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SciFIBench3

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[ "A) fer performance of the conventional stc-ofdm system for different time delays .", "B) fer performance of the conventional stc-ofdm system for different sirs .", "C) ber performance of tmp receiver with different number of iterations for otfs system .", "D) ber performance of several s-bf decoder as a functionof snr for code 2 .", "E) the performance of mpsk modulation schemes under different modulation orders ." ]

[ "A) unweighted sum rates for the systems withe [ |hsr|2 ] = 1 , e [ |hsd|2 ] = 1 ande [ |hrd|2 ] = 5 .", "B) unweighted sum rates for the systems with extra direct-link transmission , ande [ |hsr|2 ] = 1 , e [ |hsd|2 ] = 1 , e [ |hrd|2 ] = 5 .", "C) unweighted sum rates for the systems with extra direct-link transmission , ande [ |hsr|2 ] = 5 , e [ |hsd|2 ] = 1 , e [ |hrd|2 ] = 1 .", "D) unweighted sum rates for the systems with extra direct-link transmission , ande [ |hsr|2 ] = 3 , e [ |hsd|2 ] = 1 , e [ |hrd|2 ] = 3 .", "E) unweighted sum rates for the systems withe [ |hsr|2 ] = , e [ |hsd|2 ] = 1 ande [ |hrd|2 ] = ." ]

[ "A) the error performance of the ( 16129 , 1437 ) qc-ldpc code given in example over the awgn channel .", "B) the error performance of the ( 3969 , 365 ) qc-ldpc code given in example over the awgn channel .", "C) the error performances of the ( 399 , 3243 ) qc-ldpc code given in example over the awgn channel decoded with the ibmpda and the spa .", "D) the error performance of the ( 6486 , 219 ) qc-ldpc code given in example over the awgn channel .", "E) the error performance of the ( 1096 , 10587 ) qc-ldpc code given in example over the awgn channel ." ]

[ "A) the error performance of the ( 3969 , 365 ) qc-ldpc code given in example over the awgn channel .", "B) the error performance of the ( 1096 , 10587 ) qc-ldpc code given in example over the awgn channel .", "C) the error performances of the ( 399 , 3243 ) qc-ldpc code given in example over the awgn channel decoded with the ibmpda and the spa .", "D) the error performance of the ( 6486 , 219 ) qc-ldpc code given in example over the awgn channel .", "E) the error performance of the ( 16129 , 1437 ) qc-ldpc code given in example over the awgn channel ." ]

[ "A) simulation for the improved method ( nnsizze=100 , sc=50 , sum-squared error of 1x10^ ( -6 ) ) .", "B) simulation for the improved method ( nnsizze=30 , sc=50 , sum-squared error of 1x10^ ( - ) ) .", "C) simulation for the improvedl method ( nnsizze=100 , sc=100 , sum-squared error of 1x10^ ( -10 ) ) .", "D) simulation for the conventional method ( nnsizze=100 , sc=100 , sum-squared error of 1x10^ ( -10 ) ) .", "E) simulation for the conventional method ( nnsizze=0 , sc=30 , sum-squared error of 1x10^ ( -6 ) ) ." ]

[ "A) error after applying the kalman filter .", "B) error after applying the neural network .", "C) error after applying the 135 sample wiener filter .", "D) error while training the network .", "E) error after applying the original wiener filter ." ]

[ "A) the total distance measure with different window sizes on evolving graph 2 .", "B) the total distance measure with different window sizes on evolving graph 1 .", "C) the total distance measure with different window sizes on evolving graph 4 .", "D) the total distance measure with different window sizes on evolving graph 5 .", "E) the total distance measure with different window sizes on evolving graph 3 ." ]

[ "A) the total distance per graph measure with different window sizes on evolving graph 5 .", "B) the total distance per graph measure with different window sizes on evolving graph 1 .", "C) the total distance per graph measure with different window sizes on evolving graph 3 .", "D) the total distance per graph measure with different window sizes on evolving graph 4 .", "E) the total distance per graph measure with different window sizes on evolving graph 2 ." ]

[ "A) mcb algorithms – maximum yield vs. slack for large problem instances .", "B) mcb algorithms – average yield vs. slack for large problem instances .", "C) maximum yield vs. slack for large problem instances .", "D) mcb algorithms – minimum yield vs. slack for small problem instances .", "E) mcb algorithms – average yield vs. slack for small problem instances ." ]

[ "A) mcb algorithms – average yield vs. slack for small problem instances .", "B) mcb algorithms – maximum yield vs. slack for small problem instances .", "C) minimum yield vs. slack for large problem instances .", "D) mcb algorithms – average yield vs. slack for large problem instances .", "E) mcb algorithms – minimum yield vs. slack for large problem instances ." ]

[ "A) mcb algorithms – minimum yield vs. slack for small problem instances .", "B) mcb algorithms – average yield vs. slack for large problem instances .", "C) mcb algorithms – minimum yield vs. slack for large problem instances .", "D) mcb algorithms – maximum yield vs. slack for small problem instances .", "E) average yield vs. slack for small problem instances ." ]

