Describing the Business of Farming in O Pioneers! by Willa Silbert Cath

Describing the Business of Farming in O Pioneers! by Willa Silbert Cather Willa Sibert Cather was born in Virginia, December 7, 1873. At the age of nine, Cather's family moved to Nebraska. Willa fell in love with the country, with the waste prairies of the Nebraska. In her life, Willa worked for different journals and magazines and received many honorary degrees, even the Pulitzer Prize. Her literary life was extremely influenced by her childhood in the wild country. In her life story, I actually didn't find any trace of doing a business relative to farming, or running a farm on her own. Therefore she doesn't seem to have practical experience with business of farming. Maybe that's why she describes it in a general way only, without any particulars. The Cather's novel O Pioneers! gives us a realistic picture of people's life at the end of the nineteenth century. The new incomers, who settled the unfriendly countries of American continent, had very hard times. It was necessary for them to do whatever they were able to, to earn some money or to gain something to eat. As we can see in Cather's novel, many people were farming. But some of them were not farmers in their country of origin, they just started farming in the new home. Even though they knew nothing about it. Willa Cather describes a history of such people, a Norwegian immigrant family, the Bergsons. The beginnings in the new world were very tough for the Bergson family. And the situation didn't seem to get better. They have met several misfortunes that have held their farming business back. „One winter his cattle had perished in a blizzard. The next summer one of his plow horses broke its leg in a prairie-dog hole and had to be shot. Another summer he lost his hogs from cholera, and a valuable stallion died from a rattlesnake bite. Time and again his crops had failed. He had lost two children, boys, that came between Lou and Emil, and there had been the cost of sickness and death' This is Cather's idea of what John Bergson had to fight against. It's clear, that the whole family felt discouraged and helpless when there was no success coming. They saw many people around them selling their land and giving the farming up. They were going to find their fortune somewhere else. After John Bergson died, his sons also wanted to give up and change the hard work on the infertile land for some... ...ittle joke. It pretended to be poor because nobody knew how to work it right; and then, all at once, it worked itself. It woke up out of its sleep and stretched itself, and it was so big, so rich, that we suddenly found we were rich, just from sitting still.' I don't know much about farming at the end of the nineteenth century, but I heard something in the school and they have told nothing about becoming rich just from sitting still. This is the romantic point of view of the problem, and that's the Willa Cather's point of view. Actually, there has been some business behind the success. The fact, that Alexandra was buying more and more low-price land. She was very clever. She knew exactly what to do, to become rich and struggle no more. She could count the expenses and the profits several years ahead. But she did all this only because some spirit told her to, only because she felt something powerful coming out of the land. Did Willa Cather think this is the way that bussiness works? It seems to be her romantic illusion. I don't think Alexandra had sufficient reasons to mortgage a farm and start a big business from nothing with all risks. But she made a bet and won. Lucky girl.

Fuzzy Logic Momentum Analysis System For Financial Brokerage Accounting Essay

Abstract- The modeling of fiscal systems continues to keep great involvement for non lone research workers but besides investors and policymakers. Many of the features of these systems, nevertheless, can non be adequately captured by traditional fiscal modeling attacks. Fiscal systems are complex, nonlinear, dynamically altering systems in which it is frequently hard to place mutualist variables and their values. Financial securities firm is concerned with put to deathing orders of purchasing and merchandising of certain sums of portions at the best possible monetary value. Many mathematical and algorithmic systems have been developed for this undertaking, nevertheless they can non look to get the better of a criterion volume based system. This paper proposes a new model for high frequence trading utilizing an intelligent fuzzy logic based impulse analysis system. The system was applied to securities firm of fiscal stocks, and tested against the criterion volume based securities firm system. The Fuzzy Logic Momentum Analysis System has proven to surpass the traditional and standard systems that are used in the industry. Keywords ; Finacial securities firm ; fuzzed logic ; high frequence trading. Introduction It is good known that