100 research outputs found
Code: Version 2.0
Discusses the regulation of cyberspace via code, as well as possible trends to expect in this regulation. Additional topics discussed in this context include intellectual property, privacy, and free speech
Multistep-Ahead Neural-Network Predictors for Network Traffic Reduction in Distributed Interactive Applications
Predictive contract mechanisms such as dead reckoning are widely employed to support scalable
remote entity modeling in distributed interactive applications (DIAs). By employing a form of
controlled inconsistency, a reduction in network traffic is achieved. However, by relying on the
distribution of instantaneous derivative information, dead reckoning trades remote extrapolation
accuracy for low computational complexity and ease-of-implementation. In this article, we present
a novel extension of dead reckoning, termed neuro-reckoning, that seeks to replace the use of
instantaneous velocity information with predictive velocity information in order to improve the
accuracy of entity position extrapolation at remote hosts. Under our proposed neuro-reckoning
approach, each controlling host employs a bank of neural network predictors trained to estimate
future changes in entity velocity up to and including some maximum prediction horizon. The effect
of each estimated change in velocity on the current entity position is simulated to produce an
estimate for the likely position of the entity over some short time-span. Upon detecting an error
threshold violation, the controlling host transmits a predictive velocity vector that extrapolates
through the estimated position, as opposed to transmitting the instantaneous velocity vector. Such
an approach succeeds in reducing the spatial error associated with remote extrapolation of entity
state. Consequently, a further reduction in network traffic can be achieved. Simulation results
conducted using several human users in a highly interactive DIA indicate significant potential
for improved scalability when compared to the use of IEEE DIS standard dead reckoning. Our
proposed neuro-reckoning framework exhibits low computational resource overhead for real-time
use and can be seamlessly integrated into many existing dead reckoning mechanisms
Multistep-Ahead Neural-Network Predictors for Network Traffic Reduction in Distributed Interactive Applications
Predictive contract mechanisms such as dead reckoning are widely employed to support scalable
remote entity modeling in distributed interactive applications (DIAs). By employing a form of
controlled inconsistency, a reduction in network traffic is achieved. However, by relying on the
distribution of instantaneous derivative information, dead reckoning trades remote extrapolation
accuracy for low computational complexity and ease-of-implementation. In this article, we present
a novel extension of dead reckoning, termed neuro-reckoning, that seeks to replace the use of
instantaneous velocity information with predictive velocity information in order to improve the
accuracy of entity position extrapolation at remote hosts. Under our proposed neuro-reckoning
approach, each controlling host employs a bank of neural network predictors trained to estimate
future changes in entity velocity up to and including some maximum prediction horizon. The effect
of each estimated change in velocity on the current entity position is simulated to produce an
estimate for the likely position of the entity over some short time-span. Upon detecting an error
threshold violation, the controlling host transmits a predictive velocity vector that extrapolates
through the estimated position, as opposed to transmitting the instantaneous velocity vector. Such
an approach succeeds in reducing the spatial error associated with remote extrapolation of entity
state. Consequently, a further reduction in network traffic can be achieved. Simulation results
conducted using several human users in a highly interactive DIA indicate significant potential
for improved scalability when compared to the use of IEEE DIS standard dead reckoning. Our
proposed neuro-reckoning framework exhibits low computational resource overhead for real-time
use and can be seamlessly integrated into many existing dead reckoning mechanisms
Race, Religion and the City: Twitter Word Frequency Patterns Reveal Dominant Demographic Dimensions in the United States
Recently, numerous approaches have emerged in the social sciences to exploit
the opportunities made possible by the vast amounts of data generated by online
social networks (OSNs). Having access to information about users on such a
scale opens up a range of possibilities, all without the limitations associated
with often slow and expensive paper-based polls. A question that remains to be
satisfactorily addressed, however, is how demography is represented in the OSN
content? Here, we study language use in the US using a corpus of text compiled
from over half a billion geo-tagged messages from the online microblogging
platform Twitter. Our intention is to reveal the most important spatial
patterns in language use in an unsupervised manner and relate them to
demographics. Our approach is based on Latent Semantic Analysis (LSA) augmented
with the Robust Principal Component Analysis (RPCA) methodology. We find
spatially correlated patterns that can be interpreted based on the words
associated with them. The main language features can be related to slang use,
urbanization, travel, religion and ethnicity, the patterns of which are shown
to correlate plausibly with traditional census data. Our findings thus validate
the concept of demography being represented in OSN language use and show that
the traits observed are inherently present in the word frequencies without any
previous assumptions about the dataset. Thus, they could form the basis of
further research focusing on the evaluation of demographic data estimation from
other big data sources, or on the dynamical processes that result in the
patterns found here
Semantic Selection of Internet Sources through SWRL Enabled OWL Ontologies
This research examines the problem of Information Overload (IO) and give an overview of various attempts to resolve it. Furthermore, argue that instead of fighting IO, it is advisable to start learning how to live with it. It is unlikely that in modern information age, where users are producer and consumer of information, the amount of data and information generated would decrease. Furthermore, when managing IO, users are confined to the algorithms and policies of commercial Search Engines and Recommender Systems (RSs), which create results that also add to IO. this research calls to initiate a change in thinking: this by giving greater power to users when addressing the relevance and accuracy of internet searches, which helps in IO. However powerful search engines are, they do not process enough semantics in the moment when search queries are formulated. This research proposes a semantic selection of internet sources, through SWRL enabled OWL ontologies. the research focuses on SWT and its Stack because they (a)secure the semantic interpretation of the environments where internet searches take place and (b) guarantee reasoning that results in the selection of suitable internet sources in a particular moment of internet searches. Therefore, it is important to model the behaviour of users through OWL concepts and reason upon them in order to address IO when searching the internet. Thus, user behaviour is itemized through user preferences, perceptions and expectations from internet
searches. The proposed approach in this research is a Software Engineering (SE) solution which provides computations based on the semantics of the environment stored in the ontological model
A Social Dimension for Digital Architectural Practice
Merged with duplicate record 10026.1/1296 on 14.03.2017 by CS (TIS)This thesis proceeds from an analysis of practice and critical commentary to claim that the
opportunities presented to some architectural practices by the advent of ubiquitous digital
technology have not been properly exploited. The missed opportunities, it claims, can be
attributed largely to the retention of a model of time and spaces as discrete design
parameters, which is inappropriate in the context of the widening awareness of social
interconnectedness that digital technology has also facilitated. As a remedy, the thesis
shows that some social considerations essential to good architecture - which could have
been more fully integrated in practice and theory more than a decade ago - can now be
usefully revisited through a systematic reflection on an emerging use of web technologies
that support social navigation. The thesis argues through its text and a number of practical
projects that the increasing confidence and sophistication of interdisciplinary studies in
geography, most notably in human geography, combined with the technological
opportunities of social navigation, provide a useful model of time and space as a unified
design parameter. In so doing the thesis suggests new possibilities for architectural
practices involving social interaction.
