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Catch up TV on Harry's Arctic Heroes. Watch the latest and all other episodes of Harry's Arctic Heroes now online, broadcasted on ABC1. Catch up on your favorite ABC1 TV show: Harry's Arctic Heroes. Replay tv on its best! Prince Harry joins four British soldiers, wounded in the conflict in Afghanistan on an ambitious 260 km charity trek to the North Pole.
Prince Harry and the team have arrived at the ice cap. They must now navigate treacherous landscape conditions whilst pulling their own 100 kilo sledges, to reach the geographic North Pole.
Prince Harry joins four British soldiers wounded in the conflict in Afghanistan on an ambitious 260 km charity trek to the North Pole. In this opening episode Prince Harry joins his fellow servicemen in training.


Ethnologue recently announced an update. Since, at least online, they are the easiest to find and hence most commonly cited authority on worldwide language distribution, this merits some comment. They've made some improvements in North Africa, including a much prettier map. However, there still remain a fair number of errors. This is perhaps natural given that SIL, which produces Ethnologue, is basically a Christian missionary organisation and as such is unwelcome in a number of countries. (Why is there no neutral source doing something comparable, one might ask? UNESCO has attempted a language endangerment atlas, but sadly that one is both less complete and far less reliable.) However, quite a few errors could have been avoided simply by closer attention to sources.
In Algeria, they've updated the Korandjé entry with my population estimate and endangerment classification, and corrected the Tashelhiyt one based on my thesis - although they apparently couldn't be bothered to cite the source of this estimate! They've reclassified the Berber dialects of the Southwest (Boussemghoun, Igli, etc.) as Taznatit, along with the Berber of Timimoun; in previous editions, the former were classed as part of Moroccan Tashelhiyt. The new classification is rather more tenable than the old one, at any rate; the former dialects are not called "Taznatit" by their speakers, but they are rather closely related to it, and are not at all closely related to Moroccan Tashelhiyt.
There are still a fair number of errors, though: the Tarifit of Arzew became extinct a century ago (and there is no such place as "Alteria"); "Tamazight de l'Atlas blidéen" is rather more like Kabyle than like Chenoua, and is missing from their map; the boundaries they give for Kabyle are rather inflated, annexing the Arabic-speaking areas of the Boumerdes coast to the west and half of Jijel in the east; the enormous circle they draw for Teggargarent contrasts oddly with the tiny ones they draw for Korandjé and Temacine Tamazight, which in reality occupy comparable areas (perhaps this was to take into account Ngouça, but the latter oasis is even smaller than Ouargla); Hassaniyya Arabic is still missing even though it's the primary language of Tindouf; and the curiously precise boundaries they give for "Saharan Arabic" leave me baffled as to what this "language" is supposed to be. The "Algerian Arabic" dialect of Jijel or Skikda is far more different from the Algiers koine than the "Algerian Saharan Arabic" I heard in Bechar or Timimoun or Abadla; perhaps the dialect further east is more different, but the boundaries shown are indefensible. They also seem to have misunderstood the constitutional amendment: it's Tamazight in general that is legally a national language now, although it's admittedly Kabyle that benefits the most in practice.
In Morocco, they've belatedly figured out that Ghomara and Senhaja are still spoken - for the past several editions they've been labelled extinct - but according to the entry French has no presence in the Moroccan linguistic landscape, unlike Algeria or Tunisia. For Egypt, their map ignores Gara (the other oasis where Siwi is spoken), and their population figures for Siwi are extremely optimistic. For Libya, their map (unlike their text) ignores Zuwara, while grossly inflating Ghadames and Sokna (especially in contrast to Siwi, which actually occupies a much larger oasis). For Mauritania, they still include the apocryphal Imraguen "language", whose reported existence Catherine Taine-Cheikh deconstructs in a forthcoming article, and their population figures of Zenaga are mutually inconsistent bad guesses which should have been updated based on the introduction to the latter's Dictionnaire zénaga-français.
I just finished reading Benmayouf's (2009) La question linguistique en Algérie. It was... interesting.
This view, of course, ignores a long history of Standard Arabic in Algeria – the zaouias' continued presence even after the French confiscated most of their land, the manuscripts and imported books of my grandfather's generation, the excellent work of Ben Badis and the Association of Ulema starting in 1931, the expanding ranks of Arabophone intellectuals and writers since independence (tellingly, she finds time to mention Jean Amrouche but not Ahlam Mostaganemi), and even the satellite dishes tuned to Arabic channels. If Francophone professors and officials have felt threatened by institutional Arabisation, their extremely successful efforts to hold it back in turn denied (and deny) positions to the much more numerous Arabophone graduates. The social tensions caused by this did help set the stage for the violence of the 1990s, but that can hardly be blamed on Arabic, let alone caricatured in the terms above.
As for her vision of the future, I would consider it close to a worst-case scenario. Her tactical and qualified support for Algerian Arabic does not entail actually using it for anything important; while rather hostile to Standard Arabic as a medium for university education, she takes it for granted that French is appropriate in that context, and indeed is the perfect vehicle for anything related to modernity. But, frankly, I do not want a French-language-mediated "transfer of modernity from the north shore to the south shore of the Mediterranean" (p. 118); I want an Algeria with the self-confidence and self-awareness to learn from a variety of examples and choose its own path, not mechanically follow in France's footsteps. Nor do I believe that relegating "modernity" to a foreign language is likely to help Algeria achieve it!
Nonetheless, I'm glad I read the book. It's fascinating – if sad – to discover that there exists an Algerian intellectual prepared to take a position this extreme in favour specifically of French; I don't believe I've ever met one. Could one find a corresponding phenomenon in France, I wonder – some professor eagerly advocating for more English in the bureaucracy and the universities, and condemning supporters of French as narrow-minded nationalists? It's difficult to imagine... But what this book mainly leaves me wondering, to be frank, is: why on earth does the author feel this way? And that points the way towards a more anthropologically oriented book that I really would like to see. A person's feelings towards a language are shaped by memories – a mother's voice or a teacher's scolding, a story you couldn't put down or a tedious manual, a group that you hung out with or couldn't stand. To really understand the wide variation in Algerian language attitudes, we need to go beyond the political history and into experiences of learning and living the languages.
I work in France now. When I give an internal lecture, I normally do it in French - poor French, to be sure, but French. If I attend a local conference, I can usually assume that at least some of the presentations will be in French. The handful of classes I've taught here, I taught in French. Needless to say, all the internal paperwork (of which, thankfully, there isn't that much) is written in French, and I am expected to fill it out in the same language. This is not particularly convenient for me, but I expect it and approve of it. Most French academics have to speak English to be able to do their jobs well, of course. But if they shifted to using English in all contexts and relegated French to informal conversation in coffee breaks, then French academia, while it would be more hospitable to Anglo-Saxon academics, would become far less hospitable to its own citizens, who after all are the ones paying for it!
Let's shift perspectives for a second. Since 1988, the large majority of every new year's crop of university students has gone through their whole prior education being taught in Arabic, whether you approve of that or not. This was expected since well before 1988, so there was plenty of time to prepare for it; in fact, the policy of Arabising education had been consistently proclaimed since before independence, and has enjoyed widespread popular support in most parts of the country. A primary job of a university professor is to teach these students. Under the circumstances, is it really plausible to suggest that knowledge of Arabic is just an irrelevant distraction from academic ability? Yet, not just in 1988 but now, 25 years later, at least half the subjects on offer are still being taught in French. How would an ordinary English-speaking freshman - even one who had studied German in high school - react if he heard that all national universities' courses in medicine were henceforth to be taught in German?
References Benmayouf, Chafia Yamina. 2009. La question linguistique en Algérie : enjeux et perspectives. Biarritz: Séguier.


