scholarly journals Hypergraph-Based Recognition Memory Model for Lifelong Experience

2014 ◽  
Vol 2014 ◽  
pp. 1-17
Author(s):  
Hyoungnyoun Kim ◽  
Ji-Hyung Park
Keyword(s):  
Recognition Memory ◽  
Lifelong Learning ◽  
Partial Information ◽  
Memory Performance ◽  
Dynamic Environment ◽  
Memory Model ◽  
Proposed Model ◽  
Agent Interaction ◽  
Static Conditions ◽  
Initial Process

Cognitive agents are expected to interact with and adapt to a nonstationary dynamic environment. As an initial process of decision making in a real-world agent interaction, familiarity judgment leads the following processes for intelligence. Familiarity judgment includes knowing previously encoded data as well as completing original patterns from partial information, which are fundamental functions of recognition memory. Although previous computational memory models have attempted to reflect human behavioral properties on the recognition memory, they have been focused on static conditions without considering temporal changes in terms of lifelong learning. To provide temporal adaptability to an agent, in this paper, we suggest a computational model for recognition memory that enables lifelong learning. The proposed model is based on a hypergraph structure, and thus it allows a high-order relationship between contextual nodes and enables incremental learning. Through a simulated experiment, we investigate the optimal conditions of the memory model and validate the consistency of memory performance for lifelong learning.

Learning From (Test) Experience

2020 ◽  
Vol 228 (4) ◽  
pp. 264-277 ◽  
Author(s):  
Evan E. Mitton ◽  
Chris M. Fiacconi
Keyword(s):  
Recognition Memory ◽  
Test Performance ◽  
Memory Performance ◽  
Judgments Of Learning ◽  
Visual Images ◽  
Memory Tests ◽  
Recognition Memory Performance ◽  
Study Test ◽  
Explicit Feedback

Abstract. To date there has been relatively little research within the domain of metamemory that examines how individuals monitor their performance during memory tests, and whether the outcome of such monitoring informs subsequent memory predictions for novel items. In the current study, we sought to determine whether spontaneous monitoring of test performance can in fact help individuals better appreciate their memory abilities, and in turn shape future judgments of learning (JOLs). Specifically, in two experiments we examined recognition memory for visual images across three study-test cycles, each of which contained novel images. We found that across cycles, participants’ JOLs did in fact increase, reflecting metacognitive sensitivity to near-perfect levels of recognition memory performance. This finding suggests that individuals can and do monitor their test performance in the absence of explicit feedback, and further underscores the important role that test experience can play in shaping metacognitive evaluations of learning and remembering.

Semantic Congruency Improves Recognition Memory Performance for Both Audiovisual and Visual Stimuli

2017 ◽  
Vol 30 (7-8) ◽  
pp. 763-781 ◽  
Author(s):  
Jenni Heikkilä ◽  
Kimmo Alho ◽  
Kaisa Tiippana
Keyword(s):  
Recognition Memory ◽  
Congruency Effect ◽  
Memory Performance ◽  
Visual Stimuli ◽  
The Other ◽  
Memory Encoding ◽  
Semantic Congruency ◽  
Recognition Memory Performance ◽  
Visual Encoding ◽  
Per Se

Audiovisual semantic congruency during memory encoding has been shown to facilitate later recognition memory performance. However, it is still unclear whether this improvement is due to multisensory semantic congruency or just semantic congruencyper se. We investigated whether dual visual encoding facilitates recognition memory in the same way as audiovisual encoding. The participants memorized auditory or visual stimuli paired with a semantically congruent, incongruent or non-semantic stimulus in the same modality or in the other modality during encoding. Subsequent recognition memory performance was better when the stimulus was initially paired with a semantically congruent stimulus than when it was paired with a non-semantic stimulus. This congruency effect was observed with both audiovisual and dual visual stimuli. The present results indicate that not only multisensory but also unisensory semantically congruent stimuli can improve memory performance. Thus, the semantic congruency effect is not solely a multisensory phenomenon, as has been suggested previously.

Design of robust layout for unequal area dynamic facility layout problems with flexible bays structure

2020 ◽  
Vol 18 (4) ◽  
pp. 361-392
Author(s):  
Irappa Basappa Hunagund ◽  
V. Madhusudanan Pillai ◽  
Ujjani Nagegowda Kempaiah
Keyword(s):  
Simulated Annealing Algorithm ◽  
Facility Layout ◽  
Dynamic Environment ◽  
Planning Horizon ◽  
Content Type ◽  
Robust Approach ◽  
Penalty Cost ◽  
Proposed Model ◽  
Total Penalty ◽  
Flexible Bay Structure

