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GEOMATICS AND ENVIRONMENTAL ENGINEERING • Volume 8 • Number 2 • 2014 http://dx.doi.org/10.7494/geom.2014.8.2.37http://dx.doi.org/10.7494/geom.2013.7.2.37

MarekMateusz Bana Ilba*ś*

A Review ofSupport Robust for Estimation Create Methods 3D ComputerApplied Graphics in ImagesSurveying in GIS Systems Using Externals Renders

1. Introduction 1. Capabilities Results of Analyzes Despitein GIS thePrograms continuous improvement of survey methods and advances made in survey equipment technology, the elimination of outliers still remains an issue today.Browsing When performing the possibilities an adjustment posed by one GIS often and assumes CAD programsa very simple in theprobability model- distributioning of results errors, we such can as find a normal many distribution. similarities In classical and differences. the correct-Features arise nessfrom of aims the resultsfor which relies these on the types assumption, of programs that havthe echosen been errors developed. distribution Goal of mod- GIS elsoftware is strictly is totrue. do Thisdifferent is, in fact,types often of spatial not the analysis. case, as Athe secondary large errors aim occur is to consider- do visu- ablyalization more of often the resultsthan the generated. normal distribution A secondary would aim issuggest. to doing Even visualization the high-quality of the samplesresults generated. analysed CADin astronomical software is takingresearch, containing presentation several proposed thousands as an overrid-of mea- surementsing goal, however, each, do analysis not follow tools, the normal probability and relationship distribution. to the Deviations are from lim- theited model to special may overlays occur due to theto e.g. main blunders program in or measuring, did not exist. incorrect Knowing point how numbering, to do the errorsmain task made of duringparticular data programs copying etc.we can[12]. say that the CAD software is better suited for theAlthough visualization there ofexists data a than wide GIS applications. of literature concerned with gross errors detectionWe will and attempt elimination, to analyze this possibility problem of these is twostill beingtypes discussed.of software There with arere- manygard to so-called ArcGIS Versionmethods 10 robust and CAD against graphics the in software uence of Cinema4Dgross errors, R13. which can gen- erallyFor be divided visualization into two in groups. the program ArcGIS we can use two 3D environ- ments:The ArcGlobe  rst group and includes ArcScene. methods They based are designed on the criteria for different of so-called uses. robust After esti- start- mation.ing ArcGlobe These application, methods minimise we can seethe thein globe,uence ofsuggests the outlying to us, thatobservations all analysis on and the visualization nal result of willthe computationsinvolve a large by area modifying of land. Theof the data observation can be presented weights. on a sphere Earth.The ArcScene second of is designedthem consists for analysisof methods and where visualization results, coveringobtained aby small the leastarea squaresof land. adjustmentData are presented are analysed on the with local the usereference of statistical plane. tests. Differences In these methodsalso include an identidata that ed we outlier can useis removed for analysis from and the visualization.dataset. If multiple In ArcGlobe, outliers alloccur, data the can iterative be dis- processplayed inof theleast specified squares adjustment simplification, is conducted depending and followedon the magnification. by tests. The observa- This elimi- tionsnates suspectedthe problem of grossof overloading errors are thediscarded computer from memory, the dataset we do[1]. not A few have commonly to resign usedfrom methodsless important of these data groups available. are presented In ArcScene, below. all available data are automatically stored in the computer memory, we have quick access to them. The downside of

* The Bronisław Markiewicz State Higher School of Technology and in Jarosław, * Institute AGH University of Technical of Science Engineering, and Technology Poland

13 37 38 M. Ilba this is dependence of the maximum amount of data used to the quantities computer memory. Exceeding the limit of memory deteriorates the smooth operation of pro- gram. Many other differences between ArcGlobe and ArcScene software presented in the 1. After comparing the options above we can conclude that the best tool for visual- izing data on a small range, for example, the analysis of place of the buildings and the analysis of hydrographic, is a software ArcScene.

