• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.26-46
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• 2020

An irrigated-maize agroecosystem is viewed as an open thermodynamic system upon which solar radiation impresses a large gradient that moves the system away from equilibrium. Following the imperative of the second law of thermodynamics, such agroecosystem resists and reduces the externally applied gradient by using all means of this nature-human coupled system acting together as a nonequilibrium dissipative process. The ultimate purpose of our study is to test this hypothesis by examining the energetics of agroecosystem growth and development. As a first step toward this test, we employed the eddy covariance flux data from 2003 to 2014 at the AmeriFlux NE1 irrigated-maize site at Mead, Nebraska, USA, and analyzed the energetics of this agroecosystem by scrutinizing its radiation, energy and entropy exchange. Our results showed: (1) more energy capture during growing season than non-growing season, and increasing energy capture through growing season until senescence; (2) more energy flow activity within and through the system, providing greater potential for degradation; (3) higher efficiency in terms of carbon uptake and water use through growing season until senescence; and (4) the resulting energy degradation occurred at the expense of increasing net entropy accumulation within the system as well as net entropy transfer out to the surrounding environment. Under the drought conditions in 2012, the increased entropy production within the system was accompanied by the enhanced entropy transfer out of the system, resulting in insignificant net entropy change. Drought mitigation with more frequent irrigation shifted the main route of entropy transfer from sensible to latent heat fluxes, yielding the production and carbon uptake exceeding the 12-year mean values at the cost of less efficient use of water and light.

• IMMUNE NETWORK
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• v.1 no.2
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• pp.104-108
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• 2001

Aging is a senescence and defined as a normal physiologic and structural alterations in almost all organ systems with age. As Leonard Hayflick, one of the first gerontologists to propose a theory of biologic aging, indicated that a theory of aging or longevity satisfies the changes of above conditions to be universal, progressive, intrinsic and deleterious. Although a number of theories have been proposed, it is now clear that cell aging (cell senescence) is multifactorial. No single mechanism can account for the many varied manifestations of biological aging. Many theories have been proposed in attempt to understand and explain the process of aging. Aging is effected in individual by genetic factors, diet, social conditions, and the occurrence of age-related diseases as diabetes, hypertension, and arthritis. It involves an endogenous molecular program of cellular senescence as well as continuous exposure throughout life to adverse exogenous influences, leading to progressive infringement on the cell's survivability so called wear and tear. So we could say the basic mechanism of aging depends on the irreversible and universal processes at cellular and molecular level. The immediate cause of these changes is probably an interference in the function of cell's macromolecules-DNA, RNA, and cell proteins-and in the flow of information between these macromolecules. The crucial questions, unanswered at present, concerns what causes these changes in truth. Common theories of aging are able to classify as followings for the easy comprehension. 1. Biological, 1) molecular theories - a. error theory, b. programmed aging theory, c. somatic mutation theory, d. transcription theory, e. run-out-of program theory, 2) cellular theories - a. wear and tear theory, b. cross-link theory, c. clinker theory, d. free radical theory, e. waste product theory, 3) system level theory-a. immunologic/autoimmune theory, 4) others - a. telomere theory, b. rate of living theory, c. stress theory, etc. Prevention of aging is theoretically depending on the cause or theory of aging. However no single theory is available and no definite method of delaying the aging process is possible by this moment. The most popular action is anti-oxidant therapy using vitamin E and C, melatonin and DHEA, etc. Another proposal for the reverse of life-span is TCP-17 and IL-16 administration from the mouse bone marrow B cell line study for the immunoglobulin VDJ rearrangement with RAG-1 and RAG-2. Recently conclusional suggestion for the extending of maximum life-span thought to be the calory restriction.

