zilongwang/ReadingBank huggingface dataset:
Open SQL Server Management Studio. Note the deployment script in Lab Module 1 creates the SQL Server name using the define prefix + SQL + a 4-character hash. To view your server name, visit your Resource Group created by the deployment script on . You should be prompted to connect to a server. If not, click the File menu -> Connect Object Explorer. Fill in the server name and sqlusername and password created in Lab Module 1. Click the File Menu -> Open -> File. Browse to the Lab Module 9 folder from the downloaded Lab material and open the Module9query.sql file. You should see all the queries we will be running as part of this lab module. Highlight each query one at a time and run the query. Each step here will assume one query was run and discuss the purpose in the notes. To run use the Execute Icon or F5. This query returns a count of all the flights in our FlightFact table. If you did not modify the package in Lab Module 2 this should contain flight data for December 2016. The contains date for all of 2016 but the SSIS package only copied data for December 2016 to the ODS. Highlight and run Query 1 – Fact Count This query returns the top 100 airports by originating airport on the flight. Highlight and run Query 2 – Busiest Origin Airports This query returns the top 20 most used models by manufacturer. The dimension was our original set of FAA files from the Amazon S3 account that was later merged together via Hive. Highlight and run Query 3 – Most Used Planes This query returns the Average delay for each day in December at MSP along with the weather data source from our REST source. Highlight and run Query 4 – Average Delay by Day in MSP and Weather
Permanent (perennial) streams may not be labeled but are always shown with solid blue lines – intermittent streams (not shown above) are marked with dash-dot line – mark a perennial stream PS If the V or U shape in the contours points uphill, the topographic feature is a valley - streams often connect these points – mark an upward pointing U or V shape as UU or UV If the V or U shape in the contours points downhill, the feature is the nose of a hill – you will never see a stream here – mark a downward pointing V or U shape as DV or DU Contours never cross – if you see a line crossing contours, it is a stream or man-made feature such as a road – mark one of these crossings XC Sometimes you may see a loop with tic marks along the inside – this is a depression – mark one of these (a bit hard to find) with a D Visualizing in 3-D based on 2-D contours Delineate a small watershed - Delineate the watershed of the small stream at the point shown (i.e. draw a line that encloses all the area from which runoff will flow to the point): Model Watershed Features (If time permits) - For the following two topographic features, use Play-Doh to create an accurate 3-D model of the contours shown (note, this can now also be done using a digital elevation map and 3D printer): Tools: Pencil (NOT pen!) & a good eraser General method (practice makes perfect): Draw small arrows all over the map indicating the direction of maximum slope at each point Based on your arrows, locate the “drainage divides”, the topographic features such as hills and ridges that divide flow between adjacent streams – rough sketch in these boundaries first so you know the general shape of the watershed Now carefully sketch your way uphill from the point of interest, always perpendicular to contour lines For hills and other contour loops or bends, draw the boundary such that it divides these features in half Check that the watershed boundary is everywhere perpendicular to contour lines and does not cross any drainage divides
think of mail slots in a large mail room. Your computer has memory that the program is going to use to create and store information. When you create a variable, you are assigning one of the “slots” of memory to a name and then can put a value in that slot and modify it as needed. Why create variables? Variables allow the programmer to make the value modifiable in the script. For example, you want to be able to update a score variable as the player wins/loses in a game. You will see many different uses of variables during this course. You have multiple blocks to create and manipulate variables in the Variables tab palette. Make a variable button allows you to create a new variable Delete a variable button will allow you to delete a button – this button only shows after you have created a variable. Set [] to (0) will allow you to initialize, or set a beginning value, the variable to a value. Change [] by (1) allows you to modify the value of a variable Show variable [] will show the variable and value on the stage. hide variable [] will hide the variable and value on the stage. Script variables (a) will allow you to create local variables, more on this use later To create a variable In the box that pops up - type the name of the variable. The default selection “for all sprites” means that all sprites have access to this variable. Select “for this sprite only” if you want only the sprite currently selected to be able to access/modify the value of the variable. Now you’ll have blocks to use for your variable. Note that you now have a rounded button with the name of the variable in the window with a checkbox to the left. If checked, the variable and value will be show on the stage. Uncheck to hide. When you use one of the variable blocks you will be able to click on the combo box arrow for a list of your variables. Script Variables Sometimes you need a variable in your script, but you don’t want it to step through consecutive integer values as in the for block. A more general way to handle variables uses the block to create a variable, and the block to give that variable a value. Both of these blocks are in the Variables palette. Here’s an
AP Computer Science Lab15a Java Assignment The "Magic Square" Program 80, 100 & 110 Point Versions Assignment Purpose: The purpose of this program is to manipulate two-dimensional static arrays. Write a program that creates odd-sized Magic Squares. A magic square is a square matrix of consecutive numbers, such that the numbers in the rows, the numbers in the columns, and the numbers in the diagonals add up to the same sum. For this program you will only be concerned with “odd-sized” magic squares. Odd-sized refers to the size of the matrix, such as a 3 X 3, a 5 X 5, and 9 X 9 or 13 X 13 sized matrix. Examples of a 3 X 3 magic square and a 5 X 5 magic square are shown below: 8 1 6 3 5 7 4 9 2 Every row, column and diagonal in the 3 X 3 matrix adds up to 15. 17 24 1 8 14 23 5 7 14 16 4 6 13 20 22 10 12 19 21 3 11 18 25 2 9 Every row, column and diagonal in the 5 X 5 matrix adds up to 65. The magic square program is quite challenging, and comes in two different levels of difficulty. It is very important that you first are able to create magic squares, of any odd size, yourself on paper. On the next page is a five-step algorithm to create an odd magic square. Study these steps carefully and use them to create magic squares on paper. Only after you are confident that you understand the magic square algorithm, are you ready to proceed to write a program.
