• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.323-331
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• 2006

The purpose of this study was to investigate the effect of performing a cognitive task during treadmill walking on the stride rate variability. Ten university students(age $24.0{\pm}0.25$, height $172{\pm}3.1cm$, weight $66{\pm}5.3kg$) were participated in dual task experiments which consist of both walking alone and walking with a cognitive task. Two-back task was selected for the cognitive task since it did not have learning effect during the experimental procedure.3D motion analysis system was used to measure subject's position data by changing walking speed with 4.8, 5.6, 6.4, 6.8, and 7.2 km/hr. Stride rate was calculated by the time between heel contact and heel contact. Accuracy rate of a cognitive task during walking, coefficient of variance, allometric scaling methods and Fano factor were used to estimated the stride rate variability. As the walking speed increased, accuracy rate decreased and the logarithmic value of Fano factor increased which showed the statistical difference. Thus it can be concluded that the gait control mechanism is distracted by the secondary attention focus which is the cognitive task ie. two-back task. Further study is needed to clarify this by increasing the number of subject and experiment time.

• Korean Journal of Child Studies
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• v.8 no.1
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• pp.65-82
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• 1987

The purpose of the present research was to study mothers' perceptions about their children' cognitive abilities and the relations between such perceptions and the children's cognitive level. The subjects of this study were 60 children (mean age: 6 years 1 month: age range = 5;8 to 6;7) and their mothers. Each child responded to 18 tasks drawn from the Kodae-Binet IQ test. Subsequently, the mothers were asked 4 questions: an estimate of her child's success or failure on the tasks, a rating of the certainty of her judgment, an estimate of the age of mastery on each task both for her owr child and children in general. The data of the present study were analyzed with the 3-way ANOVA (sex x birth order x mother's education level), t-test, and Pearson correlation coefficient. Significant differences were found in (1) mothers' accuracy of their children's cognitive abilities according to children's birth order, (2) mothers' accuracy, overestimation, and certainty according to the level of difficulty of each task, and (3) mothers' estimate of age at mastery according to the level of each task. Furthermore, there were positive correlations between accurate predictions by the mother and correct answers by the child and between overestimations by the mother and correct answers by the child.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3472-3482
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• 2024

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.1-8
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• 2016

Spectrum sensing in cognitive radio networks allows secondary users to sense the unused spectrum without causing interference to primary users. Cognitive radio requires more accurate sensing results from unused portions of the spectrum. Accurate spectrum sensing techniques can reduce the probability of false alarms and misdetection. In this paper, a two-stage spectrum sensing scheme is proposed for cooperative spectrum sensing in cognitive radio networks. In the first stage, spectrum sensing is executed for each secondary user using energy detection based on double adaptive thresholds to determine the spectrum condition. If the energy value lies between two thresholds, a fuzzy logic scheme is applied to determine the channel conditions more accurately. In the second stage, a fusion center combines the results of each secondary user and uses a fuzzy logic scheme for combining all decisions. The simulation results show that the proposed scheme provides increased sensing accuracy by about 20% in some cases.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.119-131
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• 2014

In recent literature on traffic scheduling, the combination of the two-dimensional discrete-time Markov chain (DTMC) and the Markov modulated Poisson process (MMPP) is used to analyze the capacity of VoIP traffic in the cognitive radio system. The performance of the cognitive radio system solely depends on the accuracy of spectrum sensing techniques, the minimization of false alarms, and the scheduling of traffic channels. In this paper, we only emphasize the scheduling of traffic channels (i.e., traffic handling techniques for the primary user [PU] and the secondary user [SU]). We consider the following three different traffic models: the cross-layer analytical model, M/G/1(m) traffic, and the IEEE 802.16e/m scheduling approach to evaluate the performance of the VoIP services of the cognitive radio system from the context of blocking probability and throughput.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.17-24
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• 2023

Given the surge in the elderly population, and increasing in dementia cases, there is a growing interest in digital therapies that facilitate steady remote treatment. However, in the cognitive assessment of digital therapies through clinical trials, the absence of log data as an essential evaluation factor is a significant issue. To address this, we propose a solution of utilizing weighted derived variables based on high-importance variables' accuracy in log data utilization as an indirect cognitive assessment factor for digital therapies. We have validated the effectiveness of this approach using machine learning techniques such as XGBoost, LGBM, and CatBoost. Thus, we suggest the use of log data as a rapid and indirect cognitive evaluation factor for digital therapy users.

• Journal of Korean language education
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• v.28 no.4
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• pp.1-38
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• 2017

This longitudinal study analyzed syntactic development (Complexity, Accuracy, and Fluency; CAF) of six L2 Korean learners in a natural learning context. The learners recalled the stories of a short animated video through speaking and writing every 3 months, from month 0 to 15. The learners' responses were analyzed for a series of CAF measures and their cognitive, psychological, and social variables were investigated. The results showed that (i) L2 Korean learners' speaking and writing in various time periods showed significant differences in spoken and written accuracy, and complexity; (ii) the correlation between spoken and written complexity, spoken and written accuracy, as well as spoken and written fluency were significant, and (iii) the regression analysis showed that learners' cognitive, social, and psychological variables have significant effect on the L2 Korean syntactic development. The current study reports that L2 Korean learners engaged in self-learning in a natural learning environment without formal instruction made significant syntactic development.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.230-242
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• 2022

The purpose of this study was to verify the effectiveness of the computerized cognitive rehabilitation program in which areas and to suggest effective ways to utilize the program in the future, being conducted for 20 college students. We lasted this study from May 3 to 23, 2021. As a result of analyzing the groups using the Computer-based Cognitive Rehabilitation Program (CoTras), in terms of the difference in accuracy for the case of visual perception group B was statistically significantly improved than group C(p<0.05). In the case of attention, memory, and orientation, there was no significant difference between groups(p>0.05). In the case of reaction time difference, there was no significant difference between groups in visual perception, concentration, memory, and orientation(p>0.05). And in order to improve attention and visual perception, it is recommended to conduct the program three times with a duration of 20 minutes, and in order to improve orientation and memory, it can be said that it is helpful to conduct one experiment for at least 30 minutes rather than conducting short and frequent experiments. Through this study, we found that it is effective to apply different times according to each area to improve cognitive function. In other words, depending on the purpose of which cognitive function is to be improved, the duration of the program should be applied differently.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• Science of Emotion and Sensibility
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• v.10 no.4
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• pp.583-601
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• 2007

The desktop interface is not suitable for the environment in which mobile devices are used commonly with moving, because much attention should be paid for it. And the miniaturizing of mobile devices increases the workload for using them, makes the operation speeds lower and makes more errors. So the study of appropriate level of the input interface for this changing environment is needed. In the aspect of mobile devices. input style and the complexity of the menu hierarchy, this study will look for the way to decrease the workload when doing some primary tasks and using mobile devices simultaneously with moving. The input style was classified into gesture input style, button input style, and pointing input style. The accuracy and speed were measured when doing dual tasks, including a menu searching task and a figure memory task, through one input style of three. By Changing the level of menu hierarchy in the menu searching task, the accuracy of task execution was examined. These Experiments were done in standing state and moving state. In both state the pointing input style was the highest in the accuracy of task execution but the slowest in the speed. In contrast, the gesture input style was not high in the accuracy but the fastest in the speed. This fact shows that the gesture input style is suitable for the condition needed for speedy processing rather than accurate execution when moving.