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72-506: Early examples of mobile vehicle emissions equipment were developed and marketed in the early 1990s by Warren Spring Laboratory UK during the early 1990s, which was used to measure on-road emissions as part of the UK Environment Research Program. Governmental agencies like United States Environmental Protection Agency (USEPA) and various states and private entities have begun to use PEMS in order to reduce both

144-434: A casino may lose money in a single spin of the roulette wheel, its earnings will tend towards a predictable percentage over a large number of spins. Any winning streak by a player will eventually be overcome by the parameters of the game. Importantly, the law applies (as the name indicates) only when a large number of observations are considered. There is no principle that a small number of observations will coincide with

216-436: A broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The larger the number of repetitions, the better the approximation tends to be. The reason that this method is important is mainly that, sometimes, it is difficult or impossible to use other approaches. The average of the results obtained from a large number of trials may fail to converge in some cases. For instance,

288-567: A collection of independent and identically distributed (iid) samples from a random variable with finite mean, the sample mean converges in probability to the expected value That is, for any positive number ε , lim n → ∞ Pr ( | X ¯ n − μ | < ε ) = 1. {\displaystyle \lim _{n\to \infty }\Pr \!\left(\,|{\overline {X}}_{n}-\mu |<\varepsilon \,\right)=1.} Interpreting this result,

360-519: A conformity factor of 2.1 (1.5 after 2019), i.e. the emissions measured by the PEMS are allowed to be a factor 2.1 higher than the limit. It is expected that a variety of on-board systems will be designed, ranging from bread-box sized PEMS to instrumented trailers towed behind the tested truck. The benefits of each approach need to be considered in light of other sources of errors associated with emissions monitoring, notably vehicle-to-vehicle differences, and

432-560: A convergence of results, it means that repeatability, predictability, and accuracy are enhanced, while simultaneously reducing the overall cost of the testing. Nearly all modern engines, when tested new and according to the accepted testing protocols in a laboratory, produce relatively low emissions well within the set standards. As all individual engines of the same series are supposed to be identical, only one or several engines of each series get tested. The tests have shown that: These findings are consistent with published literature, and with

504-399: A lack of competitive tendering, arguing that the plan was essentially motivated by the government's wider privatisation agenda, while Chris Smith MP called the plan "merely a fattening-up exercise for privatising AEA, which was not a particularly sellable proposition on its own". In response, for the government, David Davis MP countered that the merger would "over the next five years, save

576-474: A non-1065 PEMS was used to establish the difference between car and motorcycle pollution. Overview of integrated PEMS (iPEMS) development In response to Dieselgate , the " Real Driving Emissions " (RDE) standard has been developed in the European Union (EU) which has, in turn, increased the demand for smaller, lighter, more portable, less expensive and integrated PEMS equipment kits. iPEMS equipment

648-451: A random variable that does not have a finite variance under some other weaker assumption, and Khinchin showed in 1929 that if the series consists of independent identically distributed random variables, it suffices that the expected value exists for the weak law of large numbers to be true. These further studies have given rise to two prominent forms of the LLN. One is called the "weak" law and

720-409: A safety hazard. Emissions data is subject to considerable variances, as real-world conditions are often neither well defined nor repeatable, and significant variances in emissions can exist even among otherwise identical engines. On-road emissions testing therefore requires a different mindset than the traditional approach of testing in the laboratory and using models to predict real-world performance. In

792-929: Is known as Kolmogorov's strong law , see e.g. Sen & Singer (1993 , Theorem 2.3.10). The weak law states that for a specified large n , the average X ¯ n {\displaystyle {\overline {X}}_{n}} is likely to be near μ . Thus, it leaves open the possibility that | X ¯ n − μ | > ε {\displaystyle |{\overline {X}}_{n}-\mu |>\varepsilon } happens an infinite number of times, although at infrequent intervals. (Not necessarily | X ¯ n − μ | ≠ 0 {\displaystyle |{\overline {X}}_{n}-\mu |\neq 0} for all n ). The strong law shows that this almost surely will not occur. It does not imply that with probability 1, we have that for any ε > 0

