Summative evaluation of the SINCGARS Tutor

In an earlier set of studies with a different Intelligently Coached Simulation (Orey, M.A., Fan, H., Park, J., Tzeng, S., & Gustafson, K. (1995). Evaluation of Device operator in a context of a coached simulation environment), we found a retention and a transfer problem. We tried to solve these problems while building a new Intelligently Coached Simulation (the SINCGARS Tutor). The solutions to the two problems were to use an interactive conceptual model for the retention problem and we used photographs of the equipment as the visuals of the simulation. We then tested this new tutor with a group of 22 officers who were not only required to know how to operate the SINCGARS radio, but would be responsible for teaching others in their unit when their training was complete. We had one group of officers train on the real equipment, in pairs, with one instructor available for guidance. The other group of 11 learned via the SINCGARS Tutor. The post test was to put an actual radio into operation while being observed by a trained observer. Results indicate that not only did the transfer problem go away, but officers trained on the computer performed the task more accurately both initially on the immediate post test and again on a surprise four-week delayed post test. The SINCGARS Tutor was found to be a very good training solution.     

Motivational and cognitive benefits of training in immersive virtual reality based on multiple assessments

The main objective of this study was to examine the effectiveness of immersive virtual reality (VR) as a medium for delivering laboratory safety training. We specifically compare an immersive VR simulation, a desktop VR simulation, and a conventional safety manual. The sample included 105 first year undergraduate engineering students (56 females).  We include five types of learning outcomes including post‐test enjoyment ratings; pre‐ to post‐test changes in intrinsic motivation and self‐efficacy; a post‐test multiple choice retention test; and two behavioral transfer tests. Results indicated that the groups did not differ on the immediate retention test, suggesting that all three media were equivalent in conveying the basic knowledge. However, significant differences were observed favoring the immersive VR group compared to the text group on the two transfer tests involving the solving problems in a physical lab setting (d = 0.54, d = 0.57), as well as enjoyment (d = 1.44) and increases in intrinsic motivation (d = 0.69) and self‐efficacy (d = 0.60). The desktop VR group scored significantly higher than the text group on one transfer test (d = 0.63) but not the other (d= 0.11), as well as enjoyment (d =1.11) and intrinsic motivation (d =0.83).     

Reality-based practice under pressure improves handgun shooting performance of police officers

The current study examined whether reality-based practice under pressure may help in preventing degradation of handgun shooting performance under pressure for police officers. Using a pre–post–test design, one group of nine police officers practised handgun shooting under pressure evoked by an opponent who also fired back using marking (coloured soap) cartridges. The control group (n = 8) practised handgun shooting on standard cardboard targets instead of real opponents. Within a fortnight after the pre-test, both groups received three training sessions of 1 h, in which each person fired a total of 72 rounds. During the pre- and post test each participant took 30 shots without pressure (cardboard targets) and 30 shots under additional pressure (with an opponent firing back). While during the pre-test both groups performed worse in front of an opponent firing back compared to the cardboard targets, after the training sessions shooting performance of the experimental group no longer deteriorated with an opponent while performance of the control group was equally harmed as during the pre-test. These results indicate that training exercises involving increased pressure can acclimatize shooting performance of ordinary police officers to those situations with elevated pressure that they may encounter during their police work.     

Massed versus distributed wordprocessor training

Two groups of subjects were trained on 12 basic word processing (WP) functions. One group was trained in a 'massed' 60-minute session and the other on a 'distributed' schedule of 60 min in two sessions separated by a ten-minute break. Subjects were tested on speed and accuracy immediately after training, and one week later to measure retention. It was found that the distributed training group performed significantly faster and more accurately than the massed group. This result was obtained at the end of the training period and also on the retention test. The results strongly indicate that a session of 60 min is too long for efficient WP training.     

