• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3943-3959
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• 2022

People are constantly exposed to stress and anxiety environment, which could contribute to a variety of psychological and physical health problems. Therefore, it is particularly important to identify psychological stress in time and to find a feasible and universal method of stress reduction. This research investigated the influence of different music, such as relaxation music and natural rhythm music, on stress relief based on Electroencephalogram signals. Mental arithmetic test was implemented to create a stressful environment. 23 participants performed the mental arithmetic test with and without music respectively, while their Electroencephalogram signal was recorded. The effect of music on stress relief was verified through stress test questionnaires, including Trait Anxiety Inventory (STAI-6) and Self-Stress Assessment. There was a significant change in the stress test questionnaire values with and without music according to paired t-test (p<0.01). Furthermore, a model based on Transformer for stress level classification from Electroencephalogram signal was proposed. Experimental results showed that the method of listening to relaxation music and natural rhythm music achieved the effect of reducing psychological stress and the proposed model yielded a promising accuracy in classifying the Electroencephalogram signal of mental stress.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.

• Sleep Medicine and Psychophysiology
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• v.8 no.2
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• pp.121-128
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• 2001

Objectives: In narcoleptic patients diagnosed with ICSD (international classification of sleep disorders, 1990) criteria, nocturnal polysomnography, and MSLT (multiple sleep latency test), we tried to find characteristic features of quantitative electroencephalography (QEEG) in a wakeful state. Methods: We compared eight drug-free narcoleptic patients with sex- and age-matched normal controls, using computerized electroencephalographic mapping technique and spectral analysis. Absolute power, relative power, interhemispheric asymmetry, interhemispheric and intrahemispheric coherence, and mean frequency in each frequency band (delta, theta, alpha and beta) were measured and analyzed. Results: Compared with normal controls, narcoleptic patients showed decrease in monopolar interhemispheric coherence of alpha frequency bands in occipital ($O_1/O_2$), parietal ($P_3/P_4$), and temporal ($T_5/T_6$) areas and beta frequency band in the occipital ($O_1/O_2$) area. Monopolar intrahemispheric coherences of alpha frequency bands in left hemispheric areas ($T_3/T_5$, $C_3/P_3$ & $F_3/O_1$) decreased. Decrease of monopolar interhemispheric asymmetry of delta frequency band in the occipital ($O_1/O_2$) area was also noted. The monopolar absolute powers of beta frequency bands decreased in occipital ($O_2,\;O_z$) areas. Conclusion: Decreases in coherences of narcoleptic patients compared with normal controls may indicate fewer posterior neocortical interhemispheric neuronal connections, and fewer left intrahemispheric neuronal connections than normal controls in a wakeful state. Therefore, we suggest that abnormal neurophysiological sites of narcolepsy may involve complex areas such as neocortex and subcortex as well as the brainstem.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.247-249
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• 2020

In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.55-64
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• 2015

The present study identified the brain based learning activities on the individual learning senses by using the brain laterality and the whole brain index. Students receive the information through the visual, auditory, and kinesthetic senses by Politano and Paquin's (2000) classification. These learning senses are reflected on brain by the various combinations of senses for learning. Measuring the types of the learning senses involving in brain laterality and whole brain is required to figure out the related learning styles. Self-directed learning involved in the learning senses shows the problem-based learning associated to the brain function by emphasizing the balanced brain utilization which is known as whole brain. These research results showed the successful whole brain learning is closely associated with elevated auditory learning and elevated visual learning in sensorimotor brainwave rhythm (SMR) while it shows the close association with elevated kinesthetic and elevated visual learning in beta brainwave rhythm.

• Economic and Environmental Geology
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• v.53 no.4
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• pp.363-381
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• 2020

The polymetallic Co, Ni, Cu, As, Au, and Ag deposits of Bou Azzer East are located in the western part of the Bou Azzer inlier in the Central Anti Atlas, Morocco. Six stages of emplacement of the mineralization have been identified. Precious metals (native gold and electrum) are present in all stages of this deposit except the early nickeliferous stage. From the Statistical analysis of the Co, As, Ni, Au, and Ag contents of a set of 501 samples, shows that the Pearson correlation coefficient between As-Co elements (0.966) is the highest followed by that of the Au-Ag couple (0.506). Principal component analysis (PCA) and hierarchical ascending classification (HAC) of the grades show, that Ni is associated with the pair (As-Co) and Cu is rather related to the pair (Au-Ag). The kriging maps show that the highest values of the Co, As and Ni appear in the contact of the serpentinite with other facies, as for those of Au and Ag, in addition to anomalous zones concordant with those of Co, Ni and As, they show anomalies at the extreme South and North of the study area. The development of the anomalous Au and Ag zones is mainly along the N40-50°E and N145°E directions.

• Economic and Environmental Geology
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• v.46 no.6
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• pp.545-559
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• 2013

Until now, research achievements of groundwater such as groundwater to depth distribution, usage, the available amount of development, water quality have been written in the watershed units($25{\sim}250km^2$). However, complex topography and geology, and the rivers of our country does not fit. And a clear management standards have not been able to present measures in groundwater quantity, water quality management such as rainfall, groundwater, utilization, water quality, pollution, etc. Therefore, in this study, the classification criterion of subwatershed unit($2.5{\sim}25km^2$), which is suitable for topography and geology of Korea, for rainfall-rating, groundwater level-rating, groundwater pollution-rating, groundwater quality-rating presented and proved its efficiency by applying in Hampyeong-Gun area.

• Journal of Korean Neurosurgical Society
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• v.56 no.3
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• pp.248-253
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• 2014

Objective : Cortical dysplasia (CD) is one of the common causes of epilepsy surgery. However, surgical outcome still remains poor, especially with frontal lobe epilepsy (FLE), despite the advancement of neuroimaging techniques and expansion of surgical indications. The aim of this study was to focus on surgical strategies in terms of extent of resection to improve surgical outcome in the cases of FLE with CD. Methods : A total of 11 patients of FLE were selected among 67 patients who were proven pathologically as CD, out of a total of 726 epilepsy surgery series since 1992. This study categorized surgical groups into three according to the extent of resection : 1) focal corticectomy, 2) regional corticectomy, and 3) partial functional lobectomy, based on the preoperative evaluation, in particular, ictal scalp EEG onset and/or intracranial recordings, and the lesions in high-resolution MRI. Surgical outcome was assessed following Engel's classification system. Results : Focal corticectomy was performed in 5 patients and regional corticectomy in another set of 5 patients. Only 1 patient underwent partial functional lobectomy. Types I and II CD were detected with the same frequency (45.45% each) and postoperative outcome was fully satisfactory (91%). Conclusion : The strategy of epilepsy surgery is to focus on the different characteristics of each individual, considering the extent of real resection, which is based on the focal ictal onset consistent with neuroimaging, especially in the practical point of view of neurosurgery.