• Title/Summary/Keyword: recall memory

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An Exam Prep App for the Secondary English Teacher Recruitment Exam with Brain-based Memory and Learning Principles (뇌 기억-학습 원리를 적용한 중등영어교사 임용시험 준비용 어플)

  • Lee, Hye-Jin
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.311-320
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    • 2021
  • At present, the secondary school teacher employment examination(SSTEE) is the only gateway to become a national and public secondary teacher in Korea, and after the revision from the 2014 academic year, all the questions of the exam have been converted to supply-type test items, requiring more definitive, accurate, and solid answers. Compared to the selection-type test items that measure recognition memory, the supply-type questions, testing recall memory, require constant memorization and retrieval practices to furnish answers; however, there is not enough learning tools available to support the practices. At this juncture, this study invented a mobile app, called ONE PASS, for the SSTEE. By unpacking the functional mechanisms of the brain, the basis of cognitive processing, this ONE PASS app offers a set of tools that feature brain-based learning principles, such as a personalized study planner, motivation measurement scales, mind mapping, brainstorming, and sample questions from previous tests. This study is expected to contribute to the research on the development of learning contents for applications, and at the same time, it hopes to be of some help for candidates in their exam preparation process.

The Effect of BPL (Brand Placement) in Movies on Short-term and Long-term Memory (영화 속 BPL이 단기기억과 장기기억에 미치는 효과)

  • Nam, Kyeong-Tae
    • Korean Journal of Communication Studies
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    • v.18 no.1
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    • pp.165-193
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    • 2010
  • The current study has significance in that it increases our understanding of BPL effectiveness by adding long-term memory dependent variables to widely used short-term memory variables. Furthermore, two unit of analysis of the current study, subject and BPL, made richer analysis possible as compared to previous studies. The result showed that BPL was effective in short-term recognition(52.8% of BPLs), long-term recognition(44.4% of BPLs), and long-term recall(30.6% of BPLs). The further result showed that audiovisual BPL, closeup BPL, long-exposed brand, leading actor using brand were more effective than other kinds of BPL. On the other hand, preference for the movie and preference for the actor were not significant factors in increasing people's memory of the brand name. Future researchers should settle the confusion existed in this field by inventing a more elaborate research design and exploring mediating and moderating variables in the subject of BPL effectiveness.

Effect of the application of low-frequency rTMS on cognitive function in chronic stroke patients (저빈도 rTMS의 적용이 만성 뇌졸중환자의 인지기능에 미치는 영향)

  • Lee, Dong-Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.12
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    • pp.7239-7247
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    • 2014
  • This study repeated low-frequency transcranial magnetic stimulation (rTMS) to evaluate the effects on cognitive function in chronic stroke patients. Among the chronic stroke patients, 30 patients selected by MMSE-K and BCRS-K were divided randomly into 3 groups. Group I (n=10) had only sound applied, group II (n=10) were applied 1 Hz rTMS on the damaged side and group III (n=10) were applied to 1 Hz rTMS on the opposite side for total 2 weeks, 20 minutes per a day, five times per a week. To examine the change in cognitive function, CREAD-K scores were measured before, 1 week, 2 weeks, and then 3 months after the intervention. The CREAD-K scores were measured before and 1 week, 2 weeks and 3 months after the interventions. The immediate recall memory showed a significant difference after 2 weeks and 3 months in groups II and III (p<.05), The recognition memory showed a significant difference after 2 weeks and 3 months in group III (p<.05). The delayed recall memory showed significant differences after 3 months in group III than in group I (p<.05). Therefore, the application of low-frequency rTMS has a positive influence on the cognitive rehabilitation of chronic stroke patients.

Comparative assessment of frost event prediction models using logistic regression, random forest, and LSTM networks (로지스틱 회귀, 랜덤포레스트, LSTM 기법을 활용한 서리예측모형 평가)

  • Chun, Jong Ahn;Lee, Hyun-Ju;Im, Seul-Hee;Kim, Daeha;Baek, Sang-Soo
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.667-680
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    • 2021
  • We investigated changes in frost days and frost-free periods and to comparatively assess frost event prediction models developed using logistic regression (LR), random forest (RF), and long short-term memory (LSTM) networks. The meteorological variables for the model development were collected from the Suwon, Cheongju, and Gwangju stations for the period of 1973-2019 for spring (March - May) and fall (September - November). The developed models were then evaluated by Precision, Recall, and f-1 score and graphical evaluation methods such as AUC and reliability diagram. The results showed that significant decreases (significance level of 0.01) in the frequencies of frost days were at the three stations in both spring and fall. Overall, the evaluation metrics showed that the performance of RF was highest, while that of LSTM was lowest. Despite higher AUC values (above 0.9) were found at the three stations, reliability diagrams showed inconsistent reliability. A further study is suggested on the improvement of the predictability of both frost events and the first and last frost days by the frost event prediction models and reliability of the models. It would be beneficial to replicate this study at more stations in other regions.

Stimulatory effects of Bordetella bronchiseptica antigen on bone marrow cells and immune memory responses (골수세포에 대한 Bordetella bronchiseptica 항원의 자극 효과 및 면역기억반응)

  • Yim, Seol-Hwa;Joo, Hong-Gu
    • Korean Journal of Veterinary Research
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    • v.54 no.4
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    • pp.203-208
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    • 2014
  • Bone marrow is a hematological and immunological organ that provides multiple immune cells, including B lymphocytes, and thus plays a critical role in the efficacy of vaccine. We previously demonstrated that Bordetella (B.) bronchiseptica antigen has high immunogenicity in spleen cells, a peripheral immune organ. In this study, we investigated the immunogenicity of B. bronchiseptica antigen in bone marrow cells, a central immune organ. B. bronchiseptica antigen increased the cellular activity of bone marrow cells and significantly enhanced the production of nitric oxide, IL-6, and TNF-${\alpha}$. Bone marrow cells primed with B. bronchiseptica antigen in vivo were harvested and stimulated with the same antigen in vitro. The stimulation of B. bronchiseptica antigen significantly increased the cellular activity and proliferation rate of the primed cells. B. bronchiseptica antigen also greatly induced the production of antigen-specific antibody in the primed cells. Taken together, the present study demonstrated that B. bronchiseptica antigen can stimulate bone marrow cells, a central immune organ, and recall the immune response of the primed bone marrow cells.