a chief insufficiency of much economic theory is that it postulates exact functional relationships between variables. On the other manus in fiscal clip series analysis, information points seldom lie precisely on consecutive lines or smooth maps. [ 7 ] suggests that trying to suit these nonlinear phenomena will present an unacceptable degree of instability in theoretical accounts. As a consequence of this intractableness, research workers and investors are turning to unreal intelligence techniques to better inform their theoretical accounts, making determination support systems that can assist a human user better understand complex fiscal systems such as stock markets. Artificial intelligence systems in portfolio choice have been shown to hold a public presentation border over the human portfolio director and recent research suggests that attacks that incorporate unreal intelligence techniques are besides likely to surpass classical fiscal theoretical accounts [ 4 ] . Artificial intelligence attacks have late been normally adopted in fiscal modeling. Traditionally, stock market calculating methodological analysiss have been based on either cardinal or proficient analysis. Cardinal analysis efforts to find the intrinsic value of stocks based on extended macroeconomic informations, whereas proficient analysis relies on analyzing market activity, peculiarly historic monetary values and volume. Whilst there is much back uping research for both schemes in fiscal theory we focus on systems utilizing proficient methodological analysis as the subjective and complex nature of cardinal analysis means it has, to day of the month, received small attending in unreal intelligence research. Fuzzy logic was foremost introduced by [ 6 ] . It is a signifier of multivalent logic which, whilst retaining the deductive construction of classical symbolic logic, includes the construct of grade of truth. Rather than being either true or false, as in binary logic, statements in fuzzed logic have a rank map which defines a fuzzy set ( as opposed to a chip set in conventional set theory ) . Fuzzy logic is hence an ideal attack to jobs that require a representation that can cover with estimates, uncertainness and deficient information and it has been applied to spheres every bit diverse as pattern acknowledgment [ 10 ] , railroad control systems [ 2 ] and computing machine game design [ 11 ] . The regulation base and illation engine of a fuzzed system is comparable to that of the cognition base of an expert system. The application of fuzzed set theory in economic science was foremost presented by [ 12 ] and has since received much attending [ 3 ] Time series theoretical accounts were foremost combined with fuzzed theory by [ 5 ] giving rise to fuzzy time-series, the cardinal model of all the investing systems. Research workers making stock trading systems have implemented many fluctuations of this theoretical account. Most late, [ 1 ] has proposed the usage of Adaptive Neuro Fuzzy Inference Systems ( ANFIS ) , which combine the prognostic belongingss of nervous webs, with the concluding mechanisms of fuzzed logic to make an machine-controlled trading and prediction system that has been used for high frequence trading of foreign exchange currencies markets ( FOREX ) . This paper is outlined as follows. In subdivision II we give a general overview about fuzzed logic illation systems. Section III introduces the fuzzed logic impulse analysis system ( FL-MAS ) . Section IV explains the methodological analysis of utilizing FL-MAS for securities firm. Section V provides a public presentation analysis of the system. Finally, reasoning comments are given in Section VI. Fuzzy illation Systems Many types of fuzzed illation systems have been proposed in literature, nevertheless, in the execution of an ANFIS for fiscal anticipations and appraisal, the most suited theoretical account is the Sugeno theoretical account, which uses if-then-rules to bring forth an end product for each regulation which is the additive combination of the input variables plus a changeless term, and the concluding end product is the leaden norm of each regulation ‘s end product. The regulation base in the Sugeno Model, has regulations of the signifier: If X is A1 and Y is B1 so f1 = p1* x + q1* y + r1 If X is A2 and Y is B2 so f2 = p2 * x + q2 * y + r2 ( 1 ) where X & A ; Y are predefined rank maps, Ai and Bi are rank values, and pi, chi, and Rhode Island are the attendant parametric quantities that are updated in the forward base on balls in the acquisition algorithm. When we calculate the equation of â€Å" First order Sugeno † the grade of rank variable of X1 in rank map of Ai is multiplied by the grade of rank variable of X2 in rank map Bi and the merchandise is deemed a first Liner Regression Weight ( Wi ) . Finally the leaden mean F1 and F2 is deemed the concluding end product ( Z ) which is calculated as follows: A fuzzed illation systems shown in Fig. 