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digital programmers 0:0:0 or look at polishers and tumblers at electrictumblers.co.uk
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Before February 2019, Paragon used three programmers: a Sentry Xpress 4.0 3-key or a Sentry 2.0 12-key developed by the Orton Ceramic Foundation and Paragon, or a Sentinel SmartTouch touch-screen programmer developed by Bartlett and Paragon.
In February 2019, two were modified, leading to the Sentry Xpress 5.0 3-key and the Sentry 3.0 12-key. The modifications had little effect on the basic functionality so kilns might ship with the older programmers for some time.
All three are made as ramp-hold, or cone-fire and ramp-hold. Your kiln will have the appropriate programmer although, if it has a Sentry Xpress ramp-hold, you can upgrade it to cone-fire ramp-hold. If the kiln's front panel is large enough, you can upgrade from a Sentry Xpress 3-key to a Sentry 12-key or a Sentinel SmartTouch.
Generally, the programmers on kilns for bead annealing, enamelling, glass, jewellery, knife-making, and metal clays have one firing mode: ramp-hold. And the programmers on kilns for ceramics, earthenware, porcelain, and stoneware have two firing modes: cone-fire and ramp-hold.
Unlike calculators, programmers aren't made 10 million at a time. Although they look like simple circuit boards, they include sophisticated feature-rich embedded software that has taken years to develop and refine.
RAMP HOLD
Ramp Hold.
The programmer runs a sequence that you have set, or one that's in its memory from a previous firing. A sequence usually has a mix of ramp and hold segments, for example: it could heat to 800°C at full speed then hold for 30 minutes. When the sequence ends, the programmer beeps, and the kiln cools in it's own time.
A ramp segment of a sequence can control the rate of heating or cooling, for example: the kiln could heat up at 200°C per hour from 200°C to 800°C, which would take three hours. Or, the kiln could cool down at 100°C per hour from 600°C to 200°C, which would take four hours.
The heating rate cannot exceed the rate at which the kiln would heat up if it was full on. The cooling rate cannot exceed the rate at which the kiln would cool if it was turned off. At full speed the elements are on all the time. During set ramps and holds they turn on and off repeatedly to maintain the heating rate, hold temperature, or cooling rate.
Cherry Heaven TV provides on-line programmes on the Cherry Heaven TV Player. To use the player, click the controls or drag the time-line slider or volume slider to a new position.
If the kiln you've chosen has a Sentry 12-key programmer, or you're considering an upgrade, here's a Cherry Heaven TV programme about setting a ramp-hold sequence.
CONE FIRE
Cone Fire.
Cone-fire is simple: just enter the cone number. Although they're a great time-saver, you'll learn more about firing if you sometimes use ramp-hold: each segment of a sequence can have a heating rate, target temperature, and hold time. It's easier to adjust sequences, add segments, experiment, and copy published sequences for materials that may need stepped heating or cooling.
The programmer is easy to use: far easier than a central heating programmer. Here's a Cherry Heaven TV programme about setting a cone-fire sequence. Setting a cone number means that the programmer will run a sequence of segments automatically. Of course, UK-EU programmers will be in degrees Celsius.
Cherry Heaven TV provides on-line radio and television programmes using the Cherry Heaven Player. To play, pause, or stop the player, or adjust the volume, click the controls or, whilst it's playing, drag the time-line slider to a new position.
THE SENTRY XPRESS 3-KEY DIGITAL CONTROLLER: RAMP-HOLD
The Paragon Sentry Xpress Controller.
Generally, this ramp-hold programmer is used on smaller kilns, such as the BlueBird and SC-2, or on glass kilns like the CS and Fusion. You can set up, and re-use, four sequences of up to eight heating, holding, and cooling segments: and do something else whilst the sequence is running. Ramp-hold also allows you to programme slow cooling: useful, for example, for annealing or controlling the colours of ceramic glazes.
Paragon programmers do not have pre-set ramp-hold programmes: you can easily set up and re-use your own. Pre-set fixed programmes might seem to be an advantage. However, having experimented and diversified, many people fire materials, or combinations of materials, at different temperatures and for different times than are recommended.
Some of its features are:
Skip Segment skips past a segment during Ramp-Hold firing.
Hold maintains the temperature for a set time.
Program Review lets you check that the program you are about to fire is correct.
Temperature Display throughout firing and cooling can be set to °F or °C.
Error Messages report problems such as a disconnected thermocouple, stuck relay, or broken element.
Delay starts a count-down timer which sets a delayed start time.
It stores 25 sequences, each with up to 20 segments.
Three LEDs show whether you are in programme, review, or firing mode.
The programmer beeps when the set firing sequence comes to an end.
Your kiln will come with a comprehensive instruction manual. Drying and firing metal clays is consistently easy whereas when working with glass you'll probably need to experiment.
SENTRY XPRESS 3-KEY DIGITAL CONTROLLER: CONE-FIRE OR RAMP-HOLD
Generally, this programmer is used on high-temperature kilns, such as the Caldera and Xpress. You can set up your own sequences using up to eight segments. There are two firing modes:
Ramp-Hold, generally used for enamelling metal clays, glass fusing, and glass slumping, allows you to customize the firing using multiple times and temperatures in eight different segments.
Ramp-Hold also allows you to programme slow cooling: useful, for example, for controlling the colours of ceramic glazes. However, plainly, the kiln cannot cool any quicker than it would do if the power was turned off.
Cone-Fire, generally used for ceramics, pottery, stoneware, glazes, china painting, and decals, fires to a set pyrometric cone number listed in the Orton cone tables. It's not designed for Art Clay, heat treating, glass work, and enameling.
Cone-Fire will only be successful if you understand how cones and cone numbers work. Unlike a programmer, a cone is a visual indicator that your work has been fired for the correct combination of kiln temperature, kiln atmosphere, and time.
Your kiln will come with a comprehensive instruction manual. Drying and firing metal clays is consistently easy whereas, working with ceramics, you'll probably need to experiment.
SENTRY XPRESS 12-KEY DIGITAL CONTROLLER
The Paragon Sentry Cone-Fire And Ramp-Hold Programmers.
Generally, this programmer is used on the larger kilns where it's extra features are important. There are two configurations: ramp-hold and cone-fire ramp-hold.
Ramp-Hold, generally used for enamelling, glass work and metal clays allows you to customize the firing using multiple times and temperatures in up to twenty different segments.
Cone-Fire, generally used for ceramics, pottery, stoneware, glazes, china painting, and decals, fires to a set pyrometric cone number listed in the Orton cone tables.
Cone-Fire will only be successful if you understand how cones and cone numbers work. Unlike a programmer, a cone is a visual indicator that your work has been fired for the correct combination of kiln temperature, kiln atmosphere, and time. To learn more about cone numbers and cone-firing, go to cone-fire using the link below the menu bar.
Stop/Back goes back one step at a time to correct programming errors.
Add Time adds five minutes to a hold.
Present Status shows the segment that is currently running.
Program Review lets you check that the programme you are about to fire is correct.
Options to set up aspects of the sequence.
It connects to a computer via an RS232 interface to monitor the sequence and produce grahical data.
It can control a kiln vent.
It can control a gas flow meter.
SENTINEL SMART TOUCH DIGITAL CONTROLLER
The Sentinel Touch Screen Programmer.
The Sentinel is a direct replacement for the Sentry 12-key. It fits in the same space and uses the same wiring harness, so it takes just a few minutes to change.
Here's a Cherry Heaven TV programme about using the Sentinel. Of course, UK-EU programmers will be in degrees Celsius.
Easy-clean touch screen.
Wi-Fi enabled for updates.
Continuous display of the voltage, in case there are any issues during firing.
Continuous display of the current, in case the elements are wearing.
Novice Mode with on-screen prompts.
Twelve ramp-hold programmes, each one with thirty two segments.
Skip Step will delete the current segment.
Add Segments adds extra segment to the whole programme.
Add Temperature increases the temperature of the current segment
Add Time adds time to a hold.
Your kiln will come with a comprehensive instruction manual. Drying and firing metal calys is consistently easy whereas, with heat treating, you'll probably need to experiment.
Glass Fusing.
If you've worked with with Art Clay, PMC, enamels, or glass, you'll probably know how a ramp-hold programmer works but, if you want to fuse properly, it'll help if you understand a multipart sequence. Here's a typical full fuse programme for pieces up to about 500mm square.
Segment 1. Ramp at 222°C per hour to 677°C and hold for 30 minutes
Segment 4. Ramp at 083°C per hour to 371°C and let it cool naturally
This is only a suggestion, so you'll need to buy a book, go to classes, experiment, or research on line. Generally, if you get cracks or bubbles, slow down the ramp rate.
CONE-FIRE
If you've worked with with Art Clay, PMC, enamels, or glass, you'll probably know how a ramp-hold programmer works but, if you want to work with ceramics, it'll help if you understand pyrometric cones. Although you don't have to use pre-set cone programmes: if you prefer, just set your own.
Pyrometric cones are slender pyramids, made from about 100 carefully controlled compositions, that measure the effect of time and temperature. As the cone nears its maturing range, it softens and the tip begins to bend down under it's own weight. Ceramics are usually sold with firing instructions, which include the cone number.
Cone-Fire, generally used for ceramics, pottery, stoneware, glazes, china painting, and decals, fires to a set pyrometric cone number listed in the Orton cone tables. It isn't used for Art Clay, heat treating, glass work, and enameling.
If you bought a ceramics kiln with a cone-fire programmer, you can fire using cones because the programmer is set up to use cone numbers. If you have a ramp-hold programmer, you'll need to be able to convert cone numbers to temperature and time. Of course, you can't use a cone that matures at a higher temperature than your kiln can maintain.
Cone numbers were originally set from 1 to 10, 1 being the coolest but cooler cones were then introduced from 022 to 01. To fire faster or slower than the segments listed, change the rates by 10 - 20%. However, the last segment should always be 108. The list below starts with the coolest, and is in degrees Fahrenheit.
Cone 022
Segment 1 Rate: 396 Temperature: 0979
Cone 09
Cone 1
As with so many things, there isn't a set of definitive rules about how to fire materials. Although you can be guided by friends, teachers, books, and the internet, part of the enjoyment and satisfaction comes from experiment.
Paragon Kilns, Furnaces, and Ovens For Annealing, Beads, Ceramics, Enamels, Glass, Jewellery, Knife Making, Lost Wax, Silver Clays, Heat Treating, Lampwork, Porcelain, And Vitrigraph.

redpajama_set_name: RedPajamaCommonCrawl


Do you spend more than your earnings? If such is the case then you must suspect Vastu in the house because directions in which you place heavy material are important to analyze which decides your expenses. Heavy material is never recommended in certain zones of house because they tend to sink money in irrelevant expenses. To save more what you earn, there is a need to examine some of home directions which are not apt for keeping weight such as East and North-east zone.
Ideal place for keeping heavy weight is South-west zone of house being the heavy zone it needs to be balanced by heavy material.
An alternative for dumping heavy stuff can be South-east zone.
North-west and South-west are again good options for keeping weight and to sink down your expenditure. This direction is believed to be ideal for keeping heavy stuff especially for people in politics and employees.
North-east and North-west zones must not be chosen for dumping heavy material and this area should have minimal things kept.
Keep North-east and East blocks must be kept free from any kind of material rather this zone should be empty & open so as to trigger down your expenditure gradually.


