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Don't Look Down 2008 108029: The Movie That Takes You on a Flying Adventure with Antonella Costa and



By default, Premiere Pro uses a 24p pulldown scheme to play back 24p DV footage at 29.97 fps in a project based on one of the NTSC presets. You can disable the pulldown scheme to give your movie the look of a film transferred to video or broadcast, without frame interpolation.




don't look down 2008 108029




Not having the same standard across the world does mean there are some issues when translating from one to another. It is easier to throw away the 5 frames of video when transcoding from NTSC to PAL (30 FPS down to 25 FPS), than it is to create frames that don't exist when transcoding from PAL to NTSC (25 FPS up to 30 FPS). Often specialized equipment is needed to help this go smoothly.


For a certain risk group switching off the machine becomes nearly impossible. Time has come to have a closer look at player profiles: Who plays and how often? The average player is about college age (17-21) or older (22.3 years appr.), male (84%), and spends 20.2 hours (16.9) a week mudding.[116] Both social and adventure (hack and slash) MUDs are equally popular in the US. Germany stays behind with almost no social MUDs. But unlike Americans (where I have no data about racial differentiation apart from guessing that players are overwhelmingly white and affluent), German players will be 97% white. My dated sources point to the fact that students are about the only group with Internet access, but in 1999 far more people are connected. Still there are strong arguments for the student suggestion because we have free access and don't pay for our amusement other than with time. Additional players are to be found in computer-based professions, where they either program or process data and have a telnet window open on their screen all day. One finds such "idle" players that simply don't respond when addressed and may use the "finger" command to see how long they have been present but inactive. There is even a player who calls himself "BigIdler" in Wunderland.


