VIRTUAL ROBOT LOCOMOTION ON VARIABLE TERRAIN WITH ADVERSARIAL REINFORCEMENT LEARNING

Reinforcement Learning (RL) is a machine learning technique where an agent learns to perform a complex action by going through a repeated process of trial and error to maximize a well-defined reward function. This form of learning has found applications in robot locomotion where it has been used to teach robots to traverse complex terrain. While RL algorithms may work well in training robot locomotion, they tend to not generalize well when the agent is brought into an environment that it has never encountered before. Possible solutions from the literature include training a destabilizing adversary alongside the locomotive learning agent. The destabilizing adversary aims to destabilize the agent by applying external forces to it, which may help the locomotive agent learn to deal with unexpected scenarios. For this project, we will train a robust, simulated quadruped robot to traverse a variable terrain. We compare and analyze Proximal Policy Optimization (PPO) with and without the use of an adversarial agent, and determine which use of PPO produces the best results

Economic mobility in Vietnam in the 1990s

Vietnam's high economic growth in the 1990s led to sharp reductions in poverty, yet over the same time period inequality increased. This increased inequality may be less worrisome if Vietnamese households experience a high degree of income mobility over time. This is because high mobility implies that the long-run distribution of income is more equally distributed than the short-run distribution, since some individuals or households are poor in some years, while others are poor in other years. The authors examine economic mobility in Vietnam using recent household survey panel data. The problem of measurement error in the income variable, which exaggerates the degree of economic mobility, is directly addressed. Correcting for measurement error dramatically changes the results. At least one half of measured mobility is because of measurement error.Statistical&Mathematical Sciences,Roads&Highways,Economic Theory&Research,Housing&Human Habitats,Environmental Economics&Policies,Economic Theory&Research,Housing&Human Habitats,Statistical&Mathematical Sciences,Inequality,Governance Indicators

Advanced Capsule Networks via Context Awareness

Capsule Networks (CN) offer new architectures for Deep Learning (DL) community. Though its effectiveness has been demonstrated in MNIST and smallNORB datasets, the networks still face challenges in other datasets for images with distinct contexts. In this research, we improve the design of CN (Vector version) namely we expand more Pooling layers to filter image backgrounds and increase Reconstruction layers to make better image restoration. Additionally, we perform experiments to compare accuracy and speed of CN versus DL models. In DL models, we utilize Inception V3 and DenseNet V201 for powerful computers besides NASNet, MobileNet V1 and MobileNet V2 for small and embedded devices. We evaluate our models on a fingerspelling alphabet dataset from American Sign Language (ASL). The results show that CNs perform comparably to DL models while dramatically reducing training time. We also make a demonstration and give a link for the purpose of illustration.Comment: 12 page

Counting Co-Cyclic Lattices

There is a well-known asymptotic formula, due to W. M. Schmidt (1968) for the number of full-rank integer lattices of index at most $V$ in $\mathbb{Z}^n$. This set of lattices $L$ can naturally be partitioned with respect to the factor group $\mathbb{Z}^n/L$. Accordingly, we count the number of full-rank integer lattices $L \subseteq \mathbb{Z}^n$ such that $\mathbb{Z}^n/L$ is cyclic and of order at most $V$, and deduce that these co-cyclic lattices are dominant among all integer lattices: their natural density is $\left(\zeta(6) \prod_{k=4}^n \zeta(k)\right)^{-1} \approx 85\%$. The problem is motivated by complexity theory, namely worst-case to average-case reductions for lattice problems

Optimising access-site risks and complications in coronary angiography and percutaneous coronary intervention

Major access-site bleeding and vascular complications are among the most dreaded complications following coronary angiography and percutaneous coronary intervention. Despite continual improvements in pharmacological and technical measures, bleeding complications still remain a major concern in patients with acute coronary syndrome undergoing invasive coronary intervention. Major bleeding and vascular complications are not only associated with prolonged hospital stay, increased costs, and reduced quality of life; but also with increased morbidity and mortality. Thus, the objective of this research thesis is to investigate measures, particularly the role of ultrasound guidance, in optimising access-site risks and complications in coronary angiography and percutaneous coronary intervention. The results showed that transradial access significantly reduced the composite outcome compared to transfemoral access. Transfemoral access remained superior to transradial access in terms of reduced mean access time, mean access attempts, number of difficult accesses, as well as procedural time and dose-area product. However, there was no difference in the number of first pass successes between the two groups. The rate of venepuncture was markedly higher in the transfemoral approach. Ultrasound guidance did not demonstrate a benefit in clinical outcomes compared with standard access. Ultrasound guidance improved the efficiency and overall success rate of arterial access when compared with the standard palpation technique. It reduced mean access time, mean access attempts, number of difficult accesses, rate of venepuncture, and improved the number of first pass success. Ultrasound guidance significantly improved successful catheterisation of the femoral artery above the bifurcation without an increase in the rate of high punctures. Ultrasounnd guidance in femoral access achieved a high level of ideal puncture and did not increase the risk of retroperitoneal haemorrhage. Obese patients with an abdominal circumference ≥ 100cm had higher rates of vascular complications and ACUITY minor bleeding in comparison to those with an abdominal circumference < 100cm, when undergoing coronary angiogram and/or PCI via a transfemoral approach. Ultrasound guidance was shown to significantly improve femoral artery access outcomes in obese patients with thigh circumference ≥ 60cm when compared with the standard palpation technique. The numbers required to attain competency in ultrasound-guided transfemoral and transradial access were 15 and 25 punctures, respectively. The incidence of subclinical stenoses of the radial artery after being cannulated for catheterization occurred more frequently than anticipated. There were no significant changes in the levels of intercellular adhesion molecule-1, vascular cell adhesion molecule-1, P-selectin and E-selectin when comparing pre- and immediately post-coronary procedures