What Are We Doing with (Or To) the F-Scale?
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Disability Classification System
CLASSIFICATION SYSTEM FOR STUDENTS WITH A DISABILITY Track & Field (NB: also used for Cross Country where applicable) Current Previous Definition Classification Classification Deaf (Track & Field Events) T/F 01 HI 55db loss on the average at 500, 1000 and 2000Hz in the better Equivalent to Au2 ear Visually Impaired T/F 11 B1 From no light perception at all in either eye, up to and including the ability to perceive light; inability to recognise objects or contours in any direction and at any distance. T/F 12 B2 Ability to recognise objects up to a distance of 2 metres ie below 2/60 and/or visual field of less than five (5) degrees. T/F13 B3 Can recognise contours between 2 and 6 metres away ie 2/60- 6/60 and visual field of more than five (5) degrees and less than twenty (20) degrees. Intellectually Disabled T/F 20 ID Intellectually disabled. The athlete’s intellectual functioning is 75 or below. Limitations in two or more of the following adaptive skill areas; communication, self-care; home living, social skills, community use, self direction, health and safety, functional academics, leisure and work. They must have acquired their condition before age 18. Cerebral Palsy C2 Upper Severe to moderate quadriplegia. Upper extremity events are Wheelchair performed by pushing the wheelchair with one or two arms and the wheelchair propulsion is restricted due to poor control. Upper extremity athletes have limited control of movements, but are able to produce some semblance of throwing motion. T/F 33 C3 Wheelchair Moderate quadriplegia. Fair functional strength and moderate problems in upper extremities and torso. -
Storm Wind Loads on Trees Thought by the Author to Provide the Best Means for Considering Fundamental Tree Health Care Issues Surrounding Tree Biomechanics
TreesTreesTrees &&& StormStormStorm WindWindWind LoadsLoadsLoads by Dr. Kim D. Coder Professor of Tree Biology & Health Care Warnell School of Forestry & Natural Resources, University of Georgia MAINE WASH. MN. VT. ND. NH. MICH. MONT. MASS. NY. 3 CT. RI. OR. WS. MICH. 2 NJ. ID. 1 SD. PA. WY. IOWA OH. DL. 5 NB. MD. IL. IN. W. NV. VA . VA . UT. CO. 6 KY. KS. MO. NC. CA. TN. SC. ARK. OK. 0 GA. AZ. AL. NM. 7 MS. TX. 8 4 LA. 9 FL. 10 Coder Storm Intensity Map of composite potential risks for tree damage. This publication is an educational product designed for helping tree professionals appreciate and understand basic aspects of tree mechanical loading during storms. This educational product is a synthesis and integration of weather data and educational concepts regarding how storms wind loads impact trees. This product is for awareness building and educational development. At the time it was finished, this publication contained information regarding storm wind loads on trees thought by the author to provide the best means for considering fundamental tree health care issues surrounding tree biomechanics. The University of Georgia, the Warnell School of Forestry & Natural Resources, and the author are not responsible for any errors, omissions, misinterpretations, or misapplications from this educational product. The author assumed professional users would have some basic tree structure and mechanics background. This product was not designed, nor is suited, for homeowner use. Always seek the advice and assistance of professional tree health providers for tree care and structural assessments. This educational product is only for noncommercial, nonprofit use and may not be copied or reproduced by any means, in any format, or in any media including electronic forms, without explicit written permission of the author. -
The Fujita Scale Is Used to Rate the Intensity of a Tornado by Examining the Damage Caused by the Tornado After It Has Passed Over a Man-Made Structure
The Fujita Scale is used to rate the intensity of a tornado by examining the damage caused by the tornado after it has passed over a man-made structure. The "Percentage of All Tornadoes 1950- 1994" pie chart reveals that the vast majority of tornadoes are either weak or do damage that can only be attributed to a weak tornado. Only a small percentage of tornadoes can be correctly classed as violent. Such a chart became possible only after the acceptance of the Fujita Scale as the official classification system for tornado damage. It is quite possible that an even higher percentage of all tornadoes are weak. Each year the National Weather Service documents about 1000 tornado touchdowns in the United States. There is evidence that 1000 or more additional weak tornadoes may occur each year and go completely undocumented. The "Percentage of Tornado-Related Deaths 1950-1994" pie chart shows that while violent tornadoes are few in number, they cause a very high percentage of tornado-related deaths. The Tornado Project has analyzed data prior to 1950, and found that the percentage of deaths from violent tornadoes was even greater in the past. This is because the death tolls prior to the introduction of the forecasting/awareness programs were enormous: 695 dead(Missouri-Illinois-Indiana, March 18, 1925); 317 dead(Natchez, Mississippi, May 7, 1840);.255 dead(St. Louis, Missouri and East St. Louis, Illinois, May 27, 1896); 216 dead(Tupelo, Mississippi, April 5, 1936); 203 dead(Gainesville, GA, April 6, 1936). In more recent times, no single tornado has killed more than 50 people since 1971. -