Table 1. Selected differences between ArcGlobe and ArcScene applications

Software variants ArcGlobe ArcScene Ability to perform 3D analysis, extension 3D Analyst Yes No The ability to support large amounts of data by caching Yes No Ability to present data on the surface of the globe Yes No Dynamic shading of depends on the definition of the position of the main No Yes source of lighting Chance of presentation images as anaglyph, stereoscopic images No Yes Loading spatial data with no defined reference system, the local system No Yes Possibility of programming images animation No Yes

In the settings display quality graphics in ArcGlobe and ArcScene is available only poorly developed illumination option responsible for the lighting. It includes elements such as the angle of incidence of solar radiation, altitude and position of the simulated sun, and contrast. Poor number of options theory gives us to under- stand that the generated images are deviate significantly from the required photo realism. ArcScene software will be analyzed as a dedicated tool for visualizing data on a small range for example, the analysis of the location the building and the analysis of hydrographic. In ArcScene, layers can be textured by any images using the sym- bolization. Texture on one layer may differ between themselves after a proper clas- sification, or use of unique symbols for the layer arising from the database. Lighting the whole scene consists in dimming or brightening the textures depending on the angle and height of the sun. The big downside is the lack of shadows cast by the illu- minated object on the other layers, such as for example, houses do not cast shadows on the ground, what makes the visualized scene the artificial. An additional prob- lem is the lack of antialising settings,i.e. smoothing the edges of objects. This minus may be removed by setting the appropriate option in the video card drivers. This will cause partial smoothing out all the edges of the escalator. Another downsides of the ArcScene are limited opportunities of modeling objects. A simple 3D model can be created from 2D polygon by extrude. Extrusion turns polygons into blocks. ž™™˜›ȱ˜›ȱ›ŽŠŽȱřȱ˜–™žŽ›ȱ ›Š™‘’Œœȱ –ŠŽœȱ’—ȱ ȱ¢œŽ–œȱœ’—ȱ¡Ž›—Š•œǯǯǯ řş

