Applications of Spatial Data Using Business Analytics Tools

This paper addresses the possibilities of using spatial data in business analytics tools, with emphasis on SAS software. Various kinds of map data sets containing spatial data are presented and discussed. Examples of map charts illustrating macroeconomic parameters demonstrate the application of spatial data for the creation of map charts in SAS Enterprise Guise. Extended features of map charts are being exemplified by producing charts via SAS programming procedures

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Monitoring and Detection of Hotspots using Satellite Images

Nowadays, the usage of optical remote sensing NOAA-AVHRR satellite data is getting familiar as it is known can save cost in order to capture a wide coverage of ground image. The captured images are meaningful after several processes done over it to produce hotspot detection. Developing a specific database to store information of Hotspots (LAC images) would make datamanagement and archiving purpose in more efficient and systematic way. Real-time data gathered are monitored countries such as Malaysia, Thailand, Singapore, Indonesia and Brunei within the region of NOAA Satellite coverage area. PostGIS, PostgreSQL, Mapserver and Autodesk MapGuide Studio software are to be studied as a guide to develop a system with simple database using object-relational database management system to store raster and vector images. This paper describes a solution for efficient handling of large raster image data sets in a standard object-relational database management system. By means of adequate indexing, retrieval techniques and multi resolution cell indexing (Quad-Tree) can be achieved using a standard DBMS, even for very large satellite images. Single image will be divided equally into 64 small squares (3 levels of image hierarchy - each level has 4 sub images of the higher image). Partial information of Daily Haze report (processed Hotspot on image map) produces by NREB can be viewed using web-based application. The final product of this project is a web-based application for displaying Hotspots on maps (combination of raster and vector images) with the ability to search record from database and functions to zoom in or zoom out the map. The objective of this paper is also to show the way satellite images and descriptive information are combined and amalgamated to form an Internet or Intranet application

Command and Control Systems for Search and Rescue Robots

The novel application of unmanned systems in the domain of humanitarian Search and Rescue (SAR) operations has created a need to develop specific multi-Robot Command and Control (RC2) systems. This societal application of robotics requires human-robot interfaces for controlling a large fleet of heterogeneous robots deployed in multiple domains of operation (ground, aerial and marine). This chapter provides an overview of the Command, Control and Intelligence (C2I) system developed within the scope of Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS). The life cycle of the system begins with a description of use cases and the deployment scenarios in collaboration with SAR teams as end-users. This is followed by an illustration of the system design and architecture, core technologies used in implementing the C2I, iterative integration phases with field deployments for evaluating and improving the system. The main subcomponents consist of a central Mission Planning and Coordination System (MPCS), field Robot Command and Control (RC2) subsystems with a portable force-feedback exoskeleton interface for robot arm tele-manipulation and field mobile devices. The distribution of these C2I subsystems with their communication links for unmanned SAR operations is described in detail. Field demonstrations of the C2I system with SAR personnel assisted by unmanned systems provide an outlook for implementing such systems into mainstream SAR operations in the future

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments

Практичний курс з перекладу термінології комп'ютерних систем з англійської на українську мову

Посібник побудовано таким чином, що кожний розділ містить у собі матеріал та вправи, в ході виконання яких студенти мають набути вказаних вище перекладацьких умінь і навичок, а саме: ознайомлення з текстами, що сприяють отриманню фонових знань (тексти і міни-тексти, що містять відповідну термінологію і опис якогось явища, наприклад, особливостей функціонування веб-сайтів); вправи для перевірки знання термінологічних еквівалентів, зокрема, переклад міні-текстів з англійської на українську і навпаки; аудіовправи, які закріплюють знання термінології і готують перекладача до усного перекладу у зазначеній галузі

Designing a training tool for imaging mental models

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network

Declarative Data Analytics: a Survey

The area of declarative data analytics explores the application of the declarative paradigm on data science and machine learning. It proposes declarative languages for expressing data analysis tasks and develops systems which optimize programs written in those languages. The execution engine can be either centralized or distributed, as the declarative paradigm advocates independence from particular physical implementations. The survey explores a wide range of declarative data analysis frameworks by examining both the programming model and the optimization techniques used, in order to provide conclusions on the current state of the art in the area and identify open challenges.Comment: 36 pages, 2 figure