scholarly journals EXTRACTION METHODS AND EXPERIMENT ON ESSENTIAL FOREST VARIABLES FOR GEOSPATIALLY-ENABLED SDGs MONITORING

2019 ◽  
Vol XLII-4/W20 ◽  
pp. 105-109
Author(s):  
Y. J. Zhao ◽  
H. Wu
Keyword(s):  
Mathematical Expression ◽  
Extraction Methods ◽  
Forest Land ◽  
Land Transfer ◽  
Multiple Data ◽  
Operation Process ◽  
Different Types ◽  
Forest Coverage ◽  
Development Goals ◽  
Data Source

Abstract. Since the United Nations passed the 17 Sustainable Development Goals (SDGs) and 169 sub-goals in 2015, many researchers have tried their best to put them into practise. However, mass data and different understanding of SDGs indicators make this work much more difficult. In this article we reference the concept of essential variables which may have some contribution to established a standard system for SDGs monitoring. Here we take SDG15 as an example. Firstly, we deeply analyse the main contents of SDG15 and select some geospatial-related indicators involved with forest land. From those forest-related and geospatial-enabled indicators we concise 5 essential forest variables (EFV4SDG15) which could be classified into 3 different types: land cover distribution and transformation, aggregative pattern and intensity and spatial-temporal evolution process. Secondly, formalized expression of EFV4SDG15 and extraction of them from multiple data source are necessary, including data processing and mathematical expression of the variables. Finally, we take global region as research target to carry out preliminary experiments. In this part, we only select 2 EFV4SDG15s: the forest coverage rate and forest land transfer matrix to show detailed operation process and then present the results in forms of figure and table. The paper has preliminary attempts to the application of essential variables in SDGs monitoring and provides an example for other fields.

A Review of Different Techniques of Age Estimation from Human Face

2018 ◽  
Vol 4 (10) ◽  
pp. 6
Author(s):  
Khemchandra Patel ◽  
Dr. Kamlesh Namdev
Keyword(s):  
Age Estimation ◽  
Real Life ◽  
Extraction Methods ◽  
Human Face ◽  
Age Changes ◽  
Missing Children ◽  
Different Types ◽  
Age Variation ◽  
Human Faces ◽  
Facial Age

Age changes cause major variations in the appearance of human faces. Due to many lifestyle factors, it is difficult to precisely predict how individuals may look with advancing years or how they looked with "retreating" years. This paper is a review of age variation methods and techniques, which is useful to capture wanted fugitives, finding missing children, updating employee databases, enhance powerful visual effect in film, television, gaming field. Currently there are many different methods available for age variation. Each has their own advantages and purpose. Because of its real life applications, researchers have shown great interest in automatic facial age estimation. In this paper, different age variation methods with their prospects are reviewed. This paper highlights latest methodologies and feature extraction methods used by researchers to estimate age. Different types of classifiers used in this domain have also been discussed.

scholarly journals A robust machine learning approach to SDG data segmentation

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kassim S. Mwitondi ◽  
Isaac Munyakazi ◽  
Barnabas N. Gatsheni
Keyword(s):  
Temporal Variations ◽  
Data Repository ◽  
The Sustainable Development ◽  
Complex Interactions ◽  
Data Segmentation ◽  
Technological Advances ◽  
Machine Learning Approach ◽  
Development Goals ◽  
Data Source ◽  
Spatio Temporal

Abstract In the light of the recent technological advances in computing and data explosion, the complex interactions of the Sustainable Development Goals (SDG) present both a challenge and an opportunity to researchers and decision makers across fields and sectors. The deep and wide socio-economic, cultural and technological variations across the globe entail a unified understanding of the SDG project. The complexity of SDGs interactions and the dynamics through their indicators align naturally to technical and application specifics that require interdisciplinary solutions. We present a consilient approach to expounding triggers of SDG indicators. Illustrated through data segmentation, it is designed to unify our understanding of the complex overlap of the SDGs by utilising data from different sources. The paper treats each SDG as a Big Data source node, with the potential to contribute towards a unified understanding of applications across the SDG spectrum. Data for five SDGs was extracted from the United Nations SDG indicators data repository and used to model spatio-temporal variations in search of robust and consilient scientific solutions. Based on a number of pre-determined assumptions on socio-economic and geo-political variations, the data is subjected to sequential analyses, exploring distributional behaviour, component extraction and clustering. All three methods exhibit pronounced variations across samples, with initial distributional and data segmentation patterns isolating South Africa from the remaining five countries. Data randomness is dealt with via a specially developed algorithm for sampling, measuring and assessing, based on repeated samples of different sizes. Results exhibit consistent variations across samples, based on socio-economic, cultural and geo-political variations entailing a unified understanding, across disciplines and sectors. The findings highlight novel paths towards attaining informative patterns for a unified understanding of the triggers of SDG indicators and open new paths to interdisciplinary research.