The Kids Can Child Development Center at SRRC provides quality educational play-based child care services to children with and without special needs that are developmentally appropriate to meet each child's needs. DCFS licensed, services are provided to children ages six weeks to 12 years and beyond in some cases.
We have eight classrooms and are open Monday – Friday, from 6:15 a.m. – 5:30 p.m.
Before and after school care and summer camp is available for school-aged children with and without special needs.
Each classroom is generally staffed by a teacher and either a second teacher or an assistant. In addition, we have floats and, at times, kitchen help in the Center. In the absence of our regular staff, substitute classroom staff, floats or other program personnel may be used. All substitute staff meet any relevant licensing requirements.
We are also privileged to have people who care enough to make a difference as a volunteer. These volunteers are a part of the team that works together with your child to make Kids Can a positive educational experience. Kids Can volunteers are required to adhere to the same standards of confidentiality as our staff. Our regular CDC volunteers are required to have a TB test and to submit to an Illinois State Police Criminal Background Check (if 18 or over).
The Center Director oversees all program operations.
Kids Can CDC has eight classes to serve children of different ages and abilities.
Inquiries are accepted over the telephone and in person at Starved Rock Center's main office at 1013 Adams Street, Ottawa, Illinois. Parents and guardians will be offered an opportunity to tour the building.
Although tours may be conducted anytime that we are open, we recommend that you do not tour between 12:00 and 2:30 as many of our children are either preparing for sleep or sleeping during that time.
We frequently have a waiting list for the CDC. Children on the waiting list are generally prioritized as follows: (a) children with special needs, (b) children with siblings already in the Center, (c) children of staff members, and (d) all other children. At times, we also need to look at age when prioritizing children on the waiting list. Starved Rock Center reserves the right to take other factors into consideration also. When we are notified of an opening, we will contact the next available family on the waiting list. Openings in the Center can be held for no longer than five days after notification of openings. If we do not hear from the family within that time, we will move onto the next family.
Priority is given to children attending full-time (five days per week). Slots for part-time care will be filled only if full-time children are not available. Part-time care of less than four days per week is considered temporary and their slot may be replaced by a family requesting full-time care.
In such a case, and if space allows, the part-time family will be allowed to become full-time. If they choose not to do so, we will terminate care after giving at least two weeks' notice.
Short-term child care services are available with prior approval from the Center Director when appropriate space is available. This service is not available for children who are sick. Nor is it available during days when school is in session for children who are enrolled in school. Payment for short-term day care is due on or before the day of service.
Kids Can CDC participates in the State of Illinois' Child Care Assistance Program (CCAP). Although Starved Rock Center will fax and/or mail documents upon request, parents and guardians are responsible for applying for CCAP and following all CCAP requirements.
Starved Rock Center staff can assist you by giving you an estimate of what you may owe if you are approved for the Child Care Assistance Program. However, please be aware that this is only an estimate. Your account will be modified based on the final decision made by the State of Illinois.
Families will be charged the full amount of tuition until such time as the State makes a decision on an application. In addition, full tuition will be charged upon termination from CCAP. Once we receive a decision from the State of Illinois, we will credit your account based on the State's decision. We will charge for co-pay and the difference between what the State pays and what we normally charge.
In addition to our child care services, Kids Can Child Development Center also provides a separate part-day preschool program for children ages three to Kindergarten.
The preschool operates September – May from 8:45 – 11:45. Parents have the choice of enrolling their child two, three, or five days a week. Kids Can's mission is to provide a loving environment for all children that is conducive to good development, exploration, imagination and cooperation.
For more information, please call 815-434-0857 or email info@starvedrockcenter.org.


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Crossing the Pacific Ocean
As we sailed away from Sydney, watching the iconic view of the Opera House and Harbor Bridge fade away into the distance, I started to feel a little emotional. Australia had been our home for three months, and continuing our journey eastward marked a fundamental turning point in our journey. Although we were taking a rather long, meandering and somewhat adventurous route, we were now officially "on our way home".
Sailing away from Sydney
Our last few days in Australia were also some of the happiest. We celebrated our first wedding anniversary in the Blue Mountains, felt amazed by how fast time flies when you are having fun, and we (almost by chance) met up with our friend Emma from Durham University in the small town of Katoomba.
With Emma in Katoomba
From Katoomba we took a train to central Sydney, and enjoyed our final night in Australia with our good friend Grant, who we have previously travelled with in Central America. Grant took us out to Bar Luca in the city center to sample the best burgers in Sydney. Having tried the best burgers in Singapore at Potato Head, and the best burgers 'in the world' at Fergburger in New Zealand (definitely oversold – our Fergburger burgers weren't even the best we had in New Zealand, let alone the world), Shane and I always welcome the opportunity to add another delicious 'best' burger to our international burger repertoire, and the 'Blame Canada' burger did not disappoint. We then went to the Opera Bar to enjoy picture perfect views of the Sydney Harbour Bridge and Opera House.
With Grant at the Opera Bar
By the next morning the view of Sydney Harbour had changed. There was a giant cruise ship (the Celebrity Solstice) right in the center, spoiling the perfect view for hundreds if not thousands of tourists. For us, however, this cruise ship was so much more than a terrible eyesore contaminating the Sydney skyline. This cruise ship was our new mode of transportation and our home for the next three weeks. The Celebrity Solstice would take us right across the planet's biggest, deepest ocean to the other side of the world.
Giant cruise ship blocking the view (thanks to Grant for this picture)
Embarking on the Celebrity Solstice ship was like saying goodbye to one life and saying hello to another. As this particular cruise was a "repositioning" cruise (to move the ship from one place to another), it was a surprisingly budget-friendly way to travel for three weeks, but involved living a not-very-typical-budget lifestyle (ideal).Gone were the days of bed bugs, horrible hostel dorm rooms, $2 Hungry Jacks burgers and long, tedious car journeys through blank landscapes. Instead we were in for a life of luxurious accommodation, all-you-can-eat extravaganza buffets and constant entertainment aimed at the over 65s. We quickly adapted to our new surroundings, making the most of the endless food, and taking a dip in the pool and hot tub while gazing at views of the Harbour Bridge and Opera House. Eventually it was time to set sail, and we watched as our new home slowly made its way out of Sydney, away from Australia and towards the big blue Pacific Ocean.
Relaxing on the ship in Sydney
The Pacific Ocean is huge. If all of the world's land area were squished up together and put in one place, it would still be smaller than the Pacific Ocean. On average, the Pacific Ocean is 4,000 metres deep, but reaches down as far as 11,000 metres deep at its deepest point. Cruising across from Australia to the USA involves looking out over a large expanse of blue water for a long time, but long days at sea were punctuated with stops at some extremely beautiful (and isolated) Pacific islands, and by lots of fun in the sun on board our floating hotel.
We settled into a relaxed routine on our days at sea. We would get up around 8.00am, and hit the gym in an attempt to counteract the millions of calories consumed at the buffet (and to prepare for our upcoming trek to Machu Picchu). Then Shane would have breakfast and we would meet for a 10.00am 'brainwaker trivia' quiz, which despite being aimed at people born before 1950, we somehow managed to win on one occasion (I'm not sure what that says about our youthful mentality). At 11am, we would usually go to a lecture on some aspect of Polynesian or Hawaiian culture or history, delivered by the ship's resident feminist historian Mary Amanda, and then it was time for lunch. We spent our afternoons relaxing at the pool, watching movies, attempting more trivia and sometimes taking part in other entertainment activities (such as the guests vs officers paper aeroplane competition, which saw Shane's paper aeroplane sail through the hoop of destiny, winning the accuracy component of the challenge, but being sadly beaten in the distance element by someone with a little too much time on their hands who had spent days preparing his extra large aeroplane).
All-you-can-eat buffet
One of the swimming pools on board
Main dining room
Handwashing our clothes as usual because laundry was too expensive
Snails for dinner
In the evenings we would have dinner with another younger couple – Rahul and Neha – from the USA and UK respectively, who were also on their honeymoon, and then we would settle into some good old fashioned cruise ship entertainment in the form of a broadway-style show, comedian, or other variety act. The standard of these shows was a little mixed, but a particular highlight was show called 'Euphoria', which featured all of the Celebrity Solstice singers and dancers, seemed to be based on Sweden's winning 2012 Eurovision song ('Euphoria', by Loreen), and contained a giant inflatable octopus. By the time the 'entertainment' was over, we were usually ready for bed.
Giant octopus in the show 'Euphoria'
After a few days on board and a couple of stops back in New Zealand, we reached a monumental moment on our journey: we crossed the International Date Line.
The concept behind the International Date Line is central to the plot of Jules Verne's book 'Around the World in Eighty Days', where Phileas Fogg attempts to travel eastward around the world in 80 days. To win the bet with his friends, Phileas Fogg must return by 8.45pm on Saturday 21 December, but he is delayed. When he arrives at 8.50pm on Friday 20 December, he believes it's Saturday 21st and that he has lost his bet by five minutes. Of course, because the International Date Line did not exist in 1872, he has added a full 24 hours to his clock as he has travelled around, but in fact, it's still Friday 20 December, and luckily for him everything is fine.
One good thing about slowly making your way around the world is that you never really encounter jet lag. Like Phileas Fogg, Shane and I have travelled eastward around the world at a gradual pace, and time usually shifts by just one hour at a time. When we cross a border into a new country, we often lose an hour of our lives. The effects of this are usually limited, but sometimes (particularly while driving on the Mongol Rally), we still had to watch out and be aware that shops, and hotel check-in would close an hour earlier over the other side of the border, and sunset would seem to come quicker every day.
Of course, this loss of time couldn't go on indefinitely as we continued around the world – otherwise, like Phileas Fogg, we would end up a day ahead of ourselves by the time we made it back to the U.K. – so at some point time has to reset, and the result is an imaginary line in the middle of the Pacific Ocean, half way round the world from the Greenwich Meridian. When we crossed the line, instead of setting our clocks forward by yet another hour, we set them back by 24 hours. We gained an entire extra day all at once!
In practice, this meant that for Shane and I, Monday 16th April happened twice. We got up in the morning, and it was Monday 16th April. We went to bed at night, and it was still Monday 16th April. We got up in the morning, and it was Monday 16th April (and so on). We took great delight in this, and celebrated by dancing the night away (on Monday 16th April) at the ship's International Date Line party, complete with Beyoncé and balloons. Anyone who had a birthday on Monday 16th April was lucky enough to celebrate twice, and Celebrity Cruises provided copious amounts of cake, two days in a row. Shane also took great delight in continually asking the staff at guest services what the date was. All in all, a great time was had, and we thoroughly enjoyed our extra day on Earth.
Crossing the Date Line
International Date Line Party
Crossing the International Date Line also marked the transition from one side of the world to another. We were as far away from the Greenwich Meridian (and from home) as it was possible to be. From Tuesday 17th April onwards, we started moving closer to home instead of further away from it.
As if crossing the International Date Line wasn't enough of a highlight, we then enjoyed three incredible days in French Polynesia. We had spent our sea days actively preparing for our arrival by attending lectures on the region's history and culture, as well as by watching the Disney movie Moana, set in Polynesia.
Our first stop was the island of Tahiti. We docked in the region's capital, Papeete, and were greeted to beautiful views of the green, mountainous landscape.
We wandered through the vibrant and colourful city of Papeete and picked up a hire car for the day, which allowed us to drive around the island in a loop and visit black sand beaches, white sand beaches, waterfalls, tropical gardens, caves and other hidden treasures.
It was hot and humid but it was also lush and tropical, with beautiful flowers around every corner.
Polyensian plants
Ancient religious site
Tahitian waterfall
The next day we took a four-wheel drive tour around the neighbouring island of Moorea – smaller and less developed than Tahiti, but with equally beautiful mountain views. We visited a number of beautiful sights, including Magic Mountain, a pineapple plantation, a rum distillery and the famous Belvedere viewpoint.
Our floating home enjoyed Moorea as much as we did!
Magic Mountain, Moorea
Belvedere Viewpoint, Moorea
Pineapple plantation, Moorea
Our final day in French Polynesia was also our favourite. We stopped in the island paradise of Bora Bora. Bora Bora has been on my list of places to visit ever since the scene in the movie 'The Parent Trap' where Annie (who is in California pretending to be Hallie), is caught making a phone call to Hallie (who is in London pretending to be Annie) in the middle of the night and explains her actions by saying she was calling her friend who "lives in New York, but is on vacation with her family in Bora Bora".
Other than this slightly obscure reference, I had no preconceived ideas about what Bora Bora would be like.
It turned out to be the most beautiful place we have ever been. Even more beautiful than the beautiful islands in Thailand, and the beautiful deserted beaches in Sumatra, and the beautiful Lake MacKenzie on Fraser Island, and the beautiful Whitsundays, and all the other beautiful places we have been lucky enough to visit on this trip and all other trips we have ever taken
As it is so expensive to get there and stay there, Bora Bora has relatively few visitors. The water is completely clear. The sand is perfectly round and soft. The islands are mountainous and green. The colours are vibrant, and it is simply paradise.
Loving Bora Bora
Swimming in the warm, shallow water
We took a snorkeling tour of the crystal clear waters, and were able to swim with more fish, sting rays and more sharks than we could count. Although the reef sharks and lemon sharks were smaller than scary great whites, they still had sinister expressions, white eyes and rows of sharp teeth, which still gave me a fright when they came straight towards me.
Sharky and Georg(ia)
Attempted shark selfie
Swimming with sharks
We also paddled in the empty beaches, and took a short trip to a private island where we had lunch on picnic benches in the sea, and saw stunning views of the whole area. "I think I have just taken the most beautiful photo anyone has ever taken of anything, ever", I said to Shane at one point. The serenity and the beauty of Bora Bora blew us away, and if only we had wifi, I would have been googling "how can I move to Bora Bora" within the hour.
Not a bad picnic spot
"The most beautiful picture anyone has ever taken, of anything, ever"
Still loving Bora Bora
French Polynesia (especially Bora Bora) was the ultimate paradise, and is somewhere that despite the long journey time from home and the inevitable associated expense, we would really like to come back to.
The journey from French Polynesia to Hawaii involved five days at sea, but with the continued entertainment on board the Celebrity Solstice, it felt like it took no time at all to reach the Big Island of Hawaii.
We had two stops in Hawaii on the way to the ship's final port of call on Oahu – the most populated Hawaiian island. First we stopped at the Big Island, where Shane and I hired a car to visit the Volcanoes National Park. We arrived at the perfect time – the volcano was starting to erupt so we were able to see some molten lava bursting up through the surface – but not enough to cause the damage to buildings, road closures and state of emergency which followed a few days later.
A small-scale eruption
We also walked through a lava tube, and hiked down into a volcanic crater.
Inside a lava tube
Shane in a volcano crater
We finished our day on the Big Island by visiting the famous 'Rainbow Falls' – which was a nice waterfall but missing its signature rainbow effect.
"Rainbow" Falls
Next we stopped at the port of Lahaina on Maui, which was a beautiful historic town filled with lovely shops and restaurants. It had a distinctly 'Hawaiian' feel, and it was difficult to resist buying a suitcase full of souvenirs. We settled on a surfboard-shaped chopping board, and left it at that.
From Maui, we stayed on the ship for the short journey to our final port of call – the island of Oahu – where we would be staying for another 10 days of Hawaiian fun. While we were sad to leave our luxury cruise ship (Hawaiian prices mean it's back to a joyful non-air-conditioned dormitory for us), we were still delighted to be in Hawaii, and to have successfully crossed the big, blue Pacific Ocean.
A certificate for the impressive achievement of sitting on a boat for three weeks
After days spent gazing out at the ocean, enjoying a relaxed lifestyle on board a cruise ship, encountering the wonders of French Polynesia and ending up in the Hawaiian islands, I realized that any sadness or apprehension I had felt about leaving Australia had disappeared the moment we sailed away from Sydney. We had a wonderful time in Australia, but the new chapter of our adventure has well and truly begun.
Aloha-ppy in Hawaii and California


