• Title/Summary/Keyword: Abnormal

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Prevalence and Predicting Factors for Anxiety in Thai Women with Abnormal Cervical Cytology Undergoing Colposcopy

  • Jerachotechueantaveechai, Tanut;Charoenkwan, Kittipat;Wongpaka, Nahathai
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.4
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    • pp.1427-1430
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    • 2015
  • Aim: To compare prevalence of anxiety in women with abnormal cervical cytology (Pap) undergoing colposcopy to that of women attending the outpatient clinic for check-up and to examine predicting factors. Materials and Methods: In this cross-sectional analytical study, 100 women with abnormal cervical cytology (abnormal Pap group) and 100 women who attended our outpatient clinic for check-up (control group) were recruited from June 2013 to January 2014. The Hospital Anxiety and Depression Scale (HADS) was employed to determine anxiety in the participants with the score of ${\geq}11$ suggestive of clinically significant anxiety. The prevalence of anxiety and the mean HADS scores for anxiety were compared between the groups. For those with abnormal Pap, association between clinical factors and anxiety was assessed. A p-value of < 0.05 was considered significant. Results: Median age was different between the groups, 44.0 years in the abnormal Pap group and 50.0 years in the control group (p=0.01). The proportion of participants who had more than one sexual partner was higher in the abnormal Pap group, 39.2% vs. 24.7% (p=0.03) and the prevalence of anxiety was significantly higher 14/100 (14.0%) vs. 3/100 (3.0%) (p < 0.01). The prevalence of depression was comparable between the groups. The mean HADS scores for anxiety and depression subscales were significantly higher in the abnormal Pap group, 6.6 vs. 4.8 (P < 0.01) and 3.9 vs. 3.1 (p=0.05), respectively. For the abnormal Pap group, no definite association between clinical factors and anxiety was demonstrated. Conclusions: The prevalence of anxiety in women with abnormal Pap awaiting colposcopy was significantly higher than that of normal controls. Special attention including thorough counselling, with use of information leaflets and psychological support, should be directed to these women.

Classification Abnormal temperatures based on Meteorological Environment using Random forests (랜덤포레스트를 이용한 기상 환경에 따른 이상기온 분류)

  • Youn Su Kim;Kwang Yoon Song;In Hong Chang
    • Journal of Integrative Natural Science
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    • v.17 no.1
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    • pp.1-12
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    • 2024
  • Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

A Clincal Case of Abnormal Uterine Bleeding (붕루(崩漏) 환자(患者)의 임상보고 1례)

  • Im, Kyu-Jung;Yoo, Dong-Youl
    • Journal of Haehwa Medicine
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    • v.23 no.1
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    • pp.167-172
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    • 2014
  • Purpose : The purpose of this report is to record the effects of oriental treatments for the abnormal uterine bleeding Methods : This is a case report of a 16 year old female patient suffering from abnormal uterine bleeding for eight months. She was treated by Herb therapy for 3 months. During the treatments, we checked changes of symptoms. Results : After Herb therapy, abnormal uterine bleeding was disappeared and recovered the normal menstrual cycle. Conclusion : This clinical case shows that Herb therapy has potentially effective for abnormal uterine bleeding. More clinical data and studies are required for the treatment of abnormal uterine bleeding.

Effect of Abnormal Grain Growth and Heat Treatment on Electrical Properties of Semiconducting BaTiO3Ceramics

  • Lee, Joon-Hyung;Cho, Sang-Hee
    • Journal of the Korean Ceramic Society
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    • v.39 no.1
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    • pp.21-25
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    • 2002
  • Effect of abnormal grain growth and heat treatment time on the electrical properties of donor-doped semiconductive BaTiO$_3$ceramics was examined. La-doped BaTiO$_3$ceramics was sintered at 134$0^{\circ}C$ for different times from 10 to 600 min in order to change the volume fraction of the abnormal grains in samples. As a result, samples with different volume fraction of abnormal grain growth from 22 to 100% were prepared. The samples were annealed at 120$0^{\circ}C$ for various times. The resistivity of the sam-ples at room and above Curie temperature was examined. The complex impedance measurement as functions of the volume fraction of abnormal grains and annealing time was conducted. Separation of complex impedance semicircle was observed in a sample in which abnormal and fine grains coexist. The results are discussed from a viewpoint of microstructure-property relationship.

Effects of Abnormal Kernels in Brown Rice on Milling Characteristics (현미 비정상립이 도정특성에 미치는 영향)

  • Kim, Chang-Jin;Lee, Hyun-Jeong;Kim, Oui-Woung;Keum, Dong-Hyuk;Kim, Hoon
    • Journal of Biosystems Engineering
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    • v.32 no.1 s.120
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    • pp.1-5
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    • 2007
  • This study was conducted to find out effects of abnormal kernels of 0 to 30% in brown rice on quality characteristics during milling using friction type test mill. The average hardness values of abnormal and normal brown rice kernels were 6.52 kg$_f$, 8.48 kg$_f$, respectively. According to the increase of abnormal kernels in brown rice, grain temperature, required electrical energy, the broken kernels ratio, and the weight of solid matter on the surface of milled rice were increased due to crush of the abnormal kernels during milling, which proves that abnormal kernels in brown rice should be removed before milling to improve milling characteristics.

