premise string | hypothesis string | label int64 |
|---|---|---|
| | MeanIU | F1score |
| --- | --- | --- |
| Levelset | 0.8235 | 0.8294 |
| CUMedNet | 0.9394 | 0.9454 |
| U-Net | 0.9479 | 0.9542 | | | OurFCN | 0.9586 | 0.9643 |
| --- | --- | --- |
| OurFCN+BR | 0.9617 | 0.9682 | | 1 |
| | MeanIU | F1score |
| --- | --- | --- |
| Levelset | 0.8235 | 0.8294 |
| CUMedNet | 0.9394 | 0.9454 |
| U-Net | 0.9479 | 0.9542 | | | | VGG-F | CaffeNet | GoogLeNet | VGG-16 | VGG-19 | ResNet-152 | Mean |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Baseline | 12.62 | 12.9 | 10.29 | 8.62 | 8.40 | 8.99 | 10.30 |
| FFF(w/oData) | 81.59 | 80.92 | 56.44 | 47.10 | 43.62 | 29.78 | 56.58 |
| Ours(w/oData) | 92.37 | 89.04 | 75.28 | 71.59 | 69.45 | 60.72 | 76.41 |
| UAP(wData) | 93.8 | 93.1 | 78.5 | 77.8 | 80.8 | 84.0 | 84.67 | | 0 |
| | MeanIU | F1score |
| --- | --- | --- |
| Levelset | 0.8235 | 0.8294 |
| CUMedNet | 0.9394 | 0.9454 |
| U-Net | 0.9479 | 0.9542 | | | OurFCN | 0.9586 | 0.9643 |
| --- | --- | --- |
| OurFCN+BR | 0.9617 | 0.9682 | | 1 |
| | MeanIU | F1score |
| --- | --- | --- |
| Levelset | 0.8235 | 0.8294 |
| CUMedNet | 0.9394 | 0.9454 |
| U-Net | 0.9479 | 0.9542 | | | Ours(w/oData) | 92.37 | 89.04 | 75.28 | 71.59 | 69.45 | 60.72 | 76.41 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| UAP(wData) | 93.8 | 93.1 | 78.5 | 77.8 | 80.8 | 84.0 | 84.67 | | 0 |
| Model | Recall | Precision | F1-Score |
| --- | --- | --- | --- |
| Concatenation-FC | 0.91 | 0.89 | 0.90 |
| OP-Concatenation | 0.93 | 0.90 | 0.91 | | | Bilinear-FC | 0.95 | 0.75 | 0.85 |
| --- | --- | --- | --- |
| OP-BilinearFusion | 0.97 | 0.96 | 0.96 | | 1 |
| Model | Recall | Precision | F1-Score |
| --- | --- | --- | --- |
| Concatenation-FC | 0.91 | 0.89 | 0.90 |
| OP-Concatenation | 0.93 | 0.90 | 0.91 | | | Model | Recall | Precision | F1-Score |
| --- | --- | --- | --- |
| AverageFusion | 0.90 | 0.92 | 0.91 |
| DempsterShaferFusion | 0.93 | 0.95 | 0.94 |
| Concatenation-FC | 0.91 | 0.89 | 0.90 |
| OP-Concatenation | 0.93 | 0.90 | 0.91 |
| OrderlessBilinear | 0.87 | 0.90 | 0.88 |
| OP-BilinearFusion | 0.97 | 0.96 | 0.96 | | 0 |
| Model | Recall | Precision | F1-Score |
| --- | --- | --- | --- |
| Concatenation-FC | 0.91 | 0.89 | 0.90 |
| OP-Concatenation | 0.93 | 0.90 | 0.91 | | | Bilinear-FC | 0.95 | 0.75 | 0.85 |
| --- | --- | --- | --- |
| OP-BilinearFusion | 0.97 | 0.96 | 0.96 | | 1 |
| Model | Recall | Precision | F1-Score |
| --- | --- | --- | --- |
| Concatenation-FC | 0.91 | 0.89 | 0.90 |
| OP-Concatenation | 0.93 | 0.90 | 0.91 | | | OP-Concatenation | 0.93 | 0.90 | 0.91 |
| --- | --- | --- | --- |
| OrderlessBilinear | 0.87 | 0.90 | 0.88 |
| OP-BilinearFusion | 0.97 | 0.96 | 0.96 | | 0 |
| | Model | FB15K<br>MRRHITS@10 | FB15K-237<br>MRRHITS@10 | WN18<br>MRRHITS@10 | NYT+FB<br>MRRHITS@10 |
| --- | --- | --- | --- | --- | --- |
| 1<br>2 | F<br>DM | 17.9423.82<br>44.7066.26 | 0.00.0<br>34.0752.93 | 0.190.24<br>75.9194.12 | 81.5193.67<br>62.4872.17 |
| 3<br>4<br>5 | E+F(AS)<br>DM+F(AS)<br>DM+E+F(AS) | 26.2437.35<br>22.4135.81<br>29.8942.00 | 29.7144.39<br>19.8141.95<br>33.6549.26 | 1.604.04<br>41.5473.32<br>22.9239.26 | 82.4692.21<br>81.4893.47<br>81.4191.41 | | | 6<br>7 | DM+F(AL)<br>DM+F(RAL) | 37.6159.0<br>45.8167.64 | 26.7749.77<br>33.3853.24 | 73.9593.22<br>74.5593.46 | 82.2895.63<br>82.2895.63 |
| --- | --- | --- | --- | --- | --- |
| 8 | DM+F(Oracle) | 49.4269.00 | 34.0752.93 | 75.9594.16 | 86.0695.73 | | 1 |
| | Model | FB15K<br>MRRHITS@10 | FB15K-237<br>MRRHITS@10 | WN18<br>MRRHITS@10 | NYT+FB<br>MRRHITS@10 |
| --- | --- | --- | --- | --- | --- |
| 1<br>2 | F<br>DM | 17.9423.82<br>44.7066.26 | 0.00.0<br>34.0752.93 | 0.190.24<br>75.9194.12 | 81.5193.67<br>62.4872.17 |
| 3<br>4<br>5 | E+F(AS)<br>DM+F(AS)<br>DM+E+F(AS) | 26.2437.35<br>22.4135.81<br>29.8942.00 | 29.7144.39<br>19.8141.95<br>33.6549.26 | 1.604.04<br>41.5473.32<br>22.9239.26 | 82.4692.21<br>81.4893.47<br>81.4191.41 | | | Index | σ0<br>Hp-valueCI2 | Index |
| --- | --- | --- |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.727]0.667<br>1<0.01[0,0.419]0.384<br>1<0.01[0,0.424]0.389<br>1<0.01[0,0.237]0.217 | WT5<br>WT6<br>A1<br>A2 |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.696]0.638<br>1<0.01[0,0.860]0.788<br>1<0.01[0,0.804]0.731<br>1<0.01[0,0.805]0.738 | WT5<br>WT6<br>A1<br>A2 |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.542]0.497<br>1<0.01[0,0.835]0.765<br>1<0.01[0,0.810]0.741<br>1<0.01[0,0.724]0.664 | WT5<br>WT6<br>A1<br>A2 |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.729]0.630<br>1<0.01[0,0.929]0.802<br>1<0.01[0,0.916]0.791<br>1<0.01[0,0.933]0.833 | WT5<br>WT6<br>A1<br>A2 | | 0 |
| | Model | FB15K<br>MRRHITS@10 | FB15K-237<br>MRRHITS@10 | WN18<br>MRRHITS@10 | NYT+FB<br>MRRHITS@10 |
| --- | --- | --- | --- | --- | --- |
| 1<br>2 | F<br>DM | 17.9423.82<br>44.7066.26 | 0.00.0<br>34.0752.93 | 0.190.24<br>75.9194.12 | 81.5193.67<br>62.4872.17 | | | 3<br>4<br>5 | E+F(AS)<br>DM+F(AS)<br>DM+E+F(AS) | 26.2437.35<br>22.4135.81<br>29.8942.00 | 29.7144.39<br>19.8141.95<br>33.6549.26 | 1.604.04<br>41.5473.32<br>22.9239.26 | 82.4692.21<br>81.4893.47<br>81.4191.41 |
| --- | --- | --- | --- | --- | --- |
| 6<br>7 | DM+F(AL)<br>DM+F(RAL) | 37.6159.0<br>45.8167.64 | 26.7749.77<br>33.3853.24 | 73.9593.22<br>74.5593.46 | 82.2895.63<br>82.2895.63 |
| 8 | DM+F(Oracle) | 49.4269.00 | 34.0752.93 | 75.9594.16 | 86.0695.73 | | 1 |
| | Model | FB15K<br>MRRHITS@10 | FB15K-237<br>MRRHITS@10 | WN18<br>MRRHITS@10 | NYT+FB<br>MRRHITS@10 |
| --- | --- | --- | --- | --- | --- |
| 1<br>2 | F<br>DM | 17.9423.82<br>44.7066.26 | 0.00.0<br>34.0752.93 | 0.190.24<br>75.9194.12 | 81.5193.67<br>62.4872.17 | | | WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.696]0.638<br>1<0.01[0,0.860]0.788<br>1<0.01[0,0.804]0.731<br>1<0.01[0,0.805]0.738 | WT5<br>WT6<br>A1<br>A2 |
| --- | --- | --- |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.542]0.497<br>1<0.01[0,0.835]0.765<br>1<0.01[0,0.810]0.741<br>1<0.01[0,0.724]0.664 | WT5<br>WT6<br>A1<br>A2 |
| WT1<br>WT2<br>WT3<br>WT4 | 1<0.01[0,0.729]0.630<br>1<0.01[0,0.929]0.802<br>1<0.01[0,0.916]0.791<br>1<0.01[0,0.933]0.833 | WT5<br>WT6<br>A1<br>A2 | | 0 |
| Step | Free | Sending | Receiving | Active |
| --- | --- | --- | --- | --- |
| 1 | 50,634 | 1 | 18 | 19 |
| 2 | 50,491 | 18 | 144 | 162 |
| 3 | 49,807 | 144 | 702 | 846 |
| 4 | 47,593 | 684 | 2,376 | 3,060 | | | 5 | 42,661 | 2,160 | 5,832 | 7,992 |
| --- | --- | --- | --- | --- |
| 6 | 35,425 | 4,752 | 10,476 | 15,228 |
| 7 | 29,809 | 7,236 | 13,608 | 20,844 |
| 8 | 31,861 | 7,128 | 11,664 | 18,792 |
| 9 | 40,933 | 3,888 | 5,832 | 9,720 |
| Total | | 26,011 | 50,652 | | | 1 |
| Step | Free | Sending | Receiving | Active |
| --- | --- | --- | --- | --- |
| 1 | 50,634 | 1 | 18 | 19 |
| 2 | 50,491 | 18 | 144 | 162 |
| 3 | 49,807 | 144 | 702 | 846 |
| 4 | 47,593 | 684 | 2,376 | 3,060 | | | Round | Step | Free | Sending | Receiving | Active |
| --- | --- | --- | --- | --- | --- |
| 1 | 1 | 50,646 | 1 | 6 | 7 |
| 2 | 50,635 | 6 | 12 | 18 | |
| 3 | 50,623 | 12 | 18 | 30 | |
| 2 | 1 | 50,394 | 37 | 222 | 259 |
| 2 | 49,987 | 222 | 444 | 666 | |
| 3 | 49,543 | 444 | 666 | 1,110 | |
| 3 | 1 | 41,070 | 1,369 | 8,214 | 9,583 |
| 2 | 26,011 | 8,214 | 16,428 | 24,642 | |
| 3 | 9,583 | 16,428 | 24,642 | 41,070 | |
