User-Relative Names for Globally Connected Personal Devices

Nontechnical users who own increasingly ubiquitous network-enabled personal devices such as laptops, digital cameras, and smart phones need a simple, intuitive, and secure way to share information and services between their devices. User Information Architecture, or UIA, is a novel naming and peer-to-peer connectivity architecture addressing this need. Users assign UIA names by "introducing" devices to each other on a common local-area network, but these names remain securely bound to their target as devices migrate. Multiple devices owned by the same user, once introduced, automatically merge their namespaces to form a distributed "personal cluster" that the owner can access or modify from any of his devices. Instead of requiring users to allocate globally unique names from a central authority, UIA enables users to assign their own "user-relative" names both to their own devices and to other users. With UIA, for example, Alice can always access her iPod from any of her own personal devices at any location via the name "ipod", and her friend Bob can access her iPod via a relative name like "ipod.Alice".Comment: 7 pages, 1 figure, 1 tabl

A Drone by Any Other Name: Purposes, End-User Trustworthiness, and Framing, but not Terminology, Affect Public Support for Drones

Projections indicate that, as an industry, unmanned aerial vehicles (UAVs, commonly known as drones) could bring more than 100 000 jobs and $80 billion in economic growth to the U.S. by 2025 [1]. However, these promising projections do not account for how various publics may perceive such technologies. Understanding public perceptions is important because the attitudes of different groups can have large effects on the trajectory of a technology, strongly facilitating or hindering technology acceptance and uptake [2]. To advance understanding of U.S. public perceptions of UAV technologies, we conducted a nationwide survey of a convenience sample of 877 Americans recruited from Amazon’s pool of Mechanical Turk (MTurk) workers. In our surveys, we used short scenarios to experimentally vary UAV characteristics, the end-users of the technology, and certain communication factors (terminology and framing). This allowed us to investigate the impacts of these factors alone and in combination. In addition, given the conflicts that sometimes arise around scientific findings and technologies (e.g., climate change, vaccines, [3], [4]), we also gave explicit attention to whether and how public support for UAVs varied by self-reported political ideology, issue attitudes, and perceptions of end-user trustworthiness. Finally, because UAVs for civilian purposes represented relatively new technologies at the time of the first survey, we examined whether public opinion is changing over time, as more people become aware of UAVs. We thus administered the same survey twice, separated by one year, in the fall of 2014 and 2015. The results of our experimental manipulations revealed a surprising lack of impact of terminology and UAV autonomy, a small impact of message framing and UAV end-user, and a relatively large impact of UAV purpose. We did not find that public attitudes changed much over the year between samples, and perceptions of end-user trustworthiness were strong predictors of public support. Still, our regression models only accounted for about 40% of the variance in public support, suggesting that additional variables should be studied in future work to gain a more complete understanding of public support for UAVs. We also found evidence of a small amount of political polarization of public opinion related to who was using the UAVs for what purpose, and this polarization appeared to be changing over time. Taken together, our results — which may be especially useful to UAV designers, marketers, and policy makers — suggest there is a need to establish that the UAVs are used for valued purposes and by users that publics find to be trustworthy. However, public judgments might be significantly impacted by personal or local ideologies rather than national priorities. In the next section, we describe in more detail prior research on public support for UAVs, and how we formulated our research questions and hypotheses. We then describe our methods, results, and findings in greater detail

MixtureTree Annotator: A Program for Automatic Colorization and Visual Annotation of MixtureTree

abstract: The MixtureTree Annotator, written in JAVA, allows the user to automatically color any phylogenetic tree in Newick format generated from any phylogeny reconstruction program and output the Nexus file. By providing the ability to automatically color the tree by sequence name, the MixtureTree Annotator provides a unique advantage over any other programs which perform a similar function. In addition, the MixtureTree Annotator is the only package that can efficiently annotate the output produced by MixtureTree with mutation information and coalescent time information. In order to visualize the resulting output file, a modified version of FigTree is used. Certain popular methods, which lack good built-in visualization tools, for example, MEGA, Mesquite, PHY-FI, TreeView, treeGraph and Geneious, may give results with human errors due to either manually adding colors to each node or with other limitations, for example only using color based on a number, such as branch length, or by taxonomy. In addition to allowing the user to automatically color any given Newick tree by sequence name, the MixtureTree Annotator is the only method that allows the user to automatically annotate the resulting tree created by the MixtureTree program. The MixtureTree Annotator is fast and easy-to-use, while still allowing the user full control over the coloring and annotating process.The article is published at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.011889

A-Lister: a tool for analysis of differentially expressed omics entities across multiple pairwise comparisons.

BackgroundResearchers commonly analyze lists of differentially expressed entities (DEEs), such as differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and differentially methylated positions/regions (DMPs/DMRs), across multiple pairwise comparisons. Large biological studies can involve multiple conditions, tissues, and timepoints that result in dozens of pairwise comparisons. Manually filtering and comparing lists of DEEs across multiple pairwise comparisons, typically done by writing custom code, is a cumbersome task that can be streamlined and standardized.ResultsA-Lister is a lightweight command line and graphical user interface tool written in Python. It can be executed in a differential expression mode or generic name list mode. In differential expression mode, A-Lister accepts as input delimited text files that are output by differential expression tools such as DESeq2, edgeR, Cuffdiff, and limma. To allow for the most flexibility in input ID types, to avoid database installation requirements, and to allow for secure offline use, A-Lister does not validate or impose restrictions on entity ID names. Users can specify thresholds to filter the input file(s) by column(s) such as p-value, q-value, and fold change. Additionally, users can filter the pairwise comparisons within the input files by fold change direction (sign). Queries composed of intersection, fuzzy intersection, difference, and union set operations can also be performed on any number of pairwise comparisons. Thus, the user can filter and compare any number of pairwise comparisons within a single A-Lister differential expression command. In generic name list mode, A-Lister accepts delimited text files containing lists of names as input. Queries composed of intersection, fuzzy intersection, difference, and union set operations can then be performed across these lists of names.ConclusionsA-Lister is a flexible tool that enables the user to rapidly narrow down large lists of DEEs to a small number of most significant entities. These entities can then be further analyzed using visualization, pathway analysis, and other bioinformatics tools

Online visualization of bibliography Using Visualization Techniques

Visualization is a concept where we can represent some raw data in the form of graphs, images, charts, etc. which will be very helpful for the end-user to correlate and be able to understand the relationships between the data elements in a single screen. Representing the bibliographic information of the computer science journals and proceedings using Visualization technique would help user choose a particular author and navigate through the hierarchy and find out what papers the author has published, the keywords of the papers, what papers cite them, the co-authors along with the main author, and how many papers are published by the author selected by the user and so on in a single page. These information is right now present in a scattered manner and the user has to search on websites like Google Scholar [1], Cite Seer [2] to get these bibliographic records. By the use of visualization techniques, all the information can be accessed on a single page by having a graph like points on the page, where the user can search for a particular author and the author and its co-authors are represented in the form of points. The goal of this project is to enhance current bibliography web services with an intuitive interactive visualization interface and to improve user understanding and conceptualization. In this project, we develop a simple web-interface which will take a search query from the user and find the related information like author\u27s name, the co-authors, number of papers published by him, related keywords, citations referred etc. The project uses the bibliographic records which are available as XML files from the Citeseer database[2], extracts the data into the database and then queries the database for the results using a web service. The data which is extracted is then presented visually to allow the user to conceptualize the results in a better way and help him/her find the articles of interest with utmost ease. In addition the user can interactively navigate the visual results to get more information about any of the article or the author displayed. So here we present both paper centric view and author centric view to the user by representing data in terms of graphs. The nodes in the graphs obtained for paper centric views and author centric views are color coded based on the paper’s weight parameter ( popularity of the paper ). For the paper centric view, the papers which are referring other papers are represented by providing a directed arrow from referred paper to referenced paper. Overall the idea here was to represent this related data in the form of a tree, so that the user can correlate all the data and get the relationships between them

Food Phone Application

This project is about implementing a food menu application for users to search and upload food information by using a mobile phone. People sometimes may just know what food they wish to eat instead of the restaurants\u27 name. Without knowing any restaurants\u27 names, our food application\u27s search only requires the name of the dish (e.g., hamburger, spaghetti, etc) in order to get the list of restaurants that serve these items and their corresponding information (e.g., location, hours, phone number, item\u27s price, etc.). An advantage of using my food application is the system not only includes Google Map, but any information other users have inputted. When a user wants to input a food item, one can either upload the item\u27s picture or a template picture to the server and input the rating and comments about the specific food item. With the rating option, my project calculates a cumulative rating result based around the original and other user\u27s input. There is also the option of having the users input a zip code to better identify where to find the food. Based on the phone\u27s capability, the system also needs to figure out the physical phone location. This requires the phone to receive the GPS signal. As a result, users can search/upload the local restaurants\u27 food without inputting the current location

Android based Maximum Discount Finder

Nowadays online shopping is rising day by day. We have thirty plus e-commerce website for online shopping. It is very easy to buy a product online, it save our time to go to market and buy it. Finding discount on various product on e-commerce website are getting quite complicated .because when we search for discount on particular product that time we just refer only two or four website which are used previously or suggested by other. But we don’t know the other e-commerce website which is also give better discount on product. So we are developing android application for finding discount on various e-commerce websites. It helps user to get maximum discount on the product. This application includes some features such as we can search any product by name or category. Then it show best of discount on that product available and also provides the link of respective website. On simply clicking on that link, application fetches that link to the user. So user can directly check specification of the product and buy that product. We have just made it easier for user to find discount

The Ciao clp(FD) library. A modular CLP extension for Prolog

We present a new free library for Constraint Logic Programming over Finite Domains, included with the Ciao Prolog system. The library is entirely written in Prolog, leveraging on Ciao's module system and code transformation capabilities in order to achieve a highly modular design without compromising performance. We describe the interface, implementation, and design rationale of each modular component. The library meets several design goals: a high level of modularity, allowing the individual components to be replaced by different versions; highefficiency, being competitive with other TT> implementations; a glass-box approach, so the user can specify new constraints at different levels; and a Prolog implementation, in order to ease the integration with Ciao's code analysis components. The core is built upon two small libraries which implement integer ranges and closures. On top of that, a finite domain variable datatype is defined, taking care of constraint reexecution depending on range changes. These three libraries form what we call the TT> kernel of the library. This TT> kernel is used in turn to implement several higher-level finite domain constraints, specified using indexicals. Together with a labeling module this layer forms what we name the TT> solver. A final level integrates the CLP (J7©) paradigm with our TT> solver. This is achieved using attributed variables and a compiler from the CLP (J7©) language to the set of constraints provided by the solver. It should be noted that the user of the library is encouraged to work in any of those levels as seen convenient: from writing a new range module to enriching the set of TT> constraints by writing new indexicals