Answers

The answers :
Q1 : 2 1 0
Q2 : 2 0 0
Q3 : 0 0 2
Q4 : 2 0 0
Q5 : 2 1 1
Q6 : 1 2 2
Q7 : 0 1 2
Q8 : 2 0 0
Q9 : 2 1 2
Q10 : 2 0 0
Q11 : 2 0 1
Q12 : 2 0 1
Q13 : 2 0 0
Q14 : 2 0 0
Q15 : 0 2 1
Q16 : 1 0 1
Q17 : 1 0 1
Q18 : 2 0 0
Q19 : 1 0 2
Q20 : 0 1 1
Q21 : 2 0 0
Q22 : 2 0 2
Q23 : 2 1 0
Q24 : 2 0 1


Source: Ollivier, Daniel et Catherine Tanguy:Génération Y; mode d'emploi, De Boeck, Bruxelles, 2008.

Workplace generations

DO YOU BELIEVE YOUNG WORKERS (born1985) [ARE MORE LIKELY TO BE] : (True, False, Neither)

1- INDIVIDUALISTIC
2- LACKING IN RESPECT FOR HIERARCHY
3- LESS INVOLVED IN THEIR WORK
4- MORE SELF-CENTERED
5- LESS INTERESTED IN COLLECTIVE VALUES
6- MORE AUTONOMOUS
7- HAVE A TENDENCY TOWARD THE EASY WAY
8- WANT EVERYTHING, RIGHT AWAY
9- DO NOT FORGIVE THEMSELVES FOR MISTAKES AT WORK
10- WORK-PLACE ZAPPERS
11- DO NOT RESPECT THE RULES
12- BELIEVE WE OWE THEM EVERYTHING, WITHOUT HAVING TO PROVE THEMSELVES
13- ARE MORE OPEN-MINDED
14- ARE MORE OPEN TO OTHER CULTURES
15- HAVE LOST FAMILY VALUES
16- WILL CHANGE JOBS FOR A BIT MORE MONEY
17- LACK PROFESSIONAL AMBITION
18- ARE NOT AFRAID OF THE FUTURE
19- ARE LESS IDEALISTIC THAN PREVIOUS GENERATIONS
20- LIVE IN SOLITUDE
21- ARE AFRAID OF NO ONE
22-LEARN MORE QUICKLY THAN PREVIOUS GENERATIONS
23-ATTATCH MORE IMPORTANCE TO THE EXTRA-PROFESSIONAL
24-ARE MORE RISK-TAKERS THAN PREVIOUS GENERATIONS

Bavaria

Generator

Waves

http://www.phy.hk/wiki/englishhtm/TwaveStatA.htm

Mad

Algorithms

The Copen Head- Scratch

http://www.spiegel.de/international/world/0,1518,665703,00.html

I Like

Electricity

Electricity was known in Antiquity, and associated with amber. During modernity, it came to be appreciated not only in its static form, but in its dynamic aspects. The English scientific advisor to Elizabeth 1, Gilbert, argued that the earth itselt was electrified. Du Fay noticided that there were two forms, amber and glass electrification, each repellent to self but attractive to the other form. And so on...until Benjamin Franklin, in the XIXth century, stated there was but one form but with negative and positive elements.

Today, atomic theory is well-established, even a bit anachronistic. The LHD is looking for particles that existed shortly after the Big Bang, the elusive particle that gives mass to elementary particles.

Electricity itself is a well-harnessed force that brings comfort and convenience to everyday life. The basic concept used to describe it is voltage, the difference in charge between each 'end' of an electrical circuit. Resistance is a factor, measured in ohms, while current intensity is measured in amperes, which are coulombs per second. There are 6,24 x 10^18 electrons in a coulomb. Thus, U = RxI.

If the resistors follow each other in a serial fashion, one ads the value of each to find the total resistance of the circuit. Amperage remains the same throughout, but voltage will decompose at each resistor. If resistors are distributed in a parallel fashion, it is as if there were many concurent circuits. Resistance equivalence is the sum of the individual resistors, that sum itself inverted. In effect, amperage will be different at each resistor, and the sum of the amperages will match the formula amperage equivalent.