Police arrest and self-defence skills: performance under anxiety of officers with and without additional experience in martial arts

We investigated whether officers with additional martial arts training experience performed better in arrest and self-defence scenarios under low and high anxiety and were better able to maintain performance under high anxiety than officers who just rely on regular police training. We were especially interested to find out whether training once a week would already lead to better performance under high anxiety. Officers with additional experience in kickboxing or karate/jiu-jitsu (training several times per week), or krav maga (training once a week) and officers with no additional experience performed several arrest and self-defence skills under low and high anxiety. Results showed that officers with additional experience (also those who trained once a week) performed better under high anxiety than officers with no additional experience. Still, the additional experience did not prevent these participants from performing worse under high anxiety compared to low anxiety. Implications for training are discussed.     

The effect of training systemic information on the retention of fault‐finding skills in manufacturing industries

This study examines how the process of skill retention (including both recall and reconstruction) can benefit from systemic training information that covers several structural, functional, physical (e.g., causal links), and supervisory features (e.g., system control and instrumentation). An experiment was carried out in which a group of participants who received systemic information was compared to a group trained in plant theory and to another three groups trained in heuristics that ranged in terms of high‐ and low‐level diagnostic information. Learning curves revealed that all groups achieved high accuracy scores in diagnosing faults in a distillation plant. Six weeks later, a retention test showed that the systemic group (S) had a better recall score than the groups trained in theory (T) and high‐level heuristics (HH). In addition, the S group had a better reconstruction score than the groups receiving the high‐ and low‐level heuristics (H+) and the low‐level diagnostic information (HL). An interesting finding was that high‐level diagnostic information seemed to support the reconstruction phase of the retention process, whereas low‐level information better supported the recall phase. Overall, it appeared that systemic information enabled trainees to acquire task cues to help recall and reconstruct diagnostic heuristics. © 2004 Wiley Periodicals, Inc. Hum Factors Man 14: 197–217, 2004.     

Studying a complex knowledge domain by exploration or explanation

Abstract  The teaching of complex knowledge domains should not be restricted to linear explanations but instead should allow the learner to travel through domains along different routes. Simulation programs provide a microworld in which the user has the freedom to explore the embedded concepts and relations by manipulating parameters and studying the resulting changes in the simulation environment. In this study two experiments were conducted to investigate the educational value of a simulation program modelling the relations between erosion and agriculture in a developing country as part of the secondary school geography curriculum. The hypothesis tested was that studying the complex domain through exploration with a simulation program decreases the retention of facts and concepts but increases performance on a problem solving test, compared with studying the same domain through traditional classroom explanation. The first experiment showed that the exploration group outperformed the explanation group on both factual knowledge and problem solving questions. A second experiment was run to control instruction time for both groups and to add a demonstration of the simulation program to the explanation condition. Under these conditions there were no post-test differences between the explanation and the exploration group. It is hypothesized that training in how to use a simulation environment to study a domain is necessary to take full advantage of the facilities to explore the domain.     

Reality-based practice under pressure improves handgun shooting performance of police officers

The current study examined whether reality-based practice under pressure may help in preventing degradation of handgun shooting performance under pressure for police officers. Using a pre-post-test design, one group of nine police officers practised handgun shooting under pressure evoked by an opponent who also fired back using marking (coloured soap) cartridges. The control group (n = 8) practised handgun shooting on standard cardboard targets instead of real opponents. Within a fortnight after the pre-test, both groups received three training sessions of 1 h, in which each person fired a total of 72 rounds. During the pre- and post test each participant took 30 shots without pressure (cardboard targets) and 30 shots under additional pressure (with an opponent firing back). While during the pre-test both groups performed worse in front of an opponent firing back compared to the cardboard targets, after the training sessions shooting performance of the experimental group no longer deteriorated with an opponent while performance of the control group was equally harmed as during the pre-test. These results indicate that training exercises involving increased pressure can acclimatize shooting performance of ordinary police officers to those situations with elevated pressure that they may encounter during their police work.     

