Good morning everyone. Jason Hinders, my name. I'm the Chairman of Milonglo Financial Services which is the Bendigo Community Bank organisation here in in Canberra and Jerobombra. I just want to give you a short history of the Bendigo Bank for those that don't know much about it and then to talk about the Bendigo Community Banks which is a more recent development and then about our local company here and then some sort of points about how we might be able to contribute to affordable housing and innovative ideas and then a few examples of things we've been involved in that are relevant or in the ballpark. So the Bendigo Bank is the fifth largest bank in the country. It was established in 1858 so now it's 156 years old. There's 450 branches of Bendigo Bank across the country. 300 of those are community owned bank franchises. So Bendigo is a real bank. It's not a building society. It's got all of the services that big banks have. We have to explain this all the time because it's called Bendigo Bank and people think of a little country town but it's actually a proper bank and it does all of those things. In the last seven years up to the year 2029% of Australia's bank branches closed for good. And those are mostly in communities in country towns when the last of the big four left the town without any banking services. So people had to travel to the nearest big town to do their banking and so then these small towns started to decline. Bendigo Bank saw this an opportunity to make banking viable again in these towns. Bendigo Bank was already rural based at that stage but only 150 odd branches across the eastern states and the south eastern states at that. They came up with a new model which I think is still unique worldwide. It's a partnership that gives the community the opportunity to raise the money to open their own community bank. They're run locally, they're owned locally and they're staffed by local people. So the first one of these opened in 1988 on not much more than a handshake. Since then 302 more communities have taken back control of their banking needs and then use the banking profits to fund all number of valuable community assets, groups, charities, associations. This is the aspect that becomes interesting to discussion about the NDIS. Over the 16 years since community bank network has evolved, we've become a bit more commercial in our expectations about communities. We no longer give money away, we invest it. It belongs, this money in our view belongs to our communities and it's a precious resource and we expect the groups that we invest it with to use it to return what we call a social dividend to the community. There's been over 120 million, I think it's $122 million, $3 million has gone back into communities across Australia. The reality is that whilst sausage is available every six months or so, raises a couple of hundred dollars for charitable organisations. To have an income stream and an expectation of ongoing return means that those communities are able to budget for long-term commitments. The community banks across the country have 26 billion dollars under management at this stage and the substantial income produced from that community bank network is beginning to think big. This again becomes relevant when trying to find new ways of funding expensive items like housing. Canberra is no different except that in long-term financial services, our organisation, we now operate four community bank branches and we're the largest community bank group in the ACT in New South Wales. Community banks such as ours are run by volunteer boards. They're community-minded people from all walks of life. I'm a lawyer, we've got directors who are serving Air Force officers and university students and all descriptions in between. The one common thing we have is an objective to get these community banks up to profit and then to return 80 percent of those profits to charities and community groups. Our first branch opened in 2002 in Corwell followed later that year in Waniasa and more recently Jerobomba in 11 and Curtin in 2012. In the process we put back $1.2 million into our local community here through what we think is about 260 local groups and charities right here in Canberra and Queenbyn. I've got a few examples of things that we have supported. Some of you might be aware of home in Queenbyn and the story there. It's an independent living and they always emphasise it's dignified living because it's not just living for people with mental health challenges. That model also is unique, I understand, in that it endeavours to do what they do, providing high quality service and facilities without ongoing government dependence. Instead they rely on community organisations and corporates to retain their independence. To this end our local community bank has committed $50,000 over five years to that very worthwhile organisation. National Health Co-op is one we supported last year, the tune of $100,000. We used profits from the banking business we do. We then leveraged with the National Health Co-op. I think it's our fault they had to change their name from West Bercon and Health Co-op because we agreed with them it was going to be in the Togrenong Valley. So we provide, so this organisation banded with us and then we went to government and we spoke to them and we leveraged $400,000 clinic in Chisholm which provides bulk build GP services, ACT government and gives them a facility where they can provide primary health care services to people that are Togrenong Valley. Oz Harvest you all might know has changed its name to the Yellow Van these days. We provided their second van to that organisation which is part of communities at work at a cost of nearly $50,000 and Lash is a small organisation which runs a couple of houses in Curtin for mostly adult disabled children of elderly parents. It comes home to us about the concern that those older parents who are finding it difficult to deal with when they've been the primary care for a long time the angst and worry that they have to deal with trying to work out what's going to happen when they're gone. So that was a history lesson I hope it wasn't too tedious for you. From now on I'll try and get a little more interesting. The fact is that Community Bank makes its decisions right here in Canberra. It's not some glass tower in Sydney or Melbourne where shareholding decisions are made we make them right here and we decide where that money's going to go. We have 600 approximately local shareholders who are not day traders they're in this because they understand what the Community Bank means to the community. They're more interested in that social dividend I spoke of earlier and that it's delivered to benefit the whole of the community not just them. They were in the whole pretty happy I understand with the five or seven cents fully frank we've been distributing in the past as a dividend. I know that stark contrast with the obscenity of the eight billion dollars profit the CBA is reported to be about to be announcing. The local community banks has the ability to partner with organizations to leverage territory and federal governments to deliver significant long-term benefits to this community. Moreover we have the ability to commit to long-term funding at our discretion and as I said those decisions are made right here. Now this is where the Bendigo Bank and affordable housing are somewhat of a perfect match. We're already in the business of lending money for housing if we increase the amount of money we lend we increase the amount of money we make to put back into things like housing. We're unapologetically parochial we're inward looking we're all about our community.  Under the NDIS it's like a disability care participants will continue to access housing either on their own jointly or in group settings in either the private rental market or via home ownership or through social housing. As a locally operated bank Bendigo is sort of uniquely positioned we think to engage directly with investors with the disability sector providers and with government to deliver increased stock of each type through either subsidies or reduced interest rates for investors who are prepared to commit to long-term specialist housing stock or perhaps capital contributions to construction costs or if appropriate modification of existing rental stocks. Another innovation and I think unique asset that we have available to us through the Bendigo Community Bank Network is something called community sector banking. Community sector banking is a niche financial organisation with products and services tailored specifically for the not-for-profit market. They're also the biggest funder I understand of not-for-profit and affordable housing in New South Wales if not Australia. They're 50% owned by the big bank Bendigo and Adelaide Bank and 50% owned by a group of 20 community sector partners. So that's 50% Bendigo and 50% 20 separate partners some of whom you've heard about already today. I notice the Brotherhood of St Lawrence is there they also include involved with the SVA, Anglicare, Scape, Oxfam, Wife Foundations, ACOSP, New South Wales Council, the Social Services so organisations that are all in the same sector. The same sector as we all work in. Whilst the local organisations banking relationships remain with the community bank and that's the retail aspect of this community sector banking they're able to provide services to not-for-profits that the community bank simply can't do things like payroll services, telecom, rental, leasing, IT hosting, equipment leasing, fleet leasing all those things. So it's very specialised around that not-for-profit. They've invested over 150 million in social and affordable housing equating to about 230 much needed dwellings. There are also the recipients some of you may be aware of Power Housing Australia. They're the recipient of the first ever strategic partnership award from Power Housing Australia. It was in recognition of their contribution to affordable housing within Australia. The first time a strategic partner award has been presented to any organisation and the first one bestowed outside of Power Housing Australia's membership group. Community sector banking commitment to societal change and connection with the community housing sector and understanding the issues confronting community housing organisations is the reasons given by PHA for awarding this. Some recent innovative affordable housing projects by community sector banking include building a shared equity model for transition to home ownership and also collaborating with PHA to create a rateable housing bond. Probably something not dissimilar to what Mark was talking about earlier. CSB is currently developing an affordable housing investment bond product which I think is going to be aimed at self-managed super funds international and institutional investors who have committed to ethical investment policies. So that's the sort of thing that we can do we think or the the area that we can get involved in. I've also got some ideas about what what government might do and I don't know whether up for suggestions or not but this year's ACT budget I think has 12 million dollars allocated for the implementation or the catalysation of the NDIS. There's probably more that government could be doing. I know government loves to see corporate dollars going towards community asset creation and PPPs are a flavour of the month. If we were to be involved we would use our proposed funding much the same way we did with the health co-op to leverage government to allocate more of its own funding to the sector and also to commit to things like reduced fees and charges for investors, stamp duties, concessions is a big one there, reduced land tax perhaps rates as incentives for investors, reductions in planning charges, the red tape, application fees for the builders who commit to building purpose-built disability housing, perhaps reserving land release, also possibly with reduced pricing for developers and or investors who are prepared to opt in to long-term disability housing market. Another thought would be giving all of the ratepayers in the territory and the option of choosing to subsidise disability housing and why not have ACTU AGUL do the same in relation to utilities, electricity, gas and water through a few-cent rate power opt-in option much like the airlines do with carbon neutral options for flyers and the power companies with the green power options that you get.  