• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.243-250
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• 2021

The purpose of this study is to discuss the implicit meaning of advertising content with highly persuasive language formats from a communication perspective and its interpretation process in relation to communication education, while simultaneously developing interpretative codes for media literacy education in modern society. For a successful discussion, I assumed the narrative content of advertising content that implements a special purpose as a general conversational act, and raised the issue anew that regularity exists for implicit semantic expressions. It also said that in order for media literacy education in the present society to proceed correctly, linguistic interpretations of implicit meaning cannot be guided as a principle of communication in prior research. As a solution, we confirm that socio-cultural sharing knowledge and recognition are essential interpretation codes. For further discussion, the analysis of advertising media languages with special purposes in terms of language usage was conducted to verify the process of interpreting the implicit meaning shown in them. After analyzing the implicit advertising language that I arbitrarily typified, I found that the linguistic meaning implicit with the intention of persuading the speaker can be provided mostly as media literacy education as a framework for analysis by various information and cognitive effects. In other words, acceptors should not perform only literal interpretations in the process of interpreting the implicit meaning inherent in the media language. If guided by including native language materials and background knowledge, socio-cultural customs, and general common knowledge, efficient media literacy education can be expected.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.73-90
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• 2021

Previous studies have demonstrated that childhood memories can impact self-concepts. However, scant research has been conducted to determine whether and how the activation of childhood memories relates to the motivation of prosocial behaviors. Thus, this study investigated whether childhood memories facilitated prosocial behaviors through implicitly activating moral purity and how differently an abstract (vs. a concrete) construal level of autobiographical memories evoke prosocial intentions. According to the results of Study 1, the participants in the experimental condition of childhood memories were more motivated to perform prosocial behaviors than those in the controlled condition of recalling recent mundane activities. In the experimental condition, moral purity was activated more strongly than in the control condition. Study 2 demonstrated that participants in the "concrete" condition of childhood memories tended to the lower levels of prosocial motivation than those in the "abstract" condition wherein they were counting and describing good deeds from their childhood in detail. These results indicate that different construal levels (abstract vs. concrete) can mediate the relationship between childhood memories and prosocial behaviors. This study contributes to extending previous research regarding the determinants of motivating prosocial behaviors in cognitive processes.

• Journal of IKEEE
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• v.26 no.4
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• pp.633-638
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• 2022

Rencently, neuromorphic systems of spiking neural networks (SNNs) that imitate the human brain have attracted attention. Neuromorphic technology has the advantage of high speed and low power consumption in cognitive applications and processing. Resistive random-access memory (RRAM) for SNNs are the most efficient structure for parallel calculation and perform the gradual switching operation of spike-timing-dependent plasticity (STDP). RRAM as synaptic device operation has low-power processing and expresses various memory states. However, the integration of RRAM device causes high switching voltage and current, resulting in high power consumption. To reduce the operation voltage of the RRAM, it is important to develop new materials of the switching layer and metal electrode. This study suggested a optimized new structure that is the Metal/Al₂O₃/HfO_x/SWCNTs/N+silicon (MOCS) with single-walled carbon nanotubes (SWCNTs), which have excellent electrical and mechanical properties in order to lower the switching voltage. Therefore, we show an improvement in the gradual switching behavior and low-power I/V curve of SWCNTs-based memristors.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.299-304
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• 2023

Recently, drones have been used as a major means of attack drones in major wars around the world, and it seems likely that they will evolve into game changers in the future. Recently, drones have been used as a major means of attack drones in major wars around the world, and it seems likely that they will evolve into game changers in the future. In the major wars of the 21century, attack drones are used for precision fire-guided or self-destruct attacks, For the purpose of cognitive warfare, its territory is expanding not only to land and air, but also to sea and water. These attack drones will perform multi-domain operations, and for this purpose, the level of autonomy will be improved and High-Low Mix We will continue to develop by strengthening concept-based scalability. North Korea has also been making considerable efforts to operate attack drones for a long time, and activities such as third-country-level self-explosive drones, artificial intelligence-based clustered self-explosive drones, and self-destructive stealth unmanned semi-submersible are expected. In addition to North Korea's provocations and attacks, it is hoped that there will be a need for active follow-up research on our military's countermeasures and utilization plans.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.167-172
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• 2024