基于分布和逆文本类别指数的特征迁移加权算法

传统机器学习面临一个难题,即当训练数据与测试数据不再服从相同分布时,由训练集得到的分类器无法对测试集文本准确分类。针对该问题,根据迁移学习原理,在源领域和目标领域的交集特征中,依据改进的特征分布相似度进行特征加权;在非交集特征中,引入语义近似度和新提出的逆文本类别指数(TF-ICF),对特征在源领域内进行加权计算,充分利用大量已标记的源领域数据和少量已标记的目标领域数据获得所需特征,以便快速构建分类器。在文本数据集20Newsgroups和非文本数据集UCI中的实验结果表明,基于分布和逆文本类别指数的特征迁移加权算法能够在保证精度的前提下对特征快速迁移并加权。     

某型制导炸弹训练弹模拟检测控制台设计

介绍了某型制导炸弹训练弹模拟检测控制系统的设计与实现方法,给出了基于PC/104总线的模拟检测控制方案,详细论述了该系统的硬件及软件模块的设计,解决了部队替代实装进行维护使用训练的问题,具有操作简单,模拟控制信号精确,检测迅速准确,可扩展性强等特点.     

基于模型的虚实结合的仿真试验技术

针对大型无人机系统复杂度高、多学科耦合强以及传统研发模式下的装备研发周期和成本快速增长的特点,为满足在地面半物理试验验证中最大程度降低迭代周期和成本的需求,设计了一种基于模型的虚实结合的地面半物理仿真试验技术。通过开展多源异构模型分布式集成技术研究,解决了跨专业飞机系统仿真模型联合仿真的难题。将仿真模型用于地面半物理试验,实现了试验环境中机载总线、仿真总线和射频网络的三网并行,进而实现机载设备和仿真模型信息交互,设计了一套针对虚实结合试验的自动化测试体系,提升了试验验证效率。通过建立一套完整的虚实结合试验的验证架构,提升了大型无人机鉴定能力,有效提升了航空武器装备研发质量、效率和水平,具有重大军事意义和社会意义。     

Complexity reduction for "large image" processing

We present a method for sampling feature vectors in large (e.g., 2000 /spl times/ 5000 /spl times/ 16 bit) images that finds subsets of pixel locations which represent c "regions" in the image. Samples are accepted by the chi-square (/spl chi//sup 2/) or divergence hypothesis test. A framework that captures the idea of efficient extension of image processing algorithms from the samples to the rest of the population is given. Computationally expensive (in time and/or space) image operators (e.g., neural networks (NNs) or clustering models) are trained on the sample, and then extended noniteratively to the rest of the population. We illustrate the general method using fuzzy c-means (FCM) clustering to segment Indian satellite images. On average, the new method can achieve about 99% accuracy (relative to running the literal algorithm) using roughly 24% of the image for training. This amounts to an average savings of 76% in CPU time. We also compare our method to its closest relative in the group of schemes used to accelerate FCM: our method averages a speedup of about 4.2, whereas the multistage random sampling approach achieves an average acceleration of 1.63.     

基于打印口的无线测控装置设计

分析了打印口的I/O特性;叙述了基于打印口的信息传送,用于“高炮激光射击训练模拟器”中各类信号遥测、遥控的无线测控装置设计实例。这个设计实例为野外军事训练装备的小型化和便携性,为笔记本电脑(不能扩充I／0板)用于实时检测和控制开拓一条途径。该装置设计性能在笔者研制开发的“高炮激光射击训练模拟器”项目上得到验证,并收到较好的效果。     

浅议创新发展士官任职教育培训机制

随着新军事变革的日益深入,军队职业化的趋势越来越明显。在我军现代化建设中,大量的新装备要靠士官来操作,这对士官任职能力提出了更高的要求。士官院校要充分发挥培训主渠道的作用,为了尽快提高士官的操作能力,对创新士官任职教育培训机制发表了相关见解。     

基于VRML的分布式装备维修仿真训练系统

在装备维修训练方面，仿真系统发挥着极为重要的作用，该文将虚拟现实技术应用于装备维修仿真训练中，建立了分布式装备维修仿真训练系统，系统可实现虚拟装备的生成，动态仿真及与数据库的关联等，有效地提高了装备仿真训练的水平。文中介绍了系统的工作流程，系统实现的若干关键技术及系统运行典型实例。     

Retention of trained performance in consistent mapping search after extended delay.

