General Learning Effect Research Articles

Minimization of maximum lateness in an m-machine permutation flow shop with a general exponential learning effect

In this paper, we consider the permutation flow shop scheduling problem with a general exponential learning effect. The objective is to minimize the maximum lateness. A special case that can be solved to optimality by EDD algorithm is provided. To form a hybrid solution framework, several heuristics, a branch-and-bound algorithm and a new Nested-Partition-based solution approach are proposed. Composite bounds and dominance rules are developed to reduce the searching region and to provide guidance on the lower bound. Finally, computational experiments are conducted to evaluate the performance of the algorithms.

Discriminative evaluative conditioning in the long-term after severe accidental injury

Impairments in classical fear conditioning and deficits in discriminative learning are observed in posttraumatic stress disorder (PTSD). However, it is unknown whether similar impairments can be found with types of discriminative learning other than classical conditioning, such as evaluative conditioning (EC), in which the valence of a stimulus can be transferred to other stimuli. In this study, we investigated whether EC is also influenced by traumatic experiences independently of presence of PTSD. We tested 14 accident survivors with remitted PTSD, 14 survivors without PTSD, and 16 non-trauma controls. We used behavioral measures, psychophysiological indicators, and subjective ratings for tasks. General effects of learning were observed across groups and conditioning/extinction. Trauma controls had slower reaction times (RTs) to the aversive conditioned stimulus compared to appetitive conditioned and neutral stimuli, as well as slower RTs and increased accuracy during conditioning than during extinction. Remitted PTSD participants showed opposite results, demonstrating decreased accuracy and slower RTs during conditioning as compared to during extinction. No discriminative effect was found in the non-trauma controls and the remitted PTSD participants. These results suggest that a traumatic experience influences EC, and that this influence differs between individuals who have and have not developed PTSD after traumatic exposure.

Resource constrained scheduling with general truncated job-dependent learning effect

Scheduling with general truncated job-dependent learning effect and resource-dependent processing times is studied on a single machine. It is assumed that the job processing time is a function of the amount of resource allocated to the job, the general job-dependent learning effect and the job-dependent control parameter. For each version of the problem that differs in terms of the objective functions and the processing time functions, the optimal resource allocation is provided. Polynomial time algorithms are also developed to find the optimal schedule of several versions of the problem.

Music therapy as specific and complementary training for adults after cochlear implantation: A pilot study

ObjectivesAlthough cochlear implant (CI) users achieve good speech comprehension, they experience difficulty perceiving music and prosody in speech. As the provision of music training in rehabilitation is limited, a novel concept of music therapy for rehabilitation of adult CI users was developed and evaluated in this pilot study.MethodsTwelve unilaterally implanted, postlingually deafened CI users attended ten sessions of individualized and standardized training. The training started about 6 weeks after the initial activation of the speech processor. Before and after therapy, psychological and musical tests were applied in order to evaluate the effects of music therapy. CI users completed the musical tests in two conditions: bilateral (CI + contralateral, unimplanted ear) and unilateral (CI only).ResultsAfter therapy, improvements were observed in the subjective sound quality (Hearing Implant Sound Quality Index) and the global score on the self-concept questionnaire (Multidimensional Self-Concept Scales) as well as in the musical subtests for melody recognition and for timbre identification in the unilateral condition.DiscussionPreliminary results suggest improvements in subjective hearing and music perception, with an additional increase in global self-concept and enhanced daily listening capacities.ConclusionsThe novel concept of individualized music therapy seems to provide an effective treatment option in the rehabilitation of adult CI users. Further investigations are necessary to evaluate effects in the area of prosody perception and to separate therapy effects from general learning effects in CI rehabilitation.