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Education, Training and Earnings - See: Chapter 9, Benjamin, Gunderson, Lemieux and Riddell Human Capital : - Skills. - Usually concerned with acquired skills. - Economic models of education and training are models of skill acquisition. - Affects the labour supply side of the market. - Determines how many people will have a particular type of skill. - Important implications for earnings: affects the type and value (productivity) of work people can do. - Modeling these decisions: - Education and training are viewed as investment decisions. - Investment: give up something now in the expectation of some future return. Education as an Investment: - Post-secondary education is usually the concern: - Why? Outcome of choice not compulsion! - Framework can still be used to think about returns from lower levels of education
Discount rate (i): 2% 4% 8% 12% (i=.02) (i=.04) (i=.08) (i=.12) Years from now (n): 0 10000 10000 10000 10000 1 9804 9615 9259 8929 2 9612 9246 8573 7972 3 9423 8890 7938 7118 4 9238 8548 7350 6355 5 9057 8219 6806 5674 10 8203 6756 4632 3220 20 6730 4564 2145 1037 30 5521 3083 994 334 - Refer to i as the “discount rate”. i.e. that rate at which you could invest $ now in a similarly risky investment. - The value now of the benefits of education (incurred period 0 to R): B0 + + …+ - The value now of the costs of education (incurred periods 0 to g): C0 + + …+ Net Present Value of Investment = B0 + + …+ - C0 - … - this can be calculated given estimates of the Bs and Cs and choice of a discount rate (i).
- If unions are viewed positively (aside from any monetary benefits they may bring) the prospects for unionization will be better. e.g., vs. United States? Are Americans more anti-union? Alberta vs. Quebec vs. Parts of Europe vs. North America. - Are there spillovers here? - are attitudes contagious? (Holmes, 2006) - Public attitudes may also affect collective bargaining legislation. (3) Worker's anticipated labour force attachment - Short tenure: is unionization is less likely? - unionization as an investment: less time to accrue benefits - costs now in terms of union dues, lost income if there is a strike, etc. - less time to reap benefits of unionization. - high cost of organizing high turnover groups. Possible examples of groups with low unionization and low attachment: - young workers, fast food industry workers. (4) Non-union pay and working conditions: - These can affect the expected benefits and demand for unionization.
Figure 1.49 Figure 1.50 Figure 1.51 When completed, select “Browse all devices” icon on the left side menu of GNS3, then you should see the ipterm in the “installed appliances” list. If the ipterm icon does not appear in the list after step 4, quit GNS3 and restart GNS3 again. The ipterm icon should appear in the appliances list as shown in Figure 1.52. Figure 1.52 Rename ipterm to PC using the following steps and remove “-“ from Default name format in Figure 1.55. Figure 1.53 Figure 1.54 Figure 1.55 You will see the following screens. Click OK. Figure 1.56 Figure 1.57 Create a new project. Figure 1.58 Give your project a name for example “pcsetup” as shown in Figure 1.59 and Click OK. Figure 1.59 Expand Browse End Devices and drag and drop PC icon to project window as shown in Figure 1.60. Note: GNS3 automatically numbers all devices.
SG 3a (θ = _______) SG 3b (θ = _______) εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error Table 5. Measured vs. Predicted Strains at Strain Gauge 4 for Round tube SG 4a (θ = _______) SG 4b (θ = _______) εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error Table 6. Measured vs. Predicted Strains at Strain Gauge 1 for C-Channel SG1a (θ = _______) SG 1b (θ = _______) SG 1c (θ = _______) εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error Table 7. Measured vs. Predicted Strains at Strain Gauge 2 for C-Channel SG2a (θ = _______) SGb (θ = _______) SG2c (θ = _______) εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error Table 8. Measured vs. Predicted Strains at Strain Gauges 3 and 4 for C-Channel SG3 (θ = _______) SG4 (θ = _______) εmeas (με) εθ (με) Percent Error εmeas (με) εθ (με) Percent Error
Table A.3. Material Properties of Aluminum Elastic Modulus, E (MPa) 69000 Yield Strength (0.2%offset), σo (MPa) 275 Poisson's ratio, υ 0.33 Ultimate Tensile Strength, σu (MPa) 324 Percent Elongation, %el (50.8mm gage length) 12 Appendix B: Free Body Diagram & Applied Load The applied load P for each beam design is found from solving the equations of static equilibrium and the force reading at the load cell, RLC. Figure B.1 Free-body diagram of 3-pt loaded beam. To find the applied load, the sum of the moments about A gives (B.1) To find the reaction force at A, the sum of the forces in the y-direction gives (B.2) The values for each load cell measurement for the round tube and C-channel are given in Table B.1 and B.2, respectively. Table B.1. Applied Loads for Round tube RLC (N) P (N) RA (N)
Psy 231 Lab Assignment 8 1. What two things does a z-score tell us about the relative standing of a particular raw score? 2. For a particular group of scores, M = 20 and SD = 5. Give the corresponding z-score for a) x = 30, b) x = 15, c) x = 20, and d) x = 22.5. Please show your work. 3. Write the formula for changing a z-score to a raw score, and define each of the symbols. 4. For a particular group of scores, M = 10 and SD = 2. Give the raw score for a) z = +2.0, b) z = +.5, c) z = 0, and d) z = -3.0. Please show your work.
