An analysis of visual adaptation and contrast perception for tone mapping

Tone Mapping is the problem of compressing the range of a High-Dynamic Range image so that it can be displayed in a Low-Dynamic Range screen, without losing or introducing novel details: The final image should produce in the observer a sensation as close as possible to the perception produced by the real-world scene. We propose a tone mapping operator with two stages. The first stage is a global method that implements visual adaptation, based on experiments on human perception, in particular we point out the importance of cone saturation. The second stage performs local contrast enhancement, based on a variational model inspired by color vision phenomenology. We evaluate this method with a metric validated by psychophysical experiments and, in terms of this metric, our method compares very well with the state of the art.

A WiMAX-based implementation of network MIMO for indoor wireless systems

It is well known that multiple-input multiple-output (MIMO) techniques can bring numerous benefits, such as higher spectral efficiency, to point-to-point wireless links. More recently, there has been interest in extending MIMO concepts tomultiuser wireless systems. Our focus in this paper is on network MIMO, a family of techniques whereby each end user in a wireless access network is served through several access points within its range of influence. By tightly coordinating the transmission and reception of signals at multiple access points, network MIMO can transcend the limits on spectral efficiency imposed by cochannel interference. Taking prior information-theoretic analyses of networkMIMO to the next level, we quantify the spectral efficiency gains obtainable under realistic propagation and operational conditions in a typical indoor deployment. Our study relies on detailed simulations and, for specificity, is conducted largely within the physical-layer framework of the IEEE 802.16e Mobile WiMAX system. Furthermore,to facilitate the coordination between access points, we assume that a high-capacity local area network, such as Gigabit Ethernet,connects all the access points. Our results confirm that network MIMO stands to provide a multiple-fold increase in spectralefficiency under these conditions.

Free-and open source software for a course on network management: authoring and enactment of scripts based on collaborative learning strategies

This paper describes a Computer-Supported Collaborative Learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on Free- and Open-Source Software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. First, the Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates onhow Collage and Gridcole were employed, describes the applied evaluation methodology, anddiscusses the most significant findings derived from the case study.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Towards the Automatic Merging of Lexical Resources: Automatic Mapping

Lexical Resources are a critical component for Natural Language Processing applications. However, the high cost of comparing and merging different resources has been a bottleneck to have richer resources with a broad range of potential uses for a significant number of languages.With the objective of reducing cost byeliminating human intervention, we present a new method for automating the merging of resources,with special emphasis in what we call the mapping step. This mapping step, which converts the resources into a common format that allows latter the merging, is usually performed with huge manual effort and thus makes the whole process very costly. Thus, we propose a method to perform this mapping fully automatically. To test our method, we have addressed the merging of two verb subcategorization frame lexica for Spanish, The resultsachieved, that almost replicate human work, demonstrate the feasibility of the approach.

2005 Annual Report of the Iowa Communications Network

This is the Annual Report for Fiscal Year 2005 (July 1, 2004-June 30, 2005) for the Iowa Communications Network.

Iowa Communications Network Performance Report, FY 2004

Agency Performance Report

Iowa Communications Network Performance Report, FY 2005

Agency Performance Report

Iowa Department of Transportation Report of Savings through use of Iowa Communications Network (ICN), FY 2005

Iowa DOT savings through use of Iowa Communications Network (ICN) videoconferencing

State of Iowa Improving Transition Outcomes Resource Mapping Workshops, 2003-2004

Iowa Vocational Rehabilitation Services, a Division of the State of Iowa Department of Education, in partnership with seven other state agencies, applied for and was awarded funding for “Improving Transition Outcomes for Youth with Disabilities Through the Use of Intermediaries.” This Innovative State Alignment Grant is funded by the Department of Labor, Office of Disability Employment Policy. For clarity and brevity, the Iowa team chose to use “Improving Transition Outcomes” as the project name, thus providing the acronym ITO. Grant funding began October 1, 2003 with the possibility of renewal for five years.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

The HVEM network: new directions in targeting novel costimulatory/co-inhibitory molecules for cancer therapy.

The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.