Coding warnings without interfering with dismounted soldiers' missions

Objectives

Warnings are an effective way to communicate hazard, yet they can also increase task demand when presented to operators involved in real-world tasks. Furthermore, in military-related tasks warnings are often given in codes to avoid counter-intelligence, which may foster additional working memory load.

Background

Adherence to warnings in the military domain is crucial to promote safety and reduce accidents and injuries. The empirical question arises as to how aspects of coding the warning may interfere with the primary task the individual is currently performing and vice versa.

Method

Six experimental conditions were designed to assess how warning-code storage format, response format, and increasing working memory demand (retention) affected both performance on the primary task and the rate of compliance to warnings, considered here as the secondary task.

Results

Results revealed that the combination of warning-code storage and response format affected compliance rate and the highest compliance occurred when warnings were presented as pictorials and responses were coded verbally. Contrary to the proposed hypotheses, warning storage format did not affect performance on the primary task, which was only affected by the level of working memory demand. Thus, the intra-modal warning storages did not interfere with the visual/spatial nature of the primary operational task. However, increase in working memory demand, by increasing the number of memorized warning codes, had an effect on both compliance rate and primary task performance.

Conclusions

Rather than warning code storage alone, it is the coupling of warning storage and response format that has the most significant effect on compliance.     

Surface partial matching and application to archaeology

Partial matching is a fundamental problem in shape analysis, a field that is recently gaining an increasing importance in computer graphics. This paper proposes a novel approach to performing partial matching of surfaces. Given two surfaces M_A and M_B, our goal is to find the best match to M_A within M_B. The key idea of our approach is to integrate feature-point similarity and segment similarity. Specifically, we introduce a probabilistic framework in which the segmentation and the correspondences of neighboring feature points allow us to enhance or moderate our certainty of a feature-point similarity. The utility of our algorithm is demonstrated in the domain of archaeology, where digital archiving is becoming ever more widespread. In this domain, automatic matching can serve as a worthy alternative to the expensive and time-consuming manual procedure that is used today.     

Integrated task assignment and path optimization for cooperating uninhabited aerial vehicles using genetic algorithms

The problem of integrating task assignment and planning paths for a group of cooperating uninhabited aerial vehicles, servicing multiple targets, is addressed. In the problem of interest the uninhabited aerial vehicles need to perform multiple consecutive tasks cooperatively on each ground target. A Dubins car model is used for motion planning, taking into account each vehicle's specific constraint of minimum turn radius. By using a finite set to define the visitation angle of a vehicle over a target we pose the integrated problem of task assignment and path optimization in the form of a graph. This new approach results in suboptimal trajectory assignments. Refining the visitation angle discretization allows for an improved solution. Due to the computational complexity of the resulting combinatorial optimization problem, we propose genetic algorithms for the stochastic search of the space of solutions. We distinguish between two cases of vehicle group composition: homogeneous, where all vehicles are identical; and heterogeneous, where the vehicles may have different operational capabilities and kinematic constraints. The performance of the genetic algorithms is demonstrated through sample runs and a Monte Carlo simulation study. Results show that the algorithms quickly provide good feasible solutions, and find the optimal solution for small sized problems.     

Algorithms on ensemble quantum computers

In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor’s factorization algorithm, Grover’s search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and s_z^1/4,\sigma_{z}^{1/4}, as these operations cannot be implemented “bitwise”, and their standard fault-tolerant implementations require measurement.     

Continuous consensus with ambiguous failures

Continuous consensus (CC) is the problem of maintaining up-to-date and identical copies of a “core” of information about the past at all correct processes in the system (Mizrahi and Moses, 2008 [6]). This is a primitive that supports simultaneous coordination among processes, and eliminates the need for issuing separate instances of consensus for different tasks. Recent work has presented new simple and efficient optimum protocols for continuous consensus in the crash and (sending) omissions failure models. For every pattern of failures, these protocols maintain at each and every time point a core that subsumes that maintained by any other continuous consensus protocol. This paper considers the continuous consensus problem in the face of harsher failures: general omissions and authenticated Byzantine failures. Computationally efficient optimum protocols for CC do not exist in these models if $P\ne NP$. A variety of CC protocols are presented. The first is a simple protocol that enters every interesting event into the core within $t+1$ rounds (where $t$ is the bound on the number of failures), provided there are a majority of correct processes. The second is a protocol that achieves similar performance so long as $n>t$ (i.e., there is always guaranteed to be at least one correct process). The final protocol makes use of active failure monitoring and failure detection to include events in the core much faster in many runs of interest. Its performance is established based on a nontrivial property of minimal vertex covers in undirected graphs. The results are adapted to the authenticated Byzantine failure model, in which it is assumed that faulty processes are malicious, but correct processes have unforgeable signatures. Finally, the problem of uniform CC is considered. It is shown that a straightforward version of uniform CC is not solvable in the setting under study. A weaker form of uniform CC is defined, and protocols achieving it are presented.     

