text:
Apple Like to Buy Twitter Before End of the Year
This is just my prediction: Apple will eventually take over Twitter and integrate it more into its ecosystem for its Mac and mobile users. So, folks who want dividends, sorry, I hope you don't get it. I rather have Apple spend its money in this manner.
How did I come to this conclusion? Well, of all the social media properties out there, only Twitter seems to be more open and less about selling user information than the likes of Facebook, My Space (yes, they're still around), or Google+. The reason is because Twitter users, more than anyone else, are more open with their tweets knowing that what they broadcast is for general consumption.
On Facebook, your updates may be for your friends or a group of friends on a list but Facebook still sell that information to the highest bidder. The same could be said of Twitter but the vast major of Twitter users don't go turning on the feature only their followers or a subset of their followers to get their update.
And this works better for Apple than others. And should Apple eventually buy Twitter, Apple is likely to integrate its own ad system, iAd, which is on life support at this time after failing to "revolutionize" the mobile ad space. And Twitter's social network would probably be similar to what Apple would create had it done so from scratch.
And today, we learn that Apple's upcoming OS X update, Mountain Lion, will gain the same Twitter integration as iOS 5 devices have. And with a Twitter buyout, Apple would instantly gain hundreds of millions of users that it could potentially convert and add to its ecosystem. Apple is likely to sweeten things up by offering iCloud integration, making Twitter the social component of Apple's cloud strategy.
Right now, the lack of a cohesive social network for Apple's other social efforts like iTunes (forget about Ping), Game Center, iMessage, and iBooks could be solved with a Twitter buyout. I mention iBooks because a virtual book club is just something that Apple can go next with its ebook effort.
You're arguing right now that Apple can achieve all this now without buying Twitter. Absolutely. Just without the control that Apple traditionally have. Keep in mind that the disagreement between iTunes data with Facebook has kept Ping from being something that Steve Jobs hope. And Twitter could well become someone else's takeover target in the future.
After the Twitter buyout, Apple should and will continue to keep Twitter as we know it now the way it is. The only different will be seen by those who use Twitter along with iOS devices or Macs.
I believe the deal between Apple and Twitter in iOS 5 was just a test run for Tim Cook and company. It's worked out great for both and in the coming year (I'll allow myself to stretch that into 2013), Apple will make Twitter officially a part of the family.


text:
module Sockit
  module V4
    module Support

      # 90 = request granted
      # 91 = request rejected or failed
      # 92 = request rejected because SOCKS server can not connect to identd on the client
      # 93 = request rejected because the client program and identd report different user-ids
      def build_v4_result_code_message(result_code)
        message = case result_code
        when 90 then
          "Request granted"
        when 91 then
          "Request rejected or failed"
        when 92 then
          "Request rejected because SOCKS server can not connect to identd on the client"
        when 93 then
          "Request rejected because the client program and identd report different user-ids"
        else
          "Unknown"
        end

        "%s (Code: 0x%02X)" % [message, result_code]

      rescue
        "Result Code: #{result_code.inspect}"
      end

    end
  end
end

redpajama_set_name: RedPajamaGithub


Fuji Compressor Mfg. Co., Ltd. Fuji Electric Systems Co., Ltd.
Gas Turbine Generators Hitachi Ltd. Hasegawa Iron Works Co., Ltd.
Ishikawajima-Harima Heavy Industries Co., Ltd. Iwata Air Compressor Mfg. Co., Ltd.
Kaji Technology Corp.(Ex Kaji Compressor) Kawasaki Heavy Industries, Ltd.
Mitsubishi Heavy Industries, Ltd. Mitsui Engineering & Shipbuilding Co., Ltd.
Miura Niigata Power System Co., Ltd.
Sanwa Iron Works Co., Ltd. Shin Nippon Machinery Co., Ltd.
Shinko Ind. Ltd. Sinco Machine Mfg. Co., Ltd.
Steam Turbine Generator Ebara Corporation Suction Gas Engine Mfg. Co., Ltd.
Sumitomo Heavy Industries, Ltd. Taiko Kikai Industries Co., Ltd.
Takuma Tanabe Pneumatic Machinery Co., Ltd.
Tsubaki-Nakashima Co., Ltd Unozawa-Gumi Iron Works, Ltd.
Alfa-Laval, Japan Asahi Gauge Mfg. Co., Ltd.
Daito Kogyo Co., Ltd Fuji Paudal Co., Ltd.
Heishin Pump Works Co., Ltd. Hisaka Works, Ltd.
Hitachi Denshi Ltd. Hokuto Mfg. Co., Ltd.
Honda Pumps Hosokawa Micron Corp.
Iwaki Co., Ltd. Iwatsu Electric Co., Ltd.
Japan Machinery Co., Ltd. Kamui Co., Ltd.
Ketaka Co., Ltd. Kosaka Laboratory Ltd.
Kubota Coryedek-parca-poration Kuramoto Instrument Mfg. Co.
Kurose Co., Ltd. Mazda Pump Mfg. Co., Ltd.
Mitsubishi Kakoki Kaisha, Ltd. Nakamura Jiko Co., Ltd.
NGK Insulations, Ltd. Nihon Den-Netsu Keiki Co., Ltd.
Nihon Seiki Co., Ltd. Niigata-Worthington Co., Ltd.
Nitta Gelatin, Inc. Okawara Mfg. Co., Ltd.
OKS Corporation (=Osaka Kiki Seizo K.K.) Osaka Vacuum, Ltd.
Pacific Machinery & Engineering Co., Ltd. Sakaguchi Electric Heaters Co., Ltd.
Sasakura Engineering Co., Ltd. Satake Chemical Equipment Mfg. Ltd.
Seibu Giken Co., Ltd. Seo Koatsu Kogyo Co., Ltd.
Shimadzu Corp Shirakawa Seisakusho, Ltd.
Teikoku Machinery Works, Ltd. Tokai Konestu Kogyo Co., Ltd.


Whether you have talents to share or a list of skills you'd like to develop, there are many ways to get involved with FIN!
Volunteering is a great way to meet new people, learn new skills, and connect with a variety of work going on in Louisville's food system.
Working groups are where most of the action is at FIN. All are welcome to connect with one or several groups! To get involved, email us to be added to a specific working group list, attend a working group meeting, or come to a FIN Quarterly Meeting to get more information.
Take a look at our calendar of events! This is a space to share volunteer opportunities, meeting information, event announcements, market schedules, and other food-focused events!
View the calendar and learn how to add public events here.
Visit the Resource Library for reports, how-to guides, funding opportunities, links to resources, supplies, and more!
Visit the online community forum where you can engage, share, and learn about food in Louisville with others around the city!
Check the Calendar and Home Page to see when the next Quarterly Meetings is scheduled. All are welcome!
Sign up with your email address for more opportunities to get involved!


text:
Пловдивска къща, симетрична пловдивска къща или пловдивска градска къща е вид еднофамилна градска къща от втората половина на XIX век.

Появата на този вид къщи се свързва с местното развитие на необароковата и неокласицистичната европейска архитектура.

Той възниква в резултат от икономическия и духовния подем през Българското възраждане. Името си получава заради това, че най-голям брой къщи от този тип са запазени в Пловдив. Наименованието е обобщаващо за семейни къщи в Пловдив, Пазарджик, Карлово, Калофер, Казанлък, Копривщица, Чирпан, Смолян.

Майсторите, които са градили тези големи къщи, сапредимно от Средногорието и Родопите. Най-добре запазени и най-много образци на пловдивската къща се намират в Пловдив и Копривщица.

Характеристики
Пловдивската къща има най-често симетрична планова композиция, но нерядко се срещат и асиметрични къщи. Това са големи многостайни къщи, предназначени само за
живеене. Състоят се обикновено от зимник, високо приземие и етаж. Приземието и етажът имат еднакво разпределение и съдържат долен и горен отвод (салон, хол) и във всеки етаж от три до десет помещения с различно предназначение, разположени около отвода. В долния отвод се влиза направо по външна, много често двустранна стълба. Горният отвод нерядко е отделен от вътрешната стълба с врата. Характерни са закритите отводи, големите, сравнително високи и светли стаи.

Типове
Пловдивска къща се поделя на два типа, които се различават един от друг по концепция и произход. Към единия спадат къщите с една надлъжна ос на симетрия, към другия – къщите с две перпендикулярни една на друга оси на симетрия.

Къщи с една надлъжна ос на симетрия са разпространени в Перущица, Брацигово и други съседни селища. Най-простата форма е двустайната къща. Бива два варианта – асиметричен и симетричен. При асиметричния двете стаи са разположени една зад друга от едната страна на навеса. При симетричния от двете страни на навеса има по една стая. И в двата варианта навесът е открит само от предната страна, излиза малко пред лицето на стаите и е подпрян на дървени колонки.

Следващата по-развита форма на този тип е четиристайната къща. Стаите в нея са разположени по две от двете страни на навеса. Когато къщите имат етаж, той повтаря разпределението на приземието. Тези симетрични селски къщи и развитите големи пловдивски къщи притежават общи характерни белези. Те имат една и съща планова схема – централно продълговато помещение с по две стаи отстрани и ясно изразена надлъжна ос на симетрия. Входът им, маркиран с дървени колонки, е на късата страна на централното помещение.

Около средата на ХIХ в. се появяват главно в Пловдив симетрични къщи с масивни външни стени. Отначало масивни са само двете странични стени на приземието. По-късно масивна става и северната стена, а южната стена и етажът остават паянтови. Има къщи, на които и четирите външни стени в приземието и етажа са масивни. В ъглите и в други конструктивно отговорни места на масивните стени са вградени дебели дъбови стълбове, свързващи във вертикална посока междуетажните дървени конструкции.