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864-457: Is not presently able to be used as a "certification" device in the U.S. Definition of iPEMS The following features are common to the smaller and lighter class of iPEMS equipment: Advantages of iPEMS over 1065 PEMS equipment The advantage of iPEMS equipment is that they are designed to both complement 1065 PEMS in addition to providing expanded capabilities, which are being driven by the requirements for quicker decision-making compounded by

936-488: Is often difficult for PEMS to offer the same accuracy and variety of species measured as is possible with top-of-the-line laboratory instrumentation because PEMS are typically limited in size, weight and power consumption. For this reason, objections were raised against using PEMS for compliance verification. But there is also the potential for inaccuracy in fleet emissions deduced from laboratory measurements. For this reason, European WLTP results from PEMS will be weighted with

1008-418: Is that the probability that, as the number of trials n goes to infinity, the average of the observations converges to the expected value, is equal to one. The modern proof of the strong law is more complex than that of the weak law, and relies on passing to an appropriate subsequence. The strong law of large numbers can itself be seen as a special case of the pointwise ergodic theorem . This view justifies

1080-446: Is where the random numbers equal the tangent of an angle uniformly distributed between −90° and +90°. The median is zero, but the expected value does not exist, and indeed the average of n such variables have the same distribution as one such variable. It does not converge in probability toward zero (or any other value) as n goes to infinity. And if the trials embed a selection bias , typical in human economic/rational behaviour,

1152-416: The average of the results obtained from a large number of independent random samples converges to the true value, if it exists. More formally, the LLN states that given a sample of independent and identically distributed values, the sample mean converges to the true mean . The LLN is important because it guarantees stable long-term results for the averages of some random events . For example, while

1224-828: The 2015 Volkswagen scandal. These devices are presently being pursued by both the European Union (EU) and China for their RDE Programs. Warren Spring Laboratory Warren Spring Laboratory was a UK government environmental science research centre that operated in Stevenage , Hertfordshire from 1958 until its closure in 1994. Described by New Scientist as "Britain's leading laboratory for environmental research", and by The Times as "one of Europe's most important environmental research centres", it had an international reputation in areas such as air and water pollution , waste management and recycling , land remediation , alternative fuel research, and chemical engineering . In 1994, after some political controversy,

1296-467: The LLN is used in many fields including statistics, probability theory, economics, and insurance. For example, a single roll of a fair, six-sided die produces one of the numbers 1, 2, 3, 4, 5, or 6, each with equal probability . Therefore, the expected value of the average of the rolls is: 1 + 2 + 3 + 4 + 5 + 6 6 = 3.5 {\displaystyle {\frac {1+2+3+4+5+6}{6}}=3.5} According to

1368-698: The Ministry of Technology in 1965, it was run by the Department of Trade and Industry (and its various successors) until 1994. In the early 1990s, Michael Heseltine , the UK government's President of the Board of Trade , announced that Warren Spring Laboratory would move to new premises in nearby Welwyn Garden City . Later, however, following a report from the PA Consulting Group , Heseltine scrapped

1440-697: The New York State Department of Environmental Conservation, as a short-hand description of the new device. Other governmental groups and universities soon followed, and quickly began to use the equipment due to its balance of accuracy, low cost, light weight, and availability. From 1999 through 2004, research groups such as Virginia Tech, Penn State, and Texas A&M Transportation Institute, Texas Southern University and others began to use PEMS in border crossing projects, roadway evaluations, traffic control methods, before-and-after scenarios, and ferries, planes, and off-road vehicles, to explore what

1512-451: The PEMS manufacturers to practically demonstrate how these non-compliant vehicles can be identified using their system. In order to achieve the required amount of 'testing volume' needed to validate real-world testing, three points must be considered: Once a particular portable emissions system has been identified and pronounced as accurate, the next step is to ensure that the worker(s) are properly protected from work hazards associated with

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1584-528: The President of the Board of Trade now intends to go back on the agreement reached in 1992 to relocate Warren Spring Laboratory and instead to close it with the loss of 150 jobs and scientific expertise built up over many years; and calls on the President of the Board of Trade to save Warren Spring Laboratory from closure". Later, opposition MP Michael Meacher highlighted what he saw as conflicts of interest and

