• Title/Summary/Keyword: Forgetting

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Analysis of the Work Time and the Collective Dose by Correcting the Learning-Forgetting Curve Model in Decommissioning of a Nuclear Facility

  • ChoongWie Lee;Hee Reyoung Kim;Jin-Woo Lee
    • Journal of Radiation Protection and Research
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    • v.48 no.1
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    • pp.20-27
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    • 2023
  • Background: As the number of nuclear facilities nearing their pre-determined design life increases, demand is increasing for technology and infrastructure related to the decommissioning and decontamination (D&D) process. It is necessary to consider the nature of the dismantling environment constantly changing and the worker doing new tasks. A method was studied that can calculate the effect of learning and the change in work time on the work process, according to the learning-forgetting curve model (LFCM). Materials and Methods: The LFCM was analyzed, and input values and scenarios were analyzed for substitution into the D&D process of a nuclear facility. Results and Discussion: The effectiveness and efficiency of the training were analyzed. It was calculated that skilled workers can receive a 16.9% less collective radiation dose than workers with only basic training. Conclusion: Using these research methods and models, it was possible to calculate the change in the efficiency of workers performing new tasks in the D&D process and the corresponding reduction in the work time and collective dose.

Low-Complexity VFF-RLS Algorithm Using Normalization Technique (정규화 기법을 이용한 낮은 연산량의 가변 망각 인자 RLS 기법)

  • Lee, Seok-Jin;Lim, Jun-Seok;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.1
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    • pp.18-23
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    • 2010
  • The RLS (Recursive Least Squares) method is a broadly used adaptive algorithm for signal processing in electronic engineering. The RLS algorithm shows a good performance and a fast adaptation within a stationary environment, but it shows a Poor performance within a non-stationary environment because the method has a fixed forgetting factor. In order to enhance 'tracking' performances, BLS methods with an adaptive forgetting factor had been developed. This method shows a good tracking performance, however, it suffers from heavy computational loads. Therefore, we propose a modified AFF-RLS which has relatively low complexity m this paper.

Forgetting Stories from the Islands, Jeju and Calauit

  • Raymon D. Ritumban
    • SUVANNABHUMI
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    • v.16 no.1
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    • pp.103-123
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    • 2024
  • The traumatic experiences of people from peripheral islands are susceptible to mnemocide. Such erasure of memory is facilitated by "defensive and complicit forgetting," which, according to Aleida Assmann, leads to "protection of perpetrators." My paper reflects on the vulnerability of traumas from the islands to mnemocide by looking into [1] the massacre of communists and civilians on Jeju Island, South Korea in 1948 as described in Hyun-Kil Un's short story "Dead Silence" (2017; English trans.) and [2] the eviction of residents and indigenous people from Calauit Island, Philippines for the creation of a safari in 1976 as imagined in Annette A. Ferrer's "Pablo and the Zebra" (2017). In "Dead Silence," I direct the attention to how to the execution of the villagers-witnesses to the death of the communist guerillas-is a three-pronged violence: it is a transgression committed against the innocent civilians; an act of "erasing traces to cover up" the military crackdown on the island; and, by leaving the corpses out in the open, a display of impunity. In "Pablo and the Zebra," I second that both residents (i.e., humans and animals) experience post-traumatic stress because of their respective displacements; thus, the tension between them has got to stop. Curiously, while it concludes with a reconciliatory gesture between an elder and a zebra, no character demanded a reparation for their traumatic past per se. Could the latter be symptomatic of a silence that lets such violence "remain concealed for a long time"?