Figure 3: Resistors with 4 bands, 5 bands and 6 bands of color code. 2) To practically study the color rings on resistors and read the resistance and tolerance values of various resistors using color code. Procedure i) Take some assorted resistors available in laboratory. Hold a resistor in your hand and read the color rings (bands) by referring to table T.1.1. ii) Read the color rings/bands on the resistors left to right one by one and record the ring color and its value in the table T 1.2 shown below. Note down the Nominal resistance value (R Nominal ) and tolerance of the resistor in the table. iii) Repeat the above procedure for few more resistors. iv) Write down your observation. 1st color band 2nd color band 3rd color band 4th color band 5th color band Value (R Nominal) in Ohms Tolerance in 1 2
Scroll up or down to find the city with a population that is closest to and greater than 50,000. What city had just over 50,000 people in 2000? Select the city by clicking on the left-hand column (all the way to the left – the “grey column” without any column name). When selected, all information for that city will be highlighted in blue in the attribute table. Scroll to the top (or bottom depending on how you sorted your data) of the attribute table. While pressing and holding down the Shift key on your keyboard, click on the largest city – this will select all of the cities with a population greater than 50,000. How many cities are selected? Without changing the selected features, close the attribute table. What color are the selected features on the map? Now you are going to create a new shapefile that contains only the Cities with a population of larger than 50,000 people. Right-click on the Cities layer in the TOC, and go to Data > Export Data. In the Export Data window, export “Selected features” and use the same coordinate system as “this layer’s source data”. Click on the button with the yellow folder icon to open the Saving Data window. Browse to the folder for your flash drive, save as type “Shapefile”, and name the new shapefile “LargeCities”. Click the “Save” button to close the Saving Data window, then click the OK button to close the Export Data window. When prompted, click “Yes” to add the exported data to the map as a layer. Remember: When saving files in ArcGIS, only use alphanumeric and no special characters (e.g. large_cities1 NOT Large Cities $) Click on the Clear Selected Features tool on the Tools toolbar.
(This space intentionally left blank.) 2.1 Prototype Architecture Description The TPOT prototype is planned to have nearly the same structure and feature set as the real world product. Table 1 shows a direct comparison between the two. The major differences are the prototype's reliance on ODU virtual machines for hosting and its use of simulated data. Features/Components Real World Product Prototype Student Team Members Actual students participating in online project-based coursework Actual student testers and TPOT team members using virtual test machines with past project data and data Instructor Instructors leading online project-bases courses Professor Pazos as well as TPOT team members simulating the instructor role Team Sites The Google Site tool created by Dr. Pazos with embedded Google Apps Scripts which structure the data teams generate The same tool and scripts Instructor Dashboard A tabbed, fully customizable dynamic web page which concisely presents data drawn from the team sites A tabbed dynamic web page which concisely presents data drawn from the team sites Google Apps Scripts A series of JS-like scripts which collect, structure, and store in the TPOT database the data generated by teams which interact with the team sites The same scripts
Figure 4. High pass filter Configure the waveform generator on the oscilloscope with following settings: Waveform = Sine Frequency = 1Hz, 10Hz, 100Hz, 1KHz, 10KHz, 100KHz and 1MHz Amplitude = 3V p-p Offset = 0V Connect the waveform generator output to the input of high pass filter. Connect channel 1 input (X) of the oscilloscope to the output of high pass filter and connect channel 2 input (Y) of the oscilloscope to the input of high pass filter. Measure V1 and V2 on the input and output of high pass filter by using the measurement function on the oscilloscope. It is more suitable to use AC to measure V1 and V2. In your lab report: Fill the table below: Frequency (Hz) V1 (Volt) V2 (Volt) Gain (dB) (G = dB) 1 10 100 1K 10K 100K 1M Plot the Frequency Response curve using semi log graph or use Excel to plot the graph. Explain why the gain of high pass filter drop significantly at very high frequency. Adjust the frequency of Wave Gen on the oscilloscope to find out the Corner frequencies of high pass filter, and . Where is the Corner frequency at lower frequency range and is the Corner frequency at higher frequency range. The Corner frequency is defined as the frequency at V2/V1 = 0.707. Measure the Corner frequency of this high pass filter found
Sales_order_details Column name Datatype Size Attributes S_order_no Varchar2 6 Primary key/foreign key references s_order_no of sales_order Product_no Varchar2 6 Primary key/foreign key references product_no of product_master Qty_order Number 8 Qty_disp Number 8 Product_rate Number 10,2 Insert the following data into their respective tables: Data for sales_man master table: no Salesman name Address City Pin code State 500001 Kiran A/14 worli Bombay 400002 Mah 3000 100 50 Goo 500002 Manish 65,narim an Bombay 400001 Mah 3000 200 100 Goo 500003 Ravi P-7 Bandra Bombay 400032 Mah 3000 200 100 Goo 500004 Ashish A/5 Juhu Bombay 400044 Mah 3500 200 150 Goo Data for salesorder table: S_orderno S_orderdate Client no Dely type Bill yn no Delay date Orderstatus 019001 12-jan-96 0001 F N 50001 20-jan- 96 Ip 019002 25-jan-96 0002 P N 50002 27-jan- 96 C 016865 18-feb-96 0003 F Y 500003 20-feb- 96 F 019003 03-apr-96 0001 F Y 500001 07-apr- 96 F 046866 20-may-96 0004 P N 500002 22- may-96 C 010008 24-may-96 0005 F N 500004 26- may-96 Ip Data for sales_order_details table: S_order no Product no Qty ordered Qty disp Product_rate 019001 P00001 4 4 525 019001 P07965 2 1 8400 019001 P07885 2 1 5250
