Simulation results Clause Samples

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. ‌ 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. 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. 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. Simulation results are from 5000 replicates of a two-armed randomised trial using four methods (KM, W, IG and GCT) to estimate survival. Figure 5.1 and Table 5.1 show details of the parameter values used in each of the eight experimental conditions investigated. All of the methods investigated successfully gave an estimate of the survival in all scenarios and replicates. All observations on individuals subsequent to their first remission were censored, to allow a fairer comparison with the survival methods that assume an absorbing endpoint. There was an approximate 35% hit rate for the event. Random intercept variance, u 1 1 1 1 9 9 9 9 Median survival time 7/6 7/6 5/5 4/4 7/6 6/6 5/5 4/3 Factor Confounding ref t + u*e e + u*t e*t + u u + e*t u*t + e u*e + t u*e*t

Simulation results. This section presents the simulation results of our protocol using two formal analysis tools. We personally build the AVISPA (Version of 2006/02/13) and Scyther(v1.1.3) in a virtual machine of an ubuntu operating system. The Fig.6 presents the results of all the four back-end analysis tools provided by AVISPA to simulate the proposed protocols for all entities. The test results of OFMC, CL-AtSe, and SATMC modules show that our protocol is safe (SUMMARY SAFE), which means it can achieve the expected security goals; the TA4SP verification model represents INCONCLUSIVE, as the current TA4SP module does not support one-way hash function and the result of No ATTACK TRACE can be provided with the current version. When using the Scyter tool to simulate the protocol, we also use the Dolev-Yao attack model and the minimum number of execution rounds in the analysis parameters is set to 3. The simulation results of the Scyther tool is present in Fig.7. The Fig.7. of (a) shows the attack path of the Scyther tool’s formal analysis under the Dolev-Yao model for our protocol. The reachability analysis report of our protocol messages is presented Fig.7. of (b). The test results show that our proposed protocol does not have any threat of attack under this model. Therefore, we can assert that our protocol can resist the various attacks, such as repaly attack, weak password guessing attack, man-in-the-middle attack, session key discloser attack and so on. (a) OFMC result (b) CL-AtSe result (c) SATMC result (d) TA4SP result Figure 6 Simulation results of the AVISPA tool under the four backends analysis (a) Attack path under the Dolev-Yao model (b) Reachability analysis report of our protocol Figure 7 Simulation results of the Scyther tool.

Simulation results. The Matlab simulation will only test the pendulum when in the upright position. However, it will consider initial angular and linear positions as well as disturbances, and allow linear set point changes. When simulat- ing the controller performance it is important to represent the system with the nonlinear equations. This is necessary to obtain results as close as possible to the real system. The block diagram of the nonlinear sys- tem representation, shown in Figure 3, was designed using Simulink because of the rapid model-based design capabilities and quick modifi- cations for simulations [4]. 3. The pendulum rod violates the maximum angular position greater than the user specified outer capture range. 4. The cart reaches a plus or minus linear position greater than the user specified cart shutdown limit. Figure 2 shows the GUI main form. This design allows for input of con- trol parameters and displays measured and calculated feedback information to the user. The ‘Active X’ uni- versal circular gauge and inverted pendulum model created for a simple inverted pendu- ▇▇▇ have been modified for this interface. The original ‘Active X’ controls are described in [3]. The user may also alter the system settings including base addressing, sampling time and inner and outer capture range for the pendulum angle. Other settings include safeties such as a motor shut down upon a critical linear position. This can potentially avoid damage to the linear position sensor and the mechanical system itself. Other adjustable settings include the swing up fre- quency and gain. Digital filter settings allow the user to con- trol the cutoff frequency of the linear position, angular position and the motor output. Each filter uses a first order discrete equation programmed into the software. The filtering of the input measurements from the linear position sensor and the angular posi- tion sensor are imperative for accurate readings. Due to the nature of the control- ler, any measured noise can affect the stability of the pendulum rod, and the posi- tion of the cart. The simulation is performed using calculated values for K and Ki. The simulation parameters are given below: • Initial Angular Position: 0.398 radians • Linear Set Point (initially 0m): 0.2m at time 7.5s • Disturbance Introduction: 0.2 radians at time 5s • Disturbance Cancellation: -0.2 radians at time 5.2s • Simulation Time: 20s

Simulation results. In all the simulations, the power of the additive white Gaussian noise is set to 0 dB. Then, for each distance d a simulation is run with transmit power(eNodeB1) = SNR(d) and transmit power(eNodeB2) = SNR(ISD-d), for each scenarios. The performance curves are given in terms of BER and throughput, for the 3 modes of Table 1. The throughput is given in percentage of the maximum achievable throughput, i.e. 100x(1-FER). The Inter Site Distance is 500 m. 3.2.2.4.1 Mode 1 100 90 80 Interference Cooperation 70 60 50 40 30 20 10 0 Results for mode 1 are given on Figure 8 and Figure 9. With this robust mode we can see that with no cooperation (curves with circles) the performance start degrading from a distance d=180 m from eNodeB1 (the throughput falls and the BER raises). With cooperation (curves with triangles) we reach the maximum performance (BER of 0 and 100 % throughput) starting from distance d=130 m. Figure 8: Throughput, mode 1 1,00E+00 1,00E-01 interference Cooperation 1,00E-02 1,00E-03 1,00E-04 Figure 9: BER, mode 1 If we consider a UE in cell 1 for mode 1, the interference free and cooperation zones are then the one given by Figure 10. In this mode, maximum performance can then be reached wherever the UE is situated in cell 1 by choosing the appropriate interference / cooperation transmission mode as a function of the distance d. Cooperation zone Interference free zone Cell 1 eNodeB1 eNodeB2 Cell 2 130 m 180 m Figure 10: Interference free and cooperation zones for mode 1 3.2.2.4.2 Mode 3 Results for mode 3 are given on Figure 11 and Figure 12. In this mode, with no cooperation the performance start degrading from a distance d=150 m from eNodeB1, as expected smaller than the case in mode 1 as mode 3 is less robust. With cooperation we reach the maximum performance starting from distance d=175 m. 100 90 Interference 80 Cooperation 70 60 50 40 30 20 10 0 Figure 11: Throughput, mode 3 1,00E+00 1,00E-01 interference Cooperation 1,00E-02 1,00E-03 1,00E-04 Figure 12: BER, mode 3 If we consider a UE in cell 1 for mode 3, the interference free and cooperation zones are then the one given by Figure 13. In this mode, maximum performance cannot then be reached for a UE situated at a distance d lying between 150 m and 175 m from eNodeB1. Cooperation Interference free zone zone Cell 1 eNodeB1 eNodeB2 Cell 2 150 m 175 m Figure 13: Interference free and cooperation zones for mode 3 3.2.2.4.3 Mode 5 Results for mode 5 are given on Figure 14 and Figure 15. In this mode,...

Simulation results. An Optimized trajectory