• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.59-67
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• 2008

Due to the fast increase in cellular phone users, public interest on health effect of electromagnetic fields(EMFs) by cellular phonos is gradually increasing. Some EHS(electromagnetic hypersensitivity) patients complain of psycho-neurophysiological symptoms such as headaches, insomnia, memory loss resulting from RF radiation by CDMA cellular phones. However, EHS is difficult to diagnose and depends on the individual's subjective judgement. And we don't know clearly if the cause of EHS is uneasiness or real exposure. There have been various EHS volunteer studies on heart rate, blood pressure and subjective symptoms using GSM phones. But there are few studies on experimental case-control study investigating physiological parameters, subjective symptoms, and perception of EMFs. In this study, two volunteer groups of 17 self-declared EHS and 19 controls were exposed to both sham and real RF exposure by CDMA cellular phones for half an hour each. We investigated not only the physiological parameters such as heart rates, respiration rates and HRVs(hear rate variability), but also the perception of EMFs and subjective symptoms. As the results, EMF exposure did not have any effects on the subjective symptoms or physiological parameters for both groups. For the EMF perception, there was no evidence that EHS group perceived the EMFs correctly than the control group.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Korean Journal of Biological Psychiatry
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• v.8 no.2
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• pp.258-265
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• 2001

Objectives : Chronic alcohol consumption has been known to result in various neurocognitive deficits. Many neuropsychological studies revealed that the major disturbances occurred in the executive function, learning and short-term memory, visuospatial performance function, perceptuo-motor skills, and abstraction and problem solving abilities. This study was done to identify which cognitive areas might be mainly affected. Methods : The cognitive disturbance was evaluated using the Korean Version of the Mini Mental State Examination(MMSEK) and the 7 Minute Screen(7MS) in male inpatients with alcohol dependence(N=3 : as well as in age and education level matched healthy male controls(N=30). Four individual tests of the 7MS were consisted of the Benton Temporal Orientation Test, the Enhanced Cued Recall, the Clock Drawing and the Category Fluency. Results : 1) The average scores of four individual test of the 7MS for the alcoholics were $2.77{\pm}4.38$ for the Benton Temporal Orientation Test, $13.90{\pm}2.02$ for the Memory Test(the Cued Recall $6.77{\pm}1.94$, the Uncued Recall $7.10{\pm}2.45$), $5.84{\pm}1.86$ for the Clock Drawing, and $12.58{\pm}3.29$ for the Category Fluency. Except the Benton Temporal Orientation Test, there were statistically significant differences between test scores of alcoholics and those of controls(p<0.01). 2) The alcoholics who had MMSE-K score <24 were 9.68%. The average(${\pm}S.D.$) score of the MMSE-K for the patient group($27.23{\pm}2.62$) was significantly(p<0.001) lower than that of the healthy controls($29.20{\pm}1.24$). There were no statistically significant differences between four individual test scores of the 7MS of alcoholics with the MMSE-K score <24(N=3) and those of alcoholics with the MMSE-K score ${\geq}24$(N=28). 3) Four individual test scores of the 7MS seemed to have statistically significant association with such variables as MMSE-K, duration of alcohol drinking, blood magnesium concentration, liver function and thyroid function. Conclusion : Mild deficits of cognitive areas such as orientation, memory, visuospatial abilities and verbal fluency could be found in alcohol dependence.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.733-740
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.355-364
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• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.377-383
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• 2021

The purpose of this study is to present the direction of elementary school AI education by analyzing cases of classes related to AI education in actual school settings. For this purpose, 19 classes were collected as elementary school class cases based on AI education. According to the result of analyzing the class case, it was confirmed that the class was designed in a hybrid aspect of learning content and method using AI. As a result of analyzing the achievement standards and learning goals, action verbs related to memory, understanding, and application were found in 8 classes using AI from a tool perspective. When class was divided into introduction, development, and rearrangement stages, the AI education element appeared the most in the development stage. On the other hand, when looking at the ratio of learning content and learning method of AI education elements in the development stage, the learning time for approaching AI education as a learning method was overwhelmingly high. Based on this, the following implications were derived. First, when designing the curriculum for schools and grades, it should be designed to comprehensively deal with AI as a learning content and method. Second, to supplement the understanding of AI, in the short term, it is necessary to secure the number of hours in practical subjects or creative experience activities, and in the long term, it is necessary to secure information subjects.