Some Major Hurricanes GALVESTON 1900 ATLANTIC-GULF 1919 MIAMI 1926 SAN FELIPE-OKEECHOBEE 1928 FLORIDA KEYS LABOR DAY 1935 NEW ENGLAND 1938 GREAT ATLANTIC 1944 CAROL AND EDNA 1954 HAZEL 1954 CONNIE AND DIANE 1955 AUDREY 1957 DONNA 1960 CAMILLE 1969 AGNES 1972 ALICIA 1983 GILBERT 1988 HUGO 1989 ANDREW 1992 OPAL 1995 MITCH 1998 FLOYD 1999 KEITH 2000 IRIS 2001 ISABEL 2003 CHARLEY 2004 FRANCES 2004 DENNIS 2005 KATRINA 2005 RITA 2005 WILMA 2005 IKE 2008 IRENE 2011 SANDY 2012
21. Make sure to rename the “Output Specification File” to something meaningful. Click on “OK“. 22. We can now create the clock tree. In the Synthesize Clock Tree window (which should still be open) make sure the “Clock Specification Files” field contains the name of the file you just generated. Leave all other values at their default s and click “OK”. 23. We can now do a timing optimization based on the clock tree we just made. Go to the “Optimize” pull down menu and select “Optimize Design”. Make sure "Post-CTS" is selected and click "OK". 24. We are finally ready to route our design. To do this we will use Nanoroute (there are several options but this is probably the best). Go to the “Route” pull down menu and select “Nanoroute” then select “Route”. We will use the default values. Click on “OK”.
27. Under the “Verify” pull down menu there are several verification functions. Use the default values and try the “Verify Geometry” and Verify Connectivity”. Once you have run both select the “Violation Browser” from the “Tools” pull down menu.
32. We have gone through a simplified design flow. There are many options that we haven’t had a chance to explore. It might be a good idea to take a look at some of the available options like RC extraction or the various routing options. Generally the last step in a design flow is to send a completed design to the fabrication facility. To do this the design is exported to a GDS2 file. To generate a GDS2 file we need a map file that relates layer names to numbers. Go to the “File” pull down menu select “Save” and then “GDS/OASIS…”. Name the output stream file anything you want (it should be related to what the design is) with the gds2 extension. Make sure the map file is “streamOut.map” and the “GDS Structure Name” is the name of your layout. click “OK”.
The Z-table (attached at the end of this lab) give the area to the left of 1.38. Look up 1.38 in the table, and we find that the area to the left of 1.38 is 0.9162. This leaves a percentage of 0.0838 to the right. Answer: 8.38% of days have a temperature above 76 degrees. Q5] Now it’s your turn. Approximately what percentage of the time are the temperatures in the pool: Greater than 78 degrees? Below 70 degrees? Between 60 and 70 degrees? Part 4 – Using R Commander The Rcmdr software package will compute normal probabilities as well. Let’s reconsider the example above, where the mean is 72.4, the standard deviation is 2.6, and we’re interested in the percentage of days above 76 degrees. Go to Distributions Continuous distributions Normal distribution Normal probabilities. Plug in the y value soon, along with the mean and standard deviation. If you want the percentage below 75 degrees, select the “lower tale” radio button. If you want the percentage above 75 degrees, use the “upper tale” radio button. We find that the percentage is 0.0831, similar to what we found by hand in Part 3 of this lab. Q6] Redo the parts of Q5 using R commander. Part 5 – Normal Percentiles The previous work of this lab gave us an observation value and asked for a percentage related to it. Example: What percentage of days would we expect to have a temperature of over 76 degrees?
PC2 10.0.2.10 / 24 PC3 10.0.3.10 / 24 PC4 10.0.4.10 / 24 Table 3.2 IP addresses for Part 4 Exercise 4. Observing forwarding loops Set up the network topology as shown in Figure 3.2 and configure the interfaces as shown in Table 3.2. Set up all the PC routing tables to allow communication between all 4 PCs. Configure the routing tables of Router2, Router3 and Router4, so that an ICMP Echo Request message generated by a ping from PC4 to PC1 creates an infinite loop. Issue a traceroute to verify that a loop exists: PC4% traceroute 10.0.1.10 You should observe that the traced path is a loop. Start Wireshark sessions on PC2, PC3, and PC4. Issue a ping from PC4 to PC1. You should observe the same ICMP Echo Request message looping in Wireshark. Save the routing tables of Router2, Router3 and Router4. Count the number of times you see the ICMP Echo Request message, as captured by Wireshark on PC4. Save at least two of these ICMP Echo Request messages. Lab Questions Are the two packets that you saved identical? If not, what is different? Why does the ICMP Echo Request packet not loop forever in the network? PART 5. NETWORK PREFIXES and ROUTING In this exercise you study how the network prefixes (netmasks) play a role when hosts determine if a datagram can be directly delivered or if it must be sent to a router. This part uses the network setup shown in Figure 3.3. The network includes one router, four hosts and two hubs. The IP addresses of all devices are given in Table 3.4. Here, each host has only a default route. In other words, the routing table at a host only knows about the directly connected networks and the default gateway.
