Improved Compressive Sensing Of Natural Scenes Using Localized Random Sampling

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, localized random sampling, which yields significantly improved CS image reconstructions. For each set of localized image measurements, our sampling method first randomly selects an image pixel and then measures its nearby pixels with probability depending on their distance from the initially selected pixel. We compare the uniformly-random and localized random sampling methods over a large space of sampling parameters, and show that, for the optimal parameter choices, higher quality image reconstructions can be consistently obtained by using localized random sampling. In addition, we argue that the localized random CS optimal parameter choice is stable with respect to diverse natural images, and scales with the number of samples used for reconstruction. We expect that the localized random sampling protocol helps to explain the evolutionarily advantageous nature of receptive field structure in visual systems and suggests several future research areas in CS theory and its application to brain imaging

Robustness assessment of the ‘cooperation under resource pressure’ (CURP) model: Insights on resource availability and sharing practices among hunter-gatherers

A well-known challenge in archaeological research is the exploration of the social mechanisms that hunter-gatherers may have implemented throughout history to deal with changes in resource availability. The agent-based model (ABM) ‘cooperation under resource pressure’ (CURP) was conceived to explore food stress episodes in societies lacking a food preservation technology. It was particularly aimed at understanding how cooperative behaviours in the form of food sharing practices emerge, increase and may become the prevailing strategy in relation to changes in resource availability and expectancy of reciprocity. CURP’s main outcome is the identification of three regimes of behaviour depending on the stress level. In this work, the model’s robustness to the original selection mechanism (random tournament) is assessed, as different dynamics can lead to different persistent regimes. For that purpose, three other selection mechanisms are implemented and evaluated, to identify the prevailing states of the system. Results show that the three regimes are robust irrespective of the analysed dynamics. We consequently examine in more detail the long-term archaeological implications that these results may have.Spanish Ministry of Economy and Competitiveness (former Ministry of Science and Innovation): SimulPast Project (CSD2010- 00034 CONSOLIDER-INGENIO 2010), HAR2009-06996 and CULM Project (HAR2016- 77672-P); from the Argentine National Scientific and Technical Research Council (CONICET): Project PIP-0706; from the Wenner-Gren Foundation for Anthropological Research: Project GR7846; from the project H2020 FET OPEN RIA IBSEN/662725 and from the European Social Fund as one of the authors is the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León (Spain)

The Rationale of China’s Media Regulation Policy in the Process of the Institutional Transformation

Through its institutional transformation, China’s media policy has features of both power-regulated societies and rights-regulated societies. The development of human societies is based on three dominant variables: competition, technology, and institutions. Throughout civilized history, human societies can be categorized into two types, either power-regulated societies or rights-regulated societies. The standard of categorization is based on different forces that coerce the social order of the society. The coercing force of power-regulated societies is rooted in the regime of power, such as authoritarianism or totalitarianism. Ancient China and the former Soviet Union are typical examples of such power-regulated societies. The coercing force of rights-regulated societies is rooted in the private rights of its citizens. Democratic societies like Great Britain and the United States are typical examples of rights-regulated societies. The morality and legitimacy of power-regulated societies are to maintain order and protect the regime of power, whereas rights-regulated societies work to protect private rights of the people. Therefore, media policy and regulations are fundamentally different in the two types of societies. Power-regulated societies use a power-controlled media model, and rights-regulated societies use a free media model. Today, China’s media policy is in the process of transforming from a state-controlled media model to a free media model and show features of both a power-regulated society and a rights-regulated society. China’s institutions have been transforming since the first exposure to globalization in the mid-nineteenth century. Over the last century, China has experience three institutional transformations: during the Xinhai revolution, the Cultural Revolution, and the reform and open policy. The current institutional transformation will change not only Chinese society, but will also impact the world. The more we understand this complicated process of transformation, the better we comprehend the rationality of media regulation policy in China

