• Title/Summary/Keyword: embedding

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Review of Clinical Researches of Thread-Embedding Therapy for Pediatric Enuresis (소아 야뇨증의 매선치료에 대한 문헌 고찰 - 중의학 논문을 중심으로 -)

  • Kim Yeon Jeong;Chang Gyu Tae;Lee Sun Haeng
    • The Journal of Pediatrics of Korean Medicine
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    • v.38 no.3
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    • pp.1-12
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    • 2024
  • Objectives This study aimed to evaluate the efficacy and usefulness of thread-embedding therapy for pediatric enuresis by analyzing clinical evidence. Methods Six clinical studies on thread-embedding therapy for pediatric enuresis were selected from the China National Knowledge Infrastructure (CNKI) database, with a focus on traditional Chinese medicine. The study designs, patient characteristics, treatment methods, and safety assessments were analyzed. Results Among the six studies, four were case reports and two were randomized controlled trials. Thread-embedding therapy was performed two to four times, with intervals ranging from one week to one month. CV3 (中極), SP6 (三陰交), ST36 (足三里) were used frequently, and the total effective rate for thread-embedding therapy ranged from 88.89% to 100%. Conclusions Thread-embedding therapy is effective for pediatric enuresis; however, more research is needed to evaluate its safety.

Enhanced robust data embedding techniques (내성을 강화한 data embedding기법)

  • 정인식;권오진
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.247-250
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    • 2002
  • Data embedding has recently become important for protecting authority. In this paper, we Propose a robust data embedding technique for images. Our techniques are based on the convolution between message image and a random phase carrier. We add extra bits with carrier image to improve precision of detecting rate, moreover, we use block by block based cyclic correlation for the compensation of distortion. In experiment, we show that the proposed a1gorithm is robust to Stirmark 3.1. attacks.

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Twitter Hashtags Clustering with Word Embedding (Word Embedding기반 Twitter 해시 태그 클러스터링)

  • Nguyen, Tien Anh;Yang, Hyung-Jeong
    • Proceedings of the Korea Contents Association Conference
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    • 2019.05a
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    • pp.179-180
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    • 2019
  • Nowadays, clustering algorithm is considered as a promising solution for lacking human-labeled and massive data of social media sites in numerous machine learning tasks. Many researchers propose disaster event detection systems have ability to determine special local events, such as missing people, public transport damage by clustering similar tweets and hashtags together. In this paper, we try to extend tweet hashtag feature definition by applying word embedding. The experimental results are described that word embedding achieve better performance than the reference method.

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A Literature Study and Recent Tendency on Oriental Correction of Deformities and 'Needle-embedding Therapy' (한방 성형과 매선 침법의 문헌적 고찰 및 최근 동향)

  • Lee, Eun-Mi;Park, Dong-Soo;Kim, Do-Ho;Kim, Hyun-Wook;Jo, Eun-Heui;Ahn, Min-Seob;Lee, Geon-Mok
    • Journal of Acupuncture Research
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    • v.25 no.3
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    • pp.229-236
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    • 2008
  • 'Needle-embedding therapy', also called 'Acupoint Embedding Therapy' is the newly induced therapy which uses specialized tools. Embedded alien substance stimulates the acupoint and helps to keep the stimulation up. Needle-embedding therapy is mainly used for chronic diseases and deficiency syndromes, and also for other diseases including acute pain and excessive syndromes. Recently, clinical doctors are studying this therapy vigorously on the foundation of 'theory of meridian pathway' and applying for facial and body esthetics such as face-lift, correction skin troubles, depilation and so on. In spite of all these effect, theories for 'Needle-embedding Therapy' doesn't seem clearly arranged yet. So we, here, present the philological basis of 'Needle-embedding Therapy' from referring to old records and newly publicated papers and consider the new trend of this therapy in Korean and China.

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The Clinical investigation studies in early stage of intractable peripheral facial paralysis using Needle-Embedding Therapy (매선요법(埋線療法)을 이용한 중증 구안괘사(口眼喎斜) 초기치료에 대한 임상적 고찰)

  • Han, Jung-Min;Yoon, Jung-Won;Kang, Na-Ru;Ko, Woo-Shin;Yoon, Hwa-Jung
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.25 no.3
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    • pp.113-128
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    • 2012
  • Objectives : This study was performed to investigate the effect of Needle-Embedding Therapy in early stage of intractable peripheral facial paralysis. Methods : 46 patients with severe peripheral facial paralysis were treated with oriental medicine therapy including Needle-Embedding Therapy in their early stage. We evaluated the effect of Needle-Embedding Therapy by House-Brackmann Grading system, decrease of subjective symptoms and satisfaction measurement. Results : After treatment, HB-Scale grade was significantly decreased(p-value<0.001). More than 50% of subjective symptoms were disappeared in 82.61% of patients. 80.48% of the patients was satisfied with the Needle-Embedding Therapy. Conclusion : Needle-Embedding Therapy could be effective to improve symptoms of severe peripheral facial paralysis in early stage. Further studies will be required to identify the beneficial effect of Needle-Embedding Therapy in early stage of peripheral facial paralysis.

Improving Embedding Model for Triple Knowledge Graph Using Neighborliness Vector (인접성 벡터를 이용한 트리플 지식 그래프의 임베딩 모델 개선)

  • Cho, Sae-rom;Kim, Han-joon
    • The Journal of Society for e-Business Studies
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    • v.26 no.3
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    • pp.67-80
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    • 2021
  • The node embedding technique for learning graph representation plays an important role in obtaining good quality results in graph mining. Until now, representative node embedding techniques have been studied for homogeneous graphs, and thus it is difficult to learn knowledge graphs with unique meanings for each edge. To resolve this problem, the conventional Triple2Vec technique builds an embedding model by learning a triple graph having a node pair and an edge of the knowledge graph as one node. However, the Triple2 Vec embedding model has limitations in improving performance because it calculates the relationship between triple nodes as a simple measure. Therefore, this paper proposes a feature extraction technique based on a graph convolutional neural network to improve the Triple2Vec embedding model. The proposed method extracts the neighborliness vector of the triple graph and learns the relationship between neighboring nodes for each node in the triple graph. We proves that the embedding model applying the proposed method is superior to the existing Triple2Vec model through category classification experiments using DBLP, DBpedia, and IMDB datasets.

A Case Study of Androgenetic Alopecia in woman Improved by Pharmacopuncture Therapy and Needle-embedding Therapy (매선 치료 및 약침 치료로 개선된 여성형 탈모 환자 1례)

  • Yoon, Hwa-Jung
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.27 no.3
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    • pp.162-170
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    • 2014
  • Objective : The purpose of this study is to report the effect of Pharmacopuncture Therapy and Needle-embedding Therapy on Androgenetic Alopecia in woman. Methods : The patient was treated by acupucture, pharmacopuncture, needle-embedding. The improvement of the patient was judged by phtograpies and VAS(Visual Analogue Scale) score. Results & Conclusions : Her hair loss and physical condition were improved remarkably, and an author consider that continuous clinical study will be needed in other needle-embedding therapy and korean medical treatment.