| Total | 12 | | 26,733 | 50,652 | | | 0 |
| Step | Free | Sending | Receiving | Active |
| --- | --- | --- | --- | --- |
| 1 | 50,634 | 1 | 18 | 19 |
| 2 | 50,491 | 18 | 144 | 162 |
| 3 | 49,807 | 144 | 702 | 846 |
| 4 | 47,593 | 684 | 2,376 | 3,060 |
| 5 | 42,661 | 2,160 | 5,832 | 7,992 |
| 6 | 35,425 | 4,752 | 10,476 | 15,228 |
| 7 | 29,809 | 7,236 | 13,608 | 20,844 |
| 8 | 31,861 | 7,128 | 11,664 | 18,792 | | | 9 | 40,933 | 3,888 | 5,832 | 9,720 |
| --- | --- | --- | --- | --- |
| Total | | 26,011 | 50,652 | | | 1 |
| Step | Free | Sending | Receiving | Active |
| --- | --- | --- | --- | --- |
| 1 | 50,634 | 1 | 18 | 19 |
| 2 | 50,491 | 18 | 144 | 162 |
| 3 | 49,807 | 144 | 702 | 846 |
| 4 | 47,593 | 684 | 2,376 | 3,060 |
| 5 | 42,661 | 2,160 | 5,832 | 7,992 |
| 6 | 35,425 | 4,752 | 10,476 | 15,228 |
| 7 | 29,809 | 7,236 | 13,608 | 20,844 |
| 8 | 31,861 | 7,128 | 11,664 | 18,792 | | | 2 | 1 | 50,394 | 37 | 222 | 259 |
| --- | --- | --- | --- | --- | --- |
| 2 | 49,987 | 222 | 444 | 666 | |
| 3 | 49,543 | 444 | 666 | 1,110 | |
| 3 | 1 | 41,070 | 1,369 | 8,214 | 9,583 |
| 2 | 26,011 | 8,214 | 16,428 | 24,642 | |
| 3 | 9,583 | 16,428 | 24,642 | 41,070 | |
| Total | 12 | | 26,733 | 50,652 | | | 0 |
| | Rainyimages | GMM | SRCNN | DDN | JORDER | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | | | Rain100H | 0.38 | 13.56 | 0.43 | 15.05 | 0.70 | 22.84 | 0.76 | 21.92 | 0.83 | 26.54 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Rain100L | 0.84 | 26.90 | 0.86 | 28.65 | 0.91 | 29.39 | 0.93 | 32.16 | 0.97 | 36.63 |
| Rain12 | 0.86 | 30.14 | 0.91 | 32.02 | 0.92 | 31.90 | 0.94 | 31.76 | 0.95 | 33.92 |
| Parameters# | - | - | 20,099 | 57,369 | 369,792 | | | | | | | 1 |
| | Rainyimages | GMM | SRCNN | DDN | JORDER | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | | | ALF | MAP | LPA-ICI | GLDP | LLDO | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR |
| 22.36 | 0.66 | 23.33 | 0.74 | 24.17 | 0.76 | 24.58 | 0.78 | 25.01 | 0.80 | 27.63 |
| 22.99 | 0.64 | 23.95 | 0.77 | 25.04 | 0.79 | 25.40 | 0.81 | 25.55 | 0.82 | 27.69 |
| 21.82 | 0.62 | 22.63 | 0.72 | 23.14 | 0.72 | 23.66 | 0.77 | 24.17 | 0.78 | 26.35 |
| 25.41 | 0.71 | 26.24 | 0.78 | 27.88 | 0.83 | 27.12 | 0.80 | 28.48 | 0.85 | 31.79 |
| 22.14 | 0.64 | 22.46 | 0.69 | 24.12 | 0.77 | 23.86 | 0.75 | 24.61 | 0.80 | 27.27 |
| 30.92 | 0.87 | 28.25 | 0.77 | 30.70 | 0.87 | 30.92 | 0.87 | 31.07 | 0.87 | 31.44 | | 0 |
| | Rainyimages | GMM | SRCNN | DDN | JORDER | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | | | Rain100H | 0.38 | 13.56 | 0.43 | 15.05 | 0.70 | 22.84 | 0.76 | 21.92 | 0.83 | 26.54 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Rain100L | 0.84 | 26.90 | 0.86 | 28.65 | 0.91 | 29.39 | 0.93 | 32.16 | 0.97 | 36.63 |
| Rain12 | 0.86 | 30.14 | 0.91 | 32.02 | 0.92 | 31.90 | 0.94 | 31.76 | 0.95 | 33.92 |
| Parameters# | - | - | 20,099 | 57,369 | 369,792 | | | | | | | 1 |
| | Rainyimages | GMM | SRCNN | DDN | JORDER | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | SSIM | PSNR | | | 22.14 | 0.64 | 22.46 | 0.69 | 24.12 | 0.77 | 23.86 | 0.75 | 24.61 | 0.80 | 27.27 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 30.92 | 0.87 | 28.25 | 0.77 | 30.70 | 0.87 | 30.92 | 0.87 | 31.07 | 0.87 | 31.44 | | 0 |
| Phrase | v1Prob | v2Prob | v3Prob |
| --- | --- | --- | --- |
| ...al...↔...with... | 0.03 | 0.35 | 0.17 |
| ...al...↔...au... | - | 0.65 | 0.62 |
| ...en...↔...in... | 0.62 | 0.70 | - |
| ...en...↔...with... | - | 0.30 | - | | | ...del...↔...ofthe... | 0.09 | 1.0 | 1.0 |
| --- | --- | --- | --- |
| ...ala...↔...with... | - | 0.82 | 0.77 |
| ...ala...↔...a`la... | - | 0.18 | 0.12 | | 1 |
| Phrase | v1Prob | v2Prob | v3Prob |
| --- | --- | --- | --- |
| ...al...↔...with... | 0.03 | 0.35 | 0.17 |
| ...al...↔...au... | - | 0.65 | 0.62 |
| ...en...↔...in... | 0.62 | 0.70 | - |
| ...en...↔...with... | - | 0.30 | - | | | linguisticterm | level | 2-tuple |
| --- | --- | --- |
| NoAlcoholR | l(3,9) | 9<br>(s,0) |
| YoungLegalLimitL | l(3,9) | (s,.0125) |
| YoungLegalLimitR | l(5,33) | (s,.003) |
| IntermediateL | l(5,33) | (s,0) |
| IntermediateR | l(4,17) | (s,0) |
| LegalLimitL | l(4,17) | (s,.005) |
| LegalLimitR | l(1,3) | (s,−.07) |
| RiskOfDeathR | l(1,3) | (s,0)1 | | 0 |
| Phrase | v1Prob | v2Prob | v3Prob |
| --- | --- | --- | --- |
| ...al...↔...with... | 0.03 | 0.35 | 0.17 |
| ...al...↔...au... | - | 0.65 | 0.62 |
| ...en...↔...in... | 0.62 | 0.70 | - | | | ...en...↔...with... | - | 0.30 | - |
| --- | --- | --- | --- |
| ...del...↔...ofthe... | 0.09 | 1.0 | 1.0 |
| ...ala...↔...with... | - | 0.82 | 0.77 |
| ...ala...↔...a`la... | - | 0.18 | 0.12 | | 1 |
| Phrase | v1Prob | v2Prob | v3Prob |
| --- | --- | --- | --- |
| ...al...↔...with... | 0.03 | 0.35 | 0.17 |
| ...al...↔...au... | - | 0.65 | 0.62 |
| ...en...↔...in... | 0.62 | 0.70 | - | | | LegalLimitL | l(4,17) | (s,.005) |
| --- | --- | --- |
| LegalLimitR | l(1,3) | (s,−.07) |
| RiskOfDeathR | l(1,3) | (s,0)1 | | 0 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 8.08<br>16.14<br>24.24<br>32.32<br>40.35<br>48.42<br>56.44<br>64.55<br>72.82<br>80.81 | 0.57<br>1.11<br>1.70<br>2.24<br>2.79<br>3.35<br>3.96<br>4.25<br>5.75<br>5.28 | | | 8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 11.05<br>22.18<br>33.35<br>44.45<br>55.93<br>67.20<br>78.49<br>89.29<br>100.11<br>110.73 | 0.74<br>1.47<br>2.42<br>3.01<br>4.47<br>5.68<br>6.44<br>6.95<br>6.56<br>5.72 |
| --- | --- | --- | --- | --- |
| 9<br>9<br>9<br>9<br>9<br>9<br>9<br>9<br>9<br>9 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 14.79<br>29.53<br>44.34<br>59.05<br>73.88<br>88.45<br>103.35<br>118.30<br>133.38<br>148.22 | 0.98<br>1.96<br>2.88<br>3.43<br>4.89<br>5.05<br>6.07<br>7.87<br>9.18<br>10.25 |
| 10<br>10<br>10<br>10<br>10<br>10<br>10<br>10<br>10<br>10 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 0.99<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 19.40<br>38.81<br>58.13<br>77.29<br>96.43<br>115.80<br>135.03<br>154.55<br>173.59<br>193.07 | 1.53<br>3.02<br>4.21<br>5.23<br>5.55<br>6.77<br>7.83<br>10.13<br>9.64<br>11.72 | | 1 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 8.08<br>16.14<br>24.24<br>32.32<br>40.35<br>48.42<br>56.44<br>64.55<br>72.82<br>80.81 | 0.57<br>1.11<br>1.70<br>2.24<br>2.79<br>3.35<br>3.96<br>4.25<br>5.75<br>5.28 | | | GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 11<br>11<br>11<br>11 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.89<br>1.00 | 0.50<br>4.99<br>49.85<br>497.92 | 0.00<br>0.01<br>0.22<br>1.18 |
| 12<br>12<br>12<br>12 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.72<br>1.00 | 0.65<br>6.49<br>64.72<br>647.08 | 0.06<br>0.24<br>2.14<br>20.84 |
| 13<br>13<br>13<br>13 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.41<br>1.00 | 0.82<br>7.92<br>80.08<br>798.90 | 0.15<br>0.28<br>7.90<br>70.81 |
| 14<br>14<br>14<br>14 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.15<br>1.00 | 0.96<br>9.56<br>94.81<br>945.17 | 0.16<br>1.59<br>7.17<br>49.22 |