For voltage=15 volts and two resistors, 2, and 3 ohms respectively:

CHINA

Lionel Crouson from Les Cahiers Science et Vie

The Emperor’s New Ideas
An immense empire, a dispersed population made up of different people, a multitude of languages…Qin, the first emperor, nonetheless succeeds in unifying the country, developing and diffusing an exceptional array of knowledge.

Having survived a sinking ship off the coast of China in 1541, merchant Fernao Mendes Pinto is picked up for loitering, then condemned and sent to Peking to be judged on appeal. From the barge where he is held in chains on the Yang-Tse river, the unfortunate Portuguese observes with attention a brilliant Chinese civilization. Impressed, he writes with enthusiasm »cleanliness and climatic moderation […]¸the police, wealth, manners, clothing, the grandeurs of all one sees », and then adding « to add shine to all that, one finds a fine observation of justice, a government equal and so excellent, that any country could well envy ».(1)

Is Pinto then curious as to how China has managed to attain such a high degree of civilization?

To understand, one needs to go back 3000 years when, on the borders of the Central Plain, emerges an agricultural people who excel in the art of Bronze work. These men, and others more to the South, are the ancestors to the Chinese. They have left written records of which the most ancient date back to the XIVth century before our era. Dating back at least 3400 years, Chinese civilization was thus contemporary to Babylon, pharaonic Egypt, ancient Greece and then Rome. Yet the birth of Empire only goes back to -221, when Qin Shi Huangdi, known to us for his army of Terracotta soldiers, became the first emperor of China. Quickly, a scafolding of measures puts in place a centralized and authorian administration. Which will survive throughout all of Chinese history. How, from this period, did the idea come to Emperor Qin?

The answer could well be the sheer scope of his territory, deprived of any true geographical borders and whose dispersed peoples, whether Barbarian or not, speak a multitude of languages. How to transmit orders and have imperial edicts obeyed? The sovereign has a handy tool : Chinese writing, inherited from his ancestors which, by the use of non-alphabetical structures, coïncides perfectly with most of the languages of the territory. The emperor thus rests his power on large codes of written law which are strictly applied in all corners of China, thanks to civil servants. Soon the economy is run by the state, with the sapèque as sole currency, while all weights and measures are unified over the empire ( a unification which will need wait for the XIXth century in France).

The ourstanding moments of the reign of Qin Shi Huangdi are described with great precision in the Historical Memoirs of Sema Qian, written in the first century before our era. For very soon , the Chinese developed a pre-occupation with dates, the only solid reference point in their ever-changing society where peoples unify, divide, and are united again, on a territory with uncertain borders. This pre-occupation with detail comes to the fore in the year 2, with a great census of population carried out by the Han dynasty, which will serve to name the dominant ethnic group the Han. In order to manage this great project, the administrators needed to master a certain level of knowledge. “It is no chance happening that a mathematical work of high quality such as the Nine Chapters on Mathematical Procedures came forth during the Han period when the bureaucratic system was being established”(2) explains Kiyosi Yabuuti, former professor at Kyoto University.

According to figures of the period, the empire measured 7 million square kilometres, thus more than twelve times the surface of France today. Counted were 12 233 062 families for 59 594 978 subjects, thus close to 60 million inhabitants. (3) In year 2 China accounted for one quarter, even one third, of world population! This demographic weight is close to that which the Roman Empire will attain at its height. Then, if the Chinese are so numerous, what do we know of their habitat?

It answers to strict architectural norms, based on the rank and status of the inhabitant. The houses in vibrant colours have a symmetrical structure and are of non-lasting materials, such as wood or raw earth. This is why China today conserves few truly ancient monuments, compared to the solid heritage of stone of the Roman Empire. Its inheritance lies largely in know-how, scrupulously transmitted from one generation to the next through written treatises which guarantee keeping unchanged traditions.

“The most ancient and the most precise document we have on Chinese architecture dates from the Song dynasty. It is a treatise admirably illustrated and printed in 1103, the Yingzao fashi, credited to Li Jie, himself architect and builder of temples and official buildings in Kaifeng”(4) tells us Jacques Gernet, professor at the Collège de France. Yet, regardless of how fleeting the buildings in large cities, these are always in a grid perfectly oriented to the four cardinal points.

