentioned intensely.
Also, the getting on pa.s.s was really a minor weird way too. It turned out an iron plate, which has a rope connected to an individual end to ensure that he could actually use it similar to a diamond necklace. There were a few engraved symbols and phone numbers over the plate. It is going to not price much to generate this sort of little plate, but it may be an alternative history if every refugee obtained this kind of plate.
He did not expect to see a comfortable confront right here. The center-aged n.o.ble whom he had attained in the trainer was position within the storage place while his two servants were definitely aiming to propel two girls down to the floor and tie up them up. The gals ended up gagged. Inarticulate groans escaped from their lips. Apparently, these folks were moved right here by pressure.
"Huh?" Mick Kinley squinted and mentioned, "Are you from the freaking brain? Are you aware who they really are? They're slaves! And G.o.d knows how many many people have made use of them. I'm very surprised that we discovered both these little things around the s.h.i.+p. There's no reason at all that their master would permit them to go. So, now, it's quite easy. They escaped from their master. You still want to help save them?"
The speech seemed to be from the ending with the hall.
"Generate them," Manfeld stated seriously.
Chapter 1246: The s.h.i.+p to the South
"Castein? I've never come across this label," the middle-old mankind explained while shrugging. "But you're lucky. As you emerged below, I'll kindly discuss the women to you, but you'll have got to put it off."
"You should have observed what those Graycasle males claimed. The Wimbledons has abolished slavery. Hence, as soon as they boarded s.h.i.+p, these people were not slaves," Manfeld was adamant defiantly. "And don't you forget about that there's an extra testing once we get off the s.h.i.+p. They'll ask you whether you might have criminal data. When I tell you exactly what you performed in the s.h.i.+p to these two girls, do you reckon Graycastle gentlemen would let you go?"
zhen hun jie characters
"… What's your factor?" Mick Kinley snarled.
"What would you like to do generally if i require?" Mick Kinley reported through his clenched the teeth.
On the other hand, he failed to feel very frustrated about the possible lack of gratitude as he do that simply because that he imagined this was the right move to make.
"Relieve them," Manfeld stated very much.
Mick Kinley slammed the entrance behind him, as well as the up coming instant, three of the impaled have been remaining alone from the stuffy storage containers place.
patient observer jobs
Manfeld soon identified the subscription work desk dependant upon the information supplied by the coachman. The fact is, a banner was installed over that location, which captivated several pa.s.sers-by.
A Graycastle soldier obtained Manfeld. All the clerks were definitely sporting a similar uniform, so it was an easy task to distinguish them.
Manfeld soon uncovered the registration table in line with the details provided by the coachman. Actually, a banner ad was put up in excess of that location, which drawn numerous pa.s.sers-by.
"Nicely… that's it?"
The voice appeared to be from the end from the hallway.
"… What's your stage?" Mick Kinley snarled.

redpajama_set_name: RedPajamaCommonCrawl


text:
Lions in Focus: Adam Swierzbiolek
in Featured Stories, Latest News
As a young boy Adam Swierzbiolek wasn't brought up with Australian Rules Football.
Having parents of German and Polish backgrounds as well as having Greek and Italian friends, Swierzbiolek was influenced into choosing soccer as his preferred childhood sport until his early teens.
'I tried AusKickwhen I was younger but didn't like it and went with soccer,' Swierzbiolek said.
'I wasn't really into contact sports which made me appreciate soccer a bit more and a lot of my friends (mostly Greek and Italian) played soccer so I drifted towards that.'
It's quite ironic that now in his mid twenties he is playing in the Victorian Football League with the Coburg Lions as a ruckman, arguably the most physical player in the game and is loving eve
ry minute of it.
'I've grown fonder of playing in the ruck as I've got older and definitely like the contact now,' Swierzbiolek said.
Swierzbiolek continued playing junior and senior level soccer with the Waverly Wanderers until he was 15 years old when he then put all his attention into his schooling. By chance his first genuine experience of playing football was in year 12 where he filled in as the ruckman for his school and did quite well. After that Swierzbiolek never looked back.
'A few mates down at Waverly Blues in the Eastern Football League (EFL) said for me to come down after year 12 and play football there. I ended up playing for them for a few years (2013-2017),' Swierzbiolek said.
From there, Swierzbiolek's coach at the Waverly Blues; Ben Carbone directed him to Marcus Buzaglo the head coach of East Ringwood Football Club who were competitors in EFL Division One last year.
Swierzbiolek signed with East Ringwood in November 2017 and started preparing for the 2018 season. Fate would have it that he got in contact with Sebastian "Seb" Spagnuolo, the General Manager of the Coburg Football Club in the VFL and tried out for the team.
'I worked pretty hard and then got on the list fortunately enough,' Swierzbiolek said.
He played eight games in his maiden Division One season as well as combining duties with the Coburg Football Club debuting for the Lions in May against Williamstown before playing a further five matches in his first year in the VFL.
Unfortunately East Ringwood was relegated from Division One for the first time since 1973 leaving Swierzbiolek unsure of his next move.
Clubs in EFL Division One and Two sought out the talented big man but Swierzbiolek knew that to progress his career he had to push on and strive for bigger things.
'I was with East Ringwood last year and played a few games there; but they got relegated for this season so I sort of wanted to challenge myself,' Swierzbiolek said.
'I wanted to play against better ruckman then EFL Division Two would allow me to so I looked at changing leagues.'
Originally seeking opportunities at Division One clubs in Northern Football League for the 2019 season, Swierzbiolek's path took a turn in a different direction.
'I looked at the Northern Football League and got in contact with "Seb" and he put me onto Christian Stagliano the coach at Macleod. I met up with him and liked the vibe and pretty much signed straight away,' he said.
Swierzbiolek too had made a strong impact in his first season with Coburg that he was given a contract for the 2019 season.
'When I got this opportunity my parents said to me "Push yourself really hard, not many people get this opportunity, take it with both hands".'
'Anything I do they're always there caring, always at games watching me play. As a kid they encouraged whatever I was into, didn't force me into doing anything I didn't want to do. I probably couldn't have asked for any more supportive parents.'
Now in his second year at the Coburg Football Club, the man known by his friends and teammates as "Swizz" is enjoying his time and has embraced what Coburg is all about.
'I just like that it's stand-alone and that it has a real club feel to it. Everyone cares about each other and looks at each other as an equal,' Swierzbiolek said.
'Everyone feels like that we all support each other and know that we're going to have their backs come the weekend. There is really good friendship and mateship that goes on here.'
As well as playing for Coburg in the VFL, the 24 year old from Mulgrave works as a carpenter five days a week and if there is time available on the weekend, "Swizz" too takes that onboard.
'I'm pretty much flat out with work. I'm a chippy and I work five days a week. I do a few cash jobs on the weekend if I've got time,' Swierzbiolek said.
'Between footy and work there isn't much time for other things….I did architecture at school, I liked my design, always liked woodwork and could draw. I did year 12 and got a pretty good score and got into an architecture course.'
Ultimately Swierzbiolek realised that he preferred the hands on approach and undertook and apprenticeship with Warwick Constructions in Hawthorn East. Currently he is now working with Kingdom Constructions in Heidelberg West.
'I enjoyed the carpentry apprenticeship, stuck with that and haven't looked back,' Swierzbiolek said.
Having only played the game since 2013, Swierzbiolek has come a long way in such a short amount of time, moving from Waverly Blues Under 19s to playing for the senior team in Division Two within his second season. He is putting no limitations on how far he can still go.
'Once I joined the Waverly Blues after year 12 I just played with mates and had fun. I guess I developed fairly quickly from where I used to be (playing soccer) and then I suppose a few people believed that I could play at a higher level,' Swierzbiolek said.
'It flowed on from there going from Division One and now VFL. I had no idea what I could achieve but I'm here now and it has got me more determined than ever to see what level I can play. Keep focused and trying and see where it gets me.'
With AFL clubs expanding their views on state league clubs, the upcoming mid-season draft is an opportunity for many footballers like "Swizz" who harbours ambition of one day getting drafted into the AFL.
'I still need to learn a lot but I wouldn't be here if I didn't want to push for that. You never know what can happen,' Swierzbiolek said.
With the departure of captain and ruckman Tom Goodwin to Port Melbourne, Swierzbiolek has taken his opportunity with both hands establishing himself as Coburg's number one ruckman. So far this season Swierzbiolek has played in all five fixtures and is averaging 19 hit outs and 10 disposals per game.
'This year I've been given the opportunity to be the number one ruckman, so it's worked out in my favour,' Swierzbiolek said.
If he isn't able to achieve his goal of playing in the AFL, Swierzbiolek hopes to one day open up his own carpentry business.
'It would be awesome if I could get into the AFL but if it's not to be than I'd like to be successful in carpentry and hopefully run my own show. I want to be in charge of a business.'
At the conclusion of the VFL season Swierzbiolek prefers to spend his time travelling.
'I like to holiday when the season is over. I went to Japan last year, which was pretty good. I'm going to America later this year, I've never been there and I'm looking forward to it.'
A huge UFC fan and other sports, "Swizz" describes himself as a 'persistent, hardworking' and 'honest' individual and tries to live with having a selfless attitude.
'It's really important, you can treat people all the same and be really selfless, allow other people opportunities and it will come back to you. What goes around comes around.'
BY NICHOLAS GALEA
tags: Adam Swierzbiolek
Local League Lions Round 5
100 YEARS OLD AND STILL ROARING FOR THE LIONS