• International Commerce and Information Review
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• v.18 no.3
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• pp.3-21
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• 2016

The thesis examines genealogical study of various aspects to overcome lots of problems which come by when we execute SWIFTNet TSU BPO. Practical implications regarding the innovation of electronic trade infrastructure are as follows. First, the shipping documents in the SWIFTNet TSU BPO are directly sent to an importer by an exporter after the baseline is confirmed. With this process itself, therefore, the bank cannot secure the account receivable. When initiating the SWIFTNet TSU BPO deal, it is needed to set regulations on the bank's account receivable security in the contract. Second, the SWIFTNet TSU BPO should also have an institutionally unified sharing platform with security, stability and convenience. It other words, it is needed to develop services which meet e-payment paradigm and international environments through continued analysis on market changes and flow. Third, the SWIFTNet TSU is useful in terms of promptness, reduction of risk in foreign exchange payment, cost reduction. Therefore, the SWIFT should be perfectly united and linked among the banks, importer and exporter to make the SWIFTNet TSU more convenient in countries around the world. Fourth, the SWIFT should be approached from the aspect of expansion of network and creation of a new business model through analysis on these problems with a worldwide perspective. At the same time, it is necessary to build a cooperative system to share information and promote comprehensive management for efficient operation.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.211-220
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• 2010

The objective of this paper presents the application of an "integrated urban flood modeling-runoff model, urban flood model and sewer system model-" in a highly urbanized area of Samcheok where is seriously inundated in 2002 and 2003. For this, we demonstrate how couple a 1-D hydrodynamic model of the river, a 2-D hydrodynamic model of the overland (surface) flow, and a sewer network model including each boundary conditions. In order to make data file for the model, topographic information like elevation and share rate of buildings are directly extracted from DEM or topographical source data without data exchange to avoid uncertainty errors. Furthermore, the research is to assess the impacts of Manning n and buildings influences to inundated depth by changing its share ratio from 10 % to 30 % in low-land urban area. As a results, we found out that the urban inundated depth was decreased by Manning n but increased by buildings ratio. The calculated results of inundation was similar with observed one in 2002 and 2003 flooding. Furthermore, the area was also inundated under not riverbank break case in 2002 flooding.

• Journal of the Korean Geographical Society
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• v.46 no.6
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• pp.673-692
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• 2011

Advances in computer technology have enabled us to develop and use numerical landscape evolution models (NLEMs) for exploring the dynamics of geomorphic system from a variety of viewpoints which previously could have not been taken. However, as of yet there have been no trials using or developing NLEMs in Korea. The purpose of this research is to develop a 2 dimensional NLEM on a geological time scale and evaluate its usefulness. The newly developed NLEM (ND-NLEM) treats bedrock weathering as one of the major geomorphic processes and attempts to simulate the thickness of soil. As such it is possible to model the weathering-limited as well as the transport-limited environment on hillslopes. Moreover the ND-NLEM includes not only slow and continuous mass transport like soil creep, but also rapid and discrete mass transport like landslides. Bedrock incision is simulated in the ND-NLEM where fluvial transport capacity is large enough to move all channel bed loads, such that ND-NLEM can model the detachment-limited environment. Furthermore the ND-NLEM adopts the D-infinity algorithm when routing flows in the model domain, so it reduces distortion due to the use of the steepest descent slope flow direction algorithm. In the experiments to evaluate the usefulness of the ND-NLEM, characteristics of the channel network observed from the model results were similar to those of the case study area for comparison, and the hypsometry curve log during the experiment showed rational evidence of landscape evolution. Therefore, the ND-NLEM is shown to be useful for simulating landscape evolution on a geological time scale.

• Journal of Pharmacopuncture
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• v.19 no.3
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• pp.197-206
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• 2016