Incentives can be reduced or increased to encourage the pipeline stock and I think this is the job of government to be realistic and educated about what's needed and how long it's going to take to bring to the market. The incentives can be up to or downed to increase particular types of housing so that the pipeline is delivering when they think it's going to be needed. While there's real concerns about the extent to which the federal government's committed or guarantee the long-term viability of the scheme and indeed any program supporting disability or social welfare and I note the Abbott government's recent decision to withdraw funding of round five of the National Rental Affordability Scheme. To me innovation is just thinking differently about solutions to the challenges that face us. In the new landscape disability service providers will need to partner with financial institutions and with the construction industry to provide the types of housing products that the newly empowered NDIS consumer wants. I'll just leave you with one final thought. I hope I haven't gone too far over. Mark talked about the 1% of available funds and and how his organisation earns for just that little bit. I've got a similar sort of example but mine's a little closer to home. In the territory's 14-15 budget here in the ACT the government's allocated 465 million for housing and 735 million for infrastructure. Now by my calculations and what we make that's a fairly small fraction of the whole budget. If we if the government were to invest half of that say into the Bendigo Community Bank the only locally owned and operated bank in addition to the interest the territory would naturally get received for its investment we would be happy to commit to at least a million dollars to deliver quality affordable housing. That'd be a million dollars every year. So delivery of affordable, appropriate and timely housing under the scheme means ensuring the experts in all the relevant fields must be in the room when the decisions are made and I think most of those people I'm talking about are in this room now. We certainly would like to be part of that and we're excited by the hard fought and won prospect of empowering people with disabilities. Thank you.


The best tasting, healthy chicken you ever had. We're gonna make three slices. The first one, you wanna cut really thin on the bottom. So here on the bottom, you have your thin piece. Now you have your thick piece.  Now you need spicy danos. Sprinkle that on the inside of your chicken. Some fresh basil. You need a roma tomato. Some thin slices. Now you need a big handful of mozzarella cheese. And roll right over just like that. And lay it in our baking dish. Now you need a little bit of olive oil. Spicy danos. And to top it off and give us a little crust, you need the danos cheesene. That's the cream top. Now we go into our oven at 400 degrees. Been about 45 minutes, the chicken's done. Now we just simply slice it. This is some apple ball somic. That is super delicious. Yum, yum, get you some. Give it a try. Let me know what you think. We'll see you next time. Keep sprinkling.


in an application so we say x percent of f's are g a is f therefore a is probably g and that's why i said that we're going to study up to generalizations and then down from generalizations in this part of the course and when they work together we can use information about the sample to reach a conclusion about the individual which is pretty useful notice also that these applications of generalizations are inductive they share all the features of inductive arguments first of all they're invalid because it's possible for the premises to be true and the conclusion false that is it's possible that x percent of f are g a is an f but it's not true that a is probably g there might be no chance at all that a is g second applications of generalizations are defeasible you can add additional information to the premises that make the argument very weak they might completely undermine the argument for example even if you know that walters a professor and most professors wear shoes while they're teaching a little bit of additional information might show you that it's just not true that walter is wearing shoes while he's teaching by the way i'm gonna well you'll have to decide for yourself whether i'm really putting my shoes back on now but the third feature of inductive arguments is that they're strong or they can be strong they can vary in strength so even if i don't have shoes on it still might be a fairly strong argument that almost all professors wear shoes while they're teaching walters a professor and he's teaching therefore he probably has shoes on that can be strong before you get that additional information before you see my feet without shoes on and now that you don't know whether i've got shoes on it can still be a strong argument so we have arguments that are not valid and they're defeasible and they vary in strength and that makes them inductive arguments so how do we tell when an application of a generalization really is strong that is when does it provide strong reasons for the conclusion now the first standard should be obvious it's the same for generalizations from samples the premises have to be true and justified if it's not true that i'm a professor or if it's not true that i'm teaching or if you have no reason to believe you're not justified in believing that i'm a professor or i'm teaching then the argument that we've been looking at can't give you a good reason to believe that i'm wearing shoes because i just don't fall into the classes that we're talking about secondly a standard that's specific to these kinds of arguments is that the strength of the argument varies with how big x is if x is 99 percent so 99 percent of f's are g's and a is an f that's a pretty strong argument that this a is a g but if it's 60 percent then it's not a very strong argument so 99 is going to be stronger than 90 which is stronger than 80 which is stronger than 70 which is stronger than 60 and the strength of the inductive argument can vary as the percentage x varies now notice if x is 10 percent then it becomes a pretty strong argument for the opposite conclusion if only 10 percent of professors wear shoes when they're teaching and i'm a professor who's teaching then it's pretty likely i'm not wearing shoes and that's stronger than if it's 20 and 30 and 40 and when you get close to the middle to 50 percent if 50 percent of professors wear shoes when they're teaching and i'm a professor then you can't really reach your conclusion one way or the other about whether i'm wearing shoes at least not on the basis of that evidence not on the basis of that argument okay so a second standard for assessing applications of generalizations is to figure out what the percentage is but another crucial feature of applications of generalizations is that there can be conflicting reference classes so it might be true that 95 percent of professors wear shoes when they're teaching but i'm not just any old professor i'm an online professor this course is online and that's very different because most professors wear shoes when they teach because the students will see their bare feet but you can't see my bare feet so maybe it turns out that a lot of online professors are really not wearing shoes when they teach so that's a conflicting reference class it's a different reference class that conflicts because it points to a different conclusion than the original reference class the original reference class was professors who are teaching the conflicting reference class is online professors who are teaching or professors who are teaching online when you're running the conflicting reference classes as a general rule what you ought to do is look at the smallest of those reference classes because that's usually going to give you a better estimate of how likely it is that this individual has the general attribute that is how likely it is that a is g so if you want to know whether walter is wearing shoes you shouldn't look at the broad class of all professors but should instead look at the narrow class of online professors if the course that he's teaching right now is an online course but there's a problem that you might run into also as you get a narrower narrower reference class you sometimes just don't have enough data to figure out what the exact percentage is how do you know what the percentage of professors who are teaching online is that are wearing shoes how many of them are wearing shoes i've never seen a survey i've seen lots of professors give regular lectures but you rarely see the feet of online professors so you might not have enough information to apply that generalization so while the narrower reference class of two reference classes that conflict can be more accurate it can also be problematic if you don't have enough information to support the premise that says that a certain percentage of that class that f have the general attribute g the fallacy of overlooking conflicting reference classes can be a little confusing but it's very important so let's look at another example and this time let's focus on a medical example let's suppose that 90 percent of the people with a certain condition certain medical condition a certain illness die and bob has that illness so looks very likely that bob will die and this is an application of the generalization about people with this illness but now suppose we find out that most people catch this illness when they're old but bob is quite young so it turns out that young people with this illness usually survive matter of fact only about 20 of the people with this illness who get it when they're