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Search for tag: "mass"
Why Study Online Churches with Tim Hutchings
Dr Tim Hutchings describes his research into the new phenomenon of on-line churches and, with Thomas O'Loughlin, discusses what this phenomenon means for the traditional understanding of…
university of notting
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From Simon Barnett on April 2nd, 2020 0 0 likes | 3 3 plays | 0
Why Study the act of Cremation with Kevin…
Why Study the act of Cremation with Kevin McGinnell
Dealing with the body of someone who has died – generically referred to as 'disposal' – is a crucial intersection of social custom, religious practices, human ritual,…
mcginnell
From Simon Barnett on April 3rd, 2017 0 0 likes | 6 6 plays | 0
Objects of Belief; The Table
Tables are a part of everyday life, but they also have significance in many religious rituals which are connected with food / eating. Here Prof. Tom O'Loughlin looks at a range of meanings…
objects of belief
frances knight
poterion
letters of paul
From Simon Barnett on January 17th, 2017 0 0 likes | 9 9 plays | 0
Objects of Belief; The Cup with Tom…
Objects of Belief; The Cup with Tom O'Loughlin
The Eucharist is a central ritual of Christians, and a central to that ritual is the use of a cup of wine for which thanks have been offered to God. But what is often forgotten is that in this…
concomitance
ardagh
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From Simon Barnett on January 6th, 2017 0 0 likes | 20 20 plays | 0
A-Z of Theology; E is for Eucharist
Professor Tom O'Loughlin points out a complexity in the use of the word 'eucharist.' It is usually thought of as just a technical name for a ritual – the ritual practiced…
thomas o'loughlin
a2zoftheology
From Simon Barnett on January 12th, 2016 0 0 likes | 11 11 plays | 0
Why Study the 4th Council of the Lateran with…
Why Study the 4th Council of the Lateran with Claire Taylor
2015 is the eighth centenary of Lateran IV – often described as the most important western church council between the Council of Nicea (325) and the Reformation. Dr Claire Taylor of the Dept of…
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From Simon Barnett on March 31st, 2015 0 0 likes | 6 6 plays | 0
Why Study Heresy in the Later Middle Ages with…
Why Study Heresy in the Later Middle Ages with Rob Lutton
Dr. Rob Lutton introduces the value to the historian of studying groups and individuals who were given the label of 'heretics' in the later middle ages. These groups point to diversity in…
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heterodoxy
wyclif
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catharism.
From Simon Barnett on May 6th, 2014 0 0 likes | 60 60 plays | 0


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Streetlife Festival und Corso Leopold
Streetlife Festival and Corso Leopold
Car-free zone with lots of music and cabaret
Two times a year, Leopoldstrasse and Ludwigstrasse are transformed into huge pedestrian zones. The booming cars that usually pass through the city are replaced by a vibrant party strip that attracts hundreds of thousands of visitors to Schwabing. And the street festival gets more opulent every year.
e.pascoe@corso-leopold.de
Leopoldstrasse and Ludwigstrasse in Schwabing have been turned into a mile of excitement and adventure for two weekends a year since the year 2000. The street festival takes place once in spring and once again in autumn; it's said to be one of the biggest of its kind in Europe. Strictly speaking, these two street festivals actually emerged separately, and the original focus was not only on celebrating, but also on idealism.
The Corso Leopold stretches from the Siegestor to the Münchner Freiheit square and dates back to an idea from 1994 that was inspired by cheering football fans who had turned Leopoldstrasse into a party street. One year later, on 21 May 1995, thousands of people strolled down the middle of the road from the Münchner Freiheit square to Odeonsplatz. The motto of the self-proclaimed "Corsaren" was "Hit the road!". The thought behind this was that the streets didn't just belong to the cars! The people behind Corso Leopold wanted to make it possible to walk along Leopoldstrasse without cars for two days. But it's not that easy to block a road in Germany.
Video: simply Streetlife Festival
In the year 2000, however, luck would have it that the environmental organisation Green City moved its Streetlife Festival to Ludwigstrasse between Odeonsplatz and Siegestor. Since then, the original pedestrian movement of the "Corsaren" takes place alongside the Streetlife Festival – with a diverse programme spread out across three kilometres.
Both events offer a wide variety of activities. The main focus of the Streetlife Festival is the environment and sustainability. There are numerous sports events, a dance floor, a fair trade bazaar, and various areas with information stands on the environment, climate change and alternative modes of transport.
The Corso Leopold focuses mainly on art and culture. Each festival has a central artistic theme developed by local artists. Stages are set up at large intersections, and visitors can enjoy music, theatre and readings at various stalls and tents. And there's certainly no shortage of food stalls.
While the initiative was once seen as a mere party street, it's since developed into a major event that attracts visitors and locals alike. There have even been calls to extend the Corso area further north to Parzivalplatz, as the European elections will be held during this year's spring festival (25 and 26 May 2019). 23 May will also mark the 70th anniversary of the German constitution, and so the organisers want to make even more space to celebrate both events with a special programme.
Photo: Redline Enterprises; Video: Redline Enterprises
Markets, fairs and festivals
Weekly markets, fairs, Spring Festival, Oktoberfest, Christmas markets: the most important dates.
Time for tradition
Customs are in!
Dult is cult!
All you need to know about the Wiesn
Which beer tent is the right one for me?
Munich's Dirndl Idol
Munich is dancing till dawn
simply magical
The alternative Christmas market
Package simply Munich
Get in and drive off is the motto on your next city break to Munich!
3 days from 318€ for 2 pers.