[ "A) network usage progression with synthetic heavy weight workload and locally varying churn .", "B) expected lookup time progression with synthetic heavy weight workload and locally varying churn .", "C) expected lookup time progression with synthetic heavy weight workload and high churn .", "D) expected lookup time progression with synthetic heavy weight workload and low churn .", "E) expected lookup time progression with synthetic heavy weight workload and temporally varying churn ." ]

[ "A) expected lookup time progression with synthetic heavy weight workload and temporally varying churn .", "B) expected lookup time progression with synthetic heavy weight workload and locally varying churn .", "C) maintenance-interval progression with synthetic heavy weight workload and low churn .", "D) expected lookup time progression with synthetic heavy weight workload and high churn .", "E) expected lookup time progression with synthetic heavy weight workload and low churn ." ]

[ "A) expected lookup time progression with synthetic heavy weight workload and high churn .", "B) network usage progression with synthetic heavy weight workload and high churn .", "C) expected lookup time progression with synthetic heavy weight workload and temporally varying churn .", "D) expected lookup time progression with synthetic heavy weight workload and low churn .", "E) expected lookup time progression with synthetic heavy weight workload and locally varying churn ." ]

[ "A) network usage progression with synthetic heavy weight workload and locally varying churn .", "B) expected lookup time progression with synthetic heavy weight workload and high churn .", "C) expected lookup time progression with synthetic heavy weight workload and low churn .", "D) expected lookup time progression with synthetic heavy weight workload and temporally varying churn .", "E) expected lookup time progression with synthetic heavy weight workload and locally varying churn ." ]

[ "A) snr vs. the number of modules for classical modular method and our proposed optimized modular method for s & h interpolation .", "B) snr vs. the number of modules for classical modular method and our proposed optimized modular method for linear interpolati n .", "C) snr vs. the number of modules for classical modular method and our proposed optimized method for s & h interpolation .", "D) snr vs. the number of modules for classical modular method and our proposed optimized method for s & h interpolation for 2-d signals .", "E) snr vs. the number of modules for classical modular method and our proposed optimized modular method for opt. interpolation ." ]

[ "A) ser performance at 8 bpcu for codes for× systems .", "B) ser performance at 4 bpcu for codes for4× systems .", "C) ser performance at 6 bpcu for codes for× 3 systems .", "D) ser performance at 4 bpcu for codes for8× 2 systems .", "E) ser performance at 8 bpcu for codes for4× 4 systems ." ]

[ "A) a graph showing the value ofǫ satisfied by a givenk if δ ≤ 10− with varying sampling probabilities .", "B) a graph showing the relationship between the values of k needed to achieve roughly the sameδ if we doubleβ .", "C) a graph showing the relationship betweenǫ and 1 δ if we vary the values ofk under fixed β .", "D) a graph showing the relationship betweenǫ and 1 δ if we vary the values ofβ under fixed k .", "E) a graph showing the relationship betweenǫ and 1 δ with small k ’ s , varying k and fixing β ." ]

[ "A) end-to-end bit error rate versus snr of the fscr scheme using a df transmission in the ln case fork = 2 and k = 4 .", "B) comparisons of error performance versus snr of the fscr and dsc schemes using a df transmission in the ln case whenk = 2 andk = ..", "C) error rate incurred in the detection of the pss vs. snr for θ = 0 .", "D) end-to-end bit error-rate versus snr of the sr schemeusing a df transmission in the ln case whenk = 2 and k = 4 .", "E) end-to-end bit error rate versus snr of the dsc schemeusing a df transmission in the ln case whenk = and k = 4 ." ]

[ "A) the number of citations , ∑p i=h+1 ci , and its upper bound , ( p − h ) h , for authors a through f .", "B) the number of citations , ∑g i=h+1 ci , and its upper bounds , ( g − h ) h , and ( g − h ) g , for authors a through f .", "C) the g-index and its upper bounds given by lemma 1 and theorem for authors a through f .", "D) the h-index and its lower bounds given by theorem 1 , theorem and theorem 4 for authors a through f .", "E) the number of citations , ∑p i=g+1 ci , and its upper bound , ( p − g ) h , for authors a through f ." ]

[ "A) the number of citations , ∑g i=h+1 ci , and its upper bounds , ( g − h ) h , and ( g − h ) g , for authors a through f .", "B) the number of citations , ∑p i=g+1 ci , and its upper bound , ( p − g ) h , for authors a through f .", "C) the number of citations , ∑p i=h+1 ci , and its upper bound , ( p − h ) h , for authors a through f .", "D) the values ofh2 , g2 , andg2 −h2 as a function of the total number of citations , where journals are arranged according to increasing number of citations .", "E) the h-index and its lower bounds given by theorem 1 , theorem and theorem 4 for authors a through f ." ]