| 15<br>15<br>15<br>15 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.01<br>1.00 | 1.15<br>11.48<br>114.62<br>1145.78 | 0.05<br>0.22<br>2.17<br>21.49 | | 0 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 8.08<br>16.14<br>24.24<br>32.32<br>40.35<br>48.42<br>56.44<br>64.55<br>72.82<br>80.81 | 0.57<br>1.11<br>1.70<br>2.24<br>2.79<br>3.35<br>3.96<br>4.25<br>5.75<br>5.28 | | | 8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8<br>8 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 11.05<br>22.18<br>33.35<br>44.45<br>55.93<br>67.20<br>78.49<br>89.29<br>100.11<br>110.73 | 0.74<br>1.47<br>2.42<br>3.01<br>4.47<br>5.68<br>6.44<br>6.95<br>6.56<br>5.72 |
| --- | --- | --- | --- | --- |
| 9<br>9<br>9<br>9<br>9<br>9<br>9<br>9<br>9<br>9 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 14.79<br>29.53<br>44.34<br>59.05<br>73.88<br>88.45<br>103.35<br>118.30<br>133.38<br>148.22 | 0.98<br>1.96<br>2.88<br>3.43<br>4.89<br>5.05<br>6.07<br>7.87<br>9.18<br>10.25 |
| 10<br>10<br>10<br>10<br>10<br>10<br>10<br>10<br>10<br>10 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 0.99<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 19.40<br>38.81<br>58.13<br>77.29<br>96.43<br>115.80<br>135.03<br>154.55<br>173.59<br>193.07 | 1.53<br>3.02<br>4.21<br>5.23<br>5.55<br>6.77<br>7.83<br>10.13<br>9.64<br>11.72 | | 1 |
| GridSize | SampleCoefficient | Accuracy | timeAVR(secs) | timeSD(secs) |
| --- | --- | --- | --- | --- |
| 7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7<br>7 | 10000<br>20000<br>30000<br>40000<br>50000<br>60000<br>70000<br>80000<br>90000<br>100000 | 1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00<br>1.00 | 8.08<br>16.14<br>24.24<br>32.32<br>40.35<br>48.42<br>56.44<br>64.55<br>72.82<br>80.81 | 0.57<br>1.11<br>1.70<br>2.24<br>2.79<br>3.35<br>3.96<br>4.25<br>5.75<br>5.28 | | | 13<br>13<br>13<br>13 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.41<br>1.00 | 0.82<br>7.92<br>80.08<br>798.90 | 0.15<br>0.28<br>7.90<br>70.81 |
| --- | --- | --- | --- | --- |
| 14<br>14<br>14<br>14 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.15<br>1.00 | 0.96<br>9.56<br>94.81<br>945.17 | 0.16<br>1.59<br>7.17<br>49.22 |
| 15<br>15<br>15<br>15 | 100<br>1000<br>10000<br>100000 | 0.00<br>0.00<br>0.01<br>1.00 | 1.15<br>11.48<br>114.62<br>1145.78 | 0.05<br>0.22<br>2.17<br>21.49 | | 0 |
| Algorithm | H.264 | JP2K | | | |
| --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | | | SSIM | 0.7674 | 0.5464 | 0.8843 | 0.7283 | 0.5974 | 0.9202 |
| --- | --- | --- | --- | --- | --- | --- |
| MS-SSIM | 0.8795 | 0.6673 | 0.6955 | 0.9414 | 0.9299 | 0.4327 |
| SBIQE | 0.0062 | 0.0058 | 1.9856 | 0.0120 | 0.0574 | 1.0289 |
| BRISQUE | 0.7915 | 0.7637 | 0.7912 | 0.8048 | 0.8999 | 0.5687 |
| NIQE | 0.6814 | 0.6412 | 0.8715 | 0.6558 | 0.6427 | 0.7157 |
| STMAD | 0.7641 | 0.7354 | 0.7296 | 0.8388 | 0.7236 | 0.7136 |
| FLOSIM | 0.9265 | 0.8987 | 0.4256 | 0.9665 | 0.9495 | 0.3359 |
| Chenetal. | 0.6618 | 0.5720 | 0.6915 | 0.8723 | 0.8724 | 0.6182 |
| STRIQE | 0.7430 | 0.7167 | 0.8433 | 0.8403 | 0.8175 | 0.5666 |
| VQUEMODES(NIQE) | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | 1 |
| Algorithm | H.264 | JP2K | | | |
| --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | | | | Algorithm | H.264 | JP2K | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | | |
| VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | |
| NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | | 0 |
| Algorithm | H.264 | JP2K | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.7674 | 0.5464 | 0.8843 | 0.7283 | 0.5974 | 0.9202 | | | MS-SSIM | 0.8795 | 0.6673 | 0.6955 | 0.9414 | 0.9299 | 0.4327 |
| --- | --- | --- | --- | --- | --- | --- |
| SBIQE | 0.0062 | 0.0058 | 1.9856 | 0.0120 | 0.0574 | 1.0289 |
| BRISQUE | 0.7915 | 0.7637 | 0.7912 | 0.8048 | 0.8999 | 0.5687 |
| NIQE | 0.6814 | 0.6412 | 0.8715 | 0.6558 | 0.6427 | 0.7157 |
| STMAD | 0.7641 | 0.7354 | 0.7296 | 0.8388 | 0.7236 | 0.7136 |
| FLOSIM | 0.9265 | 0.8987 | 0.4256 | 0.9665 | 0.9495 | 0.3359 |
| Chenetal. | 0.6618 | 0.5720 | 0.6915 | 0.8723 | 0.8724 | 0.6182 |
| STRIQE | 0.7430 | 0.7167 | 0.8433 | 0.8403 | 0.8175 | 0.5666 |
| VQUEMODES(NIQE) | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | 1 |
| Algorithm | H.264 | JP2K | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.7674 | 0.5464 | 0.8843 | 0.7283 | 0.5974 | 0.9202 | | | VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | |
| NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | | 0 |
| FileSize(MB) | No.OfAttackers | TrafficVol. |
| --- | --- | --- |
| 10 | 100 | 0.22GB |
| 50 | 500 | 0.67GB |
| 100 | 1500 | 1.67GB |
| 200 | 2000 | 3.23GB | | | 400 | 4000 | 5.91GB |
| --- | --- | --- |
| 600 | 6000 | 9.14GB |
| 800 | 8000 | 12.37GB |
| 1000 | 10,000 | 15.83GB | | 1 |
| FileSize(MB) | No.OfAttackers | TrafficVol. |
| --- | --- | --- |
| 10 | 100 | 0.22GB |
| 50 | 500 | 0.67GB |
| 100 | 1500 | 1.67GB |
| 200 | 2000 | 3.23GB | | | | | | | | |
| --- | --- | --- | --- | --- | --- |
| | | | | | |
| 2 | 0.315 | 97Mb | 2 | 0.345 | 256Mb |
| 2 | 0.282 | 388Mb | 2 | 0.321 | 1024Mb |
| 2 | 0.259 | 1552Mb | 2 | 0.305 | 4096Mb | | 0 |
| FileSize(MB) | No.OfAttackers | TrafficVol. |
| --- | --- | --- |
| 10 | 100 | 0.22GB |
| 50 | 500 | 0.67GB |
| 100 | 1500 | 1.67GB |
| 200 | 2000 | 3.23GB |
| 400 | 4000 | 5.91GB | | | 600 | 6000 | 9.14GB |
| --- | --- | --- |
| 800 | 8000 | 12.37GB |
| 1000 | 10,000 | 15.83GB | | 1 |
| FileSize(MB) | No.OfAttackers | TrafficVol. |
| --- | --- | --- |
| 10 | 100 | 0.22GB |
| 50 | 500 | 0.67GB |
| 100 | 1500 | 1.67GB |
| 200 | 2000 | 3.23GB |
| 400 | 4000 | 5.91GB | | | 2 | 0.282 | 388Mb | 2 | 0.321 | 1024Mb |
| --- | --- | --- | --- | --- | --- |
| 2 | 0.259 | 1552Mb | 2 | 0.305 | 4096Mb | | 0 |
| Qvalue | fastgreedy | Louvain |
| --- | --- | --- |
| 0 | 3.194 | 8.356 | | | 0.2 | 3.959 | 59.589 |
| --- | --- | --- |
| 0.4 | 257.696 | 331.810 |
| 0.6 | 389.301 | 421.305 |
| 0.8 | 443.650 | 454.558 | | 1 |
| Qvalue | fastgreedy | Louvain |
| --- | --- | --- |
| 0 | 3.194 | 8.356 | | | Qvalue | fastgreedy | Louvain |
| --- | --- | --- |
| 0 | 0.1409 | 0.1184 |
| 0.2 | 0.369 | 0.00386 |
| 0.4 | 0.00016 | 0.00016 |
| 0.6 | 0.00016 | 0.00012 |
| 0.8 | 0.00016 | 8e-05 | | 0 |
| Qvalue | fastgreedy | Louvain |
| --- | --- | --- |
| 0 | 3.194 | 8.356 | | | 0.2 | 3.959 | 59.589 |
| --- | --- | --- |
| 0.4 | 257.696 | 331.810 |
| 0.6 | 389.301 | 421.305 |
| 0.8 | 443.650 | 454.558 | | 1 |
| Qvalue | fastgreedy | Louvain |
| --- | --- | --- |
| 0 | 3.194 | 8.356 | | | 0.4 | 0.00016 | 0.00016 |
| --- | --- | --- |
| 0.6 | 0.00016 | 0.00012 |
| 0.8 | 0.00016 | 8e-05 | | 0 |
| Node | Benchmark<br>(inGFlops) | CPU<br>(inGHz) | RAM<br>(inGB) |
| --- | --- | --- | --- |
| Mobile(small) | 1.09 | 1.3(Dual) | 1 |
| Mobile(medium) | 1.24 | 1.4(Dual) | 1 | | | Cloudlet | 2.56 | 2.5(Quad) | 16 |
| --- | --- | --- | --- |
| Cloud(small) | 2.32 | 2.4(Single) | 1 |
| Cloud(medium) | 2.94 | 2.8(Quad) | 7.5 |
| Cloud(large) | 3.02 | 2.8(Octa) | 15 | | 1 |
| Node | Benchmark<br>(inGFlops) | CPU<br>(inGHz) | RAM<br>(inGB) |
| --- | --- | --- | --- |
| Mobile(small) | 1.09 | 1.3(Dual) | 1 |
| Mobile(medium) | 1.24 | 1.4(Dual) | 1 | | | MEM(GB) | CPU(units) | BW(G) | VM |
| --- | --- | --- | --- |
| 1.7 | 1(1coresx1units) | 160 | 1-1(1) |
| 7.5 | 4(2coresx2units) | 850 | 1-2(2) |
| 15.0 | 8(4coresx2units) | 1690 | 1-3(3) |
| 17.1 | 6.5(2coresx3.25units) | 420 | 2-1(4) |
| 34.2 | 13(4coresx3.25units) | 850 | 2-2(5) |
| 68.4 | 26(8coresx3.25units) | 1690 | 2-3(6) |
| 1.7 | 5(2coresx2.5units) | 350 | 3-1(7) |