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‘ŽȱꛜȱŠ—ȱ–˜œȱ’–™˜›Š—ȱ™‘¢œ’ŒŠ•ȱŽěŽŒȱ’œȱ•’‘’—ȱœŒŽ—Žœȱžœ’—ȱ—Šž›Š•ȱ•’‘ȱ ˜ȱ‘Žȱœž—ȱŠ—ȱœ”¢ǯȱ’‘’—ȱ‘Žȱœž—ȱ’œȱ’–™•Ž–Ž—Žȱžœ’—ȱ‘Žȱœ™˜•’‘ǰȱœ’—’ęŒŠ—ȱ ’œŠ—ŒŽȱŠ Š¢ȱ›˜–ȱ‘Žȱ™•Š—Žȱ˜ȱ’—Œ’Ž—ŒŽǰȱœ˜ȱ‘Šȱ‘Žȱ›Š¢œȱŠ›Žȱ™Š›Š••Ž•ȱ˜ȱŽŠŒ‘ȱ˜‘Ž›ǰȱ œ‘Š˜ œȱ˜ȱ˜‹“ŽŒœȱŠ›ŽȱŠ››Š—Žȱ•’”Žȱ’—ȱ—Šž›Žȱ’—ȱ‘ŽȱœŠ–Žȱ’›ŽŒ’˜—ǯȱ‘’œȱ•’‘ȱ’—ȱ‘Žȱ ™›˜›Š–ȱ’—Ž–ŠŚȱ‘Šœȱ‹ŽŽ—ȱ—Š–ŽȱŠœȱ‘Žȱž—ǯȱ ȱ’œȱŠ•œ˜ȱŠŸŠ’•Š‹•Žȱ’—ȱ–˜›ŽȱŽ•Š‹˜›ŠŽȱ ˜™’˜—ȱ‘¢œ’ŒŠ•ȱ”¢ǯȱ ••ž–’—Š’—ȱ‘ŽȱœŒŽ—Žȱ Žȱ‘ŠŸŽȱŠȱŸŠ›’Ž¢ȱ˜ȱ˜™’˜—œǰȱ’—Ž›ȱŠ•’Šǰȱ‘Žȱ šžŠ•’¢ȱŠ—ȱ¢™Žȱ˜ȱœ‘Š˜ œǰȱ•’‘’—ȱ™˜ Ž›ǰȱ™˜œ’’˜—ȱ˜ȱ‘Žȱœž—ȱ›Žž•ŠŽȱ‹¢ȱ‘ŽȱŒŠ•Ž—Ȭ Š›ȱǻž—ȱŒŠ—ȱ‹ŽȱœŽȱ˜ȱ‘ŽȱŒ˜››ŽŒȱ™˜œ’’˜—ȱ˜›ȱŠ—¢ȱŽ˜›Š™‘’ŒȱŒ˜˜›’—ŠŽœǼȱŠ—ȱ‘ŽȱŒ˜•˜›ȱ Š—ȱœŠž›Š’˜—ǯȱ‘Žȱœ‘Š˜ œȱŠ›ŽȱŽ—Ž›ŠŽȱžœ’—ȱ›Š¢ȱ›ŠŒ’—ȱŠ•˜›’‘–ǯȱ‘’œȱ’—Ÿ˜•ŸŽœȱ œŽ—’—ȱŠȱœ’—•Žȱ‹ŽŠ–ȱ˜ȱ•’‘ȱŠ—ȱŠ—ȱŠ—Š•¢œ’œȱ˜ȱ’œȱŒ˜ž›œŽǯȱ ȱ’ȱ‘’œȱŠ—ȱ˜‹œŠŒ•Žȱ˜™ŠšžŽȱ Ž›–’—ŠŽœȱ’œȱ›ž—ǰȱ˜••˜ Žȱ‹¢ȱŠȱŠ›”ȱ›Š–Ž—ȱ˜›–ŽȱŒŠ••Žȱœ‘Š˜ ǯȱ’‘’—ȱ‘Žȱœ”¢ȱ ’œȱŠȱ˜˜ȱ Š¢ȱ˜ȱœ’–ž•ŠŽȱ ŽŠ‘Ž›ȱ ’‘˜žȱœž—•’‘ǰȱŒ•˜ž¢ǯȱ‘Š˜ œȱŠȱ‘Žȱ•’‘ȱŠ›Žȱ ’—˜›ŽǰȱŠ—ȱ‘Žȱ•’‘ȱŽ–’ĴŽȱ‹¢ȱ ‘˜•Žȱœ™‘Ž›Žȱ–˜Ž•ȱ˜ȱ‘Žȱœ”¢ǯȱ‘Žȱ•’‘ȱ’œȱœŒŠĴŽ›Žȱ Š—ȱ ž—˜›ž—ŠŽ•¢ȱ —˜ȱ ‘’‘•’‘œȱ ‘Žȱ řȱ Ž™‘ȱ ŽěŽŒǯȱ›’ęŒ’Š•ȱ •’‘’—ȱ ’œȱ ‹ŠœŽȱ ˜—ȱ Ž–’œœ’˜—ȱ˜ȱ‘›ŽŽȱ¢™Žœȱ˜ȱ•’‘’—DZȱœ™˜ǰȱ’›ŽŒ’˜—Š•ȱŠ—ȱœž›ŠŒŽǯȱ ’œȱŠœ”ȱ’œȱ˜ȱ™›ŽœŽ—ȱ ‘Žȱ’쎛Ž—ȱœ˜ž›ŒŽœȱ˜ȱŠ›’ęŒ’Š•ȱ•’‘ǰȱ’—Œ•ž’—ȱ•’‘ȱ‹ž•‹œǰȱ›ŽĚŽŒ˜›ȱŠ—ȱ̞˜›ŽœŒŽ—ȱ •Š–™œǯȱ‘Žȱ•’‘ȱœ™˜ǰȱžŽȱ˜ȱ‘Šȱ’œȱŒ•˜œŽȱ˜ȱ‘Žȱœž››˜ž—’—ȱ˜‹“ŽŒœǰȱœ‘Š˜ œȱŠ›˜ž—ȱ Ž–’œǰȱ‘Ž¢ȱŠ›Žȱ—˜ȱ™Š›Š••Ž•ȱŠœȱ’—ȱ‘ŽȱŒŠœŽȱ˜ȱœž—•’‘ǯȱ’‘ȱœ™˜ȱœ‘’—Žœȱ’—ȱ˜—Žȱ’›ŽŒ’˜—ǯȱ ›ŽŠŽœȱŠȱŒ˜—Žȱ‹ŽŠ–ȱ˜ȱ•’‘ȱ ’‘ȱŠȱ˜™Ž—’—ȱŽ™Ž—’—ȱ˜—ȱ‘ŽȱžœŽ›ǯȱ—•¢ȱ’Ž–œȱœŠ¢’—ȱ ’—ȱ‘ŽȱŒ˜—Žȱ˜ȱ‘Žȱ•’‘ȱ ’••ȱ‹Žȱ•’‘ŽȱŠ—ȱŽ—Ž›ŠŽȱœ‘Š˜ œǯȱ‘Žȱ•Šœȱ¢™Žȱ˜ȱ•’‘ȱ’œȱ‘Žȱ •’‘ȱœž›ŠŒŽǰȱ ‘’Œ‘ȱžŽȱ˜ȱ‘Žȱ•Š›Žȱœž›ŠŒŽȱŽ–’Ĵ’—ȱ›Š¢œȱŒ›ŽŠŽœȱŸŽ›¢ȱœ˜ȱœ‘Š˜ œǯȱ Ž••ȱœž’Žȱ˜ȱ’–’ŠŽȱ‘Žȱ›˜˜–ȱ’••ž–’—Š’˜—ȱžœ’—ȱ̞˜›ŽœŒŽ—ȱ•Š–™œǯȱ Ž—Ž›Š’—ȱ•’‘ȱ ‹¢ȱœŽ—’—ȱ›Š¢œȱ˜ȱ•’‘’—ȱ™˜’—œȱŠ—ȱ‘Žȱœž›ŠŒŽȱ˜Žœȱ—˜ȱŒ›ŽŠŽȱž••¢ȱ™‘˜˜›ŽŠ•’œ’Œȱ •’‘’—ǯȱ‘Žȱ–˜œȱ’–™˜›Š—ȱŽěŽŒȱ‘Šȱ’ŸŽœȱ‘Žȱ›ŽŠ•’¢ȱ˜ȱ‘ŽȱœŒŽ—Žȱ’œȱŠȱ•˜‹Š•ȱ’••ž–’Ȭ —Š’˜—ȱŽěŽŒȱ‘Šȱœ’–ž•ŠŽœȱŠ—¢ȱ›ŽĚŽŒ’˜—ǰȱœŒŠĴŽ›’—ȱŠ—ȱ›Ž›ŠŒ’˜—ȱ˜ȱ•’‘ǯȱ —ȱ‘ŽȱŸŠ—ŒŽȱŽ—Ž›Ž›ǰȱ ŽȱŒŠ—ȱŒ‘˜˜œŽȱ ˜ȱ Š¢œȱ˜ȱŒŠ•Œž•Š’—ȱ•˜‹Š•ȱ’••ž–’—ŠȬ ’˜—DZȱ ››’’Š—ŒŽȱŠŒ‘ŽȱŠ—ȱžŠœ’ȱ˜—ŽȱŠ›•˜ǯȱ‘Žȱꛜȱ–˜Ž•ȱŒ›ŽŠŽœȱ›ŽŒ˜›œȱ˜—ȱŸ’œȬ ’‹•Žȱœž›ŠŒŽœȱ’—ȱŠȱ’ŸŽ—ȱ›Š—ŽǯȱŠŒ‘ȱœžŒ‘ȱ›ŽŒ˜›ȱ ’••ȱ‹ŽȱœŽ—ȱ’—ȱŠ—¢ȱ’›ŽŒ’˜—ȱ˜Œ‘Šœ’Œȱ Š–™•Žœȱǻ›Š—˜–ȱ›Š¢œǼǯȱŠŒ‘ȱ›Š¢ȱŒ˜••ŽŒœȱ’—˜›–Š’˜—ȱŠ‹˜žȱ‘ŽȱŒ˜•˜›ȱŠ—ȱœ›Ž—‘ȱ˜ȱ ‘Žȱ•’‘’—ǰȱ ‘’Œ‘ȱ›ŽŠǰȱŠ••’—ȱ˜ȱ‘Žȱœž›ŠŒŽȱŠ—ȱŒ›ŽŠŽœȱŠ—ȱŠŸŽ›ŠŽȱ™˜ Ž›ȱ˜ȱŒ˜•˜›ȱ Š—ȱ•’‘’—ȱ˜ȱ‘Žȱ›ŽŒ˜›ǯȱ‘ŽȱœŽŒ˜—ȱ–Ž‘˜ǰȱŒŠ••Žȱœ‘˜›•¢ȱȱŒ˜—œ’œœȱ’—ȱŒ›ŽŠ’—ȱ ˜—Žȱ‹’ȱ›ŽŒ˜›ȱ˜›ȱ‘ŽȱŽ—’›ŽȱœŒŽ—ŽȱœŽŽ—ȱ‹¢ȱ‘ŽȱŒŠ–Ž›Šǯȱ‘’œȱ›Žšž’›ŽœȱŒ‘Š—Žȱ‘ŽȱœŽȬ ’—œȱŠȱ•Š›Žȱ—ž–‹Ž›ȱ˜ȱœŠ–™•Žœȱ˜ȱŽ•ŽŽȱ‘Žȱ›Š’—ǰȱœ˜ȱ›Ž—Ž›’—ȱžœ’—ȱ‘’œȱŠ•˜›’‘–ȱ œ’—’ęŒŠ—•¢ȱŽ¡Ž—œȱǽśǾǯȱ —˜‘Ž›ȱžœŽž•ȱŽěŽŒȱ’œȱ‘Žȱ–‹’Ž—ȱŒŒ•žœ’˜—ǯȱ ȱŒ˜—œ’œœȱ’—ȱ˜‹žœŒŠ’˜—ȱœž’Š‹•Žȱ ™•ŠŒŽœǰȱŒ›ŽŠ’—ȱœ‘Š˜ œȱ ’‘˜žȱ•’‘ȱœ˜ž›ŒŽœǯȱ‘Žȱ‹Šœ’œȱ˜ȱ‘ŽȱŠ•˜›’‘–ȱ’œȱŠȱŸ’›žŠ•ȱ ›Š¢ȱ‘Šȱ’œȱœŽ—ȱ›˜–ȱ‘Žȱ™•Š—Žȱ˜ȱꗍȱ˜‘Ž›ȱ‘Žȱ—ŽŠ›Žœǯȱ ȱ’ȱ ’••ȱꗍȱŒŠžœŽȱœ‘Š’—ȱ‘Šȱ ™Š›ȱ˜ȱ‘Žȱ™•Š—Žȱ›˜–ȱ ‘’Œ‘ȱ’ȱ ŠœȱœŽ—ǯȱ‘ŽȱŽ›ŽŽȱ˜ȱ˜™ŠŒ’¢ȱŠ—ȱŒ˜•˜›ȱ’œȱŠěŽŒŽȱ ‹¢ȱ–Š—¢ȱŠŒ˜›œǰȱ’—Œ•ž’—ȱ’œŠ—ŒŽȱŠ—ȱ‘Žȱ Š••œȱ‘ŽȱŠ—•Žȱ˜ȱŒ˜——ŽŒ’˜—ǯȱ‘’œȱŽěŽŒȱ ‘’‘•’‘œȱ‘ŽȱŒ˜——ŽŒ’˜—ȱ˜‹“ŽŒœȱ›˜–ȱ‘Žȱ›˜ž—ȱŠ—ȱŸŠ›’˜žœȱœ–Š••ȱ™Š›œȱǽŝǾǯ ‘Žȱ˜™’˜—ȱ‘Šȱ’–™›˜ŸŽœȱ™Ž›ŒŽ™’˜—ȱ™›ŽœŽ—ŽȱœŒŽ—Žȱ’œȱž—˜ž‹Ž•¢ȱ‘ŽȱŠ‹’•’¢ȱ ˜ȱœ–˜˜‘ȱ‘ŽȱŽŽœȱ˜ȱ‘ŽȱŽœŒŠ•Š˜›ȱ‘›˜ž‘ȱŠ—’Š•’Šœ’—ȱŠ•˜›’‘–ǯȱ ȱ’œȱœ’••ȱ‹Ž’—ȱ ŽŸŽ•˜™Žǯȱ••˜ œȱœ–˜˜‘ȱ‘ŽȱŽŽœȱ˜ȱ˜‹“ŽŒœǯȱ˜Š¢ȱ’ȱ’œȱ™˜œœ’‹•Žȱ˜ȱœ–˜˜‘’—ȱȱ 42 M. Ilba transparent elements and textures on surfaces. Without it, the visualization of cer- tain types of analyzes cannot be properly understood. For enhancing the att ractiveness of our scenes, we can use a number of simula- tions of atmospheric physics eff ects, which are polluted air, fog, smoke, water vapor and clouds. These eff ects allow us to get bett er control over the photorealism scene, emphasizing the problem and simulation of phenomena occurring on the visualized area. Examples are air pollution in the city, moving fog in mountain ranges, fi re and smoke in areas aff ected by the fi res. Using multiple eff ects it also has its drawbacks. For one of them we can include rendering time. Some scenes require generation of a few hours. Another downside is that the excess of diff erent eff ects can obscure the main issue presented in the image of the analysis performed. Therefore, all eff ects and glamourizing the scene should be chosen carefully in order not to unnecessarily lengthen the rendering time and not to overshadow, but highlight the problem presented. In Figure 3 we can see an example of the algorithm renderer, contained in the CAD software, in the process of visualization objects holiday village. The picture was created using the GIS spatial data about the location of each element, and objects (trees, texture) were added at a later stage in the CAD software Cinema 4D. Time image rendering lasted about 30 minutes.