[ "A) the number of citations , ∑p i=h+1 ci , and its upper bound , ( p − h ) h , for authors a through f .", "B) the g-index and its upper bounds given by lemma 1 and theorem for authors a through f .", "C) the h-index and its lower bounds given by theorem 1 , theorem and theorem 4 for authors a through f .", "D) the number of citations , ∑g i=h+1 ci , and its upper bounds , ( g − h ) h , and ( g − h ) g , for authors a through f .", "E) the number of citations , ∑p i=g+1 ci , and its upper bound , ( p − g ) h , for authors a through f ." ]

[ "A) speedup obtained in model problem with 135 , 005 , 697 dofs .", "B) experimental vs. ideal speed up for problem 1 .", "C) experimental speed up for problem2 .", "D) experimental speed up for problem 1 .", "E) temperature experiments , with ϵ = 0.05 ." ]

[ "A) met prediction using extended met model in comparison with shoulder static models .", "B) met prediction using extended met model in comparison with hip/back static models .", "C) comparison of equation-based and model-based prediction of braking distance .", "D) met prediction using extended met model in comparison with elbow static models .", "E) met prediction using extended met model in comparison with general static models ." ]

[ "A) met prediction using extended met model in comparison with shoulder static models .", "B) performance comparison between lightweight models and unconstrained models .", "C) met prediction using extended met model in comparison with hip/back static models .", "D) met prediction using extended met model in comparison with elbow static models .", "E) met prediction using extended met model in comparison with general static models ." ]

[ "A) probability of detection vs. probability of false alarm for n = 2 , m = 8 , l = 1 .", "B) probability of detection vs. probability of false alarm for n = 8 , m = 2 , l = 1 .", "C) probability of detection vs. probability of false alarm for n = 8 , m = 8 , l = 1 .", "D) probability of detection vs. probability of false alarm for n = 2 , m = 2 , l = 1 .", "E) probability of detection vs. probability of false alarm for n = , m = 4 , l = 1 ." ]

[ "A) pdr of 30 nodes using tcp .", "B) pdr in presence of three malicious node .", "C) pdr of 60 nodes using tcp .", "D) pdr in presence of two malicious node .", "E) pdr in presence of one malicious node ." ]

[ "A) wcrt comparison : 4 processors .", "B) wcrt comparison : 16 processors .", "C) success ratio : 16 processors .", "D) wcrt comparison : 8 processors .", "E) success ratio : 8 processors ." ]

[ "A) success ratio : 4 processors .", "B) success ratio : 2 processors .", "C) wcrt comparison : 4 processors .", "D) success ratio : 8 processors .", "E) success ratio : 16 processors ." ]

[ "A) success ratio : 16 processors .", "B) wcrt comparison : 4 processors .", "C) success ratio : 2 processors .", "D) success ratio : 4 processors .", "E) success ratio : 8 processors ." ]

[ "A) snri versus l for feds algorithm .", "B) snri versus l for fap algorithm .", "C) snri versus µ for feds algorithm .", "D) snri versus m for feds algorithm .", "E) snri versus µ for fap algorithm ." ]

[ "A) pk−l+1−t is above l and pk+u−l−t is above l .", "B) pk−l+1−t is below l and pk+u−l−t is above l .", "C) pk−l+1+t is above while pk+t is below l .", "D) pk−l+1+t is below l and pk+t is below l ′ .", "E) pk−l+1−t is below l and pk+u−l−t is also below l ." ]

[ "A) pk−l+1+t is below l and pk+t is below l ′ .", "B) pk−l+1−t is above l and pk+u−l−t is above l .", "C) pk−l+1+t is above while pk+t is below l .", "D) pk−l+1−t is below l and pk+u−l−t is above l .", "E) pk−l+1−t is below l and pk+u−l−t is also below l ." ]

[ "A) pk−l+1−t is below l and pk+u−l−t is above l .", "B) both pk−l+1+t and pk+t are above l .", "C) pk−l+1+t is below l and pk+t is above l ′ .", "D) pk−l+1+t is above while pk+t is below l .", "E) pk−l+1+t is below l and pk+t is below l ′ ." ]

[ "A) both pk−l+1+t and pk+t are above l .", "B) pk−l+1−t is below l and pk+u−l−t is above l .", "C) pk−l+1+t is below l and pk+t is below l ′ .", "D) pk−l+1+t is above while pk+t is below l .", "E) pk−l+1+t is below l and pk+t is above l ′ ." ]

[ "A) pk−l+1+t is above while pk+t is below l .", "B) pk−l+1−t is below l and pk+u−l−t is above l .", "C) both pk−l+1+t and pk+t are above l .", "D) pk−l+1+t is below l and pk+t is above l ′ .", "E) pk−l+1+t is below l and pk+t is below l ′ ." ]

[ "A) pk−l+1+t is above while pk+t is below l .", "B) pk−l+1−t is below l and pk+u−l−t is also below l .", "C) pk−l+1−t is above l and pk+u−l−t is above l .", "D) pk−l+1+t is below l and pk+t is below l ′ .", "E) pk−l+1−t is below l and pk+u−l−t is above l ." ]