In major wars of the 21st century, drones are expanding beyond surveillance and reconnaissance to include land and air as well as sea and underwater for purposes such as precision strikes, suicide attacks, and cognitive warfare. These drones will perform multi-domain operations, and to this end, they will continue to develop by improving the level of autonomy and strengthening scalability based on the High-Low Mix concept. Recently, drones have been used as a major means in major wars around the world, and there seems to be a good chance that they will evolve into game changers in the future. North Korea has also been making significant efforts to operate reconnaissance and attack drones for a long time. North Korea has recently continued to engage in provocations using drones, and its capabilities are gradually becoming more sophisticated. In addition, with the recent emergence of new strategic Drones, wartime and peacetime threats such as North Korea's use of these to secure surveillance, reconnaissance and early warning capabilities against South Korea and new types of provocations are expected to be strengthened. Through this study, we hope to provide implications by analyzing the capabilities of North Korea's strategic Drones, predicting their operation patterns, and conducting active follow-up research on the establishment of a comprehensive strategy, such as our military's drone deployment and counter-drone system solutions.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.193-221
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• 2017

Grouping episodes into semantically related categories is necessary for better mnemonic structure. However, the effect of grouping on memory of subordinate details was not clearly understood. In an fMRI study, we tested whether attending superordinate during semantic association disrupts or enhances subordinate episodic details. In each cycle of the experiment, five cue words were presented sequentially with two related detail words placed underneath for each cue. Participants were asked whether they could imagine a category that includes the previously shown cue words in each cycle, and their confidence on retrieval was rated. Participants were asked to perform cued recall tests on presented detail words after the session. Behavioral data showed that reaction times for categorization tasks decreased and confidence levels increased in the third trial of each cycle, thus this trial was considered to be an important insight where a semantic category was believed to be successfully established. Critically, the accuracy of recalling detail words presented immediately prior to third trials was lower than those of followed trials, indicating that subordinate details were disrupted during categorization. General linear model analysis of the trial immediately prior to the completion of categorization, specifically the second trial, revealed significant activation in the temporal gyrus and inferior frontal gyrus, areas of semantic memory networks. Representative Similarity Analysis revealed that the activation patterns of the third trials were more consistent than those of the second trials in the temporal gyrus, inferior frontal gyrus, and hippocampus. Our research demonstrates that semantic grouping can cause memories of subordinate details to fade, suggesting that semantic retrieval during categorization affects the quality of related episodic memory.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.9-15
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• 2005

Purpose : This study attempted to investigate the effects of supply of highly concentrated $(30\%)$ oxygen on human ability of visuospatial cognition using time course data analysis of functional Magnetic Resonance Imaging (fMRI). Materials and Methods : To select an item set in the visuospatial performance test, two questionnaires with similar difficulty were developed through group testing. A group test was administered to 263 college students. Two types of questionnaire containing 20 questions were developed to measure the ability of visuospatial cognition. Eight college students (right-handed male, average age of 23.5 yrs) were examined for fMRI study. The experiment consisted of two runs of the visuospatial cognition testing, one with $21\%$ level of oxygen and the other with $30\%$ oxygen level. Each run consisted of 4 blocks, each containing control and visuospatial items. Functional brain images were taken from 37 MRI using the single-shot EPI method. Using the subtraction procedure, activated areas in the brain during visuospatial tasks were color-coded by t-score. To investigate the time course data in each activated area from brain images, 4 typical regions (cerebellum, occipital lobe, parietal lobe, and frontal lobe) were selected. Results : The average accuracy was $50.63{\pm}8.63$ and $62.50{\pm}9.64$ for $21\%\;and\;30\%$ oxygen respectively, and a statistically significant difference was found in the accuracy between the two types of oxygen (p<0.05). There were more activation areas observed at the cerebellum, occipital lobe, parietal lobe and frontal lobe with $30\%$ oxygen administration. The rate of increase in the cerebellum, occipital lobe and parietal lobe was $17\%$ and that of the frontal lobe, $50\%$. Especially, there were increase of intensity of BOLD signal at the parietal lobe with $30\%$ oxygen administration. The increase rate of the left parietal lobe was $1.4\%$ and that of the right parietal lobe, $1.7\%$. Conclusion : It is concluded that while performing visuospatial tasks, high concentrations of oxygen administration make oxygen administration sufficient, thus making neural network activate more, and the ability to perform visuospatial tasks increase.

