• Research in Community and Public Health Nursing
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• v.9 no.2
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• pp.336-349
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• 1998

The purpose of this study was to test the effects of music therapy on cognitive function and depression in demented old adults. This study was made with one -group in a pre- and post-test design. The subjects were seven demented old adults over, sixty-five years and with mild to moderate cognitive impairment, residing at a nursing home. Music therapy was given by one researcher and one research assistant for thirty to forty minutes twice a week for 4 months. Music therapy was conducted with the subjects both listening and singing with a cassette player and a double-handed drum. In order to evaluate the effects of music, we measured the level of cognitive function and depression at the beginning and at the end of the music therapy session by means of an MMSE- K developed by Kwon and Park and the Depression Inventory developed by Chon. The Data were analyzed using descriptive statistics and a paired t - test analysis using a SPSS PC package. The results are as follows: 1) The subjects of the music therapy showed improvement in cognitive function. The MMSE-K score was significantly increased after music therapy. Especially, memory recall was very significantly. 2) The subjects of the music therapy showed a slight decrease in depression. However, there was no significant difference in the degree of depression between mean scores measured before and after music therapy. The results suggest that music therapy is effective in improving and maintaining cognitive function in demented old adults. And we suggest that long-term music therapy will be required to improve depression in demented old adults. These findings are encouraging the idea that music therapy may improve cognitive impairment.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.1
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• pp.35-45
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• 2007

The log data collected from mobile devices contains diverse meaningful and practical personal information. However, this information is usually ignored because of its limitation of memory capacity, computation power and analysis. We propose a novel method that detects landmarks of meaningful information for users by analyzing the log data in distributed modules to overcome the problems of mobile environment. The proposed method adopts Bayesian probabilistic approach to enhance the inference accuracy under the uncertain environments. The new cooperative modularization technique divides Bayesian network into modules to compute efficiently with limited resources. Experiments with artificial data and real data indicate that the result with artificial data is amount to about 84% precision rate and about 76% recall rate, and that including partial matching with real data is about 89% hitting rate.

• Korean Journal of Cognitive Science
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• v.13 no.4
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• pp.91-98
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• 2002

The aim of this study is to make the recall-based reading span test(Daneman & Carpenter, 1980) into the recognition-based test for on-line measuring the capacity of the participant. In order to measure the concurrent validity, a series of experiments is performed with varying features of distractors consisting of the reading span test. In experiment 1, which included irrelevant words as distractor, low correlation was observed. And in experiment 2, including several types of distractors which interfere with the selection of target words, low correlation was observed too. But in experiment 3, including distractors no more relevant in the Present trial but relevant in previous trial, high correlation was observed. The results of this study have theoretical implications on the validity of the reading span test and practical implication in that this study provides the tool for the studies on individual differences in working memory capacity.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.211-222
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• 2012

There has been growing academic interest in revealing the effect of 3D stereoscopic displays, mostly based on the assumption that 3D would enhance the media user's psychological experiences. A 2(Display: 2D, 3D) x 2(Arousal: High, Low) x2(Valence: Positive, Negative) within-between subject experimental design, including both psychophysiological and self-report measurements, was employed to investigate if valence and arousal of the media content interact with the 3D stereo display. The results confirmed that 3D stereo significantly enhances the viewer's skin conductance level, while no meaningful difference for HR was found across the experimental conditions. The viewer's recall memory did not differ depending on the display type either. However, the viewer experienced a greater level of presence and liking of the content when the negative content was displayed in 3D stereo in comparison with the positive content. The practical implications of the results are further discussed.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.845-850
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• 2009

Use of XML data has been increased with growth of Web 2.0 environment. XML is recognized its advantages by using based technology of RSS or ATOM for transferring information from blogs and news feed. Bitmap clustering is a method to keep index in main memory based on Relational DBMS, and which performed better than the other XML indexing methods during the evaluation. Existing method generates too many clusters, and it causes deterioration of result of searching quality. This paper proposes k-Bitmap clustering method that can generate user defined k clusters to solve above-mentioned problem. The proposed method also keeps additional inverted index for searching excluded terms from representative bits of k-Bitmap. We performed evaluation and the result shows that the users can control the number of clusters. Also our method has high recall value in single term search, and it guarantees the searching result includes all related documents for its query with keeping two indices.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.1
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• pp.35-43
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• 2020

