Algorithms Clause Samples

Algorithms. Except as included in Licensed Technology, access by Orchid to algorithms for data mining and for informatics is not included in the licenses granted herein, but may be the subject of a separate agreement, subject to any ▇▇▇▇▇▇▇ agreements with third parties.

Algorithms. We have identified several well-known algorithms that can be adapted to work with for online learning in the presence of imbalanced data. An alternative to algorithm modification is through sampling strategies. But sampling is typically performed as a preprocess to classification, and it does not fit the online context.

Algorithms. In this section, we propose efficient greedy algorithms to approximate the optimiza- tion objectives for both G-STAC and L-STAC.

Algorithms. We implemented ▇▇▇▇▇▇▇▇▇▇’s algorithm [27] for performing FLASM under the Ham- ming distance model. The pseudocode for this is presented below in Algorithm 5. Let D′[0 . . m][0 . . n] be a matrix, where D′[i][j] contains the Hamming distance between some factor x[max{0, j − ℓ} . . j − 1] of a string x and factor y[max{0, i − ℓ} . . i − 1] of string y, for all 1 ≤ j ≤ n, 1 ≤ i ≤ m. The naïve way to obtaining this matrix is through a straightforward O(mℓn)-time algorithm by constructing matrices Ds[0 . . ℓ][0 . . n], for all 0 ≤ s ≤ m − ℓ, where Ds[i][j] is the Hamming distance between some factor of x[j − ℓ . . j − 1] and the prefix of length i of y[s.. s + ℓ − 1]. We obtain D′ by collating D0 and the last row of Ds, for all 0 ≤ s ≤ m − ℓ. Matrix Ds can be obtained using the standard dynamic programming algorithm. We say that x[max{0, i − ℓ} . . i − 1] occurs in y ending at y[j − 1] with k mismatches iff D′[i][j] ≤ k, for all 1 ≤ i ≤ m, 1 ≤ j ≤

Algorithms. 3.1. Kadence is comprised of five principle algorithms for tuning (1) signal splits, (2) offsets, (3) cycle time, (4) phase sequence, and (5) time-of-day (▇▇▇ schedule). Second-by-second phase timing and detector data is polled from the controller, and new signal timing parameters are downloaded to field controllers every 3-4 cycles (minimum number of cycles is configurable by the user). The field controller then begins operating in an actuated-coordinated mode with the new settings. 3.2. Kadence does not send hold or force-off commands to controllers, or suppress phase calls, so there is no risk of a controller getting stuck in a certain phase. All controller features operate normally including pedestrians, transit priority, and preemption. Kadence can run alongside an existing central system on an IP network using NTCIP or AB3418 protocols, depending on what is supported by the field device. 3.3. Kadence detects the presence of queues by measuring the average occupancy on a queue detector. When the level of occupancy is consistently high (a user-configurable threshold of occupancy) for several minutes (a user-configurable threshold of time), IF…THEN logic conditions can be configured to put Kadence into a variety of congestion management modes by selecting a new response coordination pattern with associated configuration parameters for Kadence to begin metering, increase cycle time, or change the coordination flow pattern. 3.4. All pedestrian functions are handled by the local controller. Kadence can be configured to allow split tuning to make the split lower than the pedestrian clearance times on a phase-by- phase basis, which results in a transition event if a pedestrian push button is activated, or can be configured to only allow splits that are larger than the pedestrian clearance time. Advance walk, delay walk, and all other pedestrian settings are handled by the field controller. 3.5. Kadence has a variety of configurable parameters to tailor the operation to the expectations of the City. Certain adjustments can be disallowed and some phases can be excluded from optimization by pattern. Configurable parameters include: 3.5.1. Exclude any phase from split tuning by pattern 3.5.2. Exclude or allow any lead-lag sequence by pattern 3.5.3. Exclude or allow cycle tuning by pattern 3.5.4. Exclude or allow offset tuning by pattern 3.5.5. Configure maximum deviation of splits from pattern values 3.5.6. Configure maximum deviation of offsets from pattern val...

Algorithms. The computational study aims to evaluate the performance of different algorithms for solving the MDPC model. We compare the algorithms described in Sections 6 and 7 with two state-of-the- art generic algorithms, namely: CPLEX default implementations of branch-and-cut and of Benders

Algorithms. The categorization algorithms described here are available in the ACT. Individual evaluation for each of the algorithms has been performed on the Reuters-21578 corpus. The results of the evaluations can be found in the “Performance results” subchapter.

Algorithms. 2.5.1.1 Setup A private key generator chooses a random number s ∈ Zq* and set Ppub = sP. Then the private key generator publishes system parameters params = {G1, G2, q, P, Ppub, H1, H2}, and keep s as a master key.

Algorithms. 6.1 In the absence of a funded Cooperative Research and Development Agreement (CRADA) AIPL Algorithms developed solely by employee(s) of AIPL under this Agreement shall be owned by ARS and shall be made publicly available to others by ARS. 6.2 In the absence of a funded Cooperative Research and Development Agreement (CRADA) AIPL Algorithms co-developed by employee(s) of ARS and COOPERATOR shall be co-owned by COOPERATOR and ARS and shall be made publicly available to others by ARS. 6.3 Algorithms developed solely by employee(s) of COOPERATOR shall be owned by COOPERATOR and access to such COOPERATOR owned Algorithms will be determined by COOPERATOR. 6.4 While this Agreement is in effect, AIPL has reasonable access to the Cooperator Database to generate and improve AIPL Algorithms for calculating genetic merit and for other non-commercial research purposes jointly agreed to by the parties consistent with this Agreement. Consistent with Article 2 (Confidentiality), ARS shall not release or disclose any information derived from the Cooperator Database including but not limited to individual animal genetic evaluations.