Sharing analysis of arrays, collections, and recursive structures

Precise modeling of the program heap is fundamental for understanding the behavior of a program, and is thus of signiflcant interest for many optimization applications. One of the fundamental properties of the heap that can be used in a range of optimization techniques is the sharing relationships between the elements in an array or collection. If an analysis can determine that the memory locations pointed to by different entries of an array (or collection) are disjoint, then in many cases loops that traverse the array can be vectorized or transformed into a thread-parallel versión. This paper introduces several novel sharing properties over the concrete heap and corresponding abstractions to represent them. In conjunction with an existing shape analysis technique, these abstractions allow us to precisely resolve the sharing relations in a wide range of heap structures (arrays, collections, recursive data structures, composite heap structures) in a computationally efflcient manner. The effectiveness of the approach is evaluated on a set of challenge problems from the JOlden and SPECjvm98 suites. Sharing information obtained from the analysis is used to achieve substantial thread-level parallel speedups.

Analysis of neuronal functions based on feynman diagrams

A method to study some neuronal functions, based on the use of the Feynman diagrams, employed in many-body theory, is reported. An equation obtained from the neuron cable theory is the basis for the method. The Green's function for this equation is obtained under some simple boundary conditions. An excitatory signal, with different conditions concerning high and pulse duration, is employed as input signal. Different responses have been obtained

Minimal template size for Iris-Recognition

A method to achieve improvement in template size for an iris-recognition system is reported. To achieve this result, the biological characteristics of the human iris have been studied. Processing has been performed by image processing techniques, isolating the iris and enhancing the area of study, after which multi resolution analysis is made. Reduction of the pattern obtained has been obtained via statistical study.

Leveraging Semantics to Improve Reproducibility in Scientific Workflows

Reproducibility of published results is a cornerstone in scientific publishing and progress. Therefore, the scientific community has been encouraging authors and editors to publish their contributions in a verifiable and understandable way. Efforts such as the Reproducibility Initiative [1], or the Reproducibility Projects on Biology [2] and Psychology [3] domains, have been defining standards and patterns to assess whether an experimental result is reproducible.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Map of General Sherman's March : Georgia, South Carolina, and North Carolina, 1865 (Raster Image)

This layer is a georeferenced raster image of the historic paper map: Map showing route of marches of the army of Genl. W.T. Sherman, from Atlanta, Ga. to Goldsboro, N.C. : to accompany the report of operations from Savannah, Ga. to Goldsboro, N.C., prepared by order of the Secretary of War for the officers of the U.S. Army under the command of Maj. Gen. W.T. Sherman. It was published by the Engineer Bureau, War Dept. in 1865. Scale [ca. 1:1,950,000]. Shows Sherman's March through the Carolinas covering South Carolina and portions of North Carolina, Georgia, and Tennessee. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Universal Transverse Mercator projection (WGS 1984 UTM Zone 17N). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This map shows features such as roads, railroads, cities and towns, drainage, and more. Relief shown by hachures. The routes of the 14th, 15th, 17th, and 20th corps and the cavalry are indicated by colors and symbols. This layer is part of a selection of digitally scanned and georeferenced historic maps of the Civil War from the Harvard Map Collection. Many items from this selection are from a collection of maps deposited by the Military Order of the Loyal Legion of the United States Commandery of the State of Massachusetts (MOLLUS) in the Harvard Map Collection in 1938. These maps typically portray both natural and manmade features, in particular showing places of military importance. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.

Burnt district of Boston, Massachusetts, 1873 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Plan of burnt district (by fire of Nov. 9th and 10th, 1872) : showing street improvements as adopted by Board of Street Commissioners and City Council, 1873, Thos. W. Davis, city surveyor ; presented by the Boston Safe Deposit and Trust Co. It was published in 1876. Shows street improvements, property lots, lot ownership, and square footage of lots affected by the fire of 1872. Covers area bounded by Washington St. to Oliver St., State St. to Summer St. and Atlantic Ave., Boston, Massachusetts. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This layer is part of a selection of digitally scanned and georeferenced historic maps of Massachusetts from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates (1755-1922), scales, and purposes. The digitized selection includes maps of: the state, Massachusetts counties, town surveys, coastal features, real property, parks, cemeteries, railroads, roads, public works projects, etc.

Areawide environmental assessment on the development of a NEPA compliance strategy for new source coal mining activity in the western Kentucky coal field /

Mode of access: Internet.

Immunization of adults : a call to action.

Mode of access: Internet.

Total nonagricultural employment in the South, 1939-1955.

Mode of access: Internet.

Pictorial keys to arthropods, reptiles, birds and mammals of public health significance.

Mode of access: Internet.

An Evaluation handbook for health education programs in alcohol and substance abuse /

Mode of access: Internet.

Fluoridated drinking water : proficiency testing, September 1984.

Mode of access: Internet.

Techniques for needs assessment : state experiences and suggested approaches in response to Title XX of the Social security act /

Companion vol. to the author's State experiences in social services planning.