Turbidity has various effects on the water quality and ecosystem of a river. High turbidity during floods increases the operation cost of a drinking water supply system. Thus, the management of turbidity is essential for providing safe water to the public. There have been various efforts to estimate turbidity in river systems for proper management and early warning of high turbidity in the water supply process. Advanced data analysis technology using machine learning has been increasingly used in water quality management processes. Artificial neural networks(ANNs) is one of the first algorithms applied, where the overfitting of a model to observed data and vanishing gradient in the backpropagation process limit the wide application of ANNs in practice. In recent years, deep learning, which overcomes the limitations of ANNs, has been applied in water quality management. LSTM(Long-Short Term Memory) is one of novel deep learning algorithms that is widely used in the analysis of time series data. In this study, LSTM is used for the prediction of high turbidity(>30 NTU) in a river from the relationship of turbidity to discharge, which enables early warning of high turbidity in a drinking water supply system. The model showed 0.98, 0.99, 0.98 and 0.99 for precision, recall, F1-score and accuracy respectively, for the prediction of high turbidity in a river with 2 hour frequency data. The sensitivity of the model to the observation intervals of data is also compared with time periods of 2 hour, 8 hour, 1 day and 2 days. The model shows higher precision with shorter observation intervals, which underscores the importance of collecting high frequency data for better management of water resources in the future.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.477-485
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• 2018

Beyond the mid-2010s, there has been increasing cases of using 'Reminiscence' as a trigger for recalling 'Past' in pre-production process of creative contents. In previous researches on this phenomenon, it has been recognized that retro, recall, compassion, and memory are similar. In order to look closely to grasp the psychological tendency of the contents user in detail, the study about 'Reminiscence' was conducted. The researcher analyzed 'Reminiscence' as a process of restructuration based on the experience and desire of the person individual which were derived from the past and further analyzed it as a lack of desire due to the time can never return. The study hopefully can make a balance against the cutting edge content distribution technology biased production tendency.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.

• CELLMED
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• v.11 no.1
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• pp.2.1-2.8
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• 2021

The clinical condition Amnesia causes difficulty in learning new information and the inability to recall past events. It is primarily concerned with recent memory loss. Majoon-e-Nisyan (MJN) is a polyherbal Unani formulation, present in a semi-solid form. It is widely used potent drug of the Unani System of Medicine (USM) for treating Nisyan (amnesia). In the present study polyherbal Unani formulation, MJN has been studied for its quality control and acute toxicity. Standardization (quality control) of drugs deals with drug identity, drug quality and purity determination. Standardization of MJN had been done as per the Unani pharmacopoeial parameters approved by World Health Organization (WHO) - Pharmacognostical parameters, Physico-chemical parameters, high-performance thin-layer chromatography (HPTLC), microbial load, aflatoxin, and heavy metals. Solvents and chemicals used in the study were of analytical grade and used instrument were calibrated. By conducting an acute oral toxicity study in rats, the safety of MJN was assessed. The limit test method of OECD guideline 425 was followed in the study. Results of standardization and standard operating procedures (SOPs) for preparation of MJN may serve as the standard reference in the future. The data generated in the study for the quality control of MJN proved the quality of formulation and shows that MJN is not toxic in rats following acute dosing up to 2000 mg/kg bw. The data obtained in the paper for MJN may be used as a standard guideline for preparation of the formulation which can save time, cost, and resources for future research endeavours.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.4
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• pp.71-81
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• 2022

Purpose : This study aimed to present evidence by analyzing the characteristics and effectiveness of group art therapy interventions through an examination of domestic studies on group art therapy for older people with dementia. Methods : The database used DBpia, Riss, and Google Scholar, and the research period was from 2016 to November 2021. For the selected studies, the level of evidence was analyzed, bias evaluation was performed, and patient, intervention, comparison, and outcome were analyzed. For the evaluation of bias, the risk of bias assessment tool for non-randomized study (RoBANS) and Cochrane's risk of bias (RoB) were used. Results : As for the level of evidence of the included studies, level I consisted of five studies, and levels II and III each had one article. As a result of the bias evaluation of five studies through RoB, a "low risk of bias" was found for incomplete result data, selective result reporting, and others, except for four unclear evaluation areas. The "low risk of bias" ratio was 0~25 % in the evaluation of bias in two studies through RoBANS. For the evaluation tool, cognitive evaluation tool was used the most while mini-mental state examination-Korea was used the most frequently. For the intervention method, the most frequently used was group art therapy that employed recall in three studies, while collage, Korean painting, use of paper media, and procedural memory were used in each of the other studies. Each intervention was found to be significantly effective overall. Conclusion : This study provided clinical evidence by systematically reporting research on group art therapy for older people with dementia. In the future, it is necessary to check the effect of group art therapy on various areas other than cognition for older people with dementia. Moreover, the study should be conducted with the risk of bias sufficiently taken into consideration.