1 is a regulation based fuzzy system that can be seen as an associatory memory and is made of five constituents ; regulation base which consists of the fuzzed if-then regulations, the informations base which defines rank maps of the fuzzed sets used in the fuzzy regulations, the determination devising unit which is the nucleus unit and is besides known as the illation engine, the fuzzification interface which transforms chip inputs into grades of fiting lingual values, and eventually the defuzzification interface which transforms fuzzed consequences into sharp end product [ 13 ] . Fuzzy Logic Momentum Analysis System Making a fuzzed illation system to observe impulse is a complex undertaking. The designation of assorted market conditions has been a subject topic to assorted theories [ 14 ] and suggestions. This paper proposes a fuzzed illation system which categorises the market conditions into 7 classs based on monetary value motion, and will utilize the current volume to find the engagement rates ( PR ) of the trading system each clip. Fuzzy InferenceMomentum AnalysisThe first measure in planing the Fuzzy Logic Momentum Analysis System, FL-MAS, is specifying the market conditions that the fuzzy system has to place. In this paper we use the following 7 market conditions to cover all possible motions of the monetary value series: Beat uping Strong up Slightly up Average Slightly down Strong down Crashing These conditions are considered as lingual values for the fuzzy logic system, and will be used to find the current province of the monetary value formation and its impulse. As impulse is built up, the system looks at the old x sum of ticks and performs an illation process by adding all the motions of the current monetary value to the old monetary value to find whether the general tendency has been up or down after ten points. In other words, impulse is detected by the followers: where is the current monetary value, is the old monetary value, and is a fluctuating counter which goes up or down harmonizing to the motion of the monetary value. whenever monetary value goes up it adds 1, when the monetary value goes down it subtracts 1, therefore this can be used in placing market conditions for x sum of points, where if the market is traveling strongly upwards, it will be detected by holding more 1s than -1 or 0s. This can be explained in the undermentioned equation: ( 2 ) where is the period that we want to observe the impulse for. For illustration, if we want to observe the impulse of the last 100 ticks, we add all the up, down fluctuations and so feed the ensuing figure to the fuzzy system which would lie someplace in the rank maps shown in Fig. 2. Membership maps for the lingual variable of market conditions The same process is applied for ciphering the lingual variable volatility, where the lingual values are as follows: Very fast Fast Medium Decelerate Very slow The fuzzy logic system takes both market impulse and volatility in consideration ; it generates the regulations, and eventually takes a determination based upon the sum of market engagement.The DataExperiments in this paper have been carried out on high frequence tick-data of both Vodafone Group plc ( VOD ) and Nokia Corporation ( NOK ) . For both stocks, 2 months of high frequence tick-data between 2nd Jan 2009 and 27th Feb 2009 has been obtained, and split into 30 subdivisions each. This was done in order to avoid any car correlativity between the monetary values. In other words, the fuzzy logic system gets the first batch of informations, performs all the actions of bargains or sells on it, so the same is process repeated utilizing the criterion volume based system, eventually comparing the public presentation of both systems. Once the observation is obtained, the system skips about 10000 ticks and performs the same operations once more, for 30 times, each clip observing the publi c presentation of both systems. It has to be mentioned that 2 months of high frequence tick informations is a significantly big sum of informations, taking in consideration that for each loop the system takes the analysis of the impulse of the past 100 ticks. Fig. 3 shows how the information is split after each simulation in order to avoid any possible similarities or autocorrelation in the monetary value. FL-MAS for securities firm tick informations discarded tick informations High frequence tick by tick informations Sim 1 Sim 2 Sim N The chief aim of the Fuzzy Logic Momentum Analysis System ( FL-MAS ) implemented in this paper is to surpass the industry criterion volume system, that has been used by securities firm houses to put to death big orders of purchasing or selling a certain stock. Many systems have used quantum modeling and analysis to find the assorted engagement rates ( PR ) , nevertheless they normally fail to surpass the criterion volume system in the long term [ 15 ] . This paper uses FL-MAS presented in subdivision 3, to find the PR