Viewed 1000+ timesYou Asked Hello Tom !Good to see that i can ask a question....its a long time after that i am having opportunity to ask you a question.Here is the Statspack report for my session:DB Name DB Id Instance Inst Num Release OPS Host------------ ----------- ------------ -------- ----------- --- ------------STARR 1193708462 starr 1 8.1.7.2.1 NO STARR2 Snap Id Snap Time Sessions ------- ------------------ -------- Begin Snap: 77 17-Apr-03 15:31:49 66 End Snap: 78 17-Apr-03 15:57:21 66 Elapsed: 25.53 (mins)Cache Sizes db_block_buffers: 13000 log_buffer: 1048576 db_block_size: 8192 shared_pool_size: 70483955Load Profile Per Second Per Transaction --------------- --------------- Redo size: 4,519.98 9,551.19 Logical reads: 3,979.81 8,409.75 Block changes: 13.10 27.68 Physical reads: 88.17 186.31 Physical writes: 1.94 4.11 User calls: 5.51 11.65 Parses: 0.91 1.92 Hard parses: 0.03 0.06 Sorts: 0.14 0.29 Logons: 0.14 0.30 Executes: 6.98 14.74 Transactions: 0.47 % Blocks changed per Read: 0.33 Recursive Call %: 68.76 Rollback per transaction %: 0.41 Rows per Sort: #######Instance Efficiency Percentages (Target 100%) Buffer Nowait %: 100.00 Redo NoWait %: 99.81 Buffer Hit %: 97.78 In-memory Sort %: 99.52 Library Hit %: 99.47 Soft Parse %: 96.84 Execute to Parse %: 86.98 Latch Hit %: 99.97Parse CPU to Parse Elapsd %: 0.15 % Non-Parse CPU: 99.99 Shared Pool Statistics Begin End ------ ------ Memory Usage %: 65.16 65.80 % SQL with executions>1: 52.46 52.54 % Memory for SQL w/exec>1: 58.24 58.40Top 5 Wait Events Wait % TotalEvent Waits Time (cs) Wt Time----------------------------------- --------- --------- SQL*Net message from dblink 3,718 134,049 71.99db file sequential read 96,742 27,535 14.79enqueue 77 10,868 5.84log file sync 1,068 4,003 2.15db file scattered read 5,880 2,757 1.48 ------------------------------------------------Latch Activity for DB: STARR Instance: starr Snaps: 77 -78->"Get Requests", "Pct Get Miss" and "Avg Slps/Miss" are statistics for willing-to-wait latch get requests->"NoWait Requests", "Pct NoWait Miss" are for no-wait latch get requests->"Pct Misses" for both should be very close to 0.0 Pct Avg Pct Get Get Slps NoWait NoWaitLatch Name Requests Miss /Miss Requests Miss----------------------------- -------------- ------ ------ ------------ ------enqueue hash chains 166,702 1.2 0.0 0enqueues 25,168 0.3 0.0 0library cache 94,235 0.9 0.0 0session allocation 3,107 3.4 0.0 0shared pool 4,945 0.8 0.0 0Latch Sleep breakdown for DB: STARR Instance: starr Snaps: 77 -78-> ordered by misses desc Get Spin &Latch Name Requests Misses Sleeps Sleeps 1->4-------------------------- -------------- ----------- ----------- ------------enqueue hash chains 166,702 2,066 35 2031/35/0/0/ 0checkpoint queue latch 15,739 2 1 1/1/0/0/0 -------------------------------------------------------------SGA breakdown difference for DB: STARR Instance: starr Snaps: 77 -78Pool Name Begin value End value Difference----------- ------------------------ -------------- -------------- -----------java pool free memory 32,768 32,768 0large pool free memory 15,214,400 15,214,400 0shared pool DML locks 583,200 583,200 0shared pool KGFF heap 9,812 9,812 0shared pool KGK heap 17,532 17,532 0shared pool KQLS heap 2,071,340 2,078,720 7,380shared pool PL/SQL DIANA 788,208 788,208 0shared pool PL/SQL MPCODE 974,636 974,636 0shared pool PL/SQL PPCODE 55,028 55,028 0shared pool PLS non-lib hp 2,096 2,096 0shared pool PX msg pool 69,200 69,200 0shared pool PX subheap 10,044 10,044 0shared pool State objects 1,219,760 1,219,760 0shared pool db_block_buffers 1,768,000 1,768,000 0shared pool db_block_hash_buckets 339,096 339,096 0shared pool db_files 370,988 370,988 0shared pool db_handles 500,000 500,000 0shared pool dictionary cache 1,412,720 1,420,900 8,180shared pool distributed_transactions 2,160,152 2,160,152 0shared pool enqueue_resources 425,088 425,088 0shared pool event statistics per ses 3,801,200 3,801,200 0shared pool fixed allocation callbac 960 960 0shared pool free memory 32,081,580 31,484,988 -596,592shared pool ktlbk state objects 520,020 520,020 0shared pool library cache 7,228,320 7,374,548 146,228shared pool miscellaneous 2,077,004 2,085,408 8,404shared pool network connections 890,880 890,880 0shared pool processes 808,000 808,000 0shared pool sessions 2,382,380 2,382,380 0shared pool sql area 23,915,128 24,340,848 425,720shared pool table columns 26,284 26,744 460shared pool table definiti 14,756 14,916 160shared pool transaction_branches 4,416,000 4,416,000 0shared pool transactions 1,083,780 1,083,780 0shared pool trigger defini 46,300 46,300 0shared pool trigger inform 1,308 1,368 60 db_block_buffers 106,496,000 106,496,000 0 fixed_sga 75,804 75,804 0 log_buffer 1,048,576 1,048,576 0 -------------------------------------------------------------SGA Memory Summary for DB: STARR Instance: starr Snaps: 77 -78SGA regions Size in Bytes------------------------------ ----------------Database Buffers 106,496,000Fixed Size 75,804Redo Buffers 1,056,768Variable Size 107,335,680 ----------------sum 214,964,252 ------------------------------------------------------------What are your suggestiones w.r.t:(1) Top 5 events (specially enques)(2) Database Block Buffer Size & Redo Buffer Size(3) SGA Size(4) Latches ActivityDo i have problems with sizing ? Please Advise.Regards and Tom said...well, given that enqueue waits are a measely 5% of the total waits... I wouldn't be as concerned about them as the dblink usage. Anyway -- enqueue waits mean you have "blockers" and "blockees" -- people going after the same exact row(s). It doesn't happen often but when it does -- it takes a second or more to resolve. This is an application issue, you are going after a shared resource and are forcing yourself to wait for it.The low hanging fruit here is the message from dbink -- you are waiting for a process that is running on the remote machine. It is taking a long time to return the result. You did the statspack on the wrong database perhaps -- you need to tune the remote system!Buffer cache analysis is inconclusive since a cache hit ratio cannot confirm or deny that "all is good". with a 100MB buffer cache and a 97%+ hit, it is not the cause of a problem. That is about all you can say about that -- it is probably not too small, could be larger then it needs to be.You blew out the rows per sort - that is cause for concern. you'll want to look at your SQL to figure out why that is.And your soft parse % is rather low if this system has been running for any period of time. Rating (87 ratings)Is this answer out of date? If it is, please let us know via a Comment Comments Comment Your expoert opinion needed...againRiaz Shahid, June 23, 2003 - 6:44 am UTC


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