71 research outputs found

    Independent domination versus packing in subcubic graphs

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    In 2011, Henning, L\"{o}wenstein, and Rautenbach observed that the domination number of a graph is bounded from above by the product of the packing number and the maximum degree of the graph. We prove a stronger statement in subcubic graphs: the independent domination number is bounded from above by three times the packing number.Comment: 9 pages, 3 figure

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    Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R2 of 0.98, and a root-mean-square-error (RMSE) of 0.97???. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29??? and an MAE decrease of 0.17-0.24???. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence

    Fatigue Crack Length Estimation and Prediction using Trans-fitting with Support Vector Regression

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    A method is described in this paper for crack propagation prediction using only the initial crack length of the target specimen. The proposed method consists of two parts: (1) crack length estimation using support vector regression (SVR) and (2) crack length prediction using a new trans-fitting method. Features based on the filtered wave signals were defined and a model was constructed using the SVR method to estimate the crack length. The hyper-parameters of the SVR model were selected based on a grid search algorithm. Prediction of the crack length was based on the previous crack length, which was estimated based on the wave signals. In this step, a newly proposed trans-fitting method was applied. The proposed trans-fitting method updated the selected candidate function to translocate the trend of crack propagation based on the training dataset. By translocating the trends to the estimated crack length of the target specimen, the crack propagation could be predicted. The proposed method was validated by comparison with given specimens. The results show that the proposed method can estimate and predict the crack length accurately

    Algorithms for CRT-variant of Approximate Greatest Common Divisor Problem

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    The approximate greatest common divisor problem (ACD) and its variants have been used to construct many cryptographic primitives. In particular, variants of the ACD problem based on Chinese remainder theorem (CRT) are exploited in the constructions of a batch fully homomorphic encryption to encrypt multiple messages in one ciphertext. Despite the utility of the CRT-variant scheme, the algorithms to solve its security foundation have not been studied well compared to the original ACD based scheme. In this paper, we propose two algorithms for solving the CCK-ACD problem, which is used to construct a batch fully homomorphic encryption over integers. To achieve the goal, we revisit the orthogonal lattice attack and simultaneous Diophantine approximation algorithm. Both two algorithms take the same time complexity 2O~(γ(ηρ)2)2^{\tilde{O}(\frac{\gamma}{(\eta-\rho)^2})} up to a polynomial factor to solve the CCK-ACD problem for the bit size of samples γ\gamma, secret primes η\eta, and error bound ρ\rho. Compared to Chen and Nguyen\u27s algorithm in Eurocrypt\u27 12, which takes O~(2ρ/2)\tilde{O}(2^{\rho/2}) complexity, our algorithm gives the first parameter condition related to η\eta and γ\gamma size. We also report the experimental results for our attack upon several parameters. From the results, we can see that our algorithms work well both in theoretical and experimental terms

    Design methodology to characterize and compensate for process and temperature variation in digital systems

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    The main objective of this dissertation is to investigate a design methodology that can characterize and compensate for process and temperature variation. First, a design methodology is discussed to handle process variation in low-power memory for image processing application. This is followed by a design technique to characterize and recover TSV-defect-induced signal degradation in a 3D integrated circuit. For thermal variation, the spatiotemporal power migration is proposed as a methodology to handle thermal issues in digital systems both during the test and normal operation. The power migration continuously distributes the generated heat in space and time to control chip temperature. To enable this approach a unique method is developed, and verified through hardware for post-fabrication characterization of thermal system and prediction of transient variation in chip temperature. The inverse temperature dependence in a digital logic is characterized through hardware to help better thermal management in wide operating voltage design.Ph.D
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