Training for vigilance: using predictive power to evaluate feedback effectiveness

OBJECTIVE: We examined the effects of knowledge of results (KR) on vigilance accuracy and report the first use of positive and negative predictive power (PPP and NPP) to assess vigilance training effectiveness. BACKGROUND: Training individuals to detect infrequent signals among a plethora of nonsignals is critical to success in many failure-intolerant monitoring technologies. KR has been widely used for vigilance training, but the effect of the schedule of KR presentation on accuracy has been neglected. Previous research on training for vigilance has used signal detection metrics or hits and false alarms. In this study diagnosticity measures were applied to augment traditional analytic methods. METHOD: We examined the effects of continuous KR and a partial-KR regimen versus a no-KR control on decision diagnosticity. RESULTS: Signal detection theory (SDT) analysis indicated that KR induced conservatism in responding but did not enhance sensitivity. However, KR in both forms equally enhanced PPP while selectively impairing NPP. CONCLUSION: There is a trade-off in the effectiveness of KR in reducing false alarms and misses. Together, SDT and PPP/NPP measures provide a more complete portrait of performance effects. APPLICATION: PPP and NPP together provide another assessment technique for vigilance performance, and as additional diagnostic tools, these measures are potentially useful to the human factors community.     

Target acquisition with UAVs: vigilance displays and advanced cuing interfaces

Vigilance and threat detection are critical human factors considerations in the control of unmanned aerial vehicles (UAVs). Utilizing a vigilance task in which threat detections (critical signals) led observers to perform a subsequent manual target acquisition task, this study provides information that might have important implications for both of these considerations in the design of future UAV systems. A sensory display format resulted in more threat detections, fewer false alarms, and faster target acquisition times and imposed a lighter workload than did a cognitive display format. Additionally, advanced visual, spatial-audio, and haptic cuing interfaces enhanced acquisition performance over no cuing in the target acquisition phase of the task, and they did so to a similar degree. Thus, in terms of potential applications, this research suggests that a sensory format may be the best display format for threat detection by future UAV operators, that advanced cuing interfaces may prove useful in future UAV systems, and that these interfaces are functionally interchangeable.     

False alarm moderation for performance monitoring in industrial water distribution systems

While considerable attention has been given to data driven methods that analyse and control energy systems in buildings, the same cannot be said for building water systems. As a result, approaches which support enhanced efficiency in building water consumption are somewhat underdeveloped, particularly in industrial settings. Water consumption in industrial systems features non-stationarity (i.e., variations in statistical properties over time), making it challenging to distinguish between routine and non-routine water uses. In such scenarios, fault detection and diagnosis methods that leverage multivariate statistical process control with, for example, principal component analysis and detection indices (Hotelling T²-statistics and Q-statistics), can be successfully used to identify system alarms. However, even with these approaches there can be a high prevalence of false alarms leading to low industry uptake of fault detection and diagnosis systems, or where in place, alarms can be ignored. To efficiently detect and diagnose water distribution system faults, false alarms should be controlled through false alarm moderation approaches so that building managers/operators only need to focus on critical system alarms or system alarms with high risk levels. This paper utilises two statistical non-parametric false alarm moderation approaches (window-based, and trial-based) that generate a second control limit for T²-statistics and Q-statistics. The implementation of these false alarm moderation approaches was combined with principal component analysis to detect faults with real water time series data from two case-study sites. Using both approaches false alarms were reduced, and the overall performance and reliability of the fault detection and diagnosis approach was improved. The principal component analysis model with the window-based approach was shown to be particularly effective.     