[ "A) average user time of gridsim , dwgrd and cwgrd with users=20 .", "B) average user time of gridsim , dwgrd and cwgrd with resources=20 .", "C) average user time of gridsim , dwgrd and cwgrd with resources=60 .", "D) average user time of gridsim , dwgrd and cwgrd with users=100 .", "E) average user time of gridsim , dwgrd and cwgrd with users=60 ." ]

[ "A) waterfall frequency diagram for z direction in p1 position .", "B) waterfall frequency diagram for y direction in p2 position .", "C) waterfall frequency diagram for x direction in p2 position .", "D) frequency spectrum on x , y and z direction without cutting .", "E) waterfall frequency diagram for z direction in p3 position ." ]

[ "A) waterfall frequency diagram for x direction in p2 position .", "B) frequency spectrum on x , y and z direction without cutting .", "C) waterfall frequency diagram for z direction in p3 position .", "D) waterfall frequency diagram for y direction in p2 position .", "E) waterfall frequency diagram for z direction in p1 position ." ]

[ "A) ber vs snr for fft size=2048 using ls , lmmse , lr-lmmse .", "B) ber vs snr for fft size=1024 using ls , lmmse , lr-lmmse algorithms .", "C) ber vs snr for fft size=512 using ls , lmmse , lr-lmmse algorithms .", "D) ber vs snr for fft size=256 using ls , lmmse , lr-lmmse algorithms with a 16 qam modulation .", "E) ber vs snr for a bpsk modulation ." ]

[ "A) ber vs snr for a bpsk modulation .", "B) ber vs snr for fft size=1024 using ls , lmmse , lr-lmmse algorithms .", "C) ber vs snr for fft size=256 using ls , lmmse , lr-lmmse algorithms with a 16 qam modulation .", "D) ber vs snr for fft size=2048 using ls , lmmse , lr-lmmse .", "E) ber vs snr for fft size=512 using ls , lmmse , lr-lmmse algorithms ." ]

[ "A) ber vs snr for fft size=512 using ls , lmmse , lr-lmmse algorithms .", "B) mse vs snr for a 16 qam modulation .", "C) ber vs snr for fft size=1024 using ls , lmmse , lr-lmmse algorithms .", "D) ber vs snr for fft size=256 using ls , lmmse , lr-lmmse algorithms with a 16 qam modulation .", "E) ber vs snr for a bpsk modulation ." ]

[ "A) averaged variation of ϕ ( fitness ) against increasing amount of gaussian blur and a fixed amount of gaussian noise for reference images in tid200 database .", "B) averaged variation of ϕ ( fitness ) against increasing amount of gaussian blur for reference images in tid2008 database .", "C) averaged variation of κ against increasing amount of gaussian noise for reference images in tid2008 database .", "D) averaged variation of κ against increasing amount of gaussian blur and a fixed amount of gaussian noise for reference images in tid2008 database .", "E) averaged variation of κ against increasing amount of gaussian blur for reference images in tid2008 database ." ]

[ "A) control signal of 1p for step input and load disturbance with itae based tuning .", "B) control signal of 1p for step input and load disturbance with istes based tuning .", "C) control signal of 2p for step input and load disturbance with istes based tuning .", "D) control signal of 1p for step input and load disturbance with istse based tuning .", "E) control signal of 1p for step input and load disturbance with itse based tuning ." ]

[ "A) step input and load disturbance response for plant 2p with itae based tuning .", "B) control signal of 1p for step input and load disturbance with itse based tuning .", "C) control signal of 1p for step input and load disturbance with itae based tuning .", "D) step input and load disturbance response for plant 1p with itae based tuning .", "E) control signal of 2p for step input and load disturbance with itse based tuning ." ]

[ "A) control signal of 1p for step input and load disturbance with itae based tuning .", "B) control signal of 1p for step input and load disturbance with itse based tuning .", "C) control signal of 2p for step input and load disturbance with istes based tuning .", "D) control signal of 2p for step input and load disturbance with istse based tuning .", "E) control signal of 2p for step input and load disturbance with itse based tuning ." ]

[ "A) control signal of 1p for step input and load disturbance with istes based tuning .", "B) control signal of 2p for step input and load disturbance with itse based tuning .", "C) control signal of 1p for step input and load disturbance with itse based tuning .", "D) control signal of 2p for step input and load disturbance with istse based tuning .", "E) control signal of 2p for step input and load disturbance with istes based tuning ." ]

[ "A) control signal of 2p for step input and load disturbance with istes based tuning .", "B) control signal of 2p for step input and load disturbance with itse based tuning .", "C) control signal of 1p for step input and load disturbance with itse based tuning .", "D) control signal of 2p for step input and load disturbance with istse based tuning .", "E) control signal of 1p for step input and load disturbance with istes based tuning ." ]

[ "A) control signal of 2p for step input and load disturbance with itse based tuning .", "B) control signal of 1p for step input and load disturbance with itae based tuning .", "C) control signal of 1p for step input and load disturbance with istse based tuning .", "D) control signal of 1p for step input and load disturbance with itse based tuning .", "E) control signal of 1p for step input and load disturbance with istes based tuning ." ]

