Optimization problems in contracted tensor networks

We discuss the calculus of variations in tensor representations with a special focus on tensor networks and apply it to functionals of practical interest. The survey provides all necessary ingredients for applying minimization methods in a general setting. The important cases of target functionals which are linear and quadratic with respect to the tensor product are discussed, and combinations of these functionals are presented in detail. As an example, we consider the representation rank compression in tensor networks. For the numerical treatment, we use the nonlinear block Gauss?CSeidel method. We demonstrate the rate of convergence in numerical tests.     

Automatically performing weak mutation with the aid of symbolic execution,concolic testing and search-based testing

Automating software testing activities can increase the quality and drastically decrease the cost of software development. Toward this direction, various automated test data generation tools have been developed. The majority of existing tools aim at structural testing, while a quite limited number aim at a higher level of testing thoroughness such as mutation. In this paper, an attempt toward automating the generation of mutation-based test cases by utilizing existing automated tools is proposed. This is achieved by reducing the killing mutants’ problem into a covering branches one. To this extent, this paper is motivated by the use of state of the art techniques and tools suitable for covering program branches when performing mutation. Tools and techniques such as symbolic execution, concolic execution, and evolutionary testing can be easily adopted toward automating the test input generation activity for the weak mutation testing criterion by simply utilizing a special form of the mutant schemata technique. The propositions made in this paper integrate three automated tools in order to illustrate and examine the method’s feasibility and effectiveness. The obtained results, based on a set of Java program units, indicate the applicability and effectiveness of the suggested technique. The results advocate that the proposed approach is able to guide existing automating tools in producing test cases according to the weak mutation testing criterion. Additionally, experimental results with the proposed mutation testing regime show that weak mutation is able to speedup the mutant execution time by at least 4.79 times when compared with strong mutation.     

Robot-Assisted Bridge Inspection

The Center for Robot-Assisted Search and Rescue (CRASAR®) deployed a customized AEOS man-portable unmanned surface vehicle and two commercially available underwater vehicles (the autonomous YSI EcoMapper and the tethered VideoRay) for inspection of the Rollover Pass bridge in the Bolivar peninsula of Texas in the aftermath of Hurricane Ike. A preliminary domain analysis with the vehicles identified key tasks in subsurface bridge inspection (mapping of the debris field and inspecting the bridge footings for scour), control challenges (navigation under loss of GPS, underwater obstacle avoidance, and stable positioning in high currents without GPS), possible improvements to human-robot interaction (having additional display units so that mission specialists can view and operate on imagery independently of the operator control unit, incorporating 2-way audio to allow operator and field personnel to communicate while launching or recovering the vehicle, and increased state sensing for reliability), and discussed the cooperative use of surface, underwater, and aerial vehicles. The article posits seven milestones in the development of a fully functional UMV for bridge inspection: standardize mission payloads, add health monitoring, improve teleoperation through better human-robot interaction, add 3D obstacle avoidance, improve station-keeping, handle large data sets, and support cooperative sensing.     

Understanding risk-taking behavior of groups: A “decision analysis” perspective

Past research has extensively investigated the effect of media, especially focusing on how anonymity increases risk-related behaviors of groups when using computer-mediated communication (CMC). This study extends prior research by examining the differences in group risk-taking behaviors between face-to-face groups and completely non-anonymous CMC groups (i.e., groups working in a fully identified, synchronous CMC environment similar to popular instant messaging systems utilized widely within organizations). Drawing on the “decision analysis” perspective, a key framework for understanding organizational decision-making, the study also examines the effects of the firm's risk preferences as well as the type of information distribution among group members (i.e., full information known to all group members versus partial information know by only some of the members) on the groups' risk-taking behaviors. Results from a laboratory experiment using student subjects found no differences in risk-taking behaviors between CMC and face-to-face groups; additionally, no differences were found related to how information was distributed among group members. A significant effect was found, however, for the risk preference of the firm, showing that risk-neutral firms influenced groups to make riskier decisions than groups from risk-averse firms. Finally, groups within risk-neutral firms receiving partial information made riskier decisions than groups receiving full information. The implications of these results for future research and practice are examined.     

An assessment of photosynthetic light use efficiency from space: Modeling the atmospheric and directional impacts on PRI reflectance

Estimation of photosynthetic light use efficiency (ε) from satellite observations is an important component of climate change research. The photochemical reflectance index, a narrow waveband index based on the reflectance at 531 and 570 nm, allows sampling of the photosynthetic activity of leaves; upscaling of these measurements to landscape and global scales, however, remains challenging. Only a few studies have used spaceborne observations of PRI so far, and research has largely focused on the MODIS sensor. Its daily global coverage and the capacity to detect a narrow reflectance band at 531 nm make it the best available choice for sensing ε from space. Previous results however, have identified a number of key issues with MODIS-based observations of PRI. First, the differences between the footprint of eddy covariance (EC) measurements and the MODIS footprint, which is determined by the sensor's observation geometry make a direct comparison between both data sources challenging and second, the PRI reflectance bands are affected by atmospheric scattering effects confounding the existing physiological signal. In this study we introduce a new approach for upscaling EC based ε measurements to MODIS. First, EC-measured ε values were “translated” into a tower-level optical PRI signal using AMSPEC, an automated multi-angular, tower-based spectroradiometer instrument. AMSPEC enabled us to adjust tower-measured PRI values to the individual viewing geometry of each MODIS overpass. Second, MODIS data were atmospherically corrected using a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which uses a time series approach and an image-based rather than pixel-based processing for simultaneous retrievals of atmospheric aerosol and surface bidirectional reflectance (BRDF). Using this approach, we found a strong relationship between tower-based and spaceborne reflectance measurements (r² = 0.74, p < 0.01) throughout the vegetation period of 2006. Swath (non-gridded) observations yielded stronger correlations than gridded data (r² = 0.58, p < 0.01) both of which included forward and backscatter observations. Spaceborne PRI values were strongly related to canopy shadow fractions and varied with different levels of ε. We conclude that MAIAC-corrected MODIS observations were able to track the site-level physiological changes from space throughout the observation period.     

