94,819 research outputs found
Vision systems with the human in the loop
The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed
Parallel Deferred Update Replication
Deferred update replication (DUR) is an established approach to implementing
highly efficient and available storage. While the throughput of read-only
transactions scales linearly with the number of deployed replicas in DUR, the
throughput of update transactions experiences limited improvements as replicas
are added. This paper presents Parallel Deferred Update Replication (P-DUR), a
variation of classical DUR that scales both read-only and update transactions
with the number of cores available in a replica. In addition to introducing the
new approach, we describe its full implementation and compare its performance
to classical DUR and to Berkeley DB, a well-known standalone database
First experiences with Personal Networks as an enabling platform for service providers
By developing demonstrators and performing small-scale user trials, we found various opportunities and pitfalls for deploying personal networks (PNs) on a commercial basis. The demonstrators were created using as many as possible legacy devices and proven technologies. They deal with applications in the health sector, home services, tourism, and the transportation sector. This paper describes the various architectures and our experiences with the end users and the technology. We conclude that context awareness, service discovery, and content management are very important in PNs and that a personal network provider role is necessary to realize these functions under the assumptions we made. The PNPay Travel demonstrator suggests that PN service platforms provide an opportunity to develop true trans-sector services
Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments
The increased penetration of uncertain and variable renewable energy presents
various resource and operational electric grid challenges. Micro-level
(household and small commercial) demand-side grid flexibility could be a
cost-effective strategy to integrate high penetrations of wind and solar
energy, but literature and field deployments exploring the necessary
information and communication technologies (ICTs) are scant. This paper
presents an exploratory framework for enabling information driven grid
flexibility through the Internet of Things (IoT), and a proof-of-concept
wireless sensor gateway (FlexBox) to collect the necessary parameters for
adequately monitoring and actuating the micro-level demand-side. In the summer
of 2015, thirty sensor gateways were deployed in the city of Managua
(Nicaragua) to develop a baseline for a near future small-scale demand response
pilot implementation. FlexBox field data has begun shedding light on
relationships between ambient temperature and load energy consumption, load and
building envelope energy efficiency challenges, latency communication network
challenges, and opportunities to engage existing demand-side user behavioral
patterns. Information driven grid flexibility strategies present great
opportunity to develop new technologies, system architectures, and
implementation approaches that can easily scale across regions, incomes, and
levels of development
An Architecture for Integrated Intelligence in Urban Management using Cloud Computing
With the emergence of new methodologies and technologies it has now become
possible to manage large amounts of environmental sensing data and apply new
integrated computing models to acquire information intelligence. This paper
advocates the application of cloud capacity to support the information,
communication and decision making needs of a wide variety of stakeholders in
the complex business of the management of urban and regional development. The
complexity lies in the interactions and impacts embodied in the concept of the
urban-ecosystem at various governance levels. This highlights the need for more
effective integrated environmental management systems. This paper offers a
user-orientated approach based on requirements for an effective management of
the urban-ecosystem and the potential contributions that can be supported by
the cloud computing community. Furthermore, the commonality of the influence of
the drivers of change at the urban level offers the opportunity for the cloud
computing community to develop generic solutions that can serve the needs of
hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure
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