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Automatic Target Recognition XXIX 2019

作者： Hammoud, Riad I. Overman, Timothy L.

This PDF file contains the front matter associated with SPIE Proceedings Volume 10988, including the Title Page, Copyright Information, Table of Contents, Author and Conference Committee lists.

ISBN: (纸本)9781510626416

This PDF file contains the front matter associated with SPIE Proceedings Volume 10988, including the Title Page, Copyright Information, Table of Contents, Author and Conference Committee lists.

关键词： Automatic target recognition Machine learning Computing systems Detection and tracking algorithms algorithm development Analytical research Image segmentation Data modeling Remote sensing Target recognition

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Daily estimates of Landsat fractional snow cover driven by MODIS and dynamic time-warping

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REMOTE SENSING OF ENVIRONMENT 2018年 216卷 635-646页

作者： Berman, Ethan E. Bolton, Douglas K. Coops, Nicholas C. Mityok, Zoltan K. Stenhouse, Gordon B. Moore, R. D. (Dan) Univ British Columbia Dept Forest Resources Management 2424 Mail Mall Vancouver BC V6T 1Z4 Canada fRI Res Box 6330 Hinton AB T7V 1X6 Canada Univ British Columbia Dept Geog 1984 West Mall Vancouver BC V6T 1Z2 Canada

Understanding seasonal snow cover dynamics is critical for management of hydrological regimes, habitat availability for wildlife species, forest fire risk assessment and recreational demands. Although data products provided at 500 m spatial resolution by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor provide important and readily available information on snow cover, capturing snow dynamics at finer spatial resolutions remains problematic due to the lack of high temporal and spatial resolution data, which limits the number of available observations each year. In this paper we present a new approach to create a daily time-series of 30-m snow observations (called SNOWARP), derived from daily MODIS Normalised Difference Snow Index (NDSI) snow cover data to capture the temporal dynamics of snow cover and Dynamic Time Warping (DTW) to re-order historical Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM + ), and Operational Land Imager (OLI) observations to account for inter-annual variability. The SNOWARP product was produced for 2000-2018 for an area of Western Alberta (approximately 30,000 km(2)) and was calibrated against a network of time-lapse cameras and snow pillows. Results indicate the RMSE of the SNOWARP fractional product ranges from 31.3%-68.3%, while F score of the SNOWARP binary product ranges from 87.7% - 98.6% when compared to ground truth data. Capturing fractional snow cover at a fine spatial and temporal scale is important due to the spatial heterogeneity of snow cover, particularly in mountainous regions with implications for biodiversity assessment and monitoring. SNOWARP demonstrates a novel method to increasing the temporal resolution of Landsat-derived snow cover data, providing valuable insights on regional snow cover dynamics for use in a range of applications.

关键词： Snow cover Snow accumulation and ablation Landsat MODIS data fusion algorithm development Time-lapse photography Time series

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Snow cover mapped daily at 30 meters resolution using a fusion of multi-temporal MODIS NDSI data and Landsat surface reflectance

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CANADIAN JOURNAL OF REMOTE SENSING 2018年第5期44卷 413-434页

作者： Mityok, Zoltan K. Bolton, Douglas K. Coops, Nicholas C. Berman, Ethan E. Senger, Sue Univ British Columbia Dept Forest Resources Management Integrated Remote Sensing Studio 2424 Main Mall Vancouver BC Canada Windwalker Consulting Serv POB 436 Lillooet BC Canada

Snow fall and melt events are complex meteorological phenomena that help chart the effects of climate change and impact many critical environmental processes including hydrologic and biogeographic systems. Daily snow maps, derived from MODIS imagery, provide managers and researchers with vital snow cover information, but only at spatial scales of 500 m or more. Finer resolution time series maps, however, retain large temporal gaps, particularly during recurrent cloud cover. This paper's authors have developed the novel algorithm MODSAT-NDSI to harness the strengths of both coarse and finer spatial resolution imagery by fusing MODIS and Landsat normalized difference snow index (NDSI) data. Daily 30 m snow cover maps were thus generated for 2000 - 2017 with an overall accuracy of 90%, using 33 validation sites distributed throughout south-central British Columbia. Snow cover trends were analyzed across stratified elevation bands and land cover types, revealing that snow cover persists under lower elevation forests for an average of 23.5 d longer than in adjacent open areas during spring. We conclude that the MODSAT-NDSI approach captures temporal and spatial advantages of freely available snow cover datasets and can be modified to suit a variety of novel investigations relating to snow cover or other spectral indices.

关键词： Snow cover Snow accumulation and ablation Landsat MODIS data fusion algorithm development Time-lapse photography Time series

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Can We Teach algorithm development Skills? 12

Can We Teach Algorithm Development Skills?

