text:
The Best Progressive Rock of 2011
Brice Ezell
In 2011, there were only a few high-quality progressive rock releases, but those that managed to stand out are some of the best the genre has seen in awhile.
In 2011, progressive rock was comforting and disheartening in equal measures, as it has been over the decades. It's comforting to know that every year always brings at least one quality progressive rock release, and prog's natural affinity for complex musicianship naturally attracts attention from young musicians everywhere -- those looking to prove themselves, those who would rather not get stuck in the jazz-fusion genre. On the other hand, it's also disheartening to the extent that prog's weak points continue to remain so weak. Pretentious concept records, overly grandiose musicianship, instrument solos that in themselves could compromise a whole symphony, and the ever-pervading obsession with fairy tales, space battles, and mythical creatures -- all of these qualities are as much a part of prog today as they have been in the past. Moreover, the overall tendency of bands failing to progress (which one would assume is a necessary genre component given its title) is also true of many progressive rock bands: Many get stuck in the same old ruts that other prog bands found themselves in, which hampers the overall critical and cultural view of the genre.
These problems inherent to the genre were not the only unfortunate trends in 2011 prog-rock; controversy also played a role in the prog community. The shocking departure of Mike Portnoy from Dream Theater -- the band he helped create -- was hugely important. Dream Theater's stature in contemporary progressive rock is substantial, and to see one of the core members of the band (as well as one of the band's most technically proficient members, which is saying something given the talent present) leave put the band's fate into question. Portnoy has since pursued other projects, such as the prog supergroup (cause there aren't enough of those!) Adrenaline Mob, but from what I've gathered, we still have much to hear from the phenomenal drummer. The best that prog fans can hope for is (a) that Portnoy's departure and subsequent interactions with the band don't cause any rifts, real or manufactured, and (b) that all of the musicians involved can go on to continue making quality music. Fortunately, Portnoy's future plans, as well as the release of another Dream Theater LP, give credence to the fact that all the musicians involved won't stop trying to dazzle us.
All of these things aside, 2011, while not a banner year by any means, was still a good year for prog, with many notable high-profile releases competing for the best-of-the-year title. The general trend seemed to gravitate toward instrumental-based material, though several strong releases by progressive music standbys (notably Porcupine Tree frontman and polymath Steven Wilson) stood out amongst the fray of albums with space-themed covers. This list is encompassing both of progressive rock and, to some extent, progressive metal; though the latter and former genre are not interchangeable, there are important similarities, and as a result, some progressive metal records were included here due to their relevance in the progressive rock genre. (For instance, Between the Buried and Me's suite-like, intricate metal has been used as a more intense counterpoint to the theory-heavy, technical shredding of Dream Theater on the Progressive Nation tours). The resulting top ten list is reflective both of the talent and diversity to be found in prog, whether it's an album about crazy space adventures 2,000 years in the future or a singer/songwriter record that decides to explore some unusual territory. Brice Ezell
Artist: Dream Theater
Album: A Dramatic Turn of Events
Label: Roadrunner
Image: http://images.popmatters.com/music_cover_art/d/dramatic_turn_of_events.jpg
Display Width: 200
Display as: List
List number: 10
It took me a substantial amount of time before I warmed up to A Dramatic Turn of Events. This was so, first and foremost, because my appreciation of Dream Theater has waned since 2005's Octavarium, but, secondly, because I was skeptical of the direction that the band would take after the strange circumstances surrounding founding member Mike Portnoy's departure. Portnoy had been an integral part of the band's central formula; while replacement Mike Mangini is an impressive drummer, Portnoy's unique contribution to the band's output cannot be overlooked. The band has yet to top their 1999 epic, Scenes from a Memory, which is impossible to imagine without Portnoy. Fortunately, with this record, the band has stepped back from the somewhat forced attempts at morphing into a dark metal powerhouse (The doom and gloom of the band's prior album, 2009's Black Clouds and Silver Linings, was a bit much) and have instead gone back to the epic prog at which the band so excelled in the '90s. Dream Theater has always made heavy music, but it wasn't heavy in the way the group had been aiming with records like Black Clouds. A Dramatic Turn of Events is not a perfect record; like many Dream Theater (and prog) LPs, it's too long, and some of the various experiments the band takes come off as haphazard instead of organic. That aside, this record is important, providing two forms of hope for this aging band. For one, sometimes going back to one's origins is the best way to move forward, and also, as brilliant of a drummer as Mike Portnoy is, it is possible for Dream Theater to exist without him.
Artist: Riverside
Album: Memories in My Head
Label: The Laser's Edge
Image: http://images.popmatters.com/reviews_art/r/riverside.jpg
List number: 9
Memories in My Head
Riverside's brand of prog has often marred in comparison to greats like Porcupine Tree and Tool. These comparisons hold a degree of truth ("Forgotten Land" on this EP owes much to the former band), but they tend to be unfairly reductive. The band blends the atmospheric with bass-heavy, dark prog-rock, which it has done quite well over the course of its often overlooked career. Memories in My Head is a solid sampler of the band's sonic skill, as well as proof that Riverside does have a unique sound. The album's opening track, the excellent "Goodbye Sweet Innocence", is both indicative of the band's overall style as well as a notable exercise in dynamics. The band's penchant for powerful basslines is evident on "Forgotten Land", which for a moment makes it sound as if it's about to break into a funk jam, but only for a moment, For those looking for a solid example of Riverside's work, this short but nonetheless powerful EP is an excellent introduction.
Artist: Neal Morse
Album: Testimony 2
Label: InsideOut
Image: http://images.popmatters.com/reviews_art/n/neal_morse.jpg
Neal Morse's 2002 departure from Spock's Beard, which happened simultaneously with his conversion to Christianity, was one of the most notable prog happenings of the last decade. While his departure left many Spock's Beard fans disappointed, it certainly didn't stop Morse at all; his music continued to flourish, peaking incredibly with 2007's magnum opus, Sola Scriptura. Morse, while not associated with the Christian music scene, remains unabashed about his faith in his music, and Testimony 2 is no different. The record, a continuation of the themes found on the first Testimony (from 2003), deals with the story of Morse's conversion. On the whole, the record isn't a departure from Morse's past output by any means, but given Morse's incredible talent, this record does not disappoint (well, save for the GeoCities-worthy sleeve art). Morse even brings in his old Spock's Beard bandmates in to join him in the chorus of "Time Changer", which, while somewhat cheesy, is nonetheless demonstrative of the prog that Morse does so well. At nearly two hours, Testimony 2 shows that while Morse still intends to make overly long records, he at least is still making them great.
Artist: Furyu
Album: Cio Che L'Anima Non Dice
Label: Self-released
Image: http://images.popmatters.com/reviews_art/f/furyu.jpg
Cio Che L'Anima Non Dice
Italian proggers Furyu demonstrate one very important skill on Cio Che L'Anima Non Dice, one which many prog bands lack: brevity. In just over half an hour, the band crafts a record that still manages to sound like epic prog without crossing over the border of musical excess. The record's more intense sonics recall the complicated riffs of Dream Theater and Symphony X, which balances wonderfully with beautiful acoustic passages (like the outro of "La Vastità Del Mio Tempo/Ciò Che L'Anima Non Dice"). The album is sung entirely in Italian, but it's truly accessible to any prog fan, regardless of language. Matteo Migliori's vocals are quite evocative and are a solid accompaniment to the twin guitar attack, which is surprisingly fresh instead of overdone. Cio Che L'Anima Non Dice is one of 2011's finest sleeper releases in the progressive rock scene, and since you can download the album for free, there's no reason not to give this band a listen.
Artist: Between the Buried and Me
Album: The Parallax: Hypersleep Dialogues
Image: http://images.popmatters.com/music_cover_art/0/001pmcover161.jpg
The Parallax: Hypersleep Dialogues
Between the Buried and Me's schizophrenic brand of metal always contained hints of prog, but with 2007's Colors and especially 2009's The Great Misdirect, the band brought more and more prog influences into their already progressive music. Hypersleep Dialogues is a concept record, but one doesn't need to follow the complicated plot to appreciate the even more complicated music. The band takes some adventurous turns; when opening track "Specular Reflection" begins with a dark, flurried choral and symphony prelude, it's clear that things can only get more portentous from there. And given the band's prior displays of over-the-top ambition, it does. With this record, Between the Buried and Me have ventured further into experimental territory, but, if this record is any indication, future results are likely to be equally, if not more, impressive.
Becoming the Archetype Between the Buried and Me Blackfield Dream Theater Furyu Neal Morse Opeth Pain of Salvation Prog rock Progressive rock Riverside Popmatters Picks The Best Musi
Resounding Silence and Profound Superfluity: The Actorly Camera in Jean-Pierre Melville's 'Un flic'
The movements of the camera in Melville's Un flic attempt to overcome one of the most inscrutable divides in existence.
Chadwick Jenkins


The compact and energy-efficient power pack in the WEILER E-Series range.
The allrounder for high productivity applications – minimum space requirements with maximum cutting performance.
High quality, energy-efficient, precise and universally usable.