in the market harmonizing to the current impulse. In other words, if we are on a bargain order, we would prefer to increase the PR ( figure of portions bought at that clip ) , when the monetary value is low, and diminish the engagement when the monetary value is high. Tick informations splitting mechanismStandard Volume System ( SVS )A standard securities firm mechanism for put to deathing big orders is a simple volume based system, which parses the volume being traded, whenever a certain sum of portions ( a threshold ) have been traded, the system would purchase or sell ( depending on the order ) a certain per centum of that. In other words, if there is an order to merchandise 1 million portions of a certain stock. The threshold would be for e.g. 10,000 portions, and whenever 10,000 portions have been traded, if the PR is set to 25 % , the system would purchase or sell 25 % of the mean volume. ( 3 ) where N is the figure of operations required to make the mark order for illustration 1 million portions, % is a fixed PR, for illustration, 25 % whenever the threshold is exceeded. The above system has proved to be efficient and is being adopted by many securities firm houses around the universe. The purpose of this paper, is to turn out that FL-MAS outperforms this type of system on the long tally.FL-MASThe thought here is to utilize the fuzzy logic impulse analysis system described in subdivision 3, to place what market status we are presently shacking in. This will let us to change the PR ( % ) . This provides an advantage, since the system can merchandise sharply when the status is at an extreme. It would besides understate its trading when the status is at another extreme. In other words, if we are selling million portions, the system will do a trade whenever the threshold of volume has been exceeded. However if the current market status indicates that the monetary value is real ly high or beat uping so we know that this is a good clip to sell a batch of portions, for illustration 40 % of the current volume. The same thing applies for when the impulse indicates that the monetary value is strong down which means that the system should sell less sums of volume at this low monetary value, for illustration 15 % . The contrary mechanism applies for purchasing portions. When the market is crashing, this is a good index that we should purchase a big ball of volume ( 40 % ) , and when the monetary value is at an mean point, this means that it would act like the SVS system i.e. purchasing 25 % of Volume. This is shown in Table 1. Engagement rates for buy side and the sell side of FL-MAS Market Condition Buying Praseodymium Selling Praseodymium Beat uping 10 % 40 % Strong up 15 % 35 % Slightly up 20 % 30 % Average 25 % 25 % Slightly down 30 % 20 % Strong down 35 % 15 % Crashing 40 % 10 %Performance MeasuresAfter implementing both SVS and FL-MAS, the standards at which both systems will be compared against each other will be the outperformance of FL-MAS on the SVS in footing points. TheA footing point is a unit of step used frequently to depict the per centum at which a alteration in the value or rate of a fiscal instrument has occurred. One footing point is a1/100th of a per centum orA 0.01 % . It is besides tantamount to 0.0001 in denary signifier. To cipher the betterment ( elf ) for the buy side in footing points we use the undermentioned expression:iˆ?iˆ?iˆÂ ©For the Sell Side the betterment in footing points is:iˆ?iˆÂ µiˆÂ ©Where is the entire cost of purchasing x sum of portions utilizing FL-MAS, and is the entire cost of purchasing the same figure of portions utilizing the traditional SVS. Consequences This subdivision displays the consequences of utilizing both FL-MAS and SVS to purchase 1million portions of VOD and NOK. For each symbol 30 simulations have been carried on the tick-data set described in subdivision 3. The information has been split as described in order to avoid any autocorrelations, both systems have been run and tested on the same information sets. Table 2 displays the cost at each simulation for purchasing 1million portions of NOK utilizing both systems. The mean monetary value of the whole set is besides displayed, and eventually the betterment of FL-MAS against SVS is displayed. This betterment rate can be either positive ; when FL-MAS has outperformed SVS or negative ; when FL-MAS was outperformed by SVS. Table 3 provides a full analysis of Table 2, by demoing clearly the mean outperformance rate of purchasing 1million portions of NOK utilizing FL-MAS, which turns out to be a positive of 2.98 footing points, which means that on mean utilizing FL-MAS we save about 3 footing points whenever we buy 1 million portion of NOK. Table 3 besides displays the consequences of implementing both systems to purchase 1 million portions of VOD. These consequences for VOD ( besides displayed on Fig.4 ) show a much higher mean of around 12.5 footing points. Experiments have been performed