Decision Tree Learning– Solution
Decision Tree Learning{ Solution 1) Assume that you have the following training examples available: F1 F2 F3 F4 F5 Class Example 1 t t f f f p Example 2 f f t t f p Example 3 t f f t f p Example 4 t f t f t p Example 5 f t f f f n Example 6 t t f t t n Example 7 f t t t t n Use all of the training examples to construct a decision tree. In case of ties between features, break ties in favor of features with smaller numbers (for ex- ample, favor F1 over F2, F2 over F3, and so on). How does the resulting decision tree classify the following example: F1 F2 F3 F4 F5 Class Example 8 f f f t t ? Answer: Let H(x; y) denote the entropy of a data set with x examples belonging to class p and y examples belonging to class n. That is, x x y y H(x; y) = − log − log : x + y 2 x + y x + y 2 x + y We precompute the values for some H(x; y), which will be useful when con- structing the decision tree. H(0; x) = H(x; 0) = −1 log2 1 − 0 log2 0 = 0 H(x; x) = −(1=2) log2 (1=2) − (1=2) log2 (1=2) = 1 H(1; 2) = H(2; 1) = −(1=3) log2 (1=3) − (2=3) log2 (2=3) = 0:918 H(1; 3) = H(3; 1) = −(1=4) log2 (1=4) − (3=4) log2 (3=4) = 0:811 First, we choose from f F1, F2, F3, F4, F5 g to become the root. -
Reframing Sport Contexts: Labeling, Identities, and Social Justice
Reframing Sport Contexts: Labeling, Identities, and Social Justice Dr. Ted Fay and Eli Wolff Sport in Society Disability in Sport Initiative Northeastern University Critical Context • Marginalization (Current Status Quo) vs. • Legitimatization (New Inclusive Paradigm) Critical Context Naturalism vs. Trans-Humanism (Wolbring, G. (2009) How Do We Handle Our Differences related to Labeling Language and Cultural Identities? • Stereotyping? • Prejudice? • Discrimination? (Carr-Ruffino, 2003, p. 1) Ten Major Cultural Differences 1) Source of Control 2) Collectivism or Individualism 3) Homogeneous or Heterogeneous 4) Feminine or Masculine 5) Rank Status 6) Risk orientation 7) Time use 8) Space use 9) Communication Style 10) Economic System (Carr – Ruffino, 2003, p.27) Rationale for Inclusion • Divisioning by classification relative to “fair play” and equity principles • Sport model rather than “ism” segregated model (e.g., by race, gender, disability, socio-economic class, sexual orientation, look (body image), sect (religion), age) • Legitimacy • Human rights and equality Social Dynamics of Inequality Reinforce and reproduce Social Institutions Ideology Political (Patriarchy) Economic Educational Perpetuates Religious Prejudice & Are institutionalized by Discrimination Cultural Practices (ISM) Sport Music Art (Sage, 1998) Five Interlinking Conceptual Frameworks • Critical Change Factors Model (CCFM) • Organizational Continuum in Sport Governance (OCSG) • Criteria for Inclusion in Sport Organizations (CISO) • Individual Multiple Identity Sport Classifications Index (IMISCI) • Sport Opportunity Spectrum (SOS) Critical Change Factors Model (CCFM) F1) Change/occurrence of major societal event (s) affecting public opinion toward ID group. F2) Change in laws, government and court action in changing public policies toward ID group. F3) Change in level of influence of high profile ID group role models on public opinion. -
19.4 Updated Mobile Radar Climatology of Supercell
19.4 UPDATED MOBILE RADAR CLIMATOLOGY OF SUPERCELL TORNADO STRUCTURES AND DYNAMICS Curtis R. Alexander* and Joshua M. Wurman Center for Severe Weather Research, Boulder, Colorado 1. INTRODUCTION evolution of angular momentum and vorticity near the surface in many of the tornado cases is also High-resolution mobile radar observations of providing some insight into possible modes of supercell tornadoes have been collected by the scale contraction for tornadogenesis and failure. Doppler On Wheels (DOWs) platform between 1995 and present. The result of this ongoing effort 2. DATA is a large observational database spanning over 150 separate supercell tornadoes with a typical The DOWs have collected observations in and data resolution of O(50 m X 50 m X 50 m), near supercell tornadoes from 1995 through 2008 updates every O(60 s) and measurements within including the fields of Doppler velocity, received 20 m of the surface (Wurman et al. 1997; Wurman power, normalized