基于卷积神经网络的雷达目标检测方法

雷达目标检测近年来一直是雷达信号处理中的重要任务,在探测监控等安全领域中有非常重要的作用;针对传统恒虚警目标检测方法存在的环境适应能力较弱、复杂地形环境下雷达虚警数量急剧上升等问题,提出一种基于卷积神经网络的雷达目标检测方法;以雷达回波信号数据处理后得到的距离-多普勒图像作为模型的训练集和测试集,设计基于FasterR-CNN结构的雷达目标检测模型,训练模型并将测试结果与传统恒虚警目标检测算法结果相比较,所设计的模型提升了雷达目标检测正确率并较大地减少了虚警数量,这表明将卷积神经网络应用于雷达回波信号的处理任务中是可行的。     

Zeitschrift für Arbeitswissenschaft Abstracts of papers,Vol 40 (12 NF), Part 2, 1986

Abstract

Vigilance is the ability of an observer to maintain attention for extended periods of time; however, performance tends to decline with time on watch, a pattern referred to as the vigilance decrement. Previous research has focused on factors that attenuate the decrement; however, one factor rarely studied is the effect of social facilitation. The purpose for the present investigation was to determine how different types of social presence affected the performance, workload and stress of vigilance. It was hypothesised that the presence of a supervisory figure would increase overall performance, but may occur at the cost of increased workload and stress. Results indicated that the per cent of false alarm and response times decreased in the presence of a supervisory figure. Using social facilitation in vigilance tasks may thus have positive, as well as, negative effects depending on the dependent measure of interest and the role of the observer.

Practitioner Summary: Social facilitation has rarely been examined in the context of vigilance, even though it may improve performance. Vigilance task performance was examined under social presence. The results of the present study indicated that false alarms and response times decreased in the social presence of a supervisory figure, thus improving performance.     

基于最弱前置条件的静态分析误报消除技术

针对程序静态分析技术误报过多的问题,提出一种基于最弱前置条件的静态分析误报消除方法。根据不同的软件安全性质,从目标状态出发,以需求驱动的方式得到过程起始位置的最弱前置条件,判断该条件公式的可满足性来消除误报。将该方法实例化来消除静态分析工具检测数组访问越界和空指针解引用的误报,实验结果表明该方法是有效且实用的。     

An experimental study of signal vigilance errors in train driving

Abstract

Failure to confirm a railway signal on a train's departure was investigated in four laboratory experiments. In the first two experiments, subjects were instructed to press a key when the signal colour was green as soon as a sign of departure was given by a lit pilot lamp and erroneous responses provoked by false signs were analysed. In the other two experiments, subjects were given a distracting task secondary to the train-starting operation, and signal vigilance behaviour was directly inspected using VTR recording. Results demonstrated that errors were related to two factors: automatism in information processing which may result from repetition of simple reactions to signs given with redundant information accompanying the signal, and the absence of attention to the signal which may be facilitated by redundancy and other distracting factors. A model for the mechanism of signal vigilance errors is offered and some effective countermeasures proposed.     

基于分形理论的声纳图像人造目标检测算法

声纳图像中人造目标的自动检测是当前水下探测领域需要重点解决的问题之一。传统的基于目标回波信号强度的检测方法在海底存在岩石等类似于水雷等人造目标的情况下,常会导致较高的虚警率。由于人造目标和自然背景之间的纹理特性的不同,自然背景一般具有较复杂的纹理,而人造目标形状规则、表面光滑、纹理简单。利用分形模型中分形维数特征、截距特征、分形拟合误差特征以及多尺度分形特征进行声纳图像人造目标检测,仿真实验表明基于分形的检测算法可较好地实现人造目标和自然背景的分离,从而为成像声纳水下探测技术的进一步发展奠定了基础。     

Effects of a biocybernetic system on vigilance performance

The present study was designed to determine whether a biocybernetic, adaptive system could enhance vigilance performance. Participants were asked to monitor the repetitive presentation of white bars on a computer screen for occasional increases in length. An index of task engagement was derived from participants' electroencephalographic (EEG) activity and was used to change the presentation rate of events among 3 values (6, 20, and 60 events/min). Under a negative feedback contingency, event rates increased if the engagement index decreased and, conversely, decreased if the index increased. Under positive feedback, the opposite contingency existed. Each experimental participant had a yoked control partner who received the same pattern of changes in event rates irrespective of his or her EEG activity. The results showed that better vigilance performance was obtained under negative feedback and that the performance of the yoked participants was similar to that of their experimental partners. These findings suggest that it may be possible to improve monitoring performance on critical activities such as air traffic control and radar and sonar operation through a pattern of event rate changes that do not rely on an operator's overt behavior.     