Through a literature review of the introduction and development of digital technologies to
architectural practice, the thesis identifies the inappropriate persistence of a number of
overarching concepts informing architectural practice. In a review of the emergence and
growth of 'human geography' it elaborates on the concept of the social production of
space, which it relates to an analysis of emerging social navigation technologies. In so
doing the thesis prepares the way for an integration of socially aware architecture with the
opportunities offered by social computing.
To substantiate its claim the thesis includes a number of practical public projects that have
been specifically designed to extend and amplify certain concepts, along with a large-scale
design project and systematic analysis which is intended to illustrate the theoretical claim
and provide a model for further practical exploitation
Supporting exploratory browsing with visualization of social interaction history
This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection.
This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection.
To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool
Boundary Images
How are images made, and how should we understand the capacities of digital images? This book investigates images as well as the technologies that host them. Its three chapters discuss the boundaries that images cross and blur between humans, machines, and nature and the ways in which images are political, material, and visual. Exploring these boundaries of images, this book places itself at the limits of the visual and beyond what can be seen, understanding these as starting points for the production of new and radically different ways of knowing about the world and its becomings
Collaborative Workspaces within Distributed Virtual Environments
In warfare, be it a training simulation or actual combat, a commander\u27s time is one of the most valuable and fleeting resources of a military unit. Thus, it is natural for a unit to have a plethora of personnel to analyze and filter information to the decision-maker. This dynamic exchange of ideas between analyst and commander is currently not available within the distributed interactive simulation (DIS) community. This lack of exchange limits the usefulness of the DIS experience to the commander and his troops. This thesis addresses the commander\u27s isolation problem through the integration of a collaborative workspace within AFIT\u27s Synthetic BattleBridge (SBB) as a technique to improve situational awareness. The SBB\u27s Collaborative Workspace enhances battlespace awareness through CSCW (computer supported cooperative work) enabling communication technologies. The SBB\u27s Collaborative Workspace allows the user to interact with other SBB users through the transmission and reception of public bulletins, private email, real-time chat sessions, shared viewpoints, shared video, and shared annotations to the virtual environment. Collaborative communication between SBB occurs through the use of standard and experimental DIS-compliant protocol data units. The SBB\u27s Collaborative Workspace gives the battlespace commander the widest range of communication options available within a DIS virtual environment today
An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications
Distributed Interactive Applications (DIAs) enable geographically dispersed users
to interact with each other in a virtual environment. A key factor to the success
of a DIA is the maintenance of a consistent view of the shared virtual world for
all the participants. However, maintaining consistent states in DIAs is difficult
under real networks. State changes communicated by messages over such networks
suffer latency leading to inconsistency across the application. Predictive Contract
Mechanisms (PCMs) combat this problem through reducing the number of messages
transmitted in return for perceptually tolerable inconsistency. This thesis examines
the operation of PCMs using concepts and methods derived from information theory.
This information theory perspective results in a novel information model of PCMs
that quantifies and analyzes the efficiency of such methods in communicating the
reduced state information, and a new adaptive multiple-model-based framework for
improving consistency in DIAs.
The first part of this thesis introduces information measurements of user behavior
in DIAs and formalizes the information model for PCM operation. In presenting the
information model, the statistical dependence in the entity state, which makes using
extrapolation models to predict future user behavior possible, is evaluated. The
efficiency of a PCM to exploit such predictability to reduce the amount of network
resources required to maintain consistency is also investigated. It is demonstrated
that from the information theory perspective, PCMs can be interpreted as a form
of information reduction and compression.
The second part of this thesis proposes an Information-Based Dynamic Extrapolation
Model for dynamically selecting between extrapolation algorithms based on
information evaluation and inferred network conditions. This model adapts PCM
configurations to both user behavior and network conditions, and makes the most
information-efficient use of the available network resources. In doing so, it improves
PCM performance and consistency in DIAs
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