Mean-Field-Type Games in Engineering

A mean-field-type game is a game in which the instantaneous payoffs and/or the state dynamics functions involve not only the state and the action profile but also the joint distributions of state-action pairs. This article presents some engineering applications of mean-field-type games including road traffic networks, multi-level building evacuation, millimeter wave wireless communications, distributed power networks, virus spread over networks, virtual machine resource management in cloud networks, synchronization of oscillators, energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201

Dynamic Spectrum Allocation and Sharing in Cognitive Cooperative Networks

The dramatic increase of service quality and channel capacity in wireless networks is severely limited by the scarcity of energy and bandwidth, which are the two fundamental resources for communications. New communications and networking paradigms such as cooperative communication and cognitive radio networks emerged in recent years that can intelligently and efficiently utilize these scarce resources. With the development of these new techniques, how to design efficient spectrum allocation and sharing schemes becomes very important, due to the challenges brought by the new techniques. In this dissertation we have investigated several critical issues in spectrum allocation and sharing and address these challenges. Due to limited network resources in a multiuser radio environment, a particular user may try to exploit the resources for self-enrichment, which in turn may prompt other users to behave the same way. In addition, cognitive users are able to make intelligent decisions on spectrum usage and communication parameters based on the sensed spectrum dynamics and other users' decisions. Thus, it is important to analyze the intelligent behavior and complicated interactions of cognitive users via game-theoretic approaches. Moreover, the radio environment is highly dynamic, subject to shadowing/fading, user mobility in space/frequency domains, traffic variations, and etc. Such dynamics brings a lot of overhead when users try to optimize system performance through information exchange in real-time. Hence, statistical modeling of spectrum variations becomes essential in order to achieve near-optimal solutions on average. In this dissertation, we first study a stochastic modeling approach for dynamic spectrum access. Since the radio spectrum environment is highly dynamic, we model the traffic variations in dynamic spectrum access using continuous-time Markov chains that characterizes future traffic patterns, and optimize access probabilities to reduce performance degradation due to co-channel interference. Second, we propose an evolutionary game framework for cooperative spectrum sensing with selfish users, and develop the optimal collaboration strategy that has better performance than fully cooperating strategy. Further, we study user cooperation enforcement for cooperative networks with selfish users. We model the optimal relay selection and power control problem as a Stackelberg game, and consider the joint benefits of source nodes as buyers and relay nodes as sellers. The proposed scheme achieves the same performance compared to traditional centralized optimization while reducing the signaling overhead. Finally, we investigate possible attacks on cooperative spectrum sensing under the evolutionary sensing game framework, and analyze their damage both theoretically and by simulations

Thirty-second Annual Symposium of Trinity College Undergraduate Research

2019 annual volume of abstracts for science research projects conducted by students at Trinity College

Elastic Network Models in Biology: From Protein Mode Spectra to Chromatin Dynamics

Biomacromolecules perform their functions by accessing conformations energetically favored by their structure-encoded equilibrium dynamics. Elastic network model (ENM) analysis has been widely used to decompose the equilibrium dynamics of a given molecule into a spectrum of modes of motions, which separates robust, global motions from local fluctuations. The scalability and flexibility of the ENMs permit us to efficiently analyze the spectral dynamics of large systems or perform comparative analysis for large datasets of structures. I showed in this thesis how ENMs can be adapted (1) to analyze protein superfamilies that share similar tertiary structures but may differ in their sequence and functional dynamics, and (2) to analyze chromatin dynamics using contact data from Hi-C experiments, and (3) to perform a comparative analysis of genome topology across different types of cell lines. The first study showed that protein family members share conserved, highly cooperative (global) modes of motion. A low-to-intermediate frequency spectral regime was shown to have a maximal impact on the functional differentiation of families into subfamilies. The second study demonstrated the Gaussian Network Model (GNM) can accurately model chromosomal mobility and couplings between genomic loci at multiple scales: it can quantify the spatial fluctuations in the positions of gene loci, detect large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. The third study revealed close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations in the spatial fluctuations of genomic loci. It also called attention to the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation. Together, these studies provide a comprehensive view of the versatility and utility of the ENMs in analyzing spatial dynamics of biomolecules, from individual proteins to the entire chromatin