Are these megalopolii? For the period, yes. In the VIIIth century, Chang’an, today Ki’an, is, with 2 million inhabitants, the most populous city on earth. This cosmopolitan capital has large rectilinear avenues, vast temples, and majestic palaces. The beauty and prestige of this city are such that Japan decides to take it for model in putting up its own capital, Heijô-kyô, today Nara. In effect, China has always been an important trader for material and technical goods. There are many examples, with South-East Asia, Central Asia, Iran, the steppes of the North and even the Mediterranean world.”, explains Viviane Alleton, research associate at the École des hautes études en sciences sociales, adding that these were brief periods of closure – but rarely total.

China then is not the large monolithic and closed country sometimes portrayed. It is true that the Empire of the Middle thinks of itself as a dominant center surrounded by Barbarians but so do other societies. Thus the practice of protecting itself on the North and West, while exporting its culture toward Korea, Vietnam and Japan. Remains a priority to assimilate or come to terms with the non-Hans on its territory and boot Barbarians from its frontiers.


Thus, the Chinese people are assembled around values and usages still prevalent today. Among these a moral stance, qualified as ‘confucian’, which accords great importance to family ties. These values are inculcated to the population by senior civil servants recruited through examination. A mode of recruitement not seen in Europe until the XIXth century.

So, is Confucianism a religion? Not as understood in the West. Indeed, there is not until the early XIXth century a Chinese term for religion. Confucianism is a humanist spiritual current emanating from the work of Kongfuzi (Confucius). It spread staring in the VIth century of our era. It touches social relations, strengthens hierarchy and codifies behaviour. A state doctrine in the first century, it remains so until the beginnings of the XXth century, marking Chinese society. It coexists with taoïsm, with celestial gods and divine emperors. This other spiritual stance is tied to nature, with lifestyle (hygiene) and meditation. Starting in the first century, to these two practices were added Buddhism, from India, with an emphasis on tolerance, denial, compassion and thus creating an opening for the hereafter.

Confucianism, taoïsm and Buddhism are all practiced, to various degrees by the Chinese in a non-exclusive fashion, in contrast to the strict adherence required of monotheistic religions. Thus armed with these values, the Chinese are capable of getting through the various crisis of their history. Crisis of which the most serious is a mongol invasion of almost a century, and from which the empire reforms itself once overthrown, in the XIVth century. The Ming dynasty, which follows, will be the most brilliant period of its history.

With 200m million inhabitants, China transforms itself. Maritime exploration begins, while printing – which had been xylographic – moves to mobile characters. Soon democratic distribution of writings gives birth to intellectual emulation and even political debate. The emperor Wanli (1563 – 1620) faces opposition from his own bureaucracy, organized along the lines of parties. However, it is far from his palace that the true struggle will appear. In effect, at this time, Portuguese merchants had landed in Macao. Soon they are joined by Spaniards and the Dutch, in the XVIIIth century. European courts love Chinese ceramics, in particular precious Ming pieces appreciated for tones of cobalt blue. China becomes an exporter of luxury goods, reinforced by commerce in cotton, spices and silks. Shangai then enjoys a standard of living superior to, or at least equivalent to that of England. This flowering is not merely at the level of commerce as Jacques Gernet explains:”The Chinese world has a history intellectual, religious, literary and artistic [...], and in all areas of knowledge, feelings, and thought, there was an accumulation of experiences, this movement of assimilation between old and new, of reinterpretation and evolution which is characteristic of all history [...]. Moral questioning, sociology, historical criticism and that of texts all developed sometimes more precociously than in Europe, so that China found itself, very often, an equal partner to the West when it discovered it”.

Thus in the year 1603 the emperor Wanli decides to admit a Westener to the Forbidden City. He is no conqueror or adventurer. Matteo Ricci is a man of knowledge mandated by Rome as a missionary of the company of Jesus. With great curiosity, Chinese men of knowledge, inheritors of a civilization of the millennia, will confront their knowledge with that of the Jesuits. It is a historical moment. Two great civilizations are about to meet...