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• Contact Information
• Eastover Town Council Meeting Tuesday, January 12, 2021
• Special Eastover Town Council Meeting Tuesday, August 25, 2020
• CANCELLED - April 14, 2020 Town Council Meeting
• New Eastover Town Hall Hours-Monday-Friday-8am-4:30pm
• Eastover Board of Adjustment Meeting, Tuesday January 14, 2020 6:30pm
• list all news . . .
TOWN OF EASTOVER
Contact: Eastover Town Hall
POSTED: 12:55 EST Mar 09, 2010 / UPDATED: 09:01 EST Mar 11, 2010
THE CENSUS IS COMING! DON'T BE LEFT OUT.
FILL OUT YOUR FORM AND HELP OUR COMMUNITY.
The U. S. Constitution says the government must count everyone living in the United States every 10 years. Most homes will get a Census form in the mail in March 2010. THE FORM HAS ONLY 10 QUESTIONS.
Census forms are confidential and cannot be shared with anyone, including welfare and immigration agencies. No court of law, or even the FBI, President or ICE, can see what you say. Census workers are subject to a $250,000 fine and up to five years in prison for disclosing information on someone's form.
The number of people counted by the Census determines how much government money goes to a community for programs like schools, health care, housing, roads, transit, social services, and job training. OUR COMMUNITY GETS ABOUT $1,500 FOR EACH PERSON COUNTED IN THE CENSUS. Having 100 more people fill out the Census form adds $150,000 a year for your area, and 1,000 more adds $1,500,000!
Business and government planners use the Census to make decisions about your community's future. THE CENSUS HELPS DECIDE WHERE TO LOCATE NEW GROCERY STORES, HOSPITAL, SCHOOLS, RECREATION CENTERS, AND OTHER FACILITIES.
Home :: Our Town :: News :: Services :: Government :: Contact Us
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Downgrades, ugrades and pizza madness!
Udipi Cafe, D.B.A. Barbecue and Antico
By Cliff Bostock	Friday October 9, 2009 10:00 am EDT
Some restaurants get better with time. Some get worse. I'm looking at one of each this week and we'll start with the one that's gotten worse.
Udipi Cafe (1707 Church St., Decatur, 404-296-6771) moved a few months ago from its original location on Lawrenceville Highway across the street to the shopping center that houses mainly Indian businesses.
The first shock here is the appearance of the place. The original was a rather picturesque spot – a bit gloomy – with quirky architectural details. This new location is completely undecorated unless you count a color scheme that would never occur in nature. I'm talking orange – OK, maybe saffron – with bright red in equal portions. Even the booths are red. There's one of those glass waterfall things out front, but not a bit more decoration.
The restaurant was basically empty when we visited on a Sunday night. That in itself was a shock. Udipi was many Atlantans' introduction to dosai, the huge rice crepes folded around spicy ingredients. It was also generally many people's first taste of authentic South Indian vegetarian food. Carnivores were amazed that they didn't miss meat when they ate at Udipi.
It's entirely possible that the quality of the restaurant's food has not changed as much as our palates have. Udipi has plenty of competition now, so the novelty has worn off, making us all pickier.
The first thing we noticed was that the food generally was not served very warm. Wayne ordered the classic iddly – rice and lentil patties – served with sambar and mint chutney. The iddly were room temperature and strangely misshapen.
My own starter, Mumbai pau-bhaji, didn't live up to its promise. Although the thick spread of spicy vegetables, cashews and cheese had decent flavor, it was served with unappetizing bread that resembled the bottom pieces of hamburger buns. I've been informed that this is appropriate but my own research says the bread is usually a whole, small bun that has been seasoned and toasted with butter. These tasted straight out of the bag. If they were toasted, it was long before they came to our table.
The biggest disappointment was my dosai. The restaurant offers 17 different versions (along with six uthappam, which more resemble pancakes). I ended up with the usual mysore masala dosai, which is filled with hot chutney, potatoes and onions. Again, flavors were strong, but the dosai itself was barely crisp. In fact, it grew quite soggy halfway through my eating.
Wayne made the better choice with the Royal South Indian thali – a large collection of little bowls of various dishes, all of them zingy and complementary, and perfect for someone like Wayne who is addicted to sauces, dunking and sampling as many flavors as possible.
Dessert, badam halwa, featured ground almonds cooked in honey and butter. Think baklava without the pastry. I ordered it with a scoop of intense rose ice cream.
Perhaps the restaurant's kitchen was having an off day, but our meal was not up to our prior experience. The owners, by the way, have opened another restaurant in Duluth.
D.B.A. Barbecue improves
When I first visited D.B.A. Barbecue (1190 N. Highland Ave., 404-249-5000) soon after its opening in June, I was disappointed by the dry meat, no matter what variety I sampled.
The restaurant was using electric smokers that, weirdly, did not vent a whiff of smoke to the open air. I'd never been to a barbecue joint where you didn't get a strong hit of the stuff while you waited for your meal.
That has all changed. The restaurant has a new chef, Drew Kirkland, who was chef de cuisine for Kevin Rathbun for four years. Kirkland brought his own outdoor Lang smoker to work with him and the restaurant ditched its electric smokers for a classic Ole Hickory.
As we did during our first visit, we ordered the outrageously gigantic platter, the D.B.A. Whole House, which allows you to taste all seven meats, with four sides. Just a taste of the moist, tender brisket was enough to prove things had changed. Everything on the platter had a pleasantly aromatic, smoky taste. Standouts included the spare ribs and the baby back ribs, both rubbed with spices. You can order them cooked wet but we prefer to add our own sauce.
The only problem on the platter was the turkey. I'm not sure how you keep the white meat of turkey moist in the best of conditions. I do know that the turkey at Daddy D'z is moist. It is sliced a good bit thinner than D.B.A.'s.
I'm still not terribly happy with the sauces. The "spicy" is only spicy if you're a barbecue novice. Oddly, the sweet sauce had more of a kick than the spicy, so I ended up using more of that – a complete reversal of my usual choice.
As it happens, the restaurant had debuted a few new dishes the night of our visit, mainly side dishes and a starter of bacon-wrapped shrimp. (I still do not want the starter of smoked and fried frog legs over red beans and rice.)
My favorite side was the grilled creamed corn. Collards, potato salad and Brunswick stew, thick with okra, were done right, too.
Yes, we took home a gigantic amount of food. Honestly, I think the Whole House platter, $40, would fill four average eaters.
More pizza
The latest entry into the Atlanta pizza wars is Antico Pizza Napoletana (1093 Hemphill Ave., 404-724-2333), which Jennifer Zyman discovered last week. Although it has no place to sit, you can stand and eat at a communal table.
The pizza is truly a breakthrough in our city. It's a dollar or two more than the average gourmet pie in town, but the kitchen is using such high-quality ingredients, the pies are a bargain. For example, many of the pies feature pricey bufala mozzarella, which is special-order-only at Varasano's.
The new pizzeria is only open for dinner, from 4 p.m. weekdays and noon Saturdays "until the dough runs out." My efforts to learn when the dough typically runs out have been futile.
GRAZING: Does capitalism taste bad?	Article
Friday January 3, 2020 11:48 am EST 01/03/2020 11:48 am
Check out Food Terminal and B's Cracklin' Barbecue | more...
GRAZING: Popeyes. Yes. Really.	Article
Wednesday December 4, 2019 06:20 pm EST 12/04/2019 6:20 pm
But there's more that's good in the 'hood | more...
GRAZING: Smiling before crying at Supremo Taco, dining 'mostly Southern, mainly Asian' at JenChan's	Article
Monday November 4, 2019 02:15 pm EST 11/04/2019 2:15 pm
Twenty years ago during frequent visits to LA, I often visited a late-night taco stand on Santa Monica Boulevard, not far from Silver Lake. I stood at a counter outdoors and watched the nightlife while I ate perfect tacos. My usual impromptu dinner companions were two transgender hookers who called the taqueria their "safe space." Yes, I frequently hummed Lou Reed's "Walk on the Wild Side," a... | more...
GRAZING: Perfect faux tacos and Barbie's favorite steamed rice cakes	Article
Thursday October 3, 2019 01:03 pm EDT 10/03/2019 1:03 pm
Velvet Taco and Vietvana stretch the limits | more...
GRAZING: Feasting in Summerhill	Article
Wednesday September 4, 2019 06:04 pm EDT 09/04/2019 6:04 pm
Religious barbecue, tattooed pizza, and bejeweled ice cream | more...
Search for more by Cliff Bostock
[Admin link: Downgrades, ugrades and pizza madness!]


SECO/WARWICK is a technological leader in innovative heat treatment furnaces. Expertise includes end-to-end solutions in 5 categories: vacuum heat treatment, atmosphere, and aluminium thermal processing, controlled atmosphere brazing of aluminium heat exchangers and vacuum metallurgy. SECO/WARWICK Group has 10 companies located on three continents with customers in nearly 70 countries, has its production facilities in Poland, USA (2 factories: in California and Pennsylvania) and China. In addition, the Group includes a number of service and sales offices in such countries as Germany or Russia.
The company provides standard or customised state-of-the-art heat processing equipment and technologies to leading companies in the following industries: automotive, aerospace, electronics, tooling, medical, recycling, energy including nuclear, wind, oil, gas, and solar and production of steel, titanium, and aluminium.


We need all hands on deck Saturday, October 28 for a Fall Clean-up! We'll get started at 8 a.m. and there will be plenty of upkeep items, such as cleaning windows and organizing Sunday School rooms. A continental breakfast will be served.