The effects of signal salience and caffeine on performance, workload, and stress in an abbreviated vigilance task

In 2 experiments, a 12-min computerized vigilance task was demonstrated to reproduce the vigilance decrement, high workload (NASA-TLX), and stressful character (Dundee Stress State Questionnaire) of vigilance tasks lasting 30 min or more. In Experiment 1, the abbreviated task was also shown to duplicate the signal salience effect, a major finding associated with long-duration vigilance tasks. Moreover, Experiment 2 showed that performance on the abbreviated task can be enhanced by caffeine - a drug that benefits long-duration tasks. This enhancement effect was limited to performance, however, suggesting that caffeine influences factors that control signal detection but not those that control task-induced stress. The results parallel those obtained with long-duration tasks and support a resource-depletion model of the vigilance decrement. The abbreviated task might be useful in situations in which long-duration tasks are precluded (e.g., performance assessment batteries, neuropsychological testing, and brain imaging).     

Using enhanced text to facilitate recognition of drug names: evidence from two experimental studies

Two studies examined the effects of enhanced text on immediate recognition of drug names. Study 1 sampled 102 college students using a between-subjects design, while Study 2 sampled 11 practicing pharmacists and technicians using a within-subjects Latin square design. Both studies utilized a computer-based sequential recognition task where a prime word was shown with various text enhancements, followed by a mask and then a target word. Participants decided whether the target word was the same as the prime word. Stimuli were organized so that 120 trials were matches and 120 trials were mismatches, randomly sequenced for each participant. Results showed an effect of orthographic similarity, where high-similarity name mismatches were missed more often. This effect was independent of the type of text enhancement used and response bias. Case-based enhancements also increased errors of commission (false alarms) significantly. Discussion includes the practical relevance of the data and future directions for research.     

Sorting the Wheat from the Chaff: A Study of the Detection of Alarms

The research in this paper considers the evidence on the success of alarm reduction strategies reported in the open literature. Despite strong beliefs to the contrary, the empirical evidence suggest that alarm reduction strategies have not been as successful as initially expected. This seems to be due to the fact that alarm reduction strategies actually deprive process control operators of information. In order to determine the ability of people to sift through alarm information, a study of alarm detection with three ratios of target to non-target alarms was devised (i.e. 2%, 6% and 10%) and the information was presented at three rates (i.e. 1 second, 4 seconds and 8 seconds). The results show that the ratio of target alarms has no effect on detection performance, but the temporal rate does. Given that process operators are rarely required to acknowledge alarm information in real time, it is suggested that more emphasis should be placed on initial definition of alarms and better presentation methods, rather than attempts to block the flow of alarms that have already been triggered.     

Fault management in supervisory control: the effect of false alarms and support

Automation has changed the role of human operators from direct manual control to supervision. Their main task is to monitor whether system performance remains within pre-specified ranges and intervention is only required in unusual situations. One of the consequences is a loss of situation awareness, which significantly affects performance in abnormal, time-critical situation. The present study reports two experiments, both dealing with fault management in a maritime supervisory control task. The first experiment investigated to what extent false alarms would affect performance and diagnosis behaviour when multiple disturbances occurred. Thirty-nine students from maritime curricula diagnosed disturbances that could either be real or turn out to be a false alarm. The presence of false alarms not only affected the rate with which the subsystems under control were sampled, but it also increased problem-solving time. One of the reasons for suboptimal performance in dealing with fault propagation was tunnel vision: participants had a tendency to deal with disturbances sequentially. In the second experiment the effect of support on performance and diagnosis behaviour was investigated. Two types of support were distinguished: interactive support requiring participants to provide the symptom values and automatic support that directly provided the correct action. Thirty students from maritime curricula diagnosed disturbances with the help of either the interactive or the noninteractive support tool. The results indicated that even though both support tools gave the same advice on how to act, more incorrect actions were taken in the non-interactive support condition. Even though no differences in performance were found after the tool had been removed, it was shown that participants who were used to interactive support used a more structured problem-solving strategy than participants used to the non-interactive support. Consequences for system design are discussed.     