Footnotes:
1-In Pérégrination, de Fernao Mendes Pinto, La Différence, 2002.
2-In Une histoire des mathématiques chinoises, de Kiyosi Yabuuti, Belin, 2000.
3- Chiffres cités dans Histoire et institutions de la Chine ancienne, de Henri Maspero, PUF, 1967.
4- In Le Monde chinois, de Jacques Gernet, Pocket Agora, 2006

READINGS :
Jacques Gernet, Le Monde chinois (3 tomes), Pocket Agora, 2006.
Viviane Alleton, L’Écriture chinoise. Albin Michel, 2008.
Kiyosi Yabuuti, Une histoire des mathématiques chinoises. Belin, 2000.
Chine, de Pékin à Hong-Kong. Guides Bleus. Hachette, 2007.

SAMPLE PROBLEMS
---------------------------------------------------------------------
What quantity of electrical energy can a charge of 10 coulombs give if it goes through a resistor at a tension level of 12 volts?
U = 12 q = 10 E = U x q
12 x 10 = 120 joules
---------------------------------------------------------------------

A water-heater of 1 800 watts is on for 10 hours. What does that cost at a usage rate for electricity of 0,08$ per kWxh ?
P = 1 800 watts
= 10 hours
This represents 1 800 x(10) kWxh
@ 0,08$
= 1,44$

------------------------------------------------------------------------

Electrical

I recently undertook the task of helping my favourite teen-ager with her science homework and ended up having to review electricity and the historical development of the major concepts in the area. At one point, I became quite puzzled: everything seemed to be running backwards, with the most fundamental concepts appearing after
the derived: ohm comes after ampère, volt after ohm, and, coming full circle, the newton appearing in dictionnaries in 19 35. This is not an accident; indeed it is the secret to the whole thing. Electricity in the home is not a natural phenomena, but an engineering decision, An electrical line is kept at a definite voltage, defined as the product of current intensity and resistance. Consider an alternative decision - keeping the current into the home constant - regardless of the presence or absence of resistance: the potential for accident is extreme.

The following table gives an overview.

Concept Table

Dico: le Robert.

Electricity(Macbook)

GarageB

Looking Good

Click Me!

The War

Browser Fun

Best Behaviour

Paris Showing

LONGEVITY

http://news.yahoo.com/s/hsn/20091006/hl_hsn/halfofusbabieslivingtodaymayreach100

HAD TO DO IT!

     Original photo from Perez Hilton.

LUUUUUV!

http://www.w3schools.com/

Planning ahead!

Imprey

Niagara Falls

Apple

Probabilities

Protassov, Konstantin Probabilities and Uncertainties in the Analysis of Experimental Data Grenoble Sciences, 2002.

INTRODUCTION

Why do uncertainties exist?

The purpose of the majority of experiments in physics consists in understanding a phenomenon and constructing a correct model of it. We take measurements and often have to ask ourselves the question: “What is the value of this or that magnitude?”, sometimes without first asking ourselves if this formulation is correct and if we will be able to find an answer.

The necessity for this prior questioning becomes evident as soon as one measures the same magnitude many times. The experimenter doing this is frequently confronted with a rather interesting situation: if he uses sufficiently precise instruments, he notices that repeated measurements of the same magnitude sometimes give results that are a bit different from those of the first measurement. This phenomenon is general, be it for simple or sophisticated measurements. Even repeated measurements of a metallic rod can give different measurements. Repeating the experiment shows that, on the one hand, this difference is not in general very large. In most cases, one stays close to a certain average value, but once in a while one finds values that are different from it. The more results are far from this average, the more they are rare.

Why does this dispersion exist? Whence comes this variation? A first reason for this effect is evident: the conditions under which an experiment is conducted always vary slightly, which modifies the magnitude to be measured. For example, where one determines many times the length of a metallic rod, it is the ambient temperature which may vary and thus cause the length to vary. This variation in external circumstances ( and the corresponding variance in the physical values) may be more or less important, but it is inevitable and, in the real circumstances of a physical experiment, one cannot escape it.

We are ‘condemned’ to effect measures of magnitude which are never constant. Which is why the very question of knowing what the value of a parameter is may not be absolutely correct. One must ask this question in a pertinent manner and find adequate means to describe physical magnitudes. One must find a definition which can express this physical particularity. This definition must reflect the fact that a physical value always varies, but that these variations group themselves around an average value.