1656-637: The USEPA and the United Nations Framework Convention on Climate Change or UNFCCC ) have identified target mobile-source pollutants in various mobile standards as CO 2 , NO x , Particulate Matter (PM), Carbon Monoxide (CO), Hydrocarbons (HC), to ensure that emissions standards are being met. Further, these governing bodies have begun adopting in-use testing program for non-road diesel engines , as well as other types of internal combustion engines, and are requiring

1728-696: The absence of established methods, use of PEMS requires careful, thoughtful, broad approach. This should be considered when designing, evaluating and selecting PEMS for the desired application. A recent example of PEMS advantages over laboratory testing is the Volkswagen (VW) Scandal of 2015 . Under a small grant from the International Council on Clean Transportation (icct), Daniel K Carder of West Virginia University (WVU) uncovered on-board software "cheats" that VW had installed on some diesel passenger vehicles ( Dieselgate scandal). The only way

1800-496: The account. The ability of the test crew to repair PEMS in the field using locally available resources can also be essential. Ultimately, it should be demonstrated to show that a PEMS is suitable to the desired application. If the ultimate goal is to verify the compliance with in-use emissions requirements, a fleet of vehicles with known characteristics – including engines with dual-mapping and otherwise non-compliant engines – should be made available for testing. It should be then up to

1872-656: The average of n results taken from the Cauchy distribution or some Pareto distributions (α<1) will not converge as n becomes larger; the reason is heavy tails . The Cauchy distribution and the Pareto distribution represent two cases: the Cauchy distribution does not have an expectation, whereas the expectation of the Pareto distribution ( α <1) is infinite. One way to generate the Cauchy-distributed example

1944-437: The average of a set of normally distributed variables). The variance of the sum is equal to the sum of the variances, which is asymptotic to n 2 / log ⁡ n {\displaystyle n^{2}/\log n} . The variance of the average is therefore asymptotic to 1 / log ⁡ n {\displaystyle 1/\log n} and goes to zero. There are also examples of

2016-434: The average of the first n values goes to zero as n goes to infinity. As an example, assume that each random variable in the series follows a Gaussian distribution (normal distribution) with mean zero, but with variance equal to 2 n / log ⁡ ( n + 1 ) {\displaystyle 2n/\log(n+1)} , which is not bounded. At each stage, the average will be normally distributed (as

2088-664: The average to converge almost surely on something (this can be considered another statement of the strong law), it is necessary that they have an expected value (and then of course the average will converge almost surely on that). If the summands are independent but not identically distributed, then provided that each X k has a finite second moment and ∑ k = 1 ∞ 1 k 2 Var ⁡ [ X k ] < ∞ . {\displaystyle \sum _{k=1}^{\infty }{\frac {1}{k^{2}}}\operatorname {Var} [X_{k}]<\infty .} This statement

2160-512: The case where X 1 , X 2 , ... is an infinite sequence of independent and identically distributed (i.i.d.) Lebesgue integrable random variables with expected value E( X 1 ) = E( X 2 ) = ... = μ , both versions of the law state that the sample average X ¯ n = 1 n ( X 1 + ⋯ + X n ) {\displaystyle {\overline {X}}_{n}={\frac {1}{n}}(X_{1}+\cdots +X_{n})} converges to

2232-414: The convergence is only weak (in probability). See differences between the weak law and the strong law . The strong law applies to independent identically distributed random variables having an expected value (like the weak law). This was proved by Kolmogorov in 1930. It can also apply in other cases. Kolmogorov also showed, in 1933, that if the variables are independent and identically distributed, then for

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2304-896: The costs and time involved in making mobile emissions decisions. The European Commission introduced PEMS as a mandatory requirement for light-duty vehicle type approval in 2016 by amending the regulation that was established in 2007. Leo Breton of the US EPA invented the Real-time On-road Vehicle Emissions Reporter (ROVER) in 1995. The first commercially available device was invented by Michal Vojtisek-Lom, and developed by David Miller of Clean Air Technologies International (CATI) Inc. in Buffalo, New York in 1999. These early field devices used engine data from either an on-board diagnostics (OBD) port, or directly from an engine sensor array . The first unit