We examined the retention of performance in memory, visual, and hybrid memory/visual search after subjects received extensive consistent mapping (CM) practice. In the first two experiments we examined retention of detection performance in memory scanning (Experiment 1) and in visual search (Experiment 2) approximately one month after training. In the third experiment we examined performance 1, 30, 90, 180, and 365 days following training on pure visual and hybrid memory/visual semantic-category search tasks. We examined retention at intervals up to one year after practice as a function of amount of CM practice. In addition, we assessed the degree of category activation (performance on untrained words from the trained categories) at each retention interval. Across experiments, we found no decay in CM trained memory search and minimal decay in pure visual search. Significant decline in CM performance was largely attributable to performance in the hybrid memory/visual search conditions. These data reconcile previously equivocal retention results for CM trained search performance.     

车载信息仿真与测试系统研究

传统的串行开发模式制约车载信息系统的开发。为此,通过对车载设备和车载操作系统进行仿真,获取设备通信履历,实现一种基于消息的车载信息仿真与测试系统。该系统通过实时获取车载设备的运行信息,对车载设备的运行情况进行监控。仿真实验结果证明,该系统可有效降低开发的错误率,实现车载信息系统的并行开发和测试。     

A simple learning environment improves mathematical reasoning

Abstract

ANIMATE, an interactive computer animation-based tutor, has been developed as part of an on-going test of a theory of word problem comprehension. Tutor feedback is unobtrusive and interpretive: unexpected behavior in the equation-driven animation of a situation highlights equation errors which the student resolves through iterative debugging. The student has responsibility for learning, goal-setting and diagnosis. Experimental controls (n = 96) with Motion problems show that improvement cannot be solely attributed to practice, computer use, or use of the situation-based method. Concurrent think-aloud protocols of students (n = 7) solving Motion, Work and Investment problems over two days (in a pretest-posttest design) uncover specific changes which underlie these improvements. ANIMATE is an effective problem-solving aid, and there is transfer of learning. Problems with impossible situations were acknowledged by median-level subjects (posttest scores between 77% and 85%), but solved blindly by high-level subjects (post test scores > = 95%), suggesting an automatically controlled processing dichotomy. On Day 2, subjects spent more time reviewing problem texts and correcting flawed expressions. They developed self-directed debugging skills, reminiscent of expert problem-solving in many domains, without relying on tutor feedback behaviors. The system is unintelligent by ITS standards but communicates knowledge to the students, helping them teach themselves approaches for mathematical problem-solving.     

"弹性"BP神经网络在识别带有噪声字母中的应用

字符识别是模式识别中的一个典型应用,通过训练网络可以教会计算机如何识别字符,这在票据处理方面可以大大地提高效率.该文中所建立的神经网络具有Sigmoid型可微函数的三层BP神经网络,它可以以任意精度逼近任何连续函数,实现输入和输出之间的任意非线性映射.文中分析了BP神经网络的“弹性”学习算法,利用五位二进制数来识别的输出26种状态.建立的一个三层的BP神经网络能对带有噪声的26个英文大写字母进行识别.利用MATLAB编写仿真程序对BP神经网络进行训练,仿真结果表明训练的BP神经网络可以对给定的带有噪声的字母正确地识别.     

Application of fuzzy ARTMAP and fuzzy <Emphasis Type="Italic">c</Emphasis>-means clustering to pattern classification with incomplete data

In this paper, a hybrid neural network that is capable of incremental learning and classification of patterns with incomplete data is proposed. Fuzzy ARTMAP (FAM) is employed as the constituting network for pattern classification while fuzzy c-means (FCM) clustering is used as the underlying algorithm for processing training as well as test samples with missing features. To handle an incomplete training set, FAM is first trained using complete samples only. Missing features of the training samples are estimated and replaced using two FCM-based strategies. Then, network training is conducted using all the complete and estimated samples. To handle an incomplete test set, a non-substitution FCM-based strategy is employed so that a predicted output can be produced rapidly. The performance of the proposed hybrid network is evaluated using a benchmark problem, and its practical applicability is demonstrated using a medical diagnosis task. The results are compared, analysed and quantified statistically with the bootstrap method. Implications of the proposed network for pattern classification tasks with incomplete data are discussed.