Expander Graph and Communication-Efficient Decentralized Optimization

In this paper, we discuss how to design the graph topology to reduce the communication complexity of certain algorithms for decentralized optimization. Our goal is to minimize the total communication needed to achieve a prescribed accuracy. We discover that the so-called expander graphs are near-optimal choices. We propose three approaches to construct expander graphs for different numbers of nodes and node degrees. Our numerical results show that the performance of decentralized optimization is significantly better on expander graphs than other regular graphs.Comment: 2016 IEEE Asilomar Conference on Signals, Systems, and Computer

A Dynamic Ice-structure Interaction Model for Prediction of Ice-induced Vibration

Sea ice crashing against offshore structures can cause strong ice-induced vibration and have a major impact on offshore structural safety and serviceability. This paper describes a numerical method for the prediction of ice-induced vibration when a vertical offshore structure is subjected to the impact of sea ice. In this approach, negative damping theory and fracture length theory are combined and, along with ice strength-stress rate curve and ice failure length, are coupled to model the internal fluctuating nature of ice load. Considering the elastic deformation of ice and the effect of non-simultaneous crushing failure of local contact between ice and structures, the present ice-induced vibration model is established, and the general features of the interaction process are captured. To verify its efficacy, the presented simulation methodology is subjected to a model test and two full-scale measurements based on referenced studies. Example calculations show good agreement with the results of the model test and full-scale measurements, which directly indicates the validity of the proposed simulation method. In addition, the numerical simulation method can be used in connection with FE programs to perform ice-induced vibration analysis of offshore structures

Experimental realization of non-Abelian gauge potentials and topological Chern state in circuit system

Gauge fields, both Abelian and non-Abelian type, play an important role in modern physics. It prompts extensive studies of exotic physics on a variety of platforms. In this work, we present building blocks, consist of capacitors and inductors, for implementing non-Abelian gauge fields in circuit system. Based on these building blocks, we experimentally synthesize the Rashba-Dresselhaus spin-orbit interaction. Using operational amplifier, to break the time reversal symmetry, we further provide a scheme for designing the topological Chern circuit system. By measuring the chiral edge state of the Chern circuit, we experimentally confirm its topological nature. Our scheme offers a new route to study physics related to non-Abelian gauge field using circuit systems

Study on the control algorithm for lower limb exoskeleton based on ADAMS/Simulink co-simulation

A sliding mode control algorithm based on proportional switching function was developed to make the lower limb exoskeleton more fit the human walking gait trajectory. It could improve the comfort of the exoskeleton wearer and enhance the reliability of the system. The three-dimensional mechanical model of the exoskeleton built using software SolidWorks was introduced to ADAMS and then the model parameters were set. The model was combined with the software MATLAB so that the human-machine cooperation control algorithm for lower limb exoskeleton based on ADAMS and Simulink co-simulation was developed. The simulation result was compared with the desired trajectory and the trajectory under PID control. The research discovered that the ability of trajectory tracking under the sliding mode control was much better than that under PID control. It provided an important theoretical basis for the research on human-machine cooperation control algorithm

Recent Ice Trends in Swiss Mountain Lakes: 20-year Analysis of MODIS Imagery

Depleting lake ice is a climate change indicator, just like sea-level rise or glacial retreat. Monitoring Lake Ice Phenology (LIP) is useful because long-term freezing and thawing patterns serve as sentinels to understand regional and global climate change. We report a study for the Oberengadin region of Switzerland, where several small- and medium-sized mountain lakes are located. We observe the LIP events, such as freeze-up, break-up and ice cover duration, across two decades (2000-2020) from optical satellite images. We analyse the time series of MODIS imagery by estimating spatially resolved maps of lake ice for these Alpine lakes with supervised machine learning. To train the classifier we rely on reference data annotated manually based on webcam images. From the ice maps, we derive long-term LIP trends. Since the webcam data are only available for two winters, we cross-check our results against the operational MODIS and VIIRS snow products. We find a change in complete freeze duration of -0.76 and -0.89 days per annum for lakes Sils and Silvaplana, respectively. Furthermore, we observe plausible correlations of the LIP trends with climate data measured at nearby meteorological stations. We notice that mean winter air temperature has a negative correlation with the freeze duration and break-up events and a positive correlation with the freeze-up events. Additionally, we observe a strong negative correlation of sunshine during the winter months with the freeze duration and break-up events.Comment: accepted for PFG Journal of Photogrammetry, Remote Sensing and Geoinformation Scienc