• Title/Summary/Keyword: trends over time

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Ice mass balance over the polar region and its uncertainty (극지방 빙하량 변화 (ice-mass balance) 관측과 에러 분석)

  • Seo, Ki-Weon
    • 한국지구물리탐사학회:학술대회논문집
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    • 2007.12a
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    • pp.63-72
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    • 2007
  • Current estimates of the ice-mass balance over the Greenland and the Antarctica using retrievals of time-varying gravity from GRACE are presented. Two different GRACE gravity data, UTCSR RL01 and UTCSR RL04, are used for the estimates to examine the impact of the relative accuracy of background models in the GRACE data processing for inter-annual variations of GRACE gravity data. In addition, the ice-mass balance is appraised from the conventional GRACE data, which represents global gravity, and the filtered GRACE data, which isolates the terrestrial gravity effect from GRACE gravity data. The former estimate shows that there exists similar negative trends of ice-mass balance over the Greenland from UTCSR RL01 and UTCSR RL04 while the time series from the both GRACE data over the Antarctica differ significantly from each other, and no apparent trends are observed. The result for the Greenland from the latter calculation is similar to the former estimate. However, the latter calculation presents positive trends of ice-mass balance for the Antarctica from both GRACE data. These results imply that residual oceanic geophysical signals, particularly for ocean tides, significantly corrupt the ice-mass estimate over the Antarctica as leakage error. In addition, the spatial alias of GRACE is likely to affect the ice-mass balance because the spatial spectrum of ocean tides is not conserved via GRACE sampling, and thus ocean tides contaminate terrestrial gravity signal. To minimize the alias effect, I suggest to use the combined gravity models from GRACE, SLR and polar motion.

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Exploring the Impact of Environmental Factors on Fermentation Trends: A Google Trends Analysis from 2020 to 2024

  • Won JOO;Eun-Ah CHEON
    • Journal of Wellbeing Management and Applied Psychology
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    • v.7 no.4
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    • pp.51-64
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    • 2024
  • Purpose: This study analyzes factors influencing public interest in fermentation using Google search trends. Specifically, it examines how key elements such as oxygen, temperature, time, and pH influence fermentation-0related searches from December 2020 to September 2024. Research design, data and methodology: Data from Google Trends was collected under the Beauty & Fitness category for the terms "Fermentation," "Oxygen," "Temperature," "Time," and "pH." Time series analysis was used to track trends over four years, and a correlation analysis was conducted to assess the relationships between these terms. A linear regression model was built to determine the influence of each factor on fermentation-related searches. The dataset was split into 80% training data and 20% testing data for model validation. Results: The correlation analysis indicated moderate positive relationships between fermentation-related searches and both time and pH, while oxygen had little to no correlation. The regression model showed that time and pH were the strongest influencers of fermentation interest, explaining 25% of the variance (R-squared = 0.25). Oxygen and temperature had minimal impact in predicting fermentation-related search interest. Conclusions: Time and pH are significant factors influencing public interest in fermentation-related topics, as shown by search trends. In contrast, oxygen and temperature, while important in the fermentation process itself, did not strongly affect public search behavior. These findings provide valuable insights for businesses and researchers looking to better understand consumer interest in fermentation products.

Influence of Mammographic Screening on Breast Cancer Incidence Trends in South Australia

  • Beckmann, Kerri Rose;Roder, David Murray;Hiller, Janet Esther;Farshid, Gelareh;Lynch, John William
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.7
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    • pp.3105-3112
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    • 2014
  • Purpose: To examine breast cancer (BC) incidence trends in relation to mammographic screening and risk factor prevalence in South Australia (SA). Materials and Methods: Trends in annual BC incidence rates were calculated using direct standardisation and compared with projected incidence derived from Poisson regression analysis of pre-screening rates. Annual percentage change and change time points were estimated using Joinpoint software. Biennial mammography screening participation rates were calculated using data from BreastScreen SA. Trends in overweight/obesity, alcohol use and hormone replacement therapy (HRT) use were examined using 1991-2009 Health Omnibus Survey data. Trends in total fertility were examined using data from the Australian Bureau of Statistics. Results: BC incidence increased around the time BreastScreen commenced and then stabilised in the mid-1990s. However rates have remained higher than projected, even though the proportion and age distribution of first time screening attendees stabilised around 1998. A decrease in BC incidence was observed among women aged 50-59yrs from the late-1990's but not among older women. Obesity and alcohol use have increased steadily in all age groups, while HRT use declined sharply from the late-1990s. Conclusions: BC incidence has remained higher than projected since mammography screening began. The sustained elevation is likely to be due to lead time effects, though over-diagnosis cannot be excluded. Declining HRT use has also impacted incidence trends. Implications: Studies using individual level data, which can account for changes in risk factor prevalence and lead time effects, are required to evaluate 'over-diagnosis' due to screening.