Optimal due date assignment and resource allocation in a group technology scheduling environment

We study a single machine scheduling problem in which the scheduler determines due dates for different jobs in a group technology environment. In group technology (GT) environment, a partition of the jobs into groups (families) is given and jobs of the same family are required to be processed consecutively. The partition of the jobs into families is done in order to achieve efficiency of high-volume production by exploiting similarities of different products and activities in their production. Since customers of similar jobs may expect that all jobs within the same group will be assigned with the same due date, we suggest an original due date assignment method in which all jobs within a family are restricted to be assigned the same due date, while each family can be assigned a due date without any restriction. The proposed method provides an extension of two earlier methods that appear in the literature, one which includes a single family and the other in which the number of families is identical to the number of jobs. Our objective is to find the job schedule and the due date for each group that minimizes an objective function which includes earliness, tardiness and due date assignment penalties. We also extend the analysis to address the case in which the job processing times are resource dependent. For this case we include the total weighted resource consumption and the makespan penalties to the objective function.     

A note: Minmax due-date assignment problem with lead-time cost

All three major classes of due-date assignment models (CON, SLK and DIF) have been solved in the literature for a minsum setting, and only two of them (CON and SLK) have been solved for a minmax setting. In this note we introduce a solution for the missing minmax model of DIF. Specifically, we study a single-machine scheduling and due-date assignment problem, in which job-dependent lead-times   are considered. Three cost components for each job are assumed: earliness cost, tardiness cost, and the cost for delaying the due-date (beyond its lead-time). The goal is to schedule the jobs and to assign due-dates, such that the maximum cost among all the jobs is minimized. We introduce an O(nlog²n)$O(n{\log }^{2}n)$ solution algorithm (where n is the number of jobs).     

Sensation Seeking and the Aversive Motivational System.

Sensation seeking (SS) has traditionally been viewed as a phenomenon of the appetitive motivational system. The limited SS research exploring contributions from the aversive motivational system reveals greater anxious reactivity to dangerous activities among low sensation seekers. The present study extends this line of work by comparing levels of fear and anxiety during anticipation of predictable and unpredictable aversive stimuli across high- and low-SS groups. Low sensation seekers displayed greater fear-potentiated startle (FPS) to predictable aversive stimuli, and only those low on SS showed FPS and skin conductance response effects during experimental contexts in which aversive stimuli were delivered unpredictably. Findings implicate enhanced apprehensive anticipation among those low on SS as a potential deterrent for their participation in intense and threatening stimulus events. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Automated,Ultra‐Fast Laser‐Drilling of Nanometer Scale Pores and Nanopore Arrays in Aqueous Solutions

The ability to quickly and reliably fabricate nanoscale pore arrays in ultra‐thin membranes such as silicon nitride (Si_xN) is extremely important for the growing field of nanopore biosensing. Laser‐based etching of thin Si_xN membranes immersed in aqueous solutions has recently been demonstrated as a method to produce stable functional pores. Herein, the principal mechanism governing material etching and pore formation using light is investigated. It is found that the process is extremely sensitive to the relative content of Si over N atoms in the amorphous membrane, produced by chemical vapor deposition. Commonly, Si_xN membranes are made to be Si‐rich to increase their mechanical stability, which substantially reduces the material's bandgap and increases the density of Si‐dangling bonds. Hence, even minimal batch‐to‐batch variation may lead to remarkably different etch rates. It is shown that higher Si content results in orders of magnitude faster etching rates. This rate is further accelerated in an alkaline environment allowing on‐demand controlled nanopore formation in about 10 s time even at low laser radiation intensities. These results highlight that photoactivation of the Si_xN by the incident beam is critical to the chemical etching process and can be used to readily produce nanopore arrays at any specific location.