| 7.0 | 20(8coresx2.5units) | 1690 | 3-2(8) | | 0 |
| Node | Benchmark<br>(inGFlops) | CPU<br>(inGHz) | RAM<br>(inGB) |
| --- | --- | --- | --- |
| Mobile(small) | 1.09 | 1.3(Dual) | 1 |
| Mobile(medium) | 1.24 | 1.4(Dual) | 1 |
| Cloudlet | 2.56 | 2.5(Quad) | 16 | | | Cloud(small) | 2.32 | 2.4(Single) | 1 |
| --- | --- | --- | --- |
| Cloud(medium) | 2.94 | 2.8(Quad) | 7.5 |
| Cloud(large) | 3.02 | 2.8(Octa) | 15 | | 1 |
| Node | Benchmark<br>(inGFlops) | CPU<br>(inGHz) | RAM<br>(inGB) |
| --- | --- | --- | --- |
| Mobile(small) | 1.09 | 1.3(Dual) | 1 |
| Mobile(medium) | 1.24 | 1.4(Dual) | 1 |
| Cloudlet | 2.56 | 2.5(Quad) | 16 | | | 7.5 | 4(2coresx2units) | 850 | 1-2(2) |
| --- | --- | --- | --- |
| 15.0 | 8(4coresx2units) | 1690 | 1-3(3) |
| 17.1 | 6.5(2coresx3.25units) | 420 | 2-1(4) |
| 34.2 | 13(4coresx3.25units) | 850 | 2-2(5) |
| 68.4 | 26(8coresx3.25units) | 1690 | 2-3(6) |
| 1.7 | 5(2coresx2.5units) | 350 | 3-1(7) |
| 7.0 | 20(8coresx2.5units) | 1690 | 3-2(8) | | 0 |
| | ClusterSize | Benign | Vandal | Complement |
| --- | --- | --- | --- | --- |
| C1 | 2537 | 2448 | 89 | 0 | | | C2 | 2420 | 93 | 2327 | 0 |
| --- | --- | --- | --- | --- |
| C3 | 2840 | 0 | 0 | 2840 |
| Isolated | 1203 | 459 | 584 | 160 | | 1 |
| | ClusterSize | Benign | Vandal | Complement |
| --- | --- | --- | --- | --- |
| C1 | 2537 | 2448 | 89 | 0 | | | Clusters | 1-rule | 2-rule |
| --- | --- | --- |
| 1 | 29.4 | 34.3 |
| 2 | 31.4 | 35.5 |
| 3 | 31.8 | 36.2 |
| 4 | 31.7 | 37.0 |
| 5 | 32.3 | 37.2 |
| 6 | 31.9 | 37.3 |
| 10 | 32.8 | 37.5 |
| 20 | 35.1 | 38.3 |
| 40 | 35.8 | 38.9 | | 0 |
| | ClusterSize | Benign | Vandal | Complement |
| --- | --- | --- | --- | --- |
| C1 | 2537 | 2448 | 89 | 0 |
| C2 | 2420 | 93 | 2327 | 0 | | | C3 | 2840 | 0 | 0 | 2840 |
| --- | --- | --- | --- | --- |
| Isolated | 1203 | 459 | 584 | 160 | | 1 |
| | ClusterSize | Benign | Vandal | Complement |
| --- | --- | --- | --- | --- |
| C1 | 2537 | 2448 | 89 | 0 |
| C2 | 2420 | 93 | 2327 | 0 | | | 5 | 32.3 | 37.2 |
| --- | --- | --- |
| 6 | 31.9 | 37.3 |
| 10 | 32.8 | 37.5 |
| 20 | 35.1 | 38.3 |
| 40 | 35.8 | 38.9 | | 0 |
| S1:PersonalFeatures | S1:NNLabels | S2:GPInput | S2:Output | |
| --- | --- | --- | --- | --- |
| NN-MV | | | | |
| None | VAS,OPI | VAS,OPI | 2.32(0.25) | 2.56(0.12) |
| VAS | 2.24(0.27) | | | |
| VAS | VAS | 2.30(0.26) | 2.82(0.05) | |
| 3rdNNlayer | VAS,OPI | VAS,OPI | 2.34(0.27) | 2.58(0.19) | | | VAS | 2.18(0.35) | | | |
| --- | --- | --- | --- | --- |
| VAS | VAS | 2.24(0.25) | 2.65(0.17) | |
| NNinput | VAS,OPI | VAS,OPI | 2.41(0.23) | 2.48(0.14) |
| VAS | 2.22(0.27) | | | |
| VAS | VAS | 2.22(0.30) | 2.53(0.18) | | | 1 |
| S1:PersonalFeatures | S1:NNLabels | S2:GPInput | S2:Output | |
| --- | --- | --- | --- | --- |
| NN-MV | | | | |
| None | VAS,OPI | VAS,OPI | 2.32(0.25) | 2.56(0.12) |
| VAS | 2.24(0.27) | | | |
| VAS | VAS | 2.30(0.26) | 2.82(0.05) | |
| 3rdNNlayer | VAS,OPI | VAS,OPI | 2.34(0.27) | 2.58(0.19) | | | Layer | AVGPower[mW] | ExecTime[ms] | L3-L2Time[ms] |
| --- | --- | --- | --- |
| conv1+pool | 89.01 | 12.95 | 0.02 |
| ReLU | 52.07 | 0.46 | — |
| conv2+ReLU | 87.96 | 11.12 | 0.13 |
| conv3 | 77.46 | 11.85 | 0.13 |
| conv4 | 83.56 | 5.49 | 0.02 |
| add | 37.75 | 0.12 | — |
| ReLU | 36.81 | 0.12 | — |
| conv5+ReLU | 78.10 | 8.34 | 0.26 |
| conv6 | 91.72 | 9.35 | 0.51 |
| conv7 | 66.53 | 2.08 | 0.04 |
| add | 34.98 | 0.12 | — |
| ReLU | 34.01 | 0.11 | — |
| conv8+ReLU | 87.49 | 6.37 | 1.01 |
| conv9 | 89.67 | 11.91 | 2.02 |
| conv10 | 66.00 | 2.59 | 0.12 |
| add+ReLU | 34.30 | 0.11 | — |
| fully1 | 30.76 | 0.04 | 0.09 |
| fully2 | 36.74 | 0.04 | 0.09 | | 0 |
| S1:PersonalFeatures | S1:NNLabels | S2:GPInput | S2:Output |
| --- | --- | --- | --- |
| NN-MV | | | | | | None | VAS,OPI | VAS,OPI | 2.32(0.25) | 2.56(0.12) |
| --- | --- | --- | --- | --- |
| VAS | 2.24(0.27) | | | |
| VAS | VAS | 2.30(0.26) | 2.82(0.05) | |
| 3rdNNlayer | VAS,OPI | VAS,OPI | 2.34(0.27) | 2.58(0.19) |
| VAS | 2.18(0.35) | | | |
| VAS | VAS | 2.24(0.25) | 2.65(0.17) | |
| NNinput | VAS,OPI | VAS,OPI | 2.41(0.23) | 2.48(0.14) |
| VAS | 2.22(0.27) | | | |
| VAS | VAS | 2.22(0.30) | 2.53(0.18) | | | 1 |
| S1:PersonalFeatures | S1:NNLabels | S2:GPInput | S2:Output |
| --- | --- | --- | --- |
| NN-MV | | | | | | ReLU | 36.81 | 0.12 | — |
| --- | --- | --- | --- |
| conv5+ReLU | 78.10 | 8.34 | 0.26 |
| conv6 | 91.72 | 9.35 | 0.51 |
| conv7 | 66.53 | 2.08 | 0.04 |
| add | 34.98 | 0.12 | — |
| ReLU | 34.01 | 0.11 | — |
| conv8+ReLU | 87.49 | 6.37 | 1.01 |
| conv9 | 89.67 | 11.91 | 2.02 |
| conv10 | 66.00 | 2.59 | 0.12 |
| add+ReLU | 34.30 | 0.11 | — |
| fully1 | 30.76 | 0.04 | 0.09 |
| fully2 | 36.74 | 0.04 | 0.09 | | 0 |
| | LassoDAG | DAG-W |
| --- | --- | --- |
| p | SensitivitySpecificity | SensitivitySpecificity |
| 50 | 0.61561.0000 | 0.78280.9980 |
| 100 | 0.4826∼1 | 0.75240.9977 |
| 200 | 0.3969∼1 | 0.74050.9975 |
| 500 | 0.2497∼1 | 0.65170.9982 |
| 1000 | 0.17480.9991 | 0.42480.9971 | | | 1500 | 0.12260.9981 | 0.26720.9962 |
| --- | --- | --- |
| 2000 | 0.09890.9967 | 0.19440.9944 | | 1 |
| | LassoDAG | DAG-W |
| --- | --- | --- |
| p | SensitivitySpecificity | SensitivitySpecificity |
| 50 | 0.61561.0000 | 0.78280.9980 |
| 100 | 0.4826∼1 | 0.75240.9977 |
| 200 | 0.3969∼1 | 0.74050.9975 |
| 500 | 0.2497∼1 | 0.65170.9982 |
| 1000 | 0.17480.9991 | 0.42480.9971 | | | Threshold | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1.0 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Sensitivity | 1 | 1 | 1 | 0.99 | 0.96 | 0.76 | 0.31 |
| Specificity | 0 | 0.01 | 0.03 | 0.14 | 0.51 | 0.88 | 0.98 |
| Accuracy | 0.53 | 0.54 | 0.55 | 0.59 | 0.75 | 0.82 | 0.62 |
| R0 | 0.00 | 0.01 | 0.03 | 0.14 | 0.51 | 0.88 | 0.98 |
| R1 | 1.00 | 1.00 | 1.00 | 0.97 | 0.92 | 0.60 | 0.18 |
| R2 | 1.00 | 1.00 | 1.00 | 1.00 | 0.96 | 0.72 | 0.29 |
| R3 | 1.00 | 1.00 | 1.00 | 1.00 | 0.98 | 0.92 | 0.42 | | 0 |
| | LassoDAG | DAG-W |
| --- | --- | --- |
| p | SensitivitySpecificity | SensitivitySpecificity |
| 50 | 0.61561.0000 | 0.78280.9980 |
| 100 | 0.4826∼1 | 0.75240.9977 |
| 200 | 0.3969∼1 | 0.74050.9975 | | | 500 | 0.2497∼1 | 0.65170.9982 |
| --- | --- | --- |
| 1000 | 0.17480.9991 | 0.42480.9971 |
| 1500 | 0.12260.9981 | 0.26720.9962 |
| 2000 | 0.09890.9967 | 0.19440.9944 | | 1 |
| | LassoDAG | DAG-W |
| --- | --- | --- |
| p | SensitivitySpecificity | SensitivitySpecificity |
| 50 | 0.61561.0000 | 0.78280.9980 |
| 100 | 0.4826∼1 | 0.75240.9977 |
| 200 | 0.3969∼1 | 0.74050.9975 | | | R1 | 1.00 | 1.00 | 1.00 | 0.97 | 0.92 | 0.60 | 0.18 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| R2 | 1.00 | 1.00 | 1.00 | 1.00 | 0.96 | 0.72 | 0.29 |
| R3 | 1.00 | 1.00 | 1.00 | 1.00 | 0.98 | 0.92 | 0.42 | | 0 |
| Comparisonmethodsonhandposeestimation | averagejointerror(mm) |
| --- | --- |
| RF | 24.81 | | | CNN | 18.82 |
| --- | --- |
| Tompsonet.al. | 21.00 |
| Oberwegeret.al. | 20.00 |
| Oberwegeret.al. | 16.50 |
| Zhouet.al. | 16.90 |
| Lie-X(w/omultipleinitialposes) | 20.50 |
| Lie-X(w/olearnedmetric) | 16.72 |
| Lie-X | 14.51 | | 1 |
| Comparisonmethodsonhandposeestimation | averagejointerror(mm) |
| --- | --- |
| RF | 24.81 | | | OverallScore | Uniformweights | ActualWeights | LinearRegression | HuberRegression | OrdinaryLS |
| --- | --- | --- | --- | --- | --- |
