POPCORN: a Supervisory Control Simulation for Workload and Performance Research

A multi-task simulation of a semi-automatic supervisory control system was developed to provide an environment in which training, operator strategy development, failure detection and resolution, levels of automation, and operator workload can be investigated. The goal was to develop a well-defined, but realistically complex, task that would lend itself to model-based analysis. The name of the task (POPCORN) reflects the visual display that depicts different task elements milling around waiting to be released and pop out to be performed. The operator's task was to complete each of 100 task elements that ere represented by different symbols, by selecting a target task and entering the desired a command. The simulated automatic system then completed the selected function automatically. Highly significant differences in performance, strategy, and rated workload were found as a function of all experimental manipulations (except reward/penalty)

Feature-Guided Black-Box Safety Testing of Deep Neural Networks

Despite the improved accuracy of deep neural networks, the discovery of adversarial examples has raised serious safety concerns. Most existing approaches for crafting adversarial examples necessitate some knowledge (architecture, parameters, etc.) of the network at hand. In this paper, we focus on image classifiers and propose a feature-guided black-box approach to test the safety of deep neural networks that requires no such knowledge. Our algorithm employs object detection techniques such as SIFT (Scale Invariant Feature Transform) to extract features from an image. These features are converted into a mutable saliency distribution, where high probability is assigned to pixels that affect the composition of the image with respect to the human visual system. We formulate the crafting of adversarial examples as a two-player turn-based stochastic game, where the first player's objective is to minimise the distance to an adversarial example by manipulating the features, and the second player can be cooperative, adversarial, or random. We show that, theoretically, the two-player game can con- verge to the optimal strategy, and that the optimal strategy represents a globally minimal adversarial image. For Lipschitz networks, we also identify conditions that provide safety guarantees that no adversarial examples exist. Using Monte Carlo tree search we gradually explore the game state space to search for adversarial examples. Our experiments show that, despite the black-box setting, manipulations guided by a perception-based saliency distribution are competitive with state-of-the-art methods that rely on white-box saliency matrices or sophisticated optimization procedures. Finally, we show how our method can be used to evaluate robustness of neural networks in safety-critical applications such as traffic sign recognition in self-driving cars.Comment: 35 pages, 5 tables, 23 figure

Versatile Control System for Automated Single-Molecule Optical Tweezers Investigations

We present a versatile control system to automate single-molecule biophysics experiments. This method combines low-level controls into various functional, user-configurable modules, which can be scripted in a domain-specific instruction language. The ease with which the high-level parameters can be changed accelerates the development of a durable experiment for the perishable single-molecule samples. Once the experimental parameters are tuned, the control system can be used to repeatedly manipulate other single molecules in the same way, which is necessary to accumulate the statistics needed to report results from single-molecule studies. This system has been implemented for an optical tweezers instrument for single-molecule manipulations, with real-time point-by-point feedback at a loop rate of 10-20 kHz

Comparing demand functions when different price manipulations are used: Does unit price help?

Six hens pecked a key (Experiment 1) or pushed a door (Experiment 2) to obtain food reinforcement. In both experiments and as an analogue of price changes, the response requirements were varied in two ways: by increasing the number of responses required and by increasing the required force of each response. The two price manipulations (response number and response force) had different effects on behavior and produced different-shaped demand functions when the rates of consumption were plotted logarithmically against the price analogues. Irrespective of response topography, when the number of required responses was varied, the data paths appeared linear, with slopes close to -1.0. When the required force of each keypeck and doorpush was varied, the data paths were clearly curved, with increasingly steep downward slopes as the force increased. Using the concept of unit price did not fully remove the different effects of the two price manipulations. Those differences are best attributed to the differing times needed in order to complete each response unit under those price manipulations

Using smartphones as a proxy for forensic evidence contained in cloud storage services

