Simulation results. 4.1. Vehicle parameters and the values used in the simulation that are not taken from the actual test vehicle (implicit):
4.2. Yaw stability and lateral displacement according to paragraphs 7.1. to 7.3. of this Regulation:
Simulation results. 4.1. Vehicle parameters and the values used in the simulation that are not taken from the actual test vehicle (implicit):...............................................................
4.2. Yaw stability and lateral displacement according to paragraphs 3.1. to 3.3. of Annex 9: ............................................................................................................
Simulation results. 4.1. Vehicle parameters and the values used in the simulation that are not taken from the actual test vehicle (implicit):
4.2. Results laden and unladen with the vehicle stability function switched on and off for each test conducted under paragraph 3.2. of this Appendix, including the motion variables referred to in Annex 21, Appendix 2, paragraph 2.1. as appropriate:
Simulation results. Esitmated value g(1000,0.01,w ) Simulated value L 400 350 The number of bits leaked to Eve 300 250 200 150 100 50 0 50 100 150 200 250 300 350 400 450 500 Block length w in pass 1
Simulation results. This section presents some numerical examples illustrating the performances of our proposed schemes and finally compared together. For simplicity, the scenario is as- sumed with a single secondary BS serving two secondary users and a single primary cell-edge user within the cognitive cell. It is also assumed that there is one primary user per primary cell which is located in the outer part of the cognitive cell, but within the close vicinity. Note that each user is equipped with a single antenna. As shown in Fig. 3.1, secondary and primary cell-edge users within the cognitive cell are located in sector 3, i.e. q=3. The experiment is done with a single scatterer, i.e, Q = 1. The angular spread of local scatters surrounding the users is to be assumed 2 degrees. The spacing distance between the array elements is λ/2. The carrier frequency is 2 GHz. The noise variance plus the intercell interference is set to 1. In this simulation, SeDuMi solver under optimisation solver CVX [6], [89] is used to attain the optimal solution for the problems stated in (3.16) and (3.21). The azimuth directions (angle of propagation with respect to the antenna array broadside) of the users as well as the angular spread due to the local scatters cor- responding to the sector of the secondary BS can be estimated using the algorithm
Simulation results. 4.2.1 Overall evaluations across all settings Coverage Probability of 95% CI
Simulation results. A hierarchical in-network caching system consisting of 4 levels is considered. Without loss of generality, the maximum possible storage capacities of hierar- chical caching levels 1, 2, 3 and 4 are set to 200, 400, 500 and 600 gigabytes, respectively. In order to analyze the effects of maximum possible storage ca- pacity on the performance of the proposed approach, the cache size is extended in increments of 20% until the maximum storage capacity of the first, second, third and forth level caches reach 600, 1200, 1500 and 1800 gigabytes (typical storage capacities available today). In defining the cost and return functions, it is assumed that caching in the lower levels of the in-network caching system is more costly and results in more transmission bandwidth saving benefit. The total number of popular videos is considered to be 4000 with 3 popular quality layers. As in [116, 117], it is assumed that the video popularity is Xxxx-like with a parameter of 0.6 and the video file sizes follow a Pareto (0.25) distribution with a minimum size of 60 megabytes. The KKT conditions are solved for each dual variable associated with the dual problem deploying IWO and the allocation vector xk is computed using (5.13). A pseudo code for the cache provisioning algorithm is given as Algorithm
Simulation results. All the measurements and simulations were performed on a 2 GHz Pentium dual core processor with 2 Gb RAM. We consider two cases of simulations, depending on the timeout value T for the calls to the garages (see site Timer(T ) in Table I ) : 1) No timeout (equally, T is infinite) 2) T is a finite value, which is lesser than the maximum response time of a garage. Based on the way delays of site calls are generated, we performed two types of simulations: those in which delays generation is done by 1) bootstrapping measured values, 2) sampling a T location-scale distribution, previously fit to measured data.
Simulation results. An Optimized trajectory
Simulation results. As discussed above, it is challenging to design child support policies that ensure that the basic needs of all family members—father, mother, and children—are met, especially in the context of complex families and given that many parents (both custodial and noncustodial) have limited economic resources. With this challenge in mind, we evaluate the consequences of alternative approaches to an SSR that reserves an initial set of resources for the noncustodial parents, before a child support order is determined. We first focus on the consequences of different SSR scenarios for child support order amounts and father economic well-being (income 4We do not generally have information for the children of noncustodial parents or custodial parents in new still-married or still-partnered families. poverty based on amounts owed under different scenarios). We then compare economic well- being for each parent, given variation in the amounts of child support ordered under different SSR scenarios. By illustrating the consequences of each scenario for both fathers and mothers, we provide a more complete view than is available when considering only one perspective. As noted above, we also look separately at fathers with limited economic resources (incomes less than 200 percent of the federal poverty line), and those with only nonmarital children.