young die from the illness if bob is young and has this illness so now we can reach the conclusion you probably won't die from the illness but wait a minute we now have another conflicting reference class because bob has a heart condition and it turns out that even young people when they catch this illness if they have a heart condition they usually die as a matter of fact 80 percent of the people with this illness who have a heart condition and are young die from this illness so bob who is young and has this illness and also has a heart condition will probably die from this illness but wait a minute it turns out that there's a new treatment and of the people who are given this treatment only about 30 of them die even if they're young with this illness with a heart condition and bob lives in an area where he can get the treatment so now it looks like there's only a 30 chance that bob will die from this illness so what's happening here is is we get more and more information the likelihood of bob dying from this illness starts out really high and then it goes low and then it goes high again and then it goes low again and it goes back and forth as we get more information and then the question arises which of these different generalizations should we use to figure out how likely it is that bob will die from the illness the answer here as with most cases of conflicting reference classes is that we ought to look at the narrowest class that we can because if we know there's a treatment and bob is young and he has a heart condition and he also has this illness and we put all that together and compare him to other people who are young with this illness and a heart condition who can get the treatment and look at how many of them have died in order to form an estimate of how likely it is that bob will die from this illness so we always want to look at the narrowest reference class that we can in order to get the best estimate of the probability in the conclusion but then there's a problem there might not be very many people remember it's a new treatment so they're not very many people who are young who have this illness to begin with remember most of the people with the illness are old and the treatment's new so it hasn't been tried on very many young people and of course young people don't often have heart conditions so it might be very difficult to find enough people who are like bob in all the essential respects in order to determine whether or not bob will probably die from this illness so there's a kind of attention here more information gives us more accuracy but only if we have enough information to be justified in trusting the premises of the application that we're looking at and that's one of the tricks in figuring out how to estimate whether or not bob is likely to die from the illness the same points apply to all kinds of examples no if you want to know the climate in the area that's going to be a generalization about days around here in this time of year but if you want to know the weather tomorrow you need to apply it and then you're going to need to look at specifically what the weather was yesterday specifically what the humidity is the more information you can build in the better estimate of what the weather is going to be tomorrow or if you want a better sports team you say well they're a very good team they've won most of their games in the last five years but wait a minute maybe all their players left and now it's not likely that they're going to win but wait a minute they got new players that are even better that makes it more likely they're going to win and again the information can make the probability go low and then high and then low and then high and you have to get the most specific information you can to get the most accurate estimate of how likely it is that this team will win but you might not have enough information about this team with these players under these circumstances because they just haven't been enough cases for you to observe so as with the medical example it's going to get tension between wanting the most precise the most smallest reference class among the different conflicting reference classes and yet you need premises that you have enough information that you can justify them and if you can reach that perfect point where you've got enough information to justify the premises but that premise is specific enough so that it has all the relevant information about the case that's when we're going to have the best outcome for applications of generalizations perhaps the most common kind of inductive argument is called an inference to the best explanation and to understand this kind of argument we need to think way back to the first week when we discuss the difference between justification and explanation if somebody uses an argument to justify a conclusion then they're trying to give a reason to believe that the conclusion is true and maybe you didn't believe that conclusion before you heard the argument but if somebody gives an argument to explain the conclusion then they're taking it for granted that the thing they're explaining is true and they're trying to understand why it's true and the argument is supposed to help us understand why it's true or the weird thing about an inference to the best explanation is it really combines these two it uses the argument to justify belief in the conclusion that is to give you a reason to believe that it's true and yet a premise of the argument is that that conclusion explains a phenomenon that you took for granted inferences to the best explanation are extremely common for example almost every detective story uses an inference to the best explanation just imagine that there's three suspects and you know that one of those three suspects must have done it because the door wasn't jimmied open so whoever got into the room must have had a key and there are only three people who had keys but one of them couldn't have been the one who did it because she has really small feet at the footprints outside the door were really large and so it couldn't have been her and the second person couldn't have done it because they have an alibi on the other side of town so it must have been the third person who did it and notice what you did is you can't explain why the door wasn't jimmied by the person who got in because there were no marks and that means that the best explanation or that must be that the person who did it had a key and the best explanation why the footprints were so large was that it was a large person who wore large shoes and the best explanation of why the alibi would place the person on the other side of town was that they were being honest assuming it's not their brother they're not the kind of person who would lie or so on so the best explanation of why the jewels are missing from the room or why there's a dead body in the room uh is that this third suspect is the one who did it so all the detective stories work like that it's almost always an inference to the best explanation the best explanation is he's the one who did it and one implication of this is that no matter what Sherlock Holmes says the form of reasoning that he was using was inductive reason not deduction as he claimed but it's not only detective novels it's also science that uses inference the best explanation take for example the greatest murder mystery in history what killed the dinosaurs well some people think that it was mammals eating their eggs not a chance that doesn't explain why there were also mass extensions in the oceans for the mammals weren't eating their eggs but some people think that the best explanation is that there were big volcanic eruptions in southern india that seems pretty unlikely too because the volcanoes that we know didn't put out enough material to kill things all the way around the world so they think that the best explanation of what killed the dinosaurs is that a giant meteor hit in the Yucatan Peninsula in mexico and that produced lots of soot in the atmosphere that killed the dinosaurs as well as many other species at the time but luckily not mammals and so we now have a best explanation in science and a lot of scientific theories work that way as a matter of fact the point of most scientific theories is to provide the best explanation of all the experimental data that has been observed by scientists throughout the world and of course we also use inference the best explanation our everyday lives to try to figure out what's going on around us here's an example whoa what was that drop of water just hit my head there must be a leak in the roof now that is an inference to the best explanation starts with an observation of the water hitting my head then i think about why the water would be coming down and the best explanation i can come up with is that there's a leak in the roof so i conclude that there is a leak in the roof notice that this argument uses an explanation but it runs in the opposite direction from an ordinary explanation in an explanation the premises explain the conclusion and the conclusion describes the phenomenon that was observed when there is a leak in the roof water drops through the roof when water comes through the roof it drops onto whatever is in its way i am in its way therefore water drops on to me this explains that in contrast an inference to the best explanation works in the opposite direction the conclusion is what does the explaining the premises are what get explained and the point is to justify belief in the conclusion not to explain it water drops on to me a leak in the roof would explain why water drops on to me no better explanation is available therefore there must be a leak in the roof notice that the conclusion of the left argument is a premise of the right argument and the conclusion of the right argument is part of a premise of the left argument so the form is different the function is different as well in the explanation on the left we start out already knowing that the conclusion is true in the inference to the best explanation on the right we argue that the conclusion is probably true because it is the best explanation of the observation in the first premise that's why we call it an inference to the best explanation is this argument valid yes or no right it's not valid because it's possible for the premises to be true and the conclusion falls now does its invalidity make the argument bad yes or no right it does not make it bad because an inductive argument can be good even if it's invalid the next question is a bit trickier remember that an argument is defeasible if further information can make the argument weak so is this argument defeasible yes or no right it is defeasible because further information could make this argument weak so what does its defeasibility mean that this argument was weak even before we got that additional information yes or no no because inductive arguments can be strong even though they are defeasible so now we know that this argument is invalid and it's defeasible but it still might be strong and good we've learned that inferences to the