Analysis of Recall Dynamics of Sequential Associative Memory with Delay Synapses (지연시냅스를 가진 계열 연상 메모리의 상기 다이나믹스 해석)

  • Kim, Eun-Soo
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.5
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    • pp.1130-1137
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    • 1996
  • Every neural network has some kind of feedback. For the sake of analyzing fundamental aspects of information processing in neural nets, a net without feedbacks is an important theoretical model. But here we focus on a recurrent neural net which delay synapses as a realistic dynamical model of nervous systems. Synaptic connections are determined by a version of the Hebb rule (correlation type rule). We use a statistical neurodynamic method to explain the retrieval dynamics of the network. The result of the analysis for the sequential associativ e memory with delay synapses is compared with computer simulation. We have succeeded in explaining the dynamics of this network by theoretical analyses.

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A Prospective Study on an Association between Apolipoprotein E ${\varepsilon}4$ and Cognitive Change in Community-Dwelling Elders with Alzheimer's Disease (일 지역 알츠하이머병 노인에서 Apolipoprotein E ${\varepsilon}4$와 인지변화의 연관에 대한 전향적 연구)

  • Kang, Min Sung;Moon, Seok Woo
    • Korean Journal of Biological Psychiatry
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    • v.20 no.3
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    • pp.104-110
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    • 2013
  • Objectives : The aim of this study was to examine the prospective impact of the apolipoprotein E (APOE) ${\varepsilon}4$ on cognitive performance in the community-dwelling elderly individuals with Alzheimer's disease (AD). Methods : The total number of subjects was 30 (12 men and 18 women) who were diagnosed with AD from a Korean project of "Early Detection of Dementia". People aged 65-85 years were included in the analysis. The eight neuropsychological domains from the Korean version of Consortium to Establish a Registry of Alzheimer's Disease (CERAD-K) were conducted to test subjects. They have been followed at 24-month intervals with the same assessments at each interval. Their cognitive performance at 2 year intervals was compared by the occurrence of the APOE ${\varepsilon}4$. Results : The impact of ${\varepsilon}4$ allele was significant in the Word List Memory Test (WLMT, F = 4.345, df = 1, p = 0.021) and Word List Recall Test (WLRT, F = 5.569, df = 1, p = 0.033). Conclusions : The APOE ${\varepsilon}4$ allele was significantly correlated especially with verbal episodic memory domain in community-dwelling elders diagnosed with AD.

Enhancing Multimodal Emotion Recognition in Speech and Text with Integrated CNN, LSTM, and BERT Models (통합 CNN, LSTM, 및 BERT 모델 기반의 음성 및 텍스트 다중 모달 감정 인식 연구)

  • Edward Dwijayanto Cahyadi;Hans Nathaniel Hadi Soesilo;Mi-Hwa Song
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.617-623
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    • 2024
  • Identifying emotions through speech poses a significant challenge due to the complex relationship between language and emotions. Our paper aims to take on this challenge by employing feature engineering to identify emotions in speech through a multimodal classification task involving both speech and text data. We evaluated two classifiers-Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM)-both integrated with a BERT-based pre-trained model. Our assessment covers various performance metrics (accuracy, F-score, precision, and recall) across different experimental setups). The findings highlight the impressive proficiency of two models in accurately discerning emotions from both text and speech data.

Negative Effects of City Slogan on the Retrieval of City Memory Unrelated to the Slogan (도시슬로건이 도시기억의 인출에 미치는 부정적 영향 :슬로건과 관련 없는 도시기억을 중심으로)

  • Kim, Dohyung;Hwang, Insuk
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.224-236
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    • 2022
  • This study tests the hypotheses that city slogan reduces the retrieval of city memory unrelated to the slogan from the long term memory and that some variables moderate this effect, using the experimental method. The theoretical basis for the hypotheses is from the structure of the long term memory and the principle of memory retrieval discussed in ANM(Associative Network Model). For the test of hypotheses, the study adopted 4 experimental groups (2(slogan relevance: high or low) * 2(slogan concreteness: high or low)) and 1 control group. Each experimental group was exposed to one slogan corresponding to its condition while the control group was not. Then, the recall score was compared among experimental and control groups. One hundred and seventy-four undergraduate students belonging to the college of the authors participated in the study. The sample group was between 18 and 27 years of age, with an average of 22.4 years, and 54 percent comprised males. Results showed that city slogan had a negative effect on the retrieval of city memory unrelated to the slogan in most experimental conditions. This effect was more evident when the slogan had high relevance or high concreteness. But the main effect did not appear when the slogan had low relevance and low concreteness.

Fire Detection using Deep Convolutional Neural Networks for Assisting People with Visual Impairments in an Emergency Situation (시각 장애인을 위한 영상 기반 심층 합성곱 신경망을 이용한 화재 감지기)

  • Kong, Borasy;Won, Insu;Kwon, Jangwoo
    • 재활복지
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    • v.21 no.3
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    • pp.129-146
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    • 2017
  • In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.