Chris Forsythe

Human factors in agile manufacturing: A brief overview with emphasis on communications and information infrastructure

Agile manufacturing has been promoted as a national strategy for improving industrial competitiveness. Agility refers to the capability to very rapidly go from a set of unique customer requirements to a quality, finished product. An appreciation of the human factors inherent to agile product development is pivotal to the successful integration of agility-enabling technologies, as well as the coordination of personnel working within a concurrent engineering environment. This article briefly summarizes human factors contributions to: (1) development of agile business practices; (2) design of enabling technologies; and (3) management of the introduction and fielding of new technologies and business practices. More detailed discussion is offered for human factors related to the communications and information infrastructure essential to an organization making the transition from traditional to agile product development.

Characterization and assessment of HTML style guides

This paper describes a study in which HTML style guides were characterized, compared to established HCI style guides, and evaluated against findings from HCI reviews of web paces and applications. Findings showed little consistency among the 21 HTML style guides assessed, with 75% of recommendations appearing in only one style guide. While there was some overlap, only 20% of HTML relevant recommendations from established style guides were found in HTML style guides. HTML style guides emphasized common look and feel, information display, and navigation issues with little mention of many issues prominent in established style guides such as help, message boxes and data entry. This difference is reinforced by other results showing that HTML style guides addressed concerns of web information content pages with much greater success than web-based applications. It is concluded that while the WWW represents a unique HCI environment, development of HTML style guides has been less rigorous, with issues associated with web-based applications largely ignored.

Neuroscience, Neurotechnology, and National Security: The Need for Preparedness and an Ethics of Responsible Action

We concur with Jonathan Marks (2010) that brain science can and will continue to be employed in military, and other national defense/security applications. We also concur that recent misdirection of science and medicine under the rubric of national security has raised serious concerns about (1) the uses and misuses of these techniques and technologies and (2) the level of transparency maintained by government research laboratories, if not overall initiatives. We believe that these concerns are valid and must be considered, addressed, and responded to; however, we also maintain that an intellectual, practical, and ethical commitment to brain science is critical to national security. Perhaps at the core of any such discussion is the need to consider both America’s current status as a superpower, and the importance of remaining in this position in the future. Once this affirmation is made, it then becomes critical to assess and analyze why, how, and with what means this role has been achieved and can be sustained. While a complete discussion of these variables is beyond the scope of this paper, of note to our commentary is that the superpower status of the United States is certainly attributable, at least in part, to its technologic, scientific, and economic capabilities, and to collaborative sharing of these capabilities with its allies (Baxter 1946). We assert that it is important to maintain our science and technology (S&T) initiatives through research, development, testing, and evaluation (RDTE), so as to remain in a position of global political superiority. Moreover, we believe that American superpower status is also built upon a set of moral values that are grounded in a reverence for humanity, beneficence, and respect for autonomy. Thus, we hold that any and all enterprises that fall within a rubric of asserting and sustaining

Individual Differences in Multitasking Ability and Adaptability

Multitasking has become increasingly prevalent in people’s personal and professional lives. Considerable research has attempted to identify the characteristics of people (i.e., individual differences) that predict multitasking ability, and more importantly, the ability to rapidly cope with changing task demands (adaptability). This question was assessed in an experiment wherein participants first completed a battery of individual differences tests of cognitive abilities, then multitasked in a flight simulator in which task difficulty was incrementally increased via three experimental manipulations. The results indicated that general aptitude and working memory predicted general multitasking ability, but spatial ability was the dominant factor for adapting to increasing difficulty in this flight simulator task. We conclude by discussing the implications and applied aspects of these findings.

What Do You Want? How Perceivers Use Cues to Make Goal Inferences about Others.

Variables influencing inferences about a strangers goal during an unsolicited social interaction were explored. Experiment 1 developed a procedure for identifying cues. Experiments 2 and 3 assessed the relative importance of various cues (space, time, characteristics of oneself, characteristics of the stranger, and the strangers behavior) for goal judgments. Results indicated that situational context cues informed goal judgments in ways that were consistent with diagnosticity ratings and typicality ratings of those cues. Stranger characteristics and stranger behaviors affected goal judgments more than would be expected from these quantitative measures of their informativeness. Nonetheless, the results are consistent with a mental model view that assumes perceivers monitor situational cues present during interactions and that goal inferences are guided by the informativeness of these cues.