best explanation are inductive arguments they're not valid and they are defeasible but still they might be strong and good arguments they might give you good reasons to believe their conclusions great they might be sure but how do you tell whether they really are strong arguments and good arguments we need standards for determining when an inference to the best explanation is a good argument and to understand those standards we're going to view another skit made by my students a few years ago it's time for class whoa where is everybody it's me it's monday isn't it yeah first day of the week remember the weekend hmm the weekend yeah i remember vaguely good times but now it's back to work it's monday but what time is it 12 and 15 well isn't that one class is supposed to start here's the start of a good explanation there are surprising circumstances that need to be explained maybe my watch is fast it has been giving me some trouble lately do you check yours oh i don't wear a watch i just ask you what i need to know the time great so i'm your designated timekeeper kind of but there's usually a clock around one right there okay so we know it's 11 15 right in any inference to the best explanation it's crucial to get an accurate picture of what you're trying to explain in this case if it were 11 10 instead of 11 15 then the explanation would be different or there might be nothing at all to explain so where is everybody well maybe everybody else is late after all the professor does show up a few minutes late he told me that he doesn't like to start teaching right away because it isn't like when he's talking students walk in oh that makes me mad so maybe they're coming in later because they don't want to have to wait around for him to start talking it's one of those vicious circles okay maybe that's it but then some students should start showing up so let's just wait and see okay that's enough if people were coming they'd be here by now i mean the professor's been late but he's never been this late and refutes bob's explanation by pointing out new facts that falsify bob's hypothesis that all the students are late a good explanation has to be compatible with all of the facts not just the particular ones that it's trying to explain bob's hypothesis can't be the best explanation of why the students aren't there at 11 15 if they're still not there by noon well that brings us right back to where we started why isn't anybody else here you're guessing as good as mine well well my guess is that everybody else is here we just can't see or hear them i bet they're laughing at us right now i bet the professor is up there jabbering away right now like he always does yeah well i hope this material is not on the test congratulations you proved me wrong your guess is not as good as mine why humans can't become invisible how do you know have you ever seen it no they're invisible that's why i've never seen it okay but the laws of physics don't allow humans to become silent and invisible and dismisses bob's new hypothesis because it's not conservative it conflicts with well established prior beliefs in physics if you start believing that humans can become invisible you'll have to give up everything you know about how light and matter work besides if they were here the seats wouldn't be popped up like this nope because besides being invisible and silent these students are also weightless no smell either okay so there is no way to tell whether or not their students here you're catching up but the laws of physics still don't allow people to be weightless invisible and silent well the laws of physics are based on observation and there is no way these students can be observed at all the laws of physics can apply to something that can't be observed or these students so then nothing could possibly tell whether or not there are students in these chairs exactly hey ed we're here live with an unidentifiable unobservable student what's it like to be unobservable okay back to you ed pretty sweet huh no it is not sweet the only reason why your idea isn't falsified is because it's not falsifiable if you can't prove it then it's useless i mean you might as well say there's invisible elephants floating around and rejects bob's new explanation on the grounds that it's not falsifiable it's compatible with anything that could possibly happen but that means that it can't explain why one thing happens rather than another it's completely empty i was just joking this is a philosophy class after all okay i don't mind jokes but let's get serious it's not helping us with our problem why isn't anybody here speaking of joking maybe they're all playing a trick on us maybe they decided not to show up okay but why would they do that is it april fools day no it's january oh well then i don't know why they're tricking us they just are okay i can't believe that unless you can tell me why they would be so silly and it's criticizing bob's new explanation because it's not deep it's shallow because it depends on a principle that is not itself explained and needs to be explained i guess the professor just decided to cancel class because he didn't feel like teaching today maybe but then other students wouldn't know so they would be here unless he emailed the entire class then they would know did you check your email recently about an hour ago then maybe he emailed us in the past hour i guess i mean that would explain why nobody's here some professors do cancel class at the last minute but not him i think he's too strict i've had five classes with him and he's never cancelled class at the last minute if you miss even one class in this course you will will fade fade fade so maybe this time it's different yeah maybe the sun didn't rise either way it's totally out of character Ann's point is that Bob's new explanation is ad hoc. It applies only to the very circumstances that it was invoked to explain, and it doesn't apply to other cases. That means that it lacks power and breadth. Okay, but I've got it. Classes must have been canceled for some reason. What reason? Maybe it's a holiday. Okay, what holiday? I... Martin Luther King. That's it! It's Martin Luther King Day! That would explain it.  Hi, I'm here. I guess that makes us both fools. Yeah. So I guess that's why he didn't send the note, because he figured no one would come here. I bet he wrote it down in the syllabus. It also explains why no one's in the whole classroom building. Bob's new explanation works because it has all of the virtues that the other explanations lack. It's powerful, broad, deep, simple, conservative, and not falsified and yet falsifiable. Those virtues make his explanation good, or in his words, so weak. You're right. You know, I think there's some kind of ceremony today with the president of the college and some big hot shot from Washington, from Martin Luther King Day. So probably that's where the whole class is. That's why they're not here. Maybe, but even if there weren't a ceremony, the fact that it's Martin Luther King Day would explain why nobody's here, so you don't really need to add anything else. Ann rejects Bob's newest explanation because it's not modest. It commits him to more matters of fact than are needed to explain the observations at hand. So I guess the holiday explains it all. Oh, not really. We still don't know why that big head keeps popping in on the side. That's one that I can't figure out myself. That guy looks like this kid who used to babysit me when I was younger. This whole exchange can be seen as a single argument that takes the form of a long inference to the best explanation. The first premise is an observation. Nobody else is in the room. The second premise is an explanation. The hypothesis that class was canceled because of the holiday plus accepted facts and principles gives a suitably strong explanation of the observation in premise one, namely the observation that nobody else is in the room. Premise three is a comparison. No other hypothesis provides an explanation nearly as good as the holiday hypothesis in premise two. And the conclusion is that the holiday hypothesis in premise two is true. The most controversial premise is probably premise three. It says that no other explanation provides nearly as good an explanation as the holiday hypothesis. To justify this premise, we need to compare other possible explanations. And that's exactly what the two students do throughout the skit. Their discussion can then be summarized in this background argument that supports premise three. The hypothesis that the other students are late is falsified by the passing of time. The hypothesis that the other students are invisible is not conservative. The hypothesis that the other students are undetectable is not falsifiable. The hypothesis that the other students are playing a joke is not deep. The hypothesis that the professor skipped class is not powerful or broad. The hypothesis that the other students are at a ceremony is not modest. No other hypothesis seems plausible. Therefore, no other hypothesis provides an explanation nearly as good as the holiday hypothesis in premise two. Even if the other explanations are inadequate, the inference of the best explanation fails unless the holiday hypothesis succeeds at explaining why there's nobody else in the room. Premise two claims that the holiday hypothesis does explain why there's nobody else in the room. So we need to analyze why it succeeds. And to do that, we can look at another background argument. The holiday hypothesis explains why nobody else is there because if classes were canceled because of the holiday, then nobody else would be there. That is, nobody else would be in the room at the usual time. The holiday hypothesis is also broad because it explains other actual observations, such as the observation that the whole building is empty. The holiday hypothesis is also powerful because it applies to many separate cases. For example, it explains why students won't be there on future holidays. The holiday hypothesis is also falsifiable because two students might find out that classes were not canceled for the holiday. The holiday hypothesis is not falsified because the two students do not actually find out that classes were not canceled for the holiday. And similarly for other ways to falsify the hypothesis. The holiday hypothesis is also conservative because it does not conflict with any prior well-established beliefs. The holiday hypothesis is also deep because it does not depend on any assumptions that need but lack independent explanation. So the holiday hypothesis explains why nobody else is there and it's broad, powerful, falsifiable, but not falsified, conservative, deep. Therefore, the holiday hypothesis plus accepted facts and principles gives a suitably strong explanation of why nobody else is in the room. These two background arguments use a common list of virtues that are usually called explanatory virtues. In general, one explanation is better or stronger than another if it has more of these virtues. When you understand these explanatory virtues, then you've mastered inference to the best explanation. Right? Right. Now we can go on and look at other kinds of inductive argument. In the previous lecture, we saw one example of inference to the best explanation, but it might help to go through just one more. I told you that detectives often use inference to the best explanation to figure out who committed the crime. One really neat example of this kind of argument was provided by some students in the first offering of this course. Just check out the video that they made. I think I'm going to go for a run. Philip and Mackenzie are sleeping. Work up an appetite. I might dig into some of those cookies later. That was a good run. I think I'm going to have some cookies. What? Oh man, that was a brand new day. The dish broke. And I was wondering if you heard anything or if you had anything to do with it. No, I just woke up. You didn't hear? Huh. I wonder how this could have happened. You didn't feel any earthquake. Did you or something? Well, I suggest that perhaps it was Timmy.  