acm - an acm publication

2008 - February

  • Hermeneutics facing the
    The origin of this paper goes back to the International Conference "Phenomenology and Technology" held at the Philosophy and Technology Studies Center, Polytechnic University (New York), October 2- 4, 1986 which was organized by Wolfgang Schirmacher and Carl Mitcham. After thirteen years, obviously, things have changed and I have done some further work too. My book Hermeneutik der Fachinformation was published in 1986 and since then I have written some articles on this subject as well as another book Leben im Informationszeitalter (Capurro 1995). Some of the articles as well as a list of publications can be found in my homepage (http://www.capurro.de). The present text is an enriched version of the original one. I have added some later insights without changing the basic ideas which I still think are valuable and can also be of help when reflecting, for instance, about the nature of communicating and searching for information in the Internet.
  • ERP system replacement criteria

    An ERP system is our information backbone and reaches into all areas of our business and value-chain. Replacing it can open unlimited business opportunities. The cornerstone of this effort is finding the right partner and specialist. Our long-term business strategy will form the basis of the criteria for our selection of an ERP system replacement. Our ERP provider must be part of our vision. It is the duty of a software provider to help us to get there by doing their part to make sure our next system will be our last ERP system replacement. Some of the criteria that allow us to identify and select the solution that will meet these expectations.

  • Collective intelligence: include the disabled for success
    Are you looking for new ideas to leverage your IT to allow your workforce to collectively be more efficient at solving complex problems? Want to transform your corporation so that it can reach new heights?
  • Whatever happened to cybernetics?
    Has the discipline of cybernetics been unable to recognize and respond to appropriate "midcourse corrections" and in the process had its destiny imposed by external "turning points"? (A mid-course correction is an endogenously determined action as in the classical "sense-processact" sequence, whereas a turning point is simply a reaction to that which is exogenously imposed; i.e., "being overcome by events."
  • Renovation of minimum spanning tree algorithms of weighted graph

    In this paper we describe and explain the Minimum Spanning Tree (MST) generation algorithms of a weighted graph with renovated idea. Here, we used a new cycle testing algorithm for testing cycles, if required, in generation of Minimum Spanning Tree. The reason behind this is to optimize the execution time for cycle testing. Also, we describe some Minimum Spanning Tree algorithms for weighted graph with a renovated idea. We applied here new concept for explanation of minimum Spanning tree with better time complexity.

  • Understanding software testing concepts
    Software testing concepts have been briefly described in this article. Readers would find it easier to understand fundamental concepts of software testing by going through a concept map thereof. Software testing is itself a discipline as well as a process. Software development is nothing but a process of coding functionality in order to meet the defined end-user requirements. We can think of software testing as an iterative process, which consists of Tests Designing, Tests Execution, Problems Identifying and Problem Fixing, for validating functionality and as well as for attempting the software break. Software testing aims to find problems and to fix them for improving software quality. Software testing may represent 40% of a software development budget. Basic methods of performing software testing include Manual Testing and Automated Testing. Manual software testing is the process of manually testing software (having the possible forms for example, user interfaces navigation, information submission, or attempt to hack the software or database etc.), carried out by an individual or individuals. Manual software testing is labor-intensive and slow. On the other hand, automated software testing is a process of creating test scripts, which can be run then automatically, repetitively, and through a number of iterations. Automated software testing helps us to minimize the variability of results, speed up the testing process, increase test coverage (that is, the number of different things tested), and ultimately provide greater confidence in the quality of the software being tested.
  • End laptop serfdom
    Time to end personal technology serfdom! I hate company-specific technology standards, at least those that specify technology in terms other than file formats, access protocols and application programming interfaces. In most companies I am in touch with, employees get a laptop and a cell phone and are required to use a set of standard capabilities of some sort. More often than not these are unnecessarily complicated, old-fashioned, expensive and singularly uninspiring. This is often for good reasons: The IT department wants to make things manageable for themselves and for the organization, and employees need to have a standard frame of reference and a compatible set of tools for work. The helpdesk can figure out which keys to press and the employees can see the same screens. Well and good, but the users are beginning to rebel at the lack of options especially those they have on their own or former computers.

2018 Symposia

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Ubiquity Symposium: Big Data

Table of Contents

  1. Big Data, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
  2. Big Data and the Attention Economy by Bernardo A. Huberman
  3. Big Data for Social Science Research by Mark Birkin
  4. Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
  5. High Performance Synthetic Information Environments: An integrating architecture in the age of pervasive data and computing By Christopher L. Barrett, Jeffery Johnson, and Madhav Marathe
  6. Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk
  7. When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic
  8. Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic
  9. Big Data: Business, technology, education, and science by Jeffrey Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, and Marco Amador
  10. Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic