An Attention-based Collaboration Framework for Multi-View Network Representation Learning

Learning distributed node representations in networks has been attracting increasing attention recently due to its effectiveness in a variety of applications. Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network. However, in reality there usually exists multiple types of proximities between nodes, yielding networks with multiple views. This paper studies learning node representations for networks with multiple views, which aims to infer robust node representations across different views. We propose a multi-view representation learning approach, which promotes the collaboration of different views and lets them vote for the robust representations. During the voting process, an attention mechanism is introduced, which enables each node to focus on the most informative views. Experimental results on real-world networks show that the proposed approach outperforms existing state-of-the-art approaches for network representation learning with a single view and other competitive approaches with multiple views.Comment: CIKM 201

Diseño e implementación de un monedero para criptomoneda Bitcoin

Blockchain es una tecnológica que se ha puesto de moda en estos últimos años, uno de los productos creados por esta tecnología es Bitcoin, el motivo principal de este TFG es desarrollar un monedero de Bitcoin y desde este punto enseñar al lector como funciona Bitcoin y los conocimientos que tiene que saber para desarrollar un monedero Bitcoin. Este TFG concretamente es desarrollar un monedero Bitcoin que cumple los requisitos básicos de un monedero: crear un monedero nuevo, enviar Bitcoin, recibir Bitcoin y mantener Bitcoin de forma segura. Este documento describe el diseño y la implementación de este sistema, usando patrones de diseño MVC junto con Singleton, en la parte de desarrollo se ha establecido el uso de lenguaje de programación TypeScript, acompañado con frameworks: Angular6, Ionic3 y Electron, y algunas librerías de NodeJs: BitcoinJs-lib y Crypto, para desarrollar la lógica interna del monedero de Bitcoin. El resultado final es obtener un monedero de Bitcoin diseñado como una aplicación hibrida, que es capaz de ejecutar en todas las plataformas ya sea dispositivo móvil o computadores, en tiempo real

Comparison between Gulf of Mexico and Mediterranean Offshore Reservoirs

Deepwater oil and gas are simply conventional reserves in an unconventional setting. They consist of a resource class of their own largely because they face a common set of challenges in the course of their identification, characterization, development and production. However, there have already been successful deepwater reservoir developments, in sedimentary environments such as the Gulf of Mexico, offshore Brazil and West Africa. Especially in Gulf of Mexico, the offshore reservoirs are analyzed and exploited on a large scale, rendering a good case for deepwater exploration. Recently there have been large deepwater reservoirs discovered in the Mediterranean Basin. Except for the main reservoir type, the two regions’ situations are similar to each other including large water depth, great production potential and significance in the role played in their regions’ energy industry, respectively. Before the exploration starts, the analysis and forecast of the reservoir properties and quality are always the priority. This research is to characterize these reservoirs in a way that will be useful for further exploration. A previous study of US reservoirs including both terrestrial and offshore Gulf of Mexico reservoirs showed correlations of depth vs pressure, temperature, and mobility. Similar works are done for the newly discovered reservoirs in Gulf of Mexico, and the same approach is applied to the analysis of Mediterranean reservoirs. Basically, the study showed important trends related to water depth that explains why deepwater reservoirs may offer exceptional potential over terrestrial and shallow water reservoirs. The research done in this thesis is based on the following aspects: (1) previous analysis for Gulf of Mexico, (2) the new reservoir data analysis for both Gulf of Mexico and Mediterranean, (3) evaluation and comparison of the two regions. The deepwater reservoirs in two regions are similarly impacted by the water depth. Both reservoir pressure and porosity are altered higher by water. Also, some reservoir properties like permeability can be possibly inferred under specific condition. Based on the study, it is obvious that offshore reservoirs of the two regions have the potential for high deliverability and deserve exploration

An equivalent-effect phenomenon in eddy current non-destructive testing of thin structures