Time series analysis of patients seeking orthodontic treatment at Seoul National University Dental Hospital over the past decade

  • Lim, Hyun-Woo;Park, Ji-Hoon;Park, Hyun-Hee;Lee, Shin-Jae
    • The korean journal of orthodontics
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    • v.47 no.5
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    • pp.298-305
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    • 2017
  • Objective: This paper describes changes in the characteristics of patients seeking orthodontic treatment over the past decade and the treatment they received, to identify any seasonal variations or trends. Methods: This single-center retrospective cohort study included all patients who presented to Seoul National University Dental Hospital for orthodontic diagnosis and treatment between January 1, 2005 and December 31, 2015. The study analyzed a set of heterogeneous variables grouped into the following categories: demographic (age, gender, and address), clinical (Angle Classification, anomaly, mode of orthodontic treatment, removable appliances for Phase 1 treatment, fixed appliances for Phase 2 treatment, orthognathic surgery, extraction, mini-plate, mini-implant, and patient transfer) and time-related variables (date of first visit and orthodontic treatment time). Time series analysis was applied to each variable. Results: The sample included 14,510 patients with a median age of 19.5 years. The number of patients and their ages demonstrated a clear seasonal variation, which peaked in the summer and winter. Increasing trends were observed for the proportion of male patients, use of non-extraction treatment modality, use of ceramic brackets, patients from provinces outside the Seoul region at large, patients transferred from private practitioners, and patients who underwent orthognathic surgery performed by university surgeons. Decreasing trends included the use of metal brackets and orthodontic treatment time. Conclusions: Time series analysis revealed a seasonal variation in some characteristics, and several variables showed changing trends over the past decade.

Topics and Trends in Metadata Research

  • Oh, Jung Sun;Park, Ok Nam
    • Journal of Information Science Theory and Practice
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    • v.6 no.4
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    • pp.39-53
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    • 2018
  • While the body of research on metadata has grown substantially, there has been a lack of systematic analysis of the field of metadata. In this study, we attempt to fill this gap by examining metadata literature spanning the past 20 years. With the combination of a text mining technique, topic modeling, and network analysis, we analyzed 2,713 scholarly papers on metadata published between 1995 and 2014 and identified main topics and trends in metadata research. As the result of topic modeling, 20 topics were discovered and, among those, the most prominent topics were reviewed in detail. In addition, the changes over time in the topic composition, in terms of both the relative topic proportions and the structure of topic networks, were traced to find past and emerging trends in research. The results show that a number of core themes in metadata research have been established over the past decades and the field has advanced, embracing and responding to the dynamic changes in information environments as well as new developments in the professional field.

Assessing the Public's Interest in Orofacial Pain Specialists: A Google Trends Analysis

  • Jack Botros;Mariela Padilla
    • Journal of Oral Medicine and Pain
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    • v.48 no.4
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    • pp.137-143
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    • 2023
  • Purpose: To assess Google Trends (GT) search behavior regarding orofacial pain (OFP) and headaches. Methods: GT scores for OFP and headache specialists between February 2013 and December 2022 were analyzed. Statistical tests such as Poisson regression analyses, mean differences, and Cohen's D were used to assess the score change over time. Results: The top three search words for OFP specialists were "temporomandibular joint (TMJ) specialist," "TMJ doctor," and "TMJ dentist," whereas the top three search words for headache specialists were "Headache specialist," "Headache doctor," and "Migraine specialist." Here, TMJ is temporomandibular joint. The GT scores for OFP specialists increased significantly (p<0.05) for all years except 2017, with the highest mean difference in 2020. The scores for headache specialists showed similar trends but gradually. Conclusions: The interest in OFP and headache specialists expressed by Google searches has increased over the years. More awareness is needed regarding the OFP scope of practice, and the use of GT may serve as an indicator.

Trends Analysis on Research Articles in the Journal of Korean Society for Information Management (『정보관리학회지』 연구의 동향분석)

  • Seo, Eun-Gyoung
    • Journal of the Korean Society for information Management
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    • v.27 no.4
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    • pp.7-32
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    • 2010
  • The aims of this study were to provide a global overview of research trends in information science and to trace its changes in the main research topics over time using trends analysis. The study examined the topics of research articles published in Journal of Korean Society for Information Management between 1984 and 2009. Rather than taking a single snapshot of a given point in time, this study attempted to present a series of such pictures in order to identify trends over time. The fairly arbitrary decision was taken to divide the period under consideration into three 'publication windows': 1984-1994, 1995-2002, 2003-2009. The study revealed that the most productive areas were 'Information Service', followed by 'Information Organization', and 'Information System'. The most productive sub-areas were 'Library Service', 'User Study', 'Automatic Document Analysis', 'ILS', 'Thesaurus/Ontology', and 'Digital Library'. From the comparisons of intellectual structures of title keywords, the key research area in the field of Information Science was 'Information Retrieval'. The studies of IT applications and service system evaluation have been expanded.