Some Scheduling Problems on a Single Machine with General Job Effects of Position-Dependent Learning and Start-Time-Dependent Deterioration

Job learning and deterioration coexist in many realistic machine-job scheduling situations. However, in literature, the constructed forms of the machine scheduling models with job learning and/or deteriorating effects were specific types of functions, which constrained their applicability in practice. This paper introduces a new single-machine scheduling model, where the actual processing time of a job is a general function of its starting time as well as scheduled position, which shows a broad generalization in contrast to that of certain existing models. For three objectives corresponding to the single-machine scheduling problem–total weighted completion time, discounted total weighted completion time, and maximum lateness — this paper presents their respective approximation result on the basis of the worst-case bound analysis from the optimal algorithm. The results demonstrate that under our proposed model, minimization of scheduling operations such as the makespan, sum of the kth power of completion times, and total lateness are polynomially solvable. Moreover, under some feasible conditions for the scheduling parameters, the minimum optimization problems of the total weighted completion time, discounted total weighted completion time, maximum lateness, and total tardiness are all recognized as polynomial forms and their solutions are provided.

A Note on Scheduling Jobs with Extended Sum-of-Processing-Times-Based and Position-Based Learning Effect

The note deals with machine scheduling problems with a more general learning effect model, i.e., the actual job processing time is a function of the sum of the function of the processing times of the jobs already processed and job position. We show that some single machine scheduling problems are still polynomially solvable under the proposed model. We also show that some special cases of the flow shop scheduling problems can be solved in polynomial time.

Research on scheduling problems with general effects of deterioration and learning

Jobs with deterioration and learning effect co-exist in many industry engineering and logistics management situations. In this note, the general effects of deterioration and learning are considered. It is proved that some single machine scheduling problems are still polynomially solvable under the proposed model. The note also shows that some results in Lee and Lai’s recent paper (Lee and Lai, 2011) are incorrect by a counterexample.

Single-Machine Group Scheduling Problems with Variable Job Processing Times

This paper considers two resource constrained single-machine group scheduling problems. These problems involve variable job processing times (general position-dependent learning effects and deteriorating jobs); that is, the processing time of a job is defined by the function that involves its starting time and position in the group, and groups’ setup time is a positive strictly decreasing continuous function of the amount of consumed resource. Polynomial time algorithms are proposed to optimally solve the makespan minimization problem under the constraint that the total resource consumption does not exceed a given limit and the total resource consumption minimization problem under the constraint that the makespan does not exceed a given limit, respectively.

Cluster subtypes of the Spanish version of the California Verbal Learning Test in a sample of adults with subjective memory complaints

We examined subtypes of learning and memory by administering the California Verbal Learning Test (CVLT) to a sample of adults with memory complaints that included a subsample of healthy controls and another of participants with amnesic mild cognitive impairment. We performed two-stage cluster analyses for CVLT variables representing three main factors—General Verbal Learning, Inaccurate Memory, and Serial Effect. Four, three, and two reliable subtypes were differentiated in the total sample and in the two subsamples, respectively. Gender, age, education, reading habits, vocabulary, memory complaints, and general cognitive performance were meaningfully related to variability in the performance of the subtypes.

Flowshop scheduling with a general exponential learning effect

This paper investigates flowshop scheduling problems with a general exponential learning effect, i.e., the actual processing time of a job is defined by an exponent function of the total weighted normal processing time of the already processed jobs and its position in a sequence, where the weight is a position-dependent weight. The objective is to minimize the makespan, the total (weighted) completion time, the total weighted discounted completion time, and the sum of the quadratic job completion times, respectively. Several simple heuristic algorithms are proposed in this paper by using the optimal schedules for the corresponding single machine problems. The tight worst-case bound of these heuristic algorithms is also given. Two well-known heuristics are also proposed for the flowshop scheduling with a general exponential learning effect.

Research on permutation flow shop scheduling problems with general position-dependent learning effects

Machine learning exists in many realistic scheduling situations. This study focuses on permutation flow shop scheduling problems, where the actual processing time of a job is defined by a general non-increasing function of its scheduled position, i.e., general position-dependent learning effects. The objective functions are to minimize the total completion time, the makespan, the total weighted completion time, and the total weighted discounted completion time, respectively. To solve these problems, we present approximation algorithms based on the optimal permutations for the corresponding single machine scheduling problems and analyze their worst-case error bound.

