• Title/Summary/Keyword: Heterogeneity Learning

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A Study on the Application of UDL to Christian Unification Education in the Era of Multiculturalism (다문화시대 기독교통일교육에 대한 보편적학습설계(UDL) 적용 제고)

  • Kim, Seongkyeol;Ahn, Milee
    • Journal of Christian Education in Korea
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    • v.63
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    • pp.407-433
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    • 2020
  • South Korea is currently facing multiculturalism, appropriately demanding broadened view and access to the study of Unification, especially in terms of who should be the subject. In congruence, recent Unification Education studies are proposing values stressed in Multiculturalism to function as the core ground, upon which other traits and contents are to follow. Similarly, Christian Education field is also reflecting the recent trend, welcoming 'everyone' to participate in preparing reunification of Korean Peninsula. However, most studies consist of suggesting and introducing directions for new approaches, not so much of dealing with systems or guidelines for practical practices. Information provided in fragments can rather cause confusion in understanding the concept, and lack of specific guidelines can soon lead to poor performances. In this study, Universal Design for Learning (UDL) is introduced as a methodology to be examined, whether it could effectively embody and systemize the newly emerged Multicultural Christian Unification Education. Therefore, the purpose of this study is 1) to generalize the concept of Christian unification education introduced in the multicultural era and 2) examine whether UDL is suitable for uniformizing and spreading the Multicultural approach of Christian Unification Education. Specifically, this study highly focused on examining whether UDL is a suitable methodology to achieve the goal of Multicultural Christian unification education, while uniformizing the diversities within multicultural Christian Unification Education. Through a thorough research, it was proved that the purpose and characteristics of multicultural Christian unification education are similar to those of UDL in that both focus on accepting heterogeneity as something "different" rather than something "wrong." Also, it was found that the application of the theory and guidelines of UDL can effectively unify while respecting the diverse methodologies used in Multicultural Christian Education.

A Knowledge-based Wrapper Learning Agent for Semi-Structured Information Sources (준구조화된 정보소스에 대한 지식기반의 Wrapper 학습 에이전트)

  • Seo, Hee-Kyoung;Yang, Jae-Young;Choi, Joong-Min
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.42-52
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    • 2002
  • Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.

Estimation of Spatial Distribution Using the Gaussian Mixture Model with Multivariate Geoscience Data (다변량 지구과학 데이터와 가우시안 혼합 모델을 이용한 공간 분포 추정)

  • Kim, Ho-Rim;Yu, Soonyoung;Yun, Seong-Taek;Kim, Kyoung-Ho;Lee, Goon-Taek;Lee, Jeong-Ho;Heo, Chul-Ho;Ryu, Dong-Woo
    • Economic and Environmental Geology
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    • v.55 no.4
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    • pp.353-366
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    • 2022
  • Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

Automatic Fracture Detection in CT Scan Images of Rocks Using Modified Faster R-CNN Deep-Learning Algorithm with Rotated Bounding Box (회전 경계박스 기능의 변형 FASTER R-CNN 딥러닝 알고리즘을 이용한 암석 CT 영상 내 자동 균열 탐지)

  • Pham, Chuyen;Zhuang, Li;Yeom, Sun;Shin, Hyu-Soung
    • Tunnel and Underground Space
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    • v.31 no.5
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    • pp.374-384
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    • 2021
  • In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

MORPHEUS: A More Scalable Comparison-Shopping Agent (MORPHEUS: 확장성이 있는 비교 쇼핑 에이전트)