I think we found our answer. Timmy did it. Philippa? Timmy. Timmy, what do you have to say for yourself? Love that video, didn't you? Great production values. He's ready for Hollywood. The actors, Emmys. Oh man, whatever you hired professionals. And the argument was good too. First of all, it was really clear. I mean, you know exactly why they think Timmy did it. The structure was really good. You start with a phenomenon that needs to be explained, namely, the dish was broken on the floor and you look for alternative explanations and you compare those different explanations and the best explanation is that Timmy did it. Okay, so what are the competing explanations? Well, Mackenzie might have done it, but she denied it and she wouldn't lie to her parents. She looked so innocent, at least I thought so. We'll see whether other people agree. And the other possibility is an earthquake that nobody felt an earthquake and they probably would have felt an earthquake so that's no good. Maybe Philippa did it. Wait a minute. I don't know if you noticed that little box. Philippa sleeps like a log and he got back at 7.45. That's when the dish was broken. She didn't come down till 9.45 and she's sleeping like a log. How could she have done it? So we've got different hypotheses that are being considered and he's looking for the best one. So what makes it best is not just that those other hypotheses have things that rule them out, but also that this hypothesis has a lot of positive support for it. One thing is nice is that he found the hair on the counter. That was crucial because now the hypothesis that Timmy did it explains not just the dish but also the hair on the counter and that's a sign of a good explanation that it explains not just the particular things but it's powerful and broad. It applies to other things as well and explains other phenomenon that need to be explained. So overall, I think there's pretty good reason to think that Timmy did it. And the kicker that proves it all is that the cat confessed. You heard it yourself. The cat said, Of course the argument could be stronger because inductive strength comes in degrees but the fact that it could be stronger doesn't mean it's no good. You can get a pretty good reason by ruling out the most plausible hypotheses even if there are few that you didn't quite get to in presenting your argument. And sure enough, in the discussion forums some students pointed out weaknesses which amounted to looking at these different hypotheses as possible explanations of the data. A lot of students seem to suspect Mackenzie. Here's one of them. Joe writes, Hi Kevin. While watching the interrogation of Mackenzie, I got the feeling she was hiding something. She had means, motive, and opportunity. I think in order to add to the strength of the inductive argument that she's innocent she should volunteer for a lie detector test. And then he goes on. I suspect that Timmy was framed considering how minorities and the poor are treated in the justice system I recommend that he remain silent until he secures representation. Well, I don't know about the second half of that but with regard to Mackenzie there's an interesting point to notice here. Joe doesn't know Mackenzie and he doesn't trust her. Thinks she looks suspicious. But Kevin, he knows Mackenzie. He lives with her. He spent a lot of time with her. And he trusts her. So we have a nice example of how an inductive argument might be strong for one person and not for the other person. Because Kevin has this background information that Mackenzie's trustworthy. Whereas Joe doesn't have that background information. So the argument that Kevin gave in the very short form in which it occurred might be good enough for him because of his background knowledge about Mackenzie's trustworthiness. Whereas it's not good enough for Joe because Joe doesn't have that background knowledge. And that's just a fact about inductive arguments in general that they might be strong for some people and not so strong for other people. And we could make the argument even stronger by looking at other explanations. So what about Philippa? Well, she sleeps like a log but maybe she was sleepwalking and knocked the cookies over when she was sleepwalking. What about Kevin himself?  Maybe he did it when he came back from running because he had sweat in his eyes and didn't notice it and didn't hear the plate drop because he was so tired. Maybe there was a burglar who came in and while they were stealing things they knocked the cookies over and that made noise and so they got scared and ran away. Maybe it was Santa Claus. He has been known to eat cookies that are left down on the counter for him. Maybe it was ghosts. There's all kinds of possible explanations and you could drive yourself crazy trying to rule out every possible explanation. So at a certain point you have to decide when is the argument strong enough? And that depends on what you're going to do with it. Now I've said I think this is a good argument. I think Timmy did it. The confession really is the kicker but I'm not ready to give Timmy capital punishment. I'm not ready to banish Timmy from the house. There's some steps that would just be too harsh in response to this amount of evidence. However, I do think that the evidence is strong enough that we can guide our action with it at least in ways that don't have a lot of cost. So for example, my suggestion to Kevin and his entire family is don't put the cookies on the edge of the counter.  You've got to accept some responsibility yourself and this argument can be good enough to guide our action about where to put the cookies on the counter, when to leave them out and when not to leave them out even if it's not good enough to justify capital punishment. So one thing that we need to think about in assessing not just how strong an argument it is but whether it's strong enough is what are we going to do with it and what are the costs incurred if we're wrong. Another very common kind of inductive argument is an argument from analogy. We'll see that these arguments from analogy are very closely related to inferences to the best explanation. But first we've got to ask what's an analogy? An analogy is basically a comparison between two things. It points out similarities between those two things. And analogies are given all the time. For example, a poet might say her eyes were like emeralds. Well, in what way were they like emeralds? They might have had the same color. They might have shimmered like emeralds. They might have been valuable like emeralds. And the analogy, her eyes were like emeralds, doesn't really tell you exactly which respect her eyes resembled emeralds. But that's part of the point. When you're writing poetry, you want to stimulate creative comparisons and analogies so that readers of the poem can think about it in their own way. And the same thing holds for other analogies in other areas. But because it's not very specific, some people think that analogies are just no good at all in arguments. Actually, though, we use analogies in arguments all the time. Here's an example from public policy. It built a transportation system in the city of Houston, Texas. It worked pretty well. And then the planners in the city of Phoenix, Arizona were wondering what kind of public transportation system to build there. And they reasoned like this. They said Phoenix is a lot like Houston in many ways. Large population, hot during the summer, many, many people, and large area. So they said Phoenix resembles Houston in a lot of ways. This type of transportation system worked in Houston, so it'll probably work well in Phoenix also. Now, what about law? Lots of legal decisions are based on analogies, too, because common law systems, at least, follow precedent. When judges decide a case one way at one point, then later on, other judges are supposed to make similar decisions. So you can say, for example, the Supreme Court declared that segregated public high schools are unconstitutional in the United States. Colleges are a lot like high schools, so segregated public colleges are also unconstitutional in the United States. And then med schools are a lot like colleges. So segregated public medical schools are also unconstitutional in the United States. And that's the way the legal system evolves by drawing analogies among the different cases that come up within that jurisdiction. This form of argument in law might seem to be a real problem because you don't say exactly what the similarities are. But actually, it's very useful because it is predictable if you know that segregated high schools have been declared unconstitutional. You pretty much know that judges are going to find colleges unconstitutional, too, if they're segregated. And it also gives flexibility so that judges can see when they're going too far, they say, well, that precedent's different, and they distinguish the precedents. So by resting legal reasoning on arguments from analogy, they gain both predictability and also flexibility in the legal system. So arguments from analogy can be pretty useful. Fine, but policies and laws are all about norms and values. What about science and hard facts? Well, scientists use analogies, too. For example, scientists at one point didn't know what was at the center of the earth, but they found a bunch of meteors and meteorites that had a high iron content much higher than the content of iron in the crust of the earth. So they reasoned the earth must be like these other meteors and meteorites, so it must have a similar amount of iron in it because they were produced in the same way in the history of the universe. But that means there must be a similar amount of iron in the earth. If it's not in the crust, where could it be? It must be down in the core. So they figured probably the core of the earth has a lot of iron in it. That's just one example. But scientists actually use analogies a lot. And if you don't believe me, go read some psychological studies of scientific reasoning. But we're going to focus on an example from art history. Just imagine