coherent power, radar 1999, 2001). reflectivity, coherent reflectivity and spectral width (Wurman et al. 1997). Stemming from this database is a multi-tiered effort to characterize the structure and dynamics of A typical observation is a four-second quasi- the high wind speed environments in and near horizontal scan through a tornado vortex. To date supercell tornadoes. To this end, a suite of there have been over 10000 DOW observations of algorithms is applied to the radar tornado supercell tornadoes comprising over 150 individual observations for quality assurance along with tornadoes. detection, tracking and extraction of kinematic attributes. Data used for this study include DOW supercell tornado observations from 1995-2003 comprising The integration of observations across tornado about 5000 individual observations of 69 different cases in the database is providing an estimate of mesocyclone-associated tornadoes. -
Storm Data and Unusual Weather Phenomena ....…….…....……………
MAY 2006 VOLUME 48 NUMBER 5 SSTORMTORM DDATAATA AND UNUSUAL WEATHER PHENOMENA WITH LATE REPORTS AND CORRECTIONS NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION noaa NATIONAL ENVIRONMENTAL SATELLITE, DATA AND INFORMATION SERVICE NATIONAL CLIMATIC DATA CENTER, ASHEVILLE, NC Cover: Baseball-to-softball sized hail fell from a supercell just east of Seminole in Gaines County, Texas on May 5, 2006. The supercell also produced 5 tornadoes (4 F0’s 1 F2). No deaths or injuries were reported due to the hail or tornadoes. (Photo courtesy: Matt Jacobs.) TABLE OF CONTENTS Page Outstanding Storm of the Month …..…………….….........……..…………..…….…..…..... 4 Storm Data and Unusual Weather Phenomena ....…….…....……………...........…............ 5 Additions/Corrections.......................................................................................................................... 406 Reference Notes .............……...........................……….........…..……........................................... 427 STORM DATA (ISSN 0039-1972) National Climatic Data Center Editor: William Angel Assistant Editors: Stuart Hinson and Rhonda Herndon STORM DATA is prepared, and distributed by the National Climatic Data Center (NCDC), National Environmental Satellite, Data and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA). The Storm Data and Unusual Weather Phenomena narratives and Hurricane/Tropical Storm summaries are prepared by the National Weather Service. Monthly and annual statistics and summaries of tornado and lightning events -
Probable Maximum Precipitation Estimates, United States East of the 105Th Meridian
HYDROMETEOROLOGICAL REPORT 'N0.53 L D ..... 'C..,p "\ ..u o tM/ 'A1 ws/t.d/M 'b !>"'"'"' , , 1 1 ~, 5 E.~..~t:-west J/.,e; h~ s,J~ ..s, .... ~ ,41'b ~·qto Seasonal Variation of 10-Square-Mile Probable Maximum Precipitation Estimates, United States East of the 105th Meridian ,_ U.S. DEPARTMENT OF COMMERCE, , -- NATIONAL OCEANIC AND ATMOS~HERIC ADMINISI'RATION U.S. NUCLEAR REGULATORY COMMISSION - , - Silver Spnng, Md , , Apn11980 U.S. Department of Commerce U.S. Nuclear Regulatory National Oceanic and Atmospheric Commission Administration NUREG/CR-1486 Hydrometeorological Report No. 53 SEASONAL VARIATION OF 10-SQUARE-MILE PROBABLE MAXIMUM PRECIPITATION ESTIMATES) UNITED STATES EAST OF THE 105TH MERIDIAN Prepared by Francis P. Ho and John T. Riedel Hydrometeorological Branch Office of Hydrology National Weather Service Washington, D.C. April 1980 TABLE OF CONTENTS Page Abstract. 1 1. Introduction . 1 1.1 Authorization. 1 1.2 Purpose. 1 1.3 Scope ••... 1 1.4 Definitions .. 2 1.5 Previous study 2 2. Basic data . 2 2.1 Background • • • • • . 2 2.2 Available station rainfall data •• 3 2.2.1 Storm rainfall • • • • • 3 2.2.2 Maximum 1-day or 24-hour values, each month ••••••• 3 2.2.3 Maximum 6-, 12- and 24-hr values, each month . 3 2.2.4 11aximum recorded rainfall at first-order stations. 3 2.2.5 Data tapes, selected stations. 3 2.2.6 Data tapes, 1948-73 •. 5 2.2.7 Canadian data. 5 3. Approach to PMP. • ••. 5 3.1 Summary. 5 3.2 Selected major storm values •. 5 3.3 Moisture maximization. -
The Population Bias of Severe Weather Reports West of the Continental Divide