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Music in 1969
Roswell, New Mexico S03E04 Review: Walk on the Ocean – Weird…
First of all, I should say that the dog doesn't die. Longtime readers should know that as soon as I see so much as a wagging tail on a show or in a movie, I'm hitting up Does the Dog Die just to make sure. So if you're the same, then you'll want to know that going in.
But why am I even talking about a dog? I'll get to that. I will say that it's part of Jones's storyline, which ends up being kind of muted. I certainly didn't expect that from last week. Then again, maybe the original influenced me not to trust other aliens. (I guess that's a spoiler, but it's a 20-year-old one.)
Anyway, with Alex's assertion last week that Michael couldn't be the victim (because Alex wouldn't cover up his murder), that certainly narrows down the possibilities. Or at least it does for me. I can't say the same for our characters here, who are still grasping at every single option.
Since Maria has been so hesitant to follow through with the vision, because it's scary and sad, Isobel accompanies her this week on a trip through memories. I'm not specifying whose memories, because they're kind of shared. They're not Maria's or Isobel's memories, not directly, but they still have a kind of ownership of them. What that means in practice is that they get to see Louise and Roy.
But while that's sweet, it's not really the point. The point, of course, is the funeral. At first, they think it might be Liz's. Again, though, why would they cover up her murder? And there's still Bert the beekeeper (La'Charles Trask) mentioning at the funeral how this could have been prevented if the sheriff's department had acted on his report.
It becomes clearer throughout the episode who the victim is. Or, really, who's most likely. It starts when Kyle goes to a ranch to treat a guy who's been on the wrong end of a run-in with Wyatt's pals. The man and his wife are undocumented, so they're hesitant to report that the mayor's son, Jordan Bernhardt (Michael Grant Terry), attacked the man.
And on that note, while we're Wyatt-adjacent, we did get some interesting revelations about him this week. He's still circling Rosa, whom he hasn't remembered. That's a little strange, I guess, since it seems that he and Rosa were once really good friends. Further, Wyatt was once a really good guy. He was sensitive enough to recognize Leonard Cohen lyrics on sight, for instance, and not just a stray line from "Hallelujah."
In fact, this reveal, as well as the friction between him and Jordan, made me suspect that Wyatt might be the murder victim. People might respect the new (old) Wyatt enough to attend his funeral. At the same time, none of the main characters is really close enough to him to where they'd have an issue covering up his murder. I mean, I don't think they would.
Again, that's the sticking point for me. Whose murder would they cover-up and why? I would be more inclined to think it was a baddie than a main character. It doesn't even have to be someone bad, necessarily. It could just be someone like Jones.
I still find him shifty, even though he didn't really do anything to provoke my suspicions. Yes, he shot a dog, but he didn't mean to, and he healed it. He also apparently adopted it.
And, of course, he keeps offering to heal Max, who keeps refusing. I'm not sure why, exactly. Max is dying. The medical results in Kyle's office clearly prove that. It's hard to argue your way out of late-stage heart failure. And Max can't exactly go for another transplant. GASP, unless that's why they cover up a murder.
Then again, it would appear unlikely, especially if the murder victim is who it looks to be. After that attack on the undocumented man, Kyle heads over to the sheriff's department. Unfortunately, he runs into Jordan before he can get there. They scuffle, and Kyle is impaled on…something. A piece of wood? A piece of rebar? Maybe I'm having Supernatural flashbacks.
Anyway, it doesn't really matter what it is, because it shouldn't be in Kyle's torso. Max does make it there, but we don't know yet if he's made it in time. He summons his strength to heal Kyle, but as the electricity around him crackles, and the handprint on Liz throbs, one question remains. Will this be the end of Max's heart?
8/10 – The vision stuff was fun, and I like the ambiguity of Jones, even if it makes me nervous. However, the Wyatt storyline is very weird to me. He was a malignant racist and now he's just not, but not because he grew or anything–he just forgot to be a bigot. I guess. Also, Kyle is not dying! (I hope.)
And if you need help with doggy (and other trigger questions), Does the Dog Die is here for you, too.
Roswell, New Mexico S03E03 Review: Black Hole Sun – Contact?
Roswell, New Mexico S03E01 & S03E02 Review: Hands & Give Me One Reason – Convoluted?
| August 4, 2021
Roswell, New Mexico S02E13 Review: Mr. Jones – Absolutely bananas!
TV Topics
Doctor Who 2022 New Years Day Special Review: Eve of the Daleks – Fun
By Jason Collins
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Who's Who? We have some ideas about the new Doctor Who


The Executive Council of the Board of Governors, also known as the Office of the Executive Council, has an administrative office to carry out its work.
To register and file letters, memos and general documents received by the Office of the Executive Council.
To create records of each case, for review and resolution, and issue official documents, internal communications and final versions of letters.
To assist each member of the Office of the Executive Council in their regular work.
To provide the Office of the Executive Council with general support in all relevant matters: academic events, the formal signing of agreements, travel, etc.
Although each person has a specific task, the Administrative Office of the Executive Council acts as a team, so that each member is involved in all functions.


Help break the cycle of incarceration!
Please consider partnering with Working Men of Christ. In order for us to keep serving these men inside of prison and upon their release we need your support. By giving to this ministry you help fulfill the Gospel and establish the Kingdom of God here on Earth.
You can assist us in changing the lives of "the least of these" by sponsoring an inmate through "The Captivity Series" Bible correspondence incentive course. We have established guidelines based on accountability of each inmate who participates in our course to be "a doer of the work" James 1:25. With your donation of $160.00, you can sponsor an inmate through our 8 month course.
With your help of ANY amount, you can help us keep the houses maintained, purchase Study Bibles (given to each inmate upon completion of our course), help us pay postage and paper costs, clothe those who come out of prison with no clothes, help with gas for getting the men to their different commitments, and much much more!
Are you a church leader? Please considering sponsoring WMOC! With contributions as little as $1 per member of your church per month we can maintain an entire discipleship house or establish a new one!
Request a speaker from WMOC to share our testimonies and speak to your congregation about all the wonderful things we are doing. We know they will be moved and encouraged! The REQUEST A SPEAKER button will take you to our contact page where you can send us a request.
"Then shall the King say unto them on his right hand, Come, ye blessed of my Father, inherit the kingdom prepared for you from the foundation of the world: For I was an hungred, and ye gave me meat, I was thirsty, and ye gave me drink, I was a stranger, and ye took me in, Naked, and ye clothed me, I was sick, and ye visited me, I was in prison, and ye came unto me."
All donations go to Working Men of Christ to advance the mission of the non-profit organization. Your contribution will help current and former inmates learn to live an independent, fulfilled life through our program as well as our prison ministry.


Predominently white, the appearance will vary from that illustrated as these are all natural stone with intrinsic variation but most show a good flash of colour. The illustration may be taken as a guide.
Opal is the BIRTHSTONE for OCTOBER. A symbol of hope and good luck. Thought to protect against poisoned food and to promote a good memory.


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TRU Start (Dual Credit) Information Session – TRU Newsroom
January 5, 2023 at 11:04 am Education, Kamloops, News
Interested in starting your post-secondary journey a little early? TRU Start is an opportunity for School District 73 students to experience university life and earn post-secondary credits (often dual credit) while attending high school.
This virtual information session is open to parents/guardians and students who are in grades 10 and 11 who attend school in School District 73
What programs and courses are offered? Why is it beneficial to take part in TRU Start? How does the funding work? How do you apply? We will cover all of this and more!
Hosted by the Thompson Rivers University Future Students Office and School District 73 Trades and Transitions.
View Link to Original Source


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Spin The Wheel! The Life Of Vanna White
Vanna White is a celebrity known by both older and younger generations alike. That's what happens when you're a co-host on one of America's most popular game shows, Wheel of Fortune, for 35 years. While Vanna has been responsible for uncovering the letters on the classic series for over three decades, what do we really know about the woman behind the beaming smile and glamorous dresses? Vanna has been through a number of ups and downs, such as multiple failed engagements, the death of a fiancé and, of course, family drama. But she never loses that gameshow smile. Read on to learn little-known secrets of the life of Vanna White. It's sure to surprise you!
Vanna White was born on February 18, 1957, in North Myrtle Beach, South Carolina. She started working as a professional model after high school while attending the Atlanta School of Fashion. She moved to Los Angeles to pursue a career in acting and after a number of small roles in some unknown films, Vanna landed the job that would change her life. She became the co-host and "letter-turner" on NBC's hit game show, Wheel of Fortune. Without even having any scripted lines, she quickly became a megastar, even an iconic figure, in the 1980's American pop culture.
Vanna had a lot of competition for the role on Wheel of Fortune…


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\section{INTRODUCTION}

Active stability technologies play a major role in modern vehicle dynamic systems in order to enhance the lateral vehicle stability and reduction in fatal accidents. These technologies such as torque-vectoring controllers (i.e., the control of the traction and braking torque of each wheel), can effectively enhance the vehicle handling performance in extreme manoeuvres \cite{Lu2016}\cite{Wang2018}. Torque-vectoring controller has a prominent advantage of stabilizing a vehicle through choosing appropriate control parameters. However, if the parameters cannot be adapted to the environmental changes, then control design would be cumbersome and will not guarantee good robustness.

