• The Korean Society of Law and Medicine
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• v.21 no.3
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• pp.145-178
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• 2020

This paper examines discussions surrounding cognitive liberty, neuro-privacy, and mental integrity from the perspective of Neuro-rights. The right to control one's neurological data entails self-determination of collection and usage of one's data, and the right to object to any way such data may be employed to negatively impact oneself. As innovations in neurotechnologies bear benefits and downsides, a novel concept of the neuro-rights has been suggested to protect individual liberty and rights. In Oct. 2020, the Chilean Senate presented the 'Proyecto de ley sobre neuroderechos' to promote the recognition and protection of neuro-rights. This new bill defines all data obtained from the brain as neuronal data and outlaws the commerce of this data. Neurotechnology, especially when paired with big data and artificial intelligence, has the potential to turn one's neurological state into data. The possibility of inferring one's intent, preferences, personality, memory, emotions, and so on, poses harm to individual liberty and rights. However, the collection and use of neural data may outpace legislative innovation in the near future. Legal protection of neural data and the rights of its subject must be established in a comprehensive way, to adapt to the evolving data economy and technical environment.

• Korean Journal of Food Science and Technology
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• v.51 no.3
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• pp.272-277
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• 2019

The effects of medium-chain enriched diacylglycerol (MCE-DAG) oil on hepatic cholesterol homeostasis were investigated. HepG2 hepatocytes were treated with either 0.5, 1.0, or $1.5{\mu}g/mL$ of MCE-DAG for 48 h. There was no evidence of cytotoxicity by MCE-DAG up to $1.5{\mu}g/mL$. The level of proteins for cholesterol uptake including CLATHRIN and LDL receptor increased by MCE-DAG in a dose-dependent manner (p<0.05). Furthermore, proprotein convertase subtilisin/kexin type 9, an inhibitor of LDLR, was dose-dependently diminished (p<0.05), indicating cholesterol clearance raised. MCE-DAG significantly increased 3-hydroxy-3-methylglutaryl-coenzyme A reductase and acetyl-CoA acetyltransferase2 (p<0.05), required for cholesterol synthesis, and their transcriptional regulator sterol regulatory element-binding protein2 (p<0.05). These findings suggest that given conditions of prolonged sterol fasting in the current study activated both hepatic cholesterol synthesis and clearance by MCE-DAG. However, total intracellular level of cholesterol was not altered by MCE-DAG. Taken together, MCE-DAG has the potential to prevent hypercholesterolemia by increasing hepatic cholesterol uptake without affecting intracellular cholesterol level.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.3
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• pp.12-21
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• 2011

We investigated the location and surveillance system of fortress using inter-visibility analysis between fortress and the capital of the Silla Dynasty. The digital terrain model(DTM) was generated with $10{\times}10m$ grid in Arcview 3.2. Then three fortresses lines(Myeonghwal-sanseong, Namsan-shinseong, Seohyeong-sanseong) were superimposed on the DTM. 4 results of this study were drew out from the cumulative visibility analysis. First, the most of fortress lines which showed the high visible frequency from the Sila-Capital(538 viewpoints) have a good aspect toward the capital. It means that 3 fortresses secured the visibility to the capital. Second, the cumulative visibility analysis from 3 fortresses generated evenly distributed visible frequency across the inside of fortress. It shows that the inner area of fortress is more advantageous to command during the war. On the contrary, a number of invisible(vulnerable) regions which is scattered on the outside were supplemented by adjacent fortress. Third, the north area of the Sila-captial showed the highest visible frequency generated by sum up the visibility from 3 fortresses. The northern captial is placed within 4km distance easy to support at the Myeonghwal and Seohyeong-sanseong. We proved that the Sila-capital had organized a solid surveillance system by 3 fortresses. Fourth, we could infer the practical process of fortress layout from comparing a cumulative visibility map. For the secure of visibility and defense systems, the fortress line would form a rising shape to the peak. This practical location theory can replace the vague common location theory that the fortress would constructed on two thirds of mountain height. It will be an empirical method in the ancient remains research.

• The Journal of Korean Philosophical History
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• no.30
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• pp.161-190
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• 2010

In Shanghaibochujian-ZhouYi, there are a few special signs in red and black that had never been found in previous ZhouYi texts. Pu Mao Zuo (?茅左), who first sorted out Shanghaibochujian-ZhouYi, classified the signs into six types and explained them in terms of Yin-Yang theory. On the other hand, Li Shang Xin (李尙信) classified the signs into seven types and argued that these signs show that the order of the hexagrams(卦序) in Shanghaibochujian-ZhouYi is completely identical with that of the current version of ZhouYi. Edward L. Shaughnessy also conjectured that the order of the hexagrams(卦序) of Shanghaibochujian-ZhouYi is identical with that of the current version of Zhouyi after his material analysis of the Bamboo slips(竹簡) substance. Kondo Hiroyuki (近藤浩之) is based his interpretation of the order of the hexagrams(卦序) on his own classification of the signs which identified nine types. All these opinions contain some problems and given that the number of the Bamboo slips(竹簡) are very limited, we have to be very careful when we draw a conclusion. Shanghaibochujian-ZhouYi's signs can be possible when we suppose a 64-hexagrams(64卦) system instead of the 8-trigrams(8卦) system, which demands a reexamination of the common view that the 8-trigrams system preceded the 64-hexagrams system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.59-66
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• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• Journal of Science Education
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• v.46 no.1
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• pp.121-149
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• 2022

Descriptive assessment is a meaningful assessment method in relation to problem solving ability, reasoning ability, and communication ability as emphasized in mathematics curriculum. In Korea, as performance assessment has been emphasized since the 7th mathematics curriculum, descriptive assessment is being conducted as a method of performance assessment in schools. However, descriptive assessment has not been introduced in the university scholastic ability test for various reasons. Considering that descriptive assessment is emphasized in the mathematics classroom and has sufficient educational value, a serious discussion on the implementation of descriptive assessment in the university scholastic ability test will be necessary. In this study, we analyzed the descriptive assessment of Russia's unified state examination (USE) in the mathematics, which corresponds to Korea's university scholastic ability test. Through a literature review, we investigated how mathematics examination problems were structured in the USE and which mathematical abilities were required for the examination. In particular, the outer structure of the problems was analyzed focusing on the mathematics problems of the USE 2021, and the scoring method of the descriptive problems was also analyzed. The results of this study are expected to provide a variety of information on the possibility of introducing descriptive assessment in the Korean university scholastic ability tests.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.99-107
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• 2021

We live in a myriad of data. Various data are created in all situations in which we work, and we discover the meaning of data through big data technology. Many efforts are underway to find meaningful data. This paper introduces an analysis technique that enables humans to make better choices through the trend and prediction of time series data as a principal component analysis technique. Principal component analysis constructs covariance through the input data and presents eigenvectors and eigenvalues that can infer the direction of the data. The proposed method computes a reference axis in a time series data set having a similar directionality. It predicts the directionality of data in the next section through the angle between the directionality of each time series data constituting the data set and the reference axis. In this paper, we compare and verify the accuracy of the proposed algorithm with LSTM (Long Short-Term Memory) through cryptocurrency trends. As a result of comparative verification, the proposed method recorded relatively few transactions and high returns(112%) compared to LSTM in data with high volatility. It can mean that the signal was analyzed and predicted relatively accurately, and it is expected that better results can be derived through a more accurate threshold setting.

• Science of Emotion and Sensibility
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• v.25 no.2
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• pp.11-22
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• 2022

As social beings, we need to understand others' actions as quickly and accurately as possible. Action understanding can occur at many levels. We sometimes grasp others' intentions unintentionally. Other times, however, we have to expend effort to draw inferences about their goals. In the context of joint action, the joint Simon effect demonstrates that actors are influenced by the unintended representation of a co-actor's actions. This effect has been described as quasi-automatic, but it is unclear if the effect is automatic enough to be immune to cognitive load. Thus, we asked participants to complete a joint Simon task with or without a concurrent working memory task. One group of participants maintained a single digit in their mind during working memory load blocks (low-load group), while the other group maintained five digits (high-load group). As a result, the low-load group showed a joint Simon effect both during no-load and low-load blocks. In contrast, the high-load group had no joint Simon effect during either no-load or high-load blocks. These results suggest that the joint Simon effect is not an automatic phenomenon given that it requires cognitive resources. Actors in a joint task may represent a co-actor's actions in their task set, but only when cognitive resources are available.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.159-178
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• 2013

The purpose of this study was to 1) replicate the Wells effect(i.e., reluctance to rule against the Defendant solely on the basis of probabilistic evidence) in Korea and 2) examine the validity of an Alternative explanation(i.e., perception of risk of wrong verdict). In study 1(n=46), mock jurors in the tire-tracks condition were reluctant to rule against the defendant based on their perceived probability and this pattern was not resulted in the tire-tracks-belief condition. Therefore, the Wells effect was replicated in Korea. In study 2(n=70), we manipulated the participants' perception of risk of wrong verdict. That is, participants who were assigned in the high risk perception of wrong verdict were informed that if the defendant were found guilty, the defendant would get considerable demage both in finance and reputation of the company. Participants in the low risk perception of wrong verdict condition were informed that these demage would not be great. The results revealed that the Wells effect was pronounced in the high risk perception of wrong verdict condition. That is, participants were more reluctant to rule against the defendant when they perceive the significance of the result of wrong verdict as high. Limitations of the study and the directions for future study were discussed.