1,210 research outputs found

    A survey of outlier detection methodologies

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    Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes in system behaviour, fraudulent behaviour, human error, instrument error or simply through natural deviations in populations. Their detection can identify system faults and fraud before they escalate with potentially catastrophic consequences. It can identify errors and remove their contaminating effect on the data set and as such to purify the data for processing. The original outlier detection methods were arbitrary but now, principled and systematic techniques are used, drawn from the full gamut of Computer Science and Statistics. In this paper, we introduce a survey of contemporary techniques for outlier detection. We identify their respective motivations and distinguish their advantages and disadvantages in a comparative review

    Blockchain: A Graph Primer

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    Bitcoin and its underlying technology Blockchain have become popular in recent years. Designed to facilitate a secure distributed platform without central authorities, Blockchain is heralded as a paradigm that will be as powerful as Big Data, Cloud Computing and Machine learning. Blockchain incorporates novel ideas from various fields such as public key encryption and distributed systems. As such, a reader often comes across resources that explain the Blockchain technology from a certain perspective only, leaving the reader with more questions than before. We will offer a holistic view on Blockchain. Starting with a brief history, we will give the building blocks of Blockchain, and explain their interactions. As graph mining has become a major part its analysis, we will elaborate on graph theoretical aspects of the Blockchain technology. We also devote a section to the future of Blockchain and explain how extensions like Smart Contracts and De-centralized Autonomous Organizations will function. Without assuming any reader expertise, our aim is to provide a concise but complete description of the Blockchain technology.Comment: 16 pages, 8 figure

    A taxonomy framework for unsupervised outlier detection techniques for multi-type data sets

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    The term "outlier" can generally be defined as an observation that is significantly different from the other values in a data set. The outliers may be instances of error or indicate events. The task of outlier detection aims at identifying such outliers in order to improve the analysis of data and further discover interesting and useful knowledge about unusual events within numerous applications domains. In this paper, we report on contemporary unsupervised outlier detection techniques for multiple types of data sets and provide a comprehensive taxonomy framework and two decision trees to select the most suitable technique based on data set. Furthermore, we highlight the advantages, disadvantages and performance issues of each class of outlier detection techniques under this taxonomy framework

    Time-series analyses of Monterey Bay coastal microbial picoplankton using a ‘genome proxy’ microarray

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    To investigate the temporal, spatial and phylogenetic resolution of marine microbial community structure and variability, we designed and expanded a genome proxy array (an oligonucleotide microarray targeting marine microbial genome fragments and genomes), evaluated it against metagenomic sequencing, and applied it to time-series samples from the Monterey Bay. The expanded array targeted 268 microbial genotypes across much of the known diversity of cultured and uncultured marine microbes. The target abundances measured by the array were highly correlated to pyrosequence-based abundances (linear regression R2 = 0.85–0.91, P < 0.0001). Fifty-seven samples from ∼4 years in Monterey Bay were examined with the array, spanning the photic zone (0 m), the base of the surface mixed layer (30 m) and the subphotic zone (200 m). A significant portion of the expanded genome proxy array's targets showed signal (95 out of 268 targets present in ≥ 1 sample). The multi-year community survey showed the consistent presence of a core group of common and abundant targeted taxa at each depth in Monterey Bay, higher variability among shallow than deep samples, and episodic occurrences of more transient marine genotypes. The abundance of the most dominant genotypes peaked after strong episodic upwelling events. The genome-proxy array's ability to track populations of closely related genotypes indicated population shifts within several abundant target taxa, with specific populations in some cases clustering by depth or oceanographic season. Although 51 cultivated organisms were targeted (representing 19% of the array) the majority of targets detected and of total target signal (85% and ∼92% respectively) were from uncultivated genotypes, often those derived from Monterey Bay. The array provided a relatively cost-effective approach (∼$15 per array) for surveying the natural history of uncultivated lineages.Gordon and Betty Moore FoundationNational Science Foundation (U.S.) (Science and Technology Center Award EF0424599)National Science Foundation (U.S.) (Microbial Observatory Award MCB-0348001)United States. Dept. of Energy. Office of Scienc

    Enhancement of external wall decoration material for the building in safety inspection method

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    As buildings wear out, external wall tiles or attachments will usually fall off, sometimes causing human injuries. At present, the method employed for middle-high rise buildings is mainly the method of visual inspection. The inspection results in using this method are affected by the factors of subjectivity, safety and cost. This study aims to provide a lowercost and more efficient evaluation method for inspecting the status of buildings’ external walls. This proposed method implements Forward Looking Infrared (FLIR) technology and high-resolution photographic equipment on Unmanned Aerial Vehicle (UAV) which can improve the image recording of the detection process, as well as the overall visual detection technology, and solve the existing visual detection problem of inspectors. Also, the images detected by visual inspection and UAV high-resolution video are used to develop a suitable visual evaluation process and test table for external walls. Through the test results of several cases, the deterioration status and needs for maintenance are taken into account according to the degree of performance indicators. The findings of the study is that the proposed mechanism is more efficient and lower cost for the detection of external walls or ancillary structures’ abnormal status, which is easy to use in practice
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