text:
Pokemon Emerald Party Randomizer Download
March 13, 2022 by Steven Hubs
Pokemon Emerald Party Randomizer is the randomized version of Pokemon Emerald. In the Pokemon Emerald Party Randomizer Plus hack, you have the opportunity to play through not just one but four unique games. In each game, you can play as one of four trainers choosing from a set of 10 different trainers of assorted genders and regions. The Gold version is a randomized version of the original Pokemon Ruby Version story with trades included. The Silver Version is a randomized version of the original Pokémon Sapphire Version story with trades included.
Complete Game File Details:
Complete Walkthrough of Pokemon Emerald Party Randomizer GBA Hack:
Gym leader:
Legendary Pokemons:
Some Amazing Features in Pokemon Emerald Party Randomizer ROM:
Download Pokemon Emerald Party Randomizer ROM Hack Game:
Pokémon Emerald was a great game for many reasons. It included the ability to collect all three starters, which is not possible in any of the other Pokémon games. It also offered players additional challenges that could be completed with just one starter, or even without a starter at all.
One of these challenges was known as the "Emerald Party Randomizer Challenge" where trainers are not allowed to have two Pokémon of the same type on their team. This is a new type of game which changes the movesets and item selections for every trainer in the Johto region. This means every time you play, no two trainers will have the same Pokemon, items, or set of moves.
Game Name: Pokemon Emerald Party Randomizer
Remake: Emerald
Creator: Souma
Pokemon Emerald Party Randomizer (PEPR) is a tool for the Game Boy Advance and Nintendo DS games Pokémon Emerald and Pokémon FireRed. It randomly shuffles the party in Pokemon Emerald and FireRed to help shuffle around items to make it more challenging and adds in new items that were not in the original game, such as TMs. It was created by an unknown author. Players are able to play as the evil team and capture every gym in order. The Randomizer also includes a variety of other options, such as an "Evolving Wild Pokemon" option that allows players to customize their experience with specific rules. This is one of many Pokemon ROM hacks that are available for download on the popular website, Github. Also, tryPokemon Ash Hoenn
The party randomizer is an updated version of the randomizer created by Vaporeon7. The updated version features new features, such as seeding the randomized team with a set amount of Pokemon to optimize chances for certain level ranges, and adding an option to randomize Mega Stones. It also fixes two bugs that were present in the original randomizer. The updated update also no longer crashes if one tries to give a Pokemon a nickname. It possible to create a new playthrough of the game in which the party is randomized at the start of every battle. So, instead of having six predetermined Pokemon with fixed movesets when you begin your journey, you can have a completely different set for each battle, giving a fresh way to experience Emerald.
The Pokemon Emerald Party Randomizer is an application that endlessly generates randomized parties for the player to battle. The party can be set up with nearly any combination of desired attributes, such as type alignment, species, moveset, level, and gender. The generator's results are then calculated by probability tables, which is a mathematical formula that predicts the chance of finding a specific Pokémon in an attempt to hatch eggs. What makes Pokemon Emerald different from other games in this series is that there are 11 legendaries to catch instead of 6. However, because of the limitations of the system, you can only get 9 of them without cheating or changing your game file. If you're looking for a good challenge (and not just the usual one) then Pokémon Emerald Party Randomizer can help! Also, try Pokemon Ash Journey
The Gym Leader in Pokemon Emerald Party Randomizer is a glitch that will crash your game if you try to battle them. Heatran has been a gym leader of the Pokemon Emerald party randomizer for years. He's waiting to get more challengers in the future of this project, but he would have to wait until more of his fellow creators finish their work on it. Heatran loves his job and will continue to do so until he believes everything is ready.
Aren't you tired of the same old Pokemon parties? Have you ever wished that your Pokemon's personalities and strengths would change every time you started a new game? Well, worry no longer! We here at Randomize My Teddies have created a Pokemon Emerald Party Randomizer for you! Simply input the generator with the original stats and abilities of your character, and we'll give you 10 different characters to explore in party mode.
The first few gym leaders – the ones before the Elite Four -are actually just trainers that you always fight as NPCs and never as gym leaders. These trainers will be easier than they were when you fought them the first time, but still difficult enough to be challenging. The gym leaders in Emerald are much more powerful, much more plentiful, much less useful, and much more prone to changing between seasons. Because of the nature of the trainers you fight before and after each match, it's impossible to get a true feel for how strong any of them are. They all seem like these high-level and low-level and mean and nice guys who can't be beat or beaten by me. Also, try Pokemon Ash Johto Download (Updated)
It is a game that challenges the player to defeat all of the gym leaders in randomized order, with no use of any items or leveling up. The game does not allow the player to capture any Pokémon except for the final boss in each gym. There are 469 different possible teams that can be faced when playing this game, though some are more difficult than others.
The randomizer was a tool for players of pokemon emerald to create a new playthrough without the repetitive grinding. It also had a feature that allowed you to choose if you wanted to use legendaries or not, that way those who didn't want to catch all of them from scratch could avoid that frustration. Fans of the Pokemon Emerald version of the Pokemon series will be excited to know that there is a new way to enjoy it. A group of students collaborated and created an online program that randomizes everything in the game, including which Pokemons you encounter and where they are found. This means you will never get the same experience twice!
The following article discusses the process of generating legendary pokemons in Pokemon Emerald Party Randomizer. This game is a modification of Pokemon Emerald, which has been programmed to be randomized by the player at the start of the game. The player can choose to either play with or without legendaries, though they will always be available for capture if they choose to include them. The game changes each time you play it, whether you're playing alone or with friends. Players never know what might happen when they boot up the game. One minute they might be struggling to take down a wild Pokemon in the tall grass, and in the next minute they might find themselves in a battle with Professor Birch in his lab. It's unpredictable and exciting every time! Also, try Pokemon Raptor Ex Download
Players place bets on which Pokémon they think will show up in each round of battles, earning more money if they get it right. The party randomizer also has the capability of increasing the level of your opponent's Pokémon, but this can be turned off if desired. The party randomizer is a tool that can be used to mix up the teams you battle in Pokemon Emerald. It's very common for players to think they know everything about the game after they defeat the Elite Four, but what they don't know is that there are many legendary Pokemons hidden within the game's code. Also, try Pokemon Ash Orange League Download (Updated)
Explore the Johto and Kanto Regions.
An awesome tool that makes every battle of the game more interesting because each battle will be a different experience. It contains every piece of information, including level and IVs of every pokemon in your party at beginning of every battle.
The party randomizer is a modification of Pokemon Emerald that has been programmed to be randomized by the player at the start of the game.
Players can choose to either play with or without legendaries, though they will always be available for capture if they choose to include them
Way of strangers and closest friends.
Pokemon Naranja Game Download (Updated 2023) Pokemon Perfect Red Download (Latest Version) Pokemon Pitch Black Download (Updated) Pokemon Hoenn White EX Download (Updated)
Categories GBA, Pokemon Hacks Tags English, GBA, Pokemon Emerald Party Randomizer, Pokemon Emerald Roms
Pokemon Ash Hoenn Download (Updated)
Pokemon Naruto Shippuden Advance Ninja Showdown

redpajama_set_name: RedPajamaCommonCrawl


The Philips BHD007/20 Foldable Travel Hair Dryer, equipped with the ThermoProtect temperature setting, blow dries your hair quickly at a constant temperature. This portable hair dryer with hook, located at the base of the handle, offers convenient storage. You get optimum level of airflow and gentle drying with this 1600 W hair dryer. Its 1.8 m cord allows flexibility of movement.


?oncept: This photo series is based on symbols and metaphors and represents the fragility of human consciousness, which is influenced by mass media and the hypocrisy of the modern society, which is too obsessed with consuming to notice being manipulated. Black and white colours are used to emphasize the edge between good and evil, that humanity is balancing on.
The bandages show our society's sick priorities.The marks on the model's body, resembling those made by cosmetic surgeons on the skin of their patients, represent the vain attempts of the ruling class to cover the ugly truth.


text:
Sea Island Luxury Interior Designer, VPI Design, Launches Redesign of Website
Top Luxury Interior Designer, VPI Design by Dina Varner, announces a new website design and Instagram page.
ATLANTA, GA / ACCESSWIRE / September 15, 2020 / Talented and sought-after Sea Island Luxury Interior Designer launches a 2020 re-design of both the firm's website, https://vpi-design.com, and Instagram page https://instagram.com/luxuryinteriors.redefined. The vision for the re-design was to highlight a visual experience that is both simplistic yet elegant. Founder and creative director of VPI Design, Dina Varner, wanted all aspects of the details of their work to be the focal point. "I wanted our website to reflect the story we tell within each room we design, but I wanted to tell it in a way where viewers were captivated by large-scale imagery that flowed seamlessly to allow the eye to hone in on the details, whether that be the texture of a throw pillow, or the way the reflection of light bounces throughout the space."
The new website design incorporates VPI Design's unique branding identity with the phrase "Redefining Luxury Interiors." Varner explains, "I view design as making thoughtful choices with carefully selected curated elements which can include custom pieces such as art, fabrics, and furniture that create a seamless design." By meticulously placing these components it allows the elements to work together to create an interior that reflects the vision of our client. What sets VPI Design apart from other designers is our experience and approach to 'redefining luxury interiors.' Each project is a collaborative effort of function, comfort and commitment to detail, allowing for a desired end result.
About VPI Design by Dina Varner
Dina Varner is founder and creative director of VPI Design, an Atlanta and Sea Island Interior Design Firm working with both residential and commercial clients. She and her husband have been in the commercial construction industry for many years. Her inspiration comes from over twenty-five years of collecting and selling art and antiques through venues like Sotheby's, Babcock Gallery, and Christie's. This love of art and antiques started as a passion and has evolved into a successful business. Dina's rich southern heritage in addition to her love of fashion and travel also act as her creative influence. The VPI Design team work together with a distinct flair for aesthetic insight into unique designs exhibiting elegance and style. They explore the use of light and texture for an organic appealing experience in every timeless interior. Combinations of art deco, vintage, and contemporary styles are combined to create elegance while simultaneously exuding simplicity and comfort in each living space. Her designers enjoy getting to know their clients personally to create a home that suits their individual taste. Dina believes that every aspect of a room should complement one another to tell a unique story.
For more information please visit: https://vpi-design.com
VPI Design by Dina Varner
Contact Name: Dina Varner
Website: https://vpi-design.com
Instagram: https://www.instagram.com/luxuryinteriors.redefined
SOURCE: VPI Design
https://www.accesswire.com/606243/Sea-Island-Luxury-Interior-Designer-VPI-Design-Launches-Redesign-of-Website
Tags: design, Designer, interior, Island, launches, Luxury, redesign, Sea, VPI, Website
Fall home decor trends: Comforting hues, flexible design
Woodward says there was 'denial across the board' in White House about severity of coronavirus