[ "A) roc curve of the generated multibiometrics fusion functions on the validation set of the private dataset .", "B) roc curve for the kinovis-mst dataset .", "C) roc curve of algorithms and result of fused classifier on test set .", "D) roc curve of the generated multibiometrics fusion functions on the validation set of the banca dataset .", "E) roc curve of the generated multibiometrics fusion functions on the validation set of the bssr1 dataset ." ]

[ "A) snr vs. the number of modules for classical modular method and our proposed optimized method for s & h interpolation for 2-d signals .", "B) snr vs. the number of modules for classical modular method and our proposed optimized modular method for s & h interpolation .", "C) snr vs. the number of modules for classical modular method and our proposed optimized modular method for linear interpolation .", "D) snr vs. the number of modules for classical modular method and our proposed optimized method for s & h interpolation .", "E) snr vs. the number of modules for classical modular method and our proposed optimized modular method for linear interpolati n ." ]

[ "A) psnr of various algorithms for baboon image corrupted by rvin .", "B) psnr of various algorithms for baboon image corrupted by zero mean gaussian noise .", "C) mse of various algorithms for baboon image corrupted by zero mean gaussian noise .", "D) mse of various algorithms for baboon image corrupted by rvin .", "E) ief of various algorithms for baboon image corrupted by rvin ." ]

[ "A) proposed protocol : reconstruction error performance for different values oftout , m = 0 , n = 25 , l = 5 .", "B) proposed protocol : reconstruction error performance for different values ofλ ands = 6 , 8 , 10 ; tout = 30 , n = 49 , m = 40 andl = 7 .", "C) example 1 : the accuracy errors rel ( κ ) of adnn using various numbers of the threshold tol .", "D) reconstruction error on the normal measurements in t validlstm with different missing ratios γ .", "E) proposed protocol : reconstruction error performance for different values ofm , λ andtout = 30 , n = 9 , l = 7 ." ]

[ "A) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 8-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "B) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 1-fsk wsn system over rayleigh fading channels for probabilities of correct detection equal to 0.999 .", "C) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 16-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "D) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of -fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "E) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 10 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity ." ]

[ "A) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 16-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "B) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 8-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "C) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 10 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity .", "D) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of -fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "E) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 20 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity ." ]

[ "A) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 20 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity .", "B) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of -fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "C) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 16-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "D) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 4 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity .", "E) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 8-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity ." ]

[ "A) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 16-fsk 8 node wsn system over rayleigh fading channels for probabilities of correct detection less than unity .", "B) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of mfsk for 10 nodes wsn system over rayleigh fading channels for different modulation levels with probability of correct detection equal to unity .", "C) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 1-fsk wsn system over rayleigh fading channels for probabilities of correct detection equal to 0.999 .", "D) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of 16-fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity .", "E) bit error rate ( ber ) vs signal to noise ratio ( snr ) performance of -fsk wsn for different number of sensors over rayleigh fading channels with probability of correct detection equal to unity ." ]

[ "A) ccdf vs. papr curve of ofdm signal using convolution codes with code rate 12 and constraint length ( k = 3− 8 ) .", "B) ccdf vs. papr curve of ofdm signal using convolution codes with code rate 13 and constraint length ( k = 3− 8 ) .", "C) ccdf vs. papr curve of coded ofdm signal using different channel coding techniques .", "D) ccdf vs. papr curve of ofdm signal using convolution codes with code rate 13 and constraint length ( k=6-14 ) .", "E) ccdf vs. papr curve of ofdm signal using convolution codes with code rate 12 and constraint length ( k = 9− 14 ) ." ]

[ "A) average end to end delay ( sec ) vs number of nodes .", "B) end-to-end delay vs. number of sensor nodes .", "C) data accuracy versus number of sensor nodes .", "D) end-to-end delay bounds vs number of nodes .", "E) computation overhead vs. number of sensor nodes ." ]

[ "A) the accuracy of different number of training set .", "B) precision over the test set with respect to the number of training pairs .", "C) performance over the test set with respect to the number of training pairs when the grades of documents are not known .", "D) precision of the enhanced model over the test set with respect to the number of training pairs .", "E) similarity of the enhanced model with respect to the number of training pairs ." ]

[ "A) the accuracy of different number of training set .", "B) precision of the enhanced model over the test set with respect to the number of training pairs .", "C) precision over the test set with respect to the number of training pairs .", "D) similarity of the enhanced model with respect to the number of training pairs .", "E) performance over the test set with respect to the number of training pairs when the grades of documents are not known ." ]

[ "A) recall error rate and the theoretical bounds for different architectures of network with n = 960 and n = 400 pattern neurons and l = 60 and l = 50 clusters , respectively..", "B) pattern error rate against the initial number of erroneous nodes for two different network sizes n = 800 and k = 400. in both cases k = n/2 .", "C) average normalized error of estimated matrix norm versusnl with different number of ers , k , wheremt = 4 andmr = 2 .", "D) pattern error rate in the first and last iterations against the initial number of erroneous nodes for n = 800 , k = 400 , α0 = 0.95 , θ0 = 0.029 and ϕ = 0.99 .", "E) pattern error rate against the initial number of erroneous nodes and comparison with theoretical upper bounds for n = 800 , k = 400 , α0 = 0.95 and θ0 = 0.029 ." ]