SedLog: A shareware program for drawing graphic logs and log data manipulation

SedLog is a free multi-platform software package for creating graphic sediment logs providing an intuitive graphical user interface. The graphic sediment logs generated by SedLog can be exported as PDF, Scalable Vector Graphics (SVG), or JPEG for use by other drawing applications or for publications. Log data can be imported and exported in Comma Separated Values (CSV) format. The logs can also be printed to any paper size the user wants. Zoom In, Zoom Out, Fit page, Fit Height and Fit Width facilities are also provided to enable the user to customise the workspace size.     

Simulated environments with animated agents: effects on visual attention,emotion, performance,and perception

This research assessed how emotive animated agents in a simulation‐based training affect the performance outcomes and perceptions of the individuals interacting in real time with the training application. A total of 56 participants consented to complete the study. The material for this investigation included a nursing simulation in which participants interacted with three animated agents. The results of this investigation indicated that both experienced and novice participants focused more visual attention time on the body of the animated agent than the other defined areas of interest in the simulated environment. The results also indicated that novice participants conveyed more neutral facial expressions during the interaction with the animated agents than experience participants. The results of the simulation performance scores indicated that novice participants achieved higher simulation performance scores on the simulation task than experienced participants. Lastly, the results of the agent persona instrument showed that experienced and novice participants perceived the animated agents as facilitators of learning, credible, human‐like and engaging.     

A Declarative Approach to Network Device Configuration Correctness

Configuration Logic (CL) is a formal language that allows a network engineer to express constraints in terms of the actual parameters found in the configuration of network devices. We present an efficient algorithm that can automatically check a pool of devices for conformance to a set of CL constraints; moreover, this algorithm can point to the part of the configuration responsible for the error when a constraint is violated. Contrary to other validation approaches that require dumping the configuration of the whole network to a central location in order to be verified, we also present an algorithm that analyzes the correct formulas and greatly helps reduce the amount of data that need to be transferred to that central location, pushing as much of the evaluation of the formula locally on each device. The procedure is also backwards-compatible, in such a way that a device that does not (or only partially) supports a local evaluation may simply return a subset or all of its configuration. These capabilities have been integrated into a network management tool called ValidMaker.     

Achieving traceability in large scale continuous integration and delivery deployment,usage and validation of the eiffel framework

The importance of traceability in software development has long been recognized, not only for reasons of legality and certification, but also to enable the development itself. At the same time, organizations are known to struggle to live up to traceability requirements, and there is an identified lack of studies on traceability practices in the industry, not least in the area of tooling and infrastructure. This paper presents, investigates and discusses Eiffel, an industry developed solution designed to provide real time traceability in continuous integration and delivery. The traceability needs of industry professionals are also investigated through interviews, providing context to that solution. It is then validated through further interviews, a comparison with previous traceability methods and a review of literature. It is found to address the identified traceability needs and found in some cases to reduce traceability data acquisition times from days to minutes, while at the same time alternatives offering comparable functionality are lacking. In this work, traceability is shown not only to be an important concern to engineers, but also regarded as a prerequisite to successful large scale continuous integration and delivery. At the same time, promising developments in technical infrastructure are documented and clear differences in traceability mindset between separate industry projects is revealed.     

Characterizing 3D vegetation structure from space: Mission requirements

Human and natural forces are rapidly modifying the global distribution and structure of terrestrial ecosystems on which all of life depends, altering the global carbon cycle, affecting our climate now and for the foreseeable future, causing steep reductions in species diversity, and endangering Earth's sustainability.To understand changes and trends in terrestrial ecosystems and their functioning as carbon sources and sinks, and to characterize the impact of their changes on climate, habitat and biodiversity, new space assets are urgently needed to produce high spatial resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass above ground, the carbon stored within and the implications for atmospheric green house gas concentrations and climate. These needs were articulated in a 2007 National Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives of this paper are to articulate the importance of these new, multi-year, 3D vegetation structure and biomass measurements, to briefly review the feasibility of radar and lidar remote sensing technology to meet these requirements, to define the data products and measurement requirements, and to consider implications of mission durations. The paper addresses these objectives by synthesizing research results and other input from a broad community of terrestrial ecology, carbon cycle, and remote sensing scientists and working groups. We conclude that:

(1)

Current global biomass and 3-D vegetation structure information is unsuitable for both science and management and policy. The only existing global datasets of biomass are approximations based on combining land cover type and representative carbon values, instead of measurements of actual biomass. Current measurement attempts based on radar and multispectral data have low explanatory power outside low biomass areas. There is no current capability for repeatable disturbance and regrowth estimates.

(2)

The science and policy needs for information on vegetation 3D structure can be successfully addressed by a mission capable of producing (i) a first global inventory of forest biomass with a spatial resolution 1 km or finer and unprecedented accuracy (ii) annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass accumulation rates at resolutions of 1 km or finer, and (iii) transects of vertical and horizontal forest structure with 30 m along-transect measurements globally at 25 m spatial resolution, essential for habitat characterization.

We also show from the literature that lidar profile samples together with wall-to-wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together to satisfy these vegetation 3D structure and biomass measurement requirements. Finally we argue that the technology readiness levels of combined pol-SAR and lidar instruments are adequate for space flight. Remaining to be worked out, are the particulars of a lidar/pol-SAR mission design that is feasible and at a minimum satisfies the information and measurement requirement articulated herein.