Easy to read and understand Introduction Purpose of lab Vocabulary Describes the purpose of the lab in detail Explains any new vocabulary by working it into the lab report Describes the purpose of the lab, but misses detail Vocabulary is unclear, is not evident students understand Purpose is unclear, and lacks significant detail Vocabulary is presented in word definition form, or not explained Does not address the purpose Does not explain the new vocabulary Materials All materials used are listed in one clear concise list and accurate sketch is provided Most materials used are listed in a clear concise list and sketch is provided Some materials are listed, and/or list is not clear and poor sketch is provided Many materials are missing from list and no sketch is provided Methods Detailed In order Easy to Read/Follow Meets all three criteria Meets two criteria Meets only one of the criteria Meets none of the criteria Results All necessary results included Clear data tables (labeled) Units are on all measurements Meets all three criteria All 3 graphs are included and properly labeled. Meets two criteria All 3 graphs are included but labels and keys are missing/unclear. Meets only one of the criteria One graph is missing OR contains incorrect data. Meets none of the criteria Two graphs are missing OR contain incorrect data. Conclusion Results are clearly explained, any discrepancies are described Realistic suggestions for improvement are made Answers to all 6 conclusion questions from the lab are present, Results are explained, discrepancies are not completely described Suggestions for improvement are made, but missing detail Conclusion questions are present; but 2 are Results are unclearly explained Suggestions for improvements do not make sense or are lacking Conclusion questions are present; but 3-4 are either: missing, incorrect or not Results are incorrectly explained, or not explained Suggestions are not made moving forward Conclusion questions are present; but 3-4 are either: missing, incorrect or not incorporated where appropriate.
What is the average percentage of P that becomes Q? What is the average percentage of P that becomes ET? What is the range of variation of each? Why might the Q/P and ET/P ratios be varying from year to year (note: it is not because P varies, the question is why does the ratio vary)? List the assumptions we are making in the calculations. Do you think these are reasonable assumptions? Explain your answer. List 5 academic tools used throughout this lab session that were useful in addressing the problem presented. (example…working with large amounts of data) For your lab write-up, provide a short summary with your plots and answers to the five questions above. Due Date – Next Lab Session – Must be dropped of to my office no later than 1 hours after laboratory session.
Export the map and paste it in your lab document. Part II. Navigate Color Space Open exer2.mxd. This map document has five layers organized in the Specification – HSV data frame. Each layer in the data frame contains a different task. You will mix colors to complete the color schemes. The easiest way to access a symbol's color is to click the symbol next to a data value in the table of contents. a. Mix colors to create lightness steps for one hue In the table of contents, expand the L1H layer. Colors 11 and 15 are already specified. Your task is to create a color scheme that varies in lightness between the two endpoints. Think of this as a graduated color scheme you would use to represent quantitative data. Click the symbol for data value 12. In the Symbol Selector, click the Fill Color dropdown arrow, and choose More Colors. In the Color Selector, click the dropdown arrow to choose a color space. Choose HSV. You can create colors several different ways in the Color Selector. You can move the sliders for each dimension, you can enter numeric values in the percentage boxes, or you can click on the spectrum at the bottom. As you move the sliders, the color bar above each one updates to reflect the change. Several advanced settings are also available in the Color Selector. Although you will not use them in this exercise, it is useful to look at the controls. Click Cancel to close the Color Selector. Scroll down the list of preset symbols in the Symbol Selector and click Orange. Reopen the Color Selector. Click the right-facing arrow and choose Advanced Selection. Examine the controls available in the Select Color window. Click Cancel to close the Select Color window. Using the HSV sliders in the Color Selector, mix a color for data value 12. As you change the HSV settings, the color box in the bottom left corner will reflect the current color. Click OK when you're finished. In the Symbol Selector, the Fill color has updated to match the HSV values you chose. Change the Outline color to Gray 50%. Click OK. The color for data value 12 updates in the table of contents and in the map area. Repeat the color mixing process for data values 13 and 14. Create colors that vary in lightness between the endpoints. b. Create lightness steps through multiple hues in HSV
Set it up to use Country for location and UnitsOnOrder for values. Add another visualization the Multi-row Card to the page: Add the following fields to the Card: ProductName and UnitsOnOrder Finally, configure a page-level filter to only include data where UnitsOnOrder is > 0 You should now be able to click on a Country on the map and see which products and how many units are on order from that country! Part 3: On Your Own: Business Intelligence for Northwind Sales. In this part, build out an SQL Server Analysis Services cube for project for the Northwind Sales. As you’re accustomed to doing do in part 3’s of labs you must work out many of the details on your own. After you complete the cube, create an Excel Pivot table, and dashboard in Power View and Power BI Desktop. Add the FactSales, DimCustomer and DimEmployee tables to the current Northwind data source view: Build out the Customer and Employee dimensions as follows: NOTE: Customer should display Company Name Create the Northwind Sales cube as follows: Create an Excel worksheet Northwind-Sales.xlsx with A Pivot table setup to show interesting data with drill downs. A Power View Chart of your choosing. For example you should choose to show sales by day of the week. Do not create a map. Create a power BI desktop dashboard Northwind-Sales.pibx different from the Power View you created in Excel. Some criteria: Try using a tool not available in Power View like the map, treemap, or doughnut chart. Make it interactive. Selecting portions of the chart updates another chart, matrix or card. Good Luck!
