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Preparation of Core-shell Type Nanoparticles of Poly($\varepsilon$-caprolactone) /Poly(ethylene glycol)/Poly( $\varepsilon$-caprolactone) Triblock Copolymers

  • Ryu, Jae Gon;Jeong, Yeong Il;Kim, Yeong Hun;Kim, In Suk;Kim, Do Hun;Kim, Seong Ho
    • Bulletin of the Korean Chemical Society
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    • v.22 no.5
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    • pp.467-475
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    • 2001
  • A triblock copolymer based on $poly(\varepsilon-caprolactone)$ (PCL) as the hydrophobic part and poly(ethylene glycol) (PEG) as the hydrophilic portion was synthesized by a ring-opening mechanism of ${\varepsilon}-caprolactone$ with PEG containing a hydroxyl group at bot h ends as an initiator. The synthesized block copolymers of PCL/PEG/PCL (CEC) were confirmed and characterized using various analysis equipment such as 1H NMR, DSC, FT-IR, and WAXD. Core-shell type nanoparticles of CEC triblock copolymers were prepared using a dialysis technique to estimate their potential as a colloidal drug carrier using a hydrophobic drug. From the results of particle size analysis and transmission electron microscopy, the particle size of CEC core-shell type nanoparticles was determined to be about 20-60 nm with a spherical shape. Since CEC block copolymer nanoparticles have a core-shell type micellar structure and small particle size similar to polymeric micelles, CEC block copolymer can self-associate at certain concentrations and the critical association concentration (CAC) was able to be determined by fluorescence probe techniques. The CAC values of the CEC block copolymers were dependent on the PCL block length. In addition, drug loading contents were dependent on the PCL block length: the larger the PCL block length, the higher the drug loading content. Drug release from CEC core-shell type nanoparticles showed an initial burst release for the first 12 hrs followed by pseudo-zero order release kinetics for 2 or 3 days. CEC-2 block copolymer core-shell type nanoparticles were degraded very slowly, suggesting that the drug release kinetics were governed by a diffusion mechanism rather than a degradation mechanism irrelevant to the CEC block copolymer composition.

PATTERN OF THE AMINO ACIDS INFLUENCED ON NITROGEN METABOLISM OF EDIBLE BAMBOO SPROUTS (식용죽순의 질소대사에 미치는 아미노산의 페턴에 관하여)

  • KWON, Oh Yong
    • Journal of Plant Biology
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    • v.6 no.4
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    • pp.5-10
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    • 1963
  • KWON, Oh Yong (Chunju Teacher's Coll.) Partern of the amino acids influedced on nitrogen metabolism of edible bamboo sprouts. Kor. Jour. Bot. VI (4) : 5-10, 1963. It had been scarcely reported by any worker that the essential amino acids to be indispensable in our daily life contained in edible bamboo sprouts and that they had various pattern of free amino acids. For this reason, especially two species of Korean bamboo sprouts collected from the surburb of Chunju, in April, 1963 were used for researching the essential amino acids and free amino acids appeared on paper chromatography. The most suitable part for our edibles was investigated as a part of bio-chemical studies on Korean bamboo sprouts. The free amino acids contained in two species were found as 5-15 kinds and there were a few of difference according to it's growing parts. Many kinds of free amino acids were found in the end parts more than the tip parts and mid parts of bamboo sprouts. Besides, the essential amino acids in each species were found to 3-9 kinds. From the characteristics and the experiments marked above, it was suggested to the author that many kinds of free amino acids in the end part accelerated the formation of nitrogen comounds more than the other parts.