In order to solve this problem, the adaptive control design has received wide attention. Some methods of tuning parameters have been proposed such as fuzzy logic method \cite{Fu2016}\cite{VanKien2019}, which have optimization problem of parameters and requires more knowledge of the environment. Another method is evolutionary algorithm \cite{Cao2020}\cite{Rajinikanth2012} such as genetic algorithm, which is a strong tool for tuning the control parameter with less computational requirements for prior knowledge, however depending on the complexity of the problem the calculation speed will be slow. Others have used neural networks to learn the optimal parameters for each state \cite{Fei2018}\cite{Chen2004}, typically using supervised learning to train the neural network. However, the downside of supervised learning methods is that during training, the ground truth (i.e. correct prediction for given inputs) for each prediction is required to measure the error in the network's predictions. Therefore, supervised learning is poorly suited to problems where the ground truth is not readily available or is difficult to estimate. On the other hand, reinforcement learning is a technique inspired by human and animal learning, where the neural network is trained through a trial-and-error mechanism, without requiring any ground truth labels. Therefore, reinforcement learning is better suited for this type of problem where the correct predictions are not known, as it enables the network to learn the optimal policy effectively through interaction with its environment. The success of reinforcement learning \cite{Silver2016}\cite{Silver2017} was perceived as a breakthrough in the field of artificial intelligence. This algorithm attempts to learn the optimal control policy through interactions between the system and its environment without the need of prior knowledge of an environment or the system model. In this algorithm, an agent takes an action based on environment state and consequently receives a reward. Reinforcement learning algorithms are generally divided into three groups \cite{Konda2003}\cite{Hsu2019}: value based, policy gradient and actor-critic methods. In this paper, DDPG algorithm \cite{Lillicrap2016} is used, which is in the family of actor-critic group algorithm, to tune the parameters of the torque-vectoring controller. DDPG agent is an actor-critic reinforcement learning that computes optimal policy that maximizes the long-term reward. The actor is a network attempting to execute the best action given the current state. The critic estimates the maximum value function of given state (i.e approximate maximizer). Then uses the reward from environment to determines the accuracy of the prediction value. In \cite{Wang2019}, authors proposed DDPG as a reinforcement learning algorithm for tuning the sliding mode controller parameters for autonomous underwater vehicle. Results demonstrated that DDPG achieved a good performance in terms of stability, fast convergence and low chattering. In \cite{WANG2007}, reinforcement learning was used to tune PID controller parameters where the auto tuning strategy was through actor-critic reinforcement learning method resulting in stable tracking performance of the system. However, the generalization of the trained models for the scenarios beyond the training environment were not validated. Therefore the performance of the algorithms in new environments can not be guaranteed.\\
 In this paper, reinforcement learning algorithm is incorporated into the torque-vectoring controller to adjust the control input weights in order to maintain the stability of the vehicle. The contribution in this paper lies into the utilization of DDPG algorithm as an intelligent tuning strategy for the torque-vectoring controller in a real application for different scenarios. It has been shown that proper tuning of the control input weights results in improvement in handling and stability of the vehicle. In order to validate the effectiveness of the DDPG algorithm, simulation environment has been set under different velocities ranging from 80-130  $\SI{}{\kilo\metre\per\hour}$ and different friction surface ranging from 0.4-0.6. The performance is then compared with a conventional trial-and-error approach (which will be referred as manual tuning for the rest of the paper), and a self-tuning genetic algorithm, to show the enhanced effectiveness of DDPG as a tuning strategy for active yaw control systems. Moreover, to validate the generalization capability of the trained model, simulation has been deployed in the environment that DDPG was not trained in, to ensure the robustness of the algorithm under unknown operating conditions. The simulation results have been conducted using a four wheels vehicle model \cite{Falcone2007a} with nonlinear tire characteristics in \textsc{Matlab}\xspace/Simulink environment. Moreover, for solving the on-line tuning algorithm, \textsc{Matlab}\xspace reinforcement learning toolbox is used for parameter tuning of the torque-vectoring controller.
The remainder of the paper is structured as follows: \cref{vehicle-model} describes the vehicle model used in this paper. \cref{torque} introduces the torque vectoring algorithm used for stabilization purposes in this paper. \cref{RL} presents the reinforcement learning algorithm used for tuning parameters of the torque vectoring control. \cref{S-results} demonstrates the simulation results of the trained algorithm, and finally concluding remarks are presented in \cref{conclusion}.
\section{Vehicle model}
\label{vehicle-model}
In this paper, vehicle simulation model is the six state nonlinear four wheel vehicle model presented in \cite{Falcone2007a}. The model states are $[\dot{x}, \dot{y}, \psi, \dot{\psi}, X, Y]^T$ where $\dot{x}$ and $\dot{y}$ represents the vehicle longitudinal and lateral velocities, respectively, in the body frame and $\psi$, $\dot{\psi}$, $X$ and $Y$ denotes yaw angle, yaw rate, longitudinal and lateral coordinates in the inertial frame. To describe the vehicle model, normal forces are assumed to be constant and roll angle is neglected in the formulation. The tire model used in this paper is described by pacejka model \cite{Pacejka2012a}. This is an empirical nonlinear tire model which is able to closely capture the tire dynamics.

\section{Torque vectoring control}
\label{torque}
\subsection{System Architecture}
The overall architecture of the proposed control framework is shown in \cref{structure}. In this structure, the command interpreter module (CIM) generates desired forces at the centre of gravity (C.G) based on inputs from the reference generation block ($\delta_f$ and $T_{ff}$) in order to interpret the driver's intention for the vehicle motion. CIM continuously monitors the inputs as well as the states of the vehicle to provide accurate desired values to the torque vectoring controller to keep the vehicle within the stable region. It is noted that CIM generats the desired C.G forces with assumption of normal driving conditions (e.g. high surface fricition condition). For the brevity of the paper, the calculation of CIM block is referred to \cite{Fallah2013}. The inputs to the reinforcement learning are the errors between the actual and desired forces followed by the actual states of the vehicle. Moreover, the generated error between the actual and reference signal as well as the actions from reinforcement learning ($W_{df}$) are fed to the controller in order to generate the adjustment torque required to assist the driver for improving handling and stability of the vehicle.
       \begin{figure*}[t!]
	\begin{multicols}{2}
		\includegraphics[width=1.9\linewidth]{control_system_RL.pdf}
		\hspace{16cm}
	\end{multicols}
	\caption{Adaptive torque vectoring controller based on reinforcement learning}
	\label{structure}
\end{figure*}
\subsection{Controller}
\label{control}
A torque-vectoring controller was developed to ensure lateral/yaw stability of the vehicle. The primary objective of this controller is to provide a safe driving experience in the case of unexpected driving condition e.g. low surface friction condition. The desired C.G forces ($F_{des}$) in \cref{structure} are represented as:
  \begin{equation}
F_{des}=[F_x^*, F_y^*, G_z^*]^T
\end{equation}
   where $F_x^*$,$F_y^*$ and $G_z^*$ are the desired C.G longitudinal and lateral forces and yaw moment, respectively. The actual C.G forces of the vehicle are:
\begin{equation}
F=[F_x, F_y, G_z]^T
\end{equation}
where $F_x$, $F_y$ and $G_z$ are the actual C.G longitudinal and lateral forces and yaw moment of the vehicle, respectively. Each C.G force components is a function of longitudinal and lateral tire forces (see \cref{force}) as:
\begin{align}
F_x&=F_x(f_{x1},\dots, f_{x4}, f_{y1},\dots,f_{y4}) \label{1}\\
F_y&=F_y(f_{x1},\dots, f_{x4}, f_{y1},\dots,f_{y4}) \label{2}\\
G_z&=G_z(f_{x1},\dots, f_{x4}, f_{y1},\dots,f_{y4}) \label{3}
\end{align}

where, $f_{xi}$ and $f_{yi}$,$(i=1,\dots,4)$  are longitudinal and lateral tire forces on each wheel of the vehicle, respectively. Equations \eqref{1}-\eqref{3} reveal a possible way to obtain the desired C.G forces by controlling the tire forces. The tire force vector can be represented as:
\begin{equation}
	f= [f_{x1},f_{x2},f_{x3},f_{x4},f_{y1},f_{y2},f_{y3},f_{y4}]^T
\end{equation}
The corresponding adjusted C.G forces to minimize the error between the actual forces $F(f)$ and desired forces $F_{des}$, can be written as:
\begin{equation}
F(f+\delta_F)\approx F(f)+\nabla F(f)\delta_F
\label{T1}
\end{equation}