  • Yang, Jae-Yeong;Kim, Tae-Hyeong;Choe, Jung-Min
    • Journal of KIISE:Software and Applications
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    • v.28 no.2
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    • pp.179-191
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    • 2001
  • Comparison shopping is a merchant brokering process that finds the best price for the desired product from several Web-based online stores. To get a scalable comparison shopper, we need an agent that automatically constructs a simple information extraction procedure, called a wrapper, for each semi-structured store. Automatic construction of wrappers for HTML-based Web stores is difficult because HTML only defines how information is to be displayed, not what it means, and different stores employ different ways of manipulating customer queries and different presentation formats for displaying product descriptions. Wrapper induction has been suggested as a promising strategy for overcoming this heterogeneity. However, previous scalable comparison-shoppers such as ShopBot rely on a strong bias in the product descriptions, and as a result, many stores that do not confirm to this bias were unable to be recognized. This paper proposes a more scalable comparison-shopping agent named MORPHEUS. MORPHEUS presents a simple but robust inductive learning algorithm that antomatically constructs wrappers. The main idea of the proposed algorithm is to recognize the position and the structure of a product description unit by finding the most frequent pattern from the sequence of logical line information in output HTML pages. MORPHEUS successfully constructs correct wtappers for most stores by weakening a bias assumed in previous systems. It also tolerates some noises that might be present in production descriptions such as missing attributes. MORPHEUS generates the wrappers rapidly by excluding the pre-processing phase of removing redundant fragments in a page such as a header, a tailer, and advertisements. Eventually, MORPHEUS provides a framework from which a customized comparison-shopping agent can be organized for a user by facilitating the dynamic addition of new stores.

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Full-Endoscopic versus Minimally Invasive Lumbar Interbody Fusion for Lumbar Degenerative Diseases : A Systematic Review and Meta-Analysis

  • Son, Seong;Yoo, Byung Rhae;Lee, Sang Gu;Kim, Woo Kyung;Jung, Jong Myung
    • Journal of Korean Neurosurgical Society
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    • v.65 no.4
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    • pp.539-548
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    • 2022
  • Objective : Although full-endoscopic lumbar interbody fusion (Endo-LIF) has been tried as the latest alternative technique to minimally invasive transforaminal lumbar interobody fusion (MIS-TLIF) since mid-2010, the evidence is still lacking. We compared the clinical outcome and safety of Endo-LIF to MIS-TLIF for lumbar degenerative disease. Methods : We systematically searched electronic databases, including PubMed, EMBASE, and Cochrane Library to find literature comparing Endo-LIF to MIS-TLIF. The results retrieved were last updated on December 11, 2020. The perioperative outcome included the operation time, blood loss, complication, and hospital stay. The clinical outcomes included Visual analog scale (VAS) of low back pain and leg pain and Oswestry disability index (ODI), and the radiological outcome included pseudoarthosis rate with 12-month minimum follow-up. Results : Four retrospective observational studies and one prospective observational study comprising 423 patients (183 Endo-LIF and 241 MIS-TLIF) were included, and the pooled data analysis revealed low heterogeneity between studies in our review. Baseline characteristics including age and sex were not different between the two groups. Operation time was significantly longer in Endo-LIF (mean difference [MD], 23.220 minutes; 95% confidence interval [CI], 10.669-35.771; p=0.001). However, Endo-LIF resulted in less perioperative blood loss (MD, -144.710 mL; 95% CI, 247.941-41.478; p=0.023). Although VAS back pain at final (MD, -0.120; p=0.586), leg pain within 2 weeks (MD, 0.005; p=0.293), VAS leg pain at final (MD, 0.099; p=0.099), ODI at final (MD, 0.141; p=0.093) were not different, VAS back pain within 2 weeks was more favorable in the Endo-LIF (MD, -1.538; 95% CI, -2.044 to -1.032; p<0.001). On the other hand, no statistically significant group difference in complication rate (relative risk [RR], 0.709; p=0.774), hospital stay (MD, -2.399; p=0.151), and pseudoarthrosis rate (RR, 1.284; p=0.736) were found. Conclusion : Relative to MIS-TLIF, immediate outcomes were favorable in Endo-LIF in terms of blood loss and immediate VAS back pain, although complication rate, mid-term clinical outcomes, and fusion rate were not different. However, the challenges for Endo-LIF include longer operation time which means a difficult learning curve and limited surgical indication which means patient selection bias. Larger-scale, well-designed study with long-term follow-up and randomized controlled trials are needed to confirm and update the results of this systematic review.

A Comparison between the Reference Evapotranspiration Products for Croplands in Korea: Case Study of 2016-2019 (우리나라 농지의 기준증발산 격자자료 비교평가: 2016-2019년의 사례연구)

  • Kim, Seoyeon;Jeong, Yemin;Cho, Subin;Youn, Youjeong;Kim, Nari;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1465-1483
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    • 2020
  • Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.