При къщите с две перпендикулярни една на друга оси на симетрия двете оси не са равнозначни. Главна ос на симетрията е надлъжната. На нея са разположени едно след друго портик с двустранна стълба, дълбок салон или отвод и в дъното му стълба към етажа. В някои случаи вътрешната стълба е поставена на напречната ос, а тя има второстепенно значение. Стените и таваните на салоните и стаите са разточително декорирани. Няма огнища в стаите. Останали са големите стенни долапи с алафранги в средата. Входът с двустранната стълба е силно подчертан, като е поставен в ниша между двете крила на къщата или е подслонен под портик, поддържан от две или четири дървени колони, поставени върху каменни бази. Портикът е двуколонен или четириколонен и завършва горе с архитравна греда или с арка в полукръг, полуелипса, с кобилична или друга крива. В интериора разнообразието е значително по-слабо и то се получава главно посредством формата на салона, разработката на таваните, на стенните плоскости и профилировката на алафрангите.

Бележки

Възрожденски типове къщи в България

redpajama_set_name: RedPajamaWikipedia


YANG Xiaosong,JIN Zhenmin,MA Jin. 2005. Anatexis in Himalayan crust:Evidence from geochemical and chronological investigations of Higher Himalayan Crystallines. Science in China (Series D),48(9):1347-1356.
ZHOU Yongsheng,HE Changrong,SONG Juan,MA Shengli,MA Jin. 2005. An experiment study of quartz-coesite transition at differential stress. Chinese Science Bulletin, 50(5):446-451.
CHEN Shun-yun,LIU Li-qiang,MA Sheng-li,MA Jin. 2005. An experimental study on variation of bvalue during deformation of rock samples with different structural models. ACTA SEISMOLOGICA SINICA, 18(3):338-344.
邱泽华,马瑾,刘国玺. 2005. 新发现的唐山地震大断层. 地震地质, 27(4):669-677.
陈顺云,马瑾,刘培询,刘力强,陈国强. 2005. 突出地表热辐射场中现今构造活动信息的均值梯度法. 地震地质, 27(4):661-668.
胡新亮,刁硅苓,马瑾,王俊国,赵明淳,苗菊玲. 2005. 从块体中心论看中国近期强震成组活动的特征. 地震地质, 27(2):341-351.


If this event requires multiple days please list this information "Extra Info".
The venue may already have lighting but we can also provide if needed.
Please provide the average AGE group and the culture of the group. This will help us adjust our performance for the crowd. Example: Indian Wedding, Bar Mitzvah, Prom, etc.
You will hear back from our team within 24 hours!


FAYETTEVILLE, Ark.—There's no place like home and for 'The Wizard of Oz' that home is the theater.
To celebrate eighty years of successfully traversing the yellow brick road, the classic movie will be returning to select theaters across the country. You can see the film during the three-day special release thanks to Fathom Events and Turner Classic Movies.
The event begins today (Jan. 27) and ends Wednesday (Jan. 30).
To find out if theaters near you will show the film, or if you'll have to go somewhere over the rainbow to see it, you can check out Fathom's website.


text:
The 2019 Danish Cup final was played on 17 May 2019 between FC Midtjylland and Brøndby IF at Parken Stadium, Copenhagen, a neutral ground. The final is the culmination of the 2018–19 Danish Cup, the 65th season of the Danish Cup.

Brøndby IF appeared in their 10th Danish Cup final (third consecutive) and were the defending title-holders. FC Midtjylland had never won a Danish Cup title before the match, being four times the runners-up. The winner of the final earned themselves a place in at least the second qualifying round of the 2019–20 UEFA Europa League.

FC Midtjylland won the final after a penalty shoot-out and earned their first ever Danish Cup title.

Teams

Venue
All Cup Finals except the 1991 final (Odense Stadium) and 1992 final (Aarhus Idrætspark) have been played in the Copenhagen Sports Park (1955–1990), or Parken Stadium (1993–present)

Background
Brøndby is competing in its third consecutive final, losing to F.C. Copenhagen in 2017 and capturing the title over Silkeborg IF in 2018. FC Midtjylland is appearing in its fifth final, losing all four if its previous appearances. The two teams have previously met in the 2003 and 2005 finals, and the teams share an equal 1-1-1 record during the regular season of the 2018–19 Danish Superliga.

Route to the final

Note: In all results below, the score of the finalist is given first (H: home; A: away).

Match

Details
</onlyinclude>

References

Danish Cup Final
Danish Cup Final 2019
Danish Cup Final 2019
Danish Cup Finals
Danish Cup Final
Sports competitions in Copenhagen
Danish Cup Final 2019


The cranes have been in unloading the 5-Axis CNC (which was quite tricky in the high winds) in to place and we are getting all set up ready to go. For more information on the new CNC and to understand the extra options available compared to our 3-Axis CNC's, please refer to earlier News dated 12/11/15.
Alongside this, the investment continues with new compressors being fitted, which are much more energy efficient. We here at Thermograve, are very excited about the new equipment coming in and are looking forward to 2016.
PLUS…Some very exciting news coming shortly, watch this space………..
https://thermograve.co.uk/dev/wp-content/uploads/2015/12/029.jpg 600 800 Hannah Widdowson https://thermograve.co.uk/dev/wp-content/uploads/2014/09/thermograve_logo1.png Hannah Widdowson2015-12-22 11:25:552015-12-22 11:27:52The 5-Axis is Here!


Born in the Rocky Mountains and created by professional snowboarders, the Eyce Spoon provides the great taste of glass but in an indestructible silicone package. Never worry about dropping your pipe or tossing it into your bag or purse when you're on-the-go. The removable borosilicate glass bowl is super-easy to clean and combined with the platinum-cured silicone, delivers maximum flavor every time. The Eyce Spoon comes with a poker tool and integrated/hidden stash container keep everything you need in one place.


Matt Holycross is Director of Finance of The Taft Companies, with a broad based accounting and finance background and experience leading various financial functions of insurance companies.
Previously Matt served as Controller and Chief Financial Officer of National Unity Insurance Company, a property and casualty insurer specializing in private passenger and commercial auto coverages in the Southwest US, based in San Antonio, Texas; as Controller at Accident Insurance Company, a national carrier of insurance solutions with Workers' Compensation, Garage Liability, and General Liability programs, and niche program opportunities; and as a member of the audit Staff at Elliott Davis, one of the largest accounting, tax and consulting services firms in the Southeast.
Matt is a graduate of the South Carolina Honors College with a B.S. degree in Business Administration-Finance and Accounting, and of the South Carolina Moore School of Business. He is a licensed Certified Public Accountant in South Carolina, with memberships in the American Institute of Certified Public Accountants and the South Carolina Association of Certified Public Accountants.


NHMU's Volunteer Continuing Education Lecture Series presents "The Viking Age: Cultural Transitions," by Kristina Stelter, master of letters, Celtic and Viking archaeology.
A penchant for heavy metal music, fantasy novels, and Dungeons and Dragons sparked Stelter's interest in Norse mythologies at an early age. She went on to attend the University of Glasgow, where she studied Celtic and Viking archaeology.
Learn more about Stelter and her research during our Volunteer Continuing Education Lecture Series on Wednesday, June 14, at 6 p.m.
The lecture will take place in the Swaner Forum at the Natural History Museum of Utah, Rio Tinto Center. This event is open to NHMU volunteers and staff, University of Utah students, faculty, and staff, and to the general public with Museum admission.
No RSVP is required. Seats will be reserved for late-arriving volunteers.


Need to engage key talent quickly? This leadership development experience is an excellent start. Designed as a customizable program, it's typically built around two consecutive sessions, each two days in length and scheduled six to eight weeks apart. Each session covers four leadership modules and delivers practical skills that can be applied immediately. The target audience includes individual contributors and first-level managers new - to - 1-3 years in their roles.
To register for the Leading and Managing for Results Open Enrollment Program, please contact Maureen McKee at Maureen.McKee@fccservices.com or 303.721.3279.


The problem is, the IRS doesn't care whether you are working or want to start taking withdrawals. It also does not care if you want that money to keep growing. The agreement you made back when you started putting money into those accounts, was that you could contribute pre-tax dollars and deferred paying income tax on that money and any earnings. However, once you turn 70½, withdrawals are necessary.
A recent survey from Nationwide showed that only 13% of people who are 65 and still working, were able to identify when they will need to start taking RMDs. The RMD is a percentage of your total assets based on your age and life expectancy. Let's look at these two general examples: say you are 70½ this year, and you have $200,000 in assets–your RMD is $7,300. If you are 76 and have the same asset value, then you owe the IRS $9,100. Your tax liability for RMDs should be calculated with the help of your estate planning attorney and your accountant.
How you take these distributions could have a big impact on your tax bill. For many people, the RMD bumps them into a higher tax bracket when they are combined with other retirement income sources. Another question to address is: how will the distribution impact your Social Security benefit?
The only way to completely avoid RMD taxes is to donate the RMD to a qualifying non-profit institution. This is a way to avoid taking the RMD, if you don't need the income. You will avoid paying any taxes on it. There is a $100,000 annual limit on this generous strategy.
An estate planning attorney can advise you on an estate plan that fits your unique circumstances and could include retirement fund withdrawals.
When was the last time you reviewed beneficiary designations? Like titling bank accounts, as explained above, the beneficiary designation takes precedence over anything in your will or trust. If you opened an IRA at your first job and now two decades—and two marriages—have passed, that IRA will still be passed on to the person who you named two decades ago, unless you have updated the beneficiary name. Accounts that often pass directly to beneficiaries include life insurance, annuities, 401(k), 403(b), brokerage accounts and some bank accounts.
Who is your Power of Attorney? Everyone should have a Power of Attorney. This is a person who is your legal representative if you become incapacitated. The durable power of attorney gives your agent the authority to handle banking matters, real estate transactions and other financial matters. You'll also need a Durable Power of Attorney for Healthcare Decisions and a Living Will Declaration.