Fig. 3. Visualize the location and placement buildings designed holiday resort

3. Cooperation ArcGIS Software with the Program Cinema4D

By doing the analysis of various types, to a lot of software, we are not forced to use for everything only one software. There is no question that the program will ArcScene bett er suited to do analyzes, prepare data for visualization, while the ren- dering algorithm application Cinema4D – to generate an image presenting the re- sults of analyzes. ž™™˜›ȱ˜›ȱ›ŽŠŽȱřȱ˜–™žŽ›ȱ ›Š™‘’Œœȱ –ŠŽœȱ’—ȱ ȱ¢œŽ–œȱœ’—ȱ¡Ž›—Š•œǯǯǯ Śř

‘Ž—ȱŒ›ŽŠ’—ȱřȱœŒŽ—Žȱ’—ȱ›ŒŒŽ—ŽȱŠ™™•’ŒŠ’˜—ǰȱ ŽȱŒŠ—ȱ˜—ŽȱœŽ™ȱ˜ȱŽ¡™˜›ȱ’ȱ ŠœȱŠȱęȱ•ŽȱȱǻȘǯ ›•ǼȱŠ—ȱ‘Ž—ȱ•˜Šȱ’—˜ȱ‘Žȱ™›˜›Š–ȱ’—Ž–ŠŚǯȱ‘Žȱ˜—•¢ȱ™›˜‹•Ž–ȱ ’—ȱ‘Žȱ’–™˜›ȱęȱ•Žȱ’œȱ—˜ȱ™˜’—ȱŽ•Ž–Ž—œȱŠ—ȱœ¢–‹˜•œǰȱ ‘’Œ‘ȱ–Š¢ȱ’—ȱŒŽ›Š’—ȱ™›˜“ŽŒœȱ Œ˜–™•’ŒŠŽȱ‘Žȱ™›˜ŒŽœœȱ˜ȱ’–™˜›’—ȱŠŠǯȱŠœ’•¢ȱŽ¡™˜›ȱŠȱ•Š¢Ž›ȱ˜ȱřȱŽ˜–Ž›¢ȱŠ—ȱ ™˜•¢˜—œȱŠ—ȱ ’‘ȱ’—˜›–Š’˜—ȱŠ‹˜žȱ‘ŽȱŒ˜•˜›œǯȱ ‘ŽȱœŒŽ—Žȱ‹Ž˜›Žȱ›Ž—Ž›’—ȱŒŠ—ȱ›Ž–˜Ž•ǰȱŠ“žœȱŒ˜•˜›ȱŠ—ȱ•’‘’—ǰȱ’—œŽ›ȱŠ’Ȭ ’˜—Š•ȱ˜‹“ŽŒœȱ˜›ȱ™›˜›Š–ȱŠȱœŽšžŽ—ŒŽȱ˜ȱ’–ŠŽœȱ’ȱ Žȱ Š—ȱ˜ȱŒ›ŽŠŽȱŠ—ȱŠ—’–Š’˜—ǯȱ‘Žȱ ęȱ—’œ‘Žȱ›Ž—Ž›’—ȱŒŠ—ȱ‹ŽȱœŠŸŽȱŠœȱŠ—ȱ’–ŠŽȱ˜›ȱ–˜Ÿ’Žȱęȱ•Žȱ’—ȱŠ—¢ȱœ’£Žȱ˜ȱž™ȱŗŘŞȱŖŖŖȱƼȱ ŗŘŞȱŖŖŖȱ™’¡Ž•œǯȱ —ȱ’ž›ŽœȱŚȮŜȱœ‘˜ ȱŽ¡Š–™•Žœȱ˜ȱ‘ŽȱŸ’œžŠ•’£Š’˜—ȱœ˜ Š›Žȱ›ŒŒŽ—Žȱ ™›Ž™Š›ŽǰȱŠ—ȱžœ’—ȱŠ—ȱŠ•˜›’‘–ȱ’—Œ•žŽȱ’—ȱ‘Žȱœ˜ Š›Žȱ›Ž—Ž›Ž›ȱ’—Ž–ŠŚǯȱ —ȱ ™Š›ȱȃŠȄȱ˜ȱ‘Žȱ›Š ’—œȱžœŽȱ ȱœ˜ Š›ŽȱŠ–’•¢ȱ›ŒŒŽ—ŽǰȱŠ—ȱ™Š›ȱȃ‹Ȅȱ ŠœȱžœŽȱ ˜ȱ‹ž’•ȱŠ—ȱŠ•˜›’‘–ȱ˜›ȱ›Ž—Ž›’—ȱŠ—ȱ’–ŠŽȱ›˜–ȱŠ—ȱŠ™™•’ŒŠ’˜—ȱ’—Ž–ŠŚǯȱ –ŠŽȱ ›Ž—Ž›’—ȱ’–Žȱǻ™Š›ȱȃ‹ȄǼȱ Šœȱ˜›ȱ’ž›ŽȱŚȱŗǯśȱ–’—žŽœǰȱ˜ȱ’ž›Žȱśȱ˜ȱŠ‹˜žȱŘŖȱ–’—žŽœǰȱ Š—ȱ˜›ȱ’ž›ŽȱŜǰȱ‘Žȱ›Ž—Ž›’—ȱ’–ŽȱŽ¡ŒŽŽŽȱŚŖȱ–’—žŽœǯȱ