BDO Underwater Ocean Exploration is Here!
BDO Underwater Swimming: Dive Right in!
Obviously, the Fish costume from the Pearl Shop will increase your swimming speed, but if you aren't planning to buy the convenience costume, you can also use elixirs, food and craftable costumes to increase your movement speed and stamina, and be able to breathe longer underwater.
See you under the sea!
UPDATE! Are you ready to head to deeper waters? Check out my video series on building the Epheria Sailboat!
BDO Special Seeds & the House Decor Items You can Grow!


text:
Q: MongoDB GridFS - How to use mongofiles(or some other utility) to delete all files? I would like to clean all the files from the GridFS of a particular Mongo database.  The mongofiles command line utility has a delete function but I don't know how to tell it do delete "all files".
I've been using MongoVue to select and delete the files in the fs view of GridFS but that only lets you delete specific number of selected files.
What I'm looking for is the SQL equivalent of
Delete * FROM

A:     db.fs.files.remove({})
    db.fs.chunks.remove({})
    db.repairDatabase()  (cleans out the memory)

running these commands should remove all files

redpajama_set_name: RedPajamaStackExchange


text:
\section*{Notice}

\textbf{\copyright 2021 IEEE. \textit{Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.}}

\section{Introduction}

Spam is mass text-based e-mails, such as advertising mailings, sent over the Internet. These texts are usually sent to thousands of e-mail addresses without being solicited.Apart from benign but annoying commercial spam, it often contains malicious hyperlinks pointing to various types of viruses, or phishing texts to lure individuals into providing sensitive data such as personal information, banking and credit card details, and passwords. This information is usually used to access important accounts and can lead to identity theft and financial loss. Spam can also be received on mobile phones in the form of short text messages (i.e sms). Most of them do not originate from another phone. Instead, they stem from a computer and are sent to one's phone, at virtually no cost to the sender, using an email address or an instant messaging account. Clicking a link in a spam text message can set up malicious software that can gather information about one's phone. This can also affect the performance of one's mobile phone by eating away at its memory space. This can also result in undesirable charges on one's mobile phone invoice. Identifying a message as spam is not an easy thing. Spam filters are usually offered by email or mobile phone providers. Many of these programs automatically check the contents of emails and blacklist the senders. This process works via a word list with typical spam phrases and expressions. However, no method can guarantee that spam is automatically and systematically recognized. In addition, it also happens that some important and expected emails end up in junk mail because of these filters. In this paper, we address this problem from a machine learning (ML) perspective. We propose a tool, which we call SpaML, for spam detection. This tool is based on a set of supervised and unsupervised machine learning models and relies on two Natural Language Processing (NLP) techniques that make up its two modes.

\section{Paper organization}

The rest of this paper is organized as follows. In Section \ref{sec3}, we give an overview of the Natural Language Processing (NLP) techniques we are using to convert messages into vectors of numbers. In Section \ref{sec5}, we present the SpaML architecture, as well as the base detectors it exploits.  In Section \ref{sec6}, we present our experiments, as well as the interesting results shown by SpaML regarding its accuracy and precision.  In Section \ref{sec7}, we discuss the results and we compare our research to other related pieces of research addressing the same problem.  In Section \ref{sec8}, we draw conclusions.

\section{Natural Language Processing Techniques} \label{sec3}

Natural Language Processing (NLP) is a field of Artificial Intelligence (AI). It has been used to predict diseases\cite{WashingtonGMAGWHL08}, analyze sentiment\cite{colingMurrayCJ18}, identify fake news\cite{icaartZhouGBH19}, recruit talent\cite{LytvynVR19}, detect cyberterrorism exchanges \cite{Castillo-Zuniga20}, etc. In this paper, we focus on two NLP techniques that convert natural texts into a vectors of numbers. These vectors will become the inputs of our ML models, which are used by our tool SpaML, to predict whether a vector, thus a text, is spam or ham (ham is another word for regular in this context). These two techniques are Bag of Words (BoW) and Term Frequency-Inverse Document Frequency (TF-IDF).

\subsection{Bag of words}

Bag of words  is the most basic technique of converting a text into a vector of numbers. The following is an example of how this works. Let us consider these three documents:

\begin{center}
\begin{tabular}{ l l }
$d_1$: & this is a dog \\
$d_2$: &  this is not a dog \\
$d_3$: & a dog is a special pet which is a friendly pet
\end{tabular}
\end{center}

First, we build a lexicon (i.e. set of vocabulary) from all the words appearing in all documents. The lexicon here is \{\textit{this, is, a, dog, not, special, pet, which, friendly}\}. Then, we take each of these words and score its occurrence in the text with 1 when the word exists and with 0 when the word does not. Then we sum the occurrences up. This is shown in Table \ref{tab:mytable1}.

\begin{center}
 \begin{table}[h]
\centering
    \caption{Bag of words}
    \label{tab:mytable1}
\scalebox{0.78}{
\begin{tabular}{| c| c|c| c| c|c|c|c|c|c|}
 \hline\xrowht[()]{10pt}
   \textbf{Times in}           &   \textbf{this}&   \textbf{is} &  \textbf{a}&  \textbf{dog} & \textbf{not}&  \textbf{special}&  \textbf{pet}  &  \textbf{which} &  \textbf{friendly}\\
 \hline\xrowht[()]{10pt}
$d_1$ & 1 &  1&  1&  1&  0& 0&0& 0& 0\\
 \hline\xrowht[()]{10pt}
$d_2$&   1&  1&  1&  1& 1 &0 &0&0&0\\
 \hline\xrowht[()]{10pt}
$d_3$&  0&  2& 3 & 1&  0& 1&2&1&1\\
\hline
\end{tabular}
}
 \end{table}
\end{center}

The resulting vectors for the documents $d_1$, $d_2$, and $d_3$ are (1,1,1,1,0,0,0,0,0), (1,1,1,1,1,0,0,0,0), (0,2,3,1,0,1,2,1,1), respectively.