2376-754: The data from a myriad of subsequent studies. They are more applicable to spark-ignition engines and considerably less to diesels, but with the regulation-driven advances in diesel engine technology (comparable to the advances in spark-ignition engines since the 1970s) it can be expected that these findings are likely to be applicable to the new generation diesel engines. Since 2000, multiple entities have used PEMS data to measured in-use, on-road emissions on hundreds of diesel engines installed in school buses, transit buses, delivery trucks, plow trucks, over-the-road trucks, pickups, vans, forklifts, excavators, generators, loaders, compressors, locomotives, passenger ferries, and other on-road, off-road and non-road applications . All

2448-406: The discovery could have been made was by a non-programmed, random, on-road evaluation - utilizing a PEMS device. VW is now liable for over US$ 14 billion in fines. In 2016, these latest developments led to a global resurgence of interest in smaller, lighter, integrated and cost-effective "non-1065" PEMS, similar to the demonstration on MythBusters 2011 Episode 171 of "Bikes and Bazookas", in which

2520-440: The early 1960s, the divisions were Atmospheric Pollution; Chemical Engineering and Process Development; Engineering Services and Human Sciences; Extraction of Metals; Mineral Processing; and Physical and Chemical Services. In the early 1990s, the six divisions were: Air Pollution; Pollution Abatement; Materials Recovery; Biological Treatment; Marine Pollution and Bulk Materials; and Chemical Analysis. The air pollution division

2592-484: The emissions variability within the vehicle itself. PEMS need to be safe enough to use on public roads. During testing, portable emissions systems could attach extensions of the tailpipe, add lines and cables outside the vehicle, carry lead-acid batteries in the passenger compartment, have hot components accessible to bystanders, block emergency exits, interfere with the driver, or have loose components that could be caught in moving parts. Modifications to or disassembly of

2664-493: The equipment requires, the greater the cost of testing, limiting the number of vehicles that can be tested. More testing is also possible with equipment that is versatile enough to be used on more than one type of vehicle. The weight and size of the equipment and consumables like calibration gases might limit moving to a sufficient number locations. Any restrictions on transport of hazardous materials (i.e. Flame ionization detector (FID) fuel or calibration gases) need to be taken into

2736-409: The expected value is the theoretical probability of success, and the average of n such variables (assuming they are independent and identically distributed (i.i.d.) ) is precisely the relative frequency. For example, a fair coin toss is a Bernoulli trial. When a fair coin is flipped once, the theoretical probability that the outcome will be heads is equal to 1 ⁄ 2 . Therefore, according to

2808-456: The expected value or that a streak of one value will immediately be "balanced" by the others (see the gambler's fallacy ). The LLN only applies to the average of the results obtained from repeated trials and claims that this average converges to the expected value; it does not claim that the sum of n results gets close to the expected value times n as n increases. Throughout its history, many mathematicians have refined this law. Today,

2880-639: The expected value: (Lebesgue integrability of X j means that the expected value E( X j ) exists according to Lebesgue integration and is finite. It does not mean that the associated probability measure is absolutely continuous with respect to Lebesgue measure .) Introductory probability texts often additionally assume identical finite variance Var ⁡ ( X i ) = σ 2 {\displaystyle \operatorname {Var} (X_{i})=\sigma ^{2}} (for all i {\displaystyle i} ) and no correlation between random variables. In that case,

2952-415: The inequality | X ¯ n − μ | < ε {\displaystyle |{\overline {X}}_{n}-\mu |<\varepsilon } holds for all large enough n , since the convergence is not necessarily uniform on the set where it holds. The strong law does not hold in the following cases, but the weak law does. There are extensions of

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3024-411: The intuitive interpretation of the expected value (for Lebesgue integration only) of a random variable when sampled repeatedly as the "long-term average". Law 3 is called the strong law because random variables which converge strongly (almost surely) are guaranteed to converge weakly (in probability). However the weak law is known to hold in certain conditions where the strong law does not hold and then

