• Asian Journal for Public Opinion Research
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• 제5권4호
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• pp.285-301
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• 2018

There have been many studies that applied a data-driven analysis method to social media data, and some have even argued that this method can replace traditional polls. However, some other studies show contradictory results. There seems to be no consensus as to the methodology of data collection and analysis. But as social media-based election research continues and the data collection and analysis methodology keep developing, we need to review the key points of the controversy and to identify ways to go forward. Although some previous studies have reviewed the strengths and weaknesses of the social media-based election studies, they focused on predictive performance and did not adequately address other studies that utilized social media to address other issues related with public opinion during elections, such as public agenda or information diffusion. This paper tries to find out what information we can get by utilizing social media data and what limitations social media data has. Also, we review the various attempts to overcome these limitations. Finally, we suggest how we can best utilize social media data in understanding public opinion during elections.

• 항공우주시스템공학회지
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• 제9권4호
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• pp.62-66
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• 2015

During the conceptual design of turboprop aircraft, the power effect driven from rotating propeller is typically obtained from empirical data. In the present paper, propeller power effect was obtained by using unsteady three-dimensional Navier-Stokes solver with $k-{\omega}$ turbulence model for the accurate prediction of turboprop aircraft performance. In order to simulate the relative motion between propeller and fuselage, unsteady sliding mesh method was used. During simulation, three flow conditions such as climb, cruise and descending flight were selected considering the flight envelop of the real turboprop aircraft. For the correction of aerodynamic coefficients, the thrust effect of engine exhaust gas was included based on the engine manufacturer's data. Using the computational results, the correction table for the aerodynamic coefficient of turboprop aircraft was suggested for the performance analysis of turboprop aircraft.

• 여성건강간호학회지
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• 제14권1호
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• pp.44-55
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• 2008

Purpose: This study was done to assess the personal experiences of the coping process during pregnancy for single mothers. Methods: The participants were 17 single mothers who had stayed in a social welfare facility. Data was collected with an in-depth unstructured interview. Data analysis was done by the grounded theory method. Results: One-hundred twelve concepts and 49 sub-categories were confirmed in the analysis. The sub-categories were grouped into 19 categories; escape from a miserable family, wrong meeting, openness of sex, defenseless state of pregnancy, inevitable result of pregnancy, heartbreak by herself, closure, isolation, difficult situation of being alone, stigma, supporting & protecting, helplessness, seeking, empowering, feeling of loss, conflict, facing issues, assuring a fresh start and becoming-mature. "Being driven over the edge of a cliff" was the key phenomenon which the single mothers experienced during the process of pregnancy. Conclusion: The above results will help nurses assessing single pregnancy mothers' needs and developing a nursing intervention program for supporting them. Therefore, nurses will be able to stop them from "being driven over the edge of cliff". A more vigorous nursing intervention is suggested for the research of the vulnerable classes of medical health care including single pregnant mothers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.105-125
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• 2024

Gliomas are the most common malignant brain tumor and cause the most deaths. Manual brain tumor segmentation is expensive, time-consuming, error-prone, and dependent on the radiologist's expertise and experience. Manual brain tumor segmentation outcomes by different radiologists for the same patient may differ. Thus, more robust, and dependable methods are needed. Medical imaging researchers produced numerous semi-automatic and fully automatic brain tumor segmentation algorithms using ML pipelines and accurate (handcrafted feature-based, etc.) or data-driven strategies. Current methods use CNN or handmade features such symmetry analysis, alignment-based features analysis, or textural qualities. CNN approaches provide unsupervised features, while manual features model domain knowledge. Cascaded algorithms may outperform feature-based or data-driven like CNN methods. A revolutionary cascaded strategy is presented that intelligently supplies CNN with past information from handmade feature-based ML algorithms. Each patient receives manual ground truth and four MRI modalities (T1, T1c, T2, and FLAIR). Handcrafted characteristics and deep learning are used to segment brain tumors in a Global Convolutional Neural Network (GCNN). The proposed GCNN architecture with two parallel CNNs, CSPathways CNN (CSPCNN) and MRI Pathways CNN (MRIPCNN), segmented BraTS brain tumors with high accuracy. The proposed model achieved a Dice score of 87% higher than the state of the art. This research could improve brain tumor segmentation, helping clinicians diagnose and treat patients.

