Accuracy In Terms Of Recall Research Articles

Involuntary and voluntary recall of musical memories: A comparison of temporal accuracy and emotional responses

Comparisons between involuntarily and voluntarily retrieved autobiographical memories have revealed similarities in encoding and maintenance, with differences in terms of specificity and emotional responses. Our study extended this research area into the domain of musical memory, which afforded a unique opportunity to compare the same memory as accessed both involuntarily and voluntarily. Specifically, we compared instances of involuntary musical imagery (INMI, or “earworms”)—the spontaneous mental recall and repetition of a tune—to deliberate recall of the same tune as voluntary musical imagery (VMI) in terms of recall accuracy and emotional responses. Twenty participants completed two 3-day tasks. In an INMI task, participants recorded information about INMI episodes as they occurred; in a VMI task, participants were prompted via text message to deliberately imagine each tune they had previously experienced as INMI. In both tasks, tempi of the imagined tunes were recorded by tapping to the musical beat while wearing an accelerometer and additional information (e.g., tune name, emotion ratings) was logged in a diary. Overall, INMI and VMI tempo measurements for the same tune were strongly correlated. Tempo recall for tunes that have definitive, recorded versions was relatively accurate, and tunes that were retrieved deliberately (VMI) were not recalled more accurately in terms of tempo than spontaneous and involuntary instances of imagined music (INMI). Some evidence that INMI elicited stronger emotional responses than VMI was also revealed. These results demonstrate several parallels to previous literature on involuntary memories and add new insights on the phenomenology of INMI.

Segmenting Bone Parts for Bone Age Assessment using Point Distribution Model and Contour Modelling

Bone age assessment (BAA) is a task performed on radiographs by the pediatricians in hospitals to predict the final adult height, to diagnose growth disorders by monitoring skeletal development. For building an automatic bone age assessment system the step in routine is to do image pre-processing of the bone X-rays so that features row can be constructed. In this research paper, an enhanced point distribution algorithm using contours has been implemented for segmenting bone parts as per well-established procedure of bone age assessment that would be helpful in building feature row and later on; it would be helpful in construction of automatic bone age assessment system. Implementation of the segmentation algorithm shows high degree of accuracy in terms of recall and precision in segmenting bone parts from left hand X-Rays.

The Use of Virtual Reality as Interactive Media to Support Web-based Navigation Performance for the Older Adult

The Use of Virtual Reality as Interactive Media to Support Web-based Navigation Performance for the Older Adult Dyi-Yih Michael Lin, Yu-Fei Hsu Abstract The feature of virtual reality in displaying three-dimensional digital contents may present particular benefits for the older adult in web-based navigation as spatial cognition has been shown declined with age. Sixteen subjects were recruited in an experiment where age (older vs. young) and web interface (two-dimensional vs. virtual reality) were manipulated as a between-subject and a repeated measure factor respectively. Performances were evaluated in terms of recall accuracy and the number of navigation errors when browsing the web contents. The results indicated the main effects of age and interface were both significant, and so was the interaction. For recall accuracy, the older subject achieved a performance level comparable to that for the young counterpart but only when the virtual reality interface was employed. For navigation error, the virtual reality interface assisted the older subject significantly so that the browsing orientation with this Euclidean space presentation even outperformed the orientation with two-dimensional web pages. Implications for designing web-based media that accommodate age considerations were discussed in details. Full Text: PDF DOI: 10.15640/jpbs.v4n2a14

Consensus Collaboration Enhances Group and Individual Recall Accuracy

We often remember in groups, yet research on collaborative recall finds "collaborative inhibition": Recalling with others has costs compared to recalling alone. In related paradigms, remembering with others introduces errors into recall. We compared costs and benefits of two collaboration procedures--turn taking and consensus. First, 135 individuals learned a word list and recalled it alone (Recall 1). Then, 45 participants in three-member groups took turns to recall, 45 participants in three-member groups reached a consensus, and 45 participants recalled alone but were analysed as three-member nominal groups (Recall 2). Finally, all participants recalled alone (Recall 3). Both turn-taking and consensus groups demonstrated the usual pattern of costs during collaboration and benefits after collaboration in terms of recall completeness. However, consensus groups, and not turn-taking groups, demonstrated clear benefits in terms of recall accuracy, both during and after collaboration. Consensus groups engaged in beneficial group source-monitoring processes. Our findings challenge assumptions about the negative consequences of social remembering.

Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks

BackgroundThe regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a cell. In order to understand the underlying function of organisms, it is necessary to study the behavior of genes in a gene regulatory network context. Several computational approaches are available for modeling gene regulatory networks with different datasets. In order to optimize modeling of GRN, these approaches must be compared and evaluated in terms of accuracy and efficiency.ResultsIn this paper, two important computational approaches for modeling gene regulatory networks, probabilistic Boolean network methods and dynamic Bayesian network methods, are compared using a biological time-series dataset from the Drosophila Interaction Database to construct a Drosophila gene network. A subset of time points and gene samples from the whole dataset is used to evaluate the performance of these two approaches.ConclusionThe comparison indicates that both approaches had good performance in modeling the gene regulatory networks. The accuracy in terms of recall and precision can be improved if a smaller subset of genes is selected for inferring GRNs. The accuracy of both approaches is dependent upon the number of selected genes and time points of gene samples. In all tested cases, DBN identified more gene interactions and gave better recall than PBN.

Prose memory deficits associated with schizophrenia

Memory of contextual information is essential to one's quality of living. This study investigated if the different components of prose memory, across three recall conditions: first learning trial immediate recall, fifth learning trial immediate recall, and 30-min delayed recall, are differentially impaired in people with schizophrenia, relative to healthy controls. A total of 39 patients with schizophrenia and 39 matched healthy controls were recruited. Their prose memory, in terms of recall accuracy, temporal sequence, recognition accuracy and false positives, commission of distortions, and rates of learning, forgetting, and retention were tested and compared. After controlling for the level of intelligence and depression, the patients with schizophrenia were found to commit more distortions. Furthermore, they performed poorer on recall accuracy and temporal sequence accuracy only during the first initial immediate recall. On the other hand, the rates of forgetting/retention and recognition accuracy were comparable between the two groups. These findings suggest that people with schizophrenia could be benefited by repeated exposure to the materials to be remembered. These results may have important implications for rehabilitation of verbal declarative memory deficits in schizophrenia.

Automatic Setting of Article Format Through Neural Networks

The automatic format-setting of journal articles for reducing the workload of computer users involves two processes: automatic acquisition of article format and automatic recall of article formal. Several neural networks have been explored to implement the two processes. The advantages and disadvantages of these neural networks are evaluated in comparison with capabilities of conventional computer programs. A heteroassociative back-propagation network has been developed for the automatic acquisition process. This network excels over computer programs because of its abilities in learning and generalizing implicit knowledge from examples. A bidirectional associative memory network, a Boltzman network, and an autoassociative back-propagation network have been investigated for the automatic recall process. None of them excel over computer programs in terms of recall accuracy.

Testing the Effect of Road Traffic Signs′ Informational Value on Driver Behavior

Measurement of the informational value of road traffic signs by questioning drivers at experimental roadblocks suggests that memory for signs is typically poor. This paper reports a study designed to assess the links among memory for road signs, driver behavior, and control adjustment action. Findings indicate that the effectiveness of road signs should be assessed in terms of their ability to sensitize the driver to hazards, rather than in terms of recall accuracy, and point to inconsistencies between drivers′ verbal recall and vehicle control behavior which are not readily apparent from roadblock research.

Effects of Mental Models of a Computer-Aided Instruction System on the Acquisition of Cognitive Skills

The human-computer interface of a computer-aided instruction (CAI) system can affect the learning of knowledge and skills. This study investigated the relative effectiveness of various mental models (i.e., metaphor, surrogate, and network) of a CAI system on the acquisition of intellectual skills and verbal information. Before the learning session started, subjects from each mental model group were given instructions about a representation of the system. Immediately after completion of the learning session, subjects were tested for their problem-solving performance. Time spent to solve each problem along with its accuracy was recorded. Results showed that there was an effect of mental models on the acquisition of intellectual skills. In terms of response speed and accuracy in problems requiring high complexity reasoning tasks, the Network model was most effective among the three. The Metaphor model, however, was best for problems requiring low complexity reasoning tasks. Mental models showed no effect on speed of the recall in verbal information. The metaphor model, however, was the best in terms of recall accuracy. These results suggested that CAI systems would require different human-computer interfaces depending on types of content knowledge and task requirements.