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’ǯȱŚǯȱ’œžŠ•’£Š’˜—ȱ‹ž’•’—ȱ ’‘ȱŠŒŒŽ—ȱ˜—ȱ’ěȱŽ›Ž—ȱ‘Ž’‘œȱ˜ȱ‹ž’•’—œȱ žœ’—ȱ‘ŽȱŒ˜•˜›ȱ™Š•ŽĴȱŽ ŚŚ ǯȱ •‹Š

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’ǯȱśǯȱ’œžŠ•’£Š’˜—ȱ˜ȱ ŠŽ›ȱ•ŽŸŽ•ȱŠ—ȱ•Š—œŒŠ™Žȱ˜ȱŠȱ•Š”Žǯȱ —ȱ‹˜‘ȱŒŠœŽœǰȱ‘Žȱœž›ŠŒŽȱ ˜ȱ‘ŽȱęȱŽ•ȱ ŠœȱžœŽȱ˜ȱŽ—Ž›ŠŽȱ’’Š•ȱŽ››Š’—ȱ–˜Ž•ȱ’—ȱ‘Žȱ˜›–ȱ  

’ǯȱŜǯȱ’œžŠ•’£Š’˜—ȱ˜ȱ‘ŽȱŒ’¢ȱ›£Ž–¢ï•ȱ ’‘ȱŠ™™•¢’—ȱ‘Žȱ’—ŸŽœ–Ž—ȱ›ŠŒŽ›ŠŒ” ž™™˜›ȱ˜›ȱ›ŽŠŽȱřȱ˜–™žŽ›ȱ ›Š™‘’Œœȱ –ŠŽœȱ’—ȱ ȱ¢œŽ–œȱœ’—ȱ¡Ž›—Š•œǯǯǯ Śś

—ȱ’ž›Žȱśȱ ŽȱŒŠ—ȱœŽŽȱ‘ŽȱŠŸŠ—ŠŽȱ˜ȱȱŠ™™•’ŒŠ’˜—œǰȱ—Š–Ž•¢ȱ ŠŽ›ȱ›ŽĚŽŒȬ ’˜—œȱ‘Šȱ–Š¢ȱ‘ŠŸŽȱ–˜›ŽȱŠĴ›ŠŒ’ŸŽȱ’–ŠŽǯȱ —ȱ’ž›ŽȱŜǰȱ ŽȱŒŠ—ȱœŽŽȱ‘Šȱž›’—ȱ’–™•ŽȬ –Ž—Š’˜—ȱ ˜ȱ ŠŸŠ—ŒŽȱ Ÿ’œžŠ•’£Š’˜—ȱ Š›Žȱ žœŽǰȱ ’—Ž›ȱ Š•’Šǰȱ řȱ ˜‹“ŽŒœȱŠœȱ‹ž’•’—œǰȱ ›ŽŽœǰȱŠ—ȱ˜‘Ž›ȱ˜‹“ŽŒœȱ˜ȱ•Š—ȱžœŽǯȱ••ȱꐞ›Žœȱ‘ŠŸŽȱ‹ŽŽ—ȱ™›Ž™Š›Žȱ‹¢ȱ‘ŽȱŠž‘˜›ǯ

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