Introduction: This study aims to investigate the effects of acupuncture stimulation on the radial artery's pressure pulse wave, along with various hemodynamic parameters, and to explore the possible underlying mechanism of pulse diagnosis in healthy participants in their twenties. Methods and analysis: This study is a prospective, single-arm, exploratory clinical study. A total of 25 healthy participants, without regard to gender, in their twenties will be recruited by physicians. Written informed consent will be obtained from all participants. The participants will receive acupuncture once at ST36 on both sides. The radial arterial pulse waves will be measured on the left arm of the subjects by using an applicable pulse tonometric device (KIOM-PAS). On the right arm (appearing twice), electrocardiogram (ECG), photoplethysmogram (PPG), respiration and cardiac output (CO) signals, will be measured using a physiological data acquisition system (Biopac module), while the velocity of blood flow, and the diameter and the depth of the blood vessel will be measured using an ultrasonogram machine on the right arm (appearing twice). All measurements will be conducted before, during, and after acupuncture. The primary outcome will be the spectral energy at high frequencies above 10 Hz ($SE_{10-30Hz}$) calculated from the KIOM-PAS device signal. Secondary outcomes will be various variables obtained from the KIOM-PAS device, ECG, PPG, impedance cardiography modules, and an ultrasonogram machine. Discussion: The results of this trial will provide information regarding the physiological and the hemodynamic mechanisms underlying acupuncture stimulation and clinical evidence for the influence of acupuncture on the pressure pulse wave in the radial artery. Ethics and dissemination: This study was approved by the Institutional Review Board (IRB) of Kyung Hee University's Oriental Medical Center, Seoul, Korea (KOMCIRB-150818-HR-030). The study findings will be published in peer-reviewed journals and presented at national and international conferences. Trial registration number: This trial was registered with the Clinical Research Information Service (CRIS) at the Korea National Institute of Health (NIH), Republic of Korea (KCT0001663), which is a registry in the World Health Organization's (WHO's) Registry Network.

• Journal of Korean Elementary Science Education
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• v.41 no.2
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• pp.307-324
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• 2022

This study examined the content diversity of seven authorized science textbooks by comparing the characteristics of the science concept description and the contents of inquiry activities in the "weight of objects" unit. For each textbook, the flow of concept description content and the uniqueness of the concept description process were analyzed, and the number of nodes and links and words with high connections were determined using language network analysis. In addition, for the inquiry activities described in each textbook, the inquiry subject, inquiry type, science process skill, and uniqueness were investigated. Results showed that the authorized textbooks displayed no more diversity than expected in their scientific concept description method or their inquiry activity composition. The learning elements, inclusion of subconcepts, and central words were similar for each textbook. The comparison of inquiry activities showed similarities in their contents, inquiry types, and scientific process skills. Specifically, these textbooks did not introduce any research topics or experimental methods that were absent in previous textbooks. However, despite the fact that the authorized textbook system was developed based on the same curriculum, some efforts were made to make use of its strengths. Since the sequence of subconcepts to explain the core contents differed across textbooks, this explanation process was divided into several types, and although the contents of inquiry activities were the same, the materials for inquiry activities were shown differently for each textbook to improve and overcome the difficulties in the existing experiments. These findings necessitate the continuation of efforts to utilize the strengths of certified textbooks.

• IMMUNE NETWORK
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• v.23 no.5
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• pp.39.1-39.15
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• 2023

Coronavirus disease 2019 (COVID-19) vaccination may non-specifically alter the host immune system. This study aimed to evaluate the effect of COVID-19 vaccination on hepatitis B surface Ag (HBsAg) titer and host immunity in chronic hepatitis B (CHB) patients. Consecutive 2,797 CHB patients who had serial HBsAg measurements during antiviral treatment were included in this study. Changes in the HBsAg levels after COVID-19 vaccination were analyzed. The dynamics of NK cells following COVID-19 vaccination were also examined using serial blood samples collected prospectively from 25 healthy volunteers. Vaccinated CHB patients (n=2,329) had significantly lower HBsAg levels 1-30 days post-vaccination compared to baseline (median, -21.4 IU/ml from baseline), but the levels reverted to baseline by 91-180 days (median, -3.8 IU/ml). The velocity of the HBsAg decline was transiently accelerated within 30 days after vaccination (median velocity: -0.06, -0.39, and -0.04 log₁₀ IU/ml/year in pre-vaccination period, days 1-30, and days 31-90, respectively). In contrast, unvaccinated patients (n=468) had no change in HBsAg levels. Flow cytometric analysis showed that the frequency of NK cells expressing NKG2A, an NK inhibitory receptor, significantly decreased within 7 days after the first dose of COVID-19 vaccine (median, -13.1% from baseline; p<0.001). The decrease in the frequency of NKG2A⁺ NK cells was observed in the CD56^dimCD16⁺ NK cell population regardless of type of COVID-19 vaccine. COVID-19 vaccination leads to a rapid, transient decline in HBsAg titer and a decrease in the frequency of NKG2A⁺ NK cells.