THE POPULATION BIAS OF SEVERE WEATHER REPORTS WEST OF THE CONTINENTAL DIVIDE Paul Frisbie NOAAlNational Weather Service Weather Forecast Office Grand Junction, Colorado Abstract and had 'significant consequences. Lightning from thun derstorms that afternoon sparked the Marble Cone fire Many severe storms in the West may go unreported or (several miles south of Camp Pico Blanco) that burned unobserved, and therefore, the severe weather climatology 177,866 acres - the third largest wildfire in California's is not fully understood. However, as the population has history (California Department of Forestry and Fire increased in the West, so has the number of severe weath Protection 2004). er reports. To check if a population bias exists, correlation The aforementioned cases illustrate the challenges of coefficients are calculated with respect to population for establishing a relevant severe weather climatology for tornadic and nontornadic severe storm activity. The sam the western US. Since no one knows how many severe ple size for tornadic storms is too small to draw any con storms go unreported or unobserved, there is uncertainty clusion. To calculate the correlation coefficients for non regarding the number of severe storms that actually do tornadic severe storms, population and severe weather occur. People have been gradually moving into areas that data are used for every county in each western state were once unpopulated, and are now observing severe between the years 1986-1995 and 1996-2004. The calcu storms that would not have been observed beforehand. To lated correlation coefficients reveal that population and provide a better understanding of how often severe the number ofnontornadic severe storms are significantly weather occurs, trends for tornadic and nontornadic correlated which indicates that a population bias does severe storms will be examined. -
Connexion Client Cataloging Quick Reference
OCLC Connexion Client Cataloging Quick Reference Introduction Keystroke shortcuts The Connexion client is a Windows-based interface to OCLC • Use default keystroke shortcuts or assign your own to activate Connexion® used to access WorldCat for cataloging. commands, insert characters, run macros, and insert text strings. This quick reference provides brief instructions for editing, saving, • View key assignments in View > Assigned Keys.To print or copy exporting, and printing labels for bibliographic records; using local files; the list, click Print or Copy to Clipboard. creating and adding records to WorldCat; replacing WorldCat records; Tip: Before printing, click a column heading to sort the list by data batch processing; and cataloging with non-Latin scripts. in the column. • Assign your own keystrokes in Tools > Keymaps. Multiscript support: The client supports the following non-Latin scripts: • Print a function key template to put at the top of your keyboard: Arabic, Armenian, Bengali, Chinese, Cyrillic, Devanagari, Ethiopic, Greek, Hebrew, Japanese, Korean, Syriac, Tamil, and Thai. www.oclc.org/support/documentation/connexion/client/ gettingstarted/keyboardtemplate.pdf. This quick reference does not cover instructions for authorities work or instructions already available in: Toolbar • Getting Started with Connexion Client • The client installs with three toolbars displayed by default: • Connexion Client Setup Worksheet o Main client toolbar (with command-equivalent buttons) • Connexion: Searching WorldCat Quick Reference o WorldCat quick search tool Quick tools for text strings and user tools Connexion client documentation assumes knowledge of MARC o cataloging. • Customize the main client toolbar: In Tools > Toolbar Editor, drag and drop buttons to add or remove, or reset to the default. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Tornadoes & Downburst
TORNADOES & DOWNBURST TORNADOES • A devastating F5 tornado about 200 meters wide plows through Hesston, Kansas, on March 13, 1990, leaving almost 300 people homeless and 13 injured. • Total destruction caused by an F5 tornado that devastated parts of Oklahoma on May 3, 1999. • A tornado is a violently rotating (usually counterclockwise in the northern hemisphere) column of air descending from a thunderstorm and in contact with the ground. Although tornadoes are usually brief, lasting only a few minutes, they can sometimes last for more than an hour and travel several miles causing considerable damage. In a typical year about 1000 tornadoes will strike the United States. The peak of the tornado season is April through June and more tornadoes strike the central United States than any other place in the world. This area has been nicknamed "tornado alley." Most tornadoes are spawned from supercell thunderstorms. Supercell thunderstorms are characterized by a persistent rotating updraft and form in environments of strong vertical wind shear. Wind shear is the change in wind speed and/or direction with height. • Tornadoes are natures most destructive weather hazard. Annual Number of Tornadoes per State (upper number) • Tornado incidence by state. The upper figure shows the number of tornadoes reported by each state during a 25-year period. The lower figure is the average annual number of tornadoes per 10,000 square miles. The darker the shading, the greater the frequency of tornadoes. • Average number of tornadoes during each month in the United States. Fujita Scale F0-F1 Fujita scale is a measure of tornado intensity Winds 60 - 115 mph quantified through a subjective analysis of relating tornadic damage to wind speed.