Mutual-Excitation of Cryptocurrency Market Returns and Social Media Topics

Cryptocurrencies have recently experienced a new wave of price volatility and interest; activity within social media communities relating to cryptocurrencies has increased significantly. There is currently limited documented knowledge of factors which could indicate future price movements. This paper aims to decipher relationships between cryptocurrency price changes and topic discussion on social media to provide, among other things, an understanding of which topics are indicative of future price movements. To achieve this a well-known dynamic topic modelling approach is applied to social media communication to retrieve information about the temporal occurrence of various topics. A Hawkes model is then applied to find interactions between topics and cryptocurrency prices. The results show particular topics tend to precede certain types of price movements, for example the discussion of 'risk and investment vs trading' being indicative of price falls, the discussion of 'substantial price movements' being indicative of volatility, and the discussion of 'fundamental cryptocurrency value' by technical communities being indicative of price rises. The knowledge of topic relationships gained here could be built into a real-time system, providing trading or alerting signals.Comment: 3rd International Conference on Knowledge Engineering and Applications (ICKEA 2018) - Moscow, Russia (June 25-27 2018

SOTXTSTREAM: Density-based self-organizing clustering of text streams

A streaming data clustering algorithm is presented building upon the density-based selforganizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets

FPGA Based Data Read-Out System of the Belle 2 Pixel Detector

The upgrades of the Belle experiment and the KEKB accelerator aim to increase the data set of the experiment by the factor 50. This will be achieved by increasing the luminosity of the accelerator which requires a significant upgrade of the detector. A new pixel detector based on DEPFET technology will be installed to handle the increased reaction rate and provide better vertex resolution. One of the features of the DEPFET detector is a long integration time of 20 {\mu}s, which increases detector occupancy up to 3 %. The detector will generate about 2 GB/s of data. An FPGA-based two-level read-out system, the Data Handling Hybrid, was developed for the Belle 2 pixel detector. The system consists of 40 read-out and 8 controller modules. All modules are built in {\mu}TCA form factor using Xilinx Virtex-6 FPGA and can utilize up to 4 GB DDR3 RAM. The system was successfully tested in the beam test at DESY in January 2014. The functionality and the architecture of the Belle 2 Data Handling Hybrid system as well as the performance of the system during the beam test are presented in the paper.Comment: Transactions on Nuclear Science, Proceedings of the 19th Real Time Conference, Preprin

In a search for a shape maximizing packing fraction for two-dimensional random sequential adsorption

Random sequential adsorption (RSA) of various two dimensional objects is studied in order to find a shape which maximizes the saturated packing fraction. This investigation was begun in our previous paper [Cie\'sla et al., Phys. Chem. Chem. Phys. 17, 24376 (2015)], where the densest packing was studied for smoothed dimers. Here this shape is compared with a smoothed $n$-mers, spherocylinders and ellipses. It is found that the highest packing fraction out of the studied shapes is $0.58405 \pm 0.0001$ and is obtained for ellipses having long-to-short axis ratio of $1.85$, which is also the largest anisotropy among the investigated shapes.Comment: 14 pages, 7 fiure

Microscopic basis for pattern formation and anomalous transport in two-dimensional active gels

Active gels are a class of biologically-relevant material containing embedded agents that spontaneously generate forces acting on a sparse filament network. In vitro experiments of protein filaments and molecular motors have revealed a range of non- equilibrium pattern formation resulting from motor motion along filament tracks, and there are a number of hydrodynamic models purporting to describe such systems. Here we present results of extensive simulations designed to elucidate the microscopic basis underpinning macroscopic flow in active gels. Our numerical scheme includes thermal fluctuations in filament positions, excluded volume interactions, and filament elasticity in the form of bending and stretching modes. Motors are represented individually as bipolar springs governed by rate-based rules for attachment, detachment and unidirectional motion of motor heads along the filament contour. We systematically vary motor density and speed, and uncover parameter regions corresponding to unusual statics and dynamics which overlap but do not coincide. The anomalous statics arise at high motor densities and take the form of end-bound localized filament bundles for rapid motors, and extended clusters exhibiting enhanced small-wavenumber density fluctuations and power-law cluster-size distributions for slow, processive motors. Anomalous dynamics arise for slow, processive motors over a range of motor densities, and are most evident as superdiffusive mass transport, which we argue is the consequence of a form of effective self-propulsion resulting from the polar coupling between motors and filaments.Comment: 14 pages, 17 figures. Minor clarifications and updated/additional references. To appear in Soft Matte

Health Figures: An Open Source JavaScript Library for Health Data Visualization

The way we look at data has a great impact on how we can understand it, particularly when the data is related to health and wellness. Due to the increased use of self-tracking devices and the ongoing shift towards preventive medicine, better understanding of our health data is an important part of improving the general welfare of the citizens. Electronic Health Records, self-tracking devices and mobile applications provide a rich variety of data but it often becomes difficult to understand. We implemented the hFigures library inspired on the hGraph visualization with additional improvements. The purpose of the library is to provide a visual representation of the evolution of health measurements in a complete and useful manner. We researched the usefulness and usability of the library by building an application for health data visualization in a health coaching program. We performed a user evaluation with Heuristic Evaluation, Controlled User Testing and Usability Questionnaires. In the Heuristics Evaluation the average response was 6.3 out of 7 points and the Cognitive Walkthrough done by usability experts indicated no design or mismatch errors. In the CSUQ usability test the system obtained an average score of 6.13 out of 7, and in the ASQ usability test the overall satisfaction score was 6.64 out of 7. We developed hFigures, an open source library for visualizing a complete, accurate and normalized graphical representation of health data. The idea is based on the concept of the hGraph but it provides additional key features, including a comparison of multiple health measurements over time. We conducted a usability evaluation of the library as a key component of an application for health and wellness monitoring. The results indicate that the data visualization library was helpful in assisting users in understanding health data and its evolution over time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016