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Effects of Gait Training Using a Robot for Balance in Total Hip Arthroplasty Patients after Bilateral Avascular Necrosis: A Case Study

  • Kim, So-Yeong;Kim, Byeong-Geun;Cho, Woon-Su;Park, Chi-Bok
    • The Journal of Korean Physical Therapy
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    • v.33 no.5
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    • pp.231-237
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    • 2021
  • Purpose: This study sought to investigate the effects of robot-assisted gait training on balance in total hip arthroplasty (THA) patients after bilateral avascular necrosis (AVN). Methods: This case study in two patients utilized an 'A-B-A' single-subject experimental design that included five days of pre-intervention, followed by five days of intervention, and five days of post-intervention. The intervention involved the use of a standing inclined robot (R-bot) for 15 minutes. The outcome measures were evaluated using the Functional Reaching Test (FRT), Time Up to Go (TUG), and the Modified One Leg Standing Test (OLST). Results: Patient 1 showed improvement based on data gathered from baseline A to intervention period B, with results as follows: FRT improved from 27.7 cm to 41.28 cm, OLST LT from 14.03 seconds to 67.37 seconds, OLST RT from 2.94 seconds to 35.97 seconds, and TUG from 12.96 seconds to 7.82 seconds. Patient 2 also showed improvement from baseline A to intervention period B, with results as follows: FRT improved from 17.18 cm to 24.3 cm, OLST LT from 11.53 seconds to 52.01 seconds, OLST RT from 12.99 seconds to 62.19 seconds, and TUG from 27.31 seconds to 12.99 seconds. Conclusion: Based on the results of this study, robotic rehabilitation during the early stages after surgery is effective for promoting balance in patients who have undergone THA due to bilateral AVN.

A Filtering Method of Malicious Comments Through Morpheme Analysis (형태소 분석을 통한 악성 댓글 필터링 방안)

  • Ha, Yeram;Cheon, Junseok;Wang, Inseo;Park, Minuk;Woo, Gyun
    • The Journal of the Korea Contents Association
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    • v.21 no.9
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    • pp.750-761
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    • 2021
  • Even though the replying comments on Internet articles have positive effects on discussions and communications, the malicious comments are still the source of problems even driving people to death. Automatic detection of malicious comments is important in this respect. However, the current filtering method of the malicious comments, based on forbidden words, is not so effective, especially for the replying comments written in Korean. This paper proposes a new filtering approach based on morpheme analysis, identifying coarse and polite morphemes. Based on these two groups of morphemes, the soundness of comments can be calculated. Further, this paper proposes various impact measures for comments, based on the soundness. According to the experiments on malicious comments, one of the impact measures is effective for detecting malicious comments. Comparing our method with the clean-bot of a portal site, the recall is enhanced by 37.93% point and F-measure is also enhanced up to 47.66 points. According to this result, it is highly expected that the new filtering method based on morpheme analysis can be a promising alternative to those based on forbidden words.

Intrusion Artifact Acquisition Method based on IoT Botnet Malware (IoT 봇넷 악성코드 기반 침해사고 흔적 수집 방법)

  • Lee, Hyung-Woo
    • Journal of Internet of Things and Convergence
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    • v.7 no.3
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    • pp.1-8
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    • 2021
  • With the rapid increase in the use of IoT and mobile devices, cyber criminals targeting IoT devices are also on the rise. Among IoT devices, when using a wireless access point (AP), problems such as packets being exposed to the outside due to their own security vulnerabilities or easily infected with malicious codes such as bots, causing DDoS attack traffic, are being discovered. Therefore, in this study, in order to actively respond to cyber attacks targeting IoT devices that are rapidly increasing in recent years, we proposed a method to collect traces of intrusion incidents artifacts from IoT devices, and to improve the validity of intrusion analysis data. Specifically, we presented a method to acquire and analyze digital forensics artifacts in the compromised system after identifying the causes of vulnerabilities by reproducing the behavior of the sample IoT malware. Accordingly, it is expected that it will be possible to establish a system that can efficiently detect intrusion incidents on targeting large-scale IoT devices.