Of all the labels that one can apply to a modern liberal state, "Nanny State" is to me the most pejorative. Living as I do in a city that is run according to "Nanny State ideology, it affects me personally.
I am very much in favour of educating people to make healthy choices. I have smoked heavily and drank with greater regularity than is healthy . I have noted that my lungs are not the strongest and that my pancreas likes to go on vacation. As much as it galls me to be lectured by my mayor or a sanctimonious relative at a family reunion, I have scored some successes in my battle with bad habits. Following are some moments in which I found the inner strength to kick habits that were killing me. They are as follows.
When my wife was pregnant with our second child, I visited my parents for a weekend. My father was wheelchair bound after two strokes. In a quiet, earnest voice, he told me as follows.
"I have never smoked in my life. Maybe I got drunk two or three times by accident. I certainly didn't do it on purpose. Here I am at 57 years of age in a wheelchair. You smoke three packs a day, and you are 28 years old. You have half of my genes. Where will you be at my age?
I chain smoked the rest of that weekend. The night before I left I made a commitment to my father that I would quit smoking. Withdrawal was hell. I was miserable to live with. I almost got fired from my job. That was 24 years ago. I have been jettisoning bad habits as life's storms push me to the tipping point. I still struggle.
A few years ago, I went for a routine checkup. My doctor called me up personally and told be to proceed to the nearest hospital. My sugar was 657. The doctors were surprised that I was lucid and ambulatory. From the hospital I heard that two of my daughters were crying about me being in the hospital. Although I still struggle, I have the feeling that eating white flour, failing to test my sugar level and other acts of neglect are choosing transitory physical pleasures over enjoying a long life with my family. Family reunions really drive home to me that the people who are seated at the table are far more important than what is on it.
When I was in high school, I developed an enduring dislike for "weed fascists" who considered it their mission to talk as many classmates as possible into getting high. I am so sensitive to the stuff that even being in a room where it is being smoked makes me react to it. I don't like the stuff. Get over it. And while we are on the subject, I enjoy alcohol a lot less as I get older. someone once was trying to talk me into loading a cup up with vodka. I finally said "OK fill it up."
I held my cup out and at the last minute turned it up side down. The bottom of the cup had an indentation sufficient to hold a few drops of scotch.
This is my rule. I will decide for myself if and when I want a buzz. Back off if I say no. If you are so obnoxious that I need to chemically alter my mental state to be with you, I don't want to be around you.
I make small talk with smokers. Quite a few people tell me they smoke less than 5 cigarettes a day. I always tell them to smoke one for me. I like the smell of tobacco. I enjoyed smoking. I had to give it up. I believe that there is a smoker's personality. Even ex smokers have it. I prefer to be around smokers. I like the smoker's personality.
I also enjoy the company of recovered alcoholics. People who have had to give up drink have often gained deep insights into themselves and others. What an alcoholic learns in his or her struggles can be of use to the rest of us.
I miss jelly donuts and food loaded with sugar. Whenever I see someone eating that type of food, I always tell them to eat another portion for me.
There is a critical difference between the words "compel" and "impel" . I reflect frequently upon that. When a person has internalised knowledge in such a way that they feel they must do something, it is far more profound a change than when they are externally compelled. Forcing people to make health decisions they are not ready for deprives them of opportunities for spiritual and emotional growth.
Moral decisions are ultimately for our own good. Years ago, I stopped by the home of a divorced friend whose irresponsibility led to the breakup of his marriage. I will never forget the expression on his face when his daughter told him in a matter of fact manner that mommy was out on a date.
While I am on the subject of divorce, it is not just looks that are hereditary. Emotional traits and learning patterns also have genetic roots. I can't count the number of times that I understand immediately one of my children's difficulties in learning and socialisation from first or second hand experience growing up. There are some great step parents, probably millions of them. Some are probably better than the biological parent. But common genes do make a difference. They are certainly a good card to have in your hand in the game of parenting. Why throw it out if you can avoid doing so?
Love for my family has always been a more powerful motive for making healthy choices than bluenose preachers or nanny state mayors. I still would rather blog than exercise, and that is a problem. My wife wants to hook my laptop up to a bicycle powered generator so I will burn off calories as I blog. If I could buy such a thing, I would use it in a heartbeat.
Arriving at the point where you are ready to trade physical enjoyment for longevity and a better quality of life is a very personal decision. Each person has a different constitution and different goals. The best we can do is to encourage each other as we chase our respective dreams. Kicking a bad habit, whether it is an emotional habit or a physical one has to be a free will decision for it to really take root. And what ultimately is freedom? Freedom is knowing what's right and doing it. It is arriving at that spark of insight where it appears as though there really is no choice. Sometimes even family, and certainly the state has to step back and let such a moment of insight take place.
I tried to quit smoking three times. The first two times were not failures. I learned about my self with each successive try at that and at any other goal. When you finally succeed, all your failures cease to be failures.
You can tax me and fine me. You may even make it impossible to have any bad habits at all. But how can a compulsion make up for the knowledge of self that comes through struggle and introspection? Perhaps the state can give you years. But it can not give you life.


18 мар 2013 Rebug 4.30.2 REX Edition с обновлённым Rebug Toolbox. Цитата. REBUG ADDED – Toggle QA support for all 3.55/4.21/4.30/4.31. Jan 9, 2011 . Rebug 4.81.2 REX . in which you can download plugins such as TV channels and Torrent Streamers. . A. If your PS3 is on 3.55 firmware or below, you can jailbreak it regardless of model. . It is a limited version Games Tested with IRISMAN 3:48 Unofficial & multiMAN 4.75.55: . gdljjrod has released version 2.2 of the PS Vita / PlayStation TV utility . Page 1 of 5 1 2 3 4 5 Next > . I decided to do a completely clean install, I returned to ofw 3.55, and . edit: btw, I did test the theme. it's named rebug.
Sep 7, 2015 Version 4.75.3 brings you now 4.76 Firmware spoofing which was needed plugins in Version 4.75.2, however Version 4.75.3 fixes this Bug and is now available at Rebug.me Also 3.56 base OFW can install CFW but if you downgrade to 3.55 it will Latest entries on our Smart TV dedicated sister. Jan 10, 2017 Official – Rebug 4.81.2 – Cobra 7.5 – Toolbox 2.02.12 – Jan 10th. 7.5 EDITION – INSTALL ON DEX PS3 SYSTEM REBUG 4.81.2 D-REX. Discussion in 'PS3 News' started by STLcardsWS, Nov 2, 2016. Following the release 4.81 FERROX Standard Edition CFW, You cannot downgrade an official firmware > 3.55 with a PUP. This FW possibly used old versions of the Rebug xmls I think and that is why it VITA / PS TV PSTV Whitelister. 10 апр 2016 Консоли с дата-кодом 1C и 1D, а также с цифрой 2 даунгрейду не поддаются PS3 Super Slim - PlayStation 3 Super Slim прошить на данный момент нельзя! Использовать Minimum Version Checker - com/doc- прошивки с 4.60 rogero на 4.80.01 от rebug все настроил как.


text:
Hiker, missing for five days, found alive in Strathcona Park
Search crew discovered Naswell, 50, in cabin early Monday afternoon
Mike Chouinard
The local hiker missing since last week in Strathcona Park has been found alive.
Comox Valley Ground Search and Rescue (CVGSAR) has confirmed one of its teams found Murray Naswell, 50, of Cumberland alive in a cabin at Moat Lake in the park shortly after 12 p.m. on Monday.
"He has been found alive and well," said Paul Berry of CVGSAR. "We like happy endings."
He added Naswell's family has been notified.
RELATED STORY: Comox Valley SAR looking for missing local hiker in Strathcona Park
Naswell went missing after he was supposed to summit Mount Albert Edward last Wednesday with a couple he'd met on the trail. They turned back, but he continued, leaving behind his equipment. He was wearing only basic clothing and had a fanny pack with him. One of the teams found he had left behind some identification at the cairn on the mountain. SAR teams continued searching for him through the weekend, though had difficulty because of foggy weather.
CVGSAR expanded their search Monday, with teams from the Lower Mainland and Vancouver Island. In all, there were 120 searchers, aided by four search dogs and two helicopters.
Ground searchers found Naswell in a cabin on an island in Moat Lake. As to his physical condition, Berry said they have not yet interviewed him, as he is with BC Ambulance Service currently.
Canadian aid worker jailed 16 years in Nepal for sex assault of boys
Swoop hit by ongoing wave of flight cancellations as passengers vent frustration
Bantam Wild secures spot at lacrosse provincials
It's been a wild ride to the provincial tournament for the Comox…
Comox Valley featured in B.C. rugby lineups
Provincial teams named for U16 Western Championships


text:
Q: Minimum possible value of r Suppose a machine shows a particular reading (R) dependent on the weight (w) put on it, given by: $$R(w) = \frac{50e^w}{10+e^w}$$
Find the minimum possible value of r such that R(w)< r for all w, where r belongs to integers.
I am not getting any idea on how to proceed. The correct answer is 50

A: It looks like this problem is just asking for a maximum (or, more specifically, the upper bound of the function). Here's how we get 50:
$$y = \frac{50e^x}{10+e^x}$$
$$y = \frac{e^x}{e^x}\frac{50}{\frac{10}{e^x}+1}$$
$$y = \frac{50}{\frac{10}{e^x}+1}$$
$$\lim_{x\to\infty} \frac{50}{\frac{10}{e^x}+1} = 50$$
This works because $y$ is always increasing. We could also find the minimum by taking $lim_{x\to -\infty} \frac{50}{\frac{10}{e^x}+1}$, which yields 0. Therefore, $R = \{y\in\mathbb{R} \mid 0 < y < 50\}$ and $r=50$.  A look at the graph confirms this.

redpajama_set_name: RedPajamaStackExchange


text:
\section{Introduction}
Photometric stereo aims at recovering the surface normal of a static object from a set of images captured under different light directions~\cite{woodham1980ps,silver1980determining}. \emph{Calibrated} photometric stereo methods assume known light directions, and promising results have been reported~\cite{shi2018benchmark} at the cost of tedious light source calibration. The problem of \emph{uncalibrated} photometric stereo, where light directions are unknown, still remains an open challenge, and its stable solution is wanted because of the ease of setting. In this work, we study the problem of uncalibrated photometric stereo for surfaces with general and unknown isotropic reflectance.

Most of the existing methods for uncalibrated photometric stereo~\cite{alldrin2007r,shi2010self,papad14closed} assume a simplified reflectance model, such as the Lambertian model, and focus on resolving the shape-light ambiguity, such as the Generalized Bas-Relief (GBR) ambiguity~\cite{belhumeur1999bas}. Although methods of~\cite{lu2013uncalibrated,lu2015uncalibrated} can handle surfaces with general bidirectional reflectance distribution functions (BRDFs), they rely on a uniform distribution of light directions for deriving a solution.

Recently, with the great success of deep learning in various computer vision tasks, deep learning based methods have been introduced to calibrated photometric stereo~\cite{santo2017deep,Taniai18,ikehata2018cnn,chen2018ps}. Instead of explicitly modeling complex surface reflectances, they directly learn the mapping from reflectance observations to surface normals given light directions. Although they have obtained promising results in a calibrated setting, they cannot handle the more challenging problem of \emph{uncalibrated} photometric stereo, where light directions are unknown. One simple strategy to handle uncalibrated photometric stereo with deep learning is to directly learn the mapping from images to surface normals without taking the light directions as input. However, as reported in~\cite{chen2018ps}, the performance of such a model lags far behind those which take both images and light directions as input.

In this paper, we propose a two-stage model named Self-calibrating Deep Photometric Stereo Networks (SDPS-Net) to tackle this problem. The first stage of SDPS-Net, denoted as \emph{Lighting Calibration Network} (LCNet), takes an arbitrary number of images as input and estimates their corresponding light directions and intensities. The second stage of SDPS-Net, denoted as \emph{Normal Estimation Network} (NENet), estimates a surface normal map of a scene based on the lighting conditions estimated by LCNet and the input images. The rationales behind the design of our two-stage model are as follows. First, lighting information is very important for normal estimation since lighting is the source of various cues, such as shading and reflectance, and estimating the light directions ($3$-vectors) and intensities (scalars) is in principle much easier than directly estimating the normal map (a $3$-vector at each pixel location) together with the lighting conditions. Second, by explicitly learning to estimate light directions and intensities, the model can take advantage of the intermediate supervision, resulting in a more interpretable behavior. Last, the proposed LCNet can be seamlessly integrated with existing calibrated photometric stereo methods, which enables them to deal with unknown lighting conditions.
Our code and model can be found at \url{https://guanyingc.github.io/SDPS-Net}.