This is the main idea behind BoWs. However, in practice, with long texts, we do not consider all the words in all documents to build the vectors of numbers. Instead, we only consider the most frequent words appearing in the documents by adding their occurrences in each document and ordering them. The number of the most frequent words tightly depends on its relevance to the study goals.

\subsection{Term Frequency-Inverse Document Frequency }

Term Frequency-Inverse Document Frequency is a more elaborated way to represent texts into vectors of numbers. In this technique, we first calculate the term frequency as follows:

\begin{equation} \text{TF}_{t,d} = \frac{\text{N}_{t,d}}{\text{NT}_d}  \label{eq1}\end{equation}

where $\text{N}_{t,d}$ is the number of times the term $t$ shows up in the document $d$, and ${\text{NT}_d}$ is the number of terms in the document $d$. Hence, every document has its own term frequency.

Then, we calculate the Inverse Document Frequency (IDF) for every term as follows:

\begin{equation} \text{IDF}_t = \text{Log (} \frac{{\text{ND}}}{\text{ND}_t}\text{)}  \label{eq2}\end{equation}

where $\text{Log}$ is the Logarithmic function, $\text{ND}$ is the number of documents, and $\text{ND}_t$ is the number of documents with the term $t$. The IDF measures the importance of a term for the documents. Finally, we calculate the  Term Frequency-Inverse Document Frequency (TF-IDF) score for every term in the documents as follows:

$$\text{TF}\_\text{DF}_{t,d} = \text{TF}_{t,d} \times \text{IDF}_t$$

The higher is the $\text{TF}\_\text{DF}_{t,d} $, the more important is the term. To be concrete, let us take the example of the previous subsection.  Since $d_1$ contains $4$ terms and the term  \textit{this} appears just once in $d_1$, then $\text{TF}_{d_1, this} = \frac{1}{4}$. The same thing for $\text{TF}_{d_1, is}$, $\text{TF}_{d_1, a}$, and $\text{TF}_{d_1, dog}$. Since the term \textit{not} does not appear in $d_1$, then $\text{TF}_{d_1, not} = 0$. The same thing for $\text{TF}_{d_1, special}$, $\text{TF}_{d_1, pet}$, $\text{TF}_{d_1, which}$, and $\text{TF}_{d_1, friendly}$.  Table \ref{tab:mytable2} presents the TF values for all the terms in the three documents.

\begin{center}
    \begin{table}[h]
\centering
    \caption{Term Frequency}
    \label{tab:mytable2}
\scalebox{0.78}{

\begin{tabular}{| l| l| l| l| l| l| l| }
 \hline\xrowht[()]{10pt}
      \textbf{Term}        &  N$_{d_1}$&  N$_{d_2}$ & N$_{d_3}$& TF$_{d_1}$ & TF$_{d_2}$ & TF$_{d_3}$ \\
 \hline\xrowht[()]{10pt}

      \textbf{this}        &  $1$&  $1$ & $0$& $\frac{1}{4}$ & $\frac{1}{5}$ & $0$ \\
 \hline\xrowht[()]{10pt}

      \textbf{is}        &  $1$&  $1$ & $2$& $\frac{1}{4}$ & $\frac{1}{5}$ & $\frac{2}{11}$ \\
\hline\xrowht[()]{10pt}

      \textbf{a}        &  $1$&  $1$ & $3$& $\frac{1}{4}$ & $\frac{1}{5}$ & $\frac{3}{11}$ \\
 \hline\xrowht[()]{10pt}
      \textbf{dog}        &  $1$&  $1$ & $1$& $\frac{1}{4}$ & $\frac{1}{5}$ & $\frac{1}{11}$ \\
 \hline\xrowht[()]{10pt}
      \textbf{not}        &  $0$&  $1$ & $0$& $0$ & $\frac{1}{5}$ & $0$ \\
 \hline\xrowht[()]{10pt}
      \textbf{special}        &  $0$&  $0$ & $1$& $0$ & $0$ & $\frac{1}{11}$ \\
 \hline\xrowht[()]{10pt}
     \textbf{pet}        &  $0$&  $0$ & $2$& $0$ & $0$ & $\frac{2}{11}$ \\
 \hline\xrowht[()]{10pt}
      \textbf{which}        &  $0$&  $0$ & $1$& $0$ & $0$ & $\frac{1}{11}$ \\
 \hline\xrowht[()]{10pt}
      \textbf{friendly}        &  $0$&  $0$ & $1$& $0$ & $0$ & $\frac{1}{11}$ \\
 \hline
\end{tabular}
}

\end{table}
\end{center}

As for the IDF values, since we have three documents, NT$_d = 3$. Since the term \textit{this} appears in just two documents, $d_1$ and $d_2$, then IDF$_{this} = \text{Log}(\frac{3}{2})=0.176$. Table \ref{tab:mytable3} contains the IDF values for all terms. Once done, the calculation of the TF\_DF becomes straightforward. This is given in Table \ref{tab:mytable4}. The resulting vectors for the documents $d_1$, $d_2$, and $d_3$ are (0.036,0,0,0,0,0,0,0,0), (0.035,0,0,0,0.095,0,0,0,0), (0,0,0,0,0,0.043,0.087,0.043,0.043), respectively.

\begin{center}
    \begin{table}[h]
\centering
    \caption{Inverse Document Frequency }
    \label{tab:mytable3}
\scalebox{0.78}{

\begin{tabular}{| l| l| l| l| l|}
 \hline\xrowht[()]{10pt}
     \textbf{Term}        &  N$_{d_1}$&  N$_{d_2}$ & N$_{d_3}$& IDF   \\
 \hline\xrowht[()]{10pt}

     \textbf{this}        &  $1$&  $1$ & $0$& Log($\frac{3}{2}$) = $0.176$  \\
 \hline\xrowht[()]{10pt}

     \textbf{is}        &  $1$&  $1$ & $2$& Log($\frac{3}{3}$) = $0$  \\
\hline\xrowht[()]{10pt}

     \textbf{a}        &  $1$&  $1$ & $3$& Log($\frac{3}{3}$) = $0$  \\
 \hline\xrowht[()]{10pt}
     \textbf{dog}        &  $1$&  $1$ & $1$& Log($\frac{3}{3}$) = $0$  \\
 \hline\xrowht[()]{10pt}
     \textbf{not}        &  $0$&  $1$ & $0$& Log($\frac{3}{1}$) = $0.477$  \\
 \hline\xrowht[()]{10pt}
     \textbf{special}        &  $0$&  $0$ & $1$& Log($\frac{3}{1}$) = $0.477$ \\
 \hline\xrowht[()]{10pt}
     \textbf{pet}        &  $0$&  $0$ & $2$& Log($\frac{3}{1}$) = $0.477$ \\
 \hline\xrowht[()]{10pt}
     \textbf{which}        &  $0$&  $0$ & $1$& Log($\frac{3}{1}$) = $0.477$  \\
 \hline\xrowht[()]{10pt}
     \textbf{friendly}        &  $0$&  $0$ & $1$& Log($\frac{3}{1}$) = $0.477$  \\
 \hline
\end{tabular}
}

\end{table}
\end{center}

\begin{center}
    \begin{table}[h]
\centering
    \caption{Term Frequency-Inverse Document Frequency}
    \label{tab:mytable4}
\scalebox{0.8}{

\begin{tabular}{| l| l| l| l| }
 \hline\xrowht[()]{10pt}
     \textbf{Term}        &  \textbf{TF\_IDF$_{d_1}$} & TF\_IDF$_{d_2}$ & TF\_IDF$_{d_3}$ \\
 \hline\xrowht[()]{10pt}

     \textbf{this}        &   $\frac{1}{4}*0.176 = 0.036$ & $\frac{1}{5}*0.176= 0.035$ & $0*0.176=0$ \\
 \hline\xrowht[()]{10pt}

     \textbf{is}        &   $\frac{1}{4}*0 = 0$ & $\frac{1}{5}*0 = 0$ & $\frac{2}{11}*0 = 0$ \\
\hline\xrowht[()]{10pt}

     \textbf{a}        &   $\frac{1}{4}*0 = 0$ & $\frac{1}{5}*0 = 0$ & $\frac{3}{11}*0 = 0$ \\
 \hline\xrowht[()]{10pt}
     \textbf{dog}        & $\frac{1}{4}*0 = 0$ & $\frac{1}{5}*0 = 0$ & $\frac{1}{11}*0 = 0$ \\
 \hline\xrowht[()]{10pt}
     \textbf{not}         &0 * 0.477 = 0& $\frac{1}{5}* 0.477 = 0.095$ & $0* 0.477 = 0$ \\
 \hline\xrowht[()]{10pt}
     \textbf{special}        & $0* 0.477 = 0$ & $0* 0.477 = 0$ & $\frac{1}{11}* 0.477 = 0.043$ \\
 \hline\xrowht[()]{10pt}
     \textbf{pet}       & $0* 0.477 = 0$ & $0* 0.477 = 0$ & $\frac{2}{11}* 0.477 = 0.087$ \\
 \hline\xrowht[()]{10pt}
     \textbf{which}        & $0* 0.477 = 0$ & $0* 0.477 = 0$ & $\frac{1}{11}* 0.477 = 0.043$ \\
 \hline\xrowht[()]{10pt}
     \textbf{friendly}       & $0* 0.477 = 0$ & $0* 0.477 = 0$ & $\frac{1}{11}* 0.477 = 0.043$ \\
 \hline
\end{tabular}
}