where, $\nabla F(f)$ is the Jacobian matrix and $\delta_{F}$ is the vector containing the control actions needed to minimise the error between the actual and desired forces which is:
\begin{equation}
	\delta_F= [\delta_{f_{x1}},\delta_{f_{x2}},\delta_{f_{x3}},\delta_{f_{x4}},\delta_{f_{y1}},\delta_{f_{y2}},\delta_{f_{y3}},\delta_{f_{y4}}]^T
	\label{totalforce}
\end{equation}
It is noted that in this work in order to derive torque vectoring control actions, only $\delta_{f_{xi}}$is considered for controller designing procedure and the effect of lateral control actions are neglected:
\begin{equation}
	\delta f_{yi} = 0,\hspace{0.5cm} i=1,\dots,4
	\label{y0}
\end{equation}
To formulate the required control action $\delta_{F}$, the error between the desired C.G forces at $t + \Delta t$ and actual C.G forces at $t$ is described:
\begin{equation}
E = F_{des} - F(f) = [E_x, E_y, E_z]^T
\label{e0}
\end{equation}
Then the control actions $\delta_{F}$ for time $t+\Delta t$ can be calculated from $F_{des} - F(f+\delta_{F})$, where $F(f+\delta_{F})$ is the C.G forces at $t + \Delta t$. Then using \eqref{T1}, \eqref{y0} and \eqref{e0}, one has:
\begin{equation}
	F_{des} - F(f+\delta_{F}) \approx F_{des}-F(f)-\nabla F(f)\delta F=E-\nabla F(f)\delta F
\end{equation}
where
\begin{equation}
\nabla F = \begin{bmatrix}
	 \frac{\delta F_x(f)}{\delta F} \\
	\frac{\delta F_y(f)}{\delta F}\\
	\frac{\delta G_z(f)}{\delta F}
\end{bmatrix}=\begin{bmatrix}
		\frac{\delta F_x}{\delta f_{x1}} & \frac{\delta F_x}{\delta f_{x2}} & \frac{\delta F_x}{\delta f_{x3}} & \frac{\delta F_x}{\delta f_{x4}}\\
			\frac{\delta F_y}{\delta f_{x1}} & \frac{\delta F_y}{\delta f_{x2}} & \frac{\delta F_y}{\delta f_{x3}} & \frac{\delta F_y}{\delta f_{x4}}\\
		\frac{\delta G_z}{\delta f_{x1}} & \frac{\delta G_z}{\delta f_{x2}} & \frac{\delta G_z}{\delta f_{x3}} & \frac{\delta G_z}{\delta f_{x4}}
\end{bmatrix}
\end{equation}
Then an objective function consists of weighted combination of error between the actual and desired vehicle C.G forces and control action must be defined. The mathematical representation of objective function is:
\begin{equation}
\begin{gathered}
P = \frac{1}{2}[(E-\nabla F \delta_F)^TW_E(E-\nabla F \delta_F)+\\\delta_F^TW_{df}\delta_F]
\end{gathered}
\label{index}
\end{equation}
where $W_E \in \mathbb{R}^{3x3}$ is the weight on longitudinal, lateral and yaw moment error, and $W_{df} \in \mathbb{R}^{4x4}$ is the weight on control action. Since \eqref{index} is a quadratic form with respect to the tire force adjustment $\delta F$, the necessary condition of the solution is given by solving the equation
\begin{equation}
\frac{\partial P}{\partial \delta F}=0
\end{equation}
As a result of minimization of the objective function, the control action required to stabilize the vehicle is \cite{Fallah2013}:
   \begin{equation}
\begin{gathered}
\delta F=[W_{df}+(\nabla F(f)^TW_E)\nabla F(f)]^{-1}
(\nabla F(f)^T(W_E)E)
\end{gathered}
\end{equation}
 The applied corrective torque on each wheel is $\delta T = R_{eff}\times\delta F$ where $R_{eff}$ is the effective wheel radius. It is noted that in this paper, there is no adjustment on lateral tire forces and only longitudinal corrective actions are calculated from the controller design. Subsequently, only the weights on the longitudinal corrective actions are tuned using reinforcement learning algorithm, while keeping $W_E$ as fixed values.
 	\begin{figure}[t!]
 		\hspace*{-0.2in}
 		\centering
 		\includegraphics[width=0.55\linewidth]{4wd2}
 		\caption {Force convention}
 		\label{force}
 	\end{figure}
\section{Reinforcement Learning Algorithm}
      \label{RL}
In this section an overview of reinforcement learning framework followed by DDPG algorithm used for parameter tuning of torque-vectoring controller is presented.
\subsection{Reinforcement learning overview}
To implement a Reinforcement Learning (RL) based controller, we consider a standard RL setup for continuous control in which an agent interacts with the environment, aiming to learn from its own actions. The formulation of reinforcement learning is based on a Markov Decision Process. At each time step $t, t=0,1,...,T$, the agent receives an observations $s_t$, takes an action $a_t$ from a set of possible action $\mathcal{A}$. As a consequence of the actions, the agent receives a reward $r_t$ and observes a new state $s_{t+1}$ \cite{Kuutti2019}\cite{Lillicrap2016}. The goal in reinforcement learning is to learn a policy $\pi$, which maps states to actions: $\pi$: $\mathcal{S}\rightarrow\mathcal{A}$ resulting in maximizing the expected cumulative discounted reward $R=\mathbb{E}[\sum_{t=0}^{t=T}\gamma^tr(s_t,a_t)]$ with discounting factor $\gamma\in[0,1]$ and $\mathbb{E}$ denoting the expectation of the probability. The state-action value ($Q$ value) at time step $t$ represents the expected cumulative discounted reward from time $t$. Reinforcement learning problem is solved using Bellman's principle of optimality. That is, if the optimal value of the state-action $Q^*(s_{t+1},a_{t+1})$ for the next time step is known, then the optimal state-action value for the current time step can be calculated by maximizing $r(s_t,a_t)+Q^*(s_{t+1},a_{t+1})$.\\
In this paper, the actions of the reinforcement learning framework are the control action weighting parameters $W_{df}$. The observation for reinforcement learning are the errors between the actual and desired forces at the C.G of the vehicle as well as the vehicle states $s_t=[e_x,e_y,e_{Mz}, \dot{x},\dot{y},\psi,\dot{\psi},X,Y]$.\\ To encourage the agent to tune the weighting parameters, a reward function must be appropriately defined by the user. In our model the objective is to find a selection of weighting parameters to enforce the vehicle to follow the reference signals while maintaining the stability. Therefore, a reward function must be designed such that the weighting matrix $W_{df}$ generated from reinforcement learning makes the reward function and the objective function in \eqref{index} to be as similar as possible. Hence, the error between the actual and reference C.G forces that are used in the cost function \eqref{index} are chosen for the reward function in order to find a suitable selection of weighting matrix for torque vectoring controller. It is noted that proper selection of a reward function determines the behavior of controller, and thus affects the stability of the vehicle. Therefore, in order to ensure the reliability of the torque vectoring controller a well-defined reward function $r_t$ provided at every time step $t$ is introduced:
   \begin{equation}
   r_t=-(10e_x^2+5e_y^2+5e_{Mz}^2)\times0.01+6M_t + N_t
   \label{reward}
   \end{equation}
The first term in the reward function encourages the agent to minimize the errors, while the logic conditions encourage the agent to keep the error below some threshold. The two logics in \eqref{reward} are: $M_t=0$ if the simulation is terminated, otherwise $M_t=1$. $N_t=1$ if the components of error is $e_x,e_y<\SI{200}{\newton}$ , otherwise $N_t=0$. In this way a large positive reward is applied when the agent is close to its ideal conditions which is when the errors of C.G are small. On the other hand, a negative reward is applied when the vehicle fails to maintain the stability, which discourages the agent from losing the directionality of the vehicle. It is noted that the simulation is terminated when the sideslip angle of the vehicle is greater than $\SI{8}{\degree}$. Moreover, the action signal takes the values between $40$ and $1e^3$ as lower and upper bound for all parameters in $W_{df}$.
\begin{table}[t!]
	\caption{DDPG parameter values}
	\label{table_example}
	\begin{center}
		\begin{tabular}{c||c}
			\hline
			\hline
			Reward discount factor & 0.99\\
			\hline
			Critic learning rate & $1e^{-3}$\\
			\hline
			Actor learning rate & $1e^{-4}$\\
			\hline
			Target network update & $1e^{-3}$\\
			\hline
			Mini-batch size & 70\\
			\hline
			Variance decay rate & $1e^{-3}$\\
			\hline
			Variance & $30$\\
			\hline
			Sample time & 0.5\\
			\hline
			Number of neurons & 100\\
				\hline
			Experience buffer length & $1e^6$\\
			\hline
			\hline
		\end{tabular}
	\end{center}
\end{table}
\subsection{Deep Deterministic Policy Gradient}