• Korean Journal of Psychosomatic Medicine
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• v.25 no.2
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• pp.176-184
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• 2017

Objectives : Middle aged women with depression often experience hot flush symptoms. It is still unclear about the association between depression and hot flush symptoms. Therefore, we investigated hormonal profile, functional somatic symptoms, coping styles and attitude for menopause between depressed women with hot flush and those without hot flush. Methods : This study included 33 depressed patients with hot flush symptoms and 33 depressed patients without hot flush symptoms. Hot flush was confirmed through prospective daily symptom ratings for a week. Subjects' coping styles were assessed by the stress coping checklist. Somatic symptoms were assessed by the Patient Health Questionnaire-15(PHQ-15). Sex hormonal levels were assayed by a radioimmunoassay. The Brief World Health Organization Quality of Life Assessment Instrument(WHOQOL-BREF) was used to evaluate quality of life. Results : In coping style, depressed women with hot flush symptoms used less 'problem-centered coping'($13.15{\pm}3.17$) and 'search for social support'($11.83{\pm}2.84$) than those without hot flush symptoms($15.17{\pm}3.1$, p=0.028 ; $14.25{\pm}3.22$, p=0.009 ; respectively). Depressed women with hot flush symptoms showed more negative attitude toward post-menopause, but its statistical significance was marginally insufficient(p=0.059). We did not find any group differences in sex hormonal levels and somatic complaints assessed by the PHQ-15. The score of social relationship domain of WHOQOL-BREF was significantly lower in subjects with hot flush symptoms($8.62{\pm}2.04$) than subjects without hot flush symptoms($9.71{\pm}1.65$ ; p=0.044). Conclusions : Among middle aged women with depression, the manifestation of hot flush symptoms was associated with coping styles and attitude for menopausal transition. Hot flush symptoms in depressed women negatively influence quality of life, so clinicians actively perform therapeutic approach in case of depressed patients with hot flush symptoms. In case of depressed patients who present hot flushes, cognitive behavior therapy or stress management might be an effective treatment option in company with antidepressants or hormonal treatment. Later, longitudinal study will be needed to evaluate risk factor, cause and effect associated with hot flush and depression.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.39-51
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• 2003

Objectives: The Profile of Mood States (POMS) has been used broadly and frequently in various medical studies with various subjects. For the development and application of the Korean edition of POMS, called K-POMS, we translated POMS into Korean and then evaluated the reliability and validity of K-POMS. Methods: The subjects were 161 male students with a mean age of 18.1 years (15-30) and 244 female students with a mean age of 16.6 years (14-23). They were requested to perform K-POMS and SCL-90-R (Korean version) at the same time. Means, reliability coefficients, and test-retest correlations of K-POMS were calculated. Content validities, correlations with SCL-90-R, and discrimination validities in comparison with 76 depressive patients were obtained, and factor analyses were carried out. Results: Mean scores of Total Mood Disturbance (TMD) and some subscales (T, F, C, V factor) showed a significant difference between male and female students. The internal consistency coefficient ($\alpha$) of the total 65 items was 0.93, and ranged from 0.67 to 0.90 for subscales. Test-retest correlations of 43 subjects ranged from 0.27 to 0.63. Seven psychiatrists rated the properness of the content of each item as more than moderate degree (mean scale points=2.66, in the range of 0 to 4). Every subscale of KPOMS exhibited significant correlation with the matching subscale of SCL-90-R. Mean scores of K-POMS of the total 405 subjects were significantly different from those of the 76 depressive subjects after age correction. Six factors were extracted, accounting for 51.2% of total variance. Factor 6 consisted of 6 items which came from various subscales of POMS and represented "uncertainty and helplessness," which may be somewhat different to depression or sadness proper. Conclusion: The validity and reliability of K-POMS could be confirmed. The significant difference in K-POMS scores between depressive subjects and normal subjects suggests that K-POMS can be used clinically for the evaluation and screening of depression. The main structure of K-POMS is very similar to that of POMS, except the Confusion-Bewilderment factor which shows weak factor consistency in K-POMS. This may reflect some emotional characteristic of Koreans such as an undifferentiated aspect of cognitive efficiency. The sixth factor newly extracted from K-POMS also may be indicative of an unique emotional aspect of young Koreans.