3096-508: The laboratory was closed and merged with AEA Technology to form the National Environmental Technology Centre (NETCEN). Broadly, Warren Spring's mission was to monitor and reduce environmental pollution and land contamination, to optimize the use of materials, and to recover useful materials, such as precious metals, from waste. It was organized in separate divisions, which changed over the years. In

3168-407: The law of large numbers does not help in solving the bias. Even if the number of trials is increased the selection bias remains. The Italian mathematician Gerolamo Cardano (1501–1576) stated without proof that the accuracies of empirical statistics tend to improve with the number of trials. This was then formalized as a law of large numbers. A special form of the LLN (for a binary random variable)

3240-411: The law of large numbers to collections of estimators, where the convergence is uniform over the collection; thus the name uniform law of large numbers . Suppose f ( x , θ ) is some function defined for θ ∈ Θ, and continuous in θ . Then for any fixed θ , the sequence { f ( X 1 , θ ), f ( X 2 , θ ), ...} will be a sequence of independent and identically distributed random variables, such that

3312-414: The law of large numbers, if a large number of six-sided dice are rolled, the average of their values (sometimes called the sample mean ) will approach 3.5, with the precision increasing as more dice are rolled. It follows from the law of large numbers that the empirical probability of success in a series of Bernoulli trials will converge to the theoretical probability. For a Bernoulli random variable ,

3384-426: The law of large numbers, the proportion of heads in a "large" number of coin flips "should be" roughly 1 ⁄ 2 . In particular, the proportion of heads after n flips will almost surely converge to 1 ⁄ 2 as n approaches infinity. Although the proportion of heads (and tails) approaches 1 ⁄ 2 , almost surely the absolute difference in the number of heads and tails will become large as

3456-417: The name "la loi des grands nombres" ("the law of large numbers"). Thereafter, it was known under both names, but the "law of large numbers" is most frequently used. After Bernoulli and Poisson published their efforts, other mathematicians also contributed to refinement of the law, including Chebyshev , Markov , Borel , Cantelli , Kolmogorov and Khinchin . Markov showed that the law can apply to

3528-589: The nation and which cannot be fitted into the programme of another research body". For example, in 1960, Warren Spring Laboratory was tasked with "deciding the best ways to deal with oil pollution of the foreshores of coastal resorts" (a mission later extended to include "the treatment and disposal of floating oil at sea"). The laboratory was originally conceived as a replacement for the DSIR Fuel Research Station in Greenwich . However, it

3600-491: The number of flips becomes large. That is, the probability that the absolute difference is a small number approaches zero as the number of flips becomes large. Also, almost surely the ratio of the absolute difference to the number of flips will approach zero. Intuitively, the expected difference grows, but at a slower rate than the number of flips. Another good example of the LLN is the Monte Carlo method . These methods are

3672-399: The other the "strong" law, in reference to two different modes of convergence of the cumulative sample means to the expected value; in particular, as explained below, the strong form implies the weak. There are two different versions of the law of large numbers that are described below. They are called the strong law of large numbers and the weak law of large numbers . Stated for

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3744-596: The plan and announced that the laboratory would merge with the Atomic Energy Authority (AEA) and transfer to Harwell , Oxfordshire instead. This prompted considerable public opposition – and many of the Warren Spring staff simply refused to move, including most of its air pollution scientists . There was political opposition too. In May 1993, an Early Day Motion supported by 89 mostly opposition (Labour) MPs noted "with concern reports that

3816-912: The previously listed findings were demonstrated; in addition, it was noticed that extended idling of engines can have a significant impact on the emissions during subsequent operation. Also, PEMS testing identified several engine "anomalies" where fuel-specific NOx emissions were two to three times higher than expected during some modes of operation, suggesting deliberate alterations of the engine control unit (ECU) settings. Such data set can be readily used for developing emissions inventories, as well as to evaluate various improvements in engines, fuels, exhaust after-treatment and other areas. (Data collected on "conventional" fleets then serves as "baseline" data to which various improvements are compared.) This data set can also be examined for compliance with not-to-exceed (NTE) and in-use emissions standards , which are 'US-based' emission standards that require on-road testing. It

