• Journal of Korean Dental Science
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• v.16 no.2
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• pp.128-148
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• 2023

Dementia is an umbrella term that describes the loss of thinking, memory, attention, logical reasoning, and other mental abilities to the extent that it interferes with the activities of daily living. More than 50 million individuals worldwide live with dementia, which is expected to increase to 131 million by 2050. Recent research has shown that poor oral health increases the risk of dementia, while oral health declines with cognitive decline. In this narrative review, the literature was based on the "hypothesis" that dementia and oral health have a close relationship, and appropriate oral health and occlusal rehabilitation treatment can improve the quality of life of patients with dementia and prevent progression. We conducted a literature search in PubMed and Google Scholar databases, using the search terms "dementia," "major neurocognitive disorder," "dentition," "occlusion," "tooth loss," "dental prosthesis," "dental implant," and "occlusal rehabilitation" in the title field over the past 30 years. A total of 131 studies that scientifically addressed dementia, oral health, and/or oral rehabilitation were included. In a meta-analysis, the random effect model demonstrated significant tooth loss increasing the dementia risk 3.64-fold (pooled odds ratio=3.64, 95% confidence interval [2.50~5.32], P-value=0.0348). Tooth loss can be an important indicator of cognitive function decline. As the number of missing teeth increases, the risk of dementia increases. Loss of teeth can lead to a decrease in the ascending information to the brain and reduced masticatory ability, cerebral blood flow, and psychological atrophy. Oral microbiome dysbiosis and migration of key bacterial species to the brain can also cause dementia. Additionally, inflammation in the oral cavity affects the inflammatory response of the brain and the complete body. Conversely, proper oral hygiene management, the placement of dental implants or prostheses to replace lost teeth, and the restoration of masticatory function can inhibit symptom progression in patients with dementia. Therefore, improving oral health can prevent dementia progression and improve the quality of life of patients.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1680-1689
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• 2021

Objective: To investigate the diagnostic yield of diffusion-weighted imaging (DWI) in patients with transient global amnesia (TGA) and identify significant parameters affecting diagnostic yield. Materials and Methods: A systematic literature search of the MEDLINE and EMBASE databases was conducted to identify studies that assessed the diagnostic yield of DWI in patients with TGA. The pooled diagnostic yield of DWI in patients with TGA was calculated using the DerSimonian-Laird random-effects model. Subgroup analyses were also performed of slice thickness, magnetic field strength, and interval between symptom onset and DWI. Results: Twenty-two original articles (1732 patients) were included. The pooled incidence of right, left, and bilateral hippocampal lesions was 37% (95% confidence interval [CI], 30-44%), 42% (95% CI, 39-46%), and 25% (95% CI, 20-30%) of all lesions, respectively. The pooled diagnostic yield of DWI in patients with TGA was 39% (95% CI, 27-52%). The Higgins I² statistic showed significant heterogeneity (I² = 95%). DWI with a slice thickness ≤ 3 mm showed a higher diagnostic yield than DWI with a slice thickness > 3 mm (pooled diagnostic yield: 63% [95% CI, 53-72%] vs. 26% [95% CI, 16-40%], p < 0.01). DWI performed at an interval between 24 and 96 hours after symptom onset showed a higher diagnostic yield (68% [95% CI, 57-78%], p < 0.01) than DWI performed within 24 hours (16% [95% CI, 7-34%]) or later than 96 hours (15% [95% CI, 8-26%]). There was no difference in the diagnostic yield between DWI performed using 3T vs. 1.5T (pooled diagnostic yield, 31% [95% CI, 25-38%] vs. 24% [95% CI, 14-37%], p = 0.31). Conclusion: The pooled diagnostic yield of DWI in TGA patients was 39%. DWI obtained with a slice thickness ≤ 3 mm or an interval between symptom onset and DWI of > 24 to 96 hours could increase the diagnostic yield.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.417-428
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• 2005