Lab, Chapter 4 Section 2 Parameters Name: ___________________________________Date: ___________________________________ Exercises from Chapter 4 1. Complete Exercise 5. Beetle Band Duet: __________ 2. Complete Exercise 6. Frog Escape: __________ 3. Complete Exercise 8. Dragons: __________ Concept Questions (Short Answer) 4. List four types of parameters available in . 5. Why would we want to use a parameter in a method? 6. A parameter is sometimes described as "acting as a placeholder." What does this mean? 7. In a method call, what is the purpose of an argument? 8. Suppose a classmate missed the instructor's presentation on how to import a sound file. To help your friend learn this process, write a list of steps for importing a sound file. Include a diagram or sketch to illustrate the steps.
ACS-2814-002 Lab #6 Submit your responses to the questions below via an email to: yc9579@gmail.com Consider the database of swimming lessons found by http://ion.uwinnipeg.ca/~ychen2/access2814/Lab3.accdb. Relationship diagram: This database has two tables Program and Instructor. For each program there is a unique identifier, a description, an instructor, an assistant instructor, capacity, and the current registration. For each instructor there are ID, first name, last name, and birth date. Develop the following five queries: Query1 List each program that has less than 5 participants registered. Query2 List each program that is not full; for such a program the number registered is less than the capacity. Query3 List the description of any program where the instructor’s last name is “Walker”. Query4 List the last name of the assistants for those programs where “Walker” is the last name of the instructor. Query5 List the last name of the assistant for programs where the instructor is “Walker” and where the course is not full.
What will you do next time to improve how your group worked together? How much did you as an individual participate in the group? What can you do next time to improve your own performance in the lab group? Group Rubric: Poor 1 point Developing 2 points Good 3 points Excellent 4 points Group Rating (YOU RATE) Teacher Rating Contribution One or more members do not contribute. All members contribute, but some contribute more than others. All members contribute equally. All members contribute equally, and some even contribute more than was required. Cooperation Teacher intervention needed often to help group cooperate. Members work well together some of the time. Some teacher intervention needed. Members work well together most of the time. All members work well together all of the time; assist others when needed. On task Team needs frequent teacher reminders to get on task. Team is on task some of the time. Needs teacher reminders. Team is on task most of the time. Does not need any teacher reminders. Team is on task all of the time. Does not need any teacher reminders. Communication Members need frequent teacher intervention to listen to each other and speak to each other Members need some teacher intervention to be able to listen to each other and speak to All members listen to each other and speak to each other in equal amounts. Each member listens well to other members. Each member speaks in friendly and encouraging tones.
fish habitat riparian management zones (river buffers), ungulate habitat areas, red-listed species. Since we are only interested in displaying the total area that is protected, we can use the Dissolve command (under geoprocessing – dissolve, input is the union layer, use all defaults, OK). What is the percent of the project area the falls in the sum of the protected areas? How does this value compare with the sum of answers 2-5? Part 5 Representation QUESTION 8. (10) Produce a map to include in your report with the following elements within the project boundary. Use appropriate symbology to highlight only those areas that negatively affect the proposed ski hill. As a final step, we will create a 3D hillshade of the project area, and drape some of our datasets over the hillshade. Turn off all your layers In ArcToolbox, Raster Surface > Hillshade use the original DEM as the input raster, output raster call hillshade use defaults for everything else (for fun, do this again, name your output hillshadez3 and use a Z value of 3 – see how more of the area is very steep slope with the vertical exaggeration) Click the rivers layer to draw – you will see it ‘drapped’ on the hillshade. Do the same for Roads project boundary and the index contours contours (Hint: there are a lot of contours, so reduce the line weight and, select only the index contours to map) and snowline contour (closest to 555m). Click on the ungulate to drape over the hillshade. In order to ‘see’ the hillshading under the ungulate layer, make the UGL layer transparent: Layer properties > display > transparent type in 50%. Repeat for the old grown layer. Repeat for the generalized Red listed species Repeat for the fishery habitat Add a title and subtitle: Insert > text add a title Add a legend Export to a pdf or jpg
From the class data file postings, download the mat file lab5test.mat and load this into your workspace. This mat file contains 3 A-scans (in vectors (ta1, ta2, ta3) acquired with the same scanner used to collect the training data. Use the 2 filters developed in the previous problems to find the flaw locations for each A-scan. Indicate the estimated flaw position in millimeters for each file and include these results in the results section, as well as the plots of filtered A-scans used to locate the flaws. In estimating the location, the filter delay will cause a shift between the peak in the filtered signal and the actual position. Use the estimated filter delay computed in the previous exercise to correct for this delay in your location estimates. In the discussion section describe how confident you can be about your detection and estimation for each case. Clearly indicate what you are basing your confidence (or lack thereof) on. For the filters determined in Part 1, compute the group delay of the filter. This can be done with Matlab’s command >>[G,f] = grpdelay(b,a,N,fs). See the help files on it. This works similar to the freqz() command but it shows the delay in samples that an input signal frequency component will undergo in passing through the filter. For FIR filter the group delay will be constant over all frequencies resulting in an undistorted shift in time of the filtered flaw echo. For IIR filters the delay will be variable over the filter frequency range, but should be relatively constant over the passband. In determining the delay for the IIR filter, you should focus on the spectral region where the input signal contains the most energy. Plot the group delays for the 2 filters used in Part 1 in the results section. In the discussion section, describe whether these delays are consistent with the delays you actually found in Part 1.