\section{Related Work}
In this section, we review learning based photometric stereo and uncalibrated photometric stereo methods. We also briefly review the loosely related work on learning based lighting estimation. Readers are referred to~\cite{shi2018benchmark} for a comprehensive survey on calibrated photometric stereo with Lambertian surfaces and general BRDFs using non-learning based methods.

\vspace{-1.3em}
\paragraph{Learning based photometric stereo}
Recently, a few deep learning based methods have been introduced to calibrated photometric stereo~\cite{santo2017deep,Taniai18,ikehata2018cnn,chen2018ps}. Santo~\etal~\cite{santo2017deep} proposed a fully-connected network to learn the mapping from reflectance observations captured under a pre-defined set of light directions to surface normal in a pixel-wise manner. Taniai and Maehara~\cite{Taniai18} introduced an unsupervised learning framework that predicts both the surface normals and reflectance images of an object. Their model is ``trained'' at test time for each test object by minimizing the reconstruction loss between the input images and the rendered images.
Ikehata~\cite{ikehata2018cnn} introduced a fixed shape representation, called observation map, that is invariant to the number and permutation of the images. For each surface point of the object, all its observations are merged into an observation map based on the given light directions, and the observation map is then fed to a convolutional neural network (CNN) to regress the normal vector. Chen~\etal~\cite{chen2018ps} proposed a fully-convolutional network (FCN) to infer the normal map from the input image-lighting pairs, and an order-agnostic max-pooling operation was adopted to handle an arbitrary number of inputs. All the above methods assume known lighting conditions and cannot handle uncalibrated photometric stereo, where the light directions and intensities are not known a priori.

\vspace{-1.3em}
\paragraph{Uncalibrated photometric stereo}
When lighting is unknown, the surface normals of a Lambertian object can only be estimated up to a $3\times 3$ linear ambiguity~\cite{hayakawa1994photometric}, which can be reduced to a $3$-parameter GBR ambiguity~\cite{belhumeur1999bas,yuille1999determining} using the surface integrability constraint. Previous work used additional clues like albedo priors~\cite{alldrin2007r,shi2010self}, inter-reflections~\cite{chandraker2005reflections}, specular spikes~\cite{drbohlav2005can}, Torrance and Sparrow reflectance model~\cite{georghiades2003incorporating}, reflectance symmetry~\cite{tan2007isotropy,wu2013calib}, multi-view images~\cite{esteban2008multiview}, and local diffuse maxima~\cite{papad14closed}, to resolve the GBR ambiguity. Cho~\etal~\cite{cho2016photometric} considered a semi-calibrated case where the light directions are known but not their intensities. There are few works that can handle non-Lambertian surfaces under unknown lighting. Hertzmann and Seitz~\cite{hertzmann2005example} proposed an exemplar based method by inserting an additional reference object to the scene. Methods based on cues like similarity in radiance changes~\cite{sato2007shape,lu2013uncalibrated} and attached shadow~\cite{okabe2009attached} were also introduced, but they require the light sources to be uniformly distributed on the whole sphere. Recently, Lu~\etal~\cite{lu2018symps} introduced a method based on the ``constrained half-vector symmetry'' to work with non-uniform lightings. Different from these traditional methods, our method can deal with surfaces with general and unknown isotropic reflectance without the need of explicitly utilizing any additional clues or reference objects, solving a complex optimization problem at test time, or making assumptions on the light source distribution. The work most related to ours is the UPS-FCN introduced in~\cite{chen2018ps}. UPS-FCN is a single-stage model that directly regresses surface normals from images that are normalized by the known light intensities. Its performance lags far behind the calibrated methods. In contrast, our method solves the problem in two stages. We first tackles an easier problem of estimating the light directions and intensities, and then estimates the surface normals using the estimated lightings and the input images.

\vspace{-1.3em}
\paragraph{Learning based lighting estimation}
Recently, learning based single-image lighting estimation methods have attracted considerable attention. Gardner~\etal~\cite{gardner2017learning} introduced a CNN for estimating HDR environment lighting from an indoor scene image. Hold-Goeffroy~\etal~\cite{hold2017deep} learned outdoor lighting using a physically-based sky model. Weber~\etal~\cite{weber2018learning} estimated indoor environment lighting from an image of an object with known shape. Zhou~\etal~\cite{Zhou_2018_CVPR} estimated lighting, in the form of Spherical Harmonics, from a human face image by assuming a Lambertian reflectance model. Different from the above methods, our method can estimate accurate directional lightings from multiple images of a static object with general shape and non-Lambertian surface.

\begin{figure*}[t] \centering
    \includegraphics[width=\textwidth]{images/Method/LCNet_NENet.pdf}\\
    \caption{The network architecture of SDPS-Net is composed of (a) Lighting Calibration Network and (b) Normal Estimation Network. Kernel sizes for all convolutional layers are $3\times 3$, and values above the layers indicate the number of feature channels.} \label{fig:network}
\end{figure*}

\section{Image Formation Model}
Following the conventional practice, we assume an orthographic camera with linear radiometric response, white directional lightings coming from the upper-hemisphere, and the viewing direction pointing towards the viewer.
In the rest of this paper, we refer to light direction and intensity as ``lighting''.
Consider a non-Lambertian surface whose appearance is described by a general isotropic BRDF $\rho$. Given a surface point with normal $\boldsymbol{n} \in \mathbb{R}^3$ being illuminated by the $j$-th incoming lighting with direction $\boldsymbol{l}_j \in \mathbb{R}^3$ and intensity $e_j \in \mathbb{R}$, the image formation model can be expressed as
\begin{equation}
    m_j = e_j \rho (\boldsymbol{n}, \boldsymbol{l}_j)~\text{max}(\boldsymbol{n}^\top \boldsymbol{l}_j, 0) + \epsilon_j,
\end{equation}
where $m$ represents the measured intensity, $\text{max}(:, 0)$ accounts for attached shadows, and $\epsilon$ accounts for the global illumination effects (cast shadows and inter-reflections) and noise.

Based on this model, given the observations of $p$ surface points under $q$ different incoming lightings, the goal of uncalibrated photometric stereo is to estimate the surface normals for these $p$ surface points given only the measured intensities.
In this work, we tackle this problem using a two-stage approach. In particular, we first estimate lightings from the measured intensities, and then solve for the surface normals using the estimated lightings and measured intensities.

\section{Learning Uncalibrated Photometric Stereo}
In this section, we introduce our two-stage framework, called SDPS-Net, for uncalibrated photometric stereo (see \fref{fig:network}). The first stage of SDPS-Net, denoted as \emph{Lighting Calibration Network} (LCNet, \fref{fig:network}~(a)), takes an arbitrary number of images as input and estimates their corresponding light directions and intensities. The second stage of SDPS-Net, denoted as \emph{Normal Estimation Network} (NENet, \fref{fig:network}~(b)), estimates an accurate normal map of the object based on the lightings estimated by LCNet and the input images.

\subsection{Lighting Calibration Network}
To estimate lightings from the images, an intuitive approach would be directly regressing the light direction vectors and intensity values.
However, we propose that formulating the lighting estimation as a classification problem is a superior choice, as will be verified by our experiments. Our arguments are as follows. Fist, classifying a light direction into a certain range is easier than regressing the exact value(s), and this will reduce the learning difficulty. Second, taking discretized light directions as input may allow NENet to better tolerate small errors in the estimated light directions.

\vspace{-1.0em}
\paragraph{Discretization of lighting space} Since we cast our lighting estimation as a classification problem, we need to discretize the continuous lighting space. Note that a light direction in the upper-hemisphere can be described by its azimuth $\phi \in [0\degree, 180\degree]$ and elevation $\theta \in [-90\degree, 90\degree]$ (see \fref{fig:coord}~(a)). We can discretize the light directoin space by evenly dividing both the azimuth and elevation into $K_d$ bins, resulting in $K_d^2$ classes (see \fref{fig:coord}~(b)). Solving a $K_d^2$-class classification problem is not computationally efficient, as the softmax probability vector will have a very high dimension even when $K_d$ is not large (\eg, $K_d^2=1,296$ when $K_d=36$).
Instead, we estimate the azimuth and elevation of a light direction separately, leading to two $K_d$-class classification problems. Similarly, we evenly divide the range of possible light intensities into $K_e$ classes (\eg, $K_e=20$ for a possible light intensity range of $[0.2, 2.0]$).

\begin{figure} \centering
    \input{figures/spherical_coord2}
    \raisebox{0.05\height}{\includegraphics[width=0.21\textwidth]{images/Method/hemisphere.pdf}} \\
    \vspace{-0.9em} \makebox[0.23\textwidth]{\small (a)} \makebox[0.21\textwidth]{\small (b)} \\
    \caption{(a) Illustration of the coordinate system ($z$ axis is the viewing direction). $\phi \in [0\degree, 180\degree]$ and $\theta \in [-90\degree, 90\degree]$ are the azimuth and elevation of the light direction, respectively. (b) Example discretization of the light direction space when $K_d=18$.} \label{fig:coord}
\end{figure}

\vspace{-1.0em}
\paragraph{Local-global feature fusion}
A straightforward approach to estimate the lighting for each image is simply taking a single image as input, encoding it into a feature map using a CNN, and feeding the feature map to a lighting prediction layer. It is not surprising that the result of such a simple solution is far from satisfactory. Note that the appearance of an object is determined by its surface geometry, reflectance model and the lighting. The feature map extracted from a single observation obviously does not provide sufficient information for resolving the shape-light ambiguity. Thanks to the nature of photometric stereo where multiple observations of an object are considered, we propose a local-global feature fusion strategy to extract more comprehensive information from multiple observations.

Specifically, we separately feed each image into a shared-weight feature extractor to extract a feature map, which we call \emph{local feature} as it only provides information from a single observation. All local features of the input images are then aggregated into a \emph{global feature} through a max-pooling operation, which has been proven to be efficient and robust on aggregating salient features from a varying number of unordered inputs~\cite{wiles2017silnet,chen2018ps}. Such a global feature is expected to convey implicit surface geometry and reflectance information of the object which help resolve the ambiguity in lighting estimation. Each local feature is concatenated with the global feature, and fed to a shared-weight lighting estimation sub-network to predict the lighting for each individual image. By taking both local and global features into account, our model can produce much more reliable results than using the local features alone. We empirically found that additionally including the object mask as input can effectively improve the performance of lighting estimation, as will be seen in the experiment section.

