71,163 research outputs found
Trademark Searching Tools and Strategies: Questions for the New Millennium
The intent of this discussion is to raise questions about trademark searching which will be discussed in future issues of IDEA. I will lead you through the questions raised by my journey through primarily legal literature in treatises and periodicals on the Lexis and Westlaw platforms
A Factory-based Approach to Support E-commerce Agent Fabrication
With the development of Internet computing and software agent technologies, agent-based e-commerce is emerging. How to create agents for e-commerce applications has become an important issue along the way to success. We propose a factory-based approach to support agent fabrication in e-commerce and elaborate a design based on the SAFER (Secure Agent Fabrication, Evolution & Roaming) framework. The details of agent fabrication, modular agent structure, agent life cycle, as well as advantages of agent fabrication are presented. Product-brokering agent is employed as a practical agent type to demonstrate our design and Java-based implementation
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
Doc2RDFa: Semantic Annotation for Web Documents
Ever since its conception, the amount of data published on the worldwide
web has been rapidly growing to the point where it has become an important
source of both general and domain specific information. However, the majority
of documents published online are not machine readable by default. Many researchers
believe that the answer to this problem is to semantically annotate these
documents, and thereby contribute to the linked "Web of Data". Yet, the process
of annotating web documents remains an open challenge. While some efforts towards
simplifying this process have been made in the recent years, there is still a
lack of semantic content creation tools that integrate well with information worker
toolsets. Towards this end, we introduce Doc2RDFa, an HTML rich text processor
with the ability to automatically and manually annotate domain-specific Content
BEAT: An Open-Source Web-Based Open-Science Platform
With the increased interest in computational sciences, machine learning (ML),
pattern recognition (PR) and big data, governmental agencies, academia and
manufacturers are overwhelmed by the constant influx of new algorithms and
techniques promising improved performance, generalization and robustness.
Sadly, result reproducibility is often an overlooked feature accompanying
original research publications, competitions and benchmark evaluations. The
main reasons behind such a gap arise from natural complications in research and
development in this area: the distribution of data may be a sensitive issue;
software frameworks are difficult to install and maintain; Test protocols may
involve a potentially large set of intricate steps which are difficult to
handle. Given the raising complexity of research challenges and the constant
increase in data volume, the conditions for achieving reproducible research in
the domain are also increasingly difficult to meet.
To bridge this gap, we built an open platform for research in computational
sciences related to pattern recognition and machine learning, to help on the
development, reproducibility and certification of results obtained in the
field. By making use of such a system, academic, governmental or industrial
organizations enable users to easily and socially develop processing
toolchains, re-use data, algorithms, workflows and compare results from
distinct algorithms and/or parameterizations with minimal effort. This article
presents such a platform and discusses some of its key features, uses and
limitations. We overview a currently operational prototype and provide design
insights.Comment: References to papers published on the platform incorporate
Assessing database and network threats in traditional and cloud computing
Cloud Computing is currently one of the most widely-spoken terms in IT. While it offers a range of technological and financial benefits, its wide acceptance by organizations is not yet wide spread. Security concerns are a main reason for this and this paper studies the data and network threats posed in both traditional and cloud paradigms in an effort to assert in which areas cloud computing addresses security issues and where it does introduce new ones. This evaluation is based on Microsoft’s STRIDE threat model and discusses the stakeholders, the impact and recommendations for tackling each threat
SANTO: Social Aerial NavigaTion in Outdoors
In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones
Impliance: A Next Generation Information Management Appliance
ably successful in building a large market and adapting to the changes of the
last three decades, its impact on the broader market of information management
is surprisingly limited. If we were to design an information management system
from scratch, based upon today's requirements and hardware capabilities, would
it look anything like today's database systems?" In this paper, we introduce
Impliance, a next-generation information management system consisting of
hardware and software components integrated to form an easy-to-administer
appliance that can store, retrieve, and analyze all types of structured,
semi-structured, and unstructured information. We first summarize the trends
that will shape information management for the foreseeable future. Those trends
imply three major requirements for Impliance: (1) to be able to store, manage,
and uniformly query all data, not just structured records; (2) to be able to
scale out as the volume of this data grows; and (3) to be simple and robust in
operation. We then describe four key ideas that are uniquely combined in
Impliance to address these requirements, namely the ideas of: (a) integrating
software and off-the-shelf hardware into a generic information appliance; (b)
automatically discovering, organizing, and managing all data - unstructured as
well as structured - in a uniform way; (c) achieving scale-out by exploiting
simple, massive parallel processing, and (d) virtualizing compute and storage
resources to unify, simplify, and streamline the management of Impliance.
Impliance is an ambitious, long-term effort to define simpler, more robust, and
more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement
(http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute,
display, and perform the work, make derivative works and make commercial use
of the work, but, you must attribute the work to the author and CIDR 2007.
3rd Biennial Conference on Innovative Data Systems Research (CIDR) January
710, 2007, Asilomar, California, US
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