The solution is to characterize a physical magnitude not by a value, but rather by the probability of finding in an experiment this or that value. For this one introduces a function called distribution of probability of detection of a physical value, or simply the distribution of a physical value which shows which values are the most frequent or the most rare. One must emphasize yet again, in this approach, it is not so much the concrete value of a physical magnitude, but especially the probability of arriving at different values.

One will see later that this function – the distribution of a physical value – is happily sufficiently simple ( in any event, in the majority of experiments). It has two characteristics. The first is the average value which is also the most probable. The second characteristic of this distribution function indicates, grosso modo, the region surrounding this average in which are grouped the majority of the results of the measurements. It characterizes the width of this distribution and is called uncertainty. As we will see later, this width has a rigorous interpretation in terms of probability. For reasons of simplicity, we will call this uncertainty ‘natural uncertainty’ or ‘initial’ of the physical magnitude itself. It is not altogether true, because this error or uncertainty is often due to experimental conditions. Although this definition is not perfectly rigorous, it is very useful for understanding.

The fact that, in most experiments, the result can be characterized by a mere two values, permits one to return to the question with which we began our discussion: “Can one ask what is the value of a physical parameter?” It ensues that in the case where two parameters are necessary and sufficient to characterize a physical magnitude, one can reconcile our desire to ask this question and the region of the interpretation of the results in term s of probabilities. The solution exists: one will call physical value the average value of this distribution and uncertainty or error the physical value of the width of the distribution. It is an accepted convention to say “the physical magnitude has a given value with a given error”. This means we are presenting an average value and the width of a distribution and that this answer has a precise interpretation in terms of probabilities. In this work, we use the terms ‘uncertainty’ and ‘error’ to describe the width of the distribution because, for historical reasons, the two are used in physics.

The aim of physical measures is the determination of this distribution function or, at least, of its two major parameters: the average and the width. To determine a distribution one must repeat a measure many times to find the frequency of appearance of values. The obtain the whole of the possible values as well as their probability of appearance, one should in fact make an infinite number of measurements. It is too long, too expensive, and no one needs it.

One thus limits oneself to a finite number of measurements. Of course this introduces an additional error (uncertainty). This uncertainty, due to the impossibility of measuring with absolute precision the initial distribution (natural), is called the statistical error. It is easy enough, at least in theory, to diminish this error: it is sufficient to augment the number of measurements. In principle, one can make it negligeable with respect to the initial uncertainty of the physical magnitude. However, a more delicate problem appears.

It is linked to the fact that, in each physical experiment one finds an apparatus, more or less complicated, between the experimenter and the measurable object. This apparatus inevitably brings modifications to the initial distribution: it deforms it. In the simplest case, these changes can be of two types: the apparatus can ‘displace’ the average value or it can enlarge the distribution.

The displacement of the average value is an example of what one calls “systematic errors”. The name indicates that such errors appear in all measurements. The apparatus systematically gives a value different (larger or smaller) than the ‘real’. Measuring with an apparatus with a badly calibrated zero is the most frequent example of this kind of error. Unfortunately, it is very difficult to combat this type of error: it is both difficult to detect and correct. For this, there are no general methods and one must proceed on a case by case basis.

However, it is easier to come to grips with the enlargement of the distribution introduced by the apparatus. One will see that this uncertainty having the same origin as the initial (natural) uncertainties “simply” adds on to these. In a large number of cases, enlargement due to the apparatus permits simplifying the measurements: suppose that we know the uncertainty (width) introduced by a given apparatus, and that it is clearly larger than the original uncertainty. It is possible to neglect the natural uncertainty with respect to the apparatus uncertainty. It is thus sufficient to take but one measure and to take the uncertainty of the apparatus as the uncertainty of the measure. Obviously, in this kind of experiment, one must be certain that apparatus uncertainty dominates natural uncertainty, but one can always verify this by taking repeated measurements. An apparatus of poor precision will not permit finding variations due to initial width.