DDPG is an evolution of Deterministic Policy Gradient \cite{Silver2014} algorithm. It is in the family of actor-critic network \cite{S.Sutton2015}, model-free, off-policy algorithms which utilize Deep Neural Networks as function approximators. DDPG allows to learn policies in high-dimensional, continuous state and action spaces. The DDPG used in this paper, is inspired from \cite{Lillicrap2016}. A brief description of the theory will be discussed in this section, however, a keen reader is encouraged to read the original paper. The DDPG algorithm uses two deep neural networks: actor and critic network. The actor network is responsible for state-action mapping through the deterministic $\pi(s_t|\theta^\pi)$ where $\theta^\pi$ represents the actor neural network weight parameters, and critic network is for $Q$-value function $Q(s_t,a_t)$
   \begin{equation}
   \small
Q^\pi(s_t,a_t) = \mathbb{E}_{r_t, s_{t+1}\sim{E}}[r(s_t,a_t)+\gamma(Q^\pi(s_{t+1},\pi(s_{t+1}))]
\end{equation}
The action value function $Q$ is approximated using DNN with net weights parameters $\theta^Q$. For learning the Q-value, Bellman's principle of optimality is used to minimize the root mean squared loss
   \begin{equation}
L(\theta^Q) = \mathbb{E}_{s_t\sim\rho^\beta, a_t\sim\beta,r_t\sim{E}}[(Q(s_t,a_t|\theta^Q)-y_t)^2]
\end{equation}
where
\begin{equation}
 y_t=r(s_t,a_t)+\gamma{Q(s_{t+1},\pi(s_{t+1}|\theta^Q))}
 \end{equation}
The actor policy $\pi(s_t|\theta^\pi)$ is updated using:
\begin{equation}
\small
\nabla_{\theta^\pi}\approx \mathbb{E}_{s_t\sim\rho^\beta}[\nabla_{a}Q(s,a|\theta^Q)|_{s=s_t,a=\pi(s_t)}\nabla_{\theta_\pi}\pi(s|\theta^\pi)|_{s=s_t}]
\end{equation}
	\begin{figure}[t!]
		\hspace*{-0.2in}
		\centering
		\includegraphics[width=0.95\linewidth]{reward-eps-converted-to.pdf}
		\caption {Episode reward for training the torque vectoring parameters}
		\label{Reward}
	\end{figure}
 which is the policy gradient. For learning the policy $\pi$ gradient ascent is performed with respect to the policy parameter $\theta^\pi$ to maximize the Q-value. In DDPG the target networks are used to stabilize the training \cite{Mnih2015}. Gaussian noise is used for action exploration \cite{UHLENBECK1930}. Experience replay is utilized for stability \cite{Mnih2015}. Mini-batch gradient descent is used \cite{Lillicrap2016}. The network parameters were empirically tuned, and final hyperparameters can be found in \cref{table_example}.
 	\begin{figure}[t!]
 	\hspace*{0.1in}
 	\centering
 	\includegraphics[width=0.9\linewidth]{Inputs-eps-converted-to.pdf}
 	\caption {\textbf{top figure}: Applied torque on each wheel, \textbf{bottom figure}: Input steering}
 	\label{inputs-dr}
 \end{figure}
Both the actor and critic networks are neural nets with 2 hidden layers. The hidden neurons all use Relu activation, actor output uses tanh activation, whilst critic output uses linear activation.
\section{Simulation results}
\label{S-results}
 The DDPG agent was trained for 650 episode with $\SI{15}{\second}$ episode length. At the start of each training episode, the environment parameters were varied by choosing initial velocity randomly between $\SI{80}{\kilo\meter\per\hour}$ to $\SI{130}{\kilo\meter\per\hour}$ and friction value ranging from 0.4 to 0.6. As can be seen from the episode rewards (see \cref{Reward}), the agent quickly converges to an optimal policy, although slight improvements in the average reward can still be seen in the later episodes. Once the training phase is completed, performance of the DDPG network is validated in various driving scenarios. All simulation experiments presented in this paper were performed on a four wheel vehicle model with pacejka tire model described in \cref{vehicle-model}. For the simulation purposes the driver's input torque and steering wheel angle from reference generator are shown in \cref{inputs-dr}. The parameters used to design vehicle model are tabulated in \cref{table_vehicle}. In this section, we first demonstrated the results of the algorithm in scenarios that DDPG was trained in and compared the simulation results with genetic algorithm and manual tuning of the weighting matrix $W_{df}$. It is noted that the error signals used in the reward function \eqref{reward} are chosen for designing cost function in genetic algorithm in order to have a fair comparison between two strategies. For further validation, the effectiveness of the DDPG algorithm is investigated for the conditions that reinforcement learning was not trained in, under different input steering angle. This analysis aims to investigate the generalization capability of the DDPG tuning strategy, by testing its performance in scenarios beyond the training environment. The first scenario that is chosen to demonstrate the performance of DDPG algorithm, is under conditions where the surface friction is 0.4 and initial velocity is $\SI{100}{\kilo\metre\per\hour}$.
  	\begin{figure}[t!]
 	\hspace*{-0.2in}
 	\centering
 	\includegraphics[width=0.8\linewidth]{Wdf-eps-converted-to.pdf}
 	\caption {\textbf{(a)}: Generated weighting matrix $W_{df}$, \textbf{(b)}: Applied torque on each wheels}
 	\label{inputs}
 \end{figure}
 It is noted that every iteration of the algorithm is actively trying to maximise the reward function by reducing the error signals presented in \eqref{reward}, and at the same time maintaining a smooth and low control effort from torque vectoring controller by generating an optimal set of weighting matrix from reinforcement learning. This can be observed in \cref{inputs} where the top figure shows the weighting matrix generated from the reinforcement learning algorithm while the bottom figure shows the control action from torque vectoring controller. The generated adjustment torque $\delta F$ on each wheel shows a symmetric and smooth evolution as a consequence of weighting matrix $W_{df}$. It is noted that the course of $W_{df}$ on the front left (FL) wheel is constant over the entire simulation compared to the other weights on each wheel. This behavior indicates that reinforcement learning found some semi-trivial solution to the problem for the entire operating regions, demonstrating the generalization capabilities of the trained model which will be clear later in this section.\\
 \begin{table}[b!]
 	\caption{Design parameters}
 	\label{table_vehicle}
 	\begin{center}
 		\begin{tabular}{c||c}
 			\hline
 			\hline
 			Vehicle mass  & 1360 $kg$\\
 			\hline
 			Yaw moment of inertia & 2050 $kgm^2$\\
 			\hline
 			Effective wheel radius & 0.3 $m$\\
 			\hline
 			Front distance from vehicle C.G & 1.43 $m$\\
 			\hline
 			Rear distance from vehicle C.G & 1.21 $m$\\
 			\hline
 			Front cornering stiffness & $\SI{16000}{\newton\per\radian}$\\
 			\hline
 			Rear cornering stiffness & $\SI{16000}{\newton\per\radian}$\\
 			\hline
 			$W_E$& $diag(0.4,0.02,1500)$\\
 			\hline
 			\hline
 		\end{tabular}
 	\end{center}
 \end{table}
\cref{forces}, compares the actual C.G forces obtained from the vehicle model with those estimated by CIM block. As can be seen, the generated C.G forces are able to track the reference values, resulting in stabilizing the vehicle under friction surface $\mu = 0.4$. However, the small discrepancy can be seen in the second figure of the subplot. This is due to the fact that in the formulation presented in \cref{control}, since there is no direct control of the lateral tire forces, the magnitude of the error in lateral C.G force is relatively large, hence it would be difficult to fully minimize the lateral C.G error under this condition.\par
	\begin{figure}[t!]
		\hspace*{-0.1in}
		\centering
		\includegraphics[width=0.9\linewidth]{forces-2-eps-converted-to.pdf}
		\caption {Longitudinal, lateral forces and yaw moment around C.G The yellow lines represent the actual vehicle behavior, and blue line represent the reference forces estimated from CIM block}
		\label{forces}
	\end{figure}
To validate the effectiveness of the DDPG algorithm, the result of the longitudinal C.G error is compared with genetic algorithm and trial-and-error approach (manual tuning). It is noted that, the manual tuning of $W_{df}$ was selected based on our previous work in \cite{Taherian2019} where its corresponding values resulted in maintaining the vehicle stability with $W_{df} = diag(1e^2, 1e^2, 1e^2, 1e^2)$. \cref{efx} shows the comparison between parameter tuning using DDPG algorithm, genetic algorithm and manual tuning of torque-vectoring controller.  \cref{efx}(a) demonstrates the evolution of error in longitudinal C.G forces for all tuning approaches. In this analysis the value of errors are such that vehicle can successfully maintain the stability. However, evolution of the error for DDPG algorithm outperforms the rest of the approaches with the absolute value of the maximum error of $\SI{137}{\newton}$, whereas in genetic algorithm and manual tuning this value reaches to $\SI{205}{\newton}$ and $\SI{366}{\newton}$ respectively.