Fault management in supervisory control: the effect of false alarms and support

Automation has changed the role of human operators from direct manual control to supervision. Their main task is to monitor whether system performance remains within pre-specified ranges and intervention is only required in unusual situations. One of the consequences is a loss of situation awareness, which significantly affects performance in abnormal, time-critical situation. The present study reports two experiments, both dealing with fault management in a maritime supervisory control task. The first experiment investigated to what extent false alarms would affect performance and diagnosis behaviour when multiple disturbances occurred. Thirty-nine students from maritime curricula diagnosed disturbances that could either be real or turn out to be a false alarm. The presence of false alarms not only affected the rate with which the subsystems under control were sampled, but it also increased problem-solving time. One of the reasons for suboptimal performance in dealing with fault propagation was tunnel vision: participants had a tendency to deal with disturbances sequentially. In the second experiment the effect of support on performance and diagnosis behaviour was investigated. Two types of support were distinguished: interactive support requiring participants to provide the symptom values and automatic support that directly provided the correct action. Thirty students from maritime curricula diagnosed disturbances with the help of either the interactive or the noninteractive support tool. The results indicated that even though both support tools gave the same advice on how to act, more incorrect actions were taken in the non-interactive support condition. Even though no differences in performance were found after the tool had been removed, it was shown that participants who were used to interactive support used a more structured problem-solving strategy than participants used to the non-interactive support. Consequences for system design are discussed.     

Study of generalized delay-timers in alarm configuration

In process plants, alarms are configured to notify operators of any abnormalities or faults. However, in practice a majority of raised alarms are false or nuisance and create problems for operators as they face an increasing number of alarms to handle. Adding delay-timers is a simple technique that can reduce this problem and is widely exercised in industry. In this work we propose a generalized delay-timer framework where instead of consecutive n samples in the conventional case, n₁ out of n consecutive samples (n₁ ≤ n) are considered to raise an alarm. For the generalized delay-timer, three important performance indices, namely, the false alarm rate (FAR), the missed alarm rate (MAR) and the expected detection delay (EDD), are calculated using Markov processes. Moreover, the performance and sensitivity of generalized delay-timers are compared with conventional delay-timers.     

LADAR target detection using morphological shared-weight neural networks

Morphological shared-weight neural networks (MSNN) combine the feature extraction capability of mathematical morphology with the function-mapping capability of neural networks in a single trainable architecture. The MSNN method has been previously demonstrated using a variety of imaging sensors, including TV, forward-looking infrared (FLIR) and synthetic aperture radar (SAR). In this paper, we provide experimental results with laser radar (LADAR). We present three sets of experiments. In the first set of experiments, we use the MSNN to detect different types of targets simultaneously. In the second set, we use the MSNN to detect only a particular type of target. In the third set, we test a novel scenario, referred to as the Sims scenario: we train the MSNN to recognize a particular type of target using very few examples. A detection rate of 86% with a reasonable number of false alarms was achieved in the first set of experiments and a detection rate of close to 100% with very few false alarms was achieved in the second and third sets of experiments. In all the experiments, a novel pre-processing method is used to create a pseudo-intensity images from the original LADAR range images.     

