Expandable indexes vs. sequential menus for searching hierarchies on the World Wide Web

An experiment is reported that compared expandable indexes providing full menu context with sequential menus providing only partial context. Menu depth was varied using hierarchies of two, three and four levels deep in an asymmetric structure of 457 root level items. Menus were presented on the World Wide Web within a browser. Participants searched for specific targets. Results suggest that reducing the depth of hierarchies improves performance in terms of speed and search efficiency. Surprisingly, expandable indexes resulted in poorer performance with deeper hierarchies than did sequential menus.     

A BEM‐based genetic algorithm for identification of polarization curves in cathodic protection systems

The purpose of this work is to apply an inverse boundary element formulation in order to develop efficient algorithms for identification of polarization curves in a cathodic protection system. The problem is to minimize an objective function measuring the difference between observed and BEM‐predicted surface potentials. The numerical formulation is based on the application of genetic algorithms, which are robust search techniques emulating the natural process of evolution as a means of progressing towards an optimum solution. Examples of application are included in the paper for different types of polarization curves in finite and infinite electrolytes. The accuracy and efficiency of the numerical results are verified by comparison with standard conjugate gradient techniques. As a result of this research, the genetic algorithm approach is shown to be more robust, independent of the position of the sensors and of initial guesses, and will be further developed for three‐dimensional applications. Copyright © 2002 John Wiley & Sons, Ltd.     

Can the crowd tell how I feel? Trait empathy and ethnic background in a visual pain judgment task

Many advocate for artificial agents to be empathic. Crowdsourcing could help, by facilitating human-in-the-loop approaches and data set creation for visual emotion recognition algorithms. Although crowdsourcing has been employed successfully for a range of tasks, it is not clear how effective crowdsourcing is when the task involves subjective rating of emotions. We examined relationships between demographics, empathy, and ethnic identity in pain emotion recognition tasks. Amazon MTurkers viewed images of strangers in painful settings, and tagged subjects’ emotions. They rated their level of pain arousal and confidence in their responses, and completed tests to gauge trait empathy and ethnic identity. We found that Caucasian participants were less confident than others, even when viewing other Caucasians in pain. Gender correlated to word choices for describing images, though not to pain arousal or confidence. The results underscore the need for verified information on crowdworkers, to harness diversity effectively for metadata generation tasks.     

Bedload Transport in Gravel-Bed Streams with Unimodal Sediment

Bedload transport in many gravel-bed streams becomes highly complicated because of the nonuniformity of the grain size and the vertical stratification of channel bed material. A new relation for computing bedload transport rates in gravel-bed streams is proposed here. In an effort to account for the variation of the makeup of the surface material within a wide range of Shields stresses, the relation employs a two-parameter approach, one related to the material in the pavement and the other to that in the subpavement layers. The mode is used to represent the grain sizes of each layer. Available bedload transport data from gravel-bed streams with unimodal sediment are used to test the accuracy of the relation. A comparison with other bedload transport relations is also considered.     

A motion control framework for autonomous water sampling and swing-free transportation of a multirotor UAV with a cable-suspended mechanism

In this work, we present an end-to-end solution for autonomous water sampling by utilizing an unmanned aerial vehicle (UAV) with a cable-suspended mechanism. Towards this direction, a sampling mechanism is initially designed in such a manner that the water sampling success ratio is maximized. However, the disturbances, acting on the submerged mechanism due to the water flow during the sampling procedure, impede the stabilization of the vehicle above the desired sampling position. Consequently, to achieve the precise hovering of the UAV, the vehicle's sensor suite is further augmented with a load cell, a depth sensor, an ultrasonic sensor, and a camera. The respective measurements are appropriately fused by employing an extended Kalman filter (EKF). Hence, an estimate of the disturbances is available in real-time and is incorporated into a Model Predictive Control scheme which compensates for the aforementioned disturbances and stabilizes the vehicle above the sampling location. Finally, a complete water sampling mission entails the safe and swing-free transportation of the mechanism towards the sampling location and, then, to a position where the collected samples are postprocessed by human operators. Consequently, a model predictive controller is employed which ensures the navigation of the vehicle to the desired waypoints while minimizing the swinging motion of the mechanism. The state of the mechanism is obtained by fusing measurements provided by the load cell and the camera with an EKF. The performance of the proposed framework, which aims to address all the aspects of a water sampling mission, is demonstrated through real experiments with an octorotor.     

Scanning scene tunnel for city traversing

This paper proposes a visual representation named scene tunnel for capturing urban scenes along routes and visualizing them on the Internet. We scan scenes with multiple cameras or a fish-eye camera on a moving vehicle, which generates a real scene archive along streets that is more complete than previously proposed route panoramas. Using a translating spherical eye, properly set planes of scanning, and unique parallel-central projection, we explore the image acquisition of the scene tunnel from camera selection and alignment, slit calculation, scene scanning, to image integration. The scene tunnels cover high buildings, ground, and various viewing directions and have uniformed resolutions along the street. The sequentially organized scene tunnel benefits texture mapping onto the urban models. We analyze the shape characteristics in the scene tunnels for designing visualization algorithms. After combining this with a global panorama and forward image caps, the capped scene tunnels can provide continuous views directly for virtual or real navigation in a city. We render scene tunnel dynamically by view warping, fast transmission, and flexible interaction. The compact and continuous scene tunnel facilitates model construction, data streaming, and seamless route traversing on the Internet and mobile devices.     

In-network data acquisition and replication in mobile sensor networks

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of values from the network in cases of failures. We also extend DRA with a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles to form the Hierarchical-DRA (HDRA) algorithm, which enables the approximate retrieval of events from the network. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures across all nodes are less than 60%, our framework can recover over 80% of detected values exactly.     

Specifying the dynamics of social technologies as social microworlds

This paper explores the affordances of social technologies for supporting the construction of a shareable artefact by a group of learners. A qualitative study that captures the use of five different types of social technologies (Facebook, blogs, wikis, Google Documents and Dropbox) in three different classroom settings sheds light on the potentials and challenges of these tools for supporting material exploration, artefact construction and evaluation. Qualitative content analysis of instructors’ field notes, students’ and instructors’ reflections, interviews and focus groups sheds light on the potential of social technologies to transform the activity of learning across a new culture of computational tools. The affordances of social technologies are discussed as well as design principles that need to be followed in these new arenas.     

Hyperplane Grouping and Pipelined Schedules: How to Execute Tiled Loops Fast on Clusters of SMPs

This paper proposes a novel approach for the parallel execution of tiled Iteration Spaces onto a cluster of SMP PC nodes. Each SMP node has multiple CPUs and a single memory mapped PCI-SCI Network Interface Card. We apply a hyperplane-based grouping transformation to the tiled space, so as to group together independent neighboring tiles and assign them to the same SMP node. In this way, intranode (intragroup) communication is annihilated. Groups are atomically executed inside each node. Nodes exchange data between successive group computations. We schedule groups much more efficiently by exploiting the inherent overlapping between communication and computation phases among successive atomic group executions. The applied non-blocking schedule resembles a pipelined datapath, where group computation phases are overlapped with communication ones, instead of being interleaved with them. Our experimental results illustrate that the proposed method outperforms previous approaches involving blocking communication or conventional grouping schemes.