Using After-Action Review Based on Automated Performance Assessment to Enhance Training Effectiveness

Training simulators have become increasingly popular tools for instructing humans on performance in complex environments. However, the question of how to provide individualized and scenario-specific assessment and feedback to students remains largely an open question. In this work, we follow-up on previous evaluations of the Automated Expert Modeling and Automated Student Evaluation (AEMASE) system, which automatically assesses student performance based on observed examples of good and bad performance in a given domain. The current study provides a rigorous empirical evaluation of the enhanced training effectiveness achievable with this technology. In particular, we found that students given feedback via the AEMASE-based debrief tool performed significantly better than students given only instructor feedback on two out of three domain-specific performance metrics.

Simulation of Workflow and Threat Characteristics for Cyber Security Incident Response Teams

Within large organizations, the defense of cyber assets generally involves the use of various mechanisms, such as intrusion detection systems, to alert cyber security personnel to suspicious network activity. Resulting alerts are reviewed by the organization’s cyber security personnel to investigate and assess the threat and initiate appropriate actions to defend the organization’s network assets. While automated software routines are essential to cope with the massive volumes of data transmitted across data networks, the ultimate success of an organization’s efforts to resist adversarial attacks upon their cyber assets relies on the effectiveness of individuals and teams. This paper reports research to understand the factors that impact the effectiveness of Cyber Security Incidence Response Teams (CSIRTs). Specifically, a simulation is described that captures the workflow within a CSIRT. The simulation is then demonstrated in a study comparing the differential response time to threats that vary with respect to key characteristics (attack trajectory, targeted asset and perpetrator). It is shown that the results of the simulation correlate with data from the actual incident response times of a professional CSIRT.

Using Psychologically Plausible Operator Cognitive Models to Enhance Operator Performance

Research by Sandia National Laboratories (SNL) is currently being conducted that seeks to embody human-like cognitive capacities in machines by transforming the human-machine interaction so that it more closely resembles a human-to-human interaction. This document reports on the initial phase of research and development by SNL in creating a capability whereby a machine-based cognitive model provides a real-time awareness of the cognitive state of an operator. In the capability referred to as “Discrepancy Detection,” the machine uses an operators cognitive model to monitor its own state and when there is evidence of a discrepancy between the actual state of the machine and the operators perceptions concerning the state of the machine, a discrepancy may be signaled. The current project offers successful evidence that a machine may accurately infer an operators interpretation of situations based on an individualized cognitive model of the operator.

Measuring the After-Effects of Disruption on Task Performance

In many settings, multi-tasking and interruption are commonplace. Multi-tasking has been a popular subject of recent research, but a multitasking paradigm normally allows the subject some control over the timing of the task switch. In this paper we focus on interruptions—situations in which the subject has no control over the timing of task switches. We consider three types of task: verbal (reading comprehension), visual search, and monitoring/situation awareness. Using interruptions from 30 s to 2 min in duration, we found a significant effect in each case, but with different effect sizes. For the situation awareness task, we experimented with interruptions of varying duration and found a non-linear relation between the duration of the interruption and its after-effect on performance, which may correspond to a task-dependent interruption threshold, which is lower for more dynamic tasks.

Neural assembly models derived through nano-scale measurements.

Abstract This report summarizes accomplishments of a three-year project focused on developing technical capabilities for measuring and modeling neuronal processes at the nanoscale. It was successfully demonstrated that nanoprobes could be engineered that were biocompatible, and could be biofunctionalized, that responded within the range of voltages typically associated with a neuronal action potential. Furthermore, the Xyce parallel circuit simulator was employed and models incorporated for simulating the ion channel and cable properties of neuronal membranes. The ultimate objective of the project had been to employ nanoprobes in vivo , with the nematode C elegans , and derive a simulation based on the resulting data. Techniques were developed allowing the nanoprobes to be injected into the nematode and the neuronal response recorded. To the authors’s knowledge, this is the first occasion in which nanoparticles have been successfully employed as probes for recording neuronal response in an