P 161. State-dependency of tDCS-induced plasticity in the motor cortex

Transcranial direct current stimulation (tDCS) is a non-invasive technique that can induce LTP/LTD-like plasticity in the stimulated area ( Fritsh, 2010 ). The electrical field generated by the stimulation modulates cortical activity according to polarity of the current: anodal stimulation (A-tDCS) has been shown to increase cortical excitability and cathodal stimulation (C-tDCS) to decrease cortical excitability ( [Bindman, 1964] , [Nitsche and Paulus, 2000] ). In this study we have combined tDCS with motor practice in order to evaluate if tDCS may enhance plasticity and learning through gating mechanisms or may trigger compensatory mechanisms of metaplasticity ( [Ziemann and Siebner, 2008] , [Pozo and Goda, 2010] ). To this aim, we ran two experiments: in the first experiment, the motor practice (MP) task consisted of fast thumb abduction movements (F-MP) of the left hand, which induce learning ( Muellbacher, 2002 ). In the second experiment, the motor practice task consisted of slow thumb abduction movements (S-MP), which do not induce learning. In both experiments, six blocks of MP (corresponding to 20 min) were performed while tDCS was delivered at 1.5 mA (electrode surface 25 cm 2 ; current density 0.06 mA/cm 2 ) on contralateral M1. Moreover, two blocks with fast thumb abduction were performed, one before and one after tDCS application. Peak acceleration in the fast thumb abduction blocks was used as measure of performance. Results showed a general learning effect when participants performed the F-MP task. Moreover, learning rates varied across stimulation conditions. A-tDCS reduced performance compared to sham in the early phase of learning, and C-tDCS increased performance compared to A-tDCS in the latter phase of learning. When participants performed the S-MP task, performance improved after A-tDCS, whereas no learning effect was found in the sham stimulation condition. Therefore, our results highlight that tDCS-induced plasticity in the motor cortex is state-dependent: When applied during a MP task that does not induce learning, A-tDCS increased performance. When applied during motor learning, A-tDCS interfered with performance, suggesting that the concurrent combination of tDCS with another plasticity-inducing protocol may trigger compensatory mechanisms of metaplasticity.

One-machine scheduling problems with deteriorating jobs and position-dependent learning effects under group technology considerations

In this paper, we introduce a group scheduling model with general deteriorating jobs and learning effects in which deteriorating jobs and learning effects are both considered simultaneously. This means that the actual processing time of a job depends not only on the processing time of the jobs already processed, but also on its scheduled position. In our model, the group setup times are general linear functions of their starting times and the jobs in the same group have general position-dependent learning effects and time-dependent deterioration. The objective of scheduling problems is to minimise the makespan and the sum of completion times, respectively. We show that the problems remain solvable in polynomial time under the proposed model.

Scheduling with a general learning effect

Jobs with different processing complexity may have different effects on human learning, which in turn will affect the job processing times. So, the learning effect on job processing times in scheduling is not only sum-of-processing-time-based and job-position-based, but also depends on the processing complexity of the jobs already processed. We introduce in this paper a general learning effect model for scheduling. We provide some properties that are helpful for finding the optimal solutions for some single-machine and flowshop scheduling problems under the general effect model.

Single-machine group scheduling with a general learning effect

This paper investigates some single-machine scheduling problems with a general learning effect and the group technology assumption. A setup time is incurred whenever the single machine transfers job processing from a family to another family. By the general learning effect, we mean that the actual group setup time depends not only on the total setup time of the groups already processed but also on its scheduled position, and the actual processing time of a job in a certain group depends not only on the total normal processing time of the jobs already processed in the group but also on its scheduled position. We show that the makespan minimisation problem remains polynomially solvable under the proposed models. We also show that the problems of minimising the total completion time, the total weighted completion time and the discounted total weighted completion time of all jobs have polynomial optimal solutions under certain conditions.