once more by reshuffling the information sets utilizing the informations slots that have non been used before, and the observations were really similar to these consequences. Hence another measuring mechanism was to detect the median of the consequences. The median is described as the figure dividing the higher half of a sample or distribution from the lower half. Both Medians for NOK, and VOD were positive, bespeakin g that on mean FL-MAS outperforms SVS for all the purchasing Simulations. Comparing the public presentation of FL-MAS against SVS for purchasing 1M portions of NOK Average Monetary value Cost of purchasing 1m NOK Shares utilizing FLMAS Cost of purchasing 1m NOK Shares utilizing SVS Improvement in footing points 11.55 11278964 11285761 6.02 12.19 11581642 11572708 -7.72 11.57 11904468 11910571 5.12 11.12 11610312 11581174 -25.16 11.45 11076799 11087759 9.88 11.36 11456338 11452293 -3.53 11.03 11390049 11404634 12.79 10.89 10947120 10956223 8.31 10.45 10923870 10950576 24.39 10.31 10373596 10377899 4.15 10.63 10354815 10367941 12.66 10.78 10655795 10644194 -10.90 10.70 10816236 10814437 -1.66 10.45 10723627 10737409 12.84 10.24 10281461 10286957 5.34 10.48 10214443 10205979 -8.29 9.67 10553155 10547707 -5.17 9.67 9581014 9602197 22.06 9.40 9754339 9740190 -14.53 9.22 9521736 9544895 24.26 9.10 9282640 9280416 -2.40 9.38 9135088 9149560 15.82 9.27 9434147 9457587 24.78 9.42 9262702 9272236 10.28 9.77 9439104 9430047 -9.60 9.87 9807817 9799844 -8.14 9.49 9880881 9885421 4.59 9.58 9585207 9580119 -5.31 9.48 9619778 9624263 4.66 9.40 9556780 9555829 -1.00 9.67 9350444 9359424 9.59 9.98 9724834 9707290 -18.07 9.94 9869580 9869177 -0.41 Analysis of consequences of purchasing 1m portions of NOK and VOD Mean ( elf ) Median ( elf ) Entire ( elf ) Buying NOK 2.98 4.63 101.18 Buying VOD 12.48 1.58 374.53 Besides the entire betterment of both is really high indicating that for both the 30 simulations, a 101.18 footing points was saved utilizing FL-MAS on NOK, and a 374.53 on VOD. Buying 1m portions of VOD Similarly, the sell side is displayed in Table 4, and analysed in Table 5. Similar to the bargain side, all simulations and experiments utilizing FL-MAS and SVS, have displayed that on mean FL-MAS has proved to be the better system, and therefore would increase the profitableness of a fiscal securities firm house that executes multiple big orders. Fig. 5 displays the merchandising of 1m portions of VOD. Comparing the public presentation of FL-MAS against SVS for selling 1M portions of VOD Average Monetary value Cost of selling 1m VOD Shares utilizing FLMAS Cost of selling 1m VOD Shares utilizing SVS Improvement in footing points 139.75 138379831 138304137 5.47 142.10 141880579 141466276 29.20 147.30 145752861 145974583 -15.21 145.70 147127925 147242618 -7.80 144.50 145284236 145840646 -38.30 148.30 141887321 141926909 -2.79 138.30 138593022 138540789 3.77 137.60 138159371 138119542 2.88 138.45 137192635 137152512 2.92 138.80 136243869 137297036 -77.30 138.70 138854269 138889050 -2.50 135.95 134818894 134622571 14.56 133.85 135551066 135198498 26.01 136.50 133744440 133824812 -6.01 135.55 136450408 136384280 4.85 139.50 136381824 136248448 9.78 138.30 138364382 138217262 10.63 136.85 136263730 136277519 -1.01 134.20 133894601 133855738 2.90 134.56 133894289 132534941 101.52 127.10 129477007 129129593 26.83 128.90 127159502 127174918 -1.21 130.85 129889373 129821846 5.20 135.50 130203793 130019981 14.12 136.85 135468629 135441956 1.97 136.45 136622702 136595289 2.01 138.05 136719313 136746751 -2.01 136.65 134943043 135082269 -10.32 132.15 133857223 134159108 -22.55 Analysis of consequences of Selling 1m portions of NOK and VOD Mean ( elf ) Median ( elf ) Entire ( elf ) Selling NOK 1.6812 2.9291 57.16 Selling VOD 2.73 2.46 81.83 Selling 1m portions of VOD Decision The job of order executing is a really complicated one. To be able to supply the best monetary value, an executing system has to dynamically alter the engagement rates at each case in order to provide for monetary value alterations, which are driven by impulse and volatility. This paper has introduced a system that makes usage of fuzzed logic, in order to ground out the current market status which is produced by the accretion of impulse. FL-MAS is a fuzzed logic impulse analysis system that outperforms the traditional systems used in industry which are frequently based on put to deathing orders based on the leaden norm of the current volume. Consequences of the enforced system have been displayed and compared against the traditional system. The system proves that on norm it increases profitableness on orders both on the bargain and sell sides. Further work and research has to be done to optimize the public presentation of the system. This could either include the usage of a familial algorithm to optimize the rank maps or the usage of Adaptive Neuro Fuzzy systems which would bring forth all the possible regulations for the system.