At which point they have given away their user name and password… So how does this work? Let’s break this down step by step. The first thing we look for is a <div> ID in the swap manager page that we might use for the attack. The design view is like so… We don’t need access to the source code; we simply view the HTML in the client browser… Examining the HTML we can see a nice ID that we can use for the attack… <div> ID “Panel1” will do nicely. So compared to the original attack rather than generating a simple alert we could try the following java script… <script> var myText=document.getElementById("Panel1"); myText.innerHTML = Date(); </script> Or in this more malicious example we could use the code to produce a hyperlink that re-directs data entry from one server to another (DVD Swap to MyEvilServer)… <script> var myText=document.getElementById("Panel1"); myText.innerHTML = "<a href= http://localhost:1891/Default.html>There was a system error please click here to fix it</a>"; </script> There are much more subtle and sophisticated versions of this kind of attack. It is one of the most commonly exploited vulnerabilities of web based systems.
Assume 20 years of age and healthy. 3) Now what if the same two persons were 80 years of age and still healthy The predicted VC for the female is______. The predicted VC for the male is __________. 4) Now assume that the female is your 70 year old grandmother suffering from osteoporosis with associated kyphosis (curvature of the spine) and her measured F VC is 2.5 L. Consider the need for a large volume to compress in order to a large generate pressure gradient and a productive cough. Why is this low VC associated with a very poor ability to productive cough and greater mortality from things like pneumonia? 5) Now assume that the male is your 70 year old grandfather, getting ready for the senior Olympics (In Minneapolis this summer). His measured VC (not the predicted VC) is 4.5L. What would it mean in terms of ability your grandfather to run in 10k race? Why would this VC value be helpful in this regard?
DATA SHEET Exercise 6-1 - Chemical Height Control Observationsz Initial (0 wk) Date: Final ( wk) Date: New Growth (Final-Initial) Treatment Plant Label # Nodes Height # Nodes Height # Nodes Increase Height Increase Control (water spray) C-1 C-2 Avg Growth retardant foliar spray CF-1 CF-2 Avg Growth retardant soil drench CS-1 CS-2 Avg Gibberellic Acid (GA) foliar spray GA-1 GA-2 Avg Growth retardant soil drench and GA foliar spray CG-1 CG-2 Avg Plant Used: zRecord height in centimeters (cm).
run in client mode, connecting to the specified server -u, --udp use UDP rather than TCP -b, --bandwidth n[KM] set target bandwidth to n bits/sec (default 1 Mbit/sec for UDP, unlimited for TCP). If there are multiple streams (-P flag), the bandwidth limit is applied separately to each stream. You can also add a '/' and a number to the bandwidth specifier. This is called "burst mode". It will send the given number of packets without pausing, even if that temporarily exceeds the specified bandwidth limit. Setting the target bandwidth to 0 will disable bandwidth limits (particularly useful for UDP tests) -t, --time n time in seconds to transmit for (default 10 secs) -n, --bytes n[KM] number of bytes to transmit (instead of -t) -l, --length n[KM] length of buffer to read or write (default 128 KB for TCP, 8KB for UDP) -w, --window n[KM] window size / socket buffer size (this gets sent to the server and used on that side too) -M, --set-mss n set TCP maximum segment size (MTU - 40 bytes) FOR MORE INFORMATION libiperf(3), http://software.es.net/iperf NAME: telnet – remote login to host SYNOPSIS: telnet [options] [hostname] [port] OPTIONS: -e, --exec <command> executes the given command -l, --listen bind and listen for incoming connections -k, --keep-open accept multiple connections in listen mode -u, --udp use UDP instead of the default TCP Please note that iperf3 opens two different channels: a control channel and a data channel. The iperf3 command utilizes the control channel to configure the data stream, negotiate test
Module main() //Declare local variables Declare Integer counter = 0 Declare String studentName = “NO NAME” Declare Real averageRight = 0.0 Declare Real right = 0.0 Declare Integer number1 = 0 Declare Integer number2 = 0 Declare answer = 0.0 Set studentName = inputNames() //Loop to run program again While counter < 10 //calls functions Call getNumbers(number1, number2) Set answer = getAnswer(number1, number2, answer) Set right = checkAnswer(number1, number2, answer, right) Set counter = counter + 1 End While Set averageRight = results(right, averageRight) Call displayInfo(right, averageRight, studentName) End Module Function String inputNames(String studentName) Display “Enter Student Name:” Input studentName Return studentName End Function Module getNumber(Integer Ref number1, Integer Ref number2) Set number1 = random(1, 500) Set number2 = random(1, 500) End Module Function Integer getAnswer(Integer number1, Integer number2, Integer answer) Display “What is the answer to the following equation” Display number1 Display “+” Display number2 Display “What is the sum:” Input answer Return answer End Function
