SHAREDWEALTH: A CRYPTOCURRENCY TO REWARD MINERS EVENLY

Bitcoin [19] is a decentralized cryptocurrency that has recently gained popularity and has emerged as a popular medium of exchange. The total market capitalization is around 1.5 billion US dollars as of October 2013 [28]. All the operations of Bitcoin are maintained in a distributed public global ledger known as a block chain which consists of all the successful transactions that have ever taken place. The security of a block chain is maintained by a chain of cryptographic puzzles solved by participants called miners, who in return are rewarded with bitcoins. To be successful, the miner has to put in his resources to solve the cryptographic puzzle (also known as a proof of work). The reward structure is an incentive for miners to contribute their computational resources and is also essential to the currency\u27s decentralized nature. One disadvantage of the reward structure is that the payment system is uneven. The reward is always given to one person. Hence people form mining pools where every member of the pool solves the same cryptographic puzzle and irrespective of the person who solved it, the reward is shared evenly among all the members of the pool. The Bitcoin protocol assumes that the miners are honest and they follow the Bitcoin protocol as prescribed. If group of selfish miners comes to lead by forming pools, the currency stops being decentralized and comes under the control of the selfish miners. Such miners can control the whole Bitcoin network [29]. Our goal is to address this problem by creating a distinct peer-to-peer protocol that reduces the incentives for the miners to join large mining pools. The central idea is to pay the “runners-up” who come close to finding a proof, thereby creating a less volatile payout situation. The work done by the “runners-up” can be used by other miners to find the solution of proof of work by building upon their work. Once they find the actual solution they have to include the solution of the other miner in order to get rewarded. The benefit of this protocol is that not only the miners save their computational resources but also the reward is distributed among the miners

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Stack Overflow in Github: Any Snippets There?

When programmers look for how to achieve certain programming tasks, Stack Overflow is a popular destination in search engine results. Over the years, Stack Overflow has accumulated an impressive knowledge base of snippets of code that are amply documented. We are interested in studying how programmers use these snippets of code in their projects. Can we find Stack Overflow snippets in real projects? When snippets are used, is this copy literal or does it suffer adaptations? And are these adaptations specializations required by the idiosyncrasies of the target artifact, or are they motivated by specific requirements of the programmer? The large-scale study presented on this paper analyzes 909k non-fork Python projects hosted on Github, which contain 290M function definitions, and 1.9M Python snippets captured in Stack Overflow. Results are presented as quantitative analysis of block-level code cloning intra and inter Stack Overflow and GitHub, and as an analysis of programming behaviors through the qualitative analysis of our findings.Comment: 14th International Conference on Mining Software Repositories, 11 page

Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blob-filaments in real time in fusion plasma. On a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.Comment: 14 pages, 40 figure

Online Search Tool for Graphical Patterns in Electronic Band Structures

We present an online graphical pattern search tool for electronic band structure data contained within the Organic Materials Database (OMDB) available at https://omdb.diracmaterials.org/search/pattern. The tool is capable of finding user-specified graphical patterns in the collection of thousands of band structures from high-throughput ab initio calculations in the online regime. Using this tool, it only takes a few seconds to find an arbitrary graphical pattern within the ten electronic bands near the Fermi level for 26,739 organic crystals. The tool can be used to find realizations of functional materials characterized by a specific pattern in their electronic structure, for example, Dirac materials, characterized by a linear crossing of bands; topological insulators, characterized by a "Mexican hat" pattern or an effectively free electron gas, characterized by a parabolic dispersion. The source code of the developed tool is freely available at https://github.com/OrganicMaterialsDatabase/EBS-search and can be transferred to any other electronic band structure database. The approach allows for an automatic online analysis of a large collection of band structures where the amount of data makes its manual inspection impracticable.Comment: 8 pages, 8 figure