that you're going through the attic and you find an old painting. It looks a lot like a painting by the famous impressionist Cézanne. And if it is by Cézanne, it's worth an awful lot. But you've got to figure out whether this painting is by Cézanne. How do you figure it out? Because Cézanne didn't sign it. He didn't sign a lot of his paintings. Well, what you do is you look at other Cézanne paintings and try to figure out whether they're similar. And if you're not an expert, you'd probably better check with an expert and have them do it. But they're going to do the same thing. They're going to compare this painting to a lot of other paintings that we know are by Cézanne. And then you can reason like this. This painting has a certain kind of brush work and coloring and so on and so on, subject matter, whatever. Other paintings by Cézanne have very similar brush work and color patterns and topic and so on. Those other paintings are definitely by Cézanne. We know that. Therefore, this painting is probably by Cézanne as well. Now that's an argument from analogy. This argument from analogy shares a certain form with the other arguments from analogy that we discussed before. And we can pick out that form by substituting letters for the English words in the English argument. For example, we can substitute the letter A for the subject. That is the topic of the argument, the painting that we don't know whether it's a Cézanne or not. And we can substitute the letters B, C and D for the similar objects that are also Cézanne paintings. And we can substitute the letters P, Q and R for the similarities between the paintings that we know are by Cézanne and the one that we're not sure of. And then we can substitute the letter X for that particular property of being by Cézanne. And when you substitute all those letters for the English words, then the argument simply says that object A has properties P, Q and R. And objects B, C and D also have those properties P, Q and R. And B, C and D also have the property X. So the subject, object A, probably also has the property X. Namely, this painting is by Cézanne, probably. Of course, since this argument only tries to show that the conclusion is probably true, it's an inductive argument. It's not valid. It's possible for the premises to be true and the conclusion false. Namely, this painting might resemble all those other paintings in those respects, and yet it's not by Cézanne. Secondly, the argument's defensible. You can get some additional information that makes it really look like a bad argument. For example, you could turn the painting over and on the back, you find the signature of a different artist, like Seraf. And then you realize this isn't by Cézanne at all. But nonetheless, the argument can be strong. It can always be stronger because there can be more similarities and more important similarities. But it can be a strong argument and a good argument because it's inductive, so it doesn't even try or pretend to be valid. How can we tell when an argument for an analogy really does give us a strong reason to believe the conclusion? What are the standards by which we measure how strong the argument is and how strong the reasons are? Well, one of them should be obvious. Of course, the premises have to be true and justified, like in any argument. A standard that's relevant here is that when there are more important analogies, then it provides a stronger reason. Because some analogies are just totally unimportant. The painting is square. Other paintings by Cézanne are square. Therefore, this is by Cézanne. Well, that's ridiculous, right? Because lots of painters use square candles. But something that's important that's going to be specific to Cézanne, a very idiosyncratic, is going to be more important for this type of argument. Secondly, when there are more analogies, because we don't know exactly which one is the one that's important. That's the point of an argument from an analogy. You draw the analogy without knowing exactly which respect is the crucial one. So the more analogies that you have, the more likely you're going to hit on the ones that are crucial. So if it's not just brushwork, it's also the type of paint that was used. It's also the color scheme that was used. It's also the geometric shapes. It's also the subject matter. It's a particular mountain that's close by where Cézanne lived, and he painted a lot of that mountain and on and on and on. The more analogies, the more likely that some of them are going to be the crucial ones, and therefore the stronger the argument is, and the stronger reason it gives you to believe that this particular painting is by Cézanne. But of course, there are always going to be some disanalogies as well, because Cézanne didn't paint the same thing over and over again, exactly the way he did the first time. The fewer disanalogies, the stronger the argument. There'll always be some, or there wouldn't be much of an argument there. It would be exactly the same painting. But the fewer disanalogies, and the less important those disanalogies are, then the stronger the argument is going to be. Next, the objects that you're comparing, because they're similar in various respects, that is the other paintings that we know are by Cézanne. If they're quite diverse, then that means that you have similarities among a diverse group. They all share these particular properties, and that means that Cézanne continued to use those features throughout all the different types of paintings that he did, and that means that it's going to be a stronger reason to believe that this painting is by Cézanne. Finally, the conclusion is weaker. You could say, therefore, this painting is definitely by Cézanne. It couldn't be anybody else. Well, that's kind of crazy, right? But if you say it's probably by Cézanne, but it has some chances by Cézanne, maybe you want to check it further, then you're weakening the conclusion, and that can make the argument stronger. So in all of these different ways, we can assess how strong the argument from analogy is by looking at the respects in which the objects are analogous, the diversity among the objects that are analogous, the strength of the conclusion, and so on and so on. And that's how we assess an argument from analogy for strength. I want to close with one more example that raises interesting questions about the relationship between arguments from analogy and inferences to the best explanation. It concerns the pressing issue of whether Neanderthals were cannibals. Now, it's not a pressing issue for most people, but it is a very pressing issue for people who study Neanderthals. And so it's quite a breakthrough when they found some bones in a cave that they knew was inhabited by Neanderthals. In that cave, next to what looked like a fire pit, there were bones of deer with markings of a certain sort that looked like they had been cutting the meat off the bone. And they also found bones of humans in that cave where they had been cutting, where they had similar markings. And they argued, since the bones have similar markings, and these bones, the bones of the deer, were probably cut up for food, well, the human bones were probably also cut up for food. So they reached the conclusion that at least sometimes Neanderthals ate humans. What's interesting is that there are two ways to reconstruct this argument. First, you can reconstruct it as an argument from analogy. The bones of the humans were found in this location with these kinds of markings. And the bones of deer were also found in this location with these kinds of markings. That the deer were cut up for food, therefore the humans were probably also cut up for food. Now that sounds like an argument from analogy when you think about it that way. But you can also reconstruct the argument as an inference to the best explanation. The bones of the humans had these markings on them, and were in this location. How do you explain that? The best explanation of why they have these particular kinds of markings is that they were cut up for food. Therefore the humans were probably cut up for food as well. Now notice that both reconstructions of the argument make the argument look okay. And so it's not clear which tells you the real structure of the argument that the author was trying to give. And that means that arguments from analogy and inferences of the best explanation are actually very closely related. And sometimes you can take an argument and reconstruct it either way. It's not going to affect very much how strong the argument is, but it might affect how you see the argument working. And the big difference is that when you do an argument from analogy, you don't have to specify exactly which respect is important. So you can point out lots of analogies and hope that you hit the one that really matters. Whereas when you're doing an inference to the best explanation, then you have to pick out the specific property that gives you the explanation of the phenomenon that you observe. So it forces you to get a little bit more specific than with an argument from analogy. But otherwise, these two arguments are clearly very closely related. And they're basically two different ways to argue for similar conclusions. For example, in this case, with the argument from analogy, you don't know whether it's the location next to the fire or the types of markings, or maybe there's several different types of markings, and they're all the same, but you don't know which ones are the ones that indicate how it was killed and which markings indicate how it was cut up to be eaten. And an argument from analogy can leave all that vague and just think that probably one of those similarities justifies the conclusion that the humans were cut up to be eaten. But if you're going to give an inference to the best explanation, then you're saying that these markings, for example, diagonal markings on leg bones, might suggest that they cut that up in a certain way because that's how they prepared the deer meat, and they were used to preparing deer meat that way. So they used similar cutting techniques when they were preparing human meat. And you've got an explanatory story that's much more specific than a mere analogy, but it also commits you to a lot, so it might be questionable in various ways. So when you look at an argument like this, you've got to decide which way to reconstruct the argument as an argument from analogy or as an inference to the best explanation. And the general rule is one that we saw long ago in the early weeks of this course. If you really want to understand an argument, you want to understand your opponents or you want to have a better argument for yourself, then you try to make the argument look as good as possible. So when you face a particular example like the Neanderthal example, you have to decide, is this argument going to be better if I reconstruct it as an argument from analogy, or is it going to be better if I reconstruct it as an inference to the best explanation. And the best reconstruction is going to be the one that makes the argument look best.