One must note that a separation between apparatus uncertainty and natural uncertainty remains conventional enough. Nonetheless, one can always say that variations in experimental conditions are part and parcel of apparatus uncertainty. In this work, one does not deal with measurements from quantum physics, where there is an uncertainty in physical measurement due to the Heisenberg Uncertainty Principle. Furthermore, in quantum mechanics the interference between apparatus and object becomes more complicated and interesting. Nonetheless our general conclusions are not modified since, in quantum mechanics, the notion of probability is not only useful and natural, it is also impossible to do without.

We have understood that to experimentally determine a physical value it is necessary (but not always sufficient) to find the average (value) and the width (uncertainty). Without a determination of uncertainty, the experience is not complete: one cannot compare it to either a theory or another experiment. We have also seen that his uncertainty contains three possible contributing factors. The first is uncertainty due to changes in experimental conditions or to the very nature of magnitudes (in statistics or in quantum mechanics). The second is statistical uncertainty due to the impossibility of measuring precisely the initial distribution. The third is apparatus uncertainty due to the imperfection of the working tools of the experimenter.

An experimenter always asks two questions: First, how can one measure a physical magnitude, that is to say the characteristics of its distribution: the average and the width? Secondly, how and to what extent must this uncertainty be diminished? This is why the experimenter must understand the relations between the three components of uncertainty and find how to minimize them: one can minimize natural uncertainty by changing experimental conditions, statistical uncertainty by augmenting the number of measurements, apparatus uncertainty by using more precise instruments.

Yet, one cannot reduce uncertainty indefinitely. There is a reasonable limit to uncertainty. An evaluation of this limit is not only a question of time and money spent, but also an essential question within physics. One must not forget that, whatever the magnitude to be measured, one will never be able to take into account all the physical factors that can influence its value. Further, all of our reasonings and discussions take place within the context of a model or, more generally, our view of the world. That context may not be exact.

This is why our problem is to choose experimental methods and methods for estimating uncertainties adequate to a desirable and possible level of precision.

Various situations exist as a function of desired precision. In the first we are merely seeking to obtain the order of magnitude of the measured value: in that case, uncertainty as well should be grossly evaluated. In the second we want precision in the order of one to ten percent; one must be careful in determining uncertainties, and the methods used will vary to seek greater precision. The more one looks for precision the more the methods will be elaborate, but the price to pay is the slowness of calculations and their volume. In the third we are looking for an order of precision equal to that of the standard corresponding to the physical parameter being measured; the problem of uncertainty can become more important than that of the value.

In this work, we will only consider methods for estimating error in the second situation which corresponds to the majority of experiments undertaken as practical work. Most paragraphs answer a concrete question: how does one calculate uncertainties for an experiment where few measurements are taken? How may one adjust the parameters of a curve? How does one compare an experiment and a theory? What is a number of significant digits? Etc. The reader who knows the basics of Statistics can omit without danger the first paragraphs and seek the answer to his problem. In the contrary case, this work gives him the necessary information on those parts of Statistics useful for the treatment of uncertainties.

Poisson

A problem I find charming from my recent readings in mathematics is the following: Let us suppose that it is known that accidents along a given stretch of road average three per day. What are the chances of there being precisely three on a given day. This is all the information that is given.

An accident is a multi-causal event: impossible to nail precisely what caused any given accident or series. The occurence

of an accident is, accidental; and the knowledge that they average three is statistical i.e. empirical. Someone counted them.

Our problem, then, is that we know the average - or in mathematical terms, the variance - and want to reason back to the probability for one occurence. The Poisson function turns this little trick for us.

p(X) = (e^-λ) × (λ^k∕k!) here for λ=3 et k=3

= (0,049787) × (27∕6)

= 0,224 thus, 22,4 %

It could have been three anything, as long as the occurence was too complex to untangle but the average well established. Luv’s it!

Pear

Lalanne

Bayes Problem

Rabbit

Wheel

Big O Visit

Gothic Moment

Lady Killer

M.J. Cover

Michael

Bonjour

Essay

Baaad Song!

Running Up

Photography

Strictly L

View Other Color

COLD

More

First Ice

L.A. Beauty

Great Place

Working Day

Lost

Mode Fondu

B & A

Streets of Paris

Go designer...

Give Me Liberty!

Geothermal

http://iga.igg.cnr.it/geo/geoenergy.php

Yo Hydro-Quebec!

Happy C-Day

Sad...

Great Dancing