397 research outputs found
Residual Continual Learning
We propose a novel continual learning method called Residual Continual
Learning (ResCL). Our method can prevent the catastrophic forgetting phenomenon
in sequential learning of multiple tasks, without any source task information
except the original network. ResCL reparameterizes network parameters by
linearly combining each layer of the original network and a fine-tuned network;
therefore, the size of the network does not increase at all. To apply the
proposed method to general convolutional neural networks, the effects of batch
normalization layers are also considered. By utilizing residual-learning-like
reparameterization and a special weight decay loss, the trade-off between
source and target performance is effectively controlled. The proposed method
exhibits state-of-the-art performance in various continual learning scenarios.Comment: AAAI 202
Continual Learning with Extended Kronecker-factored Approximate Curvature
We propose a quadratic penalty method for continual learning of neural
networks that contain batch normalization (BN) layers. The Hessian of a loss
function represents the curvature of the quadratic penalty function, and a
Kronecker-factored approximate curvature (K-FAC) is used widely to practically
compute the Hessian of a neural network. However, the approximation is not
valid if there is dependence between examples, typically caused by BN layers in
deep network architectures. We extend the K-FAC method so that the
inter-example relations are taken into account and the Hessian of deep neural
networks can be properly approximated under practical assumptions. We also
propose a method of weight merging and reparameterization to properly handle
statistical parameters of BN, which plays a critical role for continual
learning with BN, and a method that selects hyperparameters without source task
data. Our method shows better performance than baselines in the permuted MNIST
task with BN layers and in sequential learning from the ImageNet classification
task to fine-grained classification tasks with ResNet-50, without any explicit
or implicit use of source task data for hyperparameter selection.Comment: CVPR 202
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Estimating the malaria transmission of Plasmodium vivax based on serodiagnosis
Background: Plasmodium vivax re-emerged in 1993 and has now become a major public health problem during the summer season in South Korea. The aim of this study was to interpret and understand the meaning of seroepidemiological studies for developing the best malaria control programme in South Korea. Methods: Blood samples were collected in Gimpo city, Paju city, Yeoncheon County, Cheorwon County and Goseong County of high risk area in South Korea. Microscopy was performed to identify patients infected with P. vivax. Antibody detection for P. vivax was performed using indirect fluorescent antibody test (IFAT). Results: A total of 1,574 blood samples was collected from participants in the study areas and evaluated against three parameters: IFAT positive rate, annual antibody positive index (AAPI), and annual parasite index (API). The IFAT positive rate was 7.24% (n = 114). Of the five study areas, Gimpo had the highest IFAT positive rate (13.68%) and AAPI (4.63). Yeongcheon had the highest API in 2005 (2.06) while Gimpo had the highest API in 2006 (5.00). No correlation was observed between any of the three parameters and study sites' distance from the demilitarized zone (DMZ). Conclusions: These results showed that P. vivax antibody levels could provide useful information about the prevalence of malaria in endemic areas. Furthermore, AAPI results for each year showed a closer relationship to API the following year than the API of the same year and thus could be helpful in predicting malaria transmission risks
Torsional Vibration Transduction in a Solid Shaft by MPTs
In this study, we aim to investigate the feasibility to use MPTs (Magnetostrictive Patch Transducers) for torsional vibration measurement in solid ferromagnetic cylinders. MPTs consisting of thin magnetostrictive patches, permanent magnets and a solenoid coil have been widely used for elastic wave transduction in the ultrasound frequency range [1] but they have been seldom used for sonic-frequency range vibration measurement, in spite of their unique wireless transduction characteristics. While a MPT was used in Ref. [2] to perform torsional modal testing in a hollow cylinder or a pipe having relatively small torsional rigidity, no investigation has been reported yet on the use of MPTs in “solid” “ferromagnetic” shafts, common torsional power carrying elements in machines.While we will be mainly focused here on the torsional wave measurement in stationary shafts, the MPT-based torsional measurement can be also applied to rotating shafts. Because the torsional rigidities of solid shafts are much larger than those of hollow cylinders of the same radii, it is important to find optimal MPT configurations, such as the optimal number of rectangular patches to be installed around the surface of a solid shaft. Thereby, we performed numerical investigations and accordingly designed a series of experiments for torsional vibration testing in steel shafts. The actual modal testing experiments with the designed MPTs were found to predict the torsional Eigen-frequencies and Eigen-modes that agree well with the theoretical predictions. Also the relation between the measured vibration signals from MPTs and those from strain gages was checked experimentally and in fact, the experimental result favorably agreed with the theoretical prediction. Potential applications of the MPT-based torsional vibration measurement technique in rotating solid shafts for structural health monitoring are also briefly discussed
A SNP Harvester Analysis to Better Detect SNPs of CCDC158 Gene That Are Associated with Carcass Quality Traits in Hanwoo
The purpose of this study was to investigate interaction effects of genes using a Harvester method. A sample of Korean cattle, Hanwoo (n = 476) was chosen from the National Livestock Research Institute of Korea that were sired by 50 Korean proven bulls. The steers were born between the spring of 1998 and the autumn of 2002 and reared under a progeny-testing program at the Daekwanryeong and Namwon branches of NLRI. The steers were slaughtered at approximately 24 months of age and carcass quality traits were measured. A SNP Harvester method was applied with a support vector machine (SVM) to detect significant SNPs in the CCDC158 gene and interaction effects between the SNPs that were associated with average daily gains, cold carcass weight, longissimus dorsi muscle area, and marbling scores. The statistical significance of the major SNP combinations was evaluated with x2-statistics. The genotype combinations of three SNPs, g.34425+102 A>T(AA), g.4102636T>G(GT), and g.11614+19G>T(GG) had a greater effect than the rest of SNP combinations, e.g. 0.82 vs. 0.75 kg, 343 vs. 314 kg, 80.4 vs 74.7 cm2, and 7.35 vs. 5.01, for the four respective traits (p<0.001). Also, the estimates were greater compared with single SNPs analyzed (the greatest estimates were 0.76 kg, 320 kg, 75.5 cm2, and 5.31, respectively). This result suggests that the SNP Harvester method is a good option when multiple SNPs and interaction effects are tested. The significant SNPs could be applied to improve meat quality of Hanwoo via marker-assisted selection
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