• 한국컴퓨터정보학회지
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• 제8권2호
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• pp.67-74
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• 2001

최근에 이용 가능한 데이터의 양이 폭발적으로 증가하고 있다 따라서 이들 데이터로부터 유용한 지식을 발견하는 자동화된 기법이 주목을 받고 있다. 데이터 마이닝이란 지식 발견의 중요한 단계로서, 데이터로부터 유용한 패턴을 발견하는 방법이다. 본 논문에서는 데이터 마이닝 기법을 조사한다 이러한 조사과정을 통하여 실세계에서 보다 효율적으로 적용 가능한 데이터 마이닝 기법을 찾아내고. 이들 기법에 대한 적절한 응용 영역과 앞으로의 연구방향을 제시한다.

• 한국해양공학회지
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• 제34권3호
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• 한국국방경영분석학회지
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• 제31권2호
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• pp.105-115
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• 2005

To ensure interoperability among TADILs, we need inter-operational system of tactical data link that allows sharing of specific, planned information among different TADILs. In this paper, we have proposed the design of a conceptual software architecture of inter-operational system. For developing of a conceptual software architecture, we analyze the actual condition of ADSI used in the US military and identify functions and quality-attributes. Based on these factors, we design the conceptual software architecture for inter-operational system of tactical data link using Attribute-Driven Design(ADD) method. ADD is consist of three phases - choose the module to decompose, refine the module, repeat the steps for every module that needs further decomposition. To evaluate of ADD results, we apply the Software Architecture Analysis Method(SAAM) which is consist of making evaluation scenarios, choosing indirect scenarios, evaluation scenarios' interaction, and creating an overall evaluation. Through the evaluation, we verify the conceptual software architecture of inter-operational system.

• 대한원격탐사학회지
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• 제24권5호
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• pp.463-471
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• 2008

The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using digital terrain model (DTM) and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method used in a previous research. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.

• 전자통신동향분석
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• 제34권3호
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• pp.106-113
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• 2019

Mobile traffic is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with subscribers' service usage patterns, frequency demand and supply, network management, and information communication policy. The purpose of this paper is to understand mobile data usage in Korea and to suggest the optimal steps for establishing the frequency supply and demand system by researching the traffic trends that reflect the characteristics of radio resources in the mobile communications field. To achieve this goal, attempts were made to increase the possibility of policy use by analyzing and forecasting mobile traffic trends, and to improve the accuracy of the research through the verification of the existing prediction results. The paper ends with a discussion of the necessity of a frequency management system based on data science.

• 한국과학교육학회지
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• 제31권1호
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• pp.128-142
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• 2011

이 연구의 목적은 과학적인 문제를 해결하기 위하여 가설을 형성하는 상황에서 최초로 상정된 가설들이 어떤 정교화 과정을 거쳐 더욱 발전하게 되는지 탐색하는 것이었다. 이를 위하여 예비 초등 교사들이 조를 이루어 지구과학의 귀추적 탐구 과제를 해결하는 상황에서 자료를 수집하여 분석하였다. 그 결과, 예비 교사들의 가설 정교화 과정을 크게 '이론에 의해 유도되는 과정'과 '증거에 의해 유도되는 과정'으로 나누어 볼 수 있었다. 이론유도과정은 다시 '내적 정합성'과 '외적 정합성'을 추구하는 경우로 구분되었으며, 증거유도과정은 '직접 증거'에 의한 것과 '간접 증거' 또는 '유사 증거'에 의한 것으로 구분되었다. 또, 각각의 경우에 잘못된 이론이나 그릇된 증거에 의해 가설이 수정되어지는 사례도 발견되었다. 이러한 연구 결과가 과학 교육과 관련 연구에 시사하는 바를 논의하였다.