| Final(Normalized) | 7.2368 | 6.1644 | 0.5690 | 0.5280 | 0.6804 |
| Midterm(Normalized) | 2.9898 | 3.2856 | 0.3802 | 0.3967 | 0.3161 |
| Final(Actual) | 8.0209 | 6.3726 | 0.6013 | 0.7234 | 0.7190 |
| Midterm(Actual) | 17.5650 | 17.51134 | 0.5218 | 0.5094 | 0.4338 | | 0 |
| Comparisonmethodsonhandposeestimation | averagejointerror(mm) |
| --- | --- |
| RF | 24.81 |
| CNN | 18.82 | | | Tompsonet.al. | 21.00 |
| --- | --- |
| Oberwegeret.al. | 20.00 |
| Oberwegeret.al. | 16.50 |
| Zhouet.al. | 16.90 |
| Lie-X(w/omultipleinitialposes) | 20.50 |
| Lie-X(w/olearnedmetric) | 16.72 |
| Lie-X | 14.51 | | 1 |
| Comparisonmethodsonhandposeestimation | averagejointerror(mm) |
| --- | --- |
| RF | 24.81 |
| CNN | 18.82 | | | Final(Actual) | 8.0209 | 6.3726 | 0.6013 | 0.7234 | 0.7190 |
| --- | --- | --- | --- | --- | --- |
| Midterm(Actual) | 17.5650 | 17.51134 | 0.5218 | 0.5094 | 0.4338 | | 0 |
| Surfaceexpression(Notincluding“wa”) | Example | Weight |
| --- | --- | --- |
| Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | [Johnni(to)]shita(done). | 16 | | | Nounga(subject)/mo/da/nara/koso | Johnga(subject)shita(done). | 15 |
| --- | --- | --- |
| Nounwo(object)/ni/,/. | Johnni(object)shita(done). | 14 |
| Nounhe(to)/de(in)/kara(from)/yori | gakkou(school)he(to)iku(go). | 13 | | 1 |
| Surfaceexpression(Notincluding“wa”) | Example | Weight |
| --- | --- | --- |
| Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | [Johnni(to)]shita(done). | 16 | | | Surfaceexpression | Example | Weight |
| --- | --- | --- |
| Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | (Johnni(to))shita(done). | 16 |
| Nounga(subject)/mo/da/nara | Johnga(subject)shita(do). | 15 |
| Nounwo(object)/ni/,/. | Johnni(object)shita(do). | 14 |
| Nounhe(to)/de(in)/kara(from) | gakkou(school)he(to)iku(go). | 13 | | 0 |
| Surfaceexpression(Notincluding“wa”) | Example | Weight |
| --- | --- | --- |
| Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | [Johnni(to)]shita(done). | 16 | | | Nounga(subject)/mo/da/nara/koso | Johnga(subject)shita(done). | 15 |
| --- | --- | --- |
| Nounwo(object)/ni/,/. | Johnni(object)shita(done). | 14 |
| Nounhe(to)/de(in)/kara(from)/yori | gakkou(school)he(to)iku(go). | 13 | | 1 |
| Surfaceexpression(Notincluding“wa”) | Example | Weight |
| --- | --- | --- |
| Pronoun/zero-pronounwo(object)/ni(to)/kara(from) | [Johnni(to)]shita(done). | 16 | | | Nounga(subject)/mo/da/nara | Johnga(subject)shita(do). | 15 |
| --- | --- | --- |
| Nounwo(object)/ni/,/. | Johnni(object)shita(do). | 14 |
| Nounhe(to)/de(in)/kara(from) | gakkou(school)he(to)iku(go). | 13 | | 0 |
| 0 | 0 | 0 | 0 |
| --- | --- | --- | --- |
| 41 | 75 | 39 | 0 |
| 87 | 95 | 88 | 0 |
| 98 | 100 | 100 | 4 | | | 100 | 100 | 100 | 7 |
| --- | --- | --- | --- |
| 100 | 100 | 100 | 13 | | 1 |
| 0 | 0 | 0 | 0 |
| --- | --- | --- | --- |
| 41 | 75 | 39 | 0 |
| 87 | 95 | 88 | 0 |
| 98 | 100 | 100 | 4 | | | 1 | 100 | 0.5 | 46.889 |
| --- | --- | --- | --- |
| 1 | 100 | 0.5 | 110.956 |
| 1 | 100 | 0.5 | 135.143 |
| 2 | 100 | 0.5 | 46.844 |
| 3 | 100 | 0.5 | 47.029 |
| 1 | 200 | 0.5 | 49.069 |
| 1 | 300 | 0.5 | 50.632 |
| 1 | 400 | 0.5 | 54.916 |
| 1 | 100 | 0 | 45.034 |
| 1 | 100 | 0.1 | 47.353 | | 0 |
| 0 | 0 | 0 | 0 |
| --- | --- | --- | --- |
| 41 | 75 | 39 | 0 | | | 87 | 95 | 88 | 0 |
| --- | --- | --- | --- |
| 98 | 100 | 100 | 4 |
| 100 | 100 | 100 | 7 |
| 100 | 100 | 100 | 13 | | 1 |
| 0 | 0 | 0 | 0 |
| --- | --- | --- | --- |
| 41 | 75 | 39 | 0 | | | 1 | 400 | 0.5 | 54.916 |
| --- | --- | --- | --- |
| 1 | 100 | 0 | 45.034 |
| 1 | 100 | 0.1 | 47.353 | | 0 |
| Generatingall<br>possibleparent<br>sets(Sec.) | Generatingparent<br>setswithasizelimit<br>of4(Sec.) |
| --- | --- |
| 0.011 | 1×10 | | | 0.017 | 1.29×10 |
| --- | --- |
| 0.065 | 1.66×10 |
| 0.104 | 2.38×10 |
| 0.195 | 2.86×10 |
| 0.297 | 2.93×10 |
| 0.645 | 4.04×10 |
| 1.248 | 4.48×10 |
| 3.425 | 5.43×10 |
| 6.814 | 5.88×10 |
| 12.185 | 7.51×10 | | 1 |
| Generatingall<br>possibleparent<br>sets(Sec.) | Generatingparent<br>setswithasizelimit<br>of4(Sec.) |
| --- | --- |
| 0.011 | 1×10 | | | M | RunningTime(sec) | M | RunningTime(sec) |
| --- | --- | --- | --- |
| 1 | −2<br>1.10×10 | 40 | −1<br>3.74×10 |
| 2 | 2.04×10 | 50 | 4.61×10 |
| 4 | 3.51×10 | 80 | 7.46×10 |
| 5 | 5.01×10 | 100 | 9.32×10 |
| 8 | 8.24×10 | 200 | 1.81 |
| 10 | 9.02×10 | 250 | 2.41 |
| 16 | 1.60×10 | 400 | 3.90 |
| 20 | 1.84×10 | 500 | 5.14 |
| 25 | 2.38×10 | 1,000 | 11.31 | | 0 |
| Generatingall<br>possibleparent<br>sets(Sec.) | Generatingparent<br>setswithasizelimit<br>of4(Sec.) |
| --- | --- |
| 0.011 | 1×10 |
| 0.017 | 1.29×10 |
| 0.065 | 1.66×10 |
| 0.104 | 2.38×10 |
| 0.195 | 2.86×10 |
| 0.297 | 2.93×10 | | | 0.645 | 4.04×10 |
| --- | --- |
| 1.248 | 4.48×10 |
| 3.425 | 5.43×10 |
| 6.814 | 5.88×10 |
| 12.185 | 7.51×10 | | 1 |
| Generatingall<br>possibleparent<br>sets(Sec.) | Generatingparent<br>setswithasizelimit<br>of4(Sec.) |
| --- | --- |
| 0.011 | 1×10 |
| 0.017 | 1.29×10 |
| 0.065 | 1.66×10 |
| 0.104 | 2.38×10 |
| 0.195 | 2.86×10 |
| 0.297 | 2.93×10 | | | 4 | 3.51×10 | 80 | 7.46×10 |
| --- | --- | --- | --- |
| 5 | 5.01×10 | 100 | 9.32×10 |
| 8 | 8.24×10 | 200 | 1.81 |
| 10 | 9.02×10 | 250 | 2.41 |
| 16 | 1.60×10 | 400 | 3.90 |
| 20 | 1.84×10 | 500 | 5.14 |
| 25 | 2.38×10 | 1,000 | 11.31 | | 0 |
| #cls.,p | Polish0.07<br>acc.#cls. | Polish0.15<br>acc.#cls. | Polish0.3<br>acc.#cls. | Metis<br>acc.#cls. | DBscan<br>acc.#cls. |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.3 | 0.8192,162 | 0.6581,438 | 0.1983,789 | 0.0551,166 | 0.273131 | | | 3,000,0.3 | 0.46023,929 | 0.4544,108 | 0.1534,441 | 0.1082,787 | 0.215692 |
| --- | --- | --- | --- | --- | --- |
| 10,000,0.3 | 0.54324,965 | 0.4831,4053 | 0.1571,6940 | 0.5119,587 | 0.2272111 |
| 1,000,0.5 | 0.9942,666 | 0.9161,128 | 0.4731,973 | 0.0681,166 | 0.329193 |
| 3,000,0.5 | 0.9955,925 | 0.8153,853 | 0.2825,904 | 0.1132,787 | 0.230690 |
| 10,000,0.5 | 0.99713,653 | 0.83212,449 | 0.30420,301 | 0.5329,587 | 0.2472,201 |
| 1,000,0.9 | 12453 | 0.9975,761 | 0.8664,830 | 0.0671,156 | 0.363218 |
| 3,000,0.9 | 114,784 | 0.98910,756 | 0.7689,262 | 0.1102,775 | 0.207592 |
| 10,000,0.9 | 1254,357 | 0.99132,705 | 0.7823,2676 | 0.4709,543 | 0.2302,062 |
| 1,000,1.0 | 11803 | 0.9971,939 | 0.9261,705 | 0.081754 | 0.371205 |
| 3,000,1.0 | 15703 | 0.9858,018 | 0.8085,735 | 0.1341,986 | 0.237523 |
| 10,000,1.0 | 112,343 | 0.98819,293 | 0.82618,565 | 0.6816,739 | 0.2601,838 | | 1 |
| #cls.,p | Polish0.07<br>acc.#cls. | Polish0.15<br>acc.#cls. | Polish0.3<br>acc.#cls. | Metis<br>acc.#cls. | DBscan<br>acc.#cls. |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.3 | 0.8192,162 | 0.6581,438 | 0.1983,789 | 0.0551,166 | 0.273131 | | | #cls.,p | Polish0.07<br>acc.#cls. | Polish0.15<br>acc.#cls. | Polish0.3<br>acc.#cls. | Metis<br>acc.#cls. | DBscan<br>acc.#cls. |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.3 | 0.9931,601 | 0.7981,552 | 0.2294,891 | 0.0721,396 | 0.256710 |
| 3,000,0.3 | 0.9913,217 | 0.4845,075 | 0.1461,631 | 0.1193,299 | 0.1902,404 |
| 10,000,0.3 | 0.99311,088 | 0.57415,970 | 0.15310,169 | 0.30511,431 | 0.2037,868 |
| 1,000,0.5 | 0.9991,155 | 0.9981,026 | 0.6192,772 | 0.0651,396 | 0.381732 |
| 3,000,0.5 | 14,273 | 0.9913,152 | 0.29910,375 | 0.1173,299 | 0.3152,380 |
| 10,000,0.5 | 115,379 | 0.99310,390 | 0.35237,892 | 0.30211,431 | 0.3297,952 |
