Fs4: Fill & Download for Free

There is no standard. Manufacturers tend to use slightly different algorithms and treat them as trade secrets. But in practice, their algorithms are similar, because the theoretical optimization criteria are roughly the same:provide even service to each floorminimize how long passengers wait for an elevator to arriveminimize how long passengers spend to get to their destination floorserve as many passengers as possibleThe single elevator case is not very interesting, nor is the case when the passenger can't specify his direction of travel when making the call (one button per floor), so I'll instead discuss only the case where there are multiple elevators, and two buttons on each floor.There are several criteria to consider in elevator scheduling. For example, people have predictable behavioral patterns that must be addressed, including the uppeak and downpeak---respectively 9AM and 5PM, in many office buildings---which are when elevator efficiency matters the most. There is often a 1-2 hour two-way peak (lunchtime) to address as well. Algorithms should consider whether an elevator is full before assigning it to an elevator call. Sometimes, some blocks of floors have predictably higher interblock or intrablock traffic than other blocks. Often, calls on some floors (executive floors, for example) are given higher priority than others (basements). All of these factors increase the algorithm sophistication.Still, they tend to be based on the four classic group traffic control algorithms.Nearest Car (NC): Elevator calls are assigned to the elevator best placed to answer that call according to three criteria that are used to compute a figure of suitability (FS) for each elevator. (1) If an elevator is moving towards a call, and the call is in the same direction, FS = (N + 2) - d, where N is one less than the number of floors in the building, and d is the distance in floors between the elevator and the passenger call. (2) If the elevator is moving towards the call, but the call is in the opposite direction, FS = (N + 1) - d. (3) If the elevator is moving away from the point of call, FS = 1. The elevator with the highest FS for each call is sent to answer it. The search for the "nearest car" is performed continuously until each call is serviced.Fixed Sectoring Common Sector System (FSO): The building is divided into as many sectors as there are elevators. Elevators in each sector prefer calls in that sector.Fixed Sectoring Priority Timed System (FS4): The building is divided into up sectors and down sectors, and elevators only ever treat down calls in down sectors and up calls in up sectors. Each sector has a priority level, which increases the longer the passengers wait. The rate of increase can vary from sector to sector and over time.Dynamic Sectoring System (DS): Floors are grouped into dynamic sectors. Each elevator is allocated to a sector in the sector definition, and the sectors change size and location based on the position of moving and idle elevators.Modern control systems do even more than this. Some of them dynamically compute cost functions for passengers waiting on an elevator. Stochastic traffic control systems empirically compute the distribution of response times and try to make it as Gaussian as possible (wait times should be consistent; there shouldn't be some times when elevators respond instantly and others where they take a while). Some advanced techniques use fuzzy logic schedulers (Ho and Robertson 1994), genetic algorithms (Siikonen 2001, Miravete 1999), and neural networks (Barney and Imrak 2001).Most of this information is paraphrased from UK-based lift consultant Gina Barney's book "Elevator Traffic Handbook: Theory and Practice." A most uplifting read.

dbms_output.put_line('Fixed IO/SEC:'||to_char(fixed_io_per_sec,'9,999,999.99'));dbms_output.put_line('Temp IO/SEC :'||to_char(temp_io_per_sec, '9,999,999.99'));dbms_output.put_line('Total IO/SEC:'||to_char(tot_io_Per_Sec, '9,999,999.99'));dbms_output.put_line('FS1 Blocks = '||v_fs1_blocks);dbms_output.put_line('FS2 Blocks = '||v_fs2_blocks);dbms_output.put_line('FS3 Blocks = '||v_fs3_blocks);dbms_output.put_line('FS4 Blocks = '||v_fs4_blocks);dbms_output.put_line('Full Blocks = '||v_full_blocks);end;PL/SQL functions like the dbms_output.put_line procedure will also trims off white space.The leading and training spaces will be removed when placed in the buffer.Here is an example of dbms_output.put_line used to remove spaces:dbms_output.put_line (? This has spaces. ?);The above example Oracle dbms_output.put_line would remove the spaces before and after the phrase "This has spaces".

There’s a number, the inbreeding coefficient, that’s used to quantify inbreeding. The technical definition is “F measures the probability that two genes at any locus in an individual are identical by descent from the common ancestor(s) of the two parents.” You can get formulas from the site the quote came from.[1][1][1][1]This chart shows some sample genealogies for inbred individuals and the coefficients. It’s taken from a website which incorrectly claims that inbreeding cats might be a good idea, but the numbers here look correct to me.[2][2][2][2]If you like superheroes, there’s an article that discusses the degree of inbreeding among the X-men.[3][3][3][3]Warning: here comes technical materialThe numbers in that chart won’t be correct if the first set of parents are already inbred or related to each other. In that case, you have to go back to previous generations and sum up inbreeding. This article discusses how to do that.[4][4][4][4]You don’t have to marry cousins to become inbred. If people live in a village where the population has been small for many generations they will gradually become inbred over many generations even if everyone avoids marrying cousins. That’s because some genes gradually get lost on account of chance (bad luck). This set of formulas works in that situation. N is roughly the number of individuals in the population, though like everything else in genetics, calculating N can be complicated.[5][5][5][5]Footnotes[1] THE COEFFICIENT OF INBREEDING (F) AND ITS APPLICATIONS[1] THE COEFFICIENT OF INBREEDING (F) AND ITS APPLICATIONS[1] THE COEFFICIENT OF INBREEDING (F) AND ITS APPLICATIONS[1] THE COEFFICIENT OF INBREEDING (F) AND ITS APPLICATIONS[2] Pros and Cons of Inbreeding[2] Pros and Cons of Inbreeding[2] Pros and Cons of Inbreeding[2] Pros and Cons of Inbreeding[3] The Inbreeding Coefficient of Superheroes[3] The Inbreeding Coefficient of Superheroes[3] The Inbreeding Coefficient of Superheroes[3] The Inbreeding Coefficient of Superheroes[4] NSIF-FS4[4] NSIF-FS4[4] NSIF-FS4[4] NSIF-FS4[5] CSS 650 Advanced Plant Breeding Module 2: Inbreeding Small Populations –Random drift –Changes in variance, genotypes Mating Systems –Inbreeding coefficient. - ppt download[5] CSS 650 Advanced Plant Breeding Module 2: Inbreeding Small Populations –Random drift –Changes in variance, genotypes Mating Systems –Inbreeding coefficient. - ppt download[5] CSS 650 Advanced Plant Breeding Module 2: Inbreeding Small Populations –Random drift –Changes in variance, genotypes Mating Systems –Inbreeding coefficient. - ppt download[5] CSS 650 Advanced Plant Breeding Module 2: Inbreeding Small Populations –Random drift –Changes in variance, genotypes Mating Systems –Inbreeding coefficient. - ppt download