Intelligent Information Technology and Democracy : Algorithm-driven Information Environment and Politics (지능정보기술과 민주주의: 알고리즘 정보환경과 정치의 문제)

  • Min, Hee;Kim, Jeong-Yeon
    • Informatization Policy
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    • v.26 no.2
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    • pp.81-95
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    • 2019
  • This study explores how the advanced data analysis capabilities of intelligent information technology are being utilized in politics. In particular, we focus on the fact that voter behavioral targeting in election campaigns comes into conflict with the democratic process in various ways. For this purpose, this study examines political micro-targeting and political bots. It is aimed at showing that these technology-based campaign techniques work as a factor preventing free expression of opinions and discussions, which are the core of democracy itself. Then we identify the attributes of the algorithm that affects them. As a result, this study suggests that the following issues might arise regarding intelligent information technology-based politics and democracy. First, inequality in political participation becomes more severe. Second, the public debate between voters gets more difficult. Third, superficial politics is prevalent. Fourth, single-issue politics and the exclusion of political representation is likely to increase. Fifth, political privacy might also be invaded. Based on our discussions, this study concludes that it is our role to find ways by which intelligent information technology and democracy can coexist.

Indoor environmental alarm robot (실내환경 오염 측정장치 알람봇 구현)

  • Cho, Hae-Jin;Lee, Hye-bin;Lee, Gi-Ho;Oh, Min-u;Choi, Ji-Seung;Kim, Su-Min;Kim, Seong-Hyeon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.549-551
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    • 2016
  • In this paper, With the development of modern science and technology are Sheds to stay indoors rather than outdoors space it increased significantly compared to the past. And a wide variety of research about outdoor air quality until recently, efforts are underway but the issue of air quality in the room is the fact that all considered relatively lightly. As the contamination of the room air is polluted, unlike the natural environment, a large outdoor air dilution rate, the dilution rate is very low, once the contaminated air continuously circulating exerts a very bad influence on the health of people staying in the room. In this study, movement characteristics of the person living in a room, the air measuring device for the study of the active indoor environmental control system reflects the life form to measure the quality of the measured air in real time for transmitting the information to the user of the smart devices, alarm bot It was implemented and operational applications.

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Simulation Study on Search Strategies for the Reconnaissance Drone (정찰 드론의 탐색 경로에 대한 시뮬레이션 연구)

  • Choi, Min Woo;Cho, Namsuk
    • Journal of the Korea Society for Simulation
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    • v.28 no.1
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    • pp.23-39
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    • 2019
  • The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

A Tensor Space Model based Deep Neural Network for Automated Text Classification (자동문서분류를 위한 텐서공간모델 기반 심층 신경망)

  • Lim, Pu-reum;Kim, Han-joon
    • Database Research
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    • v.34 no.3
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    • pp.3-13
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    • 2018
  • Text classification is one of the text mining technologies that classifies a given textual document into its appropriate categories and is used in various fields such as spam email detection, news classification, question answering, emotional analysis, and chat bot. In general, the text classification system utilizes machine learning algorithms, and among a number of algorithms, naïve Bayes and support vector machine, which are suitable for text data, are known to have reasonable performance. Recently, with the development of deep learning technology, several researches on applying deep neural networks such as recurrent neural networks (RNN) and convolutional neural networks (CNN) have been introduced to improve the performance of text classification system. However, the current text classification techniques have not yet reached the perfect level of text classification. This paper focuses on the fact that the text data is expressed as a vector only with the word dimensions, which impairs the semantic information inherent in the text, and proposes a neural network architecture based upon the semantic tensor space model.

Development of Artificial Intelligence-based Legal Counseling Chatbot System

  • Park, Koo-Rack
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.3
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    • pp.29-34
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    • 2021
  • With the advent of the 4th industrial revolution era, IT technology is creating new services that have not existed by converging with various existing industries and fields. In particular, in the field of artificial intelligence, chatbots and the latest technologies have developed dramatically with the development of natural language processing technology, and various business processes are processed through chatbots. This study is a study on a system that provides a close answer to the question the user wants to find by creating a structural form for legal inquiries through Slot Filling-based chatbot technology, and inputting a predetermined type of question. Using the proposal system, it is possible to construct question-and-answer data in a more structured form of legal information, which is unstructured data in text form. In addition, by managing the accumulated Q&A data through a big data storage system such as Apache Hive and recycling the data for learning, the reliability of the response can be expected to continuously improve.