| 1,000,0.9 | 11,173 | 13,364 | 12,929 | 0.0641,373 | 0.798785 |
| 3,000,0.9 | 14,249 | 14,300 | 13,467 | 0.1143,277 | 0.8032,379 |
| 10,000,0.9 | 114,585 | 117,472 | 113,106 | 0.30411,326 | 0.7997,843 |
| 1,000,1.0 | 1999 | 1999 | 1999 | 0.0921,000 | 11,000 |
| 3,000,1.0 | 12,999 | 12,999 | 12,999 | 0.1543,000 | 13,000 |
| 10,000,1.0 | 19,999 | 19,999 | 19,999 | 0.63410,000 | 110,000 | | 0 |
| #cls.,p | Polish0.07<br>acc.#cls. | Polish0.15<br>acc.#cls. | Polish0.3<br>acc.#cls. | Metis<br>acc.#cls. | DBscan<br>acc.#cls. |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.3 | 0.8192,162 | 0.6581,438 | 0.1983,789 | 0.0551,166 | 0.273131 |
| 3,000,0.3 | 0.46023,929 | 0.4544,108 | 0.1534,441 | 0.1082,787 | 0.215692 |
| 10,000,0.3 | 0.54324,965 | 0.4831,4053 | 0.1571,6940 | 0.5119,587 | 0.2272111 | | | 1,000,0.5 | 0.9942,666 | 0.9161,128 | 0.4731,973 | 0.0681,166 | 0.329193 |
| --- | --- | --- | --- | --- | --- |
| 3,000,0.5 | 0.9955,925 | 0.8153,853 | 0.2825,904 | 0.1132,787 | 0.230690 |
| 10,000,0.5 | 0.99713,653 | 0.83212,449 | 0.30420,301 | 0.5329,587 | 0.2472,201 |
| 1,000,0.9 | 12453 | 0.9975,761 | 0.8664,830 | 0.0671,156 | 0.363218 |
| 3,000,0.9 | 114,784 | 0.98910,756 | 0.7689,262 | 0.1102,775 | 0.207592 |
| 10,000,0.9 | 1254,357 | 0.99132,705 | 0.7823,2676 | 0.4709,543 | 0.2302,062 |
| 1,000,1.0 | 11803 | 0.9971,939 | 0.9261,705 | 0.081754 | 0.371205 |
| 3,000,1.0 | 15703 | 0.9858,018 | 0.8085,735 | 0.1341,986 | 0.237523 |
| 10,000,1.0 | 112,343 | 0.98819,293 | 0.82618,565 | 0.6816,739 | 0.2601,838 | | 1 |
| #cls.,p | Polish0.07<br>acc.#cls. | Polish0.15<br>acc.#cls. | Polish0.3<br>acc.#cls. | Metis<br>acc.#cls. | DBscan<br>acc.#cls. |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.3 | 0.8192,162 | 0.6581,438 | 0.1983,789 | 0.0551,166 | 0.273131 |
| 3,000,0.3 | 0.46023,929 | 0.4544,108 | 0.1534,441 | 0.1082,787 | 0.215692 |
| 10,000,0.3 | 0.54324,965 | 0.4831,4053 | 0.1571,6940 | 0.5119,587 | 0.2272111 | | | 10,000,0.3 | 0.99311,088 | 0.57415,970 | 0.15310,169 | 0.30511,431 | 0.2037,868 |
| --- | --- | --- | --- | --- | --- |
| 1,000,0.5 | 0.9991,155 | 0.9981,026 | 0.6192,772 | 0.0651,396 | 0.381732 |
| 3,000,0.5 | 14,273 | 0.9913,152 | 0.29910,375 | 0.1173,299 | 0.3152,380 |
| 10,000,0.5 | 115,379 | 0.99310,390 | 0.35237,892 | 0.30211,431 | 0.3297,952 |
| 1,000,0.9 | 11,173 | 13,364 | 12,929 | 0.0641,373 | 0.798785 |
| 3,000,0.9 | 14,249 | 14,300 | 13,467 | 0.1143,277 | 0.8032,379 |
| 10,000,0.9 | 114,585 | 117,472 | 113,106 | 0.30411,326 | 0.7997,843 |
| 1,000,1.0 | 1999 | 1999 | 1999 | 0.0921,000 | 11,000 |
| 3,000,1.0 | 12,999 | 12,999 | 12,999 | 0.1543,000 | 13,000 |
| 10,000,1.0 | 19,999 | 19,999 | 19,999 | 0.63410,000 | 110,000 | | 0 |
| Features | Dim | mAP-100 | mAP-5000 |
| --- | --- | --- | --- |
| | 400 | 0.5503 | 0.33 |
| | 2000 | 0.6321 | - |
| | 247 | 0.7371 | 0.6189 | | | lstm-encoder | 400 | 0.7402(h1−h2)<br>0.8521(c1−c2) | 0.8521 |
| --- | --- | --- | --- |
| | - | 0.6594 | 0.7095 |
| | - | 0.8583 | 0.872 | | 1 |
| Features | Dim | mAP-100 | mAP-5000 |
| --- | --- | --- | --- |
| | 400 | 0.5503 | 0.33 |
| | 2000 | 0.6321 | - |
| | 247 | 0.7371 | 0.6189 | | | Features | L-SVM | K-SVM | NB | DT | RF | LR |
| --- | --- | --- | --- | --- | --- | --- |
| IDT | 0.7731 | 0.6374 | 0.5984 | 0.5895 | 0.5567 | 0.6425 |
| MicroExpression | 0.7502 | 0.7540 | 0.7629 | 0.7269 | 0.8064 | 0.7398 |
| Transcript | 0.6457 | 0.4667 | 0.6625 | 0.5251 | 0.6172 | 0.5643 |
| MFCC | 0.7694 | 0.8171 | 0.6726 | 0.4369 | 0.7393 | 0.6683 |
| IDT+MicroExpression | 0.8347 | 0.7540 | 0.7629 | 0.7687 | 0.8184 | 0.7419 |
| IDT+MicroExpression+Transcripts | 0.8347 | 0.7540 | 0.7776 | 0.7777 | 0.8184 | 0.7419 |
| IDT+MicroExpression+MFCC | 0.8596 | 0.8233 | 0.7629 | 0.7687 | 0.8477 | 0.7894 |
| AllModalities | 0.8773 | 0.8233 | 0.7776 | 0.7777 | 0.8477 | 0.7894 | | 0 |
| Features | Dim | mAP-100 | mAP-5000 |
| --- | --- | --- | --- |
| | 400 | 0.5503 | 0.33 |
| | 2000 | 0.6321 | - |
| | 247 | 0.7371 | 0.6189 |
| lstm-encoder | 400 | 0.7402(h1−h2)<br>0.8521(c1−c2) | 0.8521 | | | | - | 0.6594 | 0.7095 |
| --- | --- | --- | --- |
| | - | 0.8583 | 0.872 | | 1 |
| Features | Dim | mAP-100 | mAP-5000 |
| --- | --- | --- | --- |
| | 400 | 0.5503 | 0.33 |
| | 2000 | 0.6321 | - |
| | 247 | 0.7371 | 0.6189 |
| lstm-encoder | 400 | 0.7402(h1−h2)<br>0.8521(c1−c2) | 0.8521 | | | MFCC | 0.7694 | 0.8171 | 0.6726 | 0.4369 | 0.7393 | 0.6683 |
| --- | --- | --- | --- | --- | --- | --- |
| IDT+MicroExpression | 0.8347 | 0.7540 | 0.7629 | 0.7687 | 0.8184 | 0.7419 |
| IDT+MicroExpression+Transcripts | 0.8347 | 0.7540 | 0.7776 | 0.7777 | 0.8184 | 0.7419 |
| IDT+MicroExpression+MFCC | 0.8596 | 0.8233 | 0.7629 | 0.7687 | 0.8477 | 0.7894 |
| AllModalities | 0.8773 | 0.8233 | 0.7776 | 0.7777 | 0.8477 | 0.7894 | | 0 |
| name | ¡T¿ | STD(T) | ¡G¿ | STD(G) | succ. | ¡I¿ | STD(I) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p3000-1<br>p3000-2<br>p3000-3<br>p3000-4<br>p3000-5 | 292.89<br>280.17<br>313.99<br>368.17<br>323.24 | 135.37<br>124.55<br>153.08<br>148.97<br>142.11 | 0.03<br>0.01<br>0.03<br>0.04<br>0.03 | 0.03<br>0.01<br>0.02<br>0.01<br>0.01 | 40.62<br>18.75<br>15.62<br>3.12<br>0.00 | 5967.0<br>5614.8<br>6367.3<br>7423.2<br>6493.5 | 2770.8<br>2486.6<br>3080.9<br>2978.1<br>2843.6 |
| p3000 | 315.69 | 144.39 | 0.03 | 0.02 | 15.62 | 6373.2 | 2903.9 |
| p4000-1<br>p4000-2<br>p4000-3<br>p4000-4<br>p4000-5 | 599.18<br>466.75<br>544.72<br>403.19<br>564.33 | 143.46<br>187.62<br>151.48<br>210.82<br>184.65 | 0.02<br>0.05<br>0.04<br>0.02<br>0.06 | 0.03<br>0.02<br>0.02<br>0.02<br>0.02 | 43.75<br>6.25<br>0.00<br>40.62<br>0.00 | 10431.8<br>8018.7<br>9430.6<br>6996.3<br>9680.3 | 2481.5<br>3202.9<br>2619.2<br>3650.3<br>3147.6 |
| p4000 | 515.63 | 191.05 | 0.04 | 0.03 | 18.12 | 8911.5 | 3290.8 |
| p5000-1<br>p5000-2<br>p5000-3<br>p5000-4<br>p5000-5 | 773.82<br>614.80<br>623.26<br>783.66<br>774.58 | 276.58<br>263.88<br>251.04<br>228.80<br>211.93 | 0.06<br>0.04<br>0.07<br>0.07<br>0.05 | 0.03<br>0.02<br>0.03<br>0.03<br>0.02 | 0.00<br>0.00<br>3.12<br>0.00<br>0.00 | 11708.2<br>9254.3<br>9459.2<br>11714.3<br>11426.0 | 4163.0<br>3917.7<br>3739.8<br>3402.6<br>3088.7 |
| p5000 | 714.02 | 259.46 | 0.06 | 0.03 | 0.62 | 10712.4 | 3846.7 |
| p6000-1<br>p6000-2<br>p6000-3 | 1018.34<br>944.05<br>955.48 | 302.98<br>246.74<br>293.04 | 0.08<br>0.06<br>0.06 | 0.04<br>0.03<br>0.03 | 0.00<br>0.00<br>0.00 | 13584.2<br>12556.8<br>12813.8 | 3974.2<br>3255.0<br>3909.6 | | | p6000 | 972.62 | 283.87 | 0.07 | 0.03 | 0.00 | 12985.0 | 3752.6 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p7000-1<br>p7000-2<br>p7000-3 | 1215.57<br>1209.88<br>1179.84 | 362.55<br>371.84<br>337.17 | 0.06<br>0.07<br>0.09 | 0.02<br>0.02<br>0.02 | 0.00<br>0.00<br>0.00 | 14539.8<br>14574.3<br>14225.0 | 4285.1<br>4373.1<br>3940.6 |
| p7000 | 1201.76 | 357.83 | 0.07 | 0.02 | 0.00 | 14446.4 | 4206.7 | | 1 |
| name | ¡T¿ | STD(T) | ¡G¿ | STD(G) | succ. | ¡I¿ | STD(I) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p3000-1<br>p3000-2<br>p3000-3<br>p3000-4<br>p3000-5 | 292.89<br>280.17<br>313.99<br>368.17<br>323.24 | 135.37<br>124.55<br>153.08<br>148.97<br>142.11 | 0.03<br>0.01<br>0.03<br>0.04<br>0.03 | 0.03<br>0.01<br>0.02<br>0.01<br>0.01 | 40.62<br>18.75<br>15.62<br>3.12<br>0.00 | 5967.0<br>5614.8<br>6367.3<br>7423.2<br>6493.5 | 2770.8<br>2486.6<br>3080.9<br>2978.1<br>2843.6 |