An Analysis on the Rural Research Trends using Topic Modeling (토픽모델링을 활용한 농촌연구 동향분석)

  • Kim, Gaeun;Jeong, yookyung;Lim, Yeonghun
    • Journal of Korean Society of Rural Planning
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    • v.29 no.4
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    • pp.81-92
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    • 2023
  • The purpose of this study is to identify rural research topics, differences in research topics over time, and key mediators through the analysis of academic research trends using topic modeling. This study analyzed a total of 1,183 articles published in the Journal of Rural Planning and Rural Society over a 23-year period (2000-2022). We categorized rural research topics into 30, examined the proportion of research in each topic, and identified major changes in research topics over time. We also identified key words that mediate between research topics. The study found that, first, rural research trends can be categorized into five types (resources and utilization, area/space, people, ecosystem/environment, and tourism), with area/space being the most studied. Subtopics include rural amenities, rural disappearance/village miniaturization, and rural landscape management. Second, the research topics for each period were different. In the first period(2003-2007), the main research topics were rural amenities and Agricultural production- based climate vulnerability assessment. In the second period(2008-2012), the main research topics were Rural extinction and village depopulation, and rural landscape management, and in the third period(2013-2017), the main research topics were rural sixth industrialization and rural ecotourism. In the fourth period(2018-2022), rural development planning and rural life services(life SOC) were the main research topics. The significance of this study is that it extends the existing method of analyzing research trends and provides basic data to enhance comprehensive insights and understanding of rural research.

The Prevalence of Cardiovascular Disease Risk Factors and the Framingham Risk Score in Patients Undergoing Percutaneous Intervention Over the Last 17 Years by Gender: Time-trend Analysis From the Mayo Clinic PCI Registry

  • Lee, Moo-Sik;Flammer, Andreas J.;Kim, Hyun-Soo;Hong, Jee-Young;Li, Jing;Lennon, Ryan J.;Lerman, Amir
    • Journal of Preventive Medicine and Public Health
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    • v.47 no.4
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    • pp.216-229
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    • 2014
  • Objectives: This study aims to investigate trends of cardiovascular disease (CVD) risk factor profiles over 17 years in percutaneous coronary intervention (PCI) patients at the Mayo Clinic. Methods: We performed a time-trend analysis within the Mayo Clinic PCI Registry from 1994 to 2010. Results were the incidence and prevalence of CVD risk factors as estimate by the Framingham risk score. Results: Between 1994 and 2010, 25 519 patients underwent a PCI. During the time assessed, the mean age at PCI became older, but the gender distribution did not change. A significant trend towards higher body mass index and more prevalent hypercholesterolemia, hypertension, and diabetes was found over time. The prevalence of current smokers remained unchanged. The prevalence of ever-smokers decreased among males, but increased among females. However, overall CVD risk according to the Framingham risk score (FRS) and 10-year CVD risk significantly decreased. The use of most of medications elevated from 1994 to 2010, except for ${\beta}$-blockers and angiotensin converting enzyme inhibitors decreased after 2007 and 2006 in both baseline and discharge, respectively. Conclusions: Most of the major risk factors improved and the FRS and 10-year CVD risk declined in this population of PCI patients. However, obesity, history of hypercholesterolemia, hypertension, diabetes, and medication use increased substantially. Improvements to blood pressure and lipid profile management because of medication use may have influenced the positive trends.

Deep Learning Research Trend Analysis using Text Mining

  • Lee, Jee Young
    • International Journal of Advanced Culture Technology
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    • v.7 no.4
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    • pp.295-301
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    • 2019
  • Since the third artificial intelligence boom was triggered by deep learning, it has been 10 years. It is time to analyze and discuss the research trends of deep learning for the stable development of AI. In this regard, this study systematically analyzes the trends of research on deep learning over the past 10 years. We collected research literature on deep learning and performed LDA based topic modeling analysis. We analyzed trends by topic over 10 years. We have also identified differences among the major research countries, China, the United States, South Korea, and United Kingdom. The results of this study will provide insights into research direction on deep learning in the future, and provide implications for the stable development strategy of deep learning.