Cognitive Disequilibrium and Service-Learning in Physical Education Teacher Education: Perceptions of Pre-Service Teachers in a Study Abroad Experience

2017 ◽  
Vol 36 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Stefan Ward ◽  
Heidi Henschel Pellett ◽  
Mark I. Perez
Keyword(s):  
Preservice Teachers ◽  
Service Learning ◽  
Study Abroad ◽  
Physical Education Teacher Education ◽  
Multiple Data ◽  
Teachers Experiences ◽  
Data Source ◽  
Axial Coding ◽  
Member Checks ◽  
Cognitive Disequilibrium

Purpose:The purpose of this study was to explore preservice teachers’ experiences of cognitive disequilibrium (CD) theory during a service-learning project in a study abroad experience.Method:A case study with 8 participants was used. Data sources consisted of: Formal interviews, videos of planning, videos of teaching, videos of reflection sessions, and informal interviews. Data were analyzed utilizing open and axial coding (Corbin & Strauss, 2008). Trustworthiness strategies included: prolonged engagement, multiple data source triangulation, and member checks.Results:Results indicated four themes: “We made it our own thing”, “Summer camp for teachers”, “Struggle and disequilibrium”, and “By the end it was a transformation”.Discussion/Conclusions:CD was ultimately positive for these students. The positive resolution of CD catalyzed a transformative effect on their perceptions of their teaching. This was supported by positive peer interaction.

Research on Feature Extraction Method Based on Rub-Impact Acoustic Emission Signals of Mechanical Seal End Faces

2010 ◽  
Vol 36 ◽  
pp. 68-74
Author(s):  
Chuan Jun Liao ◽  
Shuang Fu Suo ◽  
Wei Feng Huang
Keyword(s):  
Acoustic Emission ◽  
Feature Extraction ◽  
Extraction Methods ◽  
Mechanical Seal ◽  
Mechanical Seals ◽  
Feature Extraction Method ◽  
Different Types ◽  
Ae Signal ◽  
Feature Information ◽  
Ae Signals

Acoustic emission (AE) techniques are put forward to monitor rub-impacts between rotating rings and stationary rings of mechanical seals by this paper. By analyzing feature extraction methods of the typical rub-impact AE signal, the method combining of wavelet scalogram and power spectrum is found useful, and can used to attribute the feature information implicated in rub-impact AE signals of mechanical seal end faces. Both simulations and experimental research prove that the method is effective, and are used successfully to identify the typical features of different types of rub-impacts of mechanical seal end faces.

scholarly journals Application of Extraction and Determination Based on Deep Eutectic Solvents in Different Types of Environmental Samples

Water ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 46
Author(s):  
Yonghua Wang ◽  
Na Li ◽  
Shengnan Jiang ◽  
Xi Chen
Keyword(s):  
Extraction Efficiency ◽  
Deep Eutectic Solvents ◽  
Extraction Methods ◽  
Water Sources ◽  
Environmental Research ◽  
Environmental Matrices ◽  
Controllable Synthesis ◽  
Surrounding Environment ◽  
Target Analytes ◽  
Different Types

Water sources are an indispensable resource for human survival. Monitoring the pollution status of the surrounding environment is necessary to protect water sources. Research on the environmental matrix of deep eutectic solvents (DESs) has expanded rapidly because of their high extraction efficiency for various target analytes, controllable synthesis, and versatile structure. Following the synthesis of hydrophobic deep eutectic solvents (HDESs), their application in aqueous matrices broadened greatly. The present review conducted a survey on the pollutant extraction methods based DESs in environmental matrices from two aspects, application methods and matrix types; discussed the potential risk of DESs to the environment and future development trends; and provided some references for researchers to choose DES-based extraction methods for environmental research.