2. Calculate how much it would cost to run or leave an appliance in standby mode. The current rate for electricity is $0.10 per Kilowatt Hour (kWh). Record these values in Tables 2 and 3. Table 1 - Appliance Power Consumption Power Consumption (Watts) Daily Energy (KWH) Operating Power Standby power Run Time Hours/day Operating Standby Microwave 1200 5 0.1 TV LCD/Plasma 425 10 3.5 Computer 300 2 3 Laptop 225 7 1.5 Cell phone 5 0.5 0.25 Hair Dryer 1500 0 0.05 Fridge 525 0 24 Game Station 35 2.5 1 Desk light 60 0 2 Stereo 180 7.5 1.5 Alarm clock 100 0 24 Incandescent Bulb 100 0 4 LED Bulb 15 0 4 Water Heater 7500 0 4 Electric Range 5500 10 2
Table 2-Appliance Operating Energy Costs Weekly Energy Consumption (KWH) Annual Energy Consumption (KWH) Cost per day ($) Cost per Week ($) Cost per Year ($) Microwave TV LCD/Plasma Computer Laptop Cell phone Hair Dryer Fridge Game Station Desk light Stereo Alarm clock Incandescent Bulb LED Bulb Water Heater Electric Range
28. ---. Paper. “From Transfrontiersmen to Squatters: the Zululand Lands Delimitation Commission of 1902-1904 and the Land Claims of Long-standing Settlers in Zululand.” Biennial Conference of the South African Historical Society, Rhodes University, Grahamstown, July 1995. 29. ---. Paper. “Lord Chelmsford's Zululand Campaign 1878-1879.” 10th Annual General Meeting of the Army Records Society, King's College, University of London, November 1994. 31. ---. Chair of session, “Race and Gender.” .University of Edinburgh's Centre of Canadian Studies' Conference on Canada's Centuries: Periodisation as a Strategy for Understanding the Canadian Past, May 1994. 32, ---. Paper. “Myth Making and Authentic Zulu Histor.”18th International Conference on Large Dams, Shakaland, October 1994. 33. ---. Paper. “Territorial Resolution of Conflict between the uSuthu and Mandlakazi, 1879- 1904.” The Roots of Conflict History Workshop, University of Natal, Pietermaritzburg, October 1993. 34. ---. Paper. “Colin Webb as Environmental Historian.” 7th Biennial Conference of the Economic History Society of Southern Africa, University of Natal, Pietermaritzburg, July 1992. 35. ---. Paper. “'New Perspectives on the Anglo-Zulu War.” Annual Conference of the Natal History Teachers' Association, at St Mary's Diocesan School for Girls, Kloof, September 1991. 36. ---. Paper. “An Assessment of the Cohesion and Resilience of the Zulu Polity under the Impact of the British Invasion of 1879.” 58th Annual Meeting of the American Military Institute, Duke University, Durham, North Carolina, USA, March 1991. 37. ---. Paper. “The Zulu Strategic Response to the British Invasion of 1879.” History Workshop on Natal and Zululand in the Colonial and Pre-Colonial Periods, University of Natal, Pietermaritzburg, October 1990. J.P.C. Laband 16 August 2016
Directions: Answer all questions without a calculator in the given time. (-160) ÷ (-8) = 20 - (-19) = (-20) ÷ (-20) = (-4) - 19 = 9 + (-25) = (-21) + (-7) = (-12) • 21 = 11 • (-20) = 12 + 9 = 7 + (-13) = (-3) • (-16) = 125 ÷ (-25) = (-220) ÷ (-22) = (-15) + 1 = (-20) - 17 = (-11) - (-19) = 7 • 11 = 12 - (-4) = 72 ÷ 18 = (-22) - (-24) = (-5) • (-9) = (-13) • (-5) = (-11) • 18 = 150 ÷ (-25) = (-3) - 14 = (-10) + 3 = (-16) • (-18) = (-16) - 21 = (-264) ÷ (-12) = 3 • 25 =
307 307 Msg #|1|, Auto Release not allowed for accession UID |2|. Results have previously been released. A result (data packet) is transmitted from GIM which contains at least one result that has already been resulted or cancelled in VistA *NOTE* A single “previously verified” or “previously cancelled” result will invalidate Auto Release for ALL results present in a given data packet, regardless of their Auto Verification status or eligibility Compare the result on GIM and VistA, if needed issue an amended report thru VistA. Testing A test will be ordered in Vista and run on an instrument. The result should be one that does not pass the rule set and is held in IM Workspace. Once the result is held the tester will go into Vista and using EM result out the test. Once the test is resulted using EM the tester will release the result from IM. This should cause an error on the Vista side since the test will have a status of “Completed” making the result ineligible for processing. Vista should send an ACK ERR message back to Instrument Manager which should appear on the Status screen. 13 13 Msg #|1|, accession not found in file 68 for area |2| (Auto Instrument Name), date |3|, entry |4|, using LRUID A result has been released by the GID that does not exist in the corresponding Auto Instrument file Confirm the UID is correct. This error typically happens with UID numbers that do not correspond to a patient and erroneously passed through the Auto Verification logic. If necessary, modify Auto Verification rules so that only acceptable UID numbers pass through to VISTA.