19,832 research outputs found
Authors' response to discussion of The relevance of Open Source to Hydroinformatics by Hamish Harvey and Dawei Han, 2002 J. Hydroinf. 4(4), 219–234
No full textDataset to support the article "High-resolution 𝜙-OFDR using phase unwrap and nonlinearity suppression"
No full textThis dataset is used for realizing high resolution of phase-sensitive Optical Frequency Domain Reflectometer. It is associated with the research paper:
Guo Z, Yan J, Han G, Yu Y, Greenwood D and Marco J (2023) "High-Resolution φ-OFDR Using Phase Unwrap and Nonlinearity Suppression". Journal of Lightwave Technology, 41 (9), 2885-2891. (https://doi.org/10.1109/JLT.2023.3236775).
The data is presented as an excel file:
High_resolution_OFDR_using_phase_unwrap_and_nonlinearity_suppression.xlsx
This work was funded by High Value Manufacturing Catapult and the Engineer and Physical Sciences Research Council - EPSRC EP/V000624/1. The author Gaoce Han would like to acknowledge the China Scholarship Council for sponsoring.</span
Harnessing rare category trinity for complex data
No full textSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo termsThe student, Dawei Zhou, accepted the attached license on 2021-12-02 at 08:59.The student, Dawei Zhou, submitted this Dissertation for approval on 2021-12-02 at 09:52.This Dissertation was approved for publication on 2021-12-02 at 12:09.DSpace SAF Submission Ingestion Package generated from Vireo submission #17356 on 2022-04-06 at 17:10:41Made available in DSpace on 2022-04-29T21:34:48Z (GMT). No. of bitstreams: 3
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2021-Thesis-Harnessing Rare Category Trinity for Complex Data.zip: 84962577 bytes, checksum: 21087915aaa7cb7a13a9eb95eea710ca (MD5)
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Previous issue date: 2021-12-02"In the era of big data, we are inundated with the sheer volume of data being collected from various domains. In contrast, it is often the rare occurrences that are crucially important to many high-impact domains with diverse data types. For example, in online transaction platforms, the percentage of fraudulent transactions might be small, but the resultant financial loss could be significant; in social networks, a novel topic is often neglected by the majority of users at the initial stage, but it could burst into an emerging trend afterward; in the Sloan Digital Sky Survey, the vast majority of sky images (e.g., known stars, comets, nebulae, etc.) are of no interest to the astronomers, while only 0.001% of the sky images lead to novel scientific discoveries; in the worldwide pandemics (e.g., SARS, MERS, COVID19, etc.), the primary cases might be limited, but the consequences could be catastrophic (e.g., mass mortality and economic recession). Therefore, studying such complex rare categories have profound significance and longstanding impact in many aspects of modern society, from preventing financial fraud to uncovering hot topics and trends, from supporting scientific research to forecasting pandemic and natural disasters.
In this thesis, we propose a generic learning mechanism with trinity modules for complex rare category analysis: (M1) Rare Category Characterization - characterizing the rare patterns with a compact representation; (M2) Rare Category Explanation - interpreting the prediction results and providing relevant clues for the end-users; (M3) Rare Category Generation - producing synthetic rare category examples that resemble the real ones. The key philosophy of our mechanism lies in ""all for one and one for all"" - each module makes unique contributions to the whole mechanism and thus receives support from its companions. In particular, M1 serves as the de-novo step to discover rare category patterns on complex data; M2 provides a proper lens to the end-users to examine the outputs and understand the learning process; and M3 synthesizes real rare category examples for data augmentation to further improve M1 and M2. To enrich the learning mechanism, we develop principled theorems and solutions to characterize, understand, and synthesize rare categories on complex scenarios, ranging from static rare categories to time-evolving rare categories, from attributed data to graph-structured data, from homogeneous data to heterogeneous data, from low-order connectivity patterns to high-order connectivity patterns, etc. It is worthy of mentioning that we have also launched one of the first visual analytic systems for dynamic rare category analysis, which integrates our developed techniques and enables users to investigate complex rare categories in practice.
sj-pdf-1-jbc-10.1177_0883911518809111 – Supplemental material for Antibacterial activity, cell toxicity, and mechanical property of ultra-high molecular weight polyethylene/chlorhexidine acetate–montmorillonite nanocomposite
No full textSupplemental material, sj-pdf-1-jbc-10.1177_0883911518809111 for Antibacterial activity, cell toxicity, and mechanical property of ultra-high molecular weight polyethylene/chlorhexidine acetate–montmorillonite nanocomposite by Jun Zhang, Fuling Feng, Bing Han, Dawei Wang, Lei Fu, Lei He, Yue Zhao, Hong Mo and Jian Shen in Journal of Bioactive and Compatible Polymers</p
Han Suyin (Chinese author) speaking at Dallas Brookes Hall.
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/276390Han Suyin (Chinese author) speaking at Dallas Brookes Hall.200056
Item: [1999.0081.00439] "Han Suyin (Chinese author) speaking at Dallas Brookes Hall.