text:
Messaging Apps
By admin @ColureMedia
Communication,Technology
When was the last time you asked someone out on a date, face-to-face? This may sound a bit prehistoric. Doesn't it? That's because the simple act of social interaction has been redefined by digital interaction. Mobile messaging apps have revolutionized the way people communicate.
Over 2.6 billion people have at least one mobile messaging app installed on their smartphone device. Today's global market seems to be defined by a small handful of messaging apps. Each app offers the ability to capture a moment in ways the other cannot. The increased competition for content exposure has forced some mobile apps to implement similar features.
Recently, Instagram integrated a story feature to their app similar to Snapchat. Instagram has a much larger following than the "exclusive" Snapchat. If this new "clone" attempt by Instagram discovers a footing in the market, it shows that market disruption is more useful when one company duplicates the strengths of another and turns them into weakness.
Because of their demonstrated income streams, mobile messaging has changed the way businesses advertise. With these apps, companies are less dependent upon selling their product. Through mobile messaging apps, businesses can establish a presence and create a greater brand awareness.
Profits are often affected by who (or what) controls the information funnel. Corporate giants, such as CNN and ESPN will be distributing original content directly through Snapchat's new feature.
"They're aggregating people's attention and linking it to other forms of commerce," Mitch Lasky told the New York Times. He's a Snapchat board member and a partner at the venture-capital firm Benchmark.
Mobile messaging apps have changed the way we communicate. They are captivating, exclusive, and unique. They have changed how we share ideas and re-shaped the market, all in the palm of your hand.
Business Basics,Product Development,Technology
Augmented Reality is the melding of the real world with the digital world found on your smartphone. Think "Pokemon Go."
You have more than likely encountered augmented reality, even if the term is unfamiliar. It is not to be confused with virtual reality, another recent development in the tech world. AR is experienced alongside the real world, while VR simulates its own reality.
Charles Arthur, a contributor to The Guardian, describes AR as taking "a real-life scene, or (better) a video of a scene, and add[ing] some sort of explanatory data to it so that you can better understand what's going on, or who the people in the scene are, or how to get to where you want to go".
By blurring the line between what is real and what is not, AR enhances the digital experience.
The most well-known examples of augmented reality in today's market are Snapchat filters and Pokémon Go. While it is more easily recognizable in entertainment, AR has also been utilized in marketing, educational and retail ventures.
Augmented reality is also starting to play a role in the workplace. It has been adapted for certain hands-on training exercises. An employee's virtual presence erases the need for direct contact with different environments.
Where direct involvement is risky, the immersive qualities of AR allows for otherwise impossible experiences. For example, NASA has started to use it for scientific research. This enables advances in exploration that humans couldn't achieve. We can't send a person to Mars, but technology is taking that giant leap for us.
In the near future, you might not even be able to tell who is seeing the world through an AR wearable. Going through a single day without experiencing augmented reality in some way might even be impossible.
As the technology behind AR continues to evolve, its limits will be pushed even further. Think about how Pong and other early video games now seem so primitive, yet they were what introduced many the members of today's workforce to computing. Their innovations have increased the capabilities of operating systems hundreds of times over.
These same kinds of giant strides in AR are still to come. The next generation might be taught about the game-changing nature of Pokémon Go just as today's youth learn about Tetris.
Apple CEO Tim Cook has already labeled augmented reality as the 'next new thing'. Anyone who is familiar with the tech industry will agree: now that AR has captured Apple's eye, every competitor will be clamoring to take it to new heights.
How does your mobile app stand out from the millions in the app stores?
Mobile App Marketing With Indexing & Deep-linking
Mobile app retention rates
Use object-based targeting to reach your audience
A brand is more than a logo
What is influencer marketing?
Digital proofing aids content development
Genuine storytelling
The importance of beta testing
Relationship marketing and customer relationships
Your corporate advertising is not for your benefit
Colure Media Inc
Book Your Free Discovery Call
© 2019 Colure Media - All Rights Reserved
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redpajama_set_name: RedPajamaCommonCrawl


Simon Fraser University, established in 1965, is a comprehensive university located in British Columbia, Canada with campuses in Burnaby, Vancouver and Surrey. The University offers undergraduate and graduate programs in various fields with eight distinct faculties.
Why study at Simon Fraser University?
As of fall 2017, a total of 35,364 students are studying at Simon Fraser University.
Here are a few stats in terms of the student intake.
4,908 of the total 35,364, are international students.
At Simon Fraser University, the programs are divided under undergraduate, graduate, Lifelong learner programs. The University has 8 faculties and offers 59 majors and 20 joint majors in undergraduate studies and around 40 graduate programs. There are also 47 certificate programs that can be joined with major programs.
Note: Apart from these programs, for workplace skills, co-op programs and study abroad programs are available.
Students are given the liberty to apply for classes as per their schedule and study plan. Some of the groups in which programs can be filtered in are given below.
SFU has three campuses located in Burnaby, Vancouver and Surrey. All three campuses offer varying academic programs.
The Burnaby campus is the University's original and main campus and hosts the largest library among the three campuses - W.A.C. Bennett Library.
The Surrey campus is particularly targeted towards first-year students with more access to professors for one-on-one support. This campus is situated conveniently between Metro Vancouver and towards the south of Fraser River.
The Vancouver Campus has multiple facilities. This campus is home to six buildings with all the amenities and facilities for students. It is also described as 'intellectual heart of the city' by Vancouver Sun.
Students can apply for their chosen programs in three sessions as per their convenience. Different programs at the institute are subject to different application procedures. Here are a few common steps that one has to follow to fill in the application form.
Check the admission requirement and select the session.
Register yourself and then proceed with application form filling.
Non-refundable application fee to be paid is CAD 78. It must be paid via credit card.
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text:
London sights and attractions
Tower Hamlets Cemetery Park
Sights and Attractions near Tower Hamlets Cemetery Park
Tower Hamlets Cemetery Park, The Soanes Centre, Tower Hamlets, Southern Grove, London E3 4PX
dawn till dusk
All Activities for Kids Art and Design Art Galleries Attractions for Kids Boats and Bridges Historic Buildings Museums Other Attractions Parks and Gardens Sights Sightseeing Tours
Potemkin Theatre
55 Laburnum Street, Columbia & Brunswick Wharf, E2 | 37 minutes walk from Tower Hamlets Cemetery Park
A bold, geometric canal-side structure attached to the top of a Haggerston warehouse has been awarded the 2019 Antepavilion Architecture Prize. London's newest theatre, the... More
Paynes and Borthwick Wharf
15 Borthwick Street, SE8 | 3 miles from Tower Hamlets Cemetery Park
Two wharves, Paynes, built in 1860, and Borthwick, built in 1934, both mostly demolished in 2004, have been incorporated into a £120 million riverside development.... More
The Postal Museum and Mail Rail
Phoenix Place, Clerkenwell, London WC1X | 3.6 miles from Tower Hamlets Cemetery Park
Explore the history of the Royal Mail at The Postal Museum where you can go on an underground adventure through narrow tunnels not used since... More
The Poetry Library
Level 5, Royal Festival Hall, Belvedere Road, South Bank, London SE1 | 3.9 miles from Tower Hamlets Cemetery Park
The most comprehensive and accessible collection of poetry from 1914 in Britain, The Poetry Library within the Southbank Centre contains 90,000 items and is still... More
Pancras Square
King's Cross, London N1C | 4.1 miles from Tower Hamlets Cemetery Park
Set between King's Cross and St Pancras stations, Pancras Square is a public square with restaurants, offices, green space and a gently flowing stepped water... More
Petrie Museum of Egyptian Archaeology
Malet Place, University College London, Bloomsbury, London WC1E | 4.4 miles from Tower Hamlets Cemetery Park
The Petrie Museum, located within University College London, is one of the largest and most fascinating collections of Egyptian archaeology anywhere in the world. There... More
Pollock's Toy Museum
1 Scala Street, Fitzrovia, London W1T | 4.5 miles from Tower Hamlets Cemetery Park
Crammed inside two townhouses (one 18th, the other 19th century) on a pretty sidestreet you'll find this historic haven for toys of all kinds. Named... More
Piccadilly Circus, Soho, London W1J | 4.6 miles from Tower Hamlets Cemetery Park
Right in the middle of the West End, Piccadilly Circus isn't a circus at all, but an enormous road junction where Piccadilly itself Regent Street,... More
Photographers' Gallery
16-18 Ramillies Street, Soho, London W1F | 4.7 miles from Tower Hamlets Cemetery Park
The Photographers' Gallery - Britain's leading centre for contemporary photography - emerged from a 3.6 million pound redesign in May 2012 revealing the work of... More
Pace Gallery London
6 Burlington Gardens, Mayfair, London W1S | 4.8 miles from Tower Hamlets Cemetery Park
New York art gallery Pace opens its second London space at 6 Burlington Gardens on 4th October 2012, a 9,000 square foot space in the... More
Painted Earth
Arch 65, The Catacombs, Stables Market, Camden, Camden Town, London NW1 | 5.2 miles from Tower Hamlets Cemetery Park
As well as housing a renowned ceramic art gallery, Painted Earth offers kids a fantastic opportunity to test their own artistic talents. Supervised by friendly... More
Portman Square
W1H | 5.5 miles from Tower Hamlets Cemetery Park
This private garden square in Marylebone offers a secluded and peaceful place to get away from it all. On the north side three... More
Primrose Hill Road, Primrose Hill, London NW3 | 5.6 miles from Tower Hamlets Cemetery Park
This small, grassy, hilly park, boasting fantastic views over London, has become increasingly popular with the young, the trendy and the famous – particularly from... More
Grosvenor Waterside, 30 Gatliff Road, Pimlico, London SW1W | 5.7 miles from Tower Hamlets Cemetery Park
Purple Dragon is a dream playground, kindergarten, day nursery and private members' for kids. Relocated from its original location in Battersea, the exclusive club... More
Proud Chelsea
161 Kings Road, Chelsea, London SW3 | 6.4 miles from Tower Hamlets Cemetery Park
Art gallery Proud Chelsea brings top quality rock 'n' roll photography to the heart of King's Road. There are several strings to the Proud bow... More
1A Sheldon Square, W2 | 6.4 miles from Tower Hamlets Cemetery Park
A peaceful canal-side new development within walking distance of Paddington Station and Marble Arch, Paddington Central is an 11 acre site, home to... More
Pump House Gallery
Battersea Park, SW11 | 6.5 miles from Tower Hamlets Cemetery Park
Built in 1861, the Pump House Gallery was originally a Victorian water tower supplying water to the lakes and cascades in Battersea Park. Following renovation,... More
Sheldon Square, Paddington, London W2 | 6.6 miles from Tower Hamlets Cemetery Park
A peaceful canal-side new development within walking distance of Paddington Station and Marble Arch, Paddington Central is an 11 acre site, home to big businesses... More
Portobello Road Market
Portobello Road, Notting Hill, London W11 | 7.6 miles from Tower Hamlets Cemetery Park
The famous Portobello Road antiques and flea market in Notting Hill takes place every Saturday although there are also stalls from Monday to Friday. Running... More
Pottery Cafe
735 Fulham Road, SW6 | 8.1 miles from Tower Hamlets Cemetery Park
All Fulham mums know and love the Pottery Cafe - it's practically a rite of passage for new mums to take their babies here to... More
Plus One Gallery
The Piper Building, Peterborough Road, Belgravia, London SW6 | 8.1 miles from Tower Hamlets Cemetery Park
Within the iconic Piper building, known for the large panels on the outside of the building by the famous British artist John Piper... More
Pagoda at Kew
Kew Gardens, TW9 | 11.5 miles from Tower Hamlets Cemetery Park
The ornate Pagoda at Kew affords spectacular views across the botanical gardens and beyond, across the rooftops of London. If you visit the gardens it... More
PM Gallery and House
Walpole Park, Mattock Lane, W5 | 12 miles from Tower Hamlets Cemetery Park
Bought by the architect John Soane in 1800, Pitzhanger Manor house - which now includes the PM Gallery and House - was to become the... More
322 Richmond Road, East Twickenham, TW1 | 13 miles from Tower Hamlets Cemetery Park
All Richmond mums know and love the Pottery Cafe - it's practically a rite of passage for new mums to take... More
People's Palace
Queen Mary, University of London, Mile End Road, Tower Hamlets, London E1 | 9 minutes walk from Tower Hamlets Cemetery Park
The historic People's Palace on Mile End Road was originally built to provide the people of the East End with diverse entertainments and is now... More
Photo-Space
530 Commercial Road, Tower Hamlets, London E1 | 18 minutes walk from Tower Hamlets Cemetery Park
photo-space is a pop-up gallery in a temporarily vacant shop which is waiting to be let commercially.... More
Pumphouse Educational Museum
Lavender Pond & Nature Park, Lavender Pumphouse Lavender Road, Southwark, London SE16 | 24 minutes walk from Tower Hamlets Cemetery Park
This museum houses a private collection of artefacts from the Thames foreshore in Rotherhithe. The story of Rotherhithe is told through its unique collection, which... More
Warburton Street Fields, Hackney, London E8 | 30 minutes walk from Tower Hamlets Cemetery Park
67 Wilton Way, E8 | 2 miles from Tower Hamlets Cemetery Park
Posted is a temporary exhibition space in a former post office in East London and is one of a series of projects funded by Hackney... More
99 Hoxton Street, Hoxton, London N1 | 2.2 miles from Tower Hamlets Cemetery Park
Near Tower Hamlets Cemetery Park
From cheap budget places to stay to luxury 5 star hotels see our special offers for Tower Hamlets Cemetery Park hotels, including DoubleTree by Hilton Tower of London from 62% off.
Hotels near Suburban Collection Showplace, USA
Hotels near The Bridgewater Hall, United Kingdom