Safety Evaluation of Elevated Guideway during Abnormal Operation on LRT of Driverless Automatic Driving System (무인자동운전 경전철시스템 고가교량의 비상운전 중 안전성평가)

  • Son Eun-Jin;Kim Min-Soo;Lim Young-Su;Lim Jong-Pil
    • Journal of the Korean Society for Railway
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    • v.9 no.1 s.32
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    • pp.29-35
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    • 2006
  • Trains in LRT(Light Railway Transit) system usually have shorter car length than metro's because of their smaller passensers demand. Therefore it is very likely that the load condition of LRT system in abnormal operation, in case of which trains are in close proximity by system broke or train rescue works, could be worse rather than in normal operation, in spite of rare probability of abnormal operation. In this study, the target reliability indexes of several abnormal operations are estimated in accordance with the occurrence probabilities of each abnormal operation case and the reliability index of normal operation presented by the specification. From the indexes, load factors for the abnormal operation cases are estimated and the safety evaluation is performed for Yong-in LRT project.

Abnormal Grain Growth Behavior of $BaTiO_3$ Ceramics with Addition of Seed Grains (Seed 입자 첨가에 따른 $BaTiO_3$ 요업체의 비정상 입성장거동)

  • 이태헌;김정주;김남경;조상희
    • Journal of the Korean Ceramic Society
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    • v.32 no.5
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    • pp.587-593
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    • 1995
  • Abnomal grain growth behavior of BaTiO3 ceramics was investigated with addition of seed grains. It was foudn that the nucleation rate of abnormal grain was constant and growth of abnormal grain was linearly increased with sitnering time, regardless of amount of seed grains. These facts were also confirmed by fitting of the volume fraction of abnormal grain vs. sintering time using Avrami type equation (n=4). It was suggested that seed grains did not change the nucleation rate or growth mechanism of abnormal grain but increase the number of abnormal grains at initial stage of sintering and then it led to fine microstructure of BaTiO3 ceramics.

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Abnormal Human Activity Recognition System Based on CNN For Elderly Home Care (노인 홈 케어를위한 CNN 기반의 비정상 인간 활동 인식 시스템)

  • Valavi, Arezoo;Lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.542-544
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    • 2019
  • Changes in a person's health affect one's lifestyle and work activities. According to the World Health Organization (WHO), abnormal activity is growing faster in people aged 60 or more than any other age group in almost every country. This trend steadily continues and expected to increase further in the near future. Abnormal activity put these people at high risk of expected incidents since most of these people live alone. Human abnormal activity analysis is a challenging, useful and interesting problem among the researchers and its particularly crucial task in life and health care areas. In this paper, we discuss the problem of abnormal activities of old people lives alone at home. We propose Convolutional Neural Network (CNN) based model to detect the abnormal behaviors of elderlies by utilizing six simulated action data from daily life actions.

A Study of Video-Based Abnormal Behavior Recognition Model Using Deep Learning

  • Lee, Jiyoo;Shin, Seung-Jung
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.115-119
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    • 2020
  • Recently, CCTV installations are rapidly increasing in the public and private sectors to prevent various crimes. In accordance with the increasing number of CCTVs, video-based abnormal behavior detection in control systems is one of the key technologies for safety. This is because it is difficult for the surveillance personnel who control multiple CCTVs to manually monitor all abnormal behaviors in the video. In order to solve this problem, research to recognize abnormal behavior using deep learning is being actively conducted. In this paper, we propose a model for detecting abnormal behavior based on the deep learning model that is currently widely used. Based on the abnormal behavior video data provided by AI Hub, we performed a comparative experiment to detect anomalous behavior through violence learning and fainting in videos using 2D CNN-LSTM, 3D CNN, and I3D models. We hope that the experimental results of this abnormal behavior learning model will be helpful in developing intelligent CCTV.

Microstructure Control of Sr-Ferrite by Seed Addition (Seed 첨가에 의한 Sr-Ferrite의 미세구조 제어)

  • 박준홍;신효순;이병교
    • Journal of the Korean Ceramic Society
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    • v.32 no.1
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    • pp.90-94
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    • 1995
  • In Sr-ferrite system, it has been attempted to inhibit the abnormal grian growth using Sr-ferrite powders synthesized by molten salt method as the matrix and the seeds, respectively. At each sintering temperature, the addition of seed more than 15% suppressed the abnormal grain growth, and the uniform microstructure resulted. Particularly, at 12$25^{\circ}C$, it was observed that the maximum number of the abnormal grain growth nuclei was achieved since the abnormal grain growth was suppressed even by the addition of 10% seed.

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