We live in the age of the automobile, an age where despite energy shortages, rising operating costs, and mass transport options, over 124 million passenger vehicles alone are registered in America, each averaging over 9,000 miles of travel annually. This ever-increasing volume of traffic has stimulated various methods of traffic management to minimize congestion, driving costs, and driver frustration. Today, through the use of modern vehicle detection devices combined with computer technologies, it is possible to monitor vehicle speeds, to record traffic volumes, to create elaborate signal systems, to display various warning signs, and even to re-root traffic away from problem areas. Vehicle detectors originally evolved for traffic signal control in the late 1920s, as increasing traffic volumes made it apparent that fixed-time signals had limitations. Fixed-time signal controllers are mechanical devices with a fixed sequence of right-of-way assignments. Although these were once the standard for signal control, their inability to respond to traffic flow and direction soon proved wasteful and unsatisfactory. In 1928, the first vehicle detector was installed at an intersection in Baltimore.  Although this may have been convenient for the waiting driver, it wasn't too popular with the neighbors. Various other detector systems have evolved since that crude beginning, such as pressure-sensitive, radar, magnetic, magnetometer, sonic, and self-powered systems. Currently, the most widely used type is the inductive loop detector. This consists of one or more loops of wire wound into slots cut into the pavement. These loops are connected by a lead-in cable to a detector unit that serves as an AC power source. The combined lengths of the loop wires and lead-in cable dictate a certain natural frequency of vibration for that system. The power source is adjusted to match this resonant frequency, creating a tuned circuit. Current flowing through the wire creates an electromagnetic field around the loop. This field can be illustrated as lines of force or flux surrounding the wire, which contain energy. When a vehicle enters this field, eddy currents are induced into the metal of the body and frame, reducing the lines of force, a kind of absorption of energy from the loop. This absorption causes a decrease in the self-inductance of the loop, which in turn raises the frequency at which the loop will resonate. Some detector units respond to this by means of feedback circuitry that increases their frequency of oscillation. Others respond to the phase shift between the loop oscillation and the reference oscillation. Either of these response designs activates an output relay in the detector unit, which sends a signal to a controller indicating that a vehicle is over the loop. Because of its flexibility in application, relatively low cost, and comparatively safe design, the inductive loop is the most common detector now in use. Recently, much research has been done by various agencies toward extending the lifespan of these detectors. In 1981, a project was undertaken by the Engineering Research and Development Bureau of the New York State Department of Transportation to study inductive loop detector failures. The study's purpose was to identify how and why these detectors fail, and how to prevent or reduce these failures in order to improve their life expectancy. The first phase of the project included a field survey of over 300 failed loops. Failure types were documented in the field and then analyzed by a statistically based computer program. In most instances, failures could be attributed to one or more of the following factors, design and installation methods, sealer reliability, and wire durability. The formulation of solutions to these problems became the major areas of study and evaluation in the second phase of the project. The question of loop placement was examined first. Because this system includes wire loops only inches below the road surface and lead-in cables sometimes extending hundreds of feet, it is vulnerable to construction and repair of the roadway, walkways, curbing, and various utilities which often damage or destroy a loop system. Before the actual installation, the work site should be inspected to determine the location of utility lines which should be avoided. A check for scheduled construction in the work site area could also prevent these types of conflicts. After the exact installation site is chosen and proper safety measures are taken, detector installations should begin by marking the loops outline on the pavement surface with chalk line, spray paint, or any other marking material. This outline is then used as a guide for sawing the slots. Formerly, loop patterns in New York State were cut according to this standard. Diagonal saw cuts at the corners were intended to limit the sharpness of bends in the installed wire. But pavement sections at these corners were subject to breaking and popping out, thus leading to exposed wire and loop failure. In March of 1983, a new loop design was approved in New York State, in which the corners are cut square and then rounded. This new pattern decreases corner-related failures and at the same time requires less sawing. Masonry saws for loop installations are available in a range of sizes and sawing capabilities. This is an 18 horsepower saw with a diamond blade in a wet cutting operation. This was found to be a most efficient method. An 18 horsepower saw is preferable to the widely used 9.5 horsepower model. The smaller model is slower and breaks down frequently due to excessive workload. A variety of saw blades can also be used in loop installation, but the diamond blade is considerably faster, neater and perhaps safer than traditional dry cutting abrasive blades. There are two acceptable methods to prepare corners in the new loop design. One is to remove a core to the full depth of the sawed slot from each corner and then round all rough and sharp edges. The other more popular method is to use a small air hammer to chip back the sharp edge, making a smooth curved surface for the signal wire to bend around. When the corners are completed, the saw slot must be cleaned in preparation for sealant installation. In the past, this was done by blowing compressed air into the slot. This method was found ineffective in slot cleaning because it left fine debris dried on the inside of the slot. This debris prevented proper bonding of the embedding sealer to the inside of the slot and eventually led to detector failure. One effective way to clean the slot is to use this hydroblasting system. This system has a nozzle that, by using the Venturi principle, combines water with compressed air to give a hydroblasting effect sufficient to clear away any debris left in the slot. Once clean, the slot must be dried completely before wire installation. This can be done by using the same instrument with the water supply disconnected. Based on the failure survey, a large percentage of failures could be prevented by using a more durable wire. Most failed loop systems studied were constructed according to a specification calling for 14 gauge stranded copper signal cable with a polyethylene insulation. This wire could not survive the stresses caused by even minor pavement disruptions such as creeping, cracking and thermal expansion and contraction. Nor could it withstand exposure to water and debris from minor sealant failure. It was found that the use of 14 gauge stranded copper wire, loosely encased in a flexible vinyl tube, had been very successful in other state's loop detector installations. With the loop wire loosely encased, it is free to move in the tube and can compensate for pavement disruptions by distributing tension throughout the entire length of the wire. Encasement also provides additional protection from water and abrasive debris. The incorporation of tube encased signal wire was carefully evaluated. It was found that a wider and deeper slot is necessary to accommodate this type of wire, resulting in increased saw cutting and sealant costs. There is also an increase in the cost of the wire itself, but increased material and installation costs are greatly offset by the resulting extended loop life. Once the proper number of wire loops are in the slot, the wire's two ends are wound together for the specified number of twists per foot. They are then threaded through a conduit into a pull box, where an electrical inspection is performed and recorded. This includes measurements for leakage to ground, loop resistance, correct inductance and induced voltage. Wire splicing in a loop system is done basically in two steps. The first, physically connecting the wire ends, can be done by soldering, a screw and nut, or a crimping method shown here. The second step is to environmentally seal the splice by either applying several layers of various re-insulating materials, or by encapsulating the spliced area in a container filled with embedding sealant. Another cause for loop failure is called wire float. When the embedding sealant is soft and plastic, the wire has a tendency to float up to the surface, exposing itself to the abrasive effects of traffic. Since some sealants remain soft, this can also happen after the sealant's curing, depending on the product used. To avoid this, various materials can be used to hold down the loop wire. Hold down should be placed at all corners, wherever the loop wire changes direction, and spaced at two-foot intervals around the entire saw slot. A material well suited for this purpose is an open-celled foam rubber backer rod. This material is readily available, easy to work with, and is unaffected by most sealants or their installation temperatures. When using this one-half-inch diameter backer rod, one-inch-long strips are torn off and pushed into the three-eighth-inch wide slot. Another major problem area is embedding sealant failure, which includes cracking, debonding, shrinking, tracking, and running out of the slot, or poor encapsulation of wire, all of which lead to loop failure. Bituminous-based materials, or hot tires, have been popular in the past because they were relatively inexpensive and easy to obtain. However, several problems exist with use of these materials. Most bituminous sealers must be heated to a pourable temperature, sometimes exceeding the melting point of the wire insulation, which, when damaged, will lose its protective properties. Working with this heated material has proved dangerous to both workers and nearby pedestrians. Hot tires also become soft in warm weather and can be tracked out of the slot or contaminated by dirt and debris. This makes it necessary to clean and reseal the slot regularly. A laboratory testing and evaluation program was developed by the Materials Bureau to produce specifications for acceptable sealants. Sealants were tested for curing time, water absorption, pot life, wire encapsulation, tensile strength, and adhesion. Based on this testing and extensive field evaluations, the best sealants for this purpose were found to be cold-poured epoxy or epoxy resin materials. They have excellent bonding capabilities, are durable, and resist effects of weather and provide good encapsulation of the loop wire. These cold-poured sealants also diminish installation hazards and increase detector cost-effectiveness by reducing periodic maintenance. A V-shaped squeegee can be used to scrape excess sealant into the slot. This reduces sealant waste and leaves the cured sealant flush with the road surface, or even slightly below the surface where it is better protected from traffic. After sealing the slot, a light dusting of Portland cement may be added to prevent tracking out if the surface of the cured sealant is still tacky. This completes the installation. Through use of these installation techniques and similar materials, the dependability of inductive loop detectors has been much improved in other states, such as Illinois and Connecticut. They both formally experienced an annual replacement rate of about 20% as did New York State. After several years of using these improved installation techniques, their current annual rate of replacement has fallen to nearly 1%. If New York State accomplishes a similar improvement, annual replacement costs of over 3400 of these detectors may be saved. This could translate into about $7 million of maintenance funds. The motoring public will also benefit directly from safer, more efficient travel with better inductive loop detectors.