France wants images of its prisons blurred online. A killer escaped from a prison near Paris. He was called the "jailbreak king". He has escaped from prison many times. His friends used a helicopter to get him out. They used online maps to help them. Blurring all images of prisons will help to stop future jailbreaks.
People use online photos to carry out crimes. A French official said: "It's not normal that photos of security buildings such as our prisons are...on the Internet." Google said its maps used pictures from other companies. It gave the companies a list of sensitive places and asked them to take the necessary steps.
France wants (1) ___________________ prisons blurred online. A killer escaped from (2) ___________________ Paris. He was called the "jailbreak king". (3) ___________________ from prison many times. His (4) ___________________ helicopter to get him out. They used (5) ___________________ help them. Blurring all images of prisons will (6) ___________________ future jailbreaks.
People use online photos (7) ___________________ crimes. A French official said: "It's (8) ___________________ photos of security buildings (9) ___________________ prisons are...on the Internet." Google said (10) ___________________ pictures from other companies. It gave the companies (11) ___________________ sensitive places. and asked them (12) ___________________ necessary steps.


text:
FREAK implementation on Github (1-bit Quantized Difference of Gaussians Descriptor)
A while back, Pierre let us know about FREAK, Fast Retina Keypoint, a competitor to SIFT. I mentioned that "As soon as the code is there, I'll make a longer mention of it". Today is the day: The paper is FREAK: Fast Retina Keypoint by Alexandre Alahi, Alexandre; Raphael Ortiz, Pierre Vandergheynst. The abstract reads:
A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT), Speed-up Robust Feature (SURF), and more recently Binary Robust Invariant Scalable Keypoints (BRISK) to name a few. These days, the deployment of vision algorithms on smart phones and embedded devices with low memory and computation complexity has even upped the ante: the goal is to make descriptors faster to compute, more compact while remaining robust to scale, rotation and noise. To best address the current requirements, we propose a novel keypoint descriptor inspired by the human visual system and more precisely the retina, coined Fast Retina Keypoint (FREAK). A cascade of binary strings is computed by efficiently comparing image intensities over a retinal sampling pattern. Our experiments show that FREAKs are in general faster to compute with lower memory load and also more robust than SIFT, SURF or BRISK. They are thus competitive alternatives to existing keypoints in particular for embedded applications.
From the conclusions:
We have presented a retina-inspired keypoint descriptor to enhance the performance of current image descriptors. It outperforms recent state-of-the-art keypoint descriptors while remaining simple (faster with lower memory load). We do not claim any biological significance but find it remarkable that the used learning stage to identify the most relevant Difference of Gaussians could match one possible understanding of the resource optimization of the human visual system. In fact, as a future work, we want to investigate more on the selection of such relevant pairs for high level applications such as object recognition.
The attendant algorithm is on Gitbub
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.
labels: compressed sensing, compressive sampling, compressive sensing, CS, implementation, MF, PierreVandergheynst, QuantCS
The partying, the Ferraris, the sex-symbol status, the need to change the world, the unbearable lightness of being is not there but everything else is, is this not good enough ?
Faster Block Sparse Bayesian Learning Implementations
Zhilin sent me the following:
Dear Igor,
Thank you for introducing my BSBL work in your blog. I have updated the BSBL codes
The package includes BSBL-EM, BSBL-BO and EBSBL-BO. The codes are much faster than the old versions. Further, the package contains a fold, which has demo files to perform the whole experiment in my telemonitoring post i.e. using BSBL-BO to recover the fetal ECG recordings and then using FastICA to do decomposition. This may be convenient to those people who want to try the experiment but are not familiar with ICA.
Best,Zhilin
The posts Zhilin refers to are:
Is compressed sensing really useful for wireless telemonitoring of non-sparse physiological signals (Part 2)?
Codes of the BSBL Family and Demos for Telemonitoring of ECG have been updated
Thanks Zhilin
By Igor at 5/31/2012 03:21:00 AM 3 comments: Links to the entry
labels: compressed sensing, compressive sampling, compressive sensing, CS, implementation, MF
Can somebody give some love ...
.... to this answer ? It's been at zero for a day.
Cosparsity
Sparsity is about non-zeros elements, cosparsity being the opposite of sparsity, it is about the non non-zeros.
labels: compressed sensing, compressive sampling, compressive sensing, cosparsity, CS
Bound-Optimization based Block Space Bayesian Learning - implementation -
Zhilin just wrote the provocative Is compressed sensing really useful for wireless telemonitoring of non-sparse physiological signals (Part 1)? where he makes the case that in most physiological signals the small stuff is sometimes as important as the large ones and that in effect in most conditions these signals are not sparse or barely compressible. This is exactly what Yonina Eldar was saying at the MIA 2012 meeting when she was talking about compressed beamformining [1] additonal work into sub-Nyquist sampling can be found in [2] and [3]. Zhilin however takes a different route it seems, i.e. more in line with structured sparsity. Going back to Zhilin's argument:
.....Clearly, we can see, if a compressed sensing algorithm can be widely used in wireless telemonitoring, it must has the ability to recover non-sparse physiological signals, which completely contradicts the sparsity assumption in all the compressed sensing algorithms.
One may ask, there is another way for compressed sensing of non-sparse signals: suppose a non-sparse signal can be represented in a transform domain (e.g. wavelet domains, DCT domains, etc), such that the representation coefficients are sparse, i.e., x = Bz,
where x is the signal, B is the basis of the transform domain, and z is the representation coefficients. Then, the signal x is compressed by, y = Ax,
where y is the compressed signal, and A is the sensing matrix. In the remote terminal, the compressed data y and the matrix product AB are used to recover the sparse coefficients z according to the relation: y = (AB) z. And then the original signal x is recovered by the relation x = Bz.
However, the success of this method relies on the sparsity of the representation coefficients z. Unfortunately, for most physiological signals, z is not sparse enough, and completely recovering z is still a challenge for most compressed sensing algorithms (especially the sensing matrix A is a binary sparse matrix, a requirement of telemonitoring with low energy consumption)....
The paper introducing the Bound-Optimization based Block Space Bayesian Learning is: Low Energy Wireless Body-Area Networks for Fetal ECG Telemonitoring via the Framework of Block Sparse Bayesian Learning by Zhilin Zhang, Tzyy-Ping Jung. , Scott Makeig , Bhaskar D. Rao . The abstract reads:
Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a telemonitoring system via a low-power wireless body-area network for ambulatory use is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in compressing data with low power consumption. However, due to some specific characteristics of FECG recordings such as non-sparsity and strong noise contamination, current CS algorithms generally fail in this application. In this work we utilize the block sparse Bayesian learning (bSBL) framework, a recently developed framework solving the CS problems. To illustrate the ability of the bSBL methods, we apply it to two representative FECG datasets. In one dataset the fetal heartbeat signals are visible, while in the other dataset are barely visible. The experiment results show that the bSBL framework is capable of compressing FECG raw recordings and successfully reconstructing them. These successes rely on two unique features of the bSBL framework; one is the ability to reconstruct less-sparse but structured signals, and the other is the ability to learn and exploit correlation structure of signals to improve performance. These two abilities of the framework greatly enhance the potential use of bSBL in telemonitoring of other physiological signals.
The BSBL-BO algorithm to break through the bottleneck in wireless telemonitoring using compressed sensing is here. Stay tuned to part 2 of this argument:
[1] Compressed Beamforming in Ultrasound Imaging by Noam Wagner, Yonina C. Eldar, Arie Feuer, Zvi Friedman.
[2] Innovation Rate Sampling of Pulse Streams with Application to Ultrasound Imaging by Ronen Tur, Yonina C. Eldar, Zvi Friedman.
[3] Sub-Nyquist Radar, Omer Bar-Ilan and Yonina C. Eldar
labels: compressed sensing, compressive sampling, compressive sensing, CS, implementation, MatrixFactorization, MF
Around the blog in 80 hours: Compressive Sensing and Advanced Matrix Factorization Edition
Since the last "around the blogs in 80 hours" blog entry, I had to answer a pretty common beginner's question in The answer is still No. We then had a large Compressive Sensing This Week entry and eventually a stream of papers and implementation on Analysis Operators that started with an implementation featured in Noise Aware Analysis Operator Learning for Approximately Cosparse Signals. Then the subject slided into inpainting with 90% missing pixels and you reconstructed that ?! Analysis Operator Learning and Its Application to Image Reconstruction and Inpainting Algorithm on GitHub (TV-L2 denoising and inpainting). I ended having to comment on Learning Analysis Operators. In the meantime, there is an implementation available for Incremented Rank PowerFactorization algorithm. Other entries/tweets that caught my attention included the following:
Suresh mentions the Summer School on Massive Data Mining in August in Copenhagen.
Emmanuel has a full entry on his release of an OpenCV/C++ implementation of TV-inpainting capability I mentioned here. It's in French but here is a Google translation.
Vladimir points to Brandywine's 1 Gigapixel Hyperspectral CMOS Sensor
Djalil mentions Simulating random walks bridges
Roberto looks deeper in Particle Sketches / 2 - Working Around The Central Limit Theorem
Bob talks about the Paper of the Day (Po'D): Semantic gap?? Schemantic Schmap!! Edition
Laurent and Petros pointed to this piece entitled "A World Without Referees" by Larry Wasserman
And then some comments:
One of Vladimir Ignatovich's work in ultra-cold neutrons has been trying to figure out why some neutrons at very low energy get absorbed. He has done some analysis on the cross section needed to account for this loss but to my knowledge has never been able to figure it out experimetnally. It remains an open problem it seems. The arxiv blog points to a paper that computes the probability these neutrons go into other worlds. Sigh....How is this Science ? Ok let's imagine they go to to other worlds,.how do you prove that experimentally ? is this reproducible ? after they have disappeared you wait for neutrons to come back ? But if they leak out, there should be some leaking in ? I am shaking my head as I am writing this.
What happened to shoddy journalism ? you don't have to look too far this week.
Finally, The astronauts on the ISS caught a Dragon
Credit photo: ESA/NASA. Opening the SpaceX Dragon's hatch.
labels: compressed sensing, compressive sampling, compressive sensing, CS, MatrixFactorization, MF
A Comment on Learning Analysis Operators
In the blog entry Inpainting Algorithm on GitHub (TV-L2 denoising and inpainting), Martin Kleinsteuber commented:
Hi everyone, "The first approach may yield better results in the inpainting stage but requires a learning phase." This sentence suggests that an operator has to be learned for every individual inpainting task. However, the operator is learned offline and universal, a replacement for the TV, so to speak. It would be interesting to see how a combination of both approaches would perform