Rediscovering the Idea of Cultural Heritage and the Relationship with Nature: Four Schools of Essential Thought of the Ancient Han Chinese
No full textAfter a long-standing debate of pluralism in heritage conservation, the global practice has just started to broaden its view from material to people and even to nature, leading to the potential of a more comprehensive understanding and harmony between these spheres. Notwithstanding that the shift from material to people and then to nature seemingly looks like the only path in the modern heritage conservation movement to achieve the foregoing goals, in fact, there exist some regional cultures that originally featured particular views on human–nature harmony. This paper hence highlights the regional difference in heritage with a focus on China of ancient times, which unfolds the particular perspective emphasising the unity of human and nature. With a case study of Huaqing Palace of the Tang Dynasty (618–907 CE), the research is expected to be the first attempt to rediscover that the four schools of thought, Buddhism, Taoism, Confucianism and I Ching, had jointly formed a “wisdom” system of the ancient Han Chinese in shaping the idea of cultural heritage, as well as the idea of heritage conservation, which were inherited by modern Chinese without knowing and recognising it. The paper, therefore, argues that without understanding and acknowledging the significance of the ancient Han Chinese’s particular view on nature and the universe formed by the four schools of thought behind the material, it is not likely to protect and promote comprehensively their heritage value, such that the importance of cultural diversity will be just rhetoric
A Study on the mathematics textbooks in the era of the Great Han Empire
No full text이 글은 갑오경장(1894)과 경술 국치(1910) 사이에 간행된 산학(수학) 교재류의 목록을 확인하고, 각 텍스트의 출판과 관련된 사항, 소장처, 이본 등의 서지적 정보와 함께 이 시기 산학 교재류의 국어사 자료로서의 의의를 언어 사용 상의 측면에 초점을 두어 정리하는 것을 목적으로 한다. 이는 현대 한국어 태동기의 분과 학문의 도입 양상에 대한 연구의 일환인 한편, 학술 용어의 번역과 정착을 중심으로 이 시기의 한국어의 어휘 확장 양상을 확인하는 데에 필요한 기초 자료를 정리하는 작업의 한 부분이다. 본 연구에 앞선 산학(수학) 교재류에 대한 연구로는 산학 교재류의 서지 사항에 대해 기술한 강윤호(1973:187-199), 김봉희(1992:247-253), 한길준(2009), 오채환 외(2010) 등이 있고, 한국 수학사를 기술하면서 교재류를 함께 다룬 것으로 김용운·김용국(1982)와 이상구(2013)이 있다.This paper aims to make a whole list of the mathematics textbooks in the era of the Great Han Empire and summerize bibliographical data and linguistic characteristics in view of Korean history. In chapter 1, the author reviewed former studies which deals with the mathematics textbooks in the era of the Great Han Empire. In chapter 2, the author summerized bibliographical data of 45 volumes of 32 kinds textbooks. In chapter 3, the author described linguistic characteristics of the textbooks, especially focusing on writing systems, the use of Arabic numerals, horizontal writing, and presence of index or glossary
Evaluation of Remotely Sensed Soil Moisture for Landslide Hazard Assessment
No full textSoil moisture is important in the triggering of many types of landslides. However, in situ soil moisture data are rarely available in hazardous zones. The advanced remote sensing technology could provide useful soil moisture information. In this study, an assessment has been carried out between the latest version of the European Space Agency Climate Change Initiative soil moisture product and the landslide events in a northern Italian region in the 14-year period 2002-2015. A clear correlation has been found between the satellite soil moisture and the landslide events, as over four-fifths of events had soil wetness conditions above the 50% regional soil moisture line. Attempts have also been made to explore the soil moisture thresholds for landslide occurrences under different environmental conditions (land cover, soil type, and slope). The results showed slope distribution could provide a rather distinct separation of the soil moisture thresholds, with thresholds becoming smaller for steeper areas, indicating dryer soil condition could trigger landslides at hilly areas than in plain areas. The thresholds validation procedure is then carried out. Forty five rainfall events between 2014 and 2015 are used as test cases. Contingency tables, statistical indicators, and receiver operating characteristic analysis for thresholds under different exceedance probabilities (1%-50%) are explored. The results have shown that the thresholds using 30% exceedance probability provide the best performance with the hitting rate at 0.92 and the false alarm at 0.50. We expect this study can provide useful information for adopting the remotely sensed soil moisture in the landslide early warnings
Application of hydrological model simulations in landslide predictions
No full textThe importance of soil moisture conditions in the initiation of landslides has been widely recognized. This study takes advantage of the distributed hydrological model to derive the soil wetness index. The derived soil wetness index is then used to determine soil wetness thresholds for landslide occurrences. In order to predict landslides based on alert zones, a zone threshold is introduced together with the soil wetness threshold to constitute the integrated threshold. We evaluate the prediction performance of the integrated thresholds with the use of skill scores and the receiver operating characteristic (ROC) curves. This study is carried out in a sub-region of the Emilia-Romagna region, Northern Italy. Results show that the derived soil wetness index could account for the hydrological process that is controlled by meteorological conditions and topographic properties. The proposed integrated threshold shows a better predictive capability than the rainfall threshold, demonstrating the effectiveness of applying the soil wetness index in landslide predictions. The optimal threshold is also determined by compromising the correct predictions and incorrect predictions; it is found that the optimal integrated threshold is more advantageous in reducing false alarms compared with the optimal rainfall threshold. This study highlights the potential of applying hydrological simulations in landslide prediction studies and provides a new way to make use of high-resolution data in zone-based landslide predictions
Also By The Same Author: AKTiveAuthor, a Citation Graph Approach to Name Disambiguation
No full textThe desire for definitive data and the semantic web drive for inference over heterogeneous data sources requires co-reference resolution to be performed on those data. In particular, name disambiguation is required to allow accurate publication lists, citation counts and impact measures to be determined. This paper describes a graph-based approach to author disambiguation on large-scale citation networks. Using self-citation, co-authorship and document source analyses, AKTiveAuthor clusters papers, achieving precision of 0.997 and recall of 0.818 over a test group of eight surname clusters
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