Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry

The Congo Basin is the world's third largest in size (~ 3.7 million km²), and second only to the Amazon River in discharge (~ 40,200 m³ s^− 1 annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3° × 3° regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 km³, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.     

Compact modeling of amorphous‐silicon thin‐film transistors with BSIM3

Abstract— A novel approach of modeling a‐Si:H TFTs with the industry‐standard BSIM3 compact model is presented. The described approach defines the a‐Si:H TFT drain current and terminal charges as explicit functions of terminal voltages using a minimum set of BSIM3 parameters. The set of BSIM3 parameters is chosen based on the electrical and physical characteristics of the a‐Si:H TFT and their values extracted from measured data. By using the selected BSIM3 model parameters, the a‐Si:H TFT is simulated inside SPICE to fit the simulated I‐V and C‐V curves with the measured results. Finally, the extracted BSIM3 model is validated by simulating the kickback voltage effect in an AMLCD pixel array.     

Usability engineering for augmented reality: employing user-based studies to inform design

A major challenge, and thus opportunity, in the field of human-computer interaction and specifically usability engineering is designing effective user interfaces for emerging technologies that have no established design guidelines or interaction metaphors or introduce completely new ways for users to perceive and interact with technology and the world around them. Clearly, augmented reality is one such emerging technology. We propose a usability engineering approach that employs user-based studies to inform design, by iteratively inserting a series of user-based studies into a traditional usability engineering lifecycle to better inform initial user interface designs. We present an exemplar user-based study conducted to gain insight into how users perceive text in outdoor augmented reality settings and to derive implications for design in outdoor augmented reality. We also describe lessons learned from our experiences conducting user-based studies as part of the design process.     

New Research Results for Electronic Voting

Voting systems have become controversial in the years following the multiple election disasters that occurred in the United States during and after 2000. Of particular note were the electronic voting (e-voting) systems that were widely deployed to replace the pre-scored punch-card systems, systems that had have been frequently judged to be central to the problem in the 2000 Florida general election. The (premature) deployment of e-voting machines stimulated a new field of security and privacy research around the subject of elections, a subject that has turned out to be more complex and deeper than anyone would have predicted a decade ago. Here we present a sample of some of the finest recent work on election technology from authors on three continents.     

Real time video frames allocation in mobile networks using cooperative pre-fetching

In this paper, we study the bandwidth allocation problem for serving video requests in a mobile real-time video player system. One of the main issues to maintain the quality of services (QoS) in mobile video playback is to ensure sufficient number of video frames available at the client side while a video is being played. However, due to the limited bandwidth of a mobile network and variable workload streaming video, this is not easy to achieve in practice. In addition, the communication link between mobile clients and a video server is subject to frequent errors and temporary disconnection. In this paper, we propose to use the notion of buffered bandwidth in addition to the network bandwidth to support real-time playback of videos at mobile clients. Based on this, we designed a bandwidth allocation scheme called Cooperative Pre-Fetching (CP) in which the amount of bandwidth to be allocated to serve a video request depends on the current buffer level of the video at the client relative to the target buffer level of the client. In determining the target buffer level, we consider the errors in communication to the client as well as the other clients who are concurrently served by the system. The buffered video frames at the clients are then used to minimize the impact of error in communications on the overall QoS of video playbacks in the whole system.

Supporting command and control training functions in the emergency management domain using cognitive systems engineering

The design and implementation of MERMAIDS, a computer-based training system in the domain of emergency command and control, is described. The research investigates the use of cognitive systems engineering and information management tools for modelling and representing training knowledge of emergency system operators. We propose a decision-centric human-computer interface as a new method of supporting computer-based modelling in the domain of emergency systems. Several interacting themes in information management relevant to emergency response planning are discussed.     

Balancing Misclassification Rates in Classification-Tree Models of Software Quality

Software product and process metrics can be useful predictorsof which modules are likely to have faults during operations.Developers and managers can use such predictions by softwarequality models to focus enhancement efforts before release.However, in practice, software quality modeling methods in theliterature may not produce a useful balance between the two kindsof misclassification rates, especially when there are few faultymodules.This paper presents a practical classificationrule in the context of classification tree models that allowsappropriate emphasis on each type of misclassification accordingto the needs of the project. This is especially important whenthe faulty modules are rare.An industrial case study using classification trees, illustrates the tradeoffs.The trees were built using the TREEDISC algorithm whichis a refinement of the CHAID algorithm. We examinedtwo releases of a very large telecommunications system, and builtmodels suited to two points in the development life cycle: theend of coding and the end of beta testing. Both trees had onlyfive significant predictors, out of 28 and 42 candidates, respectively.We interpreted the structure of the classification trees, andwe found the models had useful accuracy.