Today, IT organizations perform projects with vision related to marketing and financial profit. The objective of realizing the vision is to improve the project performing ability in terms of QCD. Organizations have made a lot of efforts to achieve this objective through process improvement. Large companies such as IBM, Ford, and GE have made over $80\%$ of success through business process re-engineering using information technology instead of business improvement effect by computers. It is important to collect, analyze and manage the data on performed projects to achieve the objective, but quantitative measurement is difficult as software is invisible and the effect and efficiency caused by process change are not visibly identified. Therefore, it is not easy to extract the strategy of improvement. This paper measures and analyzes the project performance, focusing on organizations' external effectiveness and internal efficiency (Qualify, Delivery, Cycle time, and Waste). Based on the measured project performance scores, an OT (Opportunity Tree) model was designed for optimizing the project performance. The process of design is as follows. First, meta data are derived from projects and analyzed by quantitative GQM(Goal-Question-Metric) questionnaire. Then, the project performance model is designed with the data obtained from the quantitative GQM questionnaire and organization's performance score for each area is calculated. The value is revised by integrating the measured scores by area vision weights from all stakeholders (CEO, middle-class managers, developer, investor, and custom). Through this, routes for improvement are presented and an optimized improvement method is suggested. Existing methods to improve software process have been highly effective in division of processes' but somewhat unsatisfactory in structural function to develop and systemically manage strategies by applying the processes to Projects. The proposed OT model provides a solution to this problem. The OT model is useful to provide an optimal improvement method in line with organization's goals and can reduce risks which may occur in the course of improving process if it is applied with proposed methods. In addition, satisfaction about the improvement strategy can be improved by obtaining input about vision weight from all stakeholders through the qualitative questionnaire and by reflecting it to the calculation. The OT is also useful to optimize the expansion of market and financial performance by controlling the ability of Quality, Delivery, Cycle time, and Waste.

• Cartoon and Animation Studies
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• s.42
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• pp.213-240
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• 2016

The character is not dependent on an original story world any more. It is not limited to it's own story, but gets out and expands the other story with new character, background story, and event regardless of genre and media. The purpose of this study is to analyze why should this phenomenon happen from the media perspective and to build a character storytelling model through the specific examples. With the advent of the digital paradigm the storytelling model is emphasized character storytelling. Character is no longer limited to just one narrative and extended beyond the boundary narrative, media and genre. There are four background. First, disappearance of the big story with the advent of postmodernism and the emergnece of small story. Second, the emergence of fandom culture and charater's liberalization. Third, character as public goods with database. Fourth, changes in author's position. In fact, in the traditional narrative theory there has been discussion about the character all the time. But character storytelling meets transmedia storytelling, discussions were accelerated. The character was preceded by a narrative independent existence. Even if that character has occurred even while leading cause narrative. In this paper, we suggest two model as specific methodology to expand the story world fixed character. One is phychology transition, another is roll transition. This study get the value to build the new storytelling model with digital paradigm.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.196-211
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• 2007

In the Product Line Engineering (PLE), current studies about an analysis of the feature have uncertain and ad-hoc criteria of analysis based on developer’s intuition or domain expert’s heuristic approach and difficulty to extract explicit features from a product in a product line because the stakeholders lack comprehensive understanding of the features in feature modeling. Therefore, this paper proposes a model of the analyzing commonality and variability of the feature based on the Ontology. The proposed model in this paper suggests two approaches in order to solve the problems mentioned above: First, the model explicitly expresses the feature by making an individual feature attribute list based on the meta feature modeling to understand common feature. Second, the model projects an analysis model of commonality and variability using the semantic similarity between features based on the Ontology to the stakeholders. The main contribution of this paper is to improve the reusability of distinguished features on developing products of same line henceforth.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.716-730
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• 2008

In Service-Oriented Architecture (SOA), service providers develop and deploy reusable services on the repositories, and service consumers utilize blackbox form of services through their interfaces. Services are also highly evolvable and often heterogeneous. Due to these characteristics of the service, it is hard to manage the faults if faults occur on the services. Autonomic Computing (AC) is a way of designing systems which can manage themselves without direct human intervention. Applying the key disciplines of AC to service management is appealing since key technical issues for service management can be effectively resolved by AC. In this paper, we present a theoretical model, Symptom-Cause-Actuator (SCA), to enable autonomous service fault management in SOA. We derive SCA model from our rigorous observation on how physicians treat patients. In this paper, we first define a five-phase computing model and meta-model of SCA. And, we define a schema of SCA profile, which contains instances of symptoms, causes, actuators and their dependency values in a machine readable form. Then, we present detailed algorithms for the five phases that are used to manage faults the services. To show the applicability of our approach, we demonstrate the result of our case study for the domain of 'Flight Ticket Management Services'.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.233-242
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• 2019

ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4457-4463
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• 2015

Common genetic variation Q192R in the paraoxonase 1 (PON1) gene has been considered to be implicated in the development of many cancers. Nevertheless, results from the related studies were inconsistent. To elucidate the association, we performed a meta-analysis for 8,112 cases and 10,037 controls from 32 published case-control studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the association by STATA 12.0 software. Overall, we revealed that the PON1-192R allele was associated with a reduced risk of the overall cancers. Moreover, in the stratified analysis by cancer types (breast cancer, prostate cancer, brain cancer etc.), the results showed that PON1-192R allele was associated with a decreased risk in breast cancer (R vs Q: OR=0.605, 95% CI=0.378-0.967, $P_{heterogeneity}=0.000$; RR vs QQ: OR=0.494, 95% CI=0.275-0.888, $P_{heterogeneity}=0.002$; RQ vs QQ: OR=0.465, 95% CI=0.259-0.835, $P_{heterogeneity}=0.000$; and RR+RQ vs QQ: OR=0.485, 95% CI=0.274-0.857, $P_{heterogeneity}=0.000$), and associated with prostate cancer in homozygote (RR vs QQ: OR=0.475, 95% CI=0.251-0.897, $P_{heterogeneity}=0.001$) and recessive models (RR vs RQ+QQ: OR=0.379, 95% CI=0.169-0.853, $P_{heterogeneity}=0.000$), while an increased risk was identified in lymphoma (R vs Q: OR=1.537, 95% CI=1.246-1.896, $P_{heterogeneity}=0.944$; RR vs QQ: OR=2.987, 95% CI=1.861-4.795, $P_{heterogeneity}=0.350$; RR+RQ vs QQ: OR=1.354, 95% CI=1.021-1.796, $P_{heterogeneity}=0.824$; and RR vs RQ+QQ: OR=2.934, 95% CI=1.869-4.605, $P_{heterogeneity}=0.433$), and an increased risk in prostate cancer under heterozygote comparison (RQ vs QQ: OR=1.782, 95% CI=1.077-2.950, $P_{heterogeneity}=0.000$) and dominant models (RR+RQ vs QQ: OR=1.281, 95% CI=1.044-1.573, $P_{heterogeneity}=0.056$). When subgroup analysis that performed by the control source (hospital based or population based), a decreased risk of the overall cancers was revealed by homozygote (RR vs QQ: OR=0.601, 95% CI=0.366-0.987, $P_{heterogeneity}=0.000$) and dominant models (RR vs RQ+QQ: OR= 0.611, 95% CI=0.384-0.973, $P_{heterogeneity}=0.000$) in hospital based group. Stratifying by ethnicity, a significantly reduced risk of the overall cancers under allele contrast model (R vs Q: OR=0.788, 95% CI=0.626-0.993, $P_{heterogeneity}=0.000$) was uncovered in Caucasian. In summary, these findings suggested that PON1 Q192R polymorphism was associated with a reduced risk of the overall cancers, nevertheless, it might increase cancer susceptibility of prostate and lymphoma risk. Large well-designed epidemiological studies will be continued on this issue of interest.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.239-259
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• 2024

In this study, a qualitative meta-analysis was conducted on research papers on earth science education to derive knowledge of students' understanding of specific science topics-greenhouse effect, global warming, and climate change-within the context of collective Pedagogical Content Knowledge (PCK). Twenty-two research papers addressing students' alternative conceptions (misconceptions) about these topics were selected and analyzed for their respective definitions, causes (mechanisms), and impacts. Semantic network analysis and a mental model framework were applied to synthesize the findings. The meta-analysis revealed several key insights: (1) Regarding the greenhouse effect, students often used the terms "greenhouse effect" and "global warming" interchangeably, lacked knowledge about the types of greenhouse gases, and misunderstood their roles. They commonly associated the greenhouse effect with environmental pollution or changes in the ozone layer, failing to recognize its relation to the heat balance between the surface and atmosphere. (2) Concerning global warming, students confused it with sea level rise and linked it to pollution, ozone layer changes, and glacier melting. They understood global warming as a disruption of the heat balance between the surface and atmosphere but had misconceptions about its environmental impacts. (3) In terms of climate change, students used the term interchangeably with global warming, weather change, and climate anomalies. They associated climate change with atmospheric pollution and ozone layer depletion but misunderstood its environmental impacts. As result, three mental models-categorical, mechanistic, and hierarchical misconceptions-were identified as collective PCK. The implications for enhancing earth science teachers' PCK were discussed based on these findings.