\end{table}
\end{center}

\section{SpaML architecture} \label{sec5}

SpaML is a super learner whose architecture is given by Fig \ref{fig:spamlArch}. It is bimodal. That is to say, it can operate in two modes: BoW or TF-IDF, depending on the NLP technique selected by the user. It utilizes seven supervised and unsupervised detectors, namely MNB, LR, SVM, NCC, Xgboost, KNN and Perceptron based on Multinomial Naive Bayes, logistic regression, support sector machine, nearest centroid,  Extreme Gradient Boosting, K-nearest neighbors, and Perceptron algorithms, respectively. It uses the majority of vote strategy to make the final decision founded on the prediction of its base learners. That is to say, if three base learners vote spam (i.e. 1), and four vote ham (i.e. 0), then the result is ham, for instance. Below is a reminder of the basics of our base classifiers and how they work.

\begin{figure}[hbt!]
  \centering

\scalebox{0.75}{
\forestset{
 default preamble={
 font=\Large,

 }
}
\begin{forest}
  for tree={
    draw,
    align=center,
    font=\footnotesize
  },
  forked edges,
  [Overall prediction \\ (Majority of votes), fill=melon
    [ SpaML, fill=moccasin, circle,draw
      [ Prediction, fill=melon
          [MNB , fill=moccasin
          ]
      ]
      [ Prediction , fill=melon
          [LR , fill=moccasin
          ]
      ]
      [ Prediction, fill=melon
          [SVM , fill=moccasin
          ]
      ]
      [ Prediction, fill=melon
          [NCC , fill=moccasin
          ]
      ]
      [ Prediction, fill=melon
          [Xgboost , fill=moccasin
          ]
      ]
      [ Prediction, fill=melon
          [KNN , fill=moccasin
          ]
      ]
      [ Prediction, fill=melon
          [Perceptron , fill=moccasin
          ]
      ]
    ]
  ]
\end{forest}
}
  \caption{SpaML architecture}\label{fig:spamlArch}
\end{figure}

\subsection{Multinomial Naive Bayes }

The Naive Bayes classifier (NBC)\cite{Webb2010459862} is a probabilistic and supervised model based on Bayes' theorem\cite{sep-bayes-theorem}. The theorem assumes that the features are all independent. That is why the algorithm is referred to as naive. To understand how the Naive Bayes classifier derives from Bayes theorem, assume a feature vector $X=(x_1, x_2, \mbox{...}, x_n)$ and a class variable $y_k$ among $K$ classes in the training data. Bayes's theorem implies:

\begin{equation} P(y_k|X)=\frac{P(X|y_k).P(y_k)}{P(X)}, k \in \{1,2,\mbox{...}, K\}  \label{naive_eq1}\end{equation}

Considering the chain rule \cite{wiki:chain_rule} for multiple events:
\begin{equation} P(A_1  \cap A_{2} \cap \mbox{ ... } \cap A_n)= P(A_1 | A_{2} \cap \mbox{...}\cap A_n). P(A_{2} \cap \mbox{...} \cap A_n)  \label{naive_eq2}\end{equation}

The likelihood $P(X|y_k)$ can be written as follows:
\begin{equation}  \label{naive_eq3}
\begin{split}
P(X|y_k) & = P(x_1, x_2, \mbox{ ... }, x_n|y_k) \\
 & = P(x_1|x_2, \mbox{ ... }, x_n|y_k).P(x_2|x_3 \mbox{...}, x_n|y_k) \mbox{...}P(x_n|y_k)
\end{split}
\end{equation}

This is when the independence assumption of Bayes' theorem is useful, implying:

\begin{equation} P(x_i|x_{i+1} \mbox{...} x_n| y_k)=P(x_i|y_k), i \in \{1 \mbox{...} n\}  \label{naive_eq4}\end{equation}

The likelihood can so be reduced to:

\begin{equation}P(X|y_k) = \prod_{i=1}^{n} P(x_i|y_k) \label{naive_eq5}\end{equation}

The posterior probability $P(y_k|X)$ can also be reduced to:
\begin{equation} P(y_k|X)=\frac{P(y_k).\prod_{i=1}^{n} P(x_i|y_k)}{P(X)},  k \in \{1,2, \mbox{...}, K\}  \label{naive_eq6}\end{equation}

Considering that $P(X)$ is a constant  for all $k \in \{1,2,\mbox{...}, K\}$, the Naive Bayes classification problem comes down to maximizing

\begin{equation} P(y_k).\prod_{i=1}^{n} P(x_i|y_k)\label{naive_eq7}\end{equation}

The probability $P(y_k)$ is the relative frequency of the class $y_k$ in the training data. $P(x_i|y_k)$ can be calculated using usual distributions. The classifier is referred to as Multinomial Naive base (MNB) in case of multinomial distribution\cite{wiki:Multinomialdistribution} (in our case for two classes).

\subsection{Logistic regression}

Logistic regression (LR)\cite{LR123789} is a supervised model that uses a transformation called \textit{Logit} that calculates the logarithm of the probability of an event (e.g. a message being spam) divided by the probability of no event. It is defined as follows:
\begin{center}
$\text{Logit}(p) = \text{Log}\displaystyle \frac{p}{1-p}$
\end{center}
where $p = p(y=\text{spam}|X)$ is the conditional probability of the output $y$ being spam knowing the input $X=(x_1, x_2, ..., x_n)$.
Under the assumption of a linear relationship between $\text{logit}(p)$ and the predictors, ( i.e. $\text{Logit}(p)= \beta_0 + \beta_1 x_1 + ... + \beta_n x_n$), we have:

\begin{equation}  \label{log_eq1}
\displaystyle \frac{p}{1-p} =  \displaystyle {e^{\beta_0 + \beta_1 x_1 + ... + \beta_n x_n}}
\end{equation}

\begin{center}  \text{or else}\end{center}

\begin{equation}  \label{log_eq2}
\displaystyle p = \displaystyle \frac{1}{1 + e^{-(\beta_0 + \beta_1 x_1 + ... + \beta_n x_n)}}
\end{equation}

As we can see it, $p$ is the sigmoid function applied to the weighted inputs. If it is close to $1$, then the event is present. If it is close to $0$, then it is not.

\subsection{Support vector machine}

A Support Vector Machine (SVM) is a supervised ML algorithm used for classification, regression, and anomaly detection. It is known for its strong theoretical basis \cite{SVMcortes1995support, SVM1481236}.  Its goal is to separate data into classes using a separation boundary so that the distance between the different classes of data and the boundary is as large as possible. This distance is also called \textit{margin} and the SVM is called \textit{wide-margin separator}. The \textit{support vectors} are generated by the data points closest to the boundary. They play a very important role in the model formation, and if they change, the position of the boundary will very likely change.  In Fig. \ref{fig:SVM1}, in two-dimensional space, the boundary is most likely the red line, the support vectors are most likely determined by the two points on the green line, as well as the two points on the blue line, and the margin is the distance between the boundary and the blue and red lines. Maximizing the margin reinforce noise-resistance and enables the model to be more generalizable.

\begin{figure}[htbp]
\begin{minipage}{8 cm}
\includegraphics[scale=0.55]{svm.png}
\caption{SVM}
\label{fig:SVM1}
\end{minipage}
\end{figure}

\subsection{Nearest Centroid}

The Nearest Centroid Classifier (NCC) belongs to the family of unsupervised ML algorithms. It classifies a data point in the class whose mean is closest to it (centroid is another word for mean). For a binary classification, the number of centroids is two. Initially, centroids are selected either manually, or randomly, or with the help of certain tools such as \textit{k-means++} in SKLearn. Then, each observation is assigned to the cluster whose centroid has the least squared Euclidean distance. Then, the new centroids are updated according to the observations in the modified clusters. The algorithm loops through the last two steps until the assignments no longer change. A point $P$ is assigned the class of the nearst centroid

\subsection{Extreme Gradient Boosting}

Extreme Gradient Boosting   (Xgboost)\cite{XGBoostChenG16} is a supervised algorithm. It is basically a tree ensemble model consisting of a set of classification and regression trees where a score is associated with each leaf of the tree. The algorithm uses an objective function with a regularization term and optimizes it using the second order derivative as an approximation to score gains and make the best split and prune the trees. Xgboost is able to efficiently perform parallel processing which accelerates training, handle missing values, and make non-greedy tree pruning. Dropout and regularization mechanisms of Xgboost are particularly effective to reduce overfitting.

\subsection{K-Nearest Neighbors}

The K-Nearest Neighbors (KNN, K $\in \mathbb{N}$) \cite{knn1053964}  is a very simple supervised classification algorithm. Its purpose is to classify target points of unknown classes according to their distance from the K points of a learning sample whose classes are known in advance. Each  point $P$ of the sample is considered as a vector of $\bm{\mathbb{R}}^n$, described by its coordinates $(p_1,p_2, ..., p_n)$. In order to determine the class of a target point $Q$, each of the K points closest to it takes a vote. The class of $Q$ is then the class with the majority of votes. KNN can use multiple types of distances \cite{DBLP:journals/corr/abs-1812-05944, thesis921292} in a normalized vector space to find the closest points to $Q$, such as the Euclidean distance, the Manhattan distance,  the Minkowski distance,  the Tchebychev distance, and the Canberra distance. The choice of the K parameter plays a crucial role in the accuracy and performance of the model.

\subsection{Perceptron}

Perceptron \cite{perceptron80230} is a supervised ML algorithm mainly used for binary classification. It uses a binary function that can decide whether an input, represented by a vector of numbers, belongs to a certain class or not. For an input vector $x=(x_1,...,x_n)$, $f$ is defined as follows:
$$
f(x) = \left\{
    \begin{array}{ll}
        1 & \mbox{if } w.x + b > 0\\
        o & \mbox{if not.}
    \end{array}
\right.
$$

where $w$ is weight vector of size $n$, "." is the dot product operator, and $b$ is a bias. The algorithm starts by initializing the weights and the threshold $\gamma$. At time $t$, for a sample $j$ (i.e. $x^j$ and output $y^j$) of the training dataset $D$ of cardinality $s$, perform the two following steps:

\begin{enumerate}
\item compute the predicted candidate: $\hat{y}^j(t)= f(w(t) . x^j + b)$
\item update $w$:  $w_i(t+1) = w(t) + \rho . (y^j(t) - \hat{y}^j(t)) x^j_i$, for all features $i\in \{1,...,n\}$; $\rho$ is the learning rate.
\end{enumerate}

These two steps are repeated until the mean squared error $\frac{1}{s}\sum_{j=1}^{s} (y^j(t) - \hat{y}^j(t))^2$ becomes inferior to the threshold $\gamma$, or a predefined looping limit number is reached.