The Definition of Form in Art

The term form can mean several different things in art. Form is one of the seven elements of art and connotes a three-dimensional object in space. A  formal analysis of a work of art describes how the elements and principles of artwork together independent of their meaning and the feelings or thoughts they may evoke in the viewer. Finally,  form is also used to describe the physical nature of the artwork, as in metal sculpture, an oil painting, etc.​ When used in tandem with the word art as in art form, it can also mean a medium of artistic expression recognized as fine art or an unconventional medium done so well, adroitly, or creatively as to elevate it to the level of fine art. An Element of Art Form is one of the seven elements of art  which are the visual tools that an artist uses to compose a work of art. In addition, to form, they include line, shape, value, color, texture, and space.  As an Element of Art, form connotes something that is three-dimensional and encloses volume, having length, width, and height, versus shape, which is two-dimensional, or flat. A form is a shape in three dimensions, and, like shapes, can be geometric or organic. Geometric forms are forms that are mathematical, precise, and can be named, as in the basic geometric forms: sphere, cube, pyramid, cone, and cylinder.  A circle becomes a sphere in three dimensions, a square becomes a cube, a triangle becomes a pyramid or cone. Geometric forms are most often found in architecture and the built environment, although you can also find them in the spheres of planets and bubbles, and in the crystalline pattern of snowflakes, for example. Organic forms are those that are free-flowing, curvy, sinewy, and are not symmetrical or easily measurable or named. They most often occur in nature, as in the shapes of flowers, branches, leaves, puddles, clouds, animals, the human figure, etc., but can also be found in the bold and fanciful buildings of the Spanish architect Antoni Gaudi (1852 to 1926) as well as in many sculptures. Form in Sculpture Form is most closely tied to sculpture, since it is a three-dimensional art and has traditionally consisted almost primarily of form, with color and texture being subordinate. Three-dimensional forms can be seen from more than one side. Traditionally forms could be viewed from all sides, called sculpture in-the-round, or in relief, those in which the sculpted elements remain attached to a solid background, including bas-relief, haut-relief, and sunken-relief. Historically sculptures were made in the likeness of someone, to honor a hero or god. The twentieth century broadened the meaning of sculpture, though, heralding the concept of open and closed forms, and the meaning continues to expand today. Sculptures are no longer only representational, static, stationery, forms with a solid opaque mass that has been carved out of stone or modeled out of bronze. Sculpture today may be abstract, assembled from different objects, kinetic, change with time, or made out of unconventional materials like light or holograms, as in the work of renowned artist James Turrell. Sculptures may be characterized in relative terms as closed or open forms. A closed-form has a similar feeling to the traditional form of a solid opaque mass. Even if spaces exist within the form, they are contained and confined. A closed-form has an inward-directed focus on the form, itself, isolated from ambient space. An open form is transparent, revealing its structure, and therefore has a more fluid and dynamic relationship with the ambient space.  Negative space is a major component and activating force of an open form sculpture. Pablo Picasso (1881 to 1973), Alexander Calder (1898 to 1976), and Julio Gonzalez (1876 to 1942) are some artists who created open form sculptures, made from wire and other materials. Henry Moore (1898 to 1986), the great English artist who, along with his contemporary, Barbara Hepworth (1903 to 1975), were the two most important British sculptors in modern art, both revolutionized sculpture by being the first to pierce the form of their biomorphic (biolife, morphicform) sculptures. She did so in 1931, and he did in 1932, noting that â€Å"even space can have form† and that â€Å"a hole can have as much shape meaning as a solid mass.