Parallel Implementation of Lossy Data Compression for Temporal Data Sets

Many scientific data sets contain temporal dimensions. These are the data storing information at the same spatial location but different time stamps. Some of the biggest temporal datasets are produced by parallel computing applications such as simulations of climate change and fluid dynamics. Temporal datasets can be very large and cost a huge amount of time to transfer among storage locations. Using data compression techniques, files can be transferred faster and save storage space. NUMARCK is a lossy data compression algorithm for temporal data sets that can learn emerging distributions of element-wise change ratios along the temporal dimension and encodes them into an index table to be concisely represented. This paper presents a parallel implementation of NUMARCK. Evaluated with six data sets obtained from climate and astrophysics simulations, parallel NUMARCK achieved scalable speedups of up to 8788 when running 12800 MPI processes on a parallel computer. We also compare the compression ratios against two lossy data compression algorithms, ISABELA and ZFP. The results show that NUMARCK achieved higher compression ratio than ISABELA and ZFP.Comment: 10 pages, HiPC 201

An Information-Theoretic Test for Dependence with an Application to the Temporal Structure of Stock Returns

Information theory provides ideas for conceptualising information and measuring relationships between objects. It has found wide application in the sciences, but economics and finance have made surprisingly little use of it. We show that time series data can usefully be studied as information -- by noting the relationship between statistical redundancy and dependence, we are able to use the results of information theory to construct a test for joint dependence of random variables. The test is in the same spirit of those developed by Ryabko and Astola (2005, 2006b,a), but differs from these in that we add extra randomness to the original stochatic process. It uses data compression to estimate the entropy rate of a stochastic process, which allows it to measure dependence among sets of random variables, as opposed to the existing econometric literature that uses entropy and finds itself restricted to pairwise tests of dependence. We show how serial dependence may be detected in S&P500 and PSI20 stock returns over different sample periods and frequencies. We apply the test to synthetic data to judge its ability to recover known temporal dependence structures.Comment: 22 pages, 7 figure

Active Virtual Network Management Prediction: Complexity as a Framework for Prediction, Optimization, and Assurance

Research into active networking has provided the incentive to re-visit what has traditionally been classified as distinct properties and characteristics of information transfer such as protocol versus service; at a more fundamental level this paper considers the blending of computation and communication by means of complexity. The specific service examined in this paper is network self-prediction enabled by Active Virtual Network Management Prediction. Computation/communication is analyzed via Kolmogorov Complexity. The result is a mechanism to understand and improve the performance of active networking and Active Virtual Network Management Prediction in particular. The Active Virtual Network Management Prediction mechanism allows information, in various states of algorithmic and static form, to be transported in the service of prediction for network management. The results are generally applicable to algorithmic transmission of information. Kolmogorov Complexity is used and experimentally validated as a theory describing the relationship among algorithmic compression, complexity, and prediction accuracy within an active network. Finally, the paper concludes with a complexity-based framework for Information Assurance that attempts to take a holistic view of vulnerability analysis

Quantifying Viscoelastic Properties of Nylon-6,6 Actuators

Orthostatic Hypotension (OH) is a prevalent condition affecting 52.1% of stroke patients, characterized by a drop in atrial blood pressure upon standing. This is due to the pooling of blood in the abdomen and leg, and OH results in debilitating symptoms of nausea, lightheadedness, and dizziness. Current management techniques are limited and not very effective, so I propose an active, compression abdominal band that contracts when needed. This device should have a minimal design, so nylon-6,6 actuators, powerful artificial muscles created from fishing line and conductive thread, were chosen as the compressive element. Given that previous research focused on strength and force-excursion characteristics of these actuators, this study focuses on determining their viability for this application by conducting stress-relaxation and creep tests on single actuators (sample sizes of 10) and on a forty actuator band. Stress-relaxation results indicate that actuators will be able to maintain tension levels required effective compression 18 times as long as necessary. Creep testing is inconclusive due to oscillations found in the data as a result of low processing power of the Instron machine used to conduct tests. Despite the fact that more tests need to be conducted to resolve various limitations of this study,I conclude that I can move forward to create a prototype of the abdominal band.Biomedical Engineerin

A mission synthesis algorithm for fatigue damage analysis

This paper presents a signal processing based algorithm, the Mildly Nonstationary Mission Synthesis (MNMS), which produces a short mission signal from long records of experimental data. The algorithm uses the Discrete Fourier Transform, Orthogonal Wavelet Transform and bump reinsertion procedures. In order to observe the algorithm effectiveness a fatigue damage case study was performed for a vehicle lower suspension arm using signals containing tensile and compressive preloading. The mission synthesis results were compared to the original road data in terms of both the global signal statistics and the fatigue damage variation as a function of compression ratio. Three bump reinsertion methods were used and evaluated. The methods differed in the manner in which bumps (shock events) from different wavelet groups (frequency bands) were synchronised during the reinsertion process. One method, based on time synchronised section reinsertion, produced the best results in terms of mission signal kurtosis, crest factor, root-mean-square level and power spectral density. For improved algorithm performance, bump selection was identified as the main control parameter requiring optimisation