I wholeheartedly agree with Martin, if I gave the impression it was an unsurmountable issue then clearly it is not (if you have the time and inclination to perform this calibration). I also agree with him that given the learned analysis operator, one can use verbatim the methods used by Emmanuel to get similar results and it would be great to eventually compare these two approaches. But, to me, one of the most important aspect of Analysis Operator Learning and Its Application to Image Reconstruction by Simon Hawe, Martin Kleinsteuber, Klaus Diepold is.the following: interesting line of thoughts triggered by this:
"...We want to point out that this choice of parameters leads to a suitable general analysis operator, i.e. an operator with sparsifying property for the class of all natural images. It is thinkable that for more specific classes of images, for example medical imagery, other parameters may lead to a more suitable operator. .."
And indeed where would the learning of the analysis operator be of further interest ? How is the analysis operator different from say the TV if it is learned from samples taken
from the same camera with the same lens ?
The same cameras with different lenses ? or different setting for those lenses ?
with widely differing specific natural images ?
Most synthetic experiments perform a calibration of the analysis operator with stock (2d) images, how is the analysis operator different
with a 3d physical natural scene ?
with scenes taken different kind of sensors like SEM or a random lens imager ?
In the end , how do we compare those different analysis operators ? What sort of information does it bring to the hardware maker ? to the sensor designer ? to the calibration process ?
By Igor at 5/26/2012 05:09:00 PM 2 comments: Links to the entry
labels: calibration, compressed sensing, compressive sampling, compressive sensing, CS, MatrixFactorization, MF
Inpainting Algorithm on GitHub (TV-L2 denoising and inpainting)
In light of the recent entry showing the results of an inpainting algorithm within an Analysis Operator Learning approach, Emmanuel d'Angelo let me know that he made available his TV-L2 denoising and inpainting code on Github. The photo above represents another 90% missing pixel reconstruction of Lena. The two approaches are very different in that the analysis operator approach is first learned in the first paper whereas in the case of Emmanuel's code, the analysis operator is given ( Finite Difference/TV). The first approach may yield better results in the inpainting stage but requires a learning phase.
Emmanuel is still writing up his thesis so he is pretty busy for the moment, hence only the inpainting component of the more general algorithm is available. The general algorithm will include a fast version that can deal with the speed of video streams. According to him
" The TV-L2 denoising is exactly what is described in the Chambolle-Pock [1], Alg. 1 of the primal-dual paper (no acceleration). The inpainting procedure is not described as is in the paper, but can be considered as a straightforward deduction from this same paper"
On his blog he describes the algorithm in more detail, it is in French however, so let me translate the remarks:
The functional used here is nothing remarkable: it is the famous ROF, namely argmin 1/2 ∥ Ax-y∥^2_2 + λ ∥ x ∥ TV, where A is a random mask and TV is Total Variation.
The implementation is slightly modified to simulate an infinite parameter λ where the mask is nonzero, and 0 otherwise.
The algorithm used is called primal-dual and is described this paper [1].
For the Open Lab dys et EPFL, I wrote a demo that used the video stream from a webcam on the Mac, which made quite an impression (and not just among the general public). It is used by my boss regularly when he wants to impress visitors. The algorithm was FISTA this time (Ref. 2), which converges fast..
The demo was initially written in the days of Mac OS X 1.5 Leopard withOpenCV version 1.0. Changes to QuickTime and OpenCV made that demo almost obsolete, so I invite you instead to go to the version of the code on Github.
He added in a follow-up e-mail on the state of the current code on Github
The code is C++ only, and targeted to work with OpenCV 2.4 and later. My optical flow code will be both OpenCV/C++ and GPGPU/OpenCL (it will be a bug free version of the one I presented at ICIP). I also want to add multithreading with Grand Central Dispatch (aka libdispatch), which is an Apple equivalent of Intel TBB. GCD is open sourced and available for Mac OS, iOS, and FreeBSD.
If I have the time to implement a "good" wavelet transform, I will submit it top the main OpenCV module.
Let us stay tuned for the optical flow algorithm on the Github repository that will run at 30 fps. In the meantime, Emmanuel's publications are listed here.
[1] A first-order primal-dual algorithm for convex problems with applications to imaging, Antonin Chambolle et Thomas Pock Journal of Mathematical Imaging and Vision, 2011, Volume 40, Number 1, Pages 120-145
[2] A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. Amir Beck and Marc Teboulle, SIAM J. Imaging Sci. 2, 183 (2009), DOI:10.1137/080716542
To Catch a Dragon
Awesome. Congrats to the ISS crew and SpaceX!
More on NASA TV.
"Open the pod bay doors, Hal."
Dragon being under the shadow on the ISS reminded of a study we did for the Space Shuttle approach using Crtech's SINDA/ThermalDesktop application. It's on CRTech's site: (click on the image below for the animation)
The Station crew is now go for approach. All of it can be watched on NASATV.
ISS as Viewed for SpaceX Dragon: Approach Operations start in ten minutes
More news and update on the SpaceX website (and webcast in 10 minutes). There will a similar feed at NASA TV but from the station's perspective. It's a beauty
credit: SpaceX
SpaceX Dragon as viewed from the ISS: Approach in 45 minutes.
It looks like SpaceX Dragon is switching from its primary to its secondary mission, i.e. berth to the International Space Station. More news and update on the SpaceX website (and webcast in 45 minutes). I am sure there will a similar feed at NASA TV but from the station's perspective. Woohoo.
Incremented Rank PowerFactorization algorithm - implementation-
Justin Haldar sent me the following:
I just came across your Matrix Factorization Jungle website, and thought you might like to list the Incremented Rank PowerFactorization algorithm that Diego Hernando and I published about a while back:(Rank-Constrained Solutions to Linear Matrix Equations Using PowerFactorization )
It's a fast greedy algorithm that solves a rank-constrained version of the matrix recovery inverse problem, and empirically seems to have advantages over convex-relaxation approaches in a number of settings (previously mentioned on Nuit-Blanche:). It's also been used for sparsely-sampled medical imaging reconstruction problems: See:
Low-rank approximations for dynamic imaging
Spatiotemporal imaging with partially separable functions: A matrix recovery approach
Low rank matrix recovery for real-time cardiac MRI
Here is my response
I am torn and you might help me in figuring this thing out.
You may have noticed that the Matrix Factorization Jungle only features implementations that people can download. It is just too difficult to keep track of any and all implementations that are eventually never available (for whatever reason). I would love to feature your solver. Is there anyway you could make something available even if it is at a prototype level (for a small dataset) ? I could then point to you for people who would want something with more strength.
Igor.
If you recall, I had a small rant about this a while back in Nobody Cares About You and Your Algorithm and the argument still stands. Help me help you become a rock star. Some people might not take the message kindly as it goes against some old habit of academia but Justin was not one of these people, he wrote back the next day the following:
With your encouragement, I've created a simple stripped-down Matlab implementation that people can download from here:
http://mr.usc.edu/download/irpf
Thanks Justin, it is now on the Matrix Factorization page! The IRPF page starts with:
Incremented Rank PowerFactorization: Sample Code
This page provides sample code for a basic Matlab implementation of the Incremented Rank PowerFactorization (IRPF) algorithm. IRPF is a fast greedy algorithm that solves a rank-constrained version of the matrix recovery problem:
The algorithm was originally described in:
J. P. Haldar, D. Hernando. "Rank-Constrained Solutions to Linear Matrix Equations using PowerFactorization." IEEE Signal Processing Letters 16:584-587, 2009.
[IEEE link] [PubMed Central link]
Slightly more detail about the algorithm can be found in Chapter 5 of:
J. P. Haldar. "Constrained Imaging: Denoising and Sparse Sampling." Ph.D. Dissertation, University of Illinois at Urbana-Champaign, May 2011.
The dissertation also includes application examples and additional references involving the use of IRPF in the context of spatiotemporal magnetic resonance image reconstruction. The use of IRPF and related methods in medical imaging applications continues to grow (so keep watching the literature!).
A sample Matlab implementation of IRPF is available at the bottom of the page. There are many ways to implement IRPF, and different implementations can be more or less efficient depending on the problem context. This particular version uses the iterative conjugate-gradient algorithm for matrix inversion (rather than direct matrix inversion as was described in the original paper). Some features of this iterative approach are briefly mentioned in a [conference paper] and in the Ph.D. dissertation referenced above. Other versions are available on request.
Sample results are provided below, which can be recreated using sample code provided alongside the IRPF implementation.
labels: CS, implementation, MatrixFactorization, MF
90% missing pixels and you reconstructed that ?! Analysis Operator Learning and Its Application to Image Reconstruction
I missed the following paper in yesterday's Compressive Sensing This Week review but one of the author, Simon Hawe, kindly mentioned it to me:
Analysis Operator Learning and Its Application to Image Reconstruction by Simon Hawe, Martin Kleinsteuber, Klaus Diepold. The abstract reads:
Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes that images can be decomposed into a linear combination of very few atoms of some dictionary, is now a well established tool for the design of image reconstruction algorithms. An interesting alternative is the analysis model, where the signal is multiplied by an analysis operator and the outcome is assumed to be the sparse. This approach has only recently gained increasing interest. The quality of reconstruction methods based on an analysis model severely depends on the right choice of the suitable operator.
In this work, we present an algorithm for learning an analysis operator from training images. Our method is based on an $\ell_p$-norm minimization on the set of full rank matrices with normalized columns. We carefully introduce the employed conjugate gradient method on manifolds, and explain the underlying geometry of the constraints. Moreover, we compare our approach to state-of-the-art methods for image denoising, inpainting, and single image super-resolution. Our numerical results show competitive performance of our general approach in all presented applications compared to the specialized state-of-the-art techniques.
Simon also showed me what the Omega operators looked like after the learning process as I wanted to know how far they were from a simple derivative-TV operator. Here is what he had to say:
....On Page 12 Figure 3 you see the atoms of the operator we have learned within all our experiments [see above] . They look more like higher order derivatives than first order derivatives as in the TV case. We played a little bit around with the optimization, and if we introduce a prior which enforces the atoms themselves to be sparse than the output does highly look like TV, see the attached image.[see below]
After the Noise Aware Analysis Operator Learning for Approximately Cosparse Signals featured earlier this week, the collection of approach to learning these analysis operator is growing. Simon tells me their implementation should be out soon. A new era where the fields of signal processing and mathematical physics are colliding, is born.
and yes, 90 percent missing pixels!
Compressive Sensing This Week