\vspace{-1.0em}
\paragraph{Network architecture}
LCNet is a multi-input-multi-output (MIMO) network that consists of a shared-weight \emph{feature extractor}, an \emph{aggregation layer} (\ie, max-pooling layer), and a shared-weight \emph{lighting estimation sub-network} (see \fref{fig:network}~(a)).
It takes the observations of the object together with the object mask as input, and outputs the light directions and intensities in the form of softmax probability vectors of dimension $K_d$ (azimuth), $K_d$ (elevation) and $K_e$ (intensity), respectively.
We convert the output of LCNet to $3$-vector light directions and scalar intensity values by simply taking the middle value of the range with the highest probability\footnote{We have experimentally verified that alternative ways like taking the expectation of the probability vector or performing quadratic interpolation in the neighborhood of the peak value do not improve the result.}.

\vspace{-1.0em}
\paragraph{Loss function}
Multi-class cross entropy loss is adopted for both light direction and intensity estimation, and the overall loss function is
\begin{align}
    \label{eq:cls_loss}
    \mathcal{L}_{\text{Light}} & = \lambda_{l_a} \mathcal{L}_{l_a} + \lambda_{l_e} \mathcal{L}_{l_e} + \lambda_e \mathcal{L}_e,
\end{align}
where $\mathcal{L}_{l_a}$ and $\mathcal{L}_{l_e}$ are the loss terms for azimuth and elevation of the light direction, and  $\mathcal{L}_e$ is the loss term for light intensity. During training, weights $\lambda_{l_a}$, $\lambda_{l_e}$ and $\lambda_e$ for the loss terms are set to $1$.

\subsection{Normal Estimation Network}
NENet is a multi-input-single-output (MISO) network. The network architecture of NENet is similar to PS-FCN~\cite{chen2018ps}, consisting of a shared-weight \emph{feature extractor}, an \emph{aggregation layer}, and a \emph{normal regression sub-network} (see \fref{fig:network}~(b)). The key difference between NENet and PS-FCN is that PS-FCN requires accurate lightings as input, whereas NENet is trained with discretized lightings estimated by the LCNet and shows a more robust behavior over noise in the lightings.

NENet first normalizes the input images using the light intensities predicted by LCNet, and then concatenates the light directions predicted by LCNet with the images to form the input of the shared-weight feature extractor. Given an image of size $h\times w$, the loss function for NENet is
\begin{align}
    \label{eq:normal}
    \mathcal{L}_{\text{Normal}} = \frac{1}{hw} \sum_{i}^{hw} \left(1 - \boldsymbol{n}_i^\top \tilde{\boldsymbol{n}}_{i} \right),
\end{align}
where $\boldsymbol{n}_{i}$ and $\tilde{\boldsymbol{n}}_{i}$ denote the predicted normal and the ground-truth normal, respectively, at pixel $i$.

\subsection{Training Data}
We adopted the publicly available synthetic Blobby and Sculpture datasets~\cite{chen2018ps} for training.
Blobby and Sculpture datasets provide surfaces with complex normal distributions and diverse materials from MERL dataset~\cite{matusik2003merl}. Effects of cast shadow and inter-reflection were considered during rendering using the physically based raytracer Mitsuba~\cite{jakob2010mitsuba}. There are $85,212$ samples in total. Each sample was rendered under $64$ distinct light directions sampled from the upper-hemisphere with uniform light intensity, resulting in $5,453,568$ images ($85,212 \times 64$). The rendered images have a dimension of $128\times 128$.

To simulate images under different light intensities, we randomly generated light intensities in the range of $[0.2, 2.0]$ to scale the magnitude of the images (\ie, the ratio of the highest light intensity to the lowest one is $10$)\footnote{Note that the ratio (other than the exact value) matters, since light intensity can only be estimated up to a scale factor.}. Note that this selected range contains a wider range of intensity value than the public photometric stereo datasets like DiLiGenT benchmark~\cite{shi2018benchmark} and Gourd\&Apple dataset~\cite{alldrin2008p}. The color intensities of the input images were normalized to the range of $[0, 1]$.
During training, we applied noise perturbation in the range of $[-0.025, 0.025]$ for data augmentation, and the input image size for LCNet and NENet was $128\times 128$. At test time, NENet can take images of different dimensions, while the input for LCNet is rescaled to $128\times 128$ as it contains fully-connected layers and requires the input to have a fixed spatial dimension. Trained only on the synthetic dataset, we will show that our model can generalize well on real datasets.

\section{Experimental Results}
We performed network analysis for our method, and compared our method with the previous state-of-the-art methods on both synthetic and real datasets.

\paragraph{Implementation details}
Our framework was implemented in PyTorch~\cite{paszke2017pytorch} and Adam optimizer~\cite{kingma2014adam} was used with default parameters.
LCNet and NENet contain $4.4$ million and $2.2$ million parameters, respectively.
We first trained LCNet using a batch size of $32$ for $20$ epochs until convergence, and then trained NENet from scratch given the lightings estimated by LCNet with a batch size of $16$ for $10$ epochs.
We found that end-to-end fine-tuning did not improve the performance.
The learning rate was initially set to $0.0005$ and halved every $5$ and $2$ epochs for LCNet and NENet, respectively.
It took about $22$ hours to train LCNet and $26$ hours to train NENet on a single Titan X Pascal GPU with a fixed input image number of $32$.

\vspace{-1.1em}
\paragraph{Evaluation metrics}
To measure the accuracy of the predicted light directions and surface normals, the widely used mean angular error (MAE) in degree is adopted.
Since the light intensities among the testing images can only be estimated up to a scale factor $s$, we introduce the scale-invariant relative error
\begin{equation}
    E_{err} = \frac{1}{q} \sum_i^q \left(\frac{|s e_i -\tilde{e}_i|}{\tilde{e}_i} \right),
\end{equation}
where $q$ is the number of images, $e_i$ and $\tilde{e}_i$ are the estimated and ground-truth light intensities, respectively, for image $i$. The scale factor $s$ is computed by solving \hbox{$\mathop{\rm argmin}\limits_s \sum_i^n (s e_i -\tilde{e}_i)^2$} with least squares\footnote{As the calibrated intensity in the real dataset is in the form of $3$-vector, we repeat the estimated intensity to be a $3$-vector and calculate the average result.}.

\subsection{Network Analysis with Synthetic Data}
\paragraph{MERL$^{\text{Test}}$ dataset}
To quantitatively perform network analysis for our method, we rendered a synthetic dataset, denoted as MERL$^{\text{Test}}$, of sphere and bunny shapes, denoted as {\sc Sphere} and {\sc Bunny} hereafter, respectively, using the physically based raytracer Mitsuba~\cite{jakob2010mitsuba}. Each shape was rendered with $100$ isotropic BRDFs from MERL dataset~\cite{matusik2003merl} under $100$ light directions sampled from the upper-hemisphere, leading to $200$ test objects (see \fref{fig:syn_test_sample}). Cast shadows and inter-reflections are considered for {\sc Bunny}.
For all experiments on synthetic dataset involving input with unknown light intensities, we randomly generated light intensities in the range of $[0.2, 2.0]$. Each experiment was repeated five times and the average results were reported.
\begin{figure} \centering
    \input{figures/syn_test_samples}
    \caption{(a) Lighting distribution of MERL$^{\text{Test}}$ dataset. The light direction is visualized by mapping a $3$-d vector $[x,y,z]$ to a point $[x,y]$. (b) and (c) show a sample image and ground-truth normal for {\sc Sphere} and {\sc Bunny}, respectively.} \label{fig:syn_test_sample}
\end{figure}

\begin{figure}[t] \centering
    \input{figures/discretization_coord} \hspace{-0.5em}
    \includegraphics[width=0.25\textwidth]{images/Method/sphere_errorcombine_.pdf}\\
    \vspace{-0.6em} \makebox[0.22\textwidth]{\small (a)} \hfill \makebox[0.23\textwidth]{\small (b)}
    \caption{(a) Light directions $A, B, C$, and $D$ have the maximum deviation angles with the light direction $P$ after discretization. (b) Upper-bound of normal estimation error for PS-FCN~\cite{chen2018ps} under different light direction space discretization levels ($\infty$ indicates no discretization).} \label{fig:discretization}
\end{figure}

\vspace{-1.4em}
\paragraph{Discretization of lighting space}
For a given number of bins $K_d$, the maximum deviation angle for azimuth and elevation of a light direction is $\delta = 180\degree/(K_d\times 2)$ after discretization (\eg, $\delta=2.5\degree$ when $K_d=36$).
To investigate how light direction discretization affects the normal estimation accuracy, we adopted the state-of-the-art calibrated method PS-FCN~\cite{chen2018ps} and MERL$^\text{Test}$ dataset as the testbed.
We divided the azimuth and elevation of light directions into different number of bins ranging from $2$ to $180$.
For a specific bin number, we replaced each ground-truth light direction by each of the four light directions having the maximum possible angular deviations after discretization (see \fref{fig:discretization}~(a)), respectively. We then used those light directions as input for PS-FCN to infer surface normals. The normal estimation error reported in \fref{fig:discretization} (b) is the upper-bound error for PS-FCN caused by the discretization.
We can see that the increase in error caused by discretization is marginal when $K_d\ge30$.
In our implementation, we empirically set $K_d$ and $K_e$ to $36$ and $20$, respectively. We experimentally found that the performance of LCNet is robust to different discretization levels. We chose a relatively sparse discretization of lighting space in this paper as it may allow NENet to learn to better tolerate small errors in the estimated lighting at test time.

\vspace{-1.4em}
\paragraph{Effectiveness of LCNet}
To validate the design of LCNet, we compared LCNet with three baseline models for lighting estimation.
The first baseline model, denoted as LCNet$_{\text{reg}}$, is a regression based model that directly regresses the light direction vectors and intensity values (please refer to the supplementary for implementation details).
The second baseline model, denoted as LCNet$_{\text{w/o mask}}$, is a classification based model that only takes the images as input without the object mask input.
The last baseline model, denoted as LCNet$_{\text{local}}$, is a classification based model that independently estimates lighting for each observation (\ie, without local-global feature fusion).
All models were trained under the same setting, and the results are summarized in \Tref{tab:quant_light_synth}.

\begin{table}[t] \centering
    \caption{Lighting estimation results on the MERL$^\text{Test}$ dataset. The results are averaged over samples rendered with $100$ BRDFs.}
    \input{tables/res_quant_light_synth} \label{tab:quant_light_synth}
\end{table}

Experiments with IDs A0 \& A1 in \Tref{tab:quant_light_synth} show that the proposed classification based LCNet consistently outperformed the regression based baseline on both light direction and intensity estimation.
This echoes our hypothesis that classifying a light direction to a certain range is easier than regressing an exact value. Thus, solving the classification problem reduces the learning difficulty and improves the performance.
Experiments with IDs A0 \& A2 show that taking the object mask as input can effectively improve the lighting estimation results.
This might be explained by the fact that object mask provides strong information for occluding contours of the object, and helps the network distinguish the shadow region from the non-object region.
Experiments with IDs A0 \& A3 show that the proposed local-global feature fusion strategy can effectively make use of information from multiple observations, and significantly improve the lighting estimation accuracy.
Please refer to our supplementary for detailed lighting estimation results of LCNet on {\sc Bunny} from MERL$^\text{Test}$ dataset.

