Variant versus invariant time to total forgetting: the learn–forget curve model revisited

Understanding and quantifying the learning–forgetting process helps predict the performance of an individual (or a group of individuals), estimate labor costs, bid on new and repeated orders, estimate costs of strikes, schedule production, develop training programs, set time standards, and improve work methods [IIE Trans. 29 (1997) 759]. Although there is agreement that the form of the learning curve is as presented by [J. Aeronaut. Sci. 3 (1936) 122], scientists and practitioners have not yet developed a full understanding of the behavior and factors affecting the forgetting process. The paucity of research on forgetting curves has been attributed to the practical difficulties involved in obtaining data concerning the level of forgetting as a function of time [IIE Transactions 21 (1989) 376]. The learn–forget curve model (LFCM) was shown to have many advantages over other theoretical models that capture the learning–forgetting relationship. However, the deficiency of the LFCM is in the assumption that the time for total forgetting is invariant of the experience gained prior to interruption. This paper attempts to correct this deficiency by incorporating the findings of [Int. J. Ind. Ergon. 10 (1992) 217] into the LFCM. Numerical examples are used to illustrate the behavior of the modified LFCM (MLFCM) and compare results to those of the LFCM.     

One-Dimensional Continuous-Time Quantum Walks

We survey the equations of continuous-time quantum walks on simple one-dimensional lattices, which include the finite and infinite lines and the finite cycle, and compare them with the classical continuous-time Markov chains. The focus of our expository article is on analyzing these processes using the Laplace transform on the stochastic recurrences. The resulting time evolution equations, classical vs. quantum, are strikingly similar in form, although dissimilar in behavior. We also provide comparisons with analyses performed using spectral methods. PACS: 03.67.Lx     

Evolving modular networks with genetic algorithms: application to nonlinear time series

Abstract: A key problem of modular neural networks is finding the optimal aggregation of the different subtasks (or modules) of the problem at hand. Functional networks provide a partial solution to this problem, since the inter‐module topology is obtained from domain knowledge (functional relationships and symmetries). However, the learning process may be too restrictive in some situations, since the resulting modules (functional units) are assumed to be linear combinations of selected families of functions. In this paper, we present a non‐parametric learning approach for functional networks using feedforward neural networks for approximating the functional modules of the resulting architecture; we also introduce a genetic algorithm for finding the optimal intra‐module topology (the appropriate balance of neurons for the different modules according to the complexity of their respective tasks). Some benchmark examples from nonlinear time‐series prediction are used to illustrate the performance of the algorithm for finding optimal modular network architectures for specific problems.     

A study of learning time patterns in asynchronous learning environments

Abstract This research makes use of learning time intensity, burst evaluating equations, and state denotation approaches to evaluate the learning time characteristics of students. Through comparing learning time intensity, six burst styles and three diligence styles are categorized. From the statistical results and interaction content analysis, some pedagogical phenomena were found. The first finding is that the more diligent learners were, the higher the quality and quantity of their interaction. The second is that learners whose learning time intensity was mainly located in the early period of the course and whose interaction content included many complaints were suspected to be possible dropouts. The third finding is that learners whose learning time intensity was mainly located in the later period had achievements that were significantly different from those of the regular periodical reading learners whose learning time intensity was distributed in all periods of the course. The above findings raise some issues and suggestions for those concerned with proposing asynchronous courses. As students can pace their own learning in an asynchronous learning environment, it is hard to avoid getting used to intermittent intensive reading. Instructors should consider seriously how to guide students to learn in a proper sequence through a well‐scheduled instructional programme. It is necessary to encourage students to exercise self‐discipline in regular on‐line reading for better learning outcomes.     

Short cycle time systems development

Abstract. An analysis of two studies in the US and Denmark reveals that short cycle time systems development is a new form that can be clearly distinguished among other forms. The distinction consists of a package of five systems development practices. These practices include a focus on completion speed, release‐oriented parallel prototyping, adherence to a fixed architecture, negotiable quality, and an ideal workforce. The package is consistent with amethodical development concepts. Systems are not built in a single project that completes with a delivery, but rather are continually ‘growing’ to adapt to an organizational emergence.     

An integrated real time MRP and group technology system

The approach taken in this paper is twofold. First manufacturing environment is simplified for the purposes of planning and control without losing any of the essential characteristics. Second, a simple GT model is applied to the shop floor area and real time MRP is applied to the assembly area. The aim of this study is to develop and compare with a simulation of similar proposal except that jobshop is used in the shop floor area instead. The variable factors in both models were the set up time to operation time ratio and the intensity of the loading on the machines. In the highly loaded situations, the GT model faired better than the job shop model. However, for low loaded situations the performances of the two models were similar.     

SCADA系统及其在风力发电场的应用

详细介绍了SCADA系统的设计、功能及其特点，并以SCADA系统为平台设计了可以实现实时监控并且具有巨大潜在经济效益的风力发电场。     

BLDC位置伺服系统的离散变结构控制

针对离散变结构控制系统的抖振，在离散趋近率的基础上，提出了一种扰动动态补偿的离散趋近率，设计了离散变结构控制(DVSC)策略，研究了变结构控制系统的鲁棒性能，应用于无刷直流电动机(BLDC)位置伺服系统。理论推导与仿真实验表明：新的离散变结构控制策略可以明显改善系统的品质，增强系统的鲁棒性。     

包装管理课程教学改革的实践

对包装管理教学中存在的一些问题进行了改进,通过教学实践,使学生了解和掌握现代化企业管理中的生产管理模式、科学的管理方法、先进制造技术,以及充分包装与物流的关系,从课程和教学方法上提出了一些方法.     

结构动力响应数值分析的新的广义-α方法的频率域分析

介绍了一族用于结构动力响应数值计算的新的广义-α方法。用这族算法将结构动力学方程离散得到关于位移的差分方程，然后做Z-变换得到算法传递函数、算法频率响应函数。通过算法离散的频率响应和系统真实频率响应的比较，在频率域内分析了这族算法的性能，并与常用的Newmark平均加速度方法进行了比较。在分析中，以激励力频率为自变量分析了算法的Bode图，以系统固有频率和激励力频率与时间步长的乘积为自变量在三维空间内分析了算法频率响应幅值绝对误差，又以算法自由参数、阻尼比为自变量在三维空间内分析了算法频率响应幅值2-范数意义下的相对误差。结果表明，新算法的性能得到了更深刻的认识。