We started the week with a tour of some of the blogs in Around the blogs in 80 hours: Compressive Sensing Edition , then we discovered an implementation of a Noise Aware Analysis Operator Learning for Approximately Cosparse Signals and finally answered some questions on why sparsifying a known signal (adding zeros to it) is a bad idea for sampling. Today we have a slew of papers related to compressive sensing and include two hardware instances, enjoy!
Minimum Complexity Pursuit: Stability Analysis by Shirin Jalali, Arian Maleki, Richard Baraniuk . The abstract reads:
A host of problems involve the recovery of structured signals from a dimensionality reduced representation such as a random projection; examples include sparse signals (compressive sensing) and low-rank matrices (matrix completion). Given the wide range of different recovery algorithms developed to date, it is natural to ask whether there exist "universal" algorithms for recovering "structured" signals from their linear projections. We recently answered this question in the affirmative in the noise-free setting. In this paper, we extend our results to the case of noisy measurements.
Fast Correlation Computation Method for Matching Pursuit Algorithms in Compressed Sensing by Kee-Hoon Kim, Hosung Park, Seokbeom Hong, Jong-Seon No, Habong Chung . The abstract reads:
There have been many matching pursuit algorithms (MPAs) which handle the sparse signal recovery problem a.k.a. compressed sensing (CS). In the MPAs, the correlation computation step has a dominant computational complexity. In this letter, we propose a new fast correlation computation method when we use some classes of partial unitary matrices as the sensing matrix. Those partial unitary matrices include partial Fourier matrices and partial Hadamard matrices which are popular sensing matrices. The proposed correlation computation method can be applied to almost all MPAs without causing any degradation of their recovery performance. And, for most practical parameters, the proposed method can reduce the computational complexity of the MPAs substantially.
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit by Alexandra Carpentier, Rémi Munos . The abstract reads:
We consider a linear stochastic bandit problem where the dimension $K$ of the unknown parameter $\theta$ is larger than the sampling budget $n$. In such cases, it is in general impossible to derive sub-linear regret bounds since usual linear bandit algorithms have a regret in $O(K\sqrt{n})$. In this paper we assume that $\theta$ is $S-$sparse, i.e. has at most $S-$non-zero components, and that the space of arms is the unit ball for the $||.||_2$ norm. We combine ideas from Compressed Sensing and Bandit Theory and derive algorithms with regret bounds in $O(S\sqrt{n})$.
Dynamic Compressive Sensing of Time-Varying Signals via Approximate Message Passing by Justin Ziniel, Philip Schniter. The abstract reads:
In this work the dynamic compressive sensing (CS) problem of recovering sparse, correlated, time-varying signals from sub-Nyquist, non-adaptive, linear measurements is explored from a Bayesian perspective. While there has been a handful of previously proposed Bayesian dynamic CS algorithms in the literature, the ability to perform inference on high-dimensional problems in a computationally efficient manner remains elusive. In response, we propose a probabilistic dynamic CS signal model that captures both amplitude and support correlation structure, and describe an approximate message passing algorithm that performs soft signal estimation and support detection with a computational complexity that is linear in all problem dimensions. The algorithm, DCS-AMP, can perform either causal filtering or non-causal smoothing, and is capable of learning model parameters adaptively from the data through an expectation-maximization learning procedure. We provide numerical evidence that DCS-AMP performs within 3 dB of oracle bounds on synthetic data under a variety of operating conditions. We further describe the result of applying DCS-AMP to two real dynamic CS datasets, as well as a frequency estimation task, to bolster our claim that DCS-AMP is capable of offering state-of-the-art performance and speed on real-world high-dimensional problems.
Progressive compressive imaging from Radon projections by Sergei Evladov, Ofer Levi, and Adrian Stern . The abstract reads:
In this work we propose a unique sampling scheme of Radon Projections and a non-linear reconstruction algorithm based on compressive sensing (CS) theory to implement a progressive compressive sampling imaging system. The progressive sampling scheme offers online control of the tradeoff between the compression and the quality of reconstruction. It avoids the need of a priori knowledge of the object sparsity that is usually required for CS design. In addition, the progressive data acquisition enables straightforward application of ordered-subsets algorithms which overcome computational constraints associated with the reconstruction of very large images. We present, to the best of our knowledge for the first time, a compressive imaging implementation of megapixel size images with a compression ratio of 20:1.
Recovery of partially occluded objects by applying compressive Fresnel holography by Yair Rivenson, Alon Rot, Sergey Balber, Adrian Stern, and Joseph Rosen. The abstract reads:
A compressive Fresnel holography approach is suggested for the recovery of partially occluded objects. Reconstruction guarantees are analyzed and the effectiveness of the method is demonstrated using simulations and an experimental result showing the reconstruction of a partially occluded resolution chart.
Optical compressive change and motion detection by Yuval Kashter, Ofer Levi, and Adrian Stern. The abstract reads:
Localization information of moving and changing objects, as commonly extracted from video sequences, is typically very sparse with respect to the full data frames, thus fulfilling one of the basic conditions of compressive sensing theory. Motivated by this observation, we developed an optical compressive change and motion-sensing technique that detects the location of moving objects by using a significantly fewer samples than conventionally taken. We present examples of motion detection and motion tracking with over two orders of magnitude fewer samples than required with conventional systems.
Optimal compressed sensing reconstructions of fMRI using deterministic and stochastic sampling geometries by Oliver Jeromin, Marios S Pattichis and Vince D Calhoun. The abstract reads:
Compressive sensing can provide a promising framework for accelerating fMRI image acquisition by allowing reconstructions from a limited number of frequency-domain samples. Unfortunately, the majority of compressive sensing studies are based on stochastic sampling geometries that cannot guarantee fast acquisitions that are needed for fMRI. The purpose of this study is to provide a comprehensive optimization framework that can be used to determine the optimal stochastic or deterministic sampling geometry, as well as to provide optimal reconstruction parameter values for guaranteeing image quality in the reconstructed images.
I just came across the following project page: on Graph Spectral Compressed Sensing
Project Overview:
In this project, we consider a signal whose entries are supported on the nodes of a graph. We study the metric to measure the smoothness of signals supported on graphs and provide theoretical explanations for when and why the Laplacian eigenbasis can be regarded as a meaningful "Fourier" transform of such signals. Moreover, we characterize the desired properties of the underlying graph for better compressibility of the signals. For a smooth signal with respect to the graph topology, our work proves that we can gather measurements from a random subset of nodes and then obtain a stable recovery with respect to the graph Laplacian eigenbasis, leveraging ideas from compressed sensing. We also show how such techniques can be used for both temporally and spatially correlated signals sampled by wireless sensor networks. Significant savings are made in terms of energy resources, bandwidth, and query latency by using this approach. All the theoretical analysis and the performance of proposed algorithms are verified using both synthesized data and real world data.
Two publications so far:
Approximating signals supported on graphs by Xiaofan Zhu and Michael Rabbat. The abstract reads:
In this paper, we investigate the notion of smoothness for signals supported on the vertices of a graph. We provide theoretical explanations when and why the Laplacian eigenbasis can be regarded as a meaningful "Fourier" transform of such signals. Moreover, we analyze the desired properties of the underlying graphs for better compressibility of the signals. We verify our theoretical work by experiments on real world data
Graph spectral compressed sensing for sensor networks,by Xiaofan Zhu and Michael Rabbat. The abstract reads:
Consider a wireless sensor network with N sensor nodes measuring data which are correlated temporally or spatially. We consider the problem of reconstructing the original data by only transmitting M N sensor readings while guaranteeing that the reconstruction error is small. Assuming the original signal is "smooth" with respect to the network topology, our approach to gather measurements from a random subset of nodes and then interpolate with respect to the graph Laplacian eigenbasis, leveraging ideas from compressed sensing. We propose algorithms for both temporally and spatially correlated signals, and the performance of these algorithms is verified using both synthesized data and real world data. Significant savings are made in terms of energy resources, bandwidth, and query latency
Density-based group testing by Dániel Gerbner, Balázs Keszegh, Dömötör Pálvölgyi, Gábor Wiener. The abstract reads:
In this paper we study a new, generalized version of the well-known group testing problem. In the classical model of group testing we are given n objects, some of which are considered to be defective. We can test certain subsets of the objects whether they contain at least one defective element. The goal is usually to find all defectives using as few tests as possible. In our model the presence of defective elements in a test set Q can be recognized if and only if their number is large enough compared to the size of Q. More precisely for a test Q the answer is 'yes' if and only if there are at least \alpha |Q| defective elements in Q for some fixed \alpha.
of note the following excerpt:
....The concept of group testing was developed in the middle of the previous century. Dorfman, a Swiss physician intended to test blood samples of millions of soldiers during World War II in order to find those who were infected by syphilis. His key idea was to test more blood samples at the same time and learn whether at least one of them are infected [3]. Some fifteen years later Rényi developed a theory of search in order to find which electrical part of his car went wrong. In his model – contrary to Dorfman's one – not all of the subsets of the possible defectives (electric parts) could be tested [6]. Group testing has now a wide variety of applications in areas like DNA screening, mobile networks, software and hardware testing....
Faster than Nyquist but Slower than Tropp et al by Andrew Harms, Waheed U. Bajwa, Robert Calderbank. The abstract reads:
This paper presents a significant modification to the Random Demodulator (RD) of Tropp et al. for sub-Nyquist sampling of frequency-sparse signals. The modification, termed constrained random demodulator, involves replacing the random waveform integral to the operation of the RD with a constrained random waveform that has limits on its switching rate because fast switching waveforms may be hard to generate cleanly. The result is a relaxation on the hardware requirements with a slight, but manageable, decrease in the recovery guarantees of the RD. The paper also establishes the importance of properly choosing the statistics of the constrained random waveform. If the power spectrum of the random waveform matches the distribution on the tones of the input signal (i.e., the distribution is proportional to the power spectrum), then recovery of the input signal tones is improved. The theoretical guarantees provided in the paper are validated through extensive numerical simulations and phase transition plots.
Compressed Sensing for Denoising in Adaptive System Identification by Seyed Hossein Hosseini, Mahrokh G. Shayesteh. The abstract reads:
We propose a new technique for adaptive identification of sparse systems based on the compressed sensing (CS) theory. We manipulate the transmitted pilot (input signal) and the received signal such that the weights of adaptive filter approach the compressed version of the sparse system instead of the original system. To this end, we use random filter structure at the transmitter to form the measurement matrix according to the CS framework. The original sparse system can be reconstructed by the conventional recovery algorithms. As a result, the denoising property of CS can be deployed in the proposed method at the recovery stage. The experiments indicate significant performance improvement of proposed method compared to the conventional LMS method which directly identifies the sparse system. Furthermore, at low levels of sparsity, our method outperforms a specialized identification algorithm that promotes sparsity.
Gradually Atom Pruning for Sparse Reconstruction and Extension to Correlated Sparsity by Seyed Hossein Hosseini, Mahrokh G. Shayesteh. The abstract reads:
We propose a new algorithm for recovery of sparse signals from their compressively sensed samples. The proposed algorithm benefits from the strategy of gradual movement to estimate the positions of non-zero samples of sparse signal. We decompose each sample of signal into two variables, namely "value" and "detector", by a weighted exponential function. We update these new variables using gradient descent method. Like the traditional compressed sensing algorithms, the first variable is used to solve the Least Absolute Shrinkage and Selection Operator (Lasso) problem. As a new strategy, the second variable participates in the regularization term of the Lasso (l1 norm) that gradually detects the non-zero elements. The presence of the second variable enables us to extend the corresponding vector of the first variable to matrix form. This makes possible use of the correlation matrix for a heuristic search in the case that there are correlations among the samples of signal. We compare the performance of the new algorithm with various algorithms for uncorrelated and correlated sparsity. The results indicate the efficiency of the proposed methods.
An Inversion Formula for Orlicz Norms and Sequences of Random Variables by Soeren Christensen, Joscha Prochno, Stiene Riemer. The abstract reads:
Given an Orlicz function $M$, we show which random variables $\xi_i$, $i=1,...,n$ generate the associated Orlicz norm, i.e., which random variables yield $\mathbb{E} \max\limits_{1\leq i \leq n}|x_i\xi_i| \sim \norm{(x_i)_{i=1}^n}_M$. As a corollary we obtain a representation for the distribution function in terms of $M$ and $M'$ which can be easily applied to many examples of interest.
Fast projections onto mixed-norm balls with applications by Suvrit Sra
Joint sparsity offers powerful structural cues for feature selection, especially for variables that are expected to demonstrate a "grouped" behavior. Such behavior is commonly modeled via group-lasso, multitask lasso, and related methods where feature selection is effected via mixed-norms. Several mixed-norm based sparse models have received substantial attention, and for some cases efficient algorithms are also available. Surprisingly, several constrained sparse models seem to be lacking scalable algorithms. We address this deficiency by presenting batch and online (stochastic-gradient) optimization methods, both of which rely on efficient projections onto mixed-norm balls. We illustrate our methods by applying them to the multitask lasso. We conclude by mentioning some open problems.
Video rate Atomic Force Microscopy (AFM) imaging using compressive sensing by Ning Xi ; Ruiguo Yang ; Lai, K.W.C. ; Chengeng Qu. The abstract reads:
Atomic Force Microscopy (AFM) is a powerful tool for nano-size imaging. The advantage of AFM is that it can get extraordinary high resolution image at atom level. However, AFM obtains the sample topography image through scanning on the top of sample line by line, therefore it takes couples minutes to get an image and this negative point makes it difficult to continuously observe surface change during manipulation. In this paper, a novel approach for compressive sensing based video rate AFM imaging system is proposed. In this method, compressive sensing is used for sampling topography information of sample surface efficiently. Compressive sensing could use fewer measurements for data sensing to recovery the image through image reconstruction algorithm. This technique decreases the scanning time for AFM scanner because of fewer measurements needed. The video rate for this new approach could reach as high as 1.75 seconds per frame.
Since the paper is behind a paywall, I gathered this other excerpt on the interweb
Atomic Force Microscopy (AFM) is a useful tool in nano scale imaging in both air and liquid. However, an AFM usually takes several minutes to get an image due to the limitation of the scan rate. Therefore it is difficult to use an AFM to observe dynamic changes in real-time. There is an increasing demand on fast imaging AFM system. Hardware improvement might be one of the solutions. But it needs much faster and stable AFM scanner and controller to achieve fast scan. In reality, it is still difficult to obtain high resolution and stable video-rate imaging. In this presentation, a methodology to achieve a video-rate AFM imaging by smart scan will be introduced. Based on the theory of compressive sensing, new scan patterns have been developed. Instead of scanning line by line over the imaging area, a special pattern will be developed based on the characteristics of the image. As a result, it is no longer necessary to scan everywhere in a sample to get an image. The selected scanning will provide sufficient information to recover the entire image. This will significantly reduce the amount of the scanning time and achieve a videorate AFM imaging. Furthermore, the video-rate AFM images can also provide accurate position information of an AFM probe. It can be used to replace the position sensor that usually introduces measurement noises and to enable high-precision motion control. A new non-vector space motion controller for nano-scale manipulation has been developed using the video-rate AFM images. These new imaging and motion control methods have been successfully applied to many applications such as observing chemical synthesis in real time, nano robotic manipulation, and nano assembly
I am still not quite if this is an incoherent measurement or some inpaiting.
from some of the same author, we also have: Compressive Feedback based Non-vector Space Control by Jianguo Zhao, Bo Song, Ning Xi , King Wai Chiu Lai, Hongzhi Chen, and Chengeng Qu
Abstract—A non-vector space control method based on compressive feedback is presented in this paper. The non-vector space means the control is not performed in traditional vector space but in the space of sets. Consider an initial set and a goal set, a stabilizing controller is designed to make the set dynamics converge to the goal set. The compressive feedback means the controller works even when only partial elements of the feedback set are available; that is, the same controller can still stabilize the set dynamics around the goal set with the compressive feedback. The controller is applied to visual servoing by considering images as sets. In this way, image processing for feature extraction is not required, which is an essential process in conventional servo methods. Moreover, the compressive feedback can reduce the size of feedback image. It is important when the sampling is time consuming such as imaging using atomic force microscopy (AFM). The visual servoing formulation of the controller is further applied to the motion control in nanomanipulations. Simulation results suggest good performance of the controller. The framework proposed in this paper can be extended to other systems where the signals can be represented as sets
A short proof of Paouris' inequality by Radosław Adamczak, Rafał Latała, Alexander E. Litvak, Krzysztof Oleszkiewicz, Alain Pajor, Nicole Tomczak-Jaegermann. The abstract reads:
We give a short proof of a result of G. Paouris on the tail behaviour of the Euclidean norm $|X|$ of an isotropic log-concave random vector $X\in\R^n$, stating that for every $t\geq 1$, $P(|X|\geq ct\sqrt n)\leq \exp(-t\sqrt n)$. More precisely we show that for any log-concave random vector $X$ and any $p\geq 1$, $(E|X|^p)^{1/p}\sim E |X|+\sup_{z\in S^{n-1}}(E | z,X |^p)^{1/p}$.
You might be wondering why this isotropic log-concave random vector is of importance to compressives ensing ? reading Geometric properties of random matrices with independent log-concave rows/columns by Radosław Adamczak might help.
Finally, we have a presentation ACCELERATION OF HIGH ANGULAR AND SPATIAL RESOLUTION DIFFUSION IMAGING USING COMPRESSED SENSING by Merry Mani, Mathews Jacob, Arnaud Guidon, Chunlei Liu, Allen Song, Vincent MagnoGa , Jianhui Zhong
labels: AMP, compressed sensing, compressive sampling, compressive sensing, CS, CSHardware
Guessing Names Based on What They Start With - Based on names data from the Social Security Administration, we look at trends, how common your name is, and how similar it is to others. *Tags:* Amelia Mc...
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The answer is still No
Congratulations SpaceX !
Falcon 9 is in Orbit. Woohoo!
t's a GO for Space X Falcon9/Dragon. Woohoo!
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Launch aborted.
Falcon 9 / Dragon Launch in 15 minutes.
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As Republican lawmakers and Donald Trump's inner circle start hacking away at Obamacare, some Americans are getting worried. The Current shares stories of hope and fear for the future of health care under President Donald Trump.
Republicans are planning a vote for March 23, in the U.S. House of Representatives to repeal and replace Obamacare – seven years to the day after Obamacare was signed into law.
The Congressional Budget Office estimates 14 million Americans could lose health insurance coverage by next year under the Republican plan.
According to the Obama administration, its Affordable Care Act provided health insurance to 20 million Americans who didn't have it before.
But critics say Obamacare gives Americans too little choice in their health-care plans and providers, and ultimately drives up cost.
Mark Jenkins, a retired priest in Michigan, is not yet old enough to qualify for insurance under Medicare, which provides it to seniors. He pays for a plan under the Affordable Care Act.
Jenkins tells The Current's Anna Maria Tremonti, he's done the math and figures the Republican proposal would see his insurance bill jump much higher.
"They say they don't want to pull the rug out from underneath us, but I don't know how else you could define it," he says.
"I think that they're reckless, and I think that they're rushed," Jenkins says of politicians in Congress pressing ahead with health-care changes.
"People are going to find themselves without care. Lower-income people are already having more health problems than upper-income people because they can't afford to eat as well," he explains.
"I don't like to exaggerate, but I really think people will die."
Californian Charis Hill has ankylosing spondylitis, a chronic form of arthritis that causes inflammation of joints in the spine. It can become debilitating and, if left untreated, can result in vertebrae in the spine fusing together.
"It's scary to have this disease, and then have to face this possible need to fight even harder for my health care," Hill tells Tremonti.
The treatments she requires are very expensive — thousands of dollars for each infusion. To pay for those treatments, she has health insurance under Medicaid, the program that provides insurance to low-income Americans.
Medicaid was expanded under the Affordable Care Act, raising the income level at which recipients can qualify. The new plan would see funding to states for the program cut.
Hill believes she would still qualify for Medicaid under the new plan. But as she explains, qualifying for coverage and accessing care aren't the same thing.
"If states have less funding for the same amount of people who are still enrolled in Medicaid, then states have to decide where that funding goes, what treatments are seen as an option for people," she says.
"And since I have a very expensive treatment ... thousands and thousands of dollars of treatment [every] eight weeks — the state could decide that that's not necessary for me."
This segment was produced by The Current's Sam Colbert.