• Journal of Korea Game Society
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• v.4 no.4
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• pp.11-18
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• 2004

The on-line games in the past were played by only two persons exchanging data based on one-to-one connections, whereas recent ones (e.g. MMORPG: Massively Multi-player Online Role-playings Game) enable tens of thousands of people to be connected simultaneously. Specifically, Korea has established an excellent network infrastructure that can't be found anywhere in the world. Almost every household has a high-speed Internet access. What made this possible was, in part, high density of population that has accelerated the formation of good Internet infrastructure. However, this rapid increase in the use of on-line games may lead to surging traffics exceeding the limited Internet communication capacity so that the connection to the games is unstable or the server fails. expanding the servers though this measure is very costly could solve this problem. To deal with this problem, the present study proposes the load distribution technology that connects in the form of local clustering the game servers divided by their contents used in each on-line game reduces the loads of specific servers using the load balancer, and enhances performance of sewer for their efficient operation. In this paper, a cluster system is proposed where each Game server in the system has different contents service and loads are distributed efficiently using the game server resource information such as CPU utilization. Game sewers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Simulation studies show that our method performs better than other traditional methods. In terms of response time, our method shows shorter latency than RR (Round Robin) and LC (Least Connection) by about 12%, 10% respectively.

• Korean Security Journal
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• no.12
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• pp.225-243
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• 2006

This study is focused on the relation in the motive and the evaluation for the job in a special private security field. The supplement of the outstanding human resources is one of most important matter to improve the private security industry. For it the applicant's motive and evaluation of whose quality should be screened to recruit proper and oustanding human resources into the industry. For the study the follow elements would be considered. First, What is the real motive to apply the job and how prospect on the job the applicant will be taken. Second, what is different point of view to the job between male and female. Third, what relationship is in achieving the job performance between the temporary motive and the planed motive. Forth, what effects are on the job satisfaction and the planed motive for the job. With the above elements the survey was taken based on each sex for the study and the results are out as below. a) Male is in higher than female in taking with unplaned job motive and for job satisfaction is much higher in 1-20 age range. b) In general, the expectation on the job is much higher than the current job status, the male are in the expextation on the job and the female are in the the current job status. c) The job satisfaction is on positive effect to the planed taken job but the unplaned taken job is on negative. From the Research the most concerning element on the recruiting new employee is applicant's positive attitude on the job he/she will be taken.

• Korean Security Journal
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• no.9
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• pp.99-131
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• 2005

Terrorism which became today's common phenomena over the world is one of the most serious threats the world confront. Although International society make and operate outstanding anti-terrorism system, terror would never end without solving fundamental problems. The main body of terrorism converts from nation to organization and from organization to cell, which makes it difficult for us to recognize the main body. Since the target of today's new terrorism is many and unspecified persons, terrorists will never hesitate to use mass destruction weapons such as nuclear, biological, chemical weapons, and also use cyber-technique or cyber-terrorism. So, effective counter-terrorism measures should be performed as follows. First, it must be better for international society should make long-time plan of solving fundamental problems of terrorism other than to operate directly on terror organization and its means. Second, preventive method should be made. The most effective method of eradicating terrorism is prevention. For this, it is necessary to remove environmental elements of terrorism and terrorist bases, and to stop inflow of money and mass destruction weapons to terrorists. Third, integrated anti-terror organization should be organized and operated for continuous counter-terrorism operations. Also international alliance for anti-terrorism should be maintained to share informations and measures. Fourth, concerned department in the government should prepare counter-terrorism plans in their own parts as follows and make efforts to integrate the plans. - Ministry of Government Administration and Home Affairs : conventional terror - Ministry of Health and Welfare : bio-terror - Ministry of Science and Technology : nuclear-terror Especially, they should convert their policy and operation from post-terror actions to pre-terror actions, designate terror as national disaster and organize integrated emergency response organization including civil, government, and military elements. In conclusion, pre-terror activities and remedy of fundamental causes is the best way to prevent terror. Also, strengthening of intelligence activities, international cooperations, and preventive and comprehensive counter-measures must not ignored.

• Journal of Life Science
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• v.29 no.6
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• pp.747-753
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• 2019

Cognitive decline is characterized by reduced long-/short-term memory and attention span, and increased depression and anxiety. Such decline is associated with various degenerative brain disorders, especially Alzheimer's disease (AD) and Parkinson's disease (PD). The increases in elderly populations suffering from cognitive decline create social problems and impose economic burdens, and also pose safety threats; all of these problems have been extensively researched over the past several decades. Possible causes of cognitive decline include metabolic and hormone imbalance, infection, medication abuse, and neuronal changes associated with aging. However, no treatment for cognitive decline is available. In neurodegenerative diseases, changes in the gut microbiota and gut metabolites can alter molecular expression and neurobehavioral symptoms. Changes in the gut microbiota affect memory loss in AD via the downregulation of NMDA receptor expression and increased glutamate levels. Furthermore, the use of probiotics resulted in neurological improvement in an AD model. PD and gut microbiota dysbiosis are linked directly. This interrelationship affected the development of constipation, a secondary symptom in PD. In a PD model, the administration of probiotics prevented neuron death by increasing butyrate levels. Dysfunction of the blood-brain barrier (BBB) has been identified in AD and PD. Increased BBB permeability is also associated with gut microbiota dysbiosis, which led to the destruction of microtubules via systemic inflammation. Notably, metabolites of the gut microbiota may trigger either the development or attenuation of neurodegenerative disease. Here, we discuss the correlation between cognitive decline and the gut microbiota.