Cloud storage services such as Dropbox, Box and SugarSync have been embraced by both individuals and organizations. This creates an environment that is potentially conducive to security breaches and malicious activities. The investigation of these cloud environments presents new challenges for the digital forensics community. It is anticipated that smartphone devices will retain data from these storage services. Hence, this research presents a preliminary investigation into the residual artifacts created on an iOS and Android device that has accessed a cloud storage service. The contribution of this paper is twofold. First, it provides an initial assessment on the extent to which cloud storage data is stored on these client-side devices. This view acts as a proxy for data stored in the cloud. Secondly, it provides documentation on the artifacts that could be useful in a digital forensics investigation of cloud services

Noticing the self: Implicit assessment of self-focused attention using word recognition latencies

Self-focused attention is difficult to measure. Two studies developed an implicit measure of self-focus based on word recognition latencies. Self-focused attention activates self-content, so self-focused people should recognize self-relevant words more quickly. Study 1 measured individual-differences in self-focused attention. People scoring high in private self-consciousness recognized self-relevant words more quickly. Study 2 manipulated objective self-awareness with a writing task. People who wrote about distinctive self-aspects (high self-awareness) recognized self-relevant words more quickly compared to people who wrote about a neutral topic (low self-awareness) and people who did no writing (control). The discussion considers implications for future research on self-focused attention

Fine-tuning the Advanced Encryption Standard (AES)

The Advanced Encryption Standard has been playing a prominent role in embedded systems security for a decade after being announced by the National Institute of Standards and Technology (NIST). However, vulnerabilities have emerged, especially timing attacks, that challenges its security. This paper demonstrates the introduction of a unique diffusion and confusion scheme in Rijndael by incorporating ASCII codes manipulations using playfair ciphering into the algorithm; it is not dependent on the key and input thereby making it a constant time module in AES algorithm. The concept counters possible leakages from the S-box lookups; intermediary operations (SubstituteByte, ShiftRows, MixColumns, AddRoundKey) of the AES are still applicable but it becomes impossible for cryptanalysis discovery of enciphering method and ciphertext bits. Success of cracking efforts will be beyond human patience as it avoids statistical precision, thereby curbing timing attacks

Video Manipulation Techniques for the Protection of Privacy in Remote Presence Systems

Systems that give control of a mobile robot to a remote user raise privacy concerns about what the remote user can see and do through the robot. We aim to preserve some of that privacy by manipulating the video data that the remote user sees. Through two user studies, we explore the effectiveness of different video manipulation techniques at providing different types of privacy. We simultaneously examine task performance in the presence of privacy protection. In the first study, participants were asked to watch a video captured by a robot exploring an office environment and to complete a series of observational tasks under differing video manipulation conditions. Our results show that using manipulations of the video stream can lead to fewer privacy violations for different privacy types. Through a second user study, it was demonstrated that these privacy-protecting techniques were effective without diminishing the task performance of the remote user.Comment: 14 pages, 8 figure

Voltage-sensor transitions of the inward-rectifying K+ channel KAT1 indicate a latching mechanism biased by hydration within the voltage sensor

The Kv-like K+ channels at the plasma membrane, including the inward-rectifying KAT1 K+ channel of Arabidopsis, are important targets for manipulating K+ homeostasis in plants. Gating modification, especially, has been identified as a promising means by which to engineer plants with improved characteristics in mineral and water use. Understanding plant K+ channel gating poses several challenges, despite many similarities to that of mammalian Kv and Shaker channel models. We have used site-mutagenesis to explore residues that are thought to form two electrostatic counter-charge centers either side of a conserved Phe residue within the S2 and S3 α-helices of the voltage sensor domain (VSD) of Kv channels. Consistent with molecular dynamic simulations of KAT1, we show that the voltage dependence of the channel gate is highly sensitive to manipulations affecting these residues. Mutations of the central Phe residue favored the closed KAT1 channel, whereas mutations affecting the counter-charge centers favored the open channel. Modelling of the macroscopic current kinetics also highlighted a substantial difference between the two sets of mutations. We interpret these findings in context of the effects on hydration of amino-acid residues within the VSD and with an inherent bias of the VSD, when hydrated around a central Phe residue, to the closed state of the channel