The Effect of Distinctiveness of stimulus and Partial Retrieval on Memory (자극의 구별성과 부분 인출이 기억에 미치는 영향)

  • Jung, Yoonjae
    • Korean Journal of Cognitive Science
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    • v.30 no.1
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    • pp.31-50
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    • 2019
  • The present study is designed to investigate the effect of perceptive, emotional and semantic distinctiveness on retrieval-induced forgetting(RIF). Experiment 1 was designed to construct a category and category list for RIF experimental paradigm and to investigate the effects of perceptual distinctness on retrieval-induced forgetting. It was used for the list consisting of the six categories and six words in each category list. In controlled conditions, all the stimuli were presented in black and Gothic. In contrast, perceptual distinctiveness conditions, half of the category list were presented in red and Gungseoche. RIF was observed in all conditions. Experiment 2 was designed to investigate the effects of semantic and emotional distinctiveness on retrieval-induced forgetting. In neutral conditions, adjectives related to items were added. In the emotional distinctiveness condition, half of the items in the category were manipulated in such a way as to add the negative adjectives. In the semantic distinctiveness condition, half of the items in the category were manipulated in such a way as to add the inappropriate adjective. As a result, RIF occurred in the neutral condition, but RIF did not occur in both the emotional discrimination condition and the semantic discrimination. These results suggest the possibility that the RIF will not occur when the distinctiveness occurs within a categorical relationship.

Determination of Minimum Eigenvalue in a Continuous-time Weighted Least Squares Estimator (연속시간 하중최소자승 식별기의 최소고우치 결정)

  • Kim, Sung-Duck
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1021-1030
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    • 1992
  • When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

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Passive Telemetry Sensor System using RLSE Based Real Time Estimation Technique with Optimal Forgetting Factor

  • Lee, Joon-Tark;Kim, Kyung-Yup
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.515-520
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    • 2004
  • In this paper, a passive telemetry RF capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique is proposed. To overcome these trouble problems such as a power limitation and a estimation complexity that the general passive telemetry sensor system including It chip has, the principle of inductive coupling was applied to the modeling of a passive telemetry RF capacitive humidity sensor system and its capacitance was estimatedd by the RLSE algorithm. Specially, by introducing the optimal forgetting factor, we showed that the accuracy of its estimation was improved even in the time varying system and also the convergence time was reduced.

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Adaptive Moving Jammer Cancellation Algorithm with the Robustness to the Array Aperture

  • Song, Joon-il;Lim, Jun-Seok;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.2E
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    • pp.40-43
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    • 2004
  • In moving jammer environments, the performance of conventional adaptive beamformer is severely degraded and the robust adaptive beamformer requires additional sensors to obtain desired performances. Therefore, it is necessary to develop efficient algorithm without any additional requirement of the number of sensors, etc. In this paper, we introduce a fast adaptive algorithm with variable forgetting factor, which does not have any additional requirements. From the computer simulations, we obtain the better performances than those of other techniques for the arrays with various aperture lengths.

Automatic interpretation of awaked EEG by using constructive neural networks with forgetting factor

  • Nakamura, Masatoshi;Chen, Yvette;Sugi, Takenao;Ikeda Akio;Shibasaki Hiroshi
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.505-508
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    • 1995
  • The automatic interpretation of awake background electroencephalogram (EEG), consisting of quantitative EEG interpretation and EEG report making, has been developed by the authors based on EEG data visually inspected by an electroencephalographer (EEGer). The present study was focused on the adaptability of the automatic EEG interpretation which was accomplished by the constructive neural network with forgetting factor. The artificial neural network (ANN) was constructed so as to give the integrative decision of the EEG by using the input signals of the intermediate judgment of 13 items of the EEG. The feature of the ANN was that it adapted to any EEGer who gave visual inspection for the training data. The developed method was evaluated based on the EEG data of 57 patients. The re-trained ANN adapted to another EEGer appropriately.

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Time Variant Parameter Estimation using RLS Algorithm with Adaptive Forgetting Factor Based on Newton-Raphson Method (Newton-Raphson법 기반의 적응 망각율을 갖는 RLS 알고리즘에 의한 원격센서시스템의 시변파라메타 추정)

  • Kim, Kyung-Yup;Ji, Seok-Joon;Kwak, Lee-Hui;Lee, John-T.
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1680-1681
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    • 2007
  • This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model.

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