3888-573: The proofs. This assumption of finite variance is not necessary . Large or infinite variance will make the convergence slower, but the LLN holds anyway. Mutual independence of the random variables can be replaced by pairwise independence or exchangeability in both versions of the law. The difference between the strong and the weak version is concerned with the mode of convergence being asserted. For interpretation of these modes, see Convergence of random variables . The weak law of large numbers (also called Khinchin 's law) states that given

3960-409: The required emissions testing projects are economically viable. Simply put, more testing can be done more quickly, by less workers, dramatically increasing the amount of testing done in a certain time period. This in turn, significantly reduces the 'cost per test', yet at the same time increases the overall accuracy required in a 'real-world' environment. Because the law of large numbers will create

4032-857: The sample mean of this sequence converges in probability to E[ f ( X , θ )]. This is the pointwise (in θ ) convergence. A particular example of a uniform law of large numbers states the conditions under which the convergence happens uniformly in θ . If Then E[ f ( X , θ )] is continuous in θ , and sup θ ∈ Θ ‖ 1 n ∑ i = 1 n f ( X i , θ ) − E ⁡ [ f ( X , θ ) ] ‖ → P   0. {\displaystyle \sup _{\theta \in \Theta }\left\|{\frac {1}{n}}\sum _{i=1}^{n}f(X_{i},\theta )-\operatorname {E} [f(X,\theta )]\right\|{\overset {\mathrm {P} }{\rightarrow }}\ 0.} This result

4104-412: The series, keeping the expected value constant. If the variances are bounded, then the law applies, as shown by Chebyshev as early as 1867. (If the expected values change during the series, then we can simply apply the law to the average deviation from the respective expected values. The law then states that this converges in probability to zero.) In fact, Chebyshev's proof works so long as the variance of

4176-406: The task(s) being performed in the use of the testing equipment. For example, typical functions for a worker may be to transport the equipment to the jobsite (i.e. car, truck, train, or plane), carry the equipment to the jobsite, and lift the equipment into position. On-road vehicle emissions testing is very different from the laboratory testing, bringing both considerable benefits and challenges: As

4248-421: The taxpayer perhaps £32 million", though the eventual saving was just £8 million. The site of Warren Spring Laboratory, at Gunnels Wood Road, Stevenage, was sold to Glaxo , the pharmaceuticals company, for £25 million, and subsequently became a research and development laboratory. Law of large numbers In probability theory , the law of large numbers ( LLN ) is a mathematical law that states that

4320-488: The tested vehicle such as drilling into the exhaust or removing intake air system need to be examined for their acceptance by both fleet managers and drivers, especially on passenger-carrying vehicles. The test equipment can not draw excessive electrical load from the test vehicle. Instead, sealed lead-acid batteries, fuel cells and generators have been used as external power sources, though they may add other hazards during driving. The more time and expertise installation of

4392-437: The testing can take place during the regular operation of the tested vehicles, a large number of vehicles can be tested within a relatively short period of time and at relatively low cost. Engines than cannot be easily tested otherwise (i.e., ferry boat propulsion engines) can be tested. True real-world emissions data can be obtained. The instruments have to be small, lightweight, withstand difficult environment, and must not pose

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4464-399: The use of PEMS testing. It is important to delineate the various classifications of the latest 'transferable' emissions testing equipment from-time PEMS equipment, in order to best understand the desire of portability in field-testing of emissions. Because a PEMS unit is able to be carried easily by one person from jobsite to jobsite, and can be used without the requirement of 'team lifting',

