No abstract

No abstract

Nonlinear guidance laws that consider impact time constraints are proposed. Two-dimensional and three-dimensional impact time control guidance laws are derived using Lyapunov stability theory. Under the consideration of the nonlinear kinematics, it is shown that the missile states converge to the desired equilibrium point by the Lyapunov stability theory. The singularity issue of the proposed guidance laws is also analyzed. Numerical simulations are performed to verify the performance of the proposed guidance laws.

The risk of tampering exists for conventional user recognition methods based on biometrics such as face and fingerprint. Recently, research on user recognition using biometric signals such as electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG) has been actively performed to overcome this issue. We herein propose a user recognition method applying a deep learning technique based on ensemble networks after transforming ECG signals into two-dimensional (2D) images. A preprocessing process for one-dimensional ECG signals is performed to remove noise or distortion; subsequently, they are projected onto a 2D image space and transformed into image data. For the proposed algorithm, we designed deep learning-based ensemble networks to improve the degraded performance arising from overfitting in a single network. Our experimental results demonstrate that the proposed ensemble networks exhibit an accuracy that is 1.7% higher than that of the single network. In particular, the performance of the ensemble networks is up to 13% higher compared to the single network that degrades the recognition rate by displaying similar features between classes.

BackgroundThis study was to investigate the effect of biomechanical stimulation on osteoblast differentiation of human periosteal-derived stem cell using the newly developed bioreactor.MethodsHuman periosteal-derived stem cells were harvested from the mandible during the extraction of an impacted third molar. Using the new bioreactor, 4% cyclic equibiaxial tension force (0.5 Hz) was applied for 2 and 8 h on the stem cells and cultured for 3, 7, and 14 days on the osteogenic medium. Biochemical changes of the osteoblasts after the biomechanical stimulation were investigated. No treatment group was referred to as control group.ResultsAlkaline phosphatase (ALP) activity and ALP messenger RNA (mRNA) expression level were higher in the strain group than those in the control group. The osteocalcin and osteonectin mRNA expressions were higher in the strain group compared to those in the control group on days 7 and 14. The vascular endothelial growth factor (VEGF) mRNA expression was higher in the strain group in comparison to that in the control group. Concentration of alizarin red S corresponding to calcium content was higher in the strain group than in the control group.ConclusionsThe study suggests that cyclic tension force could influence the osteoblast differentiation of periosteal-derived stem cells under optimal stimulation condition and the force could be applicable for tissue engineering.