\section{Experiments and results} \label{sec6}

\subsection{Dataset}

We use the SMS dataset \cite{datset2034742} in our experiments. It consists of 5574 instances. 747 instances are spam messages, and 4827 are ham messages. To train our models, we randomly split the dataset into two parts: a training dataset and a test dataset. The first one contains 75\% of the original dataset items and the second one contains 25\% of them. Since the SMS dataset is imbalanced, we use  the \textit{stratify} strategy so that the selected records into the two resulting datasets keep the same distribution as the original one.

\subsection{Preprocessing}

Before converting texts into vectors of numbers we proceed to preprocessing it. First, we lowercase all texts. Then, we get rid of stop words, which are useless data such as \textit{the, a, an, in, for, because, that, over, more, him, each, who, these, into, below, are, by, etc}. Then, we perform a text stemming which is the process of reducing inflection in words to their root forms. For example, the words \textit{detection, detected, detecting, detector} are reduced to their stemming root word  \textit{detect}.

\subsection{Results}

To evaluate our classifiers, we use the two following scoring metrics:

\begin{center}
\text{Accuracy} $= \displaystyle \frac{\text{TP+TN}}{\text{TP + TN + FP + FN}}$
\end{center}

and,

\begin{center}
\text{Precision} $=\displaystyle \frac{\text{TP}}{\text{TP + FP}}$
\end{center}

where \text{TP} represents the true positives, \text{TN} the true negatives,  \text{FP} the false negatives, and \text{FP} the false positives.

Accuracy is the fraction of labels that the model has managed to predict correctly. Precision is a good metric when false positives count. In spam detection, a false positive means that a message which is not actually spam has been identified as spam. In such a case, the user may lose important messages if the precision of the detection model is not high.

 Table \ref{tab:mytable5} summarizes the performance of the base detectors, as well as the overall detector, in both modes BoW and TF-IDF.

 \begin{table}[h]
\centering
    \caption{Classifier performance}
    \label{tab:mytable5}
\scalebox{0.8}{
\begin{tabular}{| l| c| c|c|c|}
 \hline\xrowht[()]{10pt}
  \multirow{2}{*}{\textbf{Classifier}} & \multicolumn{2}{|c|}{\textbf{BoW Mode}}  &  \multicolumn{2}{c|}{\textbf{\textbf{TF-IDF Mode}}} \\  \cline{2-5}\xrowht[()]{12pt}
                                                                    &\textbf{Accuracy (\%)} & \textbf{Precision} (\%)& \textbf{Accuracy (\%)} & \textbf{Precision} (\%)\\  \hline\xrowht[()]{10pt}
\textbf{MNB} & 96.04&96.16                                      & 96.08 &96.24\\  \hline\xrowht[()]{10pt}
\textbf{LR}            & 96.87&96.79                                      & 94.90 &96.89\\  \hline\xrowht[()]{10pt}
\textbf{SVM}                                        & 96.74&96.33                                      & 96.46 &96.45\\  \hline\xrowht[()]{10pt}
\textbf{NCC}               & 96.10&95.90                                      & 95.98 &95.56\\  \hline\xrowht[()]{10pt}
\textbf{Xgboost}                                & 96.65&96.24                                      & 96.13 &96.26\\  \hline\xrowht[()]{10pt}
\textbf{KNN}                                       & 90.93&95.27                                      & 89.76 &94.83\\  \hline\xrowht[()]{10pt}
\textbf{Perceptron}                          & 96.97&95.07                                      & 96.58 &94.94\\  \hline\xrowht[()]{10pt}

\textbf{SpaML}                                   & \textbf{98.11}&\textbf{98.91}    & \textbf{97.99} &\textbf{98.87}\\
\hline
\end{tabular}
}
 \end{table}

 Fig \ref{fig7} compares the accuracy of the models by mode and Fig \ref{fig8} compares the precision of the models by mode, as well.
\begin{figure}[htbp]
\centering
\begin{minipage}{7.5cm}
\includegraphics[width=7.5cm,height=4.5cm]{accJF.png}
\caption{Accuracy comparison (by Mode)}
\label{fig7}
\end{minipage}
\end{figure}

\begin{figure}[htbp]
\centering
\begin{minipage}{7.5cm}
\includegraphics[width=7.5cm,height=4.5cm]{precJF.png}
\caption{Precision comparison (by Mode)}
\label{fig8}
\end{minipage}
\end{figure}

Fig \ref{fig9} shows the confusion matrix of SpaML in BoW mode on a sample of unseen data of 1393 records with 1206 ham messages and 187 spam messages. Fig \ref{fig10} shows the confusion matrix of SpaML in mode TF-IDF for the same records. It is worth mentioning that we have used a 10-fold cross-validation procedure to evaluate SpaML, as well as its base detectors, to make sure that they do not overfit data.

\begin{figure}[htbp]
\centering
\begin{minipage}{7cm}
\includegraphics[width=7cm,height=3cm]{CMBoW.png}
\caption{SpaML confusion matrix (BoW mode)}
\label{fig9}
\end{minipage}
\end{figure}

\begin{figure}[htbp]
\centering
\begin{minipage}{7cm}
\includegraphics[width=7cm,height=3cm]{CMTFIDF.png}
\caption{SpaML confusion matrix (TF-IDF mode)}
\label{fig10}
\end{minipage}
\end{figure}

\section{Discussion and comparison with related work} \label{sec7}

In summary, in BoW mode, SpaML has displayed an accuracy of 98.11\% and a precision of 98.91\%. In TF-IDF mode, it has displayed an accuracy of 97.99\% and a precision of 98.87\%. This shows that SpaML copes very well with both modes. This being said, the difference between the two modes, although not very significant, gives a slight advantage to the BoW technique on the used dataset. Nevertheless, such a result cannot be generalized prior to evaluating SpaML on other datasets.  Other approaches like spam filtering based on adaptive statistical data compression models\cite{BratkoCFLZ06} using character-level or binary sequences have been proposed. They usually use dynamic Markov compression\cite{ItakuraC09} and partial matching\cite{NetoBC18} to evaluate the model. Rule-based filtering systems\cite{Xia20} using behavioral methods or linguistic methods have also been proposed to score and classify texts. Deep Learning\cite{DBLPMakkarK20, DBLPRoySB20, SaidaniAA19} is also beginning to be used to detect spam and algorithms such as CNN\cite{DBLPLiuL20g} and LSTM\cite{DBLPEryilmazSK20} are gaining ground. Hidden Markov Models \cite{DBLPGordilloC07, Dang7578397} have also been considered to address this problem. All these approaches and techniques give relatively good results. In our vision, these comparable  methods are not antagonistic or in competition with each other, on the contrary, they can be used in a collaborative context.

\section{Conclusion} \label{sec8}

In this paper, we have proposed a spam detector using two NLP-based techniques for text vectorization and a set of different classifiers, supervised and unsupervised. The super learner on top of these base learners, SpaML, has shown very interesting results in terms of precision and accuracy with the two techniques. This motivates us to explore other NLP techniques, as well as similar ones, to tackle this difficult problem of spam detection and extend it to other problems close to it,  such as tracking terrorism-related exchanges and targeting organized crime in social networks.

\section*{Acknowledgment}

This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC).

redpajama_set_name: RedPajamaArXiv


The page on a web site where one is taken after clicking on an advertisement. While this can be any page, it is often a page designed to expand on the service or product mentioned in the initial advertisement.
First impressions on landing pages are as important as the offline world. Make sure the headline is a direct and simple statement of what the user is trying to accomplish.
I've seen some landing pages get too tricky and try to wow their visitors. Often this frustrates visitors because they've lost control of their own computers. They may well get that control back by simply closing their browsers – and you are a goner.
While direct messages can be very effective in the body of the copy direct messages in the call to action can be a turnoff. Words like "Buy," "Add to Cart" or "Subscribe" that message commitment and a process can lower conversion rates. Softer calls to action like "Try it Now" that message immediacy (Now), but in a risk free way (Try it) can end up improving conversion by getting more users into the funnel.
What do you more concern about?


text:
using System.Collections.Generic;
using System.Linq;
using MiniCraft.Crafts;
using MiniCraft.Entities;
using MiniCraft.Gfx;
using MiniCraft.Items;
using MiniCraft.Sounds;

namespace MiniCraft.Screens
{
    public class CraftingMenu : Menu
    {
        //private class RecipeSorter : IComparer<Recipe>
        //{
        //    public int Compare(Recipe r1, Recipe r2)
        //    {
        //        if (r1.canCraft && !r2.canCraft) return -1;
        //        if (!r1.canCraft && r2.canCraft) return 1;
        //        return r1.resultTemplate.getName().CompareTo(r2.resultTemplate.getName());
        //    }
        //}

        private Player player;
        private int selected = 0;

        private List<Recipe> recipes;

        public CraftingMenu(List<Recipe> recipes, Player player)
        {
            this.player = player;

            for (int i = 0; i < recipes.size(); i++)
            {
                recipes.get(i).checkCanCraft(player);
            }

            this.recipes = new List<Recipe>(recipes.OrderByDescending(x=>x.canCraft));
            //this.recipes.Sort(new RecipeSorter());
        }

        public override void tick()
        {
            if (input.menu.clicked) game.setMenu(null);

            if (input.up.clicked) selected--;
            if (input.down.clicked) selected++;

            int len = recipes.size();
            if (len == 0) selected = 0;
            if (selected < 0) selected += len;
            if (selected >= len) selected -= len;

            if (input.attack.clicked && len > 0)
            {
                Recipe r = recipes.get(selected);
                r.checkCanCraft(player);
                if (r.canCraft)
                {
                    r.deductCost(player);
                    r.craft(player);
                    Sound.craft.play();
                }
                for (int i = 0; i < recipes.size(); i++)
                {
                    recipes.get(i).checkCanCraft(player);
                }
            }
        }

        public override void render(Screen screen)
        {
            Font.renderFrame(screen, "Have", 12, 1, 19, 3);
            Font.renderFrame(screen, "Cost", 12, 4, 19, 11);
            Font.renderFrame(screen, "Crafting", 0, 1, 11, 11);
            renderItemList(screen, 0, 1, 11, 11, recipes, selected);

            if (recipes.size() > 0)
            {
                Recipe recipe = recipes.get(selected);
                int hasResultItems = player.inventory.count(recipe.resultTemplate);
                int xo = 13 * 8;
                screen.render(xo, 2 * 8, recipe.resultTemplate.getSprite(), recipe.resultTemplate.getColor(), 0);
                Font.draw("" + hasResultItems, screen, xo + 8, 2 * 8, ColorHelper.get(-1, 555, 555, 555));

