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Color Sensing Robot vision systems often function only in grayscale, like old-fashioned 1950s television But color sensing can be added, in a manner similar to the way it is added to television systems Color sensing can help a robot with AI figure out what an object is Is that horizontal surface a parking lot, or is it a grassy yard Sometimes, objects have regions of different colors that have identical brightness as seen by a grayscale system Such objects, obviously, can be evaluated in more detail with a colorsensing system than with a vision system that sees only shades of gray In a typical color-sensing vision system, three grayscale cameras are used Each camera has a color filter in its lens One filter passes red light, another passes green light, and another passes blue light These are the three primary colors All possible hues, levels of brightness, and levels of saturation are made up of these three colors in various ratios The signals from the three cameras are processed by a microcomputer, and the result is fed to the robot controller The Eye-in-Hand System In order to assist a robot gripper (hand) in finding its way, a camera can be placed in the mechanism The camera must be equipped for work at close range, from about 1 m down to 1 mm or less The positioning error must be kept as small as possible To be sure that the camera gets a good image, lamps are included in the gripper along with the camera (Fig 34-9) This so-called eye-in-hand system can be used to precisely measure the distance between the gripper and the object it is seeking It can also make positive identification of the object The eye-in-hand system takes advantage of the properties of a servo The robot is equipped with, or has access to, a computer that processes the data from the camera and sends instructions back to the gripper Most eye-in-hand systems use visible light for guidance and manipulation Infrared (IR) can be used when it is necessary for the robot gripper to sense differences in temperature The Flying Eyeball In environments hostile to humans, robots find many uses, from manufacturing to exploration One such device, especially useful underwater, has been called a flying eyeball A cable, containing.

-- Breaks down buffers by object (table, index) in the buffer cache SELECT OBJECT_NAME(p.object_id) AS 'ObjectName', p.object_id, p.index_id, COUNT(*)/128 AS 'buffer size(MB)', COUNT(*) AS 'buffer_count' FROM sys.allocation_units AS a INNER JOIN sys.dm_os_buffer_descriptors AS b ON a.allocation_unit_id = b.allocation_unit_id INNER JOIN sys.partitions AS p ON a.container_id = p.hobt_id WHERE b.database_id = db_id() GROUP BY p.object_id, p.index_id ORDER BY buffer_count DESC

1 In AppleScript Editor, press z-N or choose File | New to create a new script 2 Press z-S or choose File | Save to display the Save As dialog box Navigate to the

SELECT TOP(100) [text], size_in_bytes FROM sys.dm_Exec_cached_plans CROSS APPLY sys.dm_exec_sql_text(plan_handle)

/Library/Scripts/Folder Action Scripts/ folder, and then save the script under a name of your choice

the robot in a special launcher housing, is dropped from a boat When the launcher gets to the desired depth, it lets out the robot, which is connected to the launcher by a tether The tether and the drop cable convey data back to the boat In some cases, the tether for a flying eyeball can be eliminated, and a wireless link can be used to convey data from the robot to the launcher The link is usually in the IR or visible red portion of the spectrum The robot contains a video camera and one or more lamps to illuminate the underwater environment It also has a set of thrusters (jets or propellers) that let it move around according to control commands sent from the boat Human operators on board the boat watch the images and guide the robot

WHERE cacheobjtype = 'Compiled Plan' AND objtype = 'Adhoc' AND usecounts = 1 ORDER BY size_in_bytes DESC

Again, using the new Optimize for Ad Hoc Workloads instance setting in SQL Server 2008 can really help if you have problems here. The query in listing 16 will show you your 25 most expensive queries from a logical reads perspective (which equates to memory pressure).

and using the variable name added_items with the after receiving parameter:

-- Get Top 25 executed SP's ordered by logical reads (memory pressure) SELECT TOP 25 qt.text AS 'SP Name', total_logical_reads, qs.execution_count AS 'Execution Count', total_logical_reads/qs.execution_count AS 'AvgLogicalReads', qs.execution_count/DATEDIFF(Second, qs.creation_time, GetDate()) AS 'Calls/Second', qs.total_worker_time/qs.execution_count AS 'AvgWorkerTime', qs.total_worker_time AS 'TotalWorkerTime', qs.total_elapsed_time/qs.execution_count AS 'AvgElapsedTime', qs.total_logical_writes, qs.max_logical_reads, qs.max_logical_writes, qs.total_physical_reads, DATEDIFF(Minute, qs.creation_time, GetDate()) AS 'Age in Cache' FROM sys.dm_exec_query_stats AS qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) AS qt WHERE qt.dbid = db_id() -- Filter by current database ORDER BY total_logical_reads DESC

Mobile robots must get around in their environment without wasting motion, without running into things, and without tipping over or falling down a flight of stairs The nature of a robot navigation system depends on the size of the work area, the type of robot used, and the sorts of tasks the robot is required to perform In this section, we ll look at four common methods of robot navigation

4 Add the end statement to end the event handler, as shown in boldface here:

The query in listing 17 will help you find tables with the most reads. (User scans are much more expensive than user seeks or lookups.)

SELECT object_name(s.object_id) AS 'Tablename', SUM(user_seeks) AS 'User Seeks', SUM(user_scans) AS 'User Scans', SUM(user_lookups)AS 'User Lookups', SUM(user_seeks + user_scans + user_lookups)AS 'Total Reads', SUM(user_updates) AS 'Total Writes' FROM sys.dm_db_index_usage_stats AS s INNER JOIN sys.indexes AS i ON s.object_id = i.object_id AND i.index_id = s.index_id WHERE objectproperty(s.object_id,'IsUserTable') = 1 AND s.database_id = db_id() GROUP BY object_name(s.object_id) ORDER BY 'Total Reads' DESC