Relaxation-based importance sampling for structural reliability analysis

This study presents an importance sampling formulation based on adaptively relaxing parameters from the indicator function and/or the probability density function. The formulation embodies the prevalent mathematical concept of relaxing a complex problem into a sequence of progressively easier sub-problems. Due to the flexibility in constructing relaxation parameters, relaxation-based importance sampling provides a unified framework for various existing variance reduction techniques, such as subset simulation, sequential importance sampling, and annealed importance sampling. More crucially, the framework lays the foundation for creating new importance sampling strategies, tailoring to specific applications. To demonstrate this potential, two importance sampling strategies are proposed. The first strategy couples annealed importance sampling with subset simulation, focusing on low-dimensional problems. The second strategy aims to solve high-dimensional problems by leveraging spherical sampling and scaling techniques. Both methods are desirable for fragility analysis in performance-based engineering, as they can produce the entire fragility surface in a single run of the sampling algorithm. Three numerical examples, including a 1000-dimensional stochastic dynamic problem, are studied to demonstrate the proposed methods

RF system for mmWave massive MIMO

Due to rapid developments in communication technology, it is likely that 5G networks will be rolled out in 2019. To adapt to 5G, hardware will have to develop to meet the requirements of this new technology. The mmWave communication is one of the main elements of 5G technology. The mmWave frequency bandwidth is used to carry the data links and can achieve a higher transmission data rate than the current LTE system. There are few continuous frequency resources under 3GHz that can be allocated. As such, the International Telecommunication Union (ITU) and the 3GPP organization mutually agree that the mmWave is the most suitable option for exploring new frequency resources. However, the mmWave has the one key weakness: high path loss for short transmission range. To compensate for this negative effect, a massive MIMO system can be used to have spatial multiplexing gains and array an-tenna gains. This article seeks a method that can acknowledge the funda-mental concepts and requirements of the mmWave massive MIMO system, from both theoretical and practical perspectives. In order to find proof of the concepts, the practical limitations, and the guild of the real design, a prototype of the system has been built. The current industry standard when creating a prototype is to use PCB. We will develop our system proposals from the prototype. To do so we use the evaluation boards to test system level performances such as link budget and identifying the most suitable components etc. Then in the PCB design, we integrate the radio frequency of the mmWave system. This has the scalability to collaborate with massive MIMO system test-bed to observe the system level performance. Finally, to verify our methods, we carry out experiments on both component level and system level in order to identify the feasibility of the prototype system. The performance of each individual component is tested using an evaluation board. Separate tests are performed for both transmitting (Tx) and receiving (Rx) chains. Finally, over-air-tests are conducted at the sys-tem level to evaluate the performance of our design5G communication system is the next milestone that will soon approach our lives. The first specification of 5G is called Release 15 and the system struc-tures and requirements of it have been identified. Compared to the LTE system, it can deliver an even higher data rate and adapt more transmission situations in the future. 5G consists of five essential technologies, mmWave, massive MIMO, the advanced channel coding, scalable OFDM and self-contained slot structure. The first two technologies, the mmWave and massive MIMO, are indispensable in this thesis. As the fre-quency resources scarcely go below 3GHz, they are retrieving the mmWave spectrum to allocate more accessible bandwidth. Nevertheless, the mmWave has high free space path loss, and the signal will be harshly weakened before it reaches the receiver. The massive MIMO is an extension of the MIMO system with massive antenna elements in the antenna array This sound solution can contradict the high free space path loss, achieve high throughput and serve tens of users simultaneously. This thesis concentrates on building a radio frequency system PCB prototype based on mmWave and massive MIMO. Now, the existing hardware devices will not placate the 5G system necessi-ties. The new system structure must be developed, and the performance will be evaluated. Prototype is a realization method to transition from theory to practice which can help the engineers comprehend the theoretical and prac-tical perspectives. In electronic industry, PCB is the correct way of building the radio frequency prototype, in which the system schematic is construct-ed in a dense area with mass circuit distribution. All electronic components are surfaced and then mounted on it and connected by conductive wires through the various layers. A flawless PCB needs to be shaped with full operational functions before the final products. To do this, the perfor-mance will be evaluated when we are building the PCB prototype and im-provements will be analysed, and additional developments will be encom-passed in the future version of PCB. In this thesis, the PCB performance is evaluated individually for different transmission chains, and then the over air test is assessed

Maximum entropy-based modeling of community-level hazard responses for civil infrastructures

Perturbed by natural hazards, community-level infrastructure networks operate like many-body systems, with behaviors emerging from coupling individual component dynamics with group correlations and interactions. It follows that we can borrow methods from statistical physics to study the response of infrastructure systems to natural disasters. This study aims to construct a joint probability distribution model to describe the post-hazard state of infrastructure networks and propose an efficient surrogate model of the joint distribution for large-scale systems. Specifically, we present maximum entropy modeling of the regional impact of natural hazards on civil infrastructures. Provided with the current state of knowledge, the principle of maximum entropy yields the ``most unbiased`` joint distribution model for the performances of infrastructures. In the general form, the model can handle multivariate performance states and higher-order correlations. In a particular yet typical scenario of binary performance state variables with knowledge of their mean and pairwise correlation, the joint distribution reduces to the Ising model in statistical physics. In this context, we propose using a dichotomized Gaussian model as an efficient surrogate for the maximum entropy model, facilitating the application to large systems. Using the proposed method, we investigate the seismic collective behavior of a large-scale road network (with 8,694 nodes and 26,964 links) in San Francisco, showcasing the non-trivial collective behaviors of infrastructure systems

A Study on Identity Construction of First Person Pronouns in Academic Papers from the Perspective of Evidentiality

The first person pronoun plays an important role in identity construction, however, there is few study on it from the perspective of evidentiality. This paper took the first person pronouns as evidentials, and conducted a comparable analysis on the frequency of them and the identities they constructed in academic papers between soft and hard sciences, aiming to find the differences between different discourse communities and explore their preferences for academic identity construction. The results showed that both fields prefer to use plural and subjective cases of first person pronouns, and they both prefer to construct the authorial identity of “researcher”, but scarcely construct the authorial identity of “responsible person”. Researchers in hard science use less evidentials than researchers in soft science, and they prefer to use evidentials “we” and “statement”, which weaken the authorial identity. Evidentials that embody authorial identity, including singular first person pronouns and “participation” evidentials, account for higher proportion in soft science than those in hard science

Online Game Level Generation from Music

Game consists of multiple types of content, while the harmony of different content types play an essential role in game design. However, most works on procedural content generation consider only one type of content at a time. In this paper, we propose and formulate online level generation from music, in a way of matching a level feature to a music feature in real-time, while adapting to players' play speed. A generic framework named online player-adaptive procedural content generation via reinforcement learning, OPARL for short, is built upon the experience-driven reinforcement learning and controllable reinforcement learning, to enable online level generation from music. Furthermore, a novel control policy based on local search and k-nearest neighbours is proposed and integrated into OPARL to control the level generator considering the play data collected online. Results of simulation-based experiments show that our implementation of OPARL is competent to generate playable levels with difficulty degree matched to the ``energy'' dynamic of music for different artificial players in an online fashion