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50th Annual Association-for-Computing-Machinery (ACM) Southeast Conference

作者： Yoo, Jungsoon Yoo, Sung Seo, Suk Dong, Zhijiang Pettey, Chrisila Middle Tennessee State Univ Dept Comp Sci Murfreesboro TN 37132 USA

ISBN: (纸本)9781450312035

Often when designing an educational tool, the focus is primarily on how well the tool helps the student learn a concept. However, always in educational research there is an underlying desire to determine what factors actually influence student learning. This is because an understanding of these factors can lead to the design of more effective tools/techniques. The focus of our research has been on developing a tool to help students learn algorithm design. The ability to design an algorithm for a given problem is one of the most important, and unfortunately one of the most difficult to accomplish, learning outcomes of computer science courses. It has previously been shown [13] that students who use AlgoTutor, a Web-based algorithm development tutor, are significantly more likely to think that algorithm design prior to coding is important and to have confidence in their own ability to design an algorithm. From follow up studies, we have found that students who have used AlgoTutor in introductory computer science classes are not only more confident in their ability to design an algorithm, but also more likely to design a correct algorithm than those who have not used AlgoTutor. Additionally, we show that the course management utility for the AlgoTutor system can be used to investigate questions about factors that influence student learning. As an example we investigate the question, "how much is too much help and how much is not enough help if a student is having difficulty solving a problem?"

关键词： algorithm development learning environment Web-based tutoring system

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Food flows between counties in the United States

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ENVIRONMENTAL RESEARCH LETTERS 2019年第8期14卷 084011-084011页

作者： Lin, Xiaowen Ruess, Paul J. Marston, Landon Konar, Megan Univ Illinois Dept Civil & Environm Engn Urbana IL 61801 USA Kansas State Univ Dept Civil & Environm Engn Manhattan KS 66506 USA

Food consumption and production are separated in space through flows of food along complex supply chains. These food supply chains are critical to our food security, making it important to evaluate them. However, detailed spatial information on food flows within countries is rare. The goal of this paper is to estimate food flows between all county pairs within the United States. To do this, we develop the Food Flow Model, a data-driven methodology to estimate spatially explicit food flows. The Food Flow Model integrates machine learning, network properties, production and consumption statistics, mass balance constraints, and linear programming. Specifically, we downscale empirical information on food flows between 132 Freight Analysis Framework locations (17 292 potential links) to the 3142 counties and county-equivalents of the United States (9869 022 potential links). Subnational food flow estimates can be used in future work to improve our understanding of vulnerabilities within a national food supply chain, determine critical infrastructures, and enable spatially detailed footprint assessments.

关键词： food flows networks algorithm development

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Exhaustive sampling of the fragment space associated to a molecule leading to the generation of conserved fragments

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CHEMICAL BIOLOGY & DRUG DESIGN 2018年第3期91卷 655-667页

作者： Heikamp, Kathrin Zuccotto, Fabio Kiczun, Michael Ray, Peter Gilbert, Ian H. Univ Dundee Drug Discovery Unit Div Biol Chem & Drug Discovery Sch Life Sci Dundee Scotland

The first step in hit optimization is the identification of the pharmacophore, which is normally achieved by deconstruction of the hit molecule to generate deletion analogues. In silico fragmentation approaches often focus on the generation of small fragments that do not describe properly the fragment space associated to the deletion analogues. We present significant modifications to the molecular fragmentation programme molBLOCKS, which allows the exhaustive sampling of the fragment space associated with a molecule to generate all possible molecular fragments. This generates larger fragments, by combining the smallest fragments. Additionally, it has been modified to deal with the problem of changing pharmacophoric properties through fragmentation, by highlighting bond cuts. The modified molBLOCKS programme was used on a set of drug compounds, where it generated more unique fragments than standard fragmentation approaches by increasing the number of fragments derived per compound. This fragment set was found to be more diverse than those generated by standard fragmentation programmes and was relevant to drug discovery as it contains the key fragments representing the pharmacophoric elements associated with ligand recognition. The use of dummy atoms to highlight bond cuts further increases the information content of fragments by visualizing their previous bonding pattern.