Stochastic scheduling problems with general position-based learning effects and stochastic breakdowns

The focus of this study is to analyze position-based learning effects in single-machine stochastic scheduling problems. The optimal permutation policies for the stochastic scheduling problems with and without machine breakdowns are examined, where the performance measures are the expectation and variance of the makespan, the expected total completion time, the expected total weighted completion time, the expected weighted sum of the discounted completion times, the maximum lateness and the maximum tardiness.

Single machine past-sequence-dependent delivery times scheduling with general position-dependent and time-dependent learning effects

This paper studies the single machine past-sequence-dependent (p-s-d) delivery times scheduling with general position-dependent and time-dependent learning effects. By the general position-dependent and time-dependent learning effects we mean that the actual processing time of a job is not only a function of the total normal processing times of the jobs already processed, but also a function of the job’s scheduled position. We consider the following objective functions: the makespan, the total completion time, the sum of the θth (θ⩾0) power of job completion times, the total lateness, the total weighted completion time, the maximum lateness, the maximum tardiness and the number of tardy jobs. We show that the problems of minimization of the makespan, the total completion time, the sum of the θth (θ⩾0) power of job completion times and the total lateness can be solved by the smallest (normal) processing time first (SPT) rule, respectively. We also show that the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness minimization problem, the maximum tardiness minimization problem and the total tardiness minimization problem can be solved in polynomial time under certain conditions.

Scheduling problems with past-sequence-dependent setup times and general effects of deterioration and learning

In this paper we consider the single-machine setup times scheduling with general effects of deterioration and learning. By the general effects of deterioration and learning, we mean that the actual job processing time is a general function of the processing times of the jobs already processed and its scheduled position. The setup times are proportional to the length of the already processed jobs, i.e., the setup times are past-sequence-dependent (p-s-d). We show that the problems to minimize the makespan, the sum of the δth (δ>0) power of job completion times, the total lateness are polynomially solvable. We also show that the total weighted completion time minimization problem, the discounted total weighted completion time minimization problem, the maximum lateness (tardiness) minimization problem, the total tardiness minimization problem can be solved in polynomial time under certain conditions.

Scheduling jobs with a general learning effect model

The paper deals with machine scheduling problems with a general learning effect. By the general learning effect, we mean that the actual processing time of a job is not only a non-increasing function of the total weighted normal processing times of the jobs already processed, but also a non-increasing function of the job’s position in the sequence, where the weight is a position-dependent weight. We show that even with the introduction of a general learning effect to job processing times, some single machine scheduling problems are still polynomially solvable under the proposed model. We also show that some special cases of the flow shop scheduling problems can be solved in polynomial time.

Scripted collaborative learning with the cognitive tutor algebra

With the aim to promote students’ mathematics learning, we extended the Cognitive Tutor Algebra (CTA), a computer-based tutoring system for high school mathematics, to a collaborative setting. Furthermore we developed a collaboration script to support students’ interactions. In an experimental classroom study, we compared three conditions: scripted collaborative learning, unscripted collaborative learning, and individual learning. After a 2-day learning phase, posttests assessed individual and collaborative reproduction of knowledge and skills, and future learning. First, with the collaboration script we aimed to improve students’ interaction. Second, we assumed that due to an improved interaction students would benefit more from the learning opportunities during collaboration and, in consequence, their learning would increase as compared with the other conditions. To investigate the first assumption, we compared the interaction of a scripted dyad and an unscripted dyad. The in-depth process analyses revealed a positive impact of the script on student collaboration and problem solving during scripted interaction and in subsequent unscripted interaction. While this effect was mirrored in the learning gains of the two dyads, we could not establish a general learning effect in the quantitative between-condition comparison of student performance. Particularly for students with low prior knowledge, the removal of the script in the test phase initially entailed a decline in reproduction performance as students had to get used to the unscripted problem-solving situation. A notable finding was, however, that the collaborative conditions yielded the same outcomes as the individual condition in the individual reproduction test even though students had solved fewer problems during the learning phase and had only solved them collaboratively.