Hi guys, welcome to EmberConference 2021. My name is Ramin Mahmood and I am from Pakistan. I am running a small IT service provider company named Allah Solutions and we use Ember on a daily basis to serve the needs of our clients. We used Ember for index to applications, mobile applications and as you know the web applications. So let's begin the journey. I would like to say big thanks to my cat because she really helped me during the preparation of this presentation and as you can see that she is really helpful. Okay, so as in every application there is a beginning to start a new application. We have this command Ember Nu and I next the project name. For the sake of this presentation we are going to use a simple listing of jobs and I have created a mock server with some jobs on there and to deal with that we are going to use a job model and here is the model and after creating the model we would be using an adapter because an adapter is needed to communicate with a server. Here you can see that I am using a rest adapter and my mock server is on this URL. So Ember should know that where the data is coming from. After that definitely some UI is very important because that's what the user will be seeing. For this example I have used Semantic UI and they have Ember component as well. You can use that but I just used their CSS from the cdn. So this is the current output so far. Let me show you some code. Okay, this is the model and this is the router. You can see that in the router I have two paths. One is home and this is going to be the root of the application and the other one is the details. So when user will click on a job it will open our details page and that detail page will show all the other information to the user which might help him score a job. Okay, let's okay and on the home I am just fetching the job from the store. This is a very standard Ember data model. This is how I am presenting the jobs. These classes are from the Semantic UI and when jobs are fetched used each helper to loop over all the jobs and created a link to the details out using the model ID and then presented some of the details. And if I show you the example this is the output on the Safari. Now when user would click on any of the job it will open the details and for the details I am just passing single record job ID which is coming from model from the link and passing that here in the details HPS file template file I am just presenting the contents. So that's pretty straightforward. Now let's move to the next step. Now let's create a progressive web app. To create a progressive web app we need couple of the add-ons to be installed. Number one is to make web app we need Ember web app component. Oh sorry pardon me Ember web app add-on because every progressive web app requires a manifest file which tells the browser how to deal with that. After that we are going to install Ember service worker which will take your application offline and there are bunch of add-ons for that. Ember service worker is the basic one to make offline. You need to install these one the index one just caches your the index file and gs file asset cache with cache the images folder the asset folder in the public path and the cache fallback will put cache your external URLs. I'll show you how. So in Ember CLI build we are going to add some configuration. Number one is the division strategy for the progressive web app. We need that version to be updated every build and for the cache part I'm going to cache the all the requests made to the mock server which I have mentioned here that application doctor and I'm also going to cache this semantic css from the cdm after that in the manifest file that can be found in the config folder. So here I would like my application to be full screen this is the name these are the colors and the icon and that's it. So let me show you a progressive web app just go to pwa.allasmission.com and here app is running click share icon add to home page and it is edit. Okay now if you open that you will see that it is showing all the contents and if I turn off my internet then if I run this application again okay you would see that yeah see content is loaded without the internet okay so this is the progressive web app now coming to the next step for the mobile development for that I have just created a separate branch to just save the time I have already installed different packages which were needed so the corboreio is a codewire app for single page applications to install corbore we just need to install the global package first you can use yarn or not npm package manager and then in your project just type corbore in it and corbore start and it would definitely start the project so let me show you how this is going to work start and you can just reinstall the package because I switch the branches and sometimes this happens that the yarn lock file is different for each one and we need to update and you can see that it is working okay let's run that in our simulator let me open this project next code so we are going to install this as a mobile application and if you already have worked with cordova you know how the process of that you can change the different settings like icon and the permissions and push notifications everything for that all the cordova add-ons like notifications camera access etc would definitely work with corbore as well okay so you can see that this is overrunning as an application and when you hit publish from the xcode you are going to definitely you need to provide the details and you would be able to publish this application on the app store and play store now let's move to the point there are some settings which you can check on the corboreio last part of my presentation is electron to use electron we need to install another add-on and then we can simply run to install electron i'm going to use the beta vision because they are using the latest electron vision which really supported us with the latest features like we need to install thermal printer for a pos module pos application which we have developed in amber and in the older regions that thermal printer was not accessible or giving us some trouble and that's why i would also recommend to you guys to use the beta version and after that just run on the electron and usually we are again i need to run the package here your desktop application is ready which is working now let me make a build a package for that this will create the package compile package for you guys which you can just hit send to your customers put online for downloading and there are other lots of settings like changing the icon adding custom menu items in the electron application for that you should go to the electron website and read the documentation i guess my package is ready here you would see that out folder and okay so my amber application is now ready to be used as an desktop application so that is that's it i would say big thanks to amber team i really enjoyed working with amber and i'm working for the with amber for a long time i would like to thank all of the e-services like amber service worker the amber web app corboraio electron gs and most definitely amber observer because for if i need to find any add-on for amber i would definitely search over here because this is the only best place to find amber okay guys thank you and please enjoy the rest of this dark conference take care bye


NATO playing with fire with latest military exercises. Medvedev, Moscow has no plans to attack any NATO country, something that is clear as day to anyone with an ounce of sense in the West. Russian Security Council Deputy Chairman Dmitry Medvedev wrote on the re-contact social media platform commenting on NATO's steadfast Defender 2024 exercise, the largest since the end of the Cold War. He noted that this was playing with fire in a very dangerous way. We don't plan to attack any of the bloc's members. This is clear to all reasonable people in the West. However, if they get carried away, playing and encroach on our country's integrity, they will immediately receive an appropriate response, Medvedev pointed out. According to him, it will mean one thing, a big war that NATO won't be able to dodge. NATO's steadfast Defender 2024 exercise is being held in Europe from February to May. 31 member states and NATO hopeful Sweden are taking part in the drills, the bloc's special representative for the Caucasus and Central Asia Javier Kolomina said in an interview with the Armin Press news agency that the drills are aimed at deterring Russia, which the alliance views as a threat.