Dearest Princess Amelia I thought that you might like a blog post about nonsense song lyrics. Songs that might have been written by your Daddy. This will be the first nonsense lyric post of many I hope. I also hope that you like the song, it is called "Rama Lama Ding Dong" and it's by Rocky Sharpe and the Replays in 1979. The song was originally by an American group called the Edsels and has been covered by many groups, including one that has a rather nonsense name; Showaddywaddy. I hope you and your Mummy and daddy enjoy a little Rama Lama Singalong now 🙂 I have added some funny versions of the song too.
Just to help you Mummmy and daddy and all the people in Godderwil to sing along here are the words.
Love her, love her so.
That I'll never, never let her go.
She's mine all of the time.
Princess Amelia meets a monster!


text:
Rik Gluaert
LGBTI People in Nepal Demand to be Counted
Rik Gluaert July 30, 2019
LGBTI rights advocates in Nepal have encouraged the government to conduct a census of the LGBTI community.
According to local LGBTI publication Pahichan, the government last conducted a survey 10 years ago.
They found 4,000 people identified as LGBTI.
But, according to Pahichan, Nepal's population of LGBTI people numbers more than 500,000.
They report that about 300 LGBTI public service sector workers are out. This suggests the number of LGBTI people in the whole country is much higher than 4,000.
Now that the government has shown interest in conducting a census of the LGBTI population, activists are urging the government to conduct the research in a sensitive way.
'Bureau [of statistics] should arrangement separate forms targeting this community' Pahichan urges.
It also urged non-governmental LGBTI groups to assist the LGBTI community to partake in the census.
Both the UK and Hong Kong have recently considered collecting census data on the LGBTI community.
In Hong Kong, experts said a census would provide empirical evidence of LGBTI citizens.
Proposals for the United Kingdom's next census, in 2021, include voluntary questions about sexual orientation and gender identity.
If the questions are approved, it will be the first time the UK has tracked this information in their census.
LGBTI life in Nepal
The mountainous South Asian country also legalized gay sex in 2007.
Theoretically, it has laws to protect LGBTI equality. But, local activists have warned, that is not always the case in practice.
Furthermore, many LGBTI Nepalis have rejected the third gender on citizenship documents. This is because it does not guarantee accompanying rights.
For example, Nepalis are unable to get driving licenses with a third gender ID.
'There has always been a romanticization of Nepal as being one of the more tolerant countries in Asia; however, the ground reality is very different' organizer of this year's pride parade Rukshana Kapali said.
A new criminal code enacted in August last year failed to guarantee equal marriage.
Lawmakers last year promised the LGBTI community parliament would continue to discuss and advocate for LGBTI issues.
These included citizenship issues, same-sex marriage, domestic violence, adoption, and access to health and education.


KP3 was created by Katie Horner as a means to help individuals on their pursuit of a healthy lifestyle. Katie Horner is a Registered Dietitian, Licensed in the state of South Carolina. She has a Masters in Exercise Science and holds her Personal Training Certification and Corrective Exercise Specialist Certification from the National Academy of Sports Medicine.
Katie works in a Surgical Weight Loss office where she counsels patients who have had weight loss surgery on diet and exercise. She also works as a Nutrition Counselor with a local health club and area universities to assist athletes with their nutrition goals.


176 Evian went under contract yesterday. The 2BR 2nd floor flat was listed at $289,000.
Good news for those thinking about listing. With that in mind, Can we send you a FREE market analysis of your property?
Interested in purchasing? No one knows the market better or will do a better job of educating you on the market and find you the right opportunity.


The Martin GPCPA5 is one of our most affordable Performing Artist Models, this Grand Performance(GP) Cutaway is great for gigging or practicing at home.
It features a top of solid sitka spruce and back and sides of mahogany-patterned HPL, and Fishman F1 Analog electronics to help it sing onstage.
This guitar is a real winner!