[ "A) number of bs 's in cwn-pam by method i for 30 nodes .", "B) number of bs 's in cwn-pam by method ii for 101 nodes .", "C) number of bs 's in m-pam by method ii for 101 nodes .", "D) number of bs 's in cwn-pam by method ii for 30 nodes .", "E) number of bs 's in cwn-pam by method i for 1 nodes ." ]

[ "A) number of bs 's in cwn-pam by method ii for 101 nodes .", "B) number of bs 's in m-pam by method ii for 101 nodes .", "C) number of bs 's in cwn-pam by method i for 1 nodes .", "D) number of bs 's in cwn-pam by method ii for 30 nodes .", "E) number of bs 's in cwn-pam by method i for 30 nodes ." ]

[ "A) number of bs 's in cwn-pam by method ii for 101 nodes .", "B) number of bs 's in cwn-pam by method i for 30 nodes .", "C) number of bs 's in m-pam by method i for 30 node .", "D) number of bs 's in cwn-pam by method i for 1 nodes .", "E) number of bs 's in cwn-pam by method ii for 30 nodes ." ]

[ "A) performance evaluation of gpcb-rs codes , with m=100 , over awgn channel .", "B) performance evaluation of gpcb-bch codes , with m=100 , over awgn channel .", "C) effect of the parameter m on iterative decoding of gpcb-bch-rs ( 1 , 113 ) code , over awgn channel .", "D) performances comparison between gpcb-rs , gpcbbch-rs and gpcb-bch codes , with m=100 , over awgn channel .", "E) performance evaluation of gpcb-bch-rs codes , with m=100 , over awgn channel ." ]

[ "A) performance evaluation of gpcb-bch codes , with m=100 , over awgn channel .", "B) effect of iterations on iterative decoding of gpcbbch ( 148 , 106 ) code , over awgn channel .", "C) performance evaluation of gpcb-bch-rs codes , with m=100 , over awgn channel .", "D) performances comparison between gpcb-rs , gpcbbch-rs and gpcb-bch codes , with m=100 , over awgn channel .", "E) performance evaluation of gpcb-rs codes , with m=100 , over awgn channel ." ]

[ "A) variation of the average delay of nrt packets according to arrival rate of rrt packets .", "B) average delays of nrt packets according to the arrival rate of rt packets .", "C) average delays of nrt packets versus service rate of rt packets .", "D) average delay of nrt packets according to the arrival rate of nrt packets .", "E) average delays of nrt packets versus service rate of nrt packets ." ]

[ "A) optimal pareto front by nsga ii for test problem i .", "B) optimal pareto front by spea ii for test problem i .", "C) the approximated pareto front obtained by different algorithms on the rosetta problem .", "D) optimal pareto front by nsga i for test problem ii .", "E) optimal pareto front by spea ii for dew point ." ]

[ "A) optimal pareto front by nsga ii for test problem ii .", "B) optimal pareto front by spea ii for test problem i .", "C) optimal pareto front by spea ii for dew point .", "D) the approximated pareto front obtained by different algorithms on the rosetta problem .", "E) optimal pareto front by nsga i for test problem i ." ]

[ "A) plot of path cost v/s generation for 2 nodes , 1000 iterations .", "B) plot of path cost v/s generation for 100 nodes , 100 iterations .", "C) plot of path cost v/s generation for 500 nodes , 200 iterations .", "D) plot of path cost v/s generation for 1000 nodes , 1000 iterations .", "E) plot of path cost v/s generation for 50 nodes , 10 iterations ." ]

[ "A) plot of path cost v/s generation for 50 nodes , 100 iterations .", "B) plot of path cost v/s generation for 500 nodes , 200 iterations .", "C) plot of path cost v/s generation for 2 nodes , 100 iterations .", "D) plot of path cost v/s generation for 100 nodes , 100 iterations .", "E) plot of path cost v/s generation for 1000 nodes , 100 iterations ." ]

[ "A) lower level function evaluations for smd from 3 runs of the nested bilevel solution procedure .", "B) simulation for the improved method ( nnsizze=100 , sc=50 , sum-squared error of 1x10^ ( -6 ) ) .", "C) upper level function evaluations for smd2 from 31 runs of the nested bilevel solution procedure .", "D) upper level function evaluations for smd1 from 31 runs of the nested bilevel solution procedure .", "E) lower level function evaluations for smd2 from 1 runs of the nested bilevel solution procedure ." ]

[ "A) evolution average ncloc per class in freemind .", "B) evolution of function per class in freemind .", "C) evolution of classes in freemind .", "D) evolution of average classes per package in freemind .", "E) evolution of modularity index in freemind ." ]