4536-789: The variance of the average of n random variables is Var ⁡ ( X ¯ n ) = Var ⁡ ( 1 n ( X 1 + ⋯ + X n ) ) = 1 n 2 Var ⁡ ( X 1 + ⋯ + X n ) = n σ 2 n 2 = σ 2 n . {\displaystyle \operatorname {Var} ({\overline {X}}_{n})=\operatorname {Var} ({\tfrac {1}{n}}(X_{1}+\cdots +X_{n}))={\frac {1}{n^{2}}}\operatorname {Var} (X_{1}+\cdots +X_{n})={\frac {n\sigma ^{2}}{n^{2}}}={\frac {\sigma ^{2}}{n}}.} which can be used to shorten and simplify

4608-494: The weak law applying even though the expected value does not exist. The strong law of large numbers (also called Kolmogorov 's law) states that the sample average converges almost surely to the expected value That is, Pr ( lim n → ∞ X ¯ n = μ ) = 1. {\displaystyle \Pr \!\left(\lim _{n\to \infty }{\overline {X}}_{n}=\mu \right)=1.} What this means

4680-455: The weak law states that for any nonzero margin specified ( ε ), no matter how small, with a sufficiently large sample there will be a very high probability that the average of the observations will be close to the expected value; that is, within the margin. As mentioned earlier, the weak law applies in the case of i.i.d. random variables, but it also applies in some other cases. For example, the variance may be different for each random variable in

4752-717: Was completed on schedule and met all the complex technical requirements". Its first director was S.H. Clarke, previously director of fire research at the Department of Scientific and Industrial Research. The laboratory initially consisted of six main buildings (the principal, 113-meter-long three-storey laboratory, a three-story administration block built at right angles to it; and three smaller laboratories), plus assorted workshops and engineering stores. The main buildings were constructed from lightweight, easily movable partition walls that were designed to be "as flexible as possible in interior layout". After transferring from DSIR to

4824-567: Was deliberately given a much less specific name, based on the area in Stevenage where it was built, to reflect a wider brief than simply researching fuel. Warren Spring was planned by the Fuel Research Station's chief development officer, David Penny, who became the project's consulting engineer. According to The Herald , "despite a rather vague and constantly changing specification, the Warren Spring laboratory at Stevenage

4896-514: Was developed for, and sold to - Dr. H. Christopher Frey of North Carolina State University (NCSU) for the first on-road testing project, which was sponsored by the North Carolina Department of Transportation. David W. Miller, who co-founded CATI, first coined the phrase "Portable Emissions Measurement System" and "PEMS" when working on a 2000 New York City Metropolitan Transportation Agency bus project with Dr. Thomas Lanni of

4968-467: Was first proved by Jacob Bernoulli . It took him over 20 years to develop a sufficiently rigorous mathematical proof which was published in his Ars Conjectandi ( The Art of Conjecturing ) in 1713. He named this his "Golden Theorem" but it became generally known as " Bernoulli's theorem ". This should not be confused with Bernoulli's principle , named after Jacob Bernoulli's nephew Daniel Bernoulli . In 1837, S. D. Poisson further described it under

5040-530: Was headed by Sean Craxford and, later, Martin Williams . Initially, its work included tackling the problem of smog , which had contributed to around 12,000 deaths during the 1952 Great Smog of London . According to a 1958 article in Nature , the Department of Scientific and Industrial Research (DSIR) wanted Warren Spring "to be a versatile station, free to do work on any subject which becomes important for

5112-840: Was possible outside of a lab environment. A project performed in April 2002 by the California Air Resources Board (CARB) - using non-1065 PEMS equipment, tested 40 trucks over a period of 2½ days; of which, 22 trucks were tested on road in Tulare, California. During this time, a high-profile project performed with early PEMS equipment was the World Trade Center (WTC) Ground Zero Project in lower Manhattan, testing concrete pumpers, bulldozers, graders, and later - diesel cranes on Building #7 - 40 stories high. Other early PEMS projects such as Dr. Chris Frey's field work

5184-576: Was used by the USEPA in the development of the MOVES Model. However, users such as regulators and vehicle manufacturers had to wait for ROVER to be commercialized to conduct actual measurements of mass emissions rather than depend on estimates of mass emissions using data the OBD port, or a direct engine measurement, in order to have a more defensible data set. This push led to a new 2005 standard known as CFR 40 Part 1065. Many governmental entities (such as

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