Purpose The purpose of this paper is to develop a mathematical model for the design of robust layout for unequal area-dynamic facility layout problem with flexible bay structure (UA-DFLP with FBS) and test the suitability of generated robust layout in a dynamic environment. Design/methodology/approach This research adopts formulation of a mathematical model for generating a single layout for unequal area facility layout problems with flexible bay structure under dynamic environment. The formulated model for the robust layout formation is solved by developing a simulated annealing algorithm. The proposed robust approach model for UA-DFLP with FBS is validated by conducting numerical experiments on standard UA-DFLPs reported in the literature. The suitability of the generated robust layout in a dynamic environment is tested with total penalty cost criteria. Findings The proposed model has given a better solution for some UA-DFLPs with FBS in comparison with the adaptive approach’s solution reported in the literature. The total penalty cost is within the specified limit given in the literature, for most of the layouts generated for UA-DFLPs with FBS. In the proposed model, there is no rearrangement of facilities in various periods of planning horizon and thus no disruptions in operations. Research limitations/implications The present work has limitations that when the area and aspect ratio of the facilities are required to change from one period to another, then it is not possible to make application of the robust approach-based formulation to the dynamic environment facility layout problems. Practical implications Rearrangement of facilities in adaptive approach disrupts the operations whereas in the proposed approach no disruption of production. The FBS approach is more suitable for layout planning where proper aisle structure is required. The solution of the proposed approach helps to create a proper aisle structure in the detailed layout plan. Thus, easy interaction of the material handling equipment, men and materials is possible. Originality/value This paper proposes a mathematical formulation for the design of robust layout for UA-FLPs with FBS in a dynamic environment and an efficient simulated annealing algorithm as its solution procedure. The proposed robust approach generates a single layout for the entire planning horizon. This approach is more useful for facilities which are difficult/sensitive to relocate in various periods of the planning horizon.

scholarly journals Earthquake Detection in a Static and Dynamic Environment Using Supervised Machine Learning and a Novel Feature Extraction Method

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 800 ◽  
Author(s):  
Irshad Khan ◽  
Seonhwa Choi ◽  
Young-Woo Kwon
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Dynamic Environment ◽  
Supervised Machine Learning ◽  
Experimental Result ◽  
Feature Extraction Method ◽  
Proposed Model ◽  
Unseen Data ◽  
Iot Devices ◽  
Hard Real Time

Detecting earthquakes using smartphones or IoT devices in real-time is an arduous and challenging task, not only because it is constrained with the hard real-time issue but also due to the similarity of earthquake signals and the non-earthquake signals (i.e., noise or other activities). Moreover, the variety of human activities also makes it more difficult when a smartphone is used as an earthquake detecting sensor. To that end, in this article, we leverage a machine learning technique with earthquake features rather than traditional seismic methods. First, we split the detection task into two categories including static environment and dynamic environment. Then, we experimentally evaluate different features and propose the most appropriate machine learning model and features for the static environment to tackle the issue of noisy components and detect earthquakes in real-time with less false alarm rates. The experimental result of the proposed model shows promising results not only on the given dataset but also on the unseen data pointing to the generalization characteristics of the model. Finally, we demonstrate that the proposed model can be also used in the dynamic environment if it is trained with different dataset.

scholarly journals Acute effects of naturalistic THC vs. CBD use on recognition memory: a preliminary study

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Tim Curran ◽  
Hélène Devillez ◽  
Sophie L. YorkWilliams ◽  
L. Cinnamon Bidwell
Keyword(s):  
Recognition Memory ◽  
Memory Performance ◽  
Recognition Task ◽  
Blood Levels ◽  
Dependent Manner ◽  
Acute Effects ◽  
Blood Draw ◽  
Memory Impairments ◽  
Verbal Recognition ◽  
Memory Accuracy

Abstract The ratio of ∆9-tetrahydrocannabinol (THC) to cannabidiol (CBD) varies widely across cannabis strains. CBD has opposite effects to THC on a variety of cognitive functions, including acute THC-induced memory impairments. However, additional data are needed, especially under naturalistic conditions with higher potency forms of cannabis, commonly available in legal markets. The goal of this study was to collect preliminary data on the acute effects of different THC:CBD ratios on memory testing in a brief verbal recognition task under naturalistic conditions, using legal-market Colorado dispensary products. Thirty-two regular cannabis users consumed cannabis of differing THC and CBD levels purchased from a dispensary and were assessed via blood draw and a verbal recognition memory test both before (pretest) and after (posttest) ad libitum home administration in a mobile laboratory. Memory accuracy decreased as post-use THC blood levels increased (n = 29), whereas performance showed no relationship to CBD blood levels. When controlling for post-use THC blood levels as a covariate, participants using primarily THC-based strains showed significantly worse memory accuracy post-use, whereas subjects using strains containing both THC and CBD showed no differences between pre- and post-use memory performance. Using a brief and sensitive verbal recognition task, our study demonstrated that naturalistic, acute THC use impairs memory in a dose dependent manner, whereas the combination of CBD and THC was not associated with impairment.

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