[ "A) evolution of average package quality in freemind .", "B) evolution of packages in freemind .", "C) evolution of modularity index in freemind .", "D) evolution of system architecture in freemind .", "E) evolution of average classes per package in freemind ." ]

[ "A) histogram of texts with different anger word densities .", "B) histogram of texts with different anticip word densities .", "C) histogram of utterance distribution across speakers .", "D) histogram of texts with different surprise word densities .", "E) histogram of texts with different joy word densities ." ]

[ "A) dr , raw feature [ 12-12 ] pair vs. enhanced features .", "B) dr , raw feature [ 8-8 ] pair vs. enhanced features .", "C) mttd , raw feature [ 8-8 ] pair vs. enhanced features .", "D) mttd , raw feature [ 12-12 ] pair vs. enhanced features .", "E) mttd , raw feature [ -2 ] pair vs. enhanced features ." ]

[ "A) mttd , raw feature [ 12-12 ] pair vs. enhanced features .", "B) dr , raw feature [ 12-12 ] pair vs. enhanced features .", "C) dr , raw feature [ 8-8 ] pair vs. enhanced features .", "D) mttd , raw feature [ 8-8 ] pair vs. enhanced features .", "E) dr , raw feature [ 4-2 ] pair vs. enhanced features ." ]

[ "A) cross correlation function between example 1 and 2 when mod n=2151 .", "B) cross correlation function between example 1 and 4 when mod n=7283 .", "C) cross correlation function between example 1 and 3 when mod n=3121 .", "D) cross correlation function between example 3 and 4 when mod n=3121 .", "E) cross correlation function between example 2 and 4 when mod n=21851 ." ]

[ "A) classification results .", "B) performance of different feature selection methods on orl data set .", "C) results of learning methods for feature engineering ii .", "D) results of learning methods for feature engineering i .", "E) results of learning methods for baseline ." ]

[ "A) computational complexity in terms of visited nodes required by guo-nilson ’ s sphere decoder with s-e for 3d mimo code and proposed simplified ml decoders , in quasi-static rayleigh channel with qpsk modulation .", "B) computational complexity in terms of multiplications required by guo-nilson ’ s sphere decoder with s-e for 3d mimo code and proposed simplified ml decoders , in quasi-static rayleigh channel with 16-qam modulation .", "C) computational complexity in terms of multiplications required by guo-nilson ’ s sphere decoder with s-e for 3d mimo code and proposed simplified ml decoders , in quasi-static rayleigh channel with qpsk modulation .", "D) computational complexity in terms of additions required by guo-nilson ’ s sphere decoder with s-e for 3d mimo code and proposed simplified ml decoders , in quasi-static rayleigh channel with 16-qam modulation .", "E) computational complexity in terms of divisions required by guo-nilson ’ s sphere decoder with s-e for 3d mimo code and proposed simplified ml decoders , in quasi-static rayleigh channel with qpsk modulation ." ]

[ "A) comparison of the different sampling strategies at estimating worker performance in the simulated pool with binary worker performance levels using pearson correlation .", "B) comparison of the different sampling strategies at estimating worker performance in the simulated pool with gaussian worker performance levels using pearson correlation .", "C) comparison of different worker selection strategies at estimated worker performance in the simulated pool with gaussian worker performance levels using chi correlation .", "D) comparison of different sampling strategies at estimated worker performance in the simulated pool with gaussian worker performance levels using spearman correlation .", "E) comparison of different sampling strategies at estimated worker performance in the simulated pool with binary worker performance levels using r correlation ." ]

[ "A) ta-mse comparison for the adaptive rx3 and rx4 for acgn channels .", "B) ta-mse comparison for awgn channel to verify robustness to noise model .", "C) ta-mse comparison for the katayama noise model of [ 6 ] .", "D) convergence of the ta-mse of the adaptive rx4 with training to the ta-mse of the optimal rx4 .", "E) theoretical ta-mse comparison with simulated ta-mse ." ]

[ "A) theoretical ta-mse comparison with simulated ta-mse .", "B) ta-mse comparison for the katayama noise model of [ 6 ] .", "C) ta-mse comparison for awgn channel to verify robustness to noise model .", "D) mse performance of the phase noise estimation .", "E) ta-mse comparison for the lptv noise model of [ 9 ] ." ]

[ "A) performance comparison on accuracy .", "B) oarae parameter values for different methods .", "C) oatprate parameter values for different methods .", "D) arae parameter values for different methods .", "E) test results of different parameters with same amount of data in one epoch ." ]

[ "A) oarae parameter values for different methods .", "B) oatprate parameter values for different methods .", "C) performance comparison on accuracy .", "D) parameter sensitivity analysis results .", "E) arae parameter values for different methods ." ]

[ "A) plot of β ( σ1 , α ) for σ1 = 0.5 , and α = 0 and α = π/ .", "B) the optimum pe1 as a function of υ for different values π1 .", "C) function υ ( α ) for α ∈ ( 0 , π2 ) and ς = 1.03 , % = 0.06 .", "D) the loss function eθ as function of ∆θ .", "E) the behavior of ϕ∗ as a function of υ for π1 = 0.01 ." ]