scholarly journals The Integration of Photodiode and Camera for Visible Light Positioning by Using Fixed-Lag Ensemble Kalman Smoother

2019 ◽  
Vol 11 (11) ◽  
pp. 1387
Author(s):  
Yuan Zhuang ◽  
Qin Wang ◽  
You Li ◽  
Zhouzheng Gao ◽  
Bingpeng Zhou ◽  
...  
Keyword(s):  
Visible Light ◽  
Real Time ◽  
Estimation Error ◽  
Navigation Systems ◽  
Stochastic Sampling ◽  
Kalman Smoother ◽  
Multiple Data ◽  
Data Source ◽  
3D Positioning ◽  
Single Data

Visible Light Positioning (VLP) has become one of the most popular positioning and navigation systems in this decade. Filter-based VLP systems can provide real-time solutions but have limited accuracy. On the contrary, fixed-interval smoothers can help VLP achieve higher accuracy but require post-processing. In this article, a trade-off solution, Fixed-Lag Ensemble Kalman Smoother (FLEnKS), is proposed for VLP to achieve a semi-real-time and accurate positioning solution. The forward part of the FLEnKS is based on the Ensemble Kalman Filter (EnKF), which uses stochastic sampling with ensemble members and enables a better reflection of the features of nonlinear systems. The backward filter in the FLEnKS compensates for the estimation error from the forward filter using the linearization based on error states and further reduces the estimation error. Furthermore, multiple data from both photodiode (PD) and camera are fused in the proposed FLEnKS for VLP, which further improves the accuracy of conventional VLP with a single data source. Preliminary field test results show that the proposed FLEnKS provides a semi-real-time positioning solution with the average 3D positioning accuracy of 15.63 cm in dynamic tests.

A Preliminary Estimate of The Apennine Brown Bear Population Size Based on Hair-Snag Sampling and Multiple Data Source Mark–Recapture Huggins Models

Ursus ◽  
2008 ◽  
Vol 19 (2) ◽  
pp. 105-121 ◽  
Author(s):  
Vincenzo Gervasi ◽  
Paolo Ciucci ◽  
John Boulanger ◽  
Mario Posillico ◽  
Cinzia Sulli ◽  
...  
Keyword(s):  
Population Size ◽  
Brown Bear ◽  
Preliminary Estimate ◽  
Mark Recapture ◽  
Multiple Data Source ◽  
Multiple Data ◽  
Data Source ◽  
Apennine Brown Bear

scholarly journals Evaluation of Biochar Nitrate Extraction Methods

2019 ◽  
Vol 9 (17) ◽  
pp. 3514 ◽  
Author(s):  
Jenna Walsh ◽  
Joseph Sanford ◽  
Rebecca Larson
Keyword(s):  
Extraction Method ◽  
Extraction Efficiency ◽  
Agricultural Soils ◽  
Extraction Methods ◽  
Multiple Methods ◽  
Soil Extraction ◽  
Future Studies ◽  
Different Types ◽  
Increasing Temperature ◽  
Biochar Amendment

Biochar amendment to soil is a method used to mitigate losses of nitrogen leaching through agricultural soils. Multiple methods for extraction of nitrogen have been used, and recent studies have indicated that traditional soil extraction methods underestimate biochar nitrate. This study evaluated the nitrate extraction efficiency of a KCl extraction method under different temperature (20 and 50 °C) and duration (24 and 96 h) conditions. Increasing the duration of extraction from 24 to 96 h did not have a significant impact on extraction efficiency. However, increasing temperature resulted in nitrate extraction efficiencies above 90%. Rinsing the biochar once with deionized (DI) water following filtration after extraction increased the extraction efficiency significantly, but any subsequent rinses were not significant. This study recommends extracting nitrate from biochar using 2 M KCl at 50 °C for a period of 24 h with one additional rinse to increase nitrate recovery above 90%. However, future studies should evaluate this procedure for different types of biochar produced from alternative biomasses and at varying temperatures.

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