                List<Item> costs = recipe.costs;
                for (int i = 0; i < costs.size(); i++)
                {
                    Item item = costs.get(i);
                    int yo = (5 + i) * 8;
                    screen.render(xo, yo, item.getSprite(), item.getColor(), 0);
                    int requiredAmt = 1;
                    if (item is ResourceItem)
                    {
                        requiredAmt = ((ResourceItem)item).count;
                    }
                    int has = player.inventory.count(item);
                    int color = ColorHelper.get(-1, 555, 555, 555);
                    if (has < requiredAmt)
                    {
                        color = ColorHelper.get(-1, 222, 222, 222);
                    }
                    if (has > 99) has = 99;
                    Font.draw("" + requiredAmt + "/" + has, screen, xo + 8, yo, color);
                }
            }
            // renderItemList(screen, 12, 4, 19, 11, recipes.get(selected).costs, -1);
        }
    }
}

redpajama_set_name: RedPajamaGithub


text:
Home 10 Questions with Vic 10 Questions with Vic: Featuring Shirley Manson
10 Questions with Vic: Featuring Shirley Manson
Vic Gerami
Shirley Manson epitomizes both the qualities of an alternative rock icon and a contemporary rebel, always edgy and timeless. With over twenty-five years in the music industry as the lead singer of the band Garbage, a lyricist and a musician, Shirley has had exceptional successes, including double platinum albums with hits such as "Only Happy When It Rains," "Stupid Girl," "Vow," and "Push it." But superstardom has not made her out-of-touch or complacent, as she is very vocal about social and cultural issues, always championing for the rights of the underdog, including female empowerment. I had the pleasure of interviewing Shirley while she was in LA from her native Scotland.
Modesty aside, how would you describe yourself?
Scottish, red-head. No further explanation necessary.
You received the Icon Award at the VO5 NME Awards last year. How do you reflect on your illustrious career, spanning over twenty-five years?
I can't believe this is my life! It feels like it should have happened to someone else except it happened to ME.
You have been ahead of the curb in more ways than one, about sexual orientation and gender roles with your song, 'Androgny', which is about owning one's age, sexual liberation, LGBTQ rights and more… Does it feel like we are fighting the same battles all over again? Do you see any improvements?
I believe wholeheartedly in evolution. I think there are always some set backs to and push back against progress but progress always wins in the end. I just wish progress would happen faster. So many good people are still forced to suffer so.
Shirley Manson – photo Credit: Joseph Cultice
Fans are anticipating your 7th album sometime this year or early 2020. Can you share any news on that?
Our 7th album is scheduled for 2020. We are spending the duration of 2019 working on getting it done!
'This Is The Noise That Keeps Me Awake', a biographical book on Garbage came out in 2017. How did the idea for the book come about?
We wanted to put a book together for all the kids in our lives so that when we are all dead and gone, they will know what it was we did with our lives! LOL.
Edinburgh, Scotland, where you were born, is such a magical and fantastical place that most of us dream of living. How is it living in Los Angeles and do you miss living in Scotland sometimes?
I love Los Angeles dearly, but yes I miss Scotland. I miss the damp and cool climate. I feel overheated in Los Angeles all the time.
Tell me about your fans when they recognize you in public?
What is shared between us and our fans is sacred. I always feel honored when they are happy to see us.
What's new on your play list?
Sharon Van Etten, Cherry Glazerr, Kelsey Lu, Leikeli47.
What is your favorite charity or cause?
The World Wildlife Fund, Amnesty International, The Trevor Project, Move On.
Tell me a secret-a good one!
I never spill my secrets.
For more information on Shirley Manson and the next Garbage tour, please visit www.garbage.com
Previous articlePower Outages Leave WeHo Areas in the Dark this Evening
Next articleLA LGBT Center Responds to Recent Developments in Jussie Smollett Investigation
Vic Gerami is journalist, media contributor and the Editor & Publisher of The Blunt Post. He spent six years at Frontiers Magazine, followed by LA Weekly and Voice Media Group. His syndicated celebrity Q&A column, 10 Questions with Vic, was a finalist for LA Press Club's National Arts & Entertainment Journalism Award in 2017. Vic is a contributor for WeHo Times, Get Out!, Los Angeles Blade, GoWeHo, Asbarez, California Courier, Desert Daily Guide, Armenian Weekly, GED, The Pride LA and The Advocate.
See ya in TJ
Can I just say HOW much I love Shirley! Have for, well, 25 years! She is so painfully cool! I follow her on a couple of social media platforms and she is very versed in politics and isn't about to let anyone push her around. I find her to be well versed, knowledgeable and able to speak cohesively on the matters that she tackles. We need to continue to celebrate women with power for standing up for what's right and just!


text:
Editorial - RT62
Artists reflect on their education
The articles on training in dance, sound art, theatre, film (animation), performance and new media art in our education feature are based on interviews with artists who graduated in the last 3 to 7 years. Already some of the courses they completed have changed substantially, others not. However, discrete new media art and especially sound art courses had barely begun in this period. It's not surprising then to find that the articles about sound art and new media art are largely about visual art school experiences.
That a considerable number of new media and sound artists have emerged from art schools says something about the way in the 1990s those schools were responding to and even initiating changes in the art world around them. For that reason, these articles should be read in conjunction with the spirited appraisal by Su Baker (Head, School of Art, Victorian College of the Arts) of students and their relationships with art schools. Given the assumptions of some critics that students are being duped and that Australian art is therefore in a sorry state, it's heartening to read former students reflecting on the many advantages, challenges and occasional conflicts in their training. Access to equipment, the importance of theory and multidisciplinary skilling, the significance of mentoring (formal or informal) and the introductions to invaluable networks all rate highly in their assessment of their education.
What is also regarded highly is a certain flexibility, the need sometimes for the student artist to change direction and for courses to be responsive. A number of the interviewed artists found their professional careers by circuitous means or sudden shifts of interest. Some worry that in the age of the pragmatic approach "targeting and attempting to second guess 'industry' may perhaps backfire, producing a glut of artists doing what is already being done, instead of producing artists who can provide new ideas and ways of thinking" (p34).
There is a difference between training students in terms of industry and the university entering a relationship with industry. In her article on music education, Helen Lancaster, while appreciating the career opportunities that are expanding beyond performance and composition for graduates, writes that "there is still little evidence of effective collaboration between institutions and industries. Few universities take seriously their potential to assist graduate placement." She also reports that, unlike their UK counterparts "Australian institutions are not required to maintain a long-term professional profile of their graduates—and they don't." What she does applaud in a number of courses is "the trend toward collaborative practice offer[ing] access to a wider range of opportunities, encouraging students to become responsible for their own learning, a positive quality for musicians who must build their own careers." It is that sense of independence which is most often felt when the artists in this edition reflect on the impact of their education. One factor that might have a negative impact in this respect is the problem growing around teacher-student ratios.
The arts, ecologically
My thanks to those of you who responded to my article on the problematic relationship between the ABC and the arts community and, more particularly, on developing a new way of thinking about the arts, one not predicated on the prevailing business model. There'll be more about this in RealTime 63 with a report on the forthcoming seminar "Culture and creativity in Australia: the role of arts and cultural organisations in innovation in the arts." This is to be held on August 27 at the University of Technology Sydney and is organised by UTS (Writing Centre and Transforming Cultures Centre) and Currency House.
Innovation and the arts
RealTime 63 will focus on innovation in new media arts and hybrid performance. The term 'innovation' is increasingly deployed as a claim for significance, it's a common criterion for arts funding and part of the justification for the arts-science-industry nexus. What does innovation mean, when does it happen, in what kind of work and who are the innovators?
RealTime-BEAP
A RealTime writing team will be responding to the exhibitions and conferences in the 2004 Biennial of Electronic Arts Perth, September 7-12. Log on to our website for daily coverage of the event. KG


text:
Acronimi
LICA – Lega internazionale contro il razzismo e l'antisemitismo
LICA – codice ICAO dell'aeroporto di Lamezia Terme

Persone
Licá – calciatore portoghese
Laurențiu Lică – pallavolista rumeno
Marcel Lică – arbitro di calcio rumeno

Altro
Lica – personaggio mitologico
Lica – personaggio dell'Eneide di Virgilio
Lica – nome proprio di persona femminile

redpajama_set_name: RedPajamaWikipedia


To create a link from one Org file to another, you would use something like '[[file:foo.org][The foo]]' or simply '[[file:foo.org]]' (see External Links). When published, this link becomes a link to 'foo.html'. You can thus interlink the pages of your "Org web" project and the links will work as expected when you publish them to HTML. If you also publish the Org source file and want to link to it, use an 'http' link instead of a 'file:' link, because 'file' links are converted to link to the corresponding '.html' file.
You may also link to related files, such as images. Provided you are careful with relative file names, and provided you have also configured Org to upload the related files, these links will work too. See Complex example, for an example of this usage.
Eventually, links between published documents can contain some search options (see Search Options), which will be resolved to the appropriate location in the linked file. For example, once published to HTML, the following links all point to a dedicated anchor in 'foo.html'.