GLORIA

GEOMAR Library Ocean Research Information Access

X

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • MDPI AG  (2)
Material
Publisher
  • MDPI AG  (2)
Person/Organisation
Language
Years
  • 1
    Online Resource
    Online Resource
    Embedding Uncertain Temporal Knowledge Graphs
    MDPI AG ; 2023
    In:  Mathematics Vol. 11, No. 3 ( 2023-02-03), p. 775-
    Details
    In: Mathematics, MDPI AG, Vol. 11, No. 3 ( 2023-02-03), p. 775-
    Abstract: Knowledge graph (KG) embedding for predicting missing relation facts in incomplete knowledge graphs (KGs) has been widely explored. In addition to the benchmark triple structural information such as head entities, tail entities, and the relations between them, there is a large amount of uncertain and temporal information, which is difficult to be exploited in KG embeddings, and there are some embedding models specifically for uncertain KGs and temporal KGs. However, these models either only utilize uncertain information or only temporal information, without integrating both kinds of information into the underlying model that utilizes triple structural information. In this paper, we propose an embedding model for uncertain temporal KGs called the confidence score, time, and ranking information embedded jointly model (CTRIEJ), which aims to preserve the uncertainty, temporal and structural information of relation facts in the embedding space. To further enhance the precision of the CTRIEJ model, we also introduce a self-adversarial negative sampling technique to generate negative samples. We use the embedding vectors obtained from our model to complete the missing relation facts and predict their corresponding confidence scores. Experiments are conducted on an uncertain temporal KG extracted from Wikidata via three tasks, i.e., confidence prediction, link prediction, and relation fact classification. The CTRIEJ model shows effectiveness in capturing uncertain and temporal knowledge by achieving promising results, and it consistently outperforms baselines on the three downstream experimental tasks.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math11030775
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704244-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    Estimating Emissions from Crop Residue Open Burning in Central China from 2012 to 2020 Using Statistical Models Combined with Satellite Observations
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 15 ( 2022-08-01), p. 3682-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 15 ( 2022-08-01), p. 3682-
    Abstract: Crop residue open burning has significant adverse effects on regional air quality, climate change, and human health. Emissions from crop residue open burning estimated by satellites are underestimated in central China due to long-term cloud cover and the limitation of spatial-temporal resolution of satellites. In this study, we used a statistical-based method to investigate the crop residue open burning emissions in central China from 2012 to 2020. The open burning proportion (OBP) of residue, updated annually by the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), and the latest observed emission factors (EFS) were used to improve the accuracy of the estimated emissions. Annual emissions of pollutants were allocated into 0.1° × 0.1° spatial grid cells using fire counts and land cover data. The results showed that the total emissions of black carbon (BC), organic carbon (OC), sulfur dioxide (SO2), nitric oxide (NOX), carbon monoxide (CO), carbon dioxide (CO2), fine particles (PM2.5), coarse particles (PM10), ammonia (NH3), methane (CH4) and non-methane volatile organic compound (NMVOC) were 34.84, 149.72, 41.06, 90.11, 2640.97, 78,094.91, 485.17, 481.05, 35.21, 246.38 and 499.59 Gg, respectively. The largest contributor of crop residue open burning was rice, followed by wheat, rapeseed and corn, with the contribution rates of 35.34–64.07%, 15.78–34.71%, 9.12–25.56%, and 5.69–14.06%, respectively. The pollutants emissions exhibit large annual variation, with the highest emissions in 2013 and a remarkable decrease from 2013 to 2015 under strict control measures. Since 2015, the emissions remained at a low level, which shows that air quality control policies play a role in recent years. The result indicates that using OBP updated by satellite active fire product in a statistical-based method can help to get more accurate and reliable multi-year emissions.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14153682
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...