[ "A) performance of the proposed asynchronous differential schemes for τ2−τ1 = ts/2 and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 4 transmit antennas and 1 receiver with 1 receive antenna .", "B) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "C) performance of the proposed asynchronous differential schemes for τj+1 − τj = ts/3 , ∀j , and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 3 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "D) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "E) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 1 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 3 receive antennas ." ]

[ "A) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "B) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "C) performance of the proposed asynchronous differential schemes for τj+1 − τj = ts/3 , ∀j , and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 3 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "D) performance of the proposed asynchronous differential schemes for τ2−τ1 = ts/2 and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 4 transmit antennas and 1 receiver with 1 receive antenna .", "E) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 1 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 3 receive antennas ." ]

[ "A) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "B) performance of the proposed asynchronous differential schemes for τ2−τ1 = ts/2 and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 4 transmit antennas and 1 receiver with 1 receive antenna .", "C) performance of the proposed asynchronous differential schemes for τj+1 − τj = ts/3 , ∀j , and the synchronous coherent scheme using ml decoding at a rate of 1 b/ ( s hz ) for 3 users each with 2 transmit antennas and 1 receiver with 2 receive antennas .", "D) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 1 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 2 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 3 receive antennas .", "E) performance of the proposed asynchronous differential schemes for τ2 − τ1 = ts/2 , the synchronous differential schemes in [ 17 ] , and the synchronous coherent schemes using zf and ml decoding at a rate of 1 b/ ( s hz ) for 2 users each with 2 transmit antennas and 1 receiver with 2 receive antennas ." ]

[ "A) relative phase difference between port 4 and output ports .", "B) relative phase difference between port 1 and output ports .", "C) relative phase difference between port 2 and output ports .", "D) relative phase difference between port 3 and output ports .", "E) relative phase difference between output ports of the blc ." ]

[ "A) relative phase difference between output ports of the blc .", "B) relative phase difference between port 2 and output ports .", "C) relative phase difference between port 4 and output ports .", "D) relative phase difference between port 1 and output ports .", "E) relative phase difference between port 3 and output ports ." ]

[ "A) relative phase difference between port 2 and output ports .", "B) relative phase difference between output ports of the blc .", "C) relative phase difference between port 1 and output ports .", "D) relative phase difference between port 4 and output ports .", "E) relative phase difference between port 3 and output ports ." ]

[ "A) 8x8 rl beam to array spillover coupling amplitude .", "B) 4x4 rl beam to array spillover coupling amplitude .", "C) 8x8 rl beam to array coupling amplitude .", "D) 8x8 rl beam to array phase error .", "E) 4x4 rl beam to array spillover amplitude ." ]

[ "A) accuracy comparison with different number of selected features on isolet5 dataset .", "B) accuracy comparison with different number of selected features on musk2 dataset .", "C) accuracy comparison with different number of selected features on splice dataset .", "D) accuracy comparison with different number of selected features on isolets .", "E) accuracy comparison with different number of selected features on mfeat-zernike dataset ." ]

[ "A) comparison of the misdetection probability of various algorithms as a function of the sample size n for the case of one strong signal with ] 1 [ when 40p .", "B) comparison of the misdetection probability of various algorithms as a function of system size p with fixed ratio 4// np when there is no signal with [ ] .", "C) comparison of the misdetection probability of various algorithms as a function of the sample size n for the case of no signal with [ ] when 0p .", "D) comparison of the misdetection probability of various algorithms as a function of system size p with fixed ratio 4/1/ np when there is one strong signal with ] 15 [ .", "E) comparison of the misdetection probability of various algorithms as function of system size p with fixed ratio ." ]

[ "A) comparison of the misdetection probability of various algorithms as a function of system size p with fixed ratio 4// np when there is no signal with [ ] .", "B) comparison of the misdetection probability of various algorithms as a function of the sample size n for the case of no signal with [ ] when 0p .", "C) comparison of the misdetection probability of various algorithms as a function of the sample size n for the case of one strong signal with ] 1 [ when 40p .", "D) comparison of the misdetection probability of various algorithms as a function of system size p with fixed ratio 4/1/ np when there is one strong signal with ] 15 [ .", "E) comparison of the misdetection probability of various algorithms as function of system size p with fixed ratio ." ]

[ "A) comparison between predicted values and actual values of final boiling point during training process .", "B) comparison between predicted values and actual values during training process .", "C) comparison between residual values and actual values during training process .", "D) comparison between predicted values and actual values of initial boiling point during training process .", "E) comparison between predicted values and actual values during training process using mlfn-7 ( forest stock volume ) ." ]

[ "A) execution time for the task with matrix addition kernels .", "B) execution time ( ms ) on random arrays - log10 scale .", "C) execution time ( ms ) on sorted arrays .", "D) execution time ( ms ) on random arrays .", "E) execution time ( ms ) on sorted arrays - log10 scale ." ]