	\begin{figure}[t!]
		\hspace*{-0.1in}
		\centering
		\includegraphics[width=0.9\linewidth]{ex-eps-converted-to.pdf}
		\caption {\textbf{(a)}: Longitudinal C.G force errors under $\mu = 0.4$, \textbf{(b)}: Performance index results, \textbf{note}: Blue line represents genetic algorithm tuning results, yellow line represents manual tuning, and orange line is DDPG algorithm results}
		\label{efx}
	\end{figure}
Moreover, unlike the manual tuning, the value of the error for both DDPG and genetic algorithm is able to return to near-zero, however the magnitude of the error for DDPG is smaller compared to genetic algorithm which shows the superiority of DDPG strategy over the rest of the approaches. This confirms that DDPG algorithm is a reliable technique to obtain better understanding of controller parameters and the tuning, particularly in the nonlinear region of operation of the vehicle. Note that, in this paper, only error on the longitudinal C.G force is analyzed, since only the longitudinal corrective action is considered to be controlled in order to stabilize the vehicle. \cref{efx}(b) demonstrates the outcome of the objective function \eqref{index} to show the optimal solution of the torque vectoring controller as a result of parameter tuning. As can be seen, DDPG is able to find the best solution by reducing the performance index to the minimum level and converges to the near-zero value around $\SI{8}{\second}$ of the simulation. This optimal value shows better result compared to genetic algorithm and almost double improvement compared to manual tuning of the weighting matrix.\\
Parametric analysis has been carried out to verify the effectiveness of DDPG algorithm. In this analysis, the absolute value of the maximum error of longitudinal C.G error force for DDPG algorithm, genetic algorithm and manual tuning of torque-vectoring controller is presented (see \cref{table_simresults}).  First, the analysis focuses on comparing the DDPG algorithm with other approaches, under different friction coefficient of the road and the same initial velocity of $\SI{100}{\kilo\meter\per\hour}$. In this analysis, the value of error is increasing gradually for all cases as the road friction decreases. However, for all friction values, DDPG reduces the maximum absolute errors by more than 50\% which shows improvement compared to genetic algorithm and manual tuning.
	\begin{table*}[t!]
	\caption{Longitudinal C.G error for various driving scenarios}
	\label{table_simresults}
	\centering
	\begin{tabular}{ m{3cm} m{1cm}  m{1cm}  m{1cm} m{1cm} m{1cm} m{1cm} m{2cm}}
		\hline
		\hline
		\textbf{$\mu$} & \textbf{0.4} & \textbf{0.45} & \textbf{0.5} & \textbf{0.55}& \textbf{0.6}& \textbf{0.65}& \textbf{0.7}
		\\
		\hline\\
		DDPG & 132 N & 115 N & 77 N & 54 N & 43 N & 32 N & 18 N\\
		Genetic algorithm & 205 N & 180 N & 163 N & 105 N & 86 N & 65 N & 32 N\\
		Manual tuning & 366 N & 289 N & 223 N & 170 N & 127 N & 95 N & 70 N \\
		\hline
		\hline
		\textbf{$V_x (km/h)$} & \textbf{70} & \textbf{80} & \textbf{90} & \textbf{100}& \textbf{110}& \textbf{120}& \textbf{130}
		\\
		\hline\\
		DDPG & 17 N &33 N & 77 N & 132 N & 182 N & 202 N & 214 N\\
		Genetic algorithm & 40 N &73 N & 161 N & 205 N & 287 N & 322 N & 390 N\\
		Manual tuning & 71 N & 105 N & 212 N & 366 N & 487 N & 498 N & 515 N\\
		\hline
		\hline
	\end{tabular}
\end{table*}
	\begin{figure}[t!]
		\hspace*{-0.1in}
		\centering
		\includegraphics[width=0.86\linewidth]{diff_scen-eps-converted-to.pdf}
		\caption {\textbf{(a)}: Longitudinal C.G force errors under $\mu = 0.3$, \textbf{(b)}: Performance index results}
		\label{error-diff}
	\end{figure}
 This analysis shows the effectiveness of DDPG algorithm on the performance of the control structure in adapting of the system to the changes of the environment condition. The second analysis has been conducted to evaluate the proposed framework under different velocities with a fixed friction surface condition ($\mu=0.4$). It can be seen that as the velocity of the vehicle increases, the absolute value of the maximum error increases for both cases. This analysis confirms the ability of the DDPG algorithm to improve the adaptive capability of the controller under different velocities and low surface friction condition.\\
Finally to validate generalization capability of the DDPG algorithm, simulation results have been conducted under the environment that DDPG was not trained in. Therefore, friction surface of $\mu=0.3$ is chosen as an environment that was not considered during training. Initial velocity of the vehicle is chosen as $\SI{80}{\kilo\meter\per\hour}$ which is a reasonable representation of high-speed driving on an icy/snow surface. Additionally, a $\SI{50}{\degree}$ step steer manoeuvre is applied as an input steering angle ($\delta_f$) to the system in order to investigate the generalization capability of DDPG algorithm under the unforeseen conditions. This can be seen in \cref{error-diff} where in \cref{error-diff}(a) the longitudinal C.G error shows larger evolution during braking and acceleration for the duration of 8 to 11s for all tuning approaches due to sudden input driving torque applied to the controller. However, as can be seen the error for DDPG algorithm converges to zero which indicates reasonably good tracking of this algorithm even in the environment that it was not trained in. On the other hand, genetic algorithm and manual tuning show larger evolution of the error and fail to converge to zero with slightly better tracking capability of genetic algorithm. \cref{error-diff}(b) demonstrates the result of the cost function \eqref{index} in order to show the optimal solution of the torque vectoring controller for all approaches. As can be seen DDPG offers a better solution compared to other methods despite a relatively large peak around 11s. The reason of this is due to a large $W_{df}$ (see \cref{inputs}(a)) applied to the controller to maintain the vehicle stability, which ultimately minimised the performance index to near-zero value and find an optimal solution. On the other hand the value of performance index for genetic algorithm and manual tuning observed an increasing trend with lack of converging to an optimal solution. The results show the superiority of the proposed DDPG approach to parameter tuning over the manual tuning and genetic algorithm baselines. More importantly, by carrying out tests with different road conditions, vehicle velocities, and steering inputs from those seen during training, the results demonstrate that the DDPG has learned a general approach to tune the weighting parameters of the torque vectoring controller which can generalize to new scenarios and environments.
\section{CONCLUSIONS}
\label{conclusion}
This paper has investigated the use of DDPG algorithm for automatically tuning a torque-vectoring controller under a wide range of different vehicle velocities and friction surface conditions. The proposed control framework consists of \textit{(i)} reinforcement learning method as an auto-tuning algorithm, \textit{(ii)} a torque-vectoring controller to ensure lateral-yaw stability of the vehicle. The closed-loop scheme was implemented on a four wheels vehicle model with nonlinear tire characteristics, and the numerical results indicate the benefits of the reinforcement learning on tuning the torque-vectoring parameters. The DDPG has multiple advantages over genetic algorithm and manual tuning as it can find better weighting parameters of the controller, as well as tuning the parameters in an online manner based on the current states of the vehicle. The results demonstrated the effectiveness of the DDPG algorithm as an auto-tuning method over wide range of operating points, resulting in significant reduction of Longitudinal C.G errors compared to other tuning approaches. The overall performance of the vehicle indicates the accurate tracking of references as well as maintaining the stability of the vehicle using DDPG which shows the efficacy of this algorithm. While this work evaluated the adaptive tuning of torque vectoring parameters via $W_{df}$, this framework is quite general and could be adapted to different controllers and even different domains.

\bibliographystyle{IEEEtran}

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