†Ã‚   Form in Drawing and Painting In drawing and painting, the illusion of three-dimensional form is conveyed through the use of lighting and shadows, and the rendering of value and tone. Shape is defined by the outer contour of an object, which is how we first perceive it and begin to make sense of it, but light, value, and shadow help to give an object form and context in space so that we can fully identify it. For example, assuming a single light source on a sphere, the highlight is where the light source hits directly; the mid-tone is the middle value on the sphere where the light does not hit directly; the core shadow is the area on the sphere that the light does not hit at all and is the darkest part of the sphere; the cast shadow is the area on surrounding surfaces that is blocked from the light by the object; reflected highlight is light that is reflected back up onto the object from the surrounding objects and surfaces. With these guidelines as to light and shading in mind, any simple shape can be drawn or painted to create the illusion of a three-dimensional form. The greater the contrast in value, the more pronounced the three-dimensional form becomes. Forms that are rendered with little variation in value appear flatter than those that are rendered with greater variation and contrast. Historically, painting has progressed from a flat representation of form and space to a three-dimensional representation of form and space, to abstraction. Egyptian painting was flat, with the human form presented frontally but with the head and feet in profile. The realistic illusion of form did not occur until the Renaissance along with the discovery of perspective. Baroque artists such as Caravaggio (1571 to 1610), explored the nature of space, light, and the three-dimensional experience of space further through the use of chiaroscuro, the strong contrast between light and dark. The portrayal of the human form became much more dynamic, with chiaroscuro and foreshortening giving the forms a sense of solidity and weight and creating a powerful sense of drama. Modernism freed artists to play with the form more abstractly. Artists such as Picasso, with the invention of Cubism, broke up the form to imply movement through space and time. Analyzing an Artwork When analyzing a work of art, a formal analysis is separate from that of its content or context. A formal analysis means applying the elements and principles of art to analyze the work visually. The formal analysis can reveal compositional decisions that help to reinforce content, the work’s essence, meaning, and the artist’s intent, as well as give clues as to historical context. For example, the feelings of mystery, awe, and transcendence that are evoked from some of the most enduring Renaissance masterpieces, such as the Mona Lisa (Leonardo da Vinci, 1517), The Creation of Adam (Michelangelo, 1512),  the Last Supper (Leonardo da Vinci, 1498) are distinct from the formal compositional elements and principles such as line, color, space, shape, contrast, emphasis, etc., the artist used to create the painting and that contribute to its meaning, effect, and timeless quality. Resources and Further Reading Form, Tate Museum, http://www.tate.org.uk/art/art-terms/f/formThe Art of Sculpture, Encyclopedia of Art, http://www.visual-arts-cork.com/sculpture.htmThe hole of life, Tate Museum, http://www.tate.org.uk/context-comment/articles/hole-of-lifeBarbara Hepworth vs Henry Moore, CultureWhisper, https://www.culturewhisper.com/r/article/preview/3670Works of Antoni Gaudi, http://whc.unesco.org/en/list/320Henry Moore Foundation, https://www.henry-moore.orgBarbara Hepworth, https://barbarahepworth.org.ukJames Turrell, http://jamesturrell.com Resources for Teachers The Elements of Art: Form, Grade Level: 3-4, National Gallery of Art, https://www.nga.gov/content/ngaweb/education/teachers/lessons-activities/elements-of-art/form.htmlShape and Form in Art: Instructional Program for Grades K-4, Teacher’s Guide, http://gettingtoknow.com/wp-content/uploads/shapeinartTG.pdf