The inductance/impedance due to thin metallic structures in non-destructive testing (NDT) is difficult to evaluate. In particular, in Finite Element Method (FEM) eddy current simulation, an extremely fine mesh is required to accurately simulate skin effects especially at high frequencies, and this could cause an extremely large total mesh for the whole problem, i.e. including, for example, other surrounding structures and excitation sources like coils. Consequently, intensive computation requirements are needed. In this paper, an equivalent-effect phenomenon is found, which has revealed that alternative structures can produce the same effect on the sensor response, i.e. mutual impedance/inductance of coupled coils if a relationship (reciprocal relationship) between the electrical conductivity and the thickness of the structure is observed. By using this relationship, the mutual inductance/impedance can be calculated from the equivalent structures with much fewer mesh elements, which can significantly save the computation time. In eddy current NDT, coils inductance/impedance is normally used as a critical parameter for various industrial applications, such as flaw detection, coating and microstructure sensing. Theoretical derivation, measurements and simulations have been presented to verify the feasibility of the proposed phenomenon

Governance and performance in UK charities

This study aims to explore the association between governance, performance, and chief executive officer (CEO) compensation in United Kingdom (UK) charities. Existing literature of the link between non-profit performance and governance quality is limited for UK charities. This study uses panel data regression analysis, by investigating 100 UK charities over five years between 2013 and 2018. The data is collected from the Charity Commission. Charity performance is measured by programme expense ratio. The results first indicate that the performance is negatively associated with board size. Second, CEO compensation is positively related to board size and CEO tenure length. The study also considers the impact of several other factors on charity performance, such as board gender diversity, CEO age, CEO tenure and CEO compensation. However, the results are not significant enough to draw conclusions. In addition, the study did not find any impact of board gender diversity, CEO age and charity performance on CEO compensation

Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift

A key challenge of modern machine learning systems is to achieve Out-of-Distribution (OOD) generalization -- generalizing to target data whose distribution differs from that of source data. Despite its significant importance, the fundamental question of ``what are the most effective algorithms for OOD generalization'' remains open even under the standard setting of covariate shift. This paper addresses this fundamental question by proving that, surprisingly, classical Maximum Likelihood Estimation (MLE) purely using source data (without any modification) achieves the minimax optimality for covariate shift under the well-specified setting. That is, no algorithm performs better than MLE in this setting (up to a constant factor), justifying MLE is all you need. Our result holds for a very rich class of parametric models, and does not require any boundedness condition on the density ratio. We illustrate the wide applicability of our framework by instantiating it to three concrete examples -- linear regression, logistic regression, and phase retrieval. This paper further complement the study by proving that, under the misspecified setting, MLE is no longer the optimal choice, whereas Maximum Weighted Likelihood Estimator (MWLE) emerges as minimax optimal in certain scenarios

Effective Numerical Simulations of Synchronous Generator System

Synchronous generator system is a complicated dynamical system for energy transmission, which plays an important role in modern industrial production. In this article, we propose some predictor-corrector methods and structure-preserving methods for a generator system based on the first benchmark model of subsynchronous resonance, among which the structure-preserving methods preserve a Dirac structure associated with the so-called port-Hamiltonian descriptor systems. To illustrate this, the simplified generator system in the form of index-1 differential-algebraic equations has been derived. Our analyses provide the global error estimates for a special class of structure-preserving methods called Gauss methods, which guarantee their superior performance over the PSCAD/EMTDC and the predictor-corrector methods in terms of computational stability. Numerical simulations are implemented to verify the effectiveness and advantages of our methods

Diversified pattern of the human colorectal cancer microbiome

BACKGROUND: The aim of this study is to expand existing knowledge about the CRC-associated microbiome among Han Chinese, and to further discover the variation pattern of the human CRC microbiome across all population. FINDINGS: Using pyrosequencing-based molecular monitoring of bacterial 16S rRNA gene from eight tumor/normal tissue pairs of eight Chinese CRC patients, we analyzed and characterized the basic features of the CRC-associated microbiome. Firstly, we discovered an increasing diversity among tumor-associated bacterial communities. Secondly, in 50% of Chinese CRC patients, we found a significant increase of Roseburia (P = 0.017), and a concurrent decrease of both Microbacterium (P = 0.009) and Anoxybacillus (P = 0.009) in tumor tissue. CONCLUSIONS: We discovered a novel CRC microbiome pattern in Chinese. Both the over-represented Roseburia bacteria at tumor sites and the over-represented Microbacterium and Anoxybacillus bacteria away from tumor sites were both closely related in Chinese CRC patients. Across several populations reported in this study and previously, we observed both common and distinctive patterns of human CRC microbiome’s association with a high-risk of CRC