| p3000 | 315.69 | 144.39 | 0.03 | 0.02 | 15.62 | 6373.2 | 2903.9 |
| p4000-1<br>p4000-2<br>p4000-3<br>p4000-4<br>p4000-5 | 599.18<br>466.75<br>544.72<br>403.19<br>564.33 | 143.46<br>187.62<br>151.48<br>210.82<br>184.65 | 0.02<br>0.05<br>0.04<br>0.02<br>0.06 | 0.03<br>0.02<br>0.02<br>0.02<br>0.02 | 43.75<br>6.25<br>0.00<br>40.62<br>0.00 | 10431.8<br>8018.7<br>9430.6<br>6996.3<br>9680.3 | 2481.5<br>3202.9<br>2619.2<br>3650.3<br>3147.6 |
| p4000 | 515.63 | 191.05 | 0.04 | 0.03 | 18.12 | 8911.5 | 3290.8 |
| p5000-1<br>p5000-2<br>p5000-3<br>p5000-4<br>p5000-5 | 773.82<br>614.80<br>623.26<br>783.66<br>774.58 | 276.58<br>263.88<br>251.04<br>228.80<br>211.93 | 0.06<br>0.04<br>0.07<br>0.07<br>0.05 | 0.03<br>0.02<br>0.03<br>0.03<br>0.02 | 0.00<br>0.00<br>3.12<br>0.00<br>0.00 | 11708.2<br>9254.3<br>9459.2<br>11714.3<br>11426.0 | 4163.0<br>3917.7<br>3739.8<br>3402.6<br>3088.7 |
| p5000 | 714.02 | 259.46 | 0.06 | 0.03 | 0.62 | 10712.4 | 3846.7 |
| p6000-1<br>p6000-2<br>p6000-3 | 1018.34<br>944.05<br>955.48 | 302.98<br>246.74<br>293.04 | 0.08<br>0.06<br>0.06 | 0.04<br>0.03<br>0.03 | 0.00<br>0.00<br>0.00 | 13584.2<br>12556.8<br>12813.8 | 3974.2<br>3255.0<br>3909.6 | | | 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 |
| 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 |
| 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| 8 | 6.4582·10 | 6.4651·10 | | 0 |
| name | ¡T¿ | STD(T) | ¡G¿ | STD(G) | succ. | ¡I¿ | STD(I) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p3000-1<br>p3000-2<br>p3000-3<br>p3000-4<br>p3000-5 | 292.89<br>280.17<br>313.99<br>368.17<br>323.24 | 135.37<br>124.55<br>153.08<br>148.97<br>142.11 | 0.03<br>0.01<br>0.03<br>0.04<br>0.03 | 0.03<br>0.01<br>0.02<br>0.01<br>0.01 | 40.62<br>18.75<br>15.62<br>3.12<br>0.00 | 5967.0<br>5614.8<br>6367.3<br>7423.2<br>6493.5 | 2770.8<br>2486.6<br>3080.9<br>2978.1<br>2843.6 |
| p3000 | 315.69 | 144.39 | 0.03 | 0.02 | 15.62 | 6373.2 | 2903.9 |
| p4000-1<br>p4000-2<br>p4000-3<br>p4000-4<br>p4000-5 | 599.18<br>466.75<br>544.72<br>403.19<br>564.33 | 143.46<br>187.62<br>151.48<br>210.82<br>184.65 | 0.02<br>0.05<br>0.04<br>0.02<br>0.06 | 0.03<br>0.02<br>0.02<br>0.02<br>0.02 | 43.75<br>6.25<br>0.00<br>40.62<br>0.00 | 10431.8<br>8018.7<br>9430.6<br>6996.3<br>9680.3 | 2481.5<br>3202.9<br>2619.2<br>3650.3<br>3147.6 |
| p4000 | 515.63 | 191.05 | 0.04 | 0.03 | 18.12 | 8911.5 | 3290.8 |
| p5000-1<br>p5000-2<br>p5000-3<br>p5000-4<br>p5000-5 | 773.82<br>614.80<br>623.26<br>783.66<br>774.58 | 276.58<br>263.88<br>251.04<br>228.80<br>211.93 | 0.06<br>0.04<br>0.07<br>0.07<br>0.05 | 0.03<br>0.02<br>0.03<br>0.03<br>0.02 | 0.00<br>0.00<br>3.12<br>0.00<br>0.00 | 11708.2<br>9254.3<br>9459.2<br>11714.3<br>11426.0 | 4163.0<br>3917.7<br>3739.8<br>3402.6<br>3088.7 |
| p5000 | 714.02 | 259.46 | 0.06 | 0.03 | 0.62 | 10712.4 | 3846.7 |
| p6000-1<br>p6000-2<br>p6000-3 | 1018.34<br>944.05<br>955.48 | 302.98<br>246.74<br>293.04 | 0.08<br>0.06<br>0.06 | 0.04<br>0.03<br>0.03 | 0.00<br>0.00<br>0.00 | 13584.2<br>12556.8<br>12813.8 | 3974.2<br>3255.0<br>3909.6 | | | p6000 | 972.62 | 283.87 | 0.07 | 0.03 | 0.00 | 12985.0 | 3752.6 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p7000-1<br>p7000-2<br>p7000-3 | 1215.57<br>1209.88<br>1179.84 | 362.55<br>371.84<br>337.17 | 0.06<br>0.07<br>0.09 | 0.02<br>0.02<br>0.02 | 0.00<br>0.00<br>0.00 | 14539.8<br>14574.3<br>14225.0 | 4285.1<br>4373.1<br>3940.6 |
| p7000 | 1201.76 | 357.83 | 0.07 | 0.02 | 0.00 | 14446.4 | 4206.7 | | 1 |
| name | ¡T¿ | STD(T) | ¡G¿ | STD(G) | succ. | ¡I¿ | STD(I) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| p3000-1<br>p3000-2<br>p3000-3<br>p3000-4<br>p3000-5 | 292.89<br>280.17<br>313.99<br>368.17<br>323.24 | 135.37<br>124.55<br>153.08<br>148.97<br>142.11 | 0.03<br>0.01<br>0.03<br>0.04<br>0.03 | 0.03<br>0.01<br>0.02<br>0.01<br>0.01 | 40.62<br>18.75<br>15.62<br>3.12<br>0.00 | 5967.0<br>5614.8<br>6367.3<br>7423.2<br>6493.5 | 2770.8<br>2486.6<br>3080.9<br>2978.1<br>2843.6 |
| p3000 | 315.69 | 144.39 | 0.03 | 0.02 | 15.62 | 6373.2 | 2903.9 |
| p4000-1<br>p4000-2<br>p4000-3<br>p4000-4<br>p4000-5 | 599.18<br>466.75<br>544.72<br>403.19<br>564.33 | 143.46<br>187.62<br>151.48<br>210.82<br>184.65 | 0.02<br>0.05<br>0.04<br>0.02<br>0.06 | 0.03<br>0.02<br>0.02<br>0.02<br>0.02 | 43.75<br>6.25<br>0.00<br>40.62<br>0.00 | 10431.8<br>8018.7<br>9430.6<br>6996.3<br>9680.3 | 2481.5<br>3202.9<br>2619.2<br>3650.3<br>3147.6 |
| p4000 | 515.63 | 191.05 | 0.04 | 0.03 | 18.12 | 8911.5 | 3290.8 |
| p5000-1<br>p5000-2<br>p5000-3<br>p5000-4<br>p5000-5 | 773.82<br>614.80<br>623.26<br>783.66<br>774.58 | 276.58<br>263.88<br>251.04<br>228.80<br>211.93 | 0.06<br>0.04<br>0.07<br>0.07<br>0.05 | 0.03<br>0.02<br>0.03<br>0.03<br>0.02 | 0.00<br>0.00<br>3.12<br>0.00<br>0.00 | 11708.2<br>9254.3<br>9459.2<br>11714.3<br>11426.0 | 4163.0<br>3917.7<br>3739.8<br>3402.6<br>3088.7 |
| p5000 | 714.02 | 259.46 | 0.06 | 0.03 | 0.62 | 10712.4 | 3846.7 |
| p6000-1<br>p6000-2<br>p6000-3 | 1018.34<br>944.05<br>955.48 | 302.98<br>246.74<br>293.04 | 0.08<br>0.06<br>0.06 | 0.04<br>0.03<br>0.03 | 0.00<br>0.00<br>0.00 | 13584.2<br>12556.8<br>12813.8 | 3974.2<br>3255.0<br>3909.6 | | | 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 |
| --- | --- | --- |
| 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| 8 | 6.4582·10 | 6.4651·10 | | 0 |
| α0 | b0 | b1 | b2 | χ |
| --- | --- | --- | --- | --- |
| 0.1 | 1664 | 0 | 0 | 1664 |
| 477 | 1 | 0 | 476 | |
| 5042 | 1 | 0 | 5041 | |
| 3491 | 2 | 0 | 3489 | |
| 0.2 | 4751 | 9 | 0 | 4742 |
| 1330 | 10 | 0 | 1320 | |
| 18691 | 9 | 0 | 18682 | |
| 11779 | 60 | 0 | 11719 | |
| 0.3 | 6113 | 260 | 0 | 5853 |
| 1606 | 110 | 0 | 1496 | |
| 32601 | 495 | 3 | 32109 | |
| 18757 | 997 | 12 | 17772 | |
| 0.4 | 1932 | 3682 | 3 | -1747 |
| 487 | 1150 | 0 | -663 | |
| 20905 | 9355 | 329 | 11879 | |
| 12813 | 9455 | 391 | 3749 | |
| 0.5 | 245 | 11389 | 163 | -10981 |
| 55 | 2995 | 29 | -2911 | |
| 4971 | 45256 | 4187 | -36098 | |
| 3713 | 28695 | 3324 | -21658 | |
| 0.6 | 18 | 8523 | 1434 | -7071 |
| 1 | 1927 | 265 | -1661 | |
| 528 | 53806 | 18129 | -35149 | |
| 473 | 29870 | 11421 | -17976 | |
| 0.7 | 1 | 3133 | 4903 | 1771 |
| 1 | 545 | 1045 | 501 | |
| 14 | 28988 | 29705 | 731 | |
| 31 | 15949 | 16832 | 914 | |
| 0.8 | 1 | 721 | 4132 | 3412 |
| 1 | 92 | 974 | 883 | |
| 1 | 6658 | 17563 | 10906 | |
| 3 | 4216 | 10220 | 6007 | |
| 0.9 | 1 | 85 | 1488 | 1404 |
| 1 | 6 | 389 | 384 | | | | 1 | 637 | 4798 | 4162 |
| --- | --- | --- | --- |
| 1 | 608 | 3171 | 2564 | | 1 |
| α0 | b0 | b1 | b2 | χ |
| --- | --- | --- | --- | --- |
| 0.1 | 1664 | 0 | 0 | 1664 |
| 477 | 1 | 0 | 476 | |
| 5042 | 1 | 0 | 5041 | |
| 3491 | 2 | 0 | 3489 | |
| 0.2 | 4751 | 9 | 0 | 4742 |
| 1330 | 10 | 0 | 1320 | |
| 18691 | 9 | 0 | 18682 | |
| 11779 | 60 | 0 | 11719 | |
| 0.3 | 6113 | 260 | 0 | 5853 |
| 1606 | 110 | 0 | 1496 | |
| 32601 | 495 | 3 | 32109 | |
| 18757 | 997 | 12 | 17772 | |
| 0.4 | 1932 | 3682 | 3 | -1747 |
| 487 | 1150 | 0 | -663 | |
| 20905 | 9355 | 329 | 11879 | |
| 12813 | 9455 | 391 | 3749 | |
| 0.5 | 245 | 11389 | 163 | -10981 |
| 55 | 2995 | 29 | -2911 | |
| 4971 | 45256 | 4187 | -36098 | |
| 3713 | 28695 | 3324 | -21658 | |
| 0.6 | 18 | 8523 | 1434 | -7071 |