关键词： algorithm development chemical space analysis fragment based drug discovery molecular fragmentation

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EPypes: a framework for building event-driven data processing pipelines

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PEERJ COMPUTER SCIENCE 2019年第2期5卷 e176页

作者： Semeniuta, Oleksandr Falkman, Petter NTNU Norwegian Univ Sci & Technol Dept Mfg & Civil Engn Gjovik Norway Chalmers Univ Technol Dept Elect Engn Gothenburg Sweden

Many data processing systems are naturally modeled as pipelines, where data flows though a network of computational procedures. This representation is particularly suitable for computer vision algorithms, which in most cases possess complex logic and a big number of parameters to tune. In addition, online vision systems, such as those in the industrial automation context, have to communicate with other distributed nodes. When developing a vision system, one normally proceeds from ad hoc experimentation and prototyping to highly structured system integration. The early stages of this continuum are characterized with the challenges of developing a feasible algorithm, while the latter deal with composing the vision function with other components in a networked environment. In between, one strives to manage the complexity of the developed system, as well as to preserve existing knowledge. To tackle these challenges, this paper presents EPypes, an architecture and Python-based software framework for developing vision algorithms in a form of computational graphs and their integration with distributed systems based on publish-subscribe communication. EPypes facilitates flexibility of algorithm prototyping, as well as provides a structured approach to managing algorithm logic and exposing the developed pipelines as a part of online systems.

关键词： Computer vision Computational graph Publish-subscribe Robotics Python Pipeline Distributed systems algorithm development Event-driven systems Concurrency

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To the Problem of Adaptive Guaranteed Estimation

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IFAC-PapersOnLine 2018年第32期51卷 717-722页

作者： Khadanovich, Dina V. Shiryaev, Vladimir I. Chelyabinsk Russia Chelyabinsk Russia

The article deals with linear dynamical system state estimation problem under uncertainty when disturbance and measurement error statistics are unknown but the sets of their possible values are available. The approach to adaptive algorithm development of guaranteed estimation is proposed. The approach is based on the processing of innovation sequence values in the Kalman filter under conditions of a small number of available measurements. The Kalman filter implementation is performed for measurement data preprocessing the result of which is the mathematical model development and refining the estimates of unknown measurement errors. © 2018

关键词： Kalman filters Adaptive algorithms Adaptive filtering Adaptive filters Dynamical systems Error statistics Estimation Forecasting Linear control systems Mathematical models Measurement errors Uncertainty analysis algorithm development Estimation algorithm Estimation problem Guaranteed estimation Innovation sequence Linear dynamical systems Measurement data Measurement Noise

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Mapping remote rural settlements at 30 m spatial resolution using geospatial data-fusion

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REMOTE SENSING OF ENVIRONMENT 2019年 233卷 111386-000页

作者： Hoffman-Hall, Amanda Loboda, Tatiana V. Hall, Joanne V. Carroll, Mark L. Chen, Dong Univ Maryland Dept Geog Sci 2181 LeFrak Hall7251 Preinkert Dr College Pk MD 20742 USA NASAs Goddard Space Flight Ctr 8800 Greenbelt Rd Greenbelt MD 20771 USA

Accurate and timely population distribution maps are critical to addressing health epidemics, coordinating natural disaster response, tracking global changes for environmental conservation, confronting human rights issues, and more. Satellite imagery has opened numerous ways for mapping population distribution - previously unattainable without conducting a resource intensive census. While great advances have been made in urban population mapping, large gaps still exist for rural and remote populations which tend to be the most vulnerable to environmental, economic, and socio-political change. Moderate resolution remote sensing data, such as Landsat, has generally been viewed as insufficient for rural mapping given its coarseness relative to the size of a rural dwelling. This paper presents an approach for detecting small rural settlements within Ann Township of Rakhine State, a remote region of Myanmar with a highly mobile population, by combining Landsat data with publicly available auxiliary geospatial data. The key to the success of detecting small settlements at the Landsat resolution was the inclusion of multi-temporal auxiliary data sensitive to human activity patterns in the regions, such as distance to water, change in seasonal vegetation signals, and distance to a recent active fire. The use of active fire in this context is novel and provided a key metric that increased the accuracy of the resultant map. The final dataset has a classification accuracy of 86.5% on a per-pixel basis and 93.1% on a location identification basis. Numerous small settlements (on the order of 2-3 structures in some cases) not previously mapped by other datasets are identified, revealing that the population of Ann Township is far more dispersed and isolated than previously mapped. This study concludes that by incorporating regionally specific characteristics, moderate resolution remotely sensed data can be used to successfully map geographically marginalized communities so that se

关键词： Landsat Rural Population mapping Settlement Image classification algorithm development Myanmar Moderate resolution Place Land use

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More Than a Paper

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OPTICAL ENGINEERING 2019年第5期58卷 050101-050101页

作者： Eismann, Michael T.

Editor-in-Chief Mike Eismann writes about supplemental materials in scientific journals.

关键词： Optical engineering Computer programming Video algorithm development Computer programming languages Scientific research Analytics Data processing Process control Software development

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