和差式相位测向法在吊放声纳改进中的运用研究

国内某型吊放声纳在模拟信号处理过程中存在操作复杂和测向精度不高等问题,早期和差式相位测向法需要复杂的显示系统,对人员的操作要求较高,并且误差较大。通过分析影响吊放声纳测向的因素,在模拟处理转变为数字信号处理技术后,基于和差式相位测向原理,同时引入恒虚假检测以及目标参数估计等后处理算法流程,可直接精确地计算出目标方位,降低了对操作技能的要求,最终确定数字化改造的方向,为早期模拟吊放声纳装备性能改进提供了依据和参考。     

Three-dimensional auditory display for enhancing detection of passive sonar signals

OBJECTIVE: The viability of a three-dimensional (3-D) auditory display for improving signal detection of passive sonar signals was investigated. BACKGROUND: Sonar operators usually have difficulty detecting targets because the sound received by the hydrophone has a low signal-to-noise ratio when coupled with the operator's headset that does not isolate well against the ambient noise. METHODS: Release from masking was assessed by pairing a recording of a torpedo with diotic broadband pink noise that served as a masker, and a 400 Hz tone with the masker. Masked thresholds were measured for seven signal durations when each signal was presented dioticly and in 3-D auditory space at three positions on the horizontal plane. RESULTS: The spatial separation of signal and masker yielded a significant improvement in detection. CONCLUSION: A 3-D auditory display is a viable technology that could lead to a significant improvement in release from masking. The magnitude of the masking level difference will vary with respect to the characteristics of the hydrophone signal and masker and the synthesis capability of the 3-D auditory display. APPLICATION: Potential applications of this research include enhanced auditory displays for processing passive sonar signals, leading to earlier detection of enemy targets.     

Training for Vigilance: Repeated Sessions with Knowledge of Results

Abstract

Two groups of subjects were run in a visual monitoring test, one with knowledge of results (KR) providing instant feedback of correct responses, commissive errors, and missed signals, and the other with no knowledge of results (NKR). The groups were run for five 48-minute sessions on consecutive days, with a follow-up transfer session five weeks later. Results showed significant differences in detection rates between the groups on all five training sessions, but not on the transfer session. Detection rates increased significantly during the five training sessions for both groups, and at approximately the same rate. Commissive errors were significantly different only in the first two training sessions, with the KR subjects showing more false alarms. Commissive errors did not increase or decrease over time within sessions, or over the five training sessions.     

Scale invariant small target detection by optimizing signal-to-clutter ratio in heterogeneous background for infrared search and track

This paper presents a novel mathematical method for incoming target detection in a cluttered background motivated by the robust properties of the human visual system (HVS). The robust detection of small targets is very important in IRST (Infrared Search and Track) applications for self-defense or attacks. HVS shows the best efficiency and robustness for the task of object detection in cluttered backgrounds. The robust properties of HVS include the contrast mechanism of figure-ground, multi-resolution representation of an object, size adaptation of object boundary, and pop-out phenomena in a complex environment. Based on these facts, a plausible computational model integrating these facts is proposed using Laplacian scale-space theory and an optimization method. Simultaneous target signal enhancement and background clutter suppression are achieved by tuning and maximizing the signal-to-clutter ratio (TM-SCR) in Laplacian scale-space. At the first stage, Tune–Max of the signal to background contrast produces candidate targets with estimated target scale. At the second stage, Tune–Max of the signal-to-clutter ratio (SCR) produces maximal SCR that is used to sort the detection results. Especially, the row-directional-local background removal filter (RD-LBRF) is preprocessed in the horizontal region to enhance the TM-SCR method. The evaluation results of incoming target sequence validate the detection capability of the proposed method from dim, small targets to strong, large targets in comparison with the Top-hat method at the same rate of false alarms. The experimental results of various cluttered background images show that the proposed TM-SCR produces less false alarms (4.3 times reduction) compared to that of the Top-hat at the same detection rate. Finally, TM-SCR after RD-LBRF can maximize the detection rate in horizontal regions.