| 1 | 1927 | 265 | -1661 | |
| 528 | 53806 | 18129 | -35149 | |
| 473 | 29870 | 11421 | -17976 | |
| 0.7 | 1 | 3133 | 4903 | 1771 |
| 1 | 545 | 1045 | 501 | |
| 14 | 28988 | 29705 | 731 | |
| 31 | 15949 | 16832 | 914 | |
| 0.8 | 1 | 721 | 4132 | 3412 |
| 1 | 92 | 974 | 883 | |
| 1 | 6658 | 17563 | 10906 | |
| 3 | 4216 | 10220 | 6007 | |
| 0.9 | 1 | 85 | 1488 | 1404 |
| 1 | 6 | 389 | 384 | | | | Alg. | H | AT | LWT | RWT | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | µh | σh | MSEh | µa | σa | MSEa | µl | σl | MSEl | µr | σr | MSEr |
| O | 22 | 17 | 765 | 12 | 8 | 201 | 28 | 46 | 2856 | 19 | 21 | 777 |
| B | 19 | 11 | 478 | 23 | 36 | 1783 | 10 | 10 | 191 | 12 | 17 | 419 |
| P | 8 | 3 | 72 | 9 | 4 | 106 | 9 | 6 | 115 | 10 | 9 | 187 | | 0 |
| α0 | b0 | b1 | b2 | χ |
| --- | --- | --- | --- | --- |
| 0.1 | 1664 | 0 | 0 | 1664 | | | 477 | 1 | 0 | 476 | |
| --- | --- | --- | --- | --- |
| 5042 | 1 | 0 | 5041 | |
| 3491 | 2 | 0 | 3489 | |
| 0.2 | 4751 | 9 | 0 | 4742 |
| 1330 | 10 | 0 | 1320 | |
| 18691 | 9 | 0 | 18682 | |
| 11779 | 60 | 0 | 11719 | |
| 0.3 | 6113 | 260 | 0 | 5853 |
| 1606 | 110 | 0 | 1496 | |
| 32601 | 495 | 3 | 32109 | |
| 18757 | 997 | 12 | 17772 | |
| 0.4 | 1932 | 3682 | 3 | -1747 |
| 487 | 1150 | 0 | -663 | |
| 20905 | 9355 | 329 | 11879 | |
| 12813 | 9455 | 391 | 3749 | |
| 0.5 | 245 | 11389 | 163 | -10981 |
| 55 | 2995 | 29 | -2911 | |
| 4971 | 45256 | 4187 | -36098 | |
| 3713 | 28695 | 3324 | -21658 | |
| 0.6 | 18 | 8523 | 1434 | -7071 |
| 1 | 1927 | 265 | -1661 | |
| 528 | 53806 | 18129 | -35149 | |
| 473 | 29870 | 11421 | -17976 | |
| 0.7 | 1 | 3133 | 4903 | 1771 |
| 1 | 545 | 1045 | 501 | |
| 14 | 28988 | 29705 | 731 | |
| 31 | 15949 | 16832 | 914 | |
| 0.8 | 1 | 721 | 4132 | 3412 |
| 1 | 92 | 974 | 883 | |
| 1 | 6658 | 17563 | 10906 | |
| 3 | 4216 | 10220 | 6007 | |
| 0.9 | 1 | 85 | 1488 | 1404 |
| 1 | 6 | 389 | 384 | |
| 1 | 637 | 4798 | 4162 | |
| 1 | 608 | 3171 | 2564 | | | 1 |
| α0 | b0 | b1 | b2 | χ |
| --- | --- | --- | --- | --- |
| 0.1 | 1664 | 0 | 0 | 1664 | | | O | 22 | 17 | 765 | 12 | 8 | 201 | 28 | 46 | 2856 | 19 | 21 | 777 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| B | 19 | 11 | 478 | 23 | 36 | 1783 | 10 | 10 | 191 | 12 | 17 | 419 |
| P | 8 | 3 | 72 | 9 | 4 | 106 | 9 | 6 | 115 | 10 | 9 | 187 | | 0 |
| Algorithm | Additions | Multiplications |
| --- | --- | --- |
| IDCCG | M+M<br>2<br>+J(M+6M−4) | 2M+2M<br>2<br>J(M+7M+3) | | | IDMCG | 2M+10M−4 | 3M+12M+3 |
| --- | --- | --- |
| IncrementalLMS | 4M−1 | 3M+1 |
| IncrementalRLS | 4M+12M+1 | 4M+12M−1 | | 1 |
| Algorithm | Additions | Multiplications |
| --- | --- | --- |
| IDCCG | M+M<br>2<br>+J(M+6M−4) | 2M+2M<br>2<br>J(M+7M+3) | | | | Doubling | DoublingandAddition |
| --- | --- | --- |
| Algorithm??<br>(Miller’salgorithm) | kk+3M2Spp<br>k=4.6Mp | kk+5M2Spp<br>k=6.6Mp |
| Algorithmin | kk1S+1Mpp<br>k=1.8Mp | kk1S+2Mpp<br>k=2.8Mp |
| Algorithm?? | kk2S+2Mpp<br>k=3.6Mp | kk2S+4Mpp<br>k=5.6Mp |
| Algorithm?? | kk2S+1Mpp<br>k=2.6Mp | kkk2S+2M=3.6M(line3)ppp<br>kkk2S+3M=4.6M(line4)ppp | | 0 |
| Algorithm | Additions | Multiplications |
| --- | --- | --- |
| IDCCG | M+M<br>2<br>+J(M+6M−4) | 2M+2M<br>2<br>J(M+7M+3) |
| IDMCG | 2M+10M−4 | 3M+12M+3 | | | IncrementalLMS | 4M−1 | 3M+1 |
| --- | --- | --- |
| IncrementalRLS | 4M+12M+1 | 4M+12M−1 | | 1 |
| Algorithm | Additions | Multiplications |
| --- | --- | --- |
| IDCCG | M+M<br>2<br>+J(M+6M−4) | 2M+2M<br>2<br>J(M+7M+3) |
| IDMCG | 2M+10M−4 | 3M+12M+3 | | | Algorithm?? | kk2S+2Mpp<br>k=3.6Mp | kk2S+4Mpp<br>k=5.6Mp |
| --- | --- | --- |
| Algorithm?? | kk2S+1Mpp<br>k=2.6Mp | kkk2S+2M=3.6M(line3)ppp<br>kkk2S+3M=4.6M(line4)ppp | | 0 |
| | Stage1Classifier | Stage3DeepLearningLayers |
| --- | --- | --- |
| TASK1 | LogisticRegression | [1013,528,128,2] |
| TASK2 | NaiveBayes | [1319,256,32,2] | | | TASK3 | NaiveBayes | [1319,256,32,4] |
| --- | --- | --- |
| TASK4 | LogisticRegression | [281,64,64,2] | | 1 |
| | Stage1Classifier | Stage3DeepLearningLayers |
| --- | --- | --- |
| TASK1 | LogisticRegression | [1013,528,128,2] |
| TASK2 | NaiveBayes | [1319,256,32,2] | | | Stage | LayerType | Size |
| --- | --- | --- |
| ConvolutionStage1 | Conv | 32(5x5) |
| Pooling | 2x2 | |
| ConvolutionStage2 | Conv | 256(5x5) |
| Pooling | 2x2 | |
| FullyConnected | ReLU | 256 |
| FeatureRepresentation | ReLU/Linear | 8 |
| Output | Softmax | 10 | | 0 |
| | Stage1Classifier | Stage3DeepLearningLayers |
| --- | --- | --- |
| TASK1 | LogisticRegression | [1013,528,128,2] |
| TASK2 | NaiveBayes | [1319,256,32,2] | | | TASK3 | NaiveBayes | [1319,256,32,4] |
| --- | --- | --- |
| TASK4 | LogisticRegression | [281,64,64,2] | | 1 |
| | Stage1Classifier | Stage3DeepLearningLayers |
| --- | --- | --- |
| TASK1 | LogisticRegression | [1013,528,128,2] |
| TASK2 | NaiveBayes | [1319,256,32,2] | | | ConvolutionStage2 | Conv | 256(5x5) |
| --- | --- | --- |
| Pooling | 2x2 | |
| FullyConnected | ReLU | 256 |
| FeatureRepresentation | ReLU/Linear | 8 |
| Output | Softmax | 10 | | 0 |
| patternp | ppppppppp123456789 | type | x(p) |
| --- | --- | --- | --- |
| p | 24-------- | T1 | 29/4956 |
| p | 1212------- | 289/4956 | |
| p | 12-6------ | 11/826 | |
| p | -66------ | T2 | 15/413 |
| p | -2244---- | 17/1239 | |
| p | -224-2--- | 34/1239 | |
| p | --424---- | T3 | 64/413 |
| p | ---8----- | T4 | 55/1239 |
| p | ---222--- | 74/1239 | |
| p | ---1114-- | 21/413 | | | | p | ----1122- | T5 | 32/413 |
| --- | --- | --- | --- |
| p | ----114-- | 3/413 | |
| p | ----11111 | 29/413 | |
| p | -----211- | T6 | 128/413 |
| p | ------111 | T7 | 96/413 |
| p | -------11 | T8 | 96/413 |
| p | --------1 | T9 | 192/413 | | 1 |
| patternp | ppppppppp123456789 | type | x(p) |
| --- | --- | --- | --- |
| p | 24-------- | T1 | 29/4956 |
| p | 1212------- | 289/4956 | |
| p | 12-6------ | 11/826 | |
| p | -66------ | T2 | 15/413 |
| p | -2244---- | 17/1239 | |
| p | -224-2--- | 34/1239 | |
| p | --424---- | T3 | 64/413 |
| p | ---8----- | T4 | 55/1239 |
| p | ---222--- | 74/1239 | |
| p | ---1114-- | 21/413 | | | | Portion | 1Annot. | 2Annot. | 3Annot. |
| --- | --- | --- | --- |
| 1-2400 | #08 | #01 | #04 |
| 2401-4800 | #04 | #03 | #01 |
| 4801-7200 | #01 | #04 | #08 |
| 7201-9600 | #03 | #08 | #02 |
| 9601-11185 | #06 | #05 | #03 |
| 11186-12772 | #07 | #02 | #06 | | 0 |
| patternp | ppppppppp123456789 | type | x(p) |
| --- | --- | --- | --- |
| p | 24-------- | T1 | 29/4956 |
| p | 1212------- | 289/4956 | |
| p | 12-6------ | 11/826 | |
| p | -66------ | T2 | 15/413 | | | p | -2244---- | 17/1239 | |
| --- | --- | --- | --- |
| p | -224-2--- | 34/1239 | |
| p | --424---- | T3 | 64/413 |
| p | ---8----- | T4 | 55/1239 |
| p | ---222--- | 74/1239 | |
| p | ---1114-- | 21/413 | |
| p | ----1122- | T5 | 32/413 |
| p | ----114-- | 3/413 | |
| p | ----11111 | 29/413 | |
| p | -----211- | T6 | 128/413 |
| p | ------111 | T7 | 96/413 |
| p | -------11 | T8 | 96/413 |
| p | --------1 | T9 | 192/413 | | 1 |
| patternp | ppppppppp123456789 | type | x(p) |
| --- | --- | --- | --- |
| p | 24-------- | T1 | 29/4956 |
| p | 1212------- | 289/4956 | |
| p | 12-6------ | 11/826 | |
| p | -66------ | T2 | 15/413 | | | 9601-11185 | #06 | #05 | #03 |
| --- | --- | --- | --- |
| 11186-12772 | #07 | #02 | #06 | | 0 |
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