\vspace{-1.4em}
\paragraph{Effectiveness of NENet}
Experiments with IDs B1 \& B2 in \Tref{tab:quant_normal_syn} show that after training with the discretized lightings estimated by LCNet, NENet performs better than PS-FCN given possibly noisy lightings at test time,
while experiments with IDs B3 \& B4 show that training NENet with the light directions estimated by the regression based baseline is not always helpful.
This result further demonstrates that the proposed framework is robust to noisy lightings.
Experiments with IDs B0 \& B1 show the proposed method achieved results comparable to the fully calibrated method PS-FCN~\cite{chen2018ps}, with average MAEs of $2.71$ and $4.09$ on {\sc Sphere} and {\sc Bunny}, respectively.

\begin{table}[th] \centering
    \caption{Normal estimation results on the MERL$^\text{Test}$ dataset. The numbers are the average MAE over samples rendered with $100$ BRDFs (value the lower the better). NENet$^{\dag}$ was trained given the lightings estimated by LCNet$_{\text{reg}}$.}
    \input{tables/res_quant_normal_synth} \label{tab:quant_normal_syn}
\end{table}

\Fref{fig:img_num_syn} shows that the performances of LCNet and NENet increased with the number of input images. This is expected, since more useful information can be used to infer the lightings and normals with more input images.

\begin{figure}[t] \centering
    \includegraphics[width=0.25\textwidth]{images/Results/synth/sphere_img_num_light_sensitivity.pdf}
    \includegraphics[width=0.22\textwidth]{images/Results/synth/sphere_img_num_norm_sensitivity.pdf}\\

    \caption{Results of SDPS-Net on {\sc Sphere} from MERL$^\text{Test}$ dataset with varying input image numbers.} \label{fig:img_num_syn}
\end{figure}

\vspace{-1.4em}
\paragraph{Comparison with single-stage models}
To validate the effectiveness of the proposed two-stage framework, we compared our method with five different single-stage baseline models.
We first retrained UPS-FCN~\cite{chen2018ps}, denoted as UPS-FCN$_{\text{retrain}}$, with images scaled by randomly generated light intensities to allow it adapt to unknown intensities at test time.
We then increased the model capacity of UPS-FCN by introducing a wider network (\ie, more channels in the convolutional layers) and a deeper network (\ie, more convolutional layers), denoted as UPS-FCN$_{\text{wide}}$ and UPS-FCN$_{\text{deep}}$, respectively.
We also trained a deeper network, denoted as UPS-FCN$_{\text{deep+mask}}$, that takes both the images and object mask as input.
We last investigated the effect of having additional lighting supervision by training a variant model, denoted as UPS-FCN$_{\text{est\_light}}$, to simultaneously estimate lighting and surface normal.
Please refer to our supplementary for detailed network architectures.

\begin{figure}[t]\centering
    \input{figures/compare_quant_pf14_v2}
    \caption{Comparison between SDPS-Net and PF14~\cite{papad14closed} on {\sc Bunny} rendered with four different types of BRDFs under a near uniform lighting distribution and a biased lighting distribution.} \label{fig:compare_pf14}
\end{figure}

Experiments with IDs B5-B9 in \Tref{tab:quant_normal_syn} show that utilizing a wider or deeper network, taking the object mask as input, or incorporating additional lighting supervision can improve the performance of single-stage model in some extent.
However, experiments with IDs B1 \& B5 show that the proposed method significantly outperformed the best-performing single-stage model, especially on surfaces with complex geometry such as {\sc Bunny}, when the input as well as the number of parameters are comparable.
This result indicates that simply increasing the layer numbers or channel numbers of the network, or incorporating additional lighting supervision cannot produce optimal results.

\vspace{-1.4em}
\paragraph{Comparison with the non-learning method~\cite{papad14closed}}
To further verify the effectiveness of our method over non-learning method, we compared SDPS-Net with the existing uncalibrated method PF14~\cite{papad14closed}, which achieved state-of-the-art results on the DiLiGenT benchmark~\cite{shi2018benchmark}, on different lighting distributions and types of BRDFs.
Specifically, we considered one near uniform and one biased lighting distribution (see \fref{fig:compare_pf14}~(a)).
We rendered {\sc Bunny} using four typical types of BRDFs, including the Lambertian model and three other types from MERL dataset~\cite{matusik2003merl}, namely, Fabric, Plastic, and Phenolic.
They contained $15$, $12$, $9$, and $12$ different BRDFs, respectively. We reported the average results for each type (see \fref{fig:compare_pf14}~(b) for an example of each type.).

\Frefs{fig:compare_pf14}~(c)-(e) compare SDPS-Net and PF14 on lighting estimation and normal estimation. The following observations are made:
1) PF14 performed well on light direction and normal estimation for diffuse or near diffuse surfaces (\ie, Lambertian and Fabric), but will quickly degenerate when dealing with non-Lambertian surfaces. Besides, it cannot reliably estimate light intensities for all the BRDFs.
2) SDPS-Net performed well on different types of BRDFs, especially on surfaces exhibit specular highlights. This result suggests that specular highlight is an important clue for uncalibrated photometric stereo~\cite{drbohlav2005can}.
3) The performance of light direction and normal estimation of both methods will have a trend of decreasing when dealing with biased lighting distribution, while the performance of intensity estimation will slightly improve.

\subsection{Evaluation on Real Datasets}
\begin{figure}[tbp] \centering
    \input{figures/test_data_light_distribution}
    \caption{Lighting distributions of real testing datasets. The light direction is visualized by mapping a $3$-d vector $[x,y,z]$ to a point $[x,y]$. The color of the point indicates the light intensity (value is divided by the highest intensity to normalize to $[0,1]$).} \label{fig:light_dist}
\end{figure}

\begin{figure*}[t] \centering
    \input{figures/res_qual_real_datasets}
    \caption{Qualitative results of SDPS-Net on the real testing datasets. The first to the fourth rows show the object, estimated normal map, error distribution of light direction and light intensity estimation, respectively.}
    \label{fig:qual_real_datasets}
\end{figure*}

\paragraph{Real testing datasets}
We evaluated our method on three publicly available non-Lambertian photometric stereo datasets, namely the \emph{DiLiGenT benchmark}~\cite{shi2018benchmark}, \emph{Gourd\&Apple dataset}~\cite{alldrin2008p} and \emph{Light Stage Data Gallery}~\cite{einarsson2006relighting}. \Fref{fig:light_dist} visualizes the lighting distribution of these datasets (note that for Light Stage Data Gallery, we only used $133$ images with the front side of the object under illumination).
Since Gourd\&Apple dataset and Light Stage Data Gallery only provide calibrated lightings (without ground-truth normal maps), we quantitatively evaluated our method on lighting estimation while qualitatively evaluated it on normal estimation.

\vspace{-1.2em}
\paragraph{Evaluation on DiLiGenT benchmark}
\Tref{tab:quant_light_normal_diligent} (a)-(b) show that LCNet outperformed the regression based baseline LCNet$_{\text{reg}}$ and achieved highly accurate results on both light direction and intensity estimation on DiLiGenT benchmark, with an average MAE of $4.92$ and an average relative error of $0.068$, respectively.
\Tref{tab:quant_light_normal_diligent} (c) compares the normal estimation results of SDPS-Net with previous state-of-the-art methods on DiLiGenT benchmark.
SDPS-Net achieved state-of-the-art results on almost all objects with an average MAE of $9.51$, except for the {\sc Bear} object.
Although UPS-FCN$_\text{deep+mask}$ achieved reasonably good results on objects with smooth surface and uniform material (\eg, {\sc Ball}), it had difficulties in handling surfaces with complex geometry and spatially-varying BRDFs (\eg, {\sc Reading} and {\sc Harvest}).
The normal estimation network coupled with LCNet (i.e., SDPS-Net) outperforms that with LCNet$_{\text{reg}}$ (i.e., LCNet$_{\text{reg}}$+NENet$^\dag$) with a clear improvement of $1.52$ in average MAE, demonstrating the effectiveness of the proposed classification based LCNet.
It is interesting to see that, coupled with our LCNet, the calibrated methods L2 baseline~\cite{woodham1980ps} and IS18~\cite{ikehata2018cnn} can already achieve results comparable to the previous state-of-the-art methods. This result indicates that our proposed LCNet can be integrated with existing calibrated methods to help handle cases where lighting conditions are unknown.
\Frefs{fig:qual_real_datasets}~(a)-(b) show the qualitative results of SDPS-Net on DiLiGenT benchmark.
\begin{table}[tbp] \centering
    \caption{Results of SDPS-Net on the DiLiGenT benchmark.} \label{tab:quant_light_normal_diligent}

    \begin{subfigure}[t]{0.48\textwidth}\centering
        \caption{Results on light direction estimation.}
        \input{tables/res_quant_light_dir_diligent}
    \end{subfigure}
    \begin{subfigure}[t]{0.48\textwidth}\centering
        \caption{Results on light intensity estimation.}
        \input{tables/res_quant_light_int_diligent}
    \end{subfigure}
    \begin{subfigure}[t]{0.48\textwidth}\centering
        \caption{Results on normal estimation. (Best viewed in PDF with zoom.)}
        \input{tables/res_quant_normal_diligent}
    \end{subfigure}
\end{table}

\vspace{-1.2em}
\paragraph{Evaluation on other real datasets}
\Tref{tab:quant_light_gourd_stage} shows that SDPS-Net can estimate accurate light directions and intensities for the challenging Gourd\&Apple dataset and Light Stage Data Gallery.
Our method can also reliably recover visually pleasing surface normal of these two datasets (see \fref{fig:qual_real_datasets}~(c)-(g)), clearly demonstrating the practicality of the proposed methods in real world applications.
Please refer to our supplementary for more results.

\section{Conclusion and Discussion}
In this paper, we have proposed a two-stage deep learning framework, called SDPS-Net, for uncalibrated photometric stereo. The first stage of our framework takes an arbitrary number of images as input and estimates their corresponding light directions and intensities, while the second stage predicts the normal map of the object based on the lightings estimated in the first stage and the input images.
By explicitly learning to estimate lighting conditions, our two-stage framework can take advantage of the intermediate supervision to reduce the learning difficulty and improve the final normal estimation results.
Besides, the first stage of our framework can be seamlessly integrated with existing calibrated methods, which enables them to handle uncalibrated photometric stereo.
Experiments on both synthetic and real datasets showed that our method significantly outperformed existing state-of-the-art uncalibrated photometric stereo methods.

\begin{table}[t] \centering
    \caption{Lighting estimation results of SDPS-Net on the Gourd\&Apple dataset and the Light Stage Data Gallery.}
    \label{tab:quant_light_gourd_stage}
    \begin{subfigure}[t]{0.48\textwidth}\centering
        \caption{Results on the Gourd\&Apple dataset.}
        \input{tables/res_quant_light_gourd}
    \end{subfigure}
    \vspace{0.2em}
    \begin{subfigure}[t]{0.48\textwidth}\centering
        \caption{Results on the Light Stage Data Gallery.}
        \input{tables/res_quant_light_lightstage}
    \end{subfigure}
    \label{tab:quant_light_gourd_stage}
\end{table}

Since our framework is trained only on surfaces with uniform material, it may not perform well in dealing with steep color changes caused by multi-material surfaces (see \fref{fig:qual_real_datasets}~(b) for an example).
In the future, we will investigate better training datasets and network architectures for handling surfaces with spatially-varying BRDFs.

\vspace{-1.4em}
\paragraph{\bf Acknowledgments}
We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU.
Kai Han is supported by EPSRC Programme Grant Seebibyte EP/M013774/1.
Boxin Shi is supported in part by National Science Foundation of China under Grant No. 61872012.
Yasuyuki Matsushita is supported by the New Energy and Industrial Technology Development Organization (NEDO).
{\small
\bibliographystyle{ieee_fullname}

redpajama_set_name: RedPajamaArXiv


text:
Huawei Faces SD and microSD Card Ban
Paul Rubens - May 27, 2019 - 05:23 AM
Huawei may be forced to find an alternative technology to boost the storage capacity of its phones.
(CCM) — Huawei may be barred from using SD cards, or the smaller microSD card variant, following action taken by the SD Association, according to an Android Authority report.
The SD Association sets the standards for the two types of memory cards, but it has recently removed Huawei from its membership list to comply with the U.S. government's ban on transferring technology to the smartphone maker. Companies which are not members of the SD Association are not permitted to produce and sell devices which support SD cards using SD standards.
Huawei said in the report that "the use of of SD cards on Huawei smartphone won't be affected. Consumers can continue purchasing and using these products," but declined to say whether new Huawei phones would still support SD cards.
The ban would mainly affect low and mid-range smartphones which rely in the use of memory cards to boost the devices' limited internal storage. But Huawei could get around the ban by using alternative forms of memory cards or create its own proprietary ones. However the company may face resistance from customers because SD and microSD cards are ubiquitous and available at very low cost.
In a further setback for the beleaguered Chinese company, the WiFi Alliance — which develops standards for wireless networking used by mobile devices — has also excluded Huawei from its membership list.
Image: © Максим Кузубов – 123RF.com
Lost Password to MicroSD Card - How-To - Memory card
MicroSD Card Has Record 400 GB Capacity - News
Microsd card write protected - How-To - USB
32gb fat32 microsd cards - How-To - Windows
MicroSD card password protected ✓ - Forum - Nokia
ByteDance Plans TikTok Smartphone
Android and Chrome OS to Get Closer
MediaTek Unveils Flagship Gaming Chips
Apple Preps 16-inch MacBook Pro
Amazon Prime Video in Virtual Reality
Pandora Launches Voice Mode


text:
Social media fitness influencer Joan MacDonald proves that good health has no age limit
Joan MacDonald was thrilled to welcome her daughter and son-in-law to her home in Ontario, Canada, just before Christmas in 2016. What she didn't expect was her daughter's reaction to the announcement that she was taking medication for high blood pressure, high cholesterol and acid reflux.
"I was really out of breath going up and down the stairs," said MacDonald, who was 70 and 198 pounds at the time. "My daughter got really, really worried. She thought if she wanted me there, she had better step in.
Fortunately, McDonald's daughter, Michelle MacDonald, happens to be a physical trainer and trainer. "Michelle challenged me, and I'm not one to back down from a challenge!" MacDonald said.
A few weeks later, in January 2017, MacDonald joined one of her daughter's transformation groups along with 10 other women who were equally determined to change their looks and abilities. The only difference was that MacDonald was significantly older than everyone else in the group.
By changing his diet, physical activity and even sleeping habits, MacDonald was able to improve his health enough to stop taking his blood pressure medication within a year. And now, at nearly 76, MacDonald is off medication, 60 pounds lighter and slimmer than she was as a teenager.
And to top it off, she can do bench press 80 pounds.
MacDonald, who documented her body transformation from a size 15 to a size four on her hugely popular Instagram accountwho has 1.5 million subscribers, said that as women, "we've been conditioned to accept the life that we have without a doubt – that we have to go through menopause, we're going to get fat, everything will collapsing after we're 40. But that's not true. It's definitely not true.
The hardest thing is to start
To kick off her trip, MacDonald decided to spend two weeks with her daughter at her home in Tulum, Mexico in January 2018. Michelle had her mom weigh in and take pictures and measurements, and then the real work began. .
Those first few weeks were extremely difficult for MacDonald. Her acid reflux flared up and she said, "I wanted to throw in the towel many, many times, let me tell you."
Along with increasing the type and amount of her physical activity, MacDonald dutifully followed her daughter's instructions for meal planning, going from two or three meals a day (plus snacks) to five small meals a day with a balance of protein, carbohydrates and good fats. But rather than being hungry, MacDonald ended up feeling full. "It's beyond your mind that you can eat more and lose!" It's just what you eat," she said.
Michelle also made sure her mother drank almost a gallon of water a day and slept a full eight hours a night (compared to seven). Adding strength training to the program has helped keep MacDonald's bones strong, a big plus for women in her age category. MacDonald laughed that with her increased activity level, she's had a lot of falls but has yet to break a bone. In fact, his bone density hasn't changed in eight years.
MacDonald now spends summers at his Canadian home and winters with his daughter in Tulum. But wherever she lives, she hits the gym five days a week, doing two days of cardio and three days of cardio and strength training. In Tulum, she regularly bikes to the beach 30 minutes each way.
MacDonald underwent quite a lifestyle change for someone who didn't consider themselves "athletic". Even so, she does not cite her progress as unique. "It's hard work. It's not easy. But anyone can do it. I'm not special. You just need to determine that you want to have a better life," she said. declared.
Become social
MacDonald transformed more than her body, she also had to transform her technical skills.
When she started her first transformation challenge with her daughter, MacDonald had an iPad but didn't really know how to use it. To keep up with her progress, MacDonald had to figure out how to navigate the iPad, and she eventually bought a smartphone later that year.
Michelle MacDonald encouraged her mother to create a social media account to demonstrate that physical transformation is possible at any age. At the time, MacDonald didn't even know what Instagram was. "I guess because I started using an iPhone so late, I didn't realize these apps are how people communicate," she said. MacDonald has his own too Youtube channel and "Train with Joan" application.
Joan MacDonald hits the gym five days a weekMichelle MacDonald
MacDonald's subscribers aren't limited to people in his age bracket. Most of her followers are women in their late 20s to early 40s who look to her for inspiration.
"I'm the conduit to showcase what's possible," she said.
"Now I live."
After starting her fitness journey, MacDonald's whole outlook changed.
"I'm much happier than I've ever been," she said. "Now I live. When I started, I felt like I existed, waiting for the day when I would leave.
MacDonald found that there was a whole community of people who rallied around her and cheered her on as she progressed. They were excited to be part of his journey. And thousands of people have started their own fitness journey.
Wondering where to start? MacDonald said all you have to do is this: "Get up off the couch or chair and get moving. Whether it's dancing, biking, walking, running, whatever. Just keep moving.
And as MacDonald demonstrated, it's never too late to start.
She wants to remind women, especially mothers, to take time for themselves. She said, "You don't have to take care of your children until they are old. Bring them. Give them all the tools to succeed on their own. And then it's time for you.


A professional team uses a drilling rig to tap into an underground aquifer, then caps the well with a hand or foot pump. These deep wells typically supply more water than hand-dug wells, but the projects are more expensive as they require heavy equipment, fuel and larger teams of skilled technicians!
Our local partner will form and train a local Water and Sanitation Committee (WATSAN) on best sanitation (use of latrines), hygienic practices, safe water storage and water point management. These efforts instill a sense of ownership and responsibility for the project.
The water project you funded at the end of 2013 is now in the construction and community engagement phase. Here's a summary of the progress made so far. We're excited to share the exact details of your project with you once it's completed!
Make a donation to #CONSERVELIFE!


text:
Many conservative Trump supporters have condemned the injustice Dr. Biru suffered and many of them have appealed to President Trump to act. His case has gotten more attention in conservative circles than in liberal ones. It was covered in leading conservative newspapers, including The Washington Times, The Hill, Town Hall, and Breitbart News.
The Bank's cover-up was more criminal than the original crime. Former World Bank President Jim Yong Kim engineered a two-pronged campaign. On one front, he launched a negative campaign against Dr. Biru using false and fabricated stories. On another front, he terminated or pushed out six white VPs to create vacancies to hire affirmative action VPs. The World Bank Spokesperson heralded the PR ploy as a successful affirmative action policy to American media stating: "Nine of 31 VPs are from Sub-Saharan Africa or are African American. Two years ago, there were only 3." Africa and African Americans account for 14% of the world population and 30% of the Bank's VPs. Terminating white VPs to enforce over-representation of Black VPs and paying the terminated white VPs millions of dollars in compensation is not affirmative action. It is a crime.
As Dr. Steve Parson, a Member of the Advisory Board for National Minority Coalition for Trump rightly said, "Dr. Biru's pursuit of justice is now in the hands of the Trump Administration. Justice and humanity demand swift action."
The following are selected leaders out of 32 Founders and Presidents of conservative organizations who wrote a letter of appeal to President Trump to stop funding the World Bank until it (1) agrees to fully redress the injustice it inflicted on Dr. Biru, (2) stops using US funds for abortion. The group was organized by Don Blake and Terry Beatley.
A $16 Billion World Bank Whistle-blower Subjected to Racial Injustice
Too Good for Black
Lies to US Gov't
Fake Board
Pres. Trump
What is Dr. Biru Asking?
In a written statement to the US Department of State, the World Bank falsely claimed Dr. Biru's request is to re-litigate his racial discrimination claim that has been reviewed and rejected by the Tribunal. As highlighted in Senator Chris Van Hollen's 73-Page Report, Dr. Biru outstanding cases are different.
Dr. Biru's outstanding cases that he brought before the Tribunal in 2013, 2014 and 2015 were triggered by what happened three years after the Tribunal made its judgements on his discrimination claims. During the Tribunal's proceedings of the racial discrimination case, the World Bank retroactively falsified Dr. Biru's record and lied under oath about it. Under enormous pressure from US lawmakers, in 2013 and 2014, the World Bank gradually restored Dr. Biru's official record internally.
Since 2014, the World Bank has two different personnel records for Dr. Biru: (1) the internally restored record which is extraordinarily positive, and (2) the information on its website and publications that are irreparably defamatory and starkly different from his official internal record. A table comparing the two is provided on Dr. Biru's website www.LongerThanApartheid.com (see page titled "Blacks Rated Inferior."
The World Bank described Dr. Biru's internally restored official performance record as "hagiographic" - too good to be true, but insisted the retroactively degraded and irreparably defamatory record will not be removed from the Bank's website. The Honorable Ken Cucinnelli described the false record that is on the World Bank's website as "a case of a deliberate and systemic destruction of a human being."
World Bank Staff Rule 2.01 prohibits the Bank from having contradictory personnel information on current or former staff members. The Staff Rule requires the World Bank to correct "false or misleading" public information and disclose the true and official record to prospective employers and others to mitigate reputational damages to the affected staff.
To date the Bank has refused to honor the Staff Rule in Dr. Biru's case, deeming his restored official record "hagiographic." What is racist about its action is that what it considered "hagiographic" for a black man it credited to white managers on its websites and publications.
In 2013, and 2014 the Tribunal accepted Dr. Biru's appeal to correct his public record and asked the Bank to respond. The Bank's Senior Advisor for Racial Equality filed an amicus brief supporting the Tribunal's decision, stating Dr. Biru's case was the worst racial discrimination case he had ever seen. Dr. Biru's appeal also coincided with the World Bank's diversity report that found his case a "blatant and virulent case of racism."
The World Bank embargoed the diversity report as confidential and filed a motion with the Tribunal to dismiss Dr. Biru's appeal, contending the Tribunal lacked jurisdiction to review his defamation and disenfranchisement claims.
The Tribunal has never reviewed the merits of his complaints, claiming it lacked jurisdiction to review the defamation and disenfranchisement claims. Another outstanding issue is Dr. Biru's severance payment. The Tribunal has not reviewed this either.
1. Redress for the irreversible disenfranchisement of his professional credentials and defamation of his character.
The World Bank has no moral or legal ground to maintain the irreparably damaging defamatory record on its website, after it corrected the record internally in 2014. Even worse, it has no basis (other than discrimination) to refuse to honor Staff Rule 2.01.
Since the World Bank has asserted the Tribunal lacks jurisdiction to review his outstanding claims and the Tribunal has stated it will not accept defamation complaints from him, the only option left is mediation or external arbitration. The buck stops with the current Interim President of the World Bank and the HR Vice President. Dr. Biru's demands are:
A. The World Bank resolve the defamation and disenfranchisement cases through mediation within 30 days.
B. If the case is not settled in 30 days, agree to resolve the case through external arbitration. The arbitrator will be agreed by both parties.
2. Immediate Payment of his severance payment + lost earning based on the DJI average return (Dividends Reinvested)
When Dr. Biru was unlawfully terminated, he was denied severance payment citing the following article in Staff Rule 7.11 (Ending Employment [due to] Unsatisfactory Performance): "A staff member separated for reasons of unsatisfactory performance is not entitled to severance payments."
The World Bank Tribunal rejected the Bank's claim of poor performance and found Dr. Biru's termination "unlawful, capricious, an abuse of discretion and a violation of due process." The Tribunal instructed the World Bank to remove all references to poor performance. The World Bank is still withholding his severance payment.
In Louis de Merode, et al v. The World Bank (1981) the Tribunal ruled "The Bank cannot deprive staff members of accrued rights for services already rendered. This well-established principle has been applied in many judgments of other international administrative tribunals." Dr. Biru's severance payment is accrued over 18 years of service.
On May 17, 2018, the current HR Vice President (Osmane Diagana) wrote to Dr. Biru stating "I will try to get the background and story on the case then I or someone in my team will revert ASAP." President Kim blocked the HR vice president from reviewing the case.
The Tribunal never reviewed this issue. His severance payment was withheld by former HR VP (Hassan Tuluy) and President Jim Yong Kim. It can only be redressed by the current HR Vice President and the Interim President. They have institutional and moral obligations to pay him his severance payment.


Get Involved. Join us for a church-wide Rebuild Upstate work day on Saturday, July 27!
Join your church family in reaching out to serve our community with Rebuild Upstate! This is a family friendly work day where we will repair/update the home of a family in need (located near our church), coordinated by Rebuild Upstate.
Feel free to sign up for a half day or a full day, or just volunteer to bring snacks and drinks.
This is family friendly! Kids under 13 must be accompanied by an adult.
Bring your own bag lunch and please wear closed toe shoes and dress appropriately.
Please watch this 4-minute safety video prior to coming that day.
(photo from Rebuild Upstate) An example of a Rebuild Upstate project is to build a ramp for an elderly or disabled homeowner, so they can safely get in and out of their home.


text:
CIA used pirated, inaccurate software to target drone attacks: lawsuit
Daniel Tencer
'They want to kill people with my software that doesn't work,' software exec tells court
The CIA used illegally pirated software to direct Predator drone attacks, despite apparently knowing the software was inaccurate, according to documents in an intellectual property lawsuit.
The lawsuit, working its way through a Massachusetts court, alleges that the CIA purchased a pirated and inaccurate version of a location analysis program, which may have incorrectly located targets by as much as 42 feet.
The allegation raises fresh questions about the CIA's execution of drone attacks in Afghanistan and Pakistan, which are believed to have killed hundreds of civilians in the past four years.
And if the court decides to grant an injunction against users of the software, it could potentially halt the CIA's drone attacks, at least temporarily, as the agency works to find a replacement.
Massachusetts-based Intelligent Integration Systems Inc., or IISI, has asked a judge to stop clients of IT firm Netezza from using software IISI says is pirated, reports The Register.
According to IISI, Netezza reverse-engineered a location analysis program called Geospatial and installed it on its own hardware, which it then sold to the CIA. Netezza had contracted IISI to build the software, but decided to create its own unauthorized version after the project suffered delays, the lawsuit alleges.
The CIA accepted the pirated software despite reportedly knowing it "produced locations inaccurate by up to 13 metres (42.6 feet)," reports The Register.
In a sworn deposition, IISI chief technical officer Richard Zimmerman said a Netezza executive pressured him to deliver the product before it was ready and told him it was their "patriotic duty" to build location software for CIA-operated drones.
Another Netezza executive reportedly asserted that the CIA would accept flawed software. "My reaction was one of stun, amazement that they want to kill people with my software that doesn't work," Zimmerman said.
According to court documents, Netezza delivered its reverse-engineered software to the CIA in 2009.
"The potential for a software malfunction to cause serious havoc with an unmanned aerial vehicle, such as a Predator Drone, is no longer a matter of pure theory," writes Bill Conroy at NarcoNews. "Last month a Navy drone entered the airspace of the nation's Capitol after being out of control for a half hour due to what the Navy called a 'software issue.'
"If the CIA is using flawed software re-engineered by Netezza 'to target predator drones in Afghanistan,' as IISI's pleadings in the lawsuit assert, then it is likely only a matter of time before innocent lives are compromised due to a 'software issue.' In that sense, IISI's motion for a preliminary junction, if successful, could be seen as a lifesaver," Conroy argues.
Last year, the New American Foundation estimated that Predator drones killed 750 to 1,000 people in Pakistan between 2006 and 2009. About one third — an estimated 320 people — were believed to be civilians.


Living Room abigail bliesner Wednesday, April 10th 2019 09:13:00 AM - So, if you wish to obtain these magnificent graphics about (20 formalbeauteous 3x2 Photo Frame nowadays), click save button to store the shots to your personal pc. They're prepared for download, if you appreciate and want to own it, click save symbol on the post, and it will be immediately saved to your home computer. At last if you desire to receive unique and the latest picture related with (20 formalbeauteous 3x2 Photo Frame nowadays), please follow us on google plus or bookmark this blog, we attempt our best to provide daily update with fresh and new pics.


The European Institute for Gender Equality  (EIGE) announces a traineeship opportunity lasting up to six months for a graduate who is either a national of an EU member state or an EFTA country.
The traineeship shall be based at the Institute's offices in Vilnius, Lithuania. The registration of applications will begin on 28 January 2013 and will close on 27 February 2013 at 23:00 Eastern European Time (EET).
To achieve its goals, the Institute shall collect and analyse objective, comparable and reliable information at EU level and develop appropriate methodological tools for the integration of gender equality into EU policies. EIGE shall equally foster the exchange of good practices and dialogue between stakeholders and raise EU citizen awareness of this policy area by providing technical assistance to the EU institutions, in particular the Commission, as well as the authorities of the Member States (MS). In the course of its work to promote and strengthen gender equality EIGE will also strive to eliminate gender discrimination.
The trainee shall provide assistance to support the smooth development of the Institute's Resource & Documentation Centre (RDC) which is foreseen to be launched in EIGE's new premises in 2013. The RDC aims to become the EU's one-stop shop on gender equality, keeping the institutional memory of gender equality work at both the EU and MS level.
The trainee shall be provided with relevant thematic work experience in the context of an EU agency.
Attend selected meetings within the RDC team.
Knowledge of PRIMO, ALEPH, METALIB and SFX will be considered an asset.
Applications must reach eige.hr@eige.europa.eu by not later than 23:00, Eastern European Time (EET) on 27 February 2013 and the subject title noted by applicants should include the reference number of the application.
their application is received after 23:00, EET on 27 February 2013.
The purpose of processing of the data submitted by candidates is to manage each application in view of a possible pre-selection and recruitment as a trainee at the Institute. Unsuccessful application files shall be kept for two years following the closure of the selection procedure, after which time they are destroyed. The personal information requested from applicants will be processed in line with Regulation (EC) N°45/2001 of the European Parliament